literature review on forest management

• Review Paper
• Open access
• Published: 14 January 2015

Climate change impacts and adaptation in forest management: a review

• Rodney J. Keenan 1  

Annals of Forest Science volume  72 ,  pages 145–167 ( 2015 ) Cite this article

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Key message

Adaptation of forest management to climate change requires an understanding of the effects of climate on forests, industries and communities; prediction of how these effects might change over time; and incorporation of this knowledge into management decisions. This requires multiple forms of knowledge and new approaches to forest management decisions. Partnerships that integrate researchers from multiple disciplines with forest managers and local actors can build a shared understanding of future challenges and facilitate improved decision making in the face of climate change.

Climate change presents significant potential risks to forests and challenges for forest managers. Adaptation to climate change involves monitoring and anticipating change and undertaking actions to avoid the negative consequences and to take advantage of potential benefits of those changes.

This paper aimed to review recent research on climate change impacts and management options for adaptation to climate change and to identify key themes for researchers and for forest managers.

The study is based on a review of literature on climate change impacts on forests and adaptation options for forest management identified in the Web of Science database, focusing on papers and reports published between 1945 and 2013.

One thousand one hundred seventy-two papers were identified in the search, with the vast majority of papers published from 1986 to 2013. Seventy-six percent of papers involved assessment of climate change impacts or the sensitivity or vulnerability of forests to climate change and 11 % (130) considered adaptation. Important themes from the analysis included (i) predicting species and ecosystem responses to future climate, (ii) adaptation actions in forest management, (iii) new approaches and tools for decision making under uncertainty and stronger partnerships between researchers and practitioners and (iv) policy arrangements for adaptation in forest management.

Conclusions

Research to support adaptation to climate change is still heavily focused on assessing impacts and vulnerability. However, more refined impact assessments are not necessarily leading to better management decisions. Multi-disciplinary research approaches are emerging that integrate traditional forest ecosystem sciences with social, economic and behavioural sciences to improve decision making. Implementing adaptation options is best achieved by building a shared understanding of future challenges among different institutions, agencies, forest owners and stakeholders. Research-policy-practice partnerships that recognise local management needs and indigenous knowledge and integrate these with climate and ecosystem science can facilitate improved decision making.

1 Introduction

Anthropogenic climate change presents potential risks to forests and future challenges for forest managers. Responding to climate change, through both mitigation and adaptation, may represent a paradigm shift for forest managers and researchers (Schoene and Bernier 2012 ). Climate change is resulting in increasing air temperature and changing precipitation regimes, including changes to snowfall and to the timing, amount and inter-annual variability of rainfall (IPCC 2013 ). Forests are widespread, long-lived ecosystems that are both intensively and extensively managed. They are potentially sensitive to these longer term climatic changes, as are the societies and economies that depend on them (Bernier and Schöne 2009 ). Climate change increases the potential consequences of many existing challenges associated with environmental, social or economic change.

Whilst forest ecosystems are resilient and many species and ecosystems have adapted historically to changing conditions, future changes are potentially of such magnitudes or will occur at rates that are beyond the natural adaptive capacity of forest species or ecosystems, leading to local extinctions and the loss of important functions and services, including reduced forest carbon stocks and sequestration capacity (Seppälä et al. 2009 ).

Recent global warming has already caused many changes in forests (Lucier et al. 2009 ). Aspects of climate change may be positive for some tree species in some locations. Tree growth is observed to be increasing in some locations under longer growing seasons, warmer temperatures and increased levels of CO 2 . However, many projected future changes in climate and their indirect effects are likely to have negative consequences for forests. Observed shifts in vegetation distribution (Kelly and Goulden 2008 ; Lenoir et al. 2010 ) or increased tree mortality due to drought and heat in forests worldwide (Allen et al. 2010 ) may not be due to human-induced climate change but demonstrate the potential impacts of rapid climate change. These impacts may be aggravated by other human-induced environmental changes such as increases in low elevation ozone concentrations, nitrogenous pollutant deposition, the introduction of exotic insect pests and pathogens, habitat fragmentation and increased disturbances such as fire (Bernier and Schöne 2009 ). Other effects of climate change may also be important for forests. Sea level rise is already impacting on tidal freshwater forests (Doyle et al. 2010 ) and tidal saltwater forests (mangroves) are expanding landward in sub-tropical coastal reaches taking over freshwater marsh and forest zones (Di Nitto et al. 2014 ).

With projected future change, species ranges will expand or contract, the geographic location of ecological zones will shift, forest ecosystem productivity will change and ecosystems could reorganise following disturbances into ecological systems with no current analogue (Campbell et al. 2009 ; Fischlin et al. 2009 ). Forests types differ in their sensitivity to climatic change. Bernier and Schöne ( 2009 ) considered boreal, mountain, Mediterranean, mangrove and tropical moist forests most vulnerable to climate change. However, there has been recent debate about the vulnerability of tropical moist forests (Corlett 2011 ; Huntingford et al. 2013 ; Feeley et al. 2012 ), and temperate forests in areas subject to drier climates may be more at risk (Choat et al. 2012 ).

Adapting to these changing and uncertain future conditions can be considered from a number of perspectives (McEvoy et al. 2013 ). Policy and management might be directed at avoiding or reducing the impact of climate-related events, reducing vulnerability to future climatic conditions, managing a broader suite of climate ‘risks’ or increasing resilience and capacity in forest ecological and production systems to recover from climate ‘shocks’.

Adapting forest management to climate change involves monitoring and anticipating change and undertaking actions to avoid the negative consequences or take advantage of potential benefits of those changes (Levina and Tirpak 2006 ). Adopting the principles and practices of sustainable forest management (SFM) can provide a sound basis for addressing the challenges of climate change. However, Innes et al. ( 2009 ) pointed out that our failure to implement the multi-faceted components of sustainable forest management in many forests around the world is likely to limit capacity to adapt to climate change. Forest managers will need to plan at multiple spatial and temporal scales and adopt more adaptive and collaborative management approaches to meet future challenges.

Whilst forest managers are accustomed to thinking in long time scales—considering the long-term implications of their decisions and factoring in uncertainty and unknowns into management—many are now responding to much shorter term social or economic imperatives. Local forestry practices are often based on an implicit assumption that local climate conditions will remain constant (Guariguata et al. 2008 ). Other social and economic changes will also continue to drive changes in forest management (Ince et al. 2011 ). For example, a growing global population, rapid economic development and increased wealth are driving demand for food and fibre crops and forest conversion to agriculture in many developing countries (Gibbs et al. 2010 ). Climate change mitigation objectives are increasing demands for wood-based bioenergy and the use of wood in construction and industrial systems. Increasing urbanisation is changing the nature of social demands on forests, and decreasing rural populations is limiting the availability of labour and capacity for intensive forest management interventions.

Ecosystem-based adaptation is being promoted as having the potential to incorporate sustainable management, conservation and restoration of ecosystems into adaptation to climate change (IUCN 2008 ). This can be achieved more effectively by integrating ecosystem management and adaptation into national development policies through education and outreach to raise societal awareness about the value of ecosystem services (Vignola et al. 2009 ).

Kimmins ( 2002 ) invoked the term ‘future shock’, first coined by Toffler ( 1970 ) to describe the situation where societal expectations from forests were changing faster than the institutional capacity for change in forest management organisations. The pace of climate change is likely to intensify this phenomenon. Empirically based management based on traditional ‘evidence-based’ approaches therefore will potentially not develop quickly enough for development of effective future management options. How can managers consider rapid change and incorporate the prospect of very different, but uncertain, future climatic conditions into their management decisions? What types of tools are needed to improve decision making capacity?

This study aimed to review the literature on studies to support forest management in a changing climate. It builds on the major review of Seppala ( 2009 ), in particular Chapter 6 of that report by Innes et al. ( 2009 ).

The study involved a systematic assessment of the literature based on the database Web of Science (Thomson-Reuters 2014 ), an online scientific citation indexing service that provides the capacity to search multiple databases, allowing in-depth exploration of the literature within an academic or scientific discipline.

The following search terms were used in the titles of publications:

(forest* or tree* or (terrestrial and ecosystem)) and climat* and (adapt* or impact* or effect* or respons*) and

(forest* or tree*) and climat* and vulnerabilit* or sensitivit*)

The search was restricted to publications between 1945 and 2013. References related solely to climate change mitigation were excluded, as were references where the word ‘climate’ simply referred to a study in a particular climatic zone. This left a database of 1172 publications for analyses (a spreadsheet of the papers revealed in the search can be obtained from the author). References were classified into various types of studies and different regions, again based on the titles. Not all papers identified in the search are referenced. The selection of themes for discussion and papers for citation was a subjective one, based on scanning abstracts and results from relevant individual papers. The focus was important themes from key papers and literature from the last 5 years. The review includes additional papers not revealed in the search relating to these themes including selected papers from the literature in the year 2014.

Of the published papers relating to climate impacts or adaptation selected for analysis, the vast majority of papers were published from 1986 onwards. The earliest paper dated from 1949 (Gentilli 1949 ) analysing the effects of trees on climate, water and soil. Most studies prior to 1986 (and even some published later) focused on the effects of trees on local or wider regional climate (Lal and Cummings 1979 ; Otterman et al. 1984 ; Bonan et al. 1992 ), the implications of climate variability (Hansenbristow et al. 1988 ; Ettl and Peterson 1995 ; Chen et al. 1999 ), studies of tree and forest responses across climatic gradients (Grubb and Whitmore 1966 ; Bongers et al. 1999 ; Davidar et al. 2007 ) or responses to historical climate (Macdonald et al. 1993 ; Huntley 1990 ; Graumlich 1993 ).

One thousand twenty-six papers specifically addressed future climate change (rather than historical climate or gradient analysis). Of these, 88 % studied impacts, effects, vulnerability or responses to climate change in tree species, forests, forest ecosystems or the forest sector (Fig.  1 ). The first study analysing the potential impacts of future climate change on terrestrial ecosystems was published in 1985 (Emanuel et al. 1985 ) with other highly cited papers soon after (Pastor and Post 1988 ; Cannell et al. 1989 ).

Publication numbers by publication year for publications relating to climate change and forests from a search of the Web of Science database to the end of 2013 (1025 in total, 896 publications studied climate change impacts, responses or vulnerability, 129 studied adaptation)

Twelve percent of papers (129) considered adaptation options, including 10 papers on adaptation in the forest sector. The first papers to focus on adaptation in the context of climate change were in 1996 with a number of papers published in that year (Kienast et al. 1996 ; Kobak et al. 1996 ; Dixon et al. 1996 ). Publications were then relatively few each year until the late 2000s with numbers increasing to 11 in 2009, 22 in 2010 and 27 in 2011. Publications on adaptation dropped to 14 papers in 2013. The ratio of adaptation-related papers has increased more recently, with 19 % of total publications on adaptation in the last 5 years. Most papers considering adaptation since the early 2000s have related to the integration of adaptation and forest management (e.g. Lindner 2000 ; Spittlehouse 2005 ; Kellomaki et al. 2008 ; Guariguata 2009 ; Bolte et al. 2009 ; Keskitalo 2011 ; Keenan 2012 ; Temperli et al. 2012 ).

Analyses of the implications of climate change for the forest sector have focused heavily on North America: Canada (Ohlson et al. 2005 ; Van Damme 2008 ; Rayner et al. 2013 ; Johnston et al. 2012 ) and the USA (Joyce et al. 1995 ; Blate et al. 2009 ; Kerhoulas et al. 2013 ); and Europe (Karjalainen et al. 2003 ; von Detten and Faber 2013 ). There has been a stronger consideration in recent years of social, institutional and policy issues (Ogden and Innes 2007b ; Kalame et al. 2011 ; Nkem et al. 2010 ; Spies et al. 2010 ; Somorin et al. 2012 ) and the assessment of adaptive capacity in forest management organisations and in society more generally (Keskitalo 2008 ; Lindner et al. 2010 ; Bele et al. 2013a ).

Regionally, there have been relatively few published journal articles on impacts or adaptation in forests in the Southern Hemisphere (Hughes et al. 1996 ; Williams 2000 ; Pinkard et al. 2010 ; Gonzalez et al. 2011 ; Mok et al. 2012 ; Breed et al. 2013 ), although there have been more studies in the grey literature for Australian forests (Battaglia et al. 2009 ; Cockfield et al. 2011 ; Medlyn et al. 2011 ; Stephens et al. 2012 ). There have been some valuable analyses for the tropics (Guariguata et al. 2008 , 2012 ; Somorin et al. 2012 ; Feeley et al. 2012 ).

Analysis of the publications identified the following key themes: (i) predicting species and ecosystem responses to future climate, (ii) adaptation actions in forest management, (iii) new approaches and tools for decision making under uncertainty and stronger partnerships between researchers and practitioners and (iv) policy arrangements for adaptation in forest management. These are discussed in more detail below.

3.1 Predicting species and ecosystem responses to future climate

Forest managers have long used climatic information in a range of ways in planning and decision making. Climate information has been used extensively to define and map vegetation types and ecological zones and for modelling habitat distributions of vertebrates and invertebrates (Daubenmire 1978 ; Pojar et al. 1987 ; Thackway and Cresswell 1992 ), for species and provenance selection (Booth et al. 1988 ; Booth 1990 ) and seed zone identification (Johnson et al. 2004 ), for forest fire weather risk assessment and fire behaviour modelling (Carvalho et al. 2008 ), for modelling forest productivity (Battaglia et al. 2004 ) and analysing the dynamics of a range of ecological processes (Anderson 1991 ; Breymeyer and Melillo 1991 ). Predicting species responses to future climate change presents a different set of challenges, involving consideration of predictions of future climate that are often outside the historical range of variability of many species. These challenges are discussed in the next section.

3.1.1 Species responses to climate

Aitken et al. ( 2008 ) argued that there were three possible fates for forest tree populations in rapidly changing climatic conditions: persistence through spatial migration to track their ecological niches, persistence through adaptation to new conditions in current locations or the extirpation of the species. Predicting the potential fate of populations in these conditions requires the integration of knowledge across biological scales from individual genes to ecosystems, across spatial scales (for example, seed and pollen dispersal distances or breadth of species ranges) and across temporal scales from the phenology of annual developmental cycle traits to glacial and interglacial cycles.

Whilst there has been widespread use of climatic information to predict future distributions in species distribution models (SDMs, Pearson and Dawson 2003 ; Attorre et al. 2008 ; Wang et al. 2012 ; Ruiz-Labourdette et al. 2013 ), understanding of the range of climatic and non-climatic factors that will determine the future range of a particular species remains limited. Many now feel that SDMs are of limited value in adaptation decision making or species conservation strategies. Some of these limitations are summarised in Table  1 .

For example, models indicate significant shifts in patterns of tree species distribution over the next century but usually without any intrinsic consideration of the biological capacity of populations to move, internal population dynamics, the extent and role of local adaptation or the effects of climate and land use (Aitken et al. 2008 ; Thuiller et al. 2008 ). In a recent study, Dobrowski et al. ( 2013 ) found that the predicted speed of movement of species to match the predicted rate of climate change appears to be well beyond the historical rates of migration. Whilst modelled outputs suggest that migration rates of 1000 m per year or higher will be necessary to track changing habitat conditions (Malcolm et al. 2002 ), actual migration rates in response to past change are generally considered to have been less than 100 m per year. This was reinforced by model predictions that incorporate species dispersal characteristics for five tree species in the eastern USA indicated very low probabilities of dispersal beyond 10–20 km from current species boundaries by 2100 (Iverson et al. 2004 ). Corlett and Westcott ( 2013 ) also argued that plant movements are not realistically represented in models used to predict future vegetation or carbon-cycle feedbacks and that fragmentation of natural systems is likely to slow migration rates.

However, these estimates do not account for the role of humans in influencing tree species distributions, which they have done for thousands of years (Clark 2007 ), and managed translocation may be an option for conserving many tree species, but there are significant unresolved technical and social questions about implementing translocation at a larger scale (Corlett and Westcott 2013 ).

Most early SDMs relied primarily on temperature envelopes to model future distribution, but factors such as precipitation and soil moisture are potentially more limiting and more important in determining distribution patterns (Dobrowski et al. 2013 ). Aitken et al. ( 2008 ) found that the degree to which variation in precipitation explains phenotypic variation among populations is greater in general for populations from continental than from maritime climates and greater for lower latitude than higher latitude populations. However, precipitation alone is often not a good predictor of variation and there is often a strong interaction with temperature (Andalo et al. 2005 ). Heat to moisture index or aridity is probably more important in determining future distribution or productivity than precipitation alone (Aitken et al. 2008 ; Harper et al. 2009 ; Wang et al. 2012 ). Soil properties (depth, texture and organic matter content) have a major influence on plant-available water, but few SDMs incorporate these.

Future precipitation is proving more difficult to model than temperature, due to the complex effects of topography, and there are more widely varying estimates between global circulation models (GCMs) of future change in precipitation (IPCC 2013 ). As such, there is more uncertainty around the extent to which moisture stress will change with warming and the extent to which natural selection pressures will change as a result. Even without changes in precipitation, increased temperatures will increase the length of growing season and potential evapotranspiration (PET) resulting in more water use over the year and greater risk plant water shortage and drought death.

Changes in the intervals of extreme events (extreme heat, cold, precipitation, humidity, wind) may also matter more than changes in the mean. Current forecasting approaches that produce future climate averages may make it difficult to detect non-linear ecosystem dynamics, or threshold effects, that could trigger abrupt ecosystem change (Campbell et al. 2009 ). Zimmermann et al. ( 2009 ) found that predictions of spatial patterns of tree species in Switzerland were improved by incorporating measures of extremes in addition to means in SDMs.

The risks of future climate will also depend on the management goal. If the aim is simply to conserve genetic diversity, risks of extinction or reduction in genetic diversity may be overstated by SDMs because much of the genetic variation within tree species is found within rather than among their populations, and the extinction of a relatively large proportion of a population is generally likely to result in relatively little overall loss of genetic diversity (Hamrick 2004 ). Local habitat heterogeneity (elevation, slope aspect, moisture, etc.) can preserve adaptive genetic variation that, when recombined and exposed to selection in newly colonised habitats, can provide for local adaptation. The longevity of individual trees can also retard population extinction and allow individuals and populations to survive until habitat recovery or because animal and wind pollination can provide levels of pollen flow that are sufficient to counteract the effects of genetic drift in fragmented populations. Consequently, widespread species with large populations, high fecundity and higher levels of phenotypic plasticity are likely to persist and adapt and have an overall greater tolerance to changing climates than predicted by SDMs (Alberto et al. 2013 ).

Tree species distributions have always been dynamic, responding to changing environmental conditions, and populations are likely to be sub-optimal for their current environments (Namkoong 2001 ; Wu and Ying 2004 ). These lag effects are important in predicting species responses to climate change. In a modelling study of Scots pine and silver birch, Kuparinen et al. ( 2010 ) predicted that after 100 years of climate change, the genotypic growth period length of both species will lag more than 50 % behind the climatically determined optimum. This lag is reduced by increased mortality of established trees, whereas earlier maturation and higher dispersal ability had comparatively minor effects. Thuiller et al. ( 2008 ) suggest that mechanisms for incorporating these ‘trailing edge’ effects into SDMs are a major area of research potential.

Trees are also capable of long-distance gene flow, which can have both adaptive evolution benefits and disadvantages. Kremer et al. ( 2012 ) found that there may be greater positive effects of gene flow for adaptation but that the balance of positive to negative consequences of gene flow differs for leading edge, core and rear sections of forest distributions.

Epigenetics—heritable changes that are not caused by changes in genetic sequences but by differences in the way DNA methylation controls the degree of gene expression—is another complicating factor in determining evolutionary response to climate change (Brautigam et al. 2013 ). For example, a recent study in Norway spruce ( Picea abies ) showed that the temperature during embryo development can dramatically affect cold hardiness and bud phenology in the offspring. In some cases, the offspring’s phenotype varied by the equivalent of 6° of latitude from what was expected given the geographic origin of the parents. It remains uncertain whether these traits are persistent, both within an individual’s lifetime and in its offspring and subsequent generations (Aitken et al. 2008 ). It is suggested that analysis of the epigenetic processes in an ecological context, or ‘ecological epigenetics’, is set to transform our understanding of the way in which organisms function in the landscape. Increased understanding of these processes can inform efforts to manage and breed tree species to help them cope with environmental stresses (Brautigam et al. 2013 ). Others argue that whilst investigating this evolutionary capacity to adapt is important, understanding responses of species to their changing biotic community is imperative (Anderson et al. 2012 ) and ‘landscape genomics’ may offer a better approach for informing management of tree populations under climate change (Sork et al. 2013 ).

These recent results indicate the importance of accounting for evolutionary processes in forecasts of the future dynamics and productivity of forests. Species experiencing high mortality rates or populations that are subject to regular disturbances such as storms or fires might actually be the quickest to adapt to a warming climate.

Species life history characteristics are also not usually well represented in most climate-based distribution models. Important factors include age to sexual maturity, fecundity, seed dispersal, competition or chilling or dormancy requirements (Nitschke and Innes 2008b ).

Competitive relationships within and between species are likely to be altered by climate change. Most models also assume open site growth conditions, rather than those within a forest, where the growth environment will be quite different. However, increased disturbance associated with climate change may create stand reinitiation conditions more often than has occurred in the past, altering competitive interactions.

Process-based models of species range shifts and ecosystem change may capture more of the life history variables and competition effects that will be important in determining responses to climate change (Kimmins 2008 ; Nitschke and Innes 2008a , b ). These can provide the basis for a more robust assessment framework that integrates biological characteristics (e.g. shade tolerance and seedling establishment) and disturbance characteristics (e.g. insect pests, drought and fire topkill). Matthews et al. ( 2011 ) integrated these factors into a decision support system that communicates uncertainty inherent in GCM outputs, emissions scenarios and species responses. This demonstrated a greater diversity among species to adapt to climate change and provides a more practical assessment of future species projections.

In summary, whilst SDMs and other climate-based modelling approaches can provide a guide to potential species responses, the extent to which future climate conditions will result in major range shifts or extinction of species is unclear and the value of this approach in adaptation and decision making is limited. The evidence from genetic studies seems to suggest that many species are reasonably robust to potential future climate change. Those with a wide geographic range, large populations and high fecundity may suffer local population extinction but are likely to persist and adapt whilst suffering adaptational lag for a few generations. For example, Booth ( 2013 ) considered that many eucalyptus species, some of which are widely planted around the world, had a high adaptive capacity even though their natural ranges are quite small.

However, large contractions or shifts in distribution could have significant consequences for different forest values and species with small populations, fragmented ranges, low fecundity or suffering declines due to introduced insects or diseases may have a higher sensitivity and are at greater risk in a changing climate (Aitken et al. 2008 ).

3.1.2 Ecosystem responses to climate

Projecting the fate of forest ecosystems under a changing climate is more challenging than for species. It has been well understood for some time that species will respond individualistically to climate change, rather than moving in concert, and that this is likely to result in ‘novel’ ecosystems, or groups of species, that are not represented in current classifications (Davis 1986 ). Forecasts need to consider the importance of these new species interactions and the confounding effects of future human activities.

Climate change affects a wide range of ecosystem functions and processes (Table  2 ). These include direct effects of temperature and precipitation on physiological and reproductive processes such as photosynthesis, water use, flowering, fruiting and regeneration, growth and mortality and litter decomposition. Changes in these processes will have effects on species attributes such as wood density or foliar nutrient status. Indirect effects will be exhibited through changing fire and other climate-driven disturbances. These will ultimately have impacts on stand composition, habitat structure, timber supply capacity, soil erosion and water yield.

Most early studies of forest ecosystem responses to climate change were built around ecosystem process models at various scales (Graham et al. 1990 ; Running and Nemani 1991 ; Rastetter et al. 1991 ). A number of recent studies have investigated the effects of past and current climate change on forest processes, often with surprising effects (Groffman et al. 2012 ).

Observed forest growth has increased recently in a number of regions, for example over the last 100 years in Europe (Pretzsch et al. 2014 ; Kint et al. 2012 ), and for more recent observations in Amazon forests (Phillips et al. 2008 ). In a major review, Boisvenue and Running ( 2006 ) found that at finer spatial scales, a trend is difficult to decipher, but globally, based on both satellite and ground-based data, climatic changes seemed to have a generally positive impact on forest productivity when water was not limiting. However, there can be a strong difference between species, complicating ecosystem level assessments (Michelot et al. 2012 ), and there are areas with little observed change (Schwartz et al. 2013 ). Generally, there are significant challenges in detecting the response of forests to climate change. For example, in the tropics, the lack of historical context, long-term growth records and access to data are real barriers (Clark 2007 ) and temperate regions also have challenges, even with well-designed, long-term experiments (Leites et al. 2012 ).

Projections of net primary productivity (NPP) under climate change indicate that there is likely to be a high level of regional variation (Zhao et al. 2013 ). Using a process model and climate scenario projections, Peters et al. ( 2013 ) predicted that average regional productivity in forests in the Great Lakes region of North America could increase from 67 to 142 %, runoff could potentially increase from 2 to 22 % and net N mineralization from 10 to 12 %. Increased productivity was almost entirely driven by potential CO 2 fertilization effects, rather than by increased temperature or changing precipitation. Productivity in these forests could shift from temperature limited to water limited by the end of the century. Reyer et al. ( 2014 ) also found strong regional differences in future NPP in European forests, with potential growth increases in the north but reduced growth in southern Europe, where forests are likely to be more water limited in the future. Again, assumptions about the impact of increasing CO 2 were a significant factor in this study.

In a different type of study using analysis of over 2400 long-term measurement plots, Bowman et al. ( 2014 ) found that there was a peaked response to temperature in temperate and sub-tropical eucalypt forests, with maximum growth occurring at a mean annual temperature of 11 °C and maximum temperature of the warmest month of 25–27 °C. Lower temperatures directly constrain growth, whilst high temperatures primarily reduced growth by reducing water availability but they also appeared to exert a direct negative effect. Overall, the productivity of Australia’s temperate eucalypt forests could decline substantially as the climate warms, given that 87 % of these forests currently experience a mean annual temperature above the ‘optimal’ temperature.

Incorporating the effects of rising CO 2 in models of future tree growth continues to be a major challenge. The sensitivity of projected productivity to assumptions regarding increased CO 2 was high in modelling studies of climate change impacts in commercial timber plantations in the Southern Hemisphere (Kirschbaum et al. 2012 ; Battaglia et al. 2009 ), and a recent analysis indicated a general convergence of different model predictions for future tree species distribution in Europe, with most of the difference between models due to the way in which this effect is incorporated (Cheaib et al. 2012 ). Increased CO 2 has been shown to increase the water-use efficiency of trees, but this is unlikely to entirely offset the effects of increased water stress on tree growth in drying climates (Leuzinger et al. 2011 ; Booth 2013 ). In general, despite studies extending over decades and improved understanding of biochemical processes (Franks et al. 2013 ), the impacts of increased CO 2 on tree and stand growth are still unresolved (Kallarackal and Roby 2012 ).

Integrating process model outputs with spatially explicit landscape models can improve understanding and projection of responses and landscape planning and this could provide for simulations of changes in ecological processes (e.g. tree growth, succession, disturbance cycles, dispersal) with other human-induced changes to landscapes (Campbell et al. 2009 ).

Investigation of current species responses to changing climate conditions may also guide improved prediction of patterns of future change in ecosystem distribution. For example, Allen et al. ( 2010 ) suggest that spatially explicit documentation of environmental conditions in areas of forest die-off is necessary to link mortality to causal climate drivers, including precipitation, temperature and vapour pressure deficit. Better prediction of climate responses will also require improved knowledge of belowground processes and soil moisture conditions. Assessments of future productivity will depend on accurate measurements of rates (net ecosystem exchange and NPP), changes in ecosystem level storage (net ecosystem production) and quantification of disturbances effects to determine net biome production (Boisvenue and Running 2006 ).

Hydrological conditions, runoff and stream flow are of critical importance for humans and aquatic organisms, and many studies have focused on the implications of climate change for these ecosystem processes. However, most of these have been undertaken at small catchment scale (Mahat and Anderson 2013 ; Neukum and Azzam 2012 ; Zhou et al. 2011 ) with few basin-scale assessments (van Dijk and Keenan 2007 ). However, the effects of climate and forest cover change on hydrology are complicated. Loss of tree cover may increase stream flow but can also increase evaporation and water loss (Guardiola-Claramonte et al. 2011 ). The extent of increasing wildfire will also be a major factor determining hydrological responses to climate change (Versini et al. 2013 ; Feikema et al. 2013 ).

Changing forest composition will also affect the habitat of vertebrate and invertebrate species. The implications of climate change for biodiversity conservation have been subject to extensive analysis (Garcia et al. 2014 ; Vihervaara et al. 2013 ; Schaich and Milad 2013 ; Clark et al. 2011 ; Heller and Zavaleta 2009 ; Miles et al. 2004 ). An integrated analytical approach, considering both impacts on species and habitat is important. For example, in a study of climate change impacts on bird habitat in the north-eastern USA, the combination of changes in tree distribution and habitat for birds resulted in significant impacts for 60 % of the species. However, the strong association of birds with certain vegetation tempers their response to climate change because localised areas of suitable habitat may persist even after the redistribution of tree species (Matthews et al. 2011 ).

Understanding thresholds in changing climate conditions that are likely to result in a switch to a different ecosystem state, and the mechanisms that underlie ecosystem responses, will be critical for forest managers (Campbell et al. 2009 ). Identifying these thresholds of change is challenging. Detailed process-based ecosystem research that identifies and studies critical species interactions and feedback loops, coupled with scenario modelling of future conditions, could provide valuable insights (Kimmins et al. 1999 , 2008 ; Walker and Meyers 2004 ). Also, rather than pushing systems across thresholds into alternative states, climate change may create a stepwise progression to unknown transitional states that track changing climate conditions, requiring a more graduated approach in management decisions (Lin and Petersen 2013 ).

Ultimately, management decisions may not be driven by whether we can determine future thresholds of change, but by observing the stressors that determine physiological limits of species distributions. These thresholds will depend on species physiology and local site conditions, with recent research demonstrating already observed ecosystem responses to climate change, including die-back of some species (Allen et al. 2010 ; Rigling et al. 2013 ).

3.1.3 Fire, pests, invasive species and disturbance risks

Many of the impacts of a changing future climate are likely to be felt through changing disturbance regimes, in particular fire. Forest fire weather risk and fire behaviour prediction have been two areas where there has been strong historical interaction between climate science and forest management and where we may see major tipping points driving change in ecosystem composition (Adams 2013 ). Fire weather is fundamentally under the control of large-scale climate conditions with antecedent moisture anomalies and large-scale atmospheric circulation patterns, further exacerbated by configuration of local winds, driving fire weather (Brotak and Reifsnyder 1977 ; Westerling et al. 2002 , 2006 ). It is therefore important to improve understanding of both short- and long-term atmospheric conditions in determining meteorological fire risk (Amraoui et al. 2013 ).

Increased fuel loads and changes to forest structure due to long periods of fire exclusion and suppression are increasing fire intensity and limiting capacity to control fires under severe conditions (Williams 2004 , 2013 ). Increasing urbanisation is increasing the interface between urban populations and forests in high fire risk regions, resulting in greater impacts of wildfire on human populations, infrastructure and assets (Williams 2004 ). Deforestation and burning of debris and other types of human activities are also introducing fire in areas where it was historically relatively rare (Tacconi et al. 2007 ).

In a recent study, Chuvieco et al. ( 2014 ) assessed ecosystem vulnerability to fire using an index based on ecological richness and fragility, provision of ecosystem services and value of houses in the wildland–urban interface. The most vulnerable areas were found to be the rainforests of the Amazon Basin, Central Africa and Southeast Asia; the temperate forest of Europe, South America and north-east America; and the ecological corridors of Central America and Southeast Asia.

In general, fire management policies in many parts of the world will need to cope with longer and more severe fire seasons, increasing fire frequency, and larger areas exposed to fire risk. This will especially be the case in the Mediterranean region of Europe (Kolström et al. 2011 ) and other fire-prone parts of the world such as South Eastern Australia (Hennessy et al. 2005 ). This will require improved approaches to fire weather modelling and behaviour prediction that integrate a more sophisticated understanding of the climate system with local knowledge of topography, vegetation and wind patterns. It will also require the development of fire management capacity where it had previously not been necessary. Increased fire weather severity could push current suppression capacity beyond a tipping point, resulting in a substantial increase in large fires (de Groot et al. 2013 ; Liu et al. 2010 ) and increased investment in resources and management efforts for disaster prevention and recovery.

Biotic factors may be more important than direct climate effects on tree populations in a changing climate. For example, insects and diseases have much shorter generation length and are able to adapt to new climatic conditions more rapidly than trees. However, if insects move more rapidly to a new environment whilst tree species lag, some parts of the tree population may be impacted less in the future (Regniere 2009 ).

The interaction of pests, diseases and fire will also be important. For example, this interaction will potentially determine the vulnerability of western white pine ( Pinus monticola ) ecosystems in Montana in the USA. Loehman et al. ( 2011 ) found that warmer temperatures will favour western white pine over existing climax and shade tolerant species, mainly because warmer conditions will lead to increased frequency and extent of wildfires that facilitates regeneration of this species.

3.2 Adaptation actions in forest management

The large majority of published studies relating to forests and climate change have been on vulnerability and impacts. These have increased understanding of the various relationships between forest ecosystems and climate and improved capacity to predict and assess ecosystem responses. However, managers need greater guidance in anticipating and responding to potential impacts of climate change and methods to determine the efficiency and efficacy of different management responses because they are generally not responding sufficiently to potential climate risks.

3.2.1 Adaptation actions at different management levels

A number of recent reviews have described adaptation actions and their potential application in different forest ecosystems being managed for different types of goods or services (Bernier and Schöne 2009 ; Innes et al. 2009 ; Lindner et al. 2010 ; Kolström et al. 2011 ), and adaptation guides and manuals have been developed (Peterson et al. 2011 ; Stephens et al. 2012 ) for different types of forest and jurisdictions. Adaptation actions can be primarily aimed at reducing vulnerability to increasing threats or shocks from natural disasters or extreme events, or increasing resilience and capacity to respond to progressive change or climate extremes. Adaptation actions can be reactive to changing conditions or planned interventions that anticipate future change. They may involve incremental changes to existing management systems or longer term transformational changes (Stafford Smith et al. 2011 ). Adaptation actions can also be applied at the stand level or at ownership, estate or national scales (Keskitalo 2011 ).

Recent research at the stand level in forests in the SE USA showed that forest thinning, often recommended in systems that are likely to experience increased temperature and decreased precipitation as a result of climate change, will need to be more aggressive than traditionally practised to stimulate growth of large residual trees, improve drought resistance and provide greater resilience to future climate-related stress (Kerhoulas et al. 2013 ).

An analysis of three multi-aged stand-level options in Nova Scotia, Canada, Steenberg et al. ( 2011 ) found that leaving sexually immature trees to build stand complexity had the most benefit for timber supply but was least effective in promoting resistance to climate change at the prescribed harvest intensity. Varying the species composition of harvested trees proved the most effective treatment for maximising forest age and old-growth area and for promoting stands composed of climatically suited target species. The combination of all three treatments resulted in an adequate representation of target species and old forest without overly diminishing the timber supply and was considered most effective in minimising the trade-offs between management values and objectives.

An estate level analysis of Austrian Federal Forests indicated that management to promote mixed stands of species that are likely to be well adapted to emerging environmental conditions, silvicultural techniques fostering complexity and increased management intensity might successfully reduce vulnerability, with the timing of adaptation measures important to sustain supply of forest goods and services (Seidl et al. 2011 ).

Whilst researchers are analysing different management options, the extent to which they are being implemented in practice is generally limited. For example, in four regions in Germany, strategies for adapting forest management to climate change are in the early stages of development or simply supplement existing strategies relating to general risk reduction or to introduce more ‘nature-orientated’ forest management (Milad et al. 2013 ). Guariguata et al. ( 2012 ) found that forest managers across the tropics perceived that natural and planted forests are at risk from climate change but were ambivalent about the value of investing in adaptation measures, with climate-related threats to forests ranked below others such as clearing for commercial agriculture and unplanned logging.

Community-based management approaches are often argued to be the most successful approach for adaptation. An analysis of 38 community forestry organisations in British Columbia found that 45 % were researching adaptation and 32 % were integrating adaptation techniques into their work (Furness and Nelson 2012 ). Whilst these community forest managers appreciated support and advice from government for adaptation, balancing this advice with autonomy for communities to make their own decisions was considered challenging.

In a study of communities impacted by drought in the forest zone of Cameroon, Bele et al. ( 2013b ) identified adaptive strategies such as community-created firebreaks to protect their forests and farms from forest fires, the culture of maize and other vegetables in dried swamps, diversifying income activities or changing food regimes. However, these coping strategies were considered to be incommensurate with the rate and magnitude of change being experienced and therefore no longer seen as useful. Some adaptive actions, whilst effective, were resource inefficient and potentially translate pressure from one sector to another or generated other secondary effects that made them undesirable.

3.2.2 Integrating adaptation and mitigation

In considering responses to climate change, forest managers will generally be looking for solutions that address both mitigation objectives and adaptation. To maintain or increase forest carbon stocks over the long term, the two are obviously inextricably linked (Innes et al. 2009 ). Whilst there are potentially strong synergies, Locatelli et al. ( 2011 ) identified potential trade-offs between actions to address mitigation and the provision of local ecosystem services and those for adaptation. They argued that mitigation projects can facilitate or hinder the adaptation of local people to climate change, whereas adaptation projects can affect ecosystems and their potential to sequester carbon.

Broadly, there has been little integration to date of mitigation and adaptation objectives in climate policy. For example, there is little connection between policies supporting the reducing emissions from deforestation and forest degradation plus (REDD+) initiatives and adaptation. Integrating adaptation into REDD+ can advance climate change mitigation goals and objectives for sustainable forest management (Long 2013 ). Kant and Wu ( 2012 ) considered that adaptation actions in tropical forests (protection against fire and disease, ensuring adequate regeneration and protecting against coastal impacts and desertification) will improve future forest resilience and have significant climate change mitigation value.

3.2.3 Sector-level adaptation

Analyses of climate change impacts and vulnerability at the sector level have been undertaken for some time (Lindner et al. 2002 ; Johnston and Williamson 2007 ; Joyce 2007 ). However, it has recently been argued (Wellstead et al. 2014 ) that these assessments, which focus on macro system-level variables and relationships, fail to account for the multi-level or polycentric nature of governance and the possibility that policy processes may result in the non-performance of critical tasks required for adaptation.

Joyce et al. ( 2009 ) considered that a toolbox of management options for the US National Forests would include the following: practices focused on reducing future climate change effects by building resistance and resilience into current ecosystems and on managing for change by enabling plants, animals and ecosystems to adapt to climate change. Sample et al. ( 2014 ) demonstrated the utility of this approach in a coniferous forest management unit in northwestern USA. It provided an effective means for guiding management decisions and an empirical basis for setting budgetary and management priorities. In general, more widespread implementation of already known practices that reduce the impact of existing stressors represents an important ‘no regrets’ strategy.

Johnston and Hesseln ( 2012 ) found that barriers to implementing adaptation across forest sector managers in Canada included inflexible tenure arrangements and regulatory environments which do not support innovation. Echoing calls for wider implementation of SFM as a key adaptation strategy (Innes et al. 2009 ), they argued that forest certification systems, participating in the Canadian model forest programme, and adopting criteria and indicators of SFM can support sectoral level adaptation.

Decentralised management approaches are considered to be a more appropriate governance arrangement for forest management, but Rayner et al. ( 2013 ) argued that a decentralised forest policy sector in Canada has resulted in limitations where policy, such as adaptation, requires a coherent national response. Climate change adaptation has led to an expansion of departmental mandates that is not being addressed by better coordination of the available policy capacity. Relevant federal agencies are not well represented in information networks, and forest policy workers report lower levels of internal and external networking than workers in related policy subsectors.

Economic diversification can be a valuable strategy to improve resilience to climate-related shocks. This can take a range of forms: developing new industries or different types of forest-based industries based on different goods or services. For the timber sector, the value of diversification as a risk management strategy for communities is open to question. Ince et al. ( 2011 ) pointed out that the forest sector operates in an international market and is susceptible to changes in the structure of this market. In the US forest sector, globalization has accelerated structural change, favouring larger and more capital-intensive enterprises and altering historical patterns of resource use. They suggest that future markets for timber will be driven by developments in these larger scale enterprises and may not lead to expansion of opportunities for smaller scale forest enterprises because development of niche markets or customised products is likely to be pursued aggressively by larger globally oriented enterprises to develop branding, product identity and product value. How to best diversify for adaptation therefore remains an open question.

Consequently, whilst policies that support economic diversification will be important, this may involve diversification well beyond traditional sectors. For example, in areas where there is a high probability that forests will be lost in favour of other ecosystems, such as grasslands, managers should recognise early on that their efforts and resources may best be focused outside forests (Innes et al. 2009 ). These adjustments will involve taking into account the perceptions of climate risk by various stakeholders, including individuals, communities, governments, private institutions and organisations (Adger et al. 2007 ). Vulnerability assessments and adaptation measures also need to be developed in a framework that takes into account the vulnerabilities and actions in other sectors that are linked to the forest sector, such as food, energy, health and water (Sonwa et al. 2012 ).

3.3 New approaches to decision making

Climate change presents new challenges for forest managers. Change is likely to happen faster than traditional, empirical approaches can provide evidence to support changes in management. Uncertainties in a range of aspects of future climate may also not be reduced through investment in research. Given that management for activities such as timber production can no longer be based solely on empirically derived growth and yield trajectories and management plans must incorporate uncertainty and the increased probability of extreme events, what types of tools are available to support these approaches? This section presents key points from the literature on decision making under uncertainty, adaptive management and resilience as a guide to future decision making in forest management.

3.3.1 Decision making under uncertainty

The future conditions for forest managers are subject to a high degree of uncertainty, and the future prospects for reducing these large uncertainties are limited. There is uncertainty regarding the trajectory of future increases in atmospheric greenhouse gases, what kind of effects these might have on the climate system and the effects of climatic changes on ecological and social systems and their capacity to adapt (see Fig.  2 ) (Wilby and Dessai 2010 ).

The cascade of uncertainty (Wilby and Dessai 2010 )

Consequently, many forest managers consider that the future situation is too uncertain to support long-term and potentially costly decisions that may be difficult to reverse. Dessai and Hulme ( 2004 ) argued that uncertainty per se should not be a reason for inaction. However, the critical issue for managers is deciding the types of actions to take and the timing and conditions under which they should be taken (Ogden and Innes 2007a ). A more reactive ‘wait and see’ approach (or ‘purposeful procrastination’) might be justified if uncertainty or costs are high relative to the expected impacts and risks, or if it is cheaper to implement interventions by waiting until after a significant disturbance (e.g. replanting an area with more fire- or drought-resistant tree species after a wildfire or drought-induced insect outbreak).

Effective adaptation requires setting clear objectives. Managers and policy makers need to decide whether they are trying to facilitate ecosystem adaptation through changing species composition or forest structure or trying to engineer resistance to change through proactive management strategies (Joyce et al. 2008 ). Establishing objectives often depends on the integration of the preferences of different stakeholders (Prato 2008 ), but changing social preferences presents another source of potential uncertainty.

Risk assessment and management provide a foundation for decision making in considering climate change in natural resource management. This approach provides both a qualitative and quantitative framework for evaluating climate change effects and adaptation options. Incorporating risk management approaches into forest management plans can provide a basis for managers to continue to provide forest conditions that meet a range of important values (Day and Perez 2013 ).

However, risk approaches generally requiring assigning probabilities to future events. In a comprehensive review, Yousefpour et al. ( 2011 ) identified a growing body of research literature on decision making under uncertainty, much of which has focused on price uncertainty and variation in timber production but is extending to multiple forest management objectives and other types of risk. They argue that we are actually in a stochastic transition from one known stable (but variable) climate state to a new but largely unknown and likely more rapidly changing set of future conditions.

Decision makers themselves may also not be the rational actors assumed by these models, with their decisions taken according to quite different assumptions, preferences and beliefs (Ananda and Herath 2009 ; Couture and Reynaud 2008 ). Therefore, the communication approach will be important in determining whether the information is acted on. In a recent study, Yousefpour et al. ( 2014 ) considered that the speed with which decision makers will form firm beliefs about future climate depends on the divergence among climate trajectories, the speed of change and short-term climate variability. Using a Bayesian modelling approach, they found that if a large change in climate occurs, the value of investing in knowledge and taking an adaptive approach would be positive and higher than a non-adaptive approach. In communicating about uncertainty, it may be better to focus discussion on the varying time in the future when things will happen, rather than on whether they will happen at all (Lindner et al. 2014 ).

Increased investment in climate science and projections or species distribution modelling may not necessarily decrease uncertainty in climate projections or impacts. Climate models are best viewed as heuristic tools rather than as accurate forecasts of the future (Innes et al. 2009 ). Trajectories of change in many other drivers of forest management (social, political or economic) are also highly uncertain (Keskitalo 2008 ) and the effects of these on the projected performance of management can be the same order of magnitude, requiring an integrated social-ecological perspective to adaptation (Seidl and Lexer 2013 ).

In a more ‘decision-centred’ approach, plausible scenarios of the potential range of future conditions are required. These can be derived from climate models but do not need to be accurate and precise ‘predictions’ of future climate states (Wilby and Dessai 2010 ). To support this type of approach, research needs to focus on improved understanding of tree and ecosystem responses and identifying those aspects of climate to which different forest types are most sensitive.

Devising strategies that are able to meet management objectives under a range of future scenarios is likely to be the most robust approach, recognising that these strategies are unlikely to be optimal under all future conditions. In some cases, the effect of different scenarios on forest growth may not be that great and differences in the present value of different management options are relatively small. For example, Eriksson et al. ( 2011 ) found that there was limited benefit in attempting to optimise management plans in accordance with future temperature scenarios.

Integration of climate change science and adaptation in forest management planning is considered important for building resilience in forest social and ecological systems (Keskitalo 2011 ; D’Amato et al. 2011 ; Chmura et al. 2011 ; Parks and Bernier 2010 ; Lindner et al. 2014 ). Forest restoration is becoming a more prominent aspect of forest management in many parts of the world and restoration approaches will also need to integrate understanding of future climate change to be successful (Stanturf et al. 2014 ).

3.3.2 Adaptive management, resilience and decisions

Adaptive management provides a mechanism to move forward when faced with future uncertainty (Innes et al. 2009 ). It can be viewed as a systematic process for continually improving management policies and practices by monitoring and then learning from the outcomes of operational programmes as a basis for incorporating adaptation actions into forest management. Whilst many management initiatives purport to implement these principles, they often lack essential characteristics of the approach (Innes et al. 2009 ).

However, effective adaptation to changing climate cannot simply involve adaptive management as it is currently understood. The pace of climate change is not likely to allow for the use of management as a tool to learn about the system by implementing methodologies to test hypotheses concerning known uncertainties (Holling 1978 ). Future climatic conditions may result in system states and dynamics that have never previously existed (Stainforth et al. 2007 ), so observation of past experience may be a poor guide for future action. Management will need to be more ‘forward-looking’, considering the range of possible future conditions and planning actions that consider that full range.

How does this translate into the practical guidance forest managers are seeking on how to adapt their current practices and, if necessary, their goals (Blate et al. 2009 )? Managers will need to consider trade-offs between different objectives under different conditions. For example, Seidl et al. ( 2011 ) showed that, to keep climate vulnerability in an Austrian forest low, Norway spruce will have to be replaced almost entirely by better adapted species. However, indicator weights that favoured timber production over C storage or biodiversity exerted a strong influence on the results. Wider social implications of imposing such drastic changes in forest landscapes will also deserve stronger consideration in decision making.

Ecosystem management will need to be reframed to accommodate the risks of a changing climate. Adaptive strategies, even without specific information on the future climate conditions of a target ecosystem, would enhance social and ecological resilience to address the uncertainties due to changing climate (Mori et al. 2013 ). These are likely to be more subject to change over the short to medium term, in response to more rapidly changing conditions.

Analysis of ecosystem resilience can provide a framework for these assessments. Resilience can be defined as ‘the capacity of ecosystems to absorb disturbance and reorganise so as to retain essentially the same function, structure and feedbacks – to have the same identity’ (Walker and Salt 2012 ). It is a function of the capacity of an ecosystem to resist change, the extent and pace of change and the ability of an ecosystem to reorganise following disturbance. The concept of resilience holds promise for informing future forest management, but Rist and Moen ( 2013 ) argue that its contributions are, so far, largely conceptual and offer more in terms of being a problem-framing approach than analytical or practical tools. There may also be trade-offs involved with focusing on resilience through retention of current species composition or using a more adaptation-oriented management approach after disturbances (Buma and Wessman 2013 ). Complexity theory and concepts can provide an appropriate framework for managing resilience (Messier et al. 2013 ).

Management decisions will ultimately depend on the costs and benefits of different options, but there are few examples of decision making frameworks that compare the costs of future impacts with the costs of different actions and the efficacy of those actions in reducing impacts. Ogden and Innes ( 2009 ) used a structured decision making process to identify and assess 24 adaptation options that managers considered important to achieve their regional goals and objectives of sustainable forest management in light of climate change. In the analysis of options for biodiversity conservation, Wintle et al. ( 2011 ) found that the amount of funding available for adaptation was a critical factor in deciding options aimed at minimising species extinctions in the mega-diverse fynbos biome of South Africa. When the available budget is small, fire management was the best strategy. If the budget is increased to an intermediate level, the marginal returns from more fire management were limited and the best strategy was added habitat protection. Above another budget threshold, increased investment should go into more fire management. By integrating ecological predictions in an economic decision framework, they found that making the choice of how much to invest is as important as determining what actions to take.

3.3.3 Adaptation as a social learning process

Whilst adaptation has been defined as ‘adjustment in natural or human systems in response to actual or expected climatic stimuli or their effects’ (Levina and Tirpak 2006 ), adaptation is essentially about meeting future human needs (Spittlehouse and Stewart 2003 ; Hahn and Knoke 2010 ). Consequently, it is inherently a social process. Forest landscapes are social-ecological systems that involve both nature and society (Innes et al. 2009 ), and resolving trade-offs between different management objectives to meet the different needs in society is an important element of sustainable forest management. As Kolström et al. ( 2011 ) pointed out, some proposed adaptation measures may change the balance between current objectives and stakeholder interests, and it will be important to consider the relative balance of different measures at the stand, management unit and landscape scales.

Those investigating adaptive management also recognise that it goes beyond the focus on scientific methods, statistical designs or analytical rigour favoured by its early proponents and that there is now an expectation of much greater stakeholder involvement, with the concept being renamed by some as adaptive, collaborative management (Innes et al. 2009 ). SFM and adaptation are as much about those who inhabit, work in or utilise forests as it is about managing the forest ecosystems themselves (White et al. 2010 ; Pramova et al. 2012 ; Fischer et al. 2013 ).

The choice of adaptation options will thus likely be relatively complex, even in cases where information and policy have been developed, and communication measures for forest management have been well formulated. Making such choices may require considerable knowledge, competence and commitment for implementation at the local level (Keskitalo 2011 ). Effective adaptation will require much greater cooperation between stakeholders, more flexibility for management actions and commitment of time to develop the social license for action in the absence of conclusive evidence or understanding. This will require venues for sharing perspectives on the nature of the problem (Fig.  3 ).

Adaptation as a social learning process. There is a need to provide situations to share different viewpoints on the nature of the problem as a basis for developing shared solutions (image source: John Rowley, http://ch301.cm.utexas.edu/learn/ )

3.3.4 Local and indigenous knowledge

The promotion of community-based forest management may increase local adaptive capacity by putting decisions in the hands of those people who first feel the effects of climate change (Gyampoh et al. 2009 ). In this context, local knowledge systems based on long-term observation and experience are likely to be of increasing importance in decision making. Adaptation strategies can benefit from combining scientific and indigenous knowledge, especially in developing countries (Gyampoh et al. 2009 ), with the translation of local forest knowledge into the language of formal forest science being considered an important step towards adaptation (Roberts et al. 2009 ). However, conservation and natural resource managers in government agencies have often discounted traditional local management systems (Scott 2005 ), although Spathelf et al. ( 2014 ) provided a useful approach for capturing local expert knowledge. Linking this type of knowledge with broader scientific understanding of ecosystem functioning and the global climate system will be a major challenge, requiring consideration of both technical and cultural issues (Caverley 2013 ), including intellectual property concerns of indigenous people (Lynch et al. 2010 ).

3.4 Policy arrangements for adaptation

Increasingly, many are arguing that effectively responding to climate change will require polycentric and multi-level governance arrangements (Peel et al. 2012 ). However, Nilsson et al. ( 2012 ) found that institutionalising of knowledge and knowledge exchange regarding climate change adaptation in Sweden was weak and that improved mechanisms are required for feedback from the local to the national level. Recent studies have described stronger relationships between scientific research and forest management to assess trade-offs and synergies, for participatory decision making and for shared learning (Blate et al. 2009 ; Littell et al. 2012 ; Klenk et al. 2011 ).

Many papers emphasised the need for greater flexibility in the policies, cultures and structures of forest management organisations (Brown 2009 ; von Detten and Faber 2013 ; Rayner et al. 2013 ). Because no single community or agency can prepare on their own for future impacts, inter-sectoral policy coordination will be required to ensure that policy developments in related policy sectors are not contradictory or counterproductive. Greater integration of information, knowledge and experience and collaborative projects involving scientists, practitioners and policy makers from multiple policy communities could increase focus on resilience, identify regions of large-scale vulnerability and provide a more rigorous framework for the analysis of vulnerability and adaptation actions (Thomalla et al. 2006 ).

There is also likely to be a greater need for cross-border implementation of different forest management options, requiring greater coordination between nation states and sub-national governments (Keenan 2012 ). Policy is the product of both ‘top-down’ and ‘bottom-up’ processes and these might sometimes be in conflict. Simply having ‘good policy’ in place is unlikely to be sufficient, as a great deal of what takes place at ‘street level’ is not determined by formal aims of central policy (Urwin and Jordan 2008 ). Having the right policies can send a strong political signal that adaptation needs to be considered seriously but flexibility in policy systems will be required to facilitate adaptive planning.

4 Discussion and conclusions

This broad survey of the literature indicated that, whilst there has been considerable development in research and thinking about adaptation in forest management over the last 10 years, research is still strongly focused on assessment of future impacts, responses and vulnerability of species and ecosystems (and in some cases communities and forest industries) to climate change. There has been some movement from a static view of climate based on long-term averages to a more detailed understanding of the drivers of different climate systems and how these affect the factors of greatest influence on different forest ecosystems processes, such as variability and extremes in temperature or precipitation or fire disturbance. For example, Guan et al. ( 2012 ) demonstrated that quasi-periodic climate variation on an inter-annual (ENSO) to inter-decadal (PDO) time scale can significantly influence tree growth and should be taken into account when assessing the impact of climate changes on forest productivity.

Adaptation is, in essence, about making good decisions for the future, taking into account the implications of climate change. It involves recognising and understanding potential future climate impacts and planning and managing for their consequences, whilst also considering the broader social, economic or other environmental changes that may impact on us, individually or collectively. To effectively provide a role in mitigation, delivering associated ecosystem services and benefits in poverty reduction (Eliasch 2008 ) forest management will have to adapt to a changing and highly variable climate. In achieving this, the roles and responsibilities of different levels of government, the private sector and different parts of the community are still being defined.

The broader literature emphasises that adaptation is a continuous process, involving a process of ‘adapting well’ to continuously changing conditions (Tompkins et al. 2010 ). This requires organisational learning based on past experience, new knowledge and a comprehensive analysis of future options. This can take place through ‘learning by doing’ or through a process of search and planned modification of routines (Berkhout et al. 2006 ). However, interpreting climate signals is not easy for organisations, the evidence of change is ambiguous and the stimuli are not often experienced directly within the organisation. For example, many forest managers in Australia currently feel little need to change practices to adapt to climate change, given both weak policy signals and limited perceived immediate evidence of increasing climate impacts (Cockfield et al. 2011 ). To explain and predict adaptation to climate change, the combination of personal experience and beliefs must be considered (Blennow et al. 2012 ). ‘Climate smart’ forest management frameworks can provide an improved basis for managing forested landscapes and maintaining ecosystem health and vitality based on an understanding of landscape vulnerability to future climatic change (Fig. 4 ) (Nitschke and Innes 2008a ).

Components of climate smart forest management (after Nitschke and Innes 2008a , b )

Many are now asking, do we really need more research to start adapting forest management to climate change? Whilst adaptation is often considered ‘knowledge deficit’ problem—where scientists provide more information and forest managers will automatically make better decisions—the reality is that the way in which this information is presented and how it is interpreted and received, will play major roles in determining potential responses. Successful adaptation will require dissemination of knowledge of potential climate impacts and suitable adaptation measures to decision makers at both practice and policy levels (Kolström et al. 2011 ) but it needs to go well beyond that.

Adaptation is, above all, a social learning process. It requires an understanding of sense of place, a capacity for individuals and society to consider potential future changes and what they mean for their circumstances. Leaders in forest management organisations will need to support a greater diversity of inputs into decision making, avoid creating rigid organisational hierarchies that deter innovation, and be inclusive, open and questioning (Konkin and Hopkins 2009 ). They will need to create more opportunities for interaction between researchers, managers and the community and space for reflection on the implications and the outcomes of management actions and unplanned events. Researchers will need to develop new modes of communication, providing knowledge in forms that are appropriate to the management decision and suitable for digestion by a range of different audiences.

From this analysis, key gaps in knowledge for adaptation may not be improved climate scenarios or better understanding of the biophysical responses of individual tree species or forest ecosystems to future climate. Knowledge gaps lie more in understanding the social and community attitudes and values that drive forest management and the decision making processes of forest managers, in order to work out how ‘climate intelligence’ can be built in to these processes.

The impacts of changing climate will vary locally. Consequently, managers must be given the flexibility to respond in ways that meet their particular needs and capacity to choose management options that are applicable to the local situation (Innes et al. 2009 ). This may not be consistent with rigid indicator-driven management assessment processes like forest certification. Whilst policy to support climate change mitigation is primarily a task for national governments and international agreements and processes, responsibility for supporting adaptation will fall more to sub-national and local governments, communities and the private sector. More active management will be required if specific values are to be maintained, particularly for forests in conservation reserves. This will require additional investment, but there has been little analysis to support the business case for investment in adaptation or to determine who should pay, particularly in developing countries.

We need to strengthen the relationship between climate science, forest research, forest managers and the community. Key challenges will include the setting of objectives for desired future conditions and accepting that we may not be able to maintain everything that forests have traditionally provided. It is important to discuss and agree on common goals in order to cope with, or benefit from, the challenges of future climates. Actively managing our forest ecosystems effectively and intelligently, using the best available knowledge and foresight capacity, can make those goals a reality.

Adams MA (2013) Mega-fires, tipping points and ecosystem services: managing forests and woodlands in an uncertain future. For Ecol Manag 294:250–261. doi: 10.1016/j.foreco.2012.11.039

Google Scholar  

Adger WN, Agrawala S, Mirza MMQ, Conde C, O’Brien K, Pulhin J, Pulwarty R, Smit B, Takahashi K (2007) Assessment of adaptation practices, options, constraints and capacity. In: Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE (eds) Climate change 2007: impacts, adaptation and vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel of Climate Change (IPCC). Cambridge University Press, Cambridge, pp 717–743

Aitken SN, Yeaman S, Holliday JA, Wang T, Curtis-McLane S (2008) Adaptation, migration or extirpation: climate change outcomes for tree populations. Evol Appl 1:95–111. doi: 10.1111/j.1752-4571.2007.00013.x

PubMed Central   PubMed   Google Scholar  

Alberto FJ, Aitken SN, Alia R, Gonzalez-Martinez SC, Hanninen H, Kremer A, Lefevre F, Lenormand T, Yeaman S, Whetten R, Savolainen O (2013) Potential for evolutionary responses to climate change evidence from tree populations. Glob Chang Biol 19:1645–1661. doi: 10.1111/gcb.12181

Allen CD, Macalady AK, Chenchouni H, Bachelet D, McDowell N, Vennetier M, Kitzberger T, Rigling A, Breshears DD, Hogg EH, Gonzalez P, Fensham R, Zhang Z, Castro J, Demidova N, Lim J-H, Allard G, Running SW, Semerci A, Cobb N (2010) A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. For Ecol Manag 259:660–684. doi: 10.1016/j.foreco.2009.09.001

Amraoui M, Liberato MLR, Calado TJ, DaCamara CC, Coelho LP, Trigo RM, Gouveia CM (2013) Fire activity over Mediterranean Europe based on information from Meteosat-8. For Ecol Manag 294:62–75. doi: 10.1016/j.foreco.2012.08.032

Ananda J, Herath G (2009) A critical review of multi-criteria decision making methods with special reference to forest management and planning. Ecol Econ 68:2535–2548. doi: 10.1016/j.ecolecon.2009.05.010

Andalo C, Beaulieu J, Bousquet J (2005) The impact of climate change on growth of local white spruce populations in Québec, Canada. For Ecol Manag 205:169–182. doi: 10.1016/j.foreco.2004.10.045

Anderson JM (1991) The effects of climate change on decomposition processes in grassland and coniferous forests. Ecol Appl 1:326–347. doi: 10.2307/1941761

Anderson JT, Panetta AM, Mitchell-Olds T (2012) Evolutionary and ecological responses to anthropogenic climate change. Plant Physiol 160:1728–1740. doi: 10.1104/pp. 112.206219

PubMed Central   CAS   PubMed   Google Scholar  

Attorre F, Francesconi F, Scarnati L, De Sanctis M, Alfo M, Bruno F (2008) Predicting the effect of climate change on tree species abundance and distribution at a regional scale. For Biogeosci For 1:132–139. doi: 10.3832/ifor0467-0010132

Battaglia M, Bruce J, Brack C, Baker T (2009) Climate change and Australia’s plantation estate: analysis of vulnerability and preliminary investigation of adaptation options.

Battaglia M, Sands P, White D, Mummery D (2004) CABALA: a linked carbon, water and nitrogen model of forest growth for silvicultural decision support. For Ecol Manag 193:251–282

Bele MY, Sonwa DJ, Tiani AM (2013a) Supporting local adaptive capacity to climate change in the Congo basin forest of Cameroon a participatory action research approach. Int J Clim Chang Strateg Manag 5:181–197. doi: 10.1108/17568691311327587

Bele MY, Tiani AM, Somorin OA, Sonwa DJ (2013b) Exploring vulnerability and adaptation to climate change of communities in the forest zone of Cameroon. Clim Chang 119:875–889. doi: 10.1007/s10584-013-0738-z

Berkhout F, Hertin J, Gann D (2006) Learning to adapt: organisational adaptation to climate change impacts. Clim Chang 78:135–156. doi: 10.1007/s10584-006-9089-3

Bernier P, Schöne D (2009) Adapting forests and their management to climate change: an overview. Unasylva 60:5–11

Blate GM, Joyce LA, Littell JS, McNulty SG, Millar CI, Moser SC, Neilson RP, O’Halloran K, Peterson DL (2009) Adapting to climate change in United States national forests. Unasylva 60:57–62

Blennow K, Persson J, Tome M, Hanewinkel M (2012) Climate change: believing and seeing implies adapting. PLoS ONE 7:e50182. doi: 10.1371/journal.pone.0050182

Boisvenue C, Running SW (2006) Impacts of climate change on natural forest productivity—evidence since the middle of the 20th century. Glob Chang Biol 12:862–882. doi: 10.1111/j.1365-2486.2006.01134.x

Bolte A, Eisenhauer DR, Ehrhart HP, Gross J, Hanewinkel M, Kolling C, Profft I, Rohde M, Rohe P, Amereller K (2009) Climate change and forest management—accordances and differences between the German states regarding assessments for needs and strategies towards forest adaptation. Landbauforschung Volkenrode 59:269–278

Bonan GB, Pollard D, Thompson SL (1992) Effects of boreal forest vegetation on global climate. Nature 359:716–718. doi: 10.1038/359716a0

Bongers F, Poorter L, Van Rompaey R, Parren MPE (1999) Distribution of twelve moist forest canopy tree species in Liberia and Cote d’Ivoire: response curves to a climatic gradient. J Veg Sci 10:371–382. doi: 10.2307/3237066

Booth TH (1990) Mapping regions climatically suitable for particular tree species at the global scale. For Ecol Manag 36:47–60

Booth TH (2013) Eucalypt plantations and climate change. For Ecol Manag 301:28–34. doi: 10.1016/j.foreco.2012.04.004

Booth TH, Nix HA, Hutchinson MF, Jovanovic T (1988) Niche analysis and tree species introduction. For Ecol Manag 23:47–59

Bowman DMJS, Williamson GJ, Keenan RJ, Prior LD (2014) A warmer world will reduce tree growth in evergreen broadleaf forests: evidence from Australian temperate and subtropical eucalypt forests. Glob Ecol Biogeogr 23:925–934. doi: 10.1111/geb.12171

Brautigam K, Vining KJ, Lafon-Placette C, Fossdal CG, Mirouze M, Marcos JG, Fluch S, Fraga MF, Guevara MA, Abarca D, Johnsen O, Maury S, Strauss SH, Campbell MM, Rohde A, Diaz-Sala C, Cervera MT (2013) Epigenetic regulation of adaptive responses of forest tree species to the environment. Ecol Evol 3:399–415. doi: 10.1002/ece3.461

Breed MF, Stead MG, Ottewell KM, Gardner MG, Lowe AJ (2013) Which provenance and where? Seed sourcing strategies for revegetation in a changing environment. Conserv Genet 14:1–10. doi: 10.1007/s10592-012-0425-z

Breymeyer A, Melillo JM (1991) Global climate change—the effects of climate change on production and decomposition in coniferous forests and grasslands. Ecol Appl 1:111–111. doi: 10.2307/1941804

Brooker RW, Travis JMJ, Clark EJ, Dytham C (2007) Modelling species’ range shifts in a changing climate: the impacts of biotic interactions, dispersal distance and the rate of climate change. J Theor Biol 245:59–65. doi: 10.1016/j.jtbi.2006.09.033

PubMed   Google Scholar  

Brotak EA, Reifsnyder WE (1977) Predicting major wildland fire occurrence. Fire Manag Notes 38:5–8

Brown HCP (2009) Climate change and Ontario forests: prospects for building institutional adaptive capacity. Mitig Adapt Strateg Glob Chang 14:513–536. doi: 10.1007/s11027-009-9183-8

Buma B, Wessman CA (2013) Forest resilience, climate change, and opportunities for adaptation: a specific case of a general problem. For Ecol Manag 306:216–225. doi: 10.1016/j.foreco.2013.06.044

Campbell EM, Saunders SC, Coates KD, Meidinger DV, MacKinnon A, O’Neil GA, MacKillop DJ, DeLong SC, Morgan. DG (2009) Ecological resilience and complexity: a theoretical framework for understanding and managing British Columbia’s forest ecosystems in a changing climate. B.C. Min. For. Range, For. Sci. Prog., Victoria, B.C.

Cannell MGR, Grace J, Booth A (1989) Possible impacts of climatic warming on trees and forests in the United Kingdom—a review. Forestry 62:337–364. doi: 10.1093/forestry/62.4.337

Carvalho A, Flannigan MD, Logan K, Miranda AI, Borrego C (2008) Fire activity in Portugal and its relationship to weather and the Canadian Fire Weather Index System. Int J Wildl Fire 17:328–338. doi: 10.1071/WF07014

Castagneri D, Motta R (2010) A research gap in the interactive effects of climate and competition on trees growth. In: Karam WP (ed) Tree growth: influences, layers and types. Nova Science, Hauppauge, pp 93–102

Caverley N (2013) The guardians of Mother Earth: a qualitative study of aboriginal knowledge keepers and their views on climate change adaptation in the South Selkirks region. Nativ Stud Rev 21:125–150

Cheaib A, Badeau V, Boe J, Chuine I, Delire C, Dufrêne E, François C, Gritti ES, Legay M, Pagé C, Thuiller W, Viovy N, Leadley P (2012) Climate change impacts on tree ranges: model intercomparison facilitates understanding and quantification of uncertainty. Ecol Lett 15:533–544. doi: 10.1111/j.1461-0248.2012.01764.x

Chen WJ, Black TA, Yang PC, Barr AG, Neumann HH, Nesic Z, Blanken PD, Novak MD, Eley J, Ketler RJ, Cuenca A (1999) Effects of climatic variability on the annual carbon sequestration by a boreal aspen forest. Glob Chang Biol 5:41–53. doi: 10.1046/j.1365-2486.1998.00201.x

CAS   Google Scholar  

Chmura DJ, Anderson PD, Howe GT, Harrington CA, Halofsky JE, Peterson DL, Shaw DC, St. Brad Clair J (2011) Forest responses to climate change in the northwestern United States: ecophysiological foundations for adaptive management. For Ecol Manag 261:1121–1142. doi: 10.1016/j.foreco.2010.12.040

Choat B, Jansen S, Brodribb TJ, Cochard H, Delzon S, Bhaskar R, Bucci SJ, Feild TS, Gleason SM, Hacke UG, Jacobsen AL, Lens F, Maherali H, Martinez-Vilalta J, Mayr S, Mencuccini M, Mitchell PJ, Nardini A, Pittermann J, Pratt RB, Sperry JS, Westoby M, Wright IJ, Zanne AE (2012) Global convergence in the vulnerability of forests to drought. Nature 491:752–755

CAS   PubMed   Google Scholar  

Chuvieco E, Martinez S, Roman MV, Hantson S, Pettinari ML (2014) Integration of ecological and socio-economic factors to assess global vulnerability to wildfire. Glob Ecol Biogeogr 23:245–258. doi: 10.1111/geb.12095

Clark DA (2007) Detecting tropical forests’ responses to global climatic and atmospheric change: current challenges and a way forward. Biotropica 39:4–19. doi: 10.1111/j.1744-7429.2006.00227.x

Clark JS, Bell DM, Hersh MH, Nichols L (2011) Climate change vulnerability of forest biodiversity: climate and competition tracking of demographic rates. Glob Chang Biol 17:1834–1849. doi: 10.1111/j.1365-2486.2010.02380.x

Cockfield G, Maraseni T, Buys L, Sommerfeld J, Wilson C, Athukorala W (2011) Socioeconomic implications of climate change with regard to forests and forest management. Contribution of Work Package 3 to the Forest Vulnerability Assessment. National Climate Change Adaptation Research Facility, Gold Coast

Corlett RT (2011) Impacts of warming on tropical lowland rainforests. Trends Ecol Evol 26:606–613

Corlett RT, Westcott DA (2013) Will plant movements keep up with climate change? Trends Ecol Evol 28:482–488. doi: 10.1016/j.tree.2013.04.003

Couture S, Reynaud A (2008) Multi-stand forest management under a climatic risk: do time and risk preferences matter? Environ Model Assess 13:181–193

D’Amato AW, Bradford JB, Fraver S, Palik BJ (2011) Forest management for mitigation and adaptation to climate change: insights from long-term silviculture experiments. For Ecol Manag 262:803–816. doi: 10.1016/j.foreco.2011.05.014

Daubenmire RF (1978) Plant geography. Academic, New York

Davidar P, Rajagopal B, Mohandass D, Puyravaud JP, Condit R, Wright SJ, Leigh EG (2007) The effect of climatic gradients, topographic variation and species traits on the beta diversity of rain forest trees. Glob Ecol Biogeogr 16:510–518. doi: 10.1111/j.1466-8238.2007.00307.x

Davis MB (1986) Climatic instability, time lags and community disequilibrium. In: Diamond J, Case TJ (eds) Community ecology. Harper and Row, New York, pp 269–284

Day JK, Perez DM (2013) Reducing uncertainty and risk through forest management planning in British Columbia. For Ecol Manag 300:117–124. doi: 10.1016/j.foreco.2012.11.035

de Groot WJ, Flannigan MD, Cantin AS (2013) Climate change impacts on future boreal fire regimes. For Ecol Manag 294:35–44. doi: 10.1016/j.foreco.2012.09.027

Dessai S, Hulme M (2004) Does climate adaptation policy need probabilities? Clim Pol 4:107–128. doi: 10.1080/14693062.2004.9685515

Di Nitto D, Neukermans G, Koedam N, Defever H, Pattyn F, Kairo JG, Dahdouh-Guebas F (2014) Mangroves facing climate change: landward migration potential in response to projected scenarios of sea level rise. Biogeosciences 11:857–871. doi: 10.5194/bg-11-857-2014

Dixon RK, Krankina ON, Kobak KI (1996) Global climate change adaptation: examples from Russian boreal forests. Adapting to climate change: an international perspective.

Dobrowski SZ, Abatzoglou J, Swanson AK, Greenberg JA, Mynsberge AR, Holden ZA, Schwartz MK (2013) The climate velocity of the contiguous United States during the 20th century. Glob Chang Biol 19:241–251. doi: 10.1111/gcb.12026

Doyle TW, Krauss KW, Conner WH, From AS (2010) Predicting the retreat and migration of tidal forests along the northern Gulf of Mexico under sea-level rise. For Ecol Manag 259:770–777. doi: 10.1016/j.foreco.2009.10.023

Eliasch J (2008) Climate change: financing global forests. The Eliasch Review. HMSO

Emanuel WR, Shugart HH, Stevenson MP (1985) Climatic-change and the broad-scale distribution of terrestrial ecosystem complexes. Clim Chang 7:29–43. doi: 10.1007/bf00139439

Eriksson LO, Backéus S, Garcia F (2011) Implications of growth uncertainties associated with climate change for stand management. Eur J For Res 131:1199–1209. doi: 10.1007/s10342-011-0591-4

Ettl GJ, Peterson DL (1995) Extreme climate and variation in tree growth—individualistic response in sub-alpine fir ( Abies-lasiocarpa ). Glob Chang Biol 1:231–241. doi: 10.1111/j.1365-2486.1995.tb00024.x

Feeley KJ, Rehm EM, Machovina B (2012) Perspective: the responses of tropical forest species to global climate change: acclimate, adapt, migrate, or go extinct? Frontiers of Biogeography 4 (2)

Feikema PM, Sherwin CB, Lane PNJ (2013) Influence of climate, fire severity and forest mortality on predictions of long term streamflow: potential effect of the 2009 wildfire on Melbourne’s water supply catchments. J Hydrol 488:1–16. doi: 10.1016/j.jhydrol.2013.02.001

Fischer AP, Paveglio T, Carroll M, Murphy D, Brenkert-Smith H (2013) Assessing social vulnerability to climate change in human communities near public forests and grasslands: a framework for resource managers and planners. J For 111:357–365. doi: 10.5849/jof. 12-091

Fischlin A, Ayres M, Karnosky D, Kellomäki S, Louman B, Ong C, Plattner G-K, Santoso H, Thompson I, Booth TH, Marcar N, Scholes B, Swanston C, Zamolodchikov D (2009) Future environmental impacts and vulnerabilities. In: Seppälä R, Buck A, Katila P (eds) Adaptation of forests and people to climate change: a global assessment report, vol 22. IUFRO World Series, Helsinki, pp 53–100

Franks PJ, Adams MA, Amthor JS, Barbour MM, Berry JA, Ellsworth DS, Farquhar GD, Ghannoum O, Lloyd J, McDowell N, Norby RJ, Tissue DT, von Caemmerer S (2013) Sensitivity of plants to changing atmospheric CO2 concentration: from the geological past to the next century. New Phytol 197:1077–1094. doi: 10.1111/nph.12104

Furness E, Nelson H (2012) Community forest organizations and adaptation to climate change in British Columbia. For Chron 88:519–524

Garcia RA, Cabeza M, Rahbek C, Araújo MB (2014) Multiple dimensions of climate change and their implications for biodiversity. Science 344 (6183). doi:10.1126/science.1247579

Gentilli J (1949) Forest influences: the effects of woody vegetation on climatic water, and soil, with applications to the conservation of water and the control of floods and erosion. Geogr Rev 39:164–164. doi: 10.2307/211169

Gibbs HK, Ruesch AS, Achard F, Clayton MK, Holmgren P, Ramankutty N, Foley JA (2010) Tropical forests were the primary sources of new agricultural land in the 1980s and 1990s. Proc Natl Acad Sci 107:16732–16737. doi: 10.1073/pnas.0910275107

Gilman RT, Fabina NS, Abbott KC, Rafferty NE (2012) Evolution of plant–pollinator mutualisms in response to climate change. Evol Appl 5:2–16. doi: 10.1111/j.1752-4571.2011.00202.x

Gonzalez ME, Lara A, Urrutia R, Bosnich J (2011) Climatic change and its potential impact on forest fire occurrence in south-central Chile (33 degrees-42 degrees S). Bosque 32:215–219. doi: 10.4067/s0717-92002011000300002

Graham RL, Turner MG, Dale VH (1990) How increasing CO2 and climate change affect forests—at many spatial and temporal scales, there will be forest responses that will be affected by human activities. Bioscience 40:575–587. doi: 10.2307/1311298

Graumlich LJ (1993) Response of tree growth to climatic variation in the mixed conifer and deciduous forests of the upper Great-Lakes region. Can J For Res 23:133–143. doi: 10.1139/x93-020

Groffman PM, Rustad LE, Templer PH, Campbell JL, Christenson LM, Lany NK, Socci AM, Vadeboncoeur MA, Schaberg PG, Wilson GF, Driscoll CT, Fahey TJ, Fisk MC, Goodale CL, Green MB, Hamburg SP, Johnson CE, Mitchell MJ, Morse JL, Pardo LH, Rodenhouse NL (2012) Long-term integrated studies show complex and surprising effects of climate change in the northern hardwood forest. Bioscience 62:1056–1066. doi: 10.1525/bio.2012.62.12.7

Grubb PJ, Whitmore TC (1966) A comparison of montane and lowland rain forest in Ecuador. 2. Climate and its effects on distribution and physiognomy of forests. J Ecol 54:303. doi: 10.2307/2257951

Guan BT, Wright WE, Chung C-H, Chang S-T (2012) ENSO and PDO strongly influence Taiwan spruce height growth. For Ecol Manag 267:50–57. doi: 10.1016/j.foreco.2011.11.028

Guardiola-Claramonte M, Troch PA, Breshears DD, Huxman TE, Switanek MB, Durcik M, Cobb NS (2011) Decreased streamflow in semi-arid basins following drought-induced tree die-off: a counter-intuitive and indirect climate impact on hydrology. J Hydrol 406:225–233. doi: 10.1016/j.jhydrol.2011.06.017

Guariguata MR (2009) Tropical forest management and climate change adaptation. Rev Estud Soc 32:98–112

Guariguata MR, Cornelius JP, Locatelli B, Forner C, Sánchez-Azofeifa GA (2008) Mitigation needs adaptation: tropical forestry and climate change. Mitig Adapt Strateg Glob Chang 13:793–808. doi: 10.1007/s11027-007-9141-2

Guariguata MR, Locatelli B, Haupt F (2012) Adapting tropical production forests to global climate change: risk perceptions and actions. Int For Rev 14:27–38

Gyampoh BA, Amisah S, Idinoba M, Nkem J (2009) Using traditional knowledge to cope with climate change in rural Ghana. Unasylva 60:70–74

Hahn WA, Knoke T (2010) Sustainable development and sustainable forestry: analogies, differences, and the role of flexibility. Eur J For Res 129:787–801. doi: 10.1007/s10342-010-0385-0

Hamrick JL (2004) Response of forest trees to global environmental changes. For Ecol Manag 197:323–335. doi: 10.1016/j.foreco.2004.05.023

Hansenbristow KJ, Ives JD, Wilson JP (1988) Climatic variability and tree response within the forest alpine tundra ecotone. Ann Assoc Am Geogr 78:505–519. doi: 10.1111/j.1467-8306.1988.tb00221.x

Harper RJ, Smettem KRJ, Carter JO, McGrath JF (2009) Drought deaths in Eucalyptus globulus (Labill.) plantations in relation to soils, geomorphology and climate. Plant Soil 324:199–207. doi: 10.1007/s11104-009-9944-x

Heller NE, Zavaleta ES (2009) Biodiversity management in the face of climate change: a review of 22 years of recommendations. Biol Conserv 142:14–32. doi: 10.1016/j.biocon.2008.10.006

Hennessy K, Lucas C, Nicholls N, Bathols J, Suppiah R, Ricketts J (2005) Climate change impacts on fire-weather in south-east Australia. CSIRO Division of Marine and Atmospheric Research, Aspendale

Holling CS (1978) Adaptive environmental assessment and management. Wiley, Chichester

Hughes L, Cawsey EM, Westoby M (1996) Climatic range sizes of Eucalyptus species in relation to future climate change. Glob Ecol Biogeogr Lett 5:23–29. doi: 10.2307/2997467

Huntingford C, Zelazowski P, Galbraith D, Mercado LM, Sitch S, Fisher R, Lomas M, Walker AP, Jones CD, Booth BBB, Malhi Y, Hemming D, Kay G, Good P, Lewis SL, Phillips OL, Atkin OK, Lloyd J, Gloor E, Zaragoza-Castells J, Meir P, Betts R, Harris PP, Nobre C, Marengo J, Cox PM (2013) Simulated resilience of tropical rainforests to CO2-induced climate change. Nat Geosci 6:268–273

Huntley B (1990) European postglacial forests—compositional changes in response to climatic-change. J Veg Sci 1:507–518. doi: 10.2307/3235785

Ince PJ, Kramp AD, Skog KE, Yoo DI, Sample VA (2011) Modeling future U.S. forest sector market and trade impacts of expansion in wood energy consumption. J For Econ 17:142–156. doi: 10.1016/j.jfe.2011.02.007

Innes J, Joyce LA, Kellomäki S, Louman B, Ogden A, Parrotta J, Thompson I, Ayres M, Ong C, Santoso H, Sohngen B, Wreford A (2009) Management for adaptation. In: Seppälä R, Buck A, Katila P (eds) Adaptation of forests and people to climate change: a global assessment report, vol World Series Volume 22. IUFRO Helsinki, pp 135–186

IPCC (2013) Climate Change 2013: The physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge, United Kingdom and New York, NY, USA

IUCN (2008) Ecosystem-based adaptation: an approach for building resilience and reducing risk for local communities and ecosystems. Submission to the Chair of the AWG-LCA with respect to the Shared Vision and Enhanced Action on Adaptation. International Union for the Conservation of Nature,

Iverson LR, Schwartz MW, Prasad AM (2004) How fast and far might tree species migrate in the eastern United States due to climate change? Glob Ecol Biogeogr 13:209–219

Johnson G, Sorensen FC, St Clair JB, Cronn RC (2004) Pacific Northwest forest tree seed zones: a template for native plants? Nativ Plants J 5:131–140

Johnston M, Hesseln H (2012) Climate change adaptive capacity of the Canadian forest sector. For Policy Econ 24:29–34. doi: 10.1016/j.forpol.2012.06.001

Johnston M, Lindner M, Parrotta J, Giessen L (2012) Adaptation and mitigation options for forests and forest management in a changing climate. For Policy Econ 24:1–2. doi: 10.1016/j.forpol.2012.09.007

Johnston M, Williamson T (2007) A framework for assessing climate change vulnerability of the Canadian forest sector. For Chron 83:358–361

Joyce LA (2007) The impacts of climate change on forestry. In: Adams DM, Haynes RW (eds) Resource and market projections for forest policy development: twenty-five years of experience with the US RPA Timber Assessment, vol 14. Managing Forest Ecosystems. pp 449–488

Joyce LA, Blate GM, Littell JS, McNulty SG, Millar CI, Moser SC, Neilson RP, O’Halloran K, Peterson DL (2008) National forests. Preliminary review of adaptation options for climate-sensitive ecosystems and resources. A report by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research. US Environmental Protection Agency, Washington, DC

Joyce LA, Blate GM, McNulty SG, Millar CI, Moser S, Neilson RP, Peterson DL (2009) Managing for multiple resources under climate change: national forests. Environ Manag 44:1022–1032. doi: 10.1007/s00267-009-9324-6

Joyce LA, Mills JR, Heath LS, McGuire AD, Haynes RW, Birdsey RA (1995) Forest sector impacts from changes in forest productivity under climate change. J Biogeogr 22:703–713. doi: 10.2307/2845973

Kalame FB, Luukkanen O, Kanninen M (2011) Making the National Adaptation Programme of Action (NAPA) more responsive to the livelihood needs of tree planting farmers, drawing on previous experience in dryland Sudan. Forests 2:948–960. doi: 10.3390/f2040948

Kallarackal J, Roby TJ (2012) Responses of trees to elevated carbon dioxide and climate change. Biodivers Conserv 21:1327–1342. doi: 10.1007/s10531-012-0254-x

Kant P, Wu S (2012) Should adaptation to climate change be given priority over mitigation in tropical forests? Carbon Manag 3:303–311. doi: 10.4155/cmt.12.29

Karjalainen T, Pussinen A, Liski J, Nabuurs GJ, Eggers T, Lapvetelainen T, Kaipainen T (2003) Scenario analysis of the impacts of forest management and climate change on the European forest sector carbon budget. For Policy Econ 5:141–155. doi: 10.1016/s1389-9341(03)00021-2

Keenan RJ (2012) Adaptation of forests and forest management to climate change: an editorial. Forests 3:75–82. doi: 10.3390/f3010075

Kellomaki S, Peltola H, Nuutinen T, Korhonen KT, Strandman H (2008) Sensitivity of managed boreal forests in Finland to climate change, with implications for adaptive management. Phil Trans R Soc B 363:2341–2351. doi: 10.1098/rstb.2007.2204

Kelly AE, Goulden ML (2008) Rapid shifts in plant distribution with recent climate change. Proc Natl Acad Sci 105:11823–11826. doi: 10.1073/pnas.0802891105

Kerhoulas LP, Kolb TE, Hurteau MD, Koch GW (2013) Managing climate change adaptation in forests: a case study from the US Southwest. J Appl Ecol 50:1311–1320. doi: 10.1111/1365-2664.12139

Keskitalo EC (2008) Vulnerability and adaptive capacity in forestry in northern Europe: a Swedish case study. Clim Chang 87:219–234. doi: 10.1007/s10584-007-9337-1

Keskitalo ECH (2011) How can forest management adapt to climate change? Possibilities in different forestry systems. Forests 2:415–430. doi: 10.3390/f2010415

Kienast F, Brzeziecki B, Wildi O (1996) Long-term adaptation potential of Central European mountain forests to climate change: a GIS-assisted sensitivity assessment. For Ecol Manag 80:133–153. doi: 10.1016/0378-1127(95)03633-4

Kimmins JP (2002) Future shock in forestry—where have we come from; where are we going; is there a “right way” to manage forests? Lessons from Thoreau, Leopold, Toffler, Botkin and Nature. For Chron 78:263–271

Kimmins JP (2008) From science to stewardship: harnessing forest ecology in the service of society. For Ecol Manag 256:1625–1635. doi: 10.1016/j.foreco.2008.02.057

Kimmins JP, Blanco JA, Seely B, Welham C, Scoullar K (2008) Complexity in modelling forest ecosystems: how much is enough? For Ecol Manag 256:1646–1658. doi: 10.1016/j.foreco.2008.03.011

Kimmins JP, Mailly D, Seely B (1999) Modelling forest ecosystem net primary production: the hybrid simulation approach used in forecast. Ecol Model 122:195–224

Kint V, Aertsen W, Campioli M, Vansteenkiste D, Delcloo A, Muys B (2012) Radial growth change of temperate tree species in response to altered regional climate and air quality in the period 1901–2008. Clim Chang 115:343–363. doi: 10.1007/s10584-012-0465-x

Kirschbaum MUF, Watt MS, Tait A, Ausseil A-GE (2012) Future wood productivity of Pinus radiata in New Zealand under expected climatic changes. Glob Chang Biol 18:1342–1356. doi: 10.1111/j.1365-2486.2011.02625.x

Klenk NL, Adams BW, Bull GQ, Innes JL, Cohen SJ, Larson BC (2011) Climate change adaptation and sustainable forest management: a proposed reflexive research agenda. For Chron 87:351–357

Kobak KI, Turchinovich IY, Kondrasheva NY, Schulze ED, Schulze W, Koch H, Vygodskaya NN (1996) Vulnerability and adaptation of the larch forest in eastern Siberia to climate change. Water Air Soil Pollut 92:119–127

Kolström M, Lindner M, Vilén T, Maroschek M, Seidl R, Lexer MJ, Netherer S, Kremer A, Delzon S, Barbati A, Marchetti M, Corona P (2011) Reviewing the science and Implementation of climate change adaptation measures in European forestry. Forests 2:961–982. doi: 10.3390/f2040961

Konkin D, Hopkins K (2009) Learning to deal with climate change and catastrophic forest disturbances. Unasylva 60:17–23

Kremer A, Ronce O, Robledo-Arnuncio JJ, Guillaume F, Bohrer G, Nathan R, Bridle JR, Gomulkiewicz R, Klein EK, Ritland K, Kuparinen A, Gerber S, Schueler S (2012) Long-distance gene flow and adaptation of forest trees to rapid climate change. Ecol Lett 15:378–392. doi: 10.1111/j.1461-0248.2012.01746.x

PubMed Central   Google Scholar  

Kuparinen A, Savolainen O, Schurr FM (2010) Increased mortality can promote evolutionary adaptation of forest trees to climate change. For Ecol Manag 259:1003–1008. doi: 10.1016/j.foreco.2009.12.006

Lal R, Cummings DJ (1979) Clearing a tropical forest. 1. Effects on soil and micro-climate. Field Crop Res 2:91–107. doi: 10.1016/0378-4290(79)90012-1

Leites LP, Rehfeldt GE, Robinson AP, Crookston NL, Jaquish B (2012) Possibilities and limitations of using historic provenance tests to infer forest species growth responses to climate change. Nat Resour Model 25:409–433. doi: 10.1111/j.1939-7445.2012.00129.x

Lenoir J, Gegout JC, Dupouey JL, Bert D, Svenning JC (2010) Forest plant community changes during 1989–2007 in response to climate warming in the Jura Mountains (France and Switzerland). J Veg Sci 21:949–964. doi: 10.1111/j.1654-1103.2010.01201.x

Leuzinger S, Luo Y, Beier C, Dieleman W, Vicca S, Körner C (2011) Do global change experiments overestimate impacts on terrestrial ecosystems? Trends Ecol Evol 26:236–241

Levina E, Tirpak D (2006) Adaptation to climate change: key terms. OECD/IEA, Paris

Lin BB, Petersen B (2013) Resilience, regime shifts, and guided transition under climate change: examining the practical difficulties of managing continually changing systems. Ecology and Society 18 (1). doi:10.5751/es-05128-180128

Lindner M (2000) Developing adaptive forest management strategies to cope with climate change. Tree Physiol 20:299–307

Lindner M, Fitzgerald JB, Zimmermann NE, Reyer C, Delzon S, van der Maaten E, Schelhaas MJ, Lasch P, Eggers J, van der Maaten-Theunissen M, Suckow F, Psomas A, Poulter B, Hanewinkel M (2014) Climate change and European forests: what do we know, what are the uncertainties, and what are the implications for forest management? J Environ Manag 146:69–83. doi: 10.1016/j.jenvman.2014.07.030

Lindner M, Maroschek M, Netherer S, Kremer A, Barbati A, Garcia-Gonzalo J, Seidl R, Delzon S, Corona P, Kolström M, Lexer MJ, Marchetti M (2010) Climate change impacts, adaptive capacity, and vulnerability of European forest ecosystems. For Ecol Manag 259:698–709. doi: 10.1016/j.foreco.2009.09.023

Lindner M, Sohngen B, Joyce LA, Price DT, Bernier PY, Karjalainen T (2002) Integrated forestry assessments for climate change impacts. For Ecol Manag 162:117–136. doi: 10.1016/S0378-1127(02)00054-3

Littell JS, Peterson DL, Millar CI, O’Halloran KA (2012) U.S. national forests adapt to climate change through science-management partnerships. Clim Chang 110:269–296. doi: 10.1007/s10584-011-0066-0

Liu Y, Stanturf J, Goodrick S (2010) Trends in global wildfire potential in a changing climate. For Ecol Manag 259:685–697. doi: 10.1016/j.foreco.2009.09.002

Locatelli B, Evans V, Wardell A, Andrade A, Vignola R (2011) Forests and climate change in Latin America: linking adaptation and mitigation. Forests 2:431–450. doi: 10.3390/f2010431

Loehman RA, Clark JA, Keane RE (2011) Modeling effects of climate change and fire management on Western White Pine (Pinus monticola) in the Northern Rocky Mountains, USA. Forests 2:832–860. doi: 10.3390/f2040832

Long A (2013) REDD plus, adaptation, and sustainable forest management: toward effective polycentric global forest governance. Trop Conserv Sci 6:384–408

Lucier A, Ayres M, Karnosky D, Thompson I, Loehle C, Percy K, Sohngen B (2009) Forest responses and vulnerabilities to recent climate change. In: Seppälä R, Buck A, Katila P (eds) Adaptation of forests and people to climate change: a global assessment report, vol World Series Volume 22. IUFRO Helsinki, pp 29–52

Lynch AJJ, Fell DG, McIntyre-Tamwoy S (2010) Incorporating Indigenous values with ‘Western’ conservation values in sustainable biodiversity management. Aust J Environ Manag 17:244–255

Macdonald GM, Edwards TWD, Moser KA, Pienitz R, Smol JP (1993) Rapid response of treeline vegetation and lakes to past climate warming. Nature 361:243–246. doi: 10.1038/361243a0

Mahat V, Anderson A (2013) Impacts of climate and catastrophic forest changes on streamflow and water balance in a mountainous headwater stream in Southern Alberta. Hydrol Earth Syst Sci 17:4941–4956. doi: 10.5194/hess-17-4941-2013

Malcolm JR, Markham A, Neilson RP, Garaci M (2002) Estimated migration rates under scenarios of global climate change. J Biogeogr 29:835–849. doi: 10.1046/j.1365-2699.2002.00702.x

Matthews SN, Iverson LR, Prasad AM, Peters MP (2011) Changes in potential habitat of 147 North American breeding bird species in response to redistribution of trees and climate following predicted climate change. Ecography 34:933–945. doi: 10.1111/j.1600-0587.2011.06803.x

McEvoy D, Fünfgeld H, Bosomworth K (2013) Resilience and climate change adaptation: the importance of framing. Plan Pract Res 28:280–293. doi: 10.1080/02697459.2013.787710

Medlyn B, Zeppel M, Brouwers N, Howard K, O’Gara E, Hardy G, Lyons T, Li L, Evans B (2011) Biophysical impacts of climate change on Australia’s forests. Contribution of Work Package 2 to the Forest Vulnerability Assessment. National Climate Change Adaptation Research Facility, Gold Coast

Messier C, Puettmann K, Coates DJ (2013) Managing forests as complex adaptive systems: building resilience to the challenge of global change. Earthscan, London

Michelot A, Breda N, Damesin C, Dufrene E (2012) Differing growth responses to climatic variations and soil water deficits of Fagus sylvatica, Quercus petraea and Pinus sylvestris in a temperate forest. For Ecol Manag 265:161–171. doi: 10.1016/j.foreco.2011.10.024

Milad M, Schaich H, Konold W (2013) How is adaptation to climate change reflected in current practice of forest management and conservation? A case study from Germany. Biodivers Conserv 22:1181–1202. doi: 10.1007/s10531-012-0337-8

Miles L, Grainger A, Phillips O (2004) The impact of global climate change on tropical forest biodiversity in Amazonia. Glob Ecol Biogeogr 13:553–565. doi: 10.1111/j.1466-822X.2004.00105.x

Mok H-F, Arndt SK, Nitschke CR (2012) Modelling the potential impact of climate variability and change on species regeneration potential in the temperate forests of South-Eastern Australia. Glob Chang Biol 18:1053–1072. doi: 10.1111/j.1365-2486.2011.02591.x

Mori AS, Spies TA, Sudmeier-Rieux K, Andrade A (2013) Reframing ecosystem management in the era of climate change: issues and knowledge from forests. Biol Conserv 165:115–127. doi: 10.1016/j.biocon.2013.05.020

Namkoong G (2001) Forest genetics: pattern and complexity. Can J For Res 31:623–632. doi: 10.1139/cjfr-31-4-623

Neukum C, Azzam R (2012) Impact of climate change on groundwater recharge in a small catchment in the Black Forest, Germany. Hydrogeol J 20:547–560. doi: 10.1007/s10040-011-0827-x

Nilsson AE, Gerger Swartling Å, Eckerberg K (2012) Knowledge for local climate change adaptation in Sweden: challenges of multilevel governance. Local Environ 17:751–767. doi: 10.1080/13549839.2012.678316

Nitschke CR, Innes JL (2008a) Integrating climate change into forest management in South-Central British Columbia: an assessment of landscape vulnerability and development of a climate-smart framework. For Ecol Manag 256:313–327. doi: 10.1016/j.foreco.2008.04.026

Nitschke CR, Innes JL (2008b) A tree and climate assessment tool for modelling ecosystem response to climate change. Ecol Model 210:263–277. doi: 10.1016/j.ecolmodel.2007.07.026

Nkem J, Kalame FB, Idinoba M, Somorin OA, Ndoye O, Awono A (2010) Shaping forest safety nets with markets: adaptation to climate change under changing roles of tropical forests in Congo Basin. Environ Sci Pol 13:498–508. doi: 10.1016/j.envsci.2010.06.004

Ogden AE, Innes J (2007a) Incorporating climate change adaptation considerations into forest management planning in the boreal forest. Int For Rev 9:713–733. doi: 10.1505/ifor.9.3.713

Ogden AE, Innes JL (2007b) Perspectives of forest practitioners on climate change adaptation in the Yukon and Northwest Territories of Canada. For Chron 83:557–569

Ogden AE, Innes JL (2009) Application of structured decision making to an assessment of climate change vulnerabilities and adaptation options for sustainable forest management. Ecology and Society 14 (1). doi:11

Ohlson DW, McKinnon GA, Hirsch KG (2005) A structured decision-making approach to climate change adaptation in the forest sector. For Chron 81:97–103

Otterman J, Chou MD, Arking A (1984) Effects of nontropical forest cover on climate. J Clim Appl Meteorol 23:762–767. doi: 10.1175/1520-0450(1984)023<0762:eonfco>2.0.co;2

Parks CG, Bernier P (2010) Adaptation of forests and forest management to changing climate with emphasis on forest health: a review of science, policies and practices. For Ecol Manag 259:657–659. doi: 10.1016/s0378-1127(09)00903-7

Pastor J, Post WM (1988) Response of northern forests to CO2-induced climate change. Nature 334:55–58. doi: 10.1038/334055a0

Pearson RG, Dawson TP (2003) Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Glob Ecol Biogeogr 12:361–371. doi: 10.1046/j.1466-822X.2003.00042.x

Peel J, Godden L, Keenan RJ (2012) Climate change law in an era of multi-level governance. Transl Environ Law 1:245–280. doi: 10.1017/S2047102512000052

Peters EB, Wythers KR, Zhang SX, Bradford JB, Reich PB (2013) Potential climate change impacts on temperate forest ecosystem processes. Can J For Res 43:939–950. doi: 10.1139/cjfr-2013-0013

Peterson DL, Millar CI, Joyce LA, Furniss MJ, Halofsky JE, Neilson RP, Morelli TL (2011) Responding to climate change in national forests: a guidebook for developing adaptation options. General Technical Report. USDA Forest Service, Pacific Northwest Research Station

Phillips OL, Lewis SL, Baker TR, Chao K-J, Higuchi N (2008) The changing Amazon forest. Phil Trans R Soc B 363:1819–1827. doi: 10.1098/rstb.2007.0033

Pinkard EA, Battaglia M, Bruce J, Leriche A, Kriticos DJ (2010) Process-based modelling of the severity and impact of foliar pest attack on eucalypt plantation productivity under current and future climates. For Ecol Manag 259:839–847. doi: 10.1016/j.foreco.2009.06.027

Pojar J, Klinka K, Meidinger DV (1987) Biogeoclimatic ecosystem classification in British Columbia. For Ecol Manag 22:119–154

Pramova E, Locatelli B, Djoudi H, Somorin OA (2012) Forests and trees for social adaptation to climate variability and change. Wiley Interdiscip Rev Clim Chang 3:581–596. doi: 10.1002/wcc.195

Prato T (2008) Conceptual framework for assessment and management of ecosystem impacts of climate change. Ecol Complex 5:329–338

Pretzsch H, Biber P, Schütze G, Uhl E, Rötzer T (2014) Forest stand growth dynamics in Central Europe have accelerated since 1870. Nat Commun 5. doi:10.1038/ncomms5967

Rastetter EB, Ryan MG, Shaver GR, Melillo JM, Nadelhoffer KJ, Hobbie JE, Aber JD (1991) A general biogeochemical model describing the responses of the C and N cycles in terrestrial ecosystems to changes in CO2, climate, and N deposition. Tree Physiol 9:101–126

Rayner J, McNutt K, Wellstead A (2013) Dispersed capacity and weak coordination: the challenge of climate change adaptation in Canada’s forest policy sector. Rev Policy Res 30:66–90. doi: 10.1111/ropr.12003

Regniere J (2009) Predicting insect continental distributions from species physiology. Unasylva 60:37–42

Reyer C, Lasch-Born P, Suckow F, Gutsch M, Murawski A, Pilz T (2014) Projections of regional changes in forest net primary productivity for different tree species in Europe driven by climate change and carbon dioxide. Ann For Sci 71:211–225. doi: 10.1007/s13595-013-0306-8

Rigling A, Bigler C, Eilmann B, Feldmeyer-Christe E, Gimmi U, Ginzler C, Graf U, Mayer P, Vacchiano G, Weber P, Wohlgemuth T, Zweifel R, Dobbertin M (2013) Driving factors of a vegetation shift from Scots pine to pubescent oak in dry Alpine forests. Glob Chang Biol 19:229–240. doi: 10.1111/gcb.12038

Rist L, Moen J (2013) Sustainability in forest management and a new role for resilience thinking. For Ecol Manag 310:416–427. doi: 10.1016/j.foreco.2013.08.033

Roberts G, Parrotta J, Wreford A (2009) Current adaptation measures and policies. In: Seppälä R, Buck A, Katila P (eds) Adaptation of forests and people to climate change: a global assessment report, vol World Series Volume 22. IUFRO Helsinki, pp 123–134

Ruiz-Labourdette D, Schmitz MF, Pineda FD (2013) Changes in tree species composition in Mediterranean mountains under climate change: indicators for conservation planning. Ecol Indic 24:310–323. doi: 10.1016/j.ecolind.2012.06.021

Running SW, Nemani RR (1991) Regional hydrologic and carbon balance responses of forests resulting from potential climate change. Clim Chang 19:349–368. doi: 10.1007/bf00151173

Sample VA, Halofsky JE, Peterson DL (2014) US strategy for forest management adaptation to climate change: building a framework for decision making. Ann For Sci 71:125–130. doi: 10.1007/s13595-013-0288-6

Schaich H, Milad M (2013) Forest biodiversity in a changing climate: which logic for conservation strategies? Biodivers Conserv 22:1107–1114. doi: 10.1007/s10531-013-0491-7

Schoene DHF, Bernier PY (2012) Adapting forestry and forests to climate change: a challenge to change the paradigm. For Policy Econ 24:12–19. doi: 10.1016/j.forpol.2011.04.007

Schwartz MW, Dolanc CR, Gao H, Strauss SY, Schwartz AC, Williams JN, Tang Y (2013) Forest structure, stand composition, and climate-growth response in montane forests of Jiuzhaigou National Nature Reserve, China. Plos One 8 (8). doi:10.1371/journal.pone.0071559

Scott D (2005) Integrating climate change into Canada’s National Parks System. In: Lovejoy T, Hannah L (eds) Climate change and biodiversity. Yale University Press, New Haven, pp 343–345

Seidl R, Lexer MJ (2013) Forest management under climatic and social uncertainty: trade-offs between reducing climate change impacts and fostering adaptive capacity. J Environ Manag 114:461–469. doi: 10.1016/j.jenvman.2012.09.028

Seidl R, Rammer W, Lexer MJ (2011) Adaptation options to reduce climate change vulnerability of sustainable forest management in the Austrian Alps. Can J For Res 41:694–706. doi: 10.1139/x10-235

Seppala R (2009) A global assessment on adaptation of forests to climate change. Scand J For Res 24:469–472. doi: 10.1080/02827580903378626

Seppälä R, Buck A, Katila P (2009) Adaptation of forests and people to climate change: a global assessment report, vol World Series Volume 22. Helsinki, IUFRO

Six DL (2009) Climate change and mutualism. Nat Rev Microbiol 7:686–686

Somorin OA, Brown HCP, Visseren-Hamakers IJ, Sonwa DJ, Arts B, Nkem J (2012) The Congo Basin forests in a changing climate: Policy discourses on adaptation and mitigation (REDD+). Glob Environ Chang 22:288–298. doi: 10.1016/j.gloenvcha.2011.08.001

Sonwa DJ, Somorin OA, Jum C, Bele MY, Nkem JN (2012) Vulnerability, forest-related sectors and climate change adaptation: the case of Cameroon. For Policy Econ 23:1–9. doi: 10.1016/j.forpol.2012.06.009

Sork VL, Aitken SN, Dyer RJ, Eckert AJ, Legendre P, Neale DB (2013) Putting the landscape into the genomics of trees: approaches for understanding local adaptation and population responses to changing climate. Tree Genet Genome 9:901–911. doi: 10.1007/s11295-013-0596-x

Spathelf P, van der Maaten E, van der Maaten-Theunissen M, Campioli M, Dobrowolska D (2014) Climate change impacts in European forests: the expert views of local observers. Ann For Sci 71:131–137. doi: 10.1007/s13595-013-0280-1

Spies TA, Giesen TW, Swanson FJ, Franklin JF, Lach D, Johnson KN (2010) Climate change adaptation strategies for federal forests of the Pacific Northwest, USA: ecological, policy, and socio-economic perspectives. Landsc Ecol 25:1185–1199. doi: 10.1007/s10980-010-9483-0

Spittlehouse DL (2005) Integrating climate change adaptation into forest management. For Chron 81:691–695

Spittlehouse DL, Stewart RB (2003) Adaption to climate change in forest management. BCJ Ecosyst Manag 4:1–11

Stafford Smith M, Horrocks L, Harvey A, Hamilton C (2011) Rethinking adaptation for a 4 degrees C world. Philos Transact A Math Phys Eng Sci 369:196–216

Stainforth DA, Allen MR, Tredger ER, Smith LA (2007) Confidence, uncertainty and decision-support relevance in climate predictions. Philos Trans R Soc A Math Phys Eng Sci 365:2145–2161. doi: 10.1098/rsta.2007.2074

Stanturf JA, Palik BJ, Dumroese RK (2014) Contemporary forest restoration: a review emphasizing function. For Ecol Manag 331:292–323

Steenberg JWN, Duinker PN, Bush PG (2011) Exploring adaptation to climate change in the forests of central Nova Scotia, Canada. For Ecol Manag 262:2316–2327. doi: 10.1016/j.foreco.2011.08.027

Stephens M, Pinkard L, Keenan RJ (2012) Plantation forest industry climate change adaptation handbook. Australian Forest Products Association, Canberra

Tacconi L, Moore PF, Kaimowitz D (2007) Fires in tropical forests—what is really the problem? Lessons from Indonesia. Mitig Adapt Strateg Glob Chang 12:55–66. doi: 10.1007/s11027-006-9040-y

Temperli C, Bugmann H, Elkin C (2012) Adaptive management for competing forest goods and services under climate change. Ecol Appl 22:2065–2077

Thackway R, Cresswell ID (1992) Environmental regionalisations of Australia: a user-oriented approach. Environmental Resources Information Network, Canberra

Thomalla F, Downing T, Spanger-Siegfried E, Han GY, Rockstrom J (2006) Reducing hazard vulnerability: towards a common approach between disaster risk reduction and climate adaptation. Disasters 30:39–48. doi: 10.1111/j.1467-9523.2006.00305.x

Thomson-Reuters (2014) Web of Science. http://thomsonreuters.com/thomson-reuters-web-of-science/ . Accessed 21 Aug 2014

Thuiller W, Albert C, Araújo MB, Berry PM, Cabeza M, Guisan A, Hickler T, Midgley GF, Paterson J, Schurr FM, Sykes MT, Zimmermann NE (2008) Predicting global change impacts on plant species’ distributions: future challenges. Perspect Plant Ecol Evol Syst 9:137–152. doi: 10.1016/j.ppees.2007.09.004

Toffler A (1970) Future shock. Bantam, Toronto

Tompkins EL, Adger WN, Boyd E, Nicholson-Cole S, Weatherhead K, Arnell N (2010) Observed adaptation to climate change: UK evidence of transition to a well-adapting society. Glob Environ Chang Hum Policy Dimens 20:627–635. doi: 10.1016/j.gloenvcha.2010.05.001

Urwin K, Jordan A (2008) Does public policy support or undermine climate change adaptation? Exploring policy interplay across different scales of governance. Glob Environ Chang Hum Policy Dimens 18:180–191. doi: 10.1016/j.gloenvcha.2007.08.002

Van Damme L (2008) Can the forest sector adapt to climate change? For Chron 84:633–634

van Dijk AIJM, Keenan RJ (2007) Planted forests and water in perspective. For Ecol Manag 251:1–9. doi: 10.1016/j.foreco.2007.06.010

Versini PA, Velasco M, Cabello A, Sempere-Torres D (2013) Hydrological impact of forest fires and climate change in a Mediterranean basin. Nat Hazards 66:609–628. doi: 10.1007/s11069-012-0503-z

Vignola R, Locatelli B, Martinez C, Imbach P (2009) Ecosystem-based adaptation to climate change: what role for policy-makers, society and scientists? Mitig Adapt Strateg Glob Chang 14:691–696. doi: 10.1007/s11027-009-9193-6

Vihervaara P, D’Amato D, Forsius M, Angelstam P, Baessler C, Balvanera P, Boldgiv B, Bourgeron P, Dick J, Kanka R, Klotz S, Maass M, Melecis V, Petrik P, Shibata H, Tang JW, Thompson J, Zacharias S (2013) Using long-term ecosystem service and biodiversity data to study the impacts and adaptation options in response to climate change: insights from the global ILTER sites network. Curr Opin Environ Sustain 5:53–66. doi: 10.1016/j.cosust.2012.11.002

von Detten R, Faber F (2013) Organizational decision-making by German state-owned forest companies concerning climate change adaptation measures. For Policy Econ 35:57–65. doi: 10.1016/j.forpol.2013.06.009

Walker B, Meyers JA (2004) Thresholds in ecological and social-ecological systems: a developing database. Ecology and Society 9 (2)

Walker B, Salt D (2012) Resilience practice: engaging the sources of our sustainability. Island Press, Washington, DC

Wang T, Campbell EM, O’Neill GA, Aitken SN (2012) Projecting future distributions of ecosystem climate niches: uncertainties and management applications. For Ecol Manag 279:128–140. doi: 10.1016/j.foreco.2012.05.034

Wellstead A, Rayner J, Howlett M (2014) Beyond the black box: forest sector vulnerability assessments and adaptation to climate change in North America. Environ Sci Pol 35:109–116. doi: 10.1016/j.envsci.2013.04.002

Westerling AL, Gershunov A, Cayan DR, Barnett TP (2002) Long lead statistical forecasts of area burned in western US wildfires by ecosystem province. Int J Wildl Fire 11:257–266. doi: 10.1071/wf02009

Westerling AL, Hidalgo HG, Cayan DR, Swetnam TW (2006) Warming and earlier spring increase western U.S. forest wildfire activity. Science 313:940–943. doi: 10.1126/science.1128834

White A, Hatcher J, Khare A, Liddle M, Molnar A, Sunderlin WD (2010) Seeing people through the trees and the carbon: mitigating and adapting to climate change without undermining rights and livelihoods. Social dimensions of climate change: equity and vulnerability in a warming world: 277–301

Wilby RL, Dessai S (2010) Robust adaptation to climate change. Weather 65:180–185. doi: 10.1002/wea.543

Williams J (2013) Exploring the onset of high-impact mega-fires through a forest land management prism. For Ecol Manag 294:4–10. doi: 10.1016/j.foreco.2012.06.030

Williams JE (2000) The biodiversity crisis and adaptation to climate change: a case study from Australia’s forests. Environ Monit Assess 61:65–74. doi: 10.1023/a:1006361917359

Williams JT (2004) Managing fire-dependent ecosystems: we need a public lands policy debate. Fire Manag Today 64:6–11

Wintle BA, Bekessy SA, Keith DA, van Wilgen BW, Cabeza M, Schroder B, Carvalho SB, Falcucci A, Maiorano L, Regan TJ, Rondinini C, Boitani L, Possingham HP (2011) Ecological-economic optimization of biodiversity conservation under climate change. Nat Clim Chang 1:355–359. doi: 10.1038/nclimate1227

Wu HX, Ying CC (2004) Geographic pattern of local optimality in natural populations of lodgepole pine. For Ecol Manag 194:177–198. doi: 10.1016/j.foreco.2004.02.017

Yousefpour R, Jacobsen JB, Meilby H, Thorsen BJ (2014) Knowledge update in adaptive management of forest resources under climate change: a Bayesian simulation approach. Ann For Sci 71:301–312. doi: 10.1007/s13595-013-0320-x

Yousefpour R, Jacobsen JB, Thorsen BJ, Meilby H, Hanewinkel M, Oehler K (2011) A review of decision-making approaches to handle uncertainty and risk in adaptive forest management under climate change. Ann For Sci 69:1–15. doi: 10.1007/s13595-011-0153-4

Zhao D, Wu S, Yin Y (2013) Responses of terrestrial ecosystems’ net primary productivity to future regional climate change in China. PLoS ONE 8:e60849. doi: 10.1371/journal.pone.0060849

Zhou GY, Wei XH, Wu YP, Liu SG, Huang YH, Yan JH, Zhang DQ, Zhang QM, Liu JX, Meng Z, Wang CL, Chu GW, Liu SZ, Tang XL, Liu XD (2011) Quantifying the hydrological responses to climate change in an intact forested small watershed in Southern China. Glob Chang Biol 17:3736–3746. doi: 10.1111/j.1365-2486.2011.02499.x

Zimmermann NE, Yoccoz NG, Edwards TC, Meier ES, Thuiller W, Guisan A, Schmatz DR, Pearman PB (2009) Climatic extremes improve predictions of spatial patterns of tree species. Proc Natl Acad Sci 106:19723–19728. doi: 10.1073/pnas.0901643106

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Acknowledgments

Thanks to Linda Joyce for her comments on an earlier draft of this paper, to a number of anonymous reviewers for their thoughtful suggestions and to many colleagues that I have discussed these ideas with over the past five years.

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Keenan, R.J. Climate change impacts and adaptation in forest management: a review. Annals of Forest Science 72 , 145–167 (2015). https://doi.org/10.1007/s13595-014-0446-5

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SYSTEMATIC REVIEW article

The effect of forest management options on forest resilience to pathogens.

• 1 Social, Economic and Geographical Sciences Group, James Hutton Institute, Aberdeen, United Kingdom
• 2 Department of Geography and Sustainable Development, University of St Andrews, St Andrews, United Kingdom
• 3 School of Natural Sciences, Bangor University, Bangor, United Kingdom
• 4 Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom
• 5 Department of Mathematics and Statistics, University of Strathclyde, Glasgow, United Kingdom
• 6 Faculty of Natural Sciences, University of Stirling, Glasgow, United Kingdom
• 7 Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, United Kingdom
• 8 Warwick Business School, University of Warwick, Coventry, United Kingdom

Invasive pathogens threaten the ability of forests globally to produce a range of valuable ecosystem services over time. However, the ability to detect such pathogen invasions—and thus to produce appropriate and timely management responses—is relatively low. We argue that a promising approach is to plan and manage forests in a way that increases their resilience to invasive pathogens not yet present or ubiquitous in the forest. This paper is based on a systematic search and critical review of empirical evidence of the effect of a wide range of forest management options on the primary and secondary infection rates of forest pathogens, and on subsequent forest recovery. Our goals are to inform forest management decision making to increase forest resilience, and to identify the most important evidence gaps for future research. The management options for which there is the strongest evidence that they increase forest resilience to pathogens are: reduced forest connectivity, removal or treatment of inoculum sources such as cut stumps, reduced tree density, removal of diseased trees and increased tree species diversity. In all cases the effect of these options on infection dynamics differs greatly amongst tree and pathogen species and between forest environments. However, the lack of consistent effects of silvicultural systems or of thinning, pruning or coppicing treatments is notable. There is also a lack of evidence of how the effects of treatments are influenced by the scale at which they are applied, e.g., the mixture of tree species. An overall conclusion is that forest managers often need to trade-off increased resilience to tree pathogens against other benefits obtained from forests.

Introduction

Invasive species present significant threats to natural and planted forests ( Wingfield et al., 2015 ; Liebhold et al., 2017 ; Muzika, 2017 ), and can, in combination with climate change, create “mega disturbances” which disrupt forests worldwide ( Millar and Stephenson, 2015 ), leading to large ecological, economic, and social losses ( Hill et al., 2019 ). While invasive species research often focuses on animal and plant invasions, forest ecosystems are also threatened by invasive microbial pathogens. Pathogens have the potential to disrupt timber and non-timber benefits provided by forests, and the need for a coordinated effort to tackle such invasive species is being increasingly recognized ( Wingfield et al., 2015 ). In this context, to be considered invasive a pathogen does not need to be non-native to the region, but rather through an increase in its abundance produce a widespread negative impact on a given ecosystem ( Warren, 2007 ; Carey et al., 2012 ).

Managing invasive pathogens presents unique challenges not associated with controlling invasive plants and animals, including insects. The cryptic nature of infection by pathogens, particularly at the beginning of their life cycles, means that many invasions remain undetected until trees become symptomatic, by which time the pathogen is often already widespread ( Liebhold et al., 2017 ; Muzika, 2017 ). Even after infection has been detected, identification of the causal pathogen is normally reliant on examination of spores and/or DNA sequencing. As a result, many pathogens have remained unidentified or misidentified, restricting our capacity to manage invasions effectively ( Wingfield et al., 2015 , 2017 ). Genetic variation amongst microbial pathogens is greater than even that found between the plant and animal kingdoms, and as such these pathogens have highly varied life histories. This not only creates challenges in designing control measures for pathogens as a general invasive threat, but also in tackling individual pathogens, which can present unfamiliar life history traits ( Wingfield et al., 2017 ). These complex and often still unknown life histories, as well as their potential for relatively rapid evolution, restrict our ability to predict which pathogens will become invasive, and how any invasion will progress ( Ghelardini et al., 2017 ).

Tree pathogens threaten the ability of forests to deliver ecosystem services over the long-term. The importance of phytosanitary measures, such as quarantine, to reduce the risk of invasive tree pathogens reaching a country or a given forest have long been recognized ( Wingfield et al., 2015 ). However, as rotation lengths from establishment to harvest of a forest tree crop generally last for several decades, the high rate of arrival of new pathogen species to locations around the world means that any newly established crop may potentially be subject to many new pathogens before it reaches maturity. This poses a particular challenge for forest managers. So far, management responses have largely been restricted to reactive measures taken after the presence of a given pathogen has been detected, by which time economic and ecological damage costs can rarely be avoided. This restriction on the ability of forest managers to respond until a specific pathogen has been detected raises the important question of whether and how forests should be planned and managed to maximize their resilience to the threat of future unknown pathogens.

To help address this challenge, a recent extension of epidemiological modeling (“epi-economic modeling”) has linked the economics of forest management practices to the impacts of tree pathogens across a range of primary and secondary infection rates and damage costs ( Macpherson et al., 2017a , b , 2018 ). This approach is based on an epidemiological paradigm ( Kleczkowski et al., 2019 ), whereby the population of trees is divided between healthy and susceptible individuals, and infected individuals. Mathematical models capturing the infection process can take different forms but the simplest equation is

with S ( t ) denoting the number of still healthy but susceptible trees, r p and r s the rate of primary and secondary infection, respectively, I (t) currently infected trees within the unit, and d I /d t the rate of appearance of new infections ( Brassett and Gilligan, 1988 ).

The fundamental difference between primary and secondary infection is epidemiological. Primary infection is the invasion of the population of trees within the forest management or landscape-patch unit from an external source, e.g., an infected population of trees in another unit, and requires management at the boundary or beyond. Primary infections can also occur from a reservoir of inoculum in alternative hosts, or in soil or dead plant material when sites are replanted. Thus, the source is “external” to the population under threat albeit occupying the same parcel of land. Secondary infection is transmission from currently infected trees within the unit's population to its susceptible trees, driven by multiplication, dispersal, and infection of inoculum. Hence management activity in that forest unit can influence secondary infection and reduce epidemic spread. The rates of primary and secondary infections in Equation (1) capture the whole range of factors, including the susceptibility of individual trees to infection as well as the dispersal characteristics of the pathogen.

Fundamental to this paper is the recognition that resilience of a forest is linked to its response to invasions by forest pathogens. This response, in turn, is influenced by the management practices aimed at the prevention of such invasions, their control and, if control is unsuccessful, the mitigation of their effects. The modeling framework described above and its extensions, have successfully been used in describing spread and control of tree pathogens in forests ( Macpherson et al., 2017a , 2018 ). However, application of such an approach to inform forest managers about how to increase forest resilience against future pathogen threats requires empirical evidence about the effects of forest management options on tree pathogen primary and secondary infection rates, and rates of forest recovery.

The key question in ecological and economic applications of the concept of resilience is “resilience of what, to what?” ( Walker et al., 2010 ; Matsushita et al., 2018 ). The focus of this study is forests that are managed predominantly for timber production and in this case the most relevant concept of resilience is the one termed “engineering resilience,” which comprises two main components: “resistance” to the initial impact of a disturbance agent (in this case the invasion of a tree pathogen) and “recovery” toward the previous state or functioning of the forest ecosystem ( Pimm, 1984 ; Holling, 1996 ; Grimm and Wissel, 1997 ; Newton and Cantarello, 2015 ). In the literature reviewed in our study, the measured response variables that give the best indication of “resistance” (at the scale of the forest ecosystem or stand) were level of individual tree infection or mortality, and the best indicators of “recovery” were rates of natural regeneration or stand-level growth rates of all surviving or subsequently established trees. We assume throughout the paper that managers are concerned with a single spatially contiguous unit of forest, because this is the scale at which most studies are carried out. However, the size of this unit may be highly variable, and we focus only on net increases or decreases in resilience. The majority of studies available for our review assumed that provisioning of timber was the ecosystem service of greatest importance resulting from the state or functioning of the forest.

The impacts of forest management on tree pathogens have been the subject of many recent reviews. Each has tended to focus on a single pathogen, such as white pine blister rust ( Cronartium ribicola ) ( Schoettle and Sniezko, 2007 ; Hunt et al., 2010 ; Ostry et al., 2010 ; Zeglen et al., 2010 ), Phytophthora ramorum ( Valachovic et al., 2010 ), ash dieback ( Hymenoscyphus fraxineus ) ( Pautasso et al., 2013 ) or dothistroma needle blight ( Dothistroma septosporum and D. pini ) ( Bulman et al., 2016 ). As a result, the findings have been highly variable, with recommendations largely dependent on the pathogen considered. Alternatively, pathogens have been considered alongside insect pests ( Waring and O'Hara, 2005 ; Liebhold et al., 2017 ; Muzika, 2017 ) or other general threats to forest ecosystems ( Jactel et al., 2009 , 2017 ). Reviews focused on broader forest resistance to the threat of tree pathogens have been limited to considering only the effect of tree species mixtures on the spread of and damage caused by pathogens ( Pautasso et al., 2005 ; Prospero and Cleary, 2017 ) or of more general principles of interactions and ecosystems services ( Boyd et al., 2014 ). Overall, the local context of the forest and pathogen have been recognized as important in directing management responses.

The objective of the current study is to synthesize the evidence for the effect of forest management options on forest resilience to tree pathogens. The scope is broad, including all of the main categories of forest management variables and all tree pathogen species. However, animal pests, invasive plants and abiotic threats such as fire were excluded. A second objective is to forge an explicit link between forest resilience, forest design, or silvicultural management practices and epi-economic modeling grounded in plant and tree epidemiology ( Macpherson et al., 2017a , b , 2018 ). Thus, we seek to assess the empirical evidence for the effect of each forest management option on the three key elements of primary infection, secondary infection and subsequent forest recovery, in order to inform forest management decision making to increase forest resilience, and to identify the most important evidence gaps to motivate future research.

We carried out a literature review using a systematic search method to identify published sources of empirical data on the relationship between forest management and resilience to tree pathogens. We conducted an initial search of the peer-reviewed literature through Web of Science, using search strings to identify papers on all of forest management, pests, pathogens or disease, and resilience, excluding medical papers and those concerned with food supply, using the Boolean search string of:

TS = (((( * forest * OR wood * OR tree * ) AND (manage * )) OR silvicult * ) AND (pest * OR disease * OR pathogen * ) AND (exposure OR resist * OR recover * OR spread OR risk OR suscept * OR transmit * OR dispers * OR infect * ) NOT (medicin * OR clinic * OR pharma * OR foodborne OR food-borne OR mycorrhizal OR biomedic * OR mosquito OR tick OR lyme * OR malaria * )) NOT SO = (medicin * OR clinic * OR pharma * OR biomedic * ) NOT WC = (medicin * OR clinic * OR pharma * OR biomedic * )

This search (run on 27/06/2017) returned 3,534 papers. The papers were screened first by title, then abstract, and finally full text to identify papers reporting original empirical data on the effects of forest management on tree diseases caused by pests or pathogens, which retained 599 papers. We then excluded papers that only covered tree pests (362 papers), were only concerned with tropical forests (85 papers) or orchards (235 papers), were concerned with tree breeding (74 papers), or were entirely review (23 papers) or theoretical modeling (21 papers) studies (note papers may be present in more than one category). Removal of tree pests also included removing papers concerning insect vectors, because in the majority of cases the distinction between direct damage and vectoring of a pathogen could not be determined. This procedure retained 81 papers. As many forest management actions are not reported in the published literature, searches were also run in TREESEARCH, the research portal for the US Forest Service, using the following search string:

(disease OR fung * OR pathogen OR bacteri * OR oomycete OR virus) AND (((tree OR forest * OR wood) AND manage * ) OR silvicult * )

and the UK Forestry Commission website, using the search string:

disease fung * pathogen bacteria * oomycete virus

Restrictions on the search terms for each search engine prevented identical searches from being carried out. The search in TREESEARCH returned 158 documents, of which 12 were identified as relevant and containing data. The Forestry Commission website returned 58 documents, of which three were identified as relevant and containing data. Together with literature identified from the reference lists of retained papers and identified reviews (nine papers), and further search terms added to account for fertilizer application (four papers), the final reference list contained 114 papers and reports. This list was further refined to include only papers whose reliability, robustness and applicability to forest management could be assured. Studies which were purely descriptive, lab-based or considered only pathogen presence, rather than impact, were excluded. The remaining 109 papers included within the review were scored for strength of evidence based on whether they were correlative or experimental, and whether single or multiple sites had been considered, within single or multiple forests.

We organized papers by management technique, treating each technique reported within a single paper independently, and then by pathogen type. We have included a broad range of management options, including forest design planning, site preparation for forest establishment, tree species diversity, silvicultural system and individual silvicultural actions. These categories were not pre-determined but were decided through reading the papers.

To assess the outcome of each management technique we classified the results of each study as strong positive or strong negative (relationship observed in all sites within the study), weak positive or weak negative (relationship observed in at least one site within the study, with no sites showing the opposite relationship), no relationship, or mixed (both positive and negative relationships observed across sites). A technique was therefore considered to have an overall positive or negative impact where multiple studies, or a robust single study across multiple forests, found the same result, and there were no robust studies reporting a contradictory result. If studies reported contradicting results, we considered the outcome of this technique to be mixed unless the results were weighted heavily in one direction, and the contradicting study was considered to be of low robustness. Where only a limited number of studies was available this was identified as a weakness in our conclusions. A fuller description of this critical appraisal of the studies is provided in the Supplementary Material , together with the full outputs of the search and critical appraisal in the Table 1 .

Table 1 . Overview of coverage of identified papers.

The large variation in tree species, pathogens, and management techniques considered, as well as limited reporting of the particulars of management, prevented us from conducting a formal meta-analysis.

General Trends

Our review of the literature revealed a clear bias toward a small number of highly damaging pathogens. Studies into Armillaria and Phytophthora species comprised 38% of all studies identified (17 and 21%, respectively), and we found no studies on the effects of forest management on bacteria or viruses. Studies mainly covered commercially valuable host tree species, with equal coverage of conifers and broadleaves ( Table 1 ).

A geographical bias was also evident, with 59% of studies based in North America, and California and Oregon coastal forests alone accounting for 24%. The majority of the remaining papers originate from Europe (29%), with eight papers from Oceania and two from Asia. Studies reporting only from natural tropical forests had previously been excluded. Only a single paper ( Cleary et al., 2013 ) reported results from more than one region ( Table 1 ).

The response variables most commonly reported were mortality, disease incidence, and disease severity. The only indicator of forest recovery (defined in the section Introduction) that was widely reported was of subsequent tree growth rate, though this was often only measured over the short-term. There was minimal reporting of rates of tree natural regeneration. Studies generally reported outcomes in terms of symptoms of forest disease, and few papers considered the mechanisms connecting forest management to these outcomes. The distribution of studies amongst each forest management variable and each response variable is summarized in Table 2 .

Table 2 . Overview of published evidence of effects of forest management on resilience to tree diseases.

Identification and Management of Sources of Primary Infection

As explained above, the concept of primary infection [cf. Equation (1)] captures the pathways by which the pathogen enters the forest unit of interest. These primary infections can occur from other forest units, for example by wind or water movement of inoculum, from alternative hosts, by movement on machinery and other human-mediated activities, or by transmission from soil inoculum.

Connectivity

The importance of connectivity for the conservation of forest ecosystems at a landscape scale is well-recognized ( Lindenmayer et al., 2006 ). However, connectivity can increase the risk of transmission of infection from one forest patch or unit to another, including from outside the region of interest. For tree pathogens connectivity does not just refer to spatial proximity, but also any connection through which inoculum may spread to a forest unit, such as via streams, wind, fog, animal (e.g., insects, fur, feathers) or human vectors (e.g., vehicles, recreation). The scale at which connectivity is important also varies with dispersal mechanism, and can be large in the case of flying animal and vehicle vectors. These “least cost” (resistance), but not necessarily shortest-distance, pathways have been shown to be important in models accounting for the spread of pathogens ( Ellis et al., 2010 ).

The impacts of connectivity on tree diseases have predominantly been studied in coastal forests of California and Oregon (USA). Total forest area within a landscape, correlated with connectivity, predicted increases in incidence ( Meentemeyer et al., 2008a ) and severity of P. ramorum in Notholithocarpus densiflorus (tanoak) ( Haas et al., 2011 ) and Umbellularia californica (California bay laurel) ( Condeso and Meentemeyer, 2007 ; Meentemeyer et al., 2008a , b ; Haas et al., 2011 ). Disease was considered only in these species because they represent the most prevalent hosts for P. ramorum within this landscape. Phytophthora ramorum incidence increased closer to streams in one site, suggesting that streams are also an important connectivity pathway for dispersal of this pathogen, though this relationship appears to depend on site topography and fog movement ( Peterson et al., 2014 ). Connectivity through human vectors was related to higher concentrations of P. ramorum being isolated in soil from sites surrounded by larger human populations ( Cushman and Meentemeyer, 2008 ), and increased mortality of Chamaecyparis lawsoniana (Port Orford cedar) caused by Phytophthora lateralis was found in sites intersected by a road ( Jules et al., 2002 ). Phytophthora lateralis has been isolated from water used to wash vehicles and boots, providing further evidence of the importance of human vectors to the spread of this pathogen ( Goheen et al., 2012 ). Within California and Oregon coastal forests, black stain root disease ( Leptographium wageneri ) is also concentrated at the roadside ( Hessburg, 2001 ).

Forest connectivity via spatial proximity ( Condeso and Meentemeyer, 2007 ; Meentemeyer et al., 2008a ; Ellis et al., 2010 ; Haas et al., 2011 ), streams ( Peterson et al., 2014 ; Havdova et al., 2017 ), or roads ( Hessburg, 2001 ; Jules et al., 2002 ; Goheen et al., 2012 ) shows a consistent positive relationship with disease incidence and severity compared with less well-connected forests. However, the limited geographical range of these studies and their predominant focus on pathogen spread through soil restricts their applicability to other systems. There is also little mention of the effect of land cover in the matrix between forest patches that could affect pathogen dispersal. When addressing the increased risk of pathogen infection due to high connectivity, forest managers must also balance the extensive benefits that connected forests can have for biodiversity and some ecosystem services against increased vulnerability to disease ( Lindenmayer et al., 2006 ). Future studies should identify and quantify pathogen transmission along different types of pathway connecting forest units and via different vectors in order to assess risks. This should help selection of management strategies to reduce the risk of primary infection of forest units.

Previous Land Use

Many tree pathogens, in particular root rots, can persist in soils following tree felling. Siting new plantations on previously forested sites may therefore increase the risk of infection due to high inoculum load in the soil. Here the soil acts as an “external” reservoir of inoculum for primary infection to initiate an epidemic in a newly planted tree population. However, research into the effects of previous land use is limited, due to the relative rarity of studies into forests established on previously non-forest land.

Naturally occurring U. californica trees on former grassland sites within Quercus forests in northern California had lower incidence of P. ramorum than U. californica growing in long-term forest areas ( Meentemeyer et al., 2008a ). However, this relationship was not reflected in Italian Abies alba (silver fir) plantations, where Heterobasidion annosum infection rate was significantly higher in forests established on former pastureland. Although A. alba planted on former pastureland was expected to be exposed to lower inoculum load, these trees were less healthy due to exposure to adverse environmental conditions resulting from previous intensive land use, potentially increasing susceptibility to disease ( Puddu et al., 2003 ).

While previous land use could be expected to affect forest resilience to tree diseases, research on this is rare, and the findings amongst published studies are not consistent. This is likely to be due to the large variation in previous land use types, and particulars of previous land management, amongst the studies. However, such research is likely to increase in relevance for rotational forest systems, where the previous species planted in the unit may be considered. In some countries, including the UK, new forests are also being planted on land not forested in recent history in order to increase carbon capture in response to climate change, and natural tree regeneration is occurring due to abandonment of agricultural land ( Poyatos et al., 2002 ).

Site Preparation

Site preparation methods can either introduce pathogens into an area where they were not previously found or reduce forest resistance to primary infection and hence increase the initiation of local disease spread. Previously felled sites contain remnant stumps, root fragments and brash, which may be a source of primary infection through spread of pathogens over time (from a previous tree population to a new one). Nonetheless, stumps resulting from thinning or partial cutting can also act as a source of secondary infection within the current tree population. Although this coarse woody debris is important for forest biodiversity more generally ( Hartley, 2002 ), it acts as a reservoir for many pests and pathogens, increasing exposure of newly established trees to inoculum. Stumps can also provide a nutrient source for inoculum of pathogens with saprotrophic activity. In response to this risk, site preparation may include stump removal or chemical treatment, in some cases accompanied by removal of part of the root system through raking. The origin of stumps can also be important for identifying the risks posed, with clearcut stumps having lower infection rates than stumps resulting from thinning ( Bendz-Hellgren and Stenlid, 1998 ). Burning presents an alternative option to remove woody debris or reduce pathogen survival, but has other risks and environmental costs, such as to habitat quality or native fauna, or it can in fact increase disease incidence in the case of Rhizina undulata ( Wingfield and Swart, 1994 ). In some cases site preparation also includes application of fertilizer, which may reduce impacts of pathogens on tree health through increasing tree nutrient concentrations, especially of calcium and magnesium ( Anglberger and Halmschlager, 2003 ; Halmschlager and Katzensteiner, 2017 ). However, fertilizer application (especially of nitrogen and phosphorus) that increases tree growth rate can lead to nutrient inbalances that increase susceptibility to pathogens ( Jactel et al., 2009 ).

Root rots have the highest potential for management through stump treatment and have unsurprisingly been the subject of the greatest number of studies. Methods of stump treatment may be physical or chemical. Infection of forest stands by H. annosum has long been known to be increased by any tree felling resulting in cut stumps that are susceptible to colonization from air-borne basidiospores ( Woodward et al., 1998 ). The most extensive study of stump removal incorporated five sites from Canada and Scandinavia subject to infection by the conifer root rot pathogens H. annosum sensu lato ( s.l .), Armillaria ostoyae and laminated root rot ( Phellinus sulphurascens ). The severity of infection and its contribution to mortality were monitored in stands that had been subject to removal of stumps, either as part of the whole tree or in a separate operation following felling, with raking to remove larger roots occurring in one site, compared with controls where no stump removal took place ( Cleary et al., 2013 ). Stump removal was clearly associated with reduced disease incidence and tree mortality up to 21–50 years after treatment. One of these sites was then studied in more detail by Morrison et al. (2014) , who confirmed that over 40 years after treatment, stump removal had reduced the rate of mortality in the next rotation of trees by 14% across all species. Notably, for Pseudotsuga menziesii (Douglas fir), Pinus contorta var. latifolia (lodgepole pine), Larix occidentalis (western larch), Thuja plicata (western red cedar), and Picea engelmannii (Engelmann spruce), stump removal reduced the mortality rate due to A. ostoyae and completely eliminated the occurrence of mortality in P. menziesii due to P. sulphurascens . These findings support those of a previous study of P. menziesii further south in Washington State and Oregon, where mortality due to P. sulphurascens was significantly reduced by pre-planting stump removal ( Thies and Westlind, 2005 ).

There has been a long history of incidence of H. annosum in the plantations of Pinus sylvestris (Scots pine) and Pinus nigra ssp. laricio (Corsican pine) in Thetford Forest, UK. A series of experiments showed that colonization of stumps by air-borne basidiospores of H. annosum can be greatly reduced by stump treatment with spores of Phlebiopsis gigantea , a non-pathogenic basidiomycete. However, a series of long-term experiments have shown that only stump removal achieves adequate reduction in mortality into the second plantation rotation ( Gibbs et al., 2002 ). The importance of removing stumps was further supported in studies of P. sylvestris infected by H. annosum in Sweden, where infection rate was higher in trees closer to infected stumps ( Swedjemark and Stenlid, 1993 ). In contrast, in New Zealand Pinus radiata plantations infected by Armillaria novae-zelandiae , while inoculum load in stumps was high, this did not lead to greater infection within the forest after 19 years compared with forests where stumps were removed ( Hood et al., 2002 ; Hood and Kimberley, 2009 ).

In addition to retained stumps, root fragments from felled trees can act as reservoirs of pathogen inoculum. Few studies have reported beneficial effects of root removal, although Shaw et al. (2012) found that greater intensity or thoroughness of removal of roots that acted as a source of A. ostoyae inoculum did significantly reduce the incidence of infection and resultant mortality in Pinus ponderosa after 35 years, though the study concluded that its benefits are unlikely to exceed its costs. In contrast, several studies have reported increases in infection following root removal. Negative impacts of mechanical root removal treatments can occur through increasing the dispersal of pathogen inoculum. Root raking has been found to move infected root fragments closer to the soil surface, although this was not associated with increased infection rates ( Morrison et al., 1988 , 2014 ). The incidence of western gall rust was found to be positively associated with sites that had undergone a variety of methods of mechanical site preparation to disrupt slash, forest floor and mineral soil layers, compared with control sites ( Roach et al., 2015 ). Similar results were observed in Castanea dentata (American chestnut) infected by chestnut blight ( Cryphonectria parasitica ). In a study of plantations on reclaimed mine land in Ohio, USA, the site preparation treatments of deep ripping to 1 m depth resulted in a higher incidence of chestnut blight cankers on seedlings than in those plots plowed and disked to 30 cm depth, though this still exceeded the incidence of cankers for trees in control plots ( Bauman et al., 2014 ).

Prescribed or natural fire reduces pre-planting inoculum load through either burning of stumps, root fragments and woody debris, or through killing of the pathogen due to high temperatures. However, results from burning are not consistent. Naturally occurring fires in Californian coastal redwood and mixed-evergreen forests led to reduced isolation rates of P. ramorum in symptomatic trees for 1 and 2 years following fire, however incidence of the pathogen increased by the second year, associated with the number of surviving symptomatic U. californica trees which acted as an inoculum reservoir ( Beh et al., 2012 ). A prescribed burn treatment in a Pinus palustris (longleaf pine) forest in South Carolina, USA, was associated with increased mortality through H. annosum after 8–10 years, linked to reductions in tree health caused by the fire ( Cram et al., 2010 ). Varied burning regimes in conifer forests in Ontario, Canada, had no impact on Armillaria sp. root rot ( Whitney and Irwin, 2005 ).

Fertilizer application has mixed impacts on disease severity. Increased damage by twisting rust fungus ( Melampsora pinitorqua ) was found on Pinus pinaster (maritime pine) that had been fertilized with phosphorus compared with no fertilizer controls ( Desprez-Loustau et al., 2016 ). However, fertilization of Picea abies (Norway spruce) did show a reduction in severity of infection by Sirococcus shoot blight ( Sirococcus conigenus ), linked to improved tree health ( Anglberger and Halmschlager, 2003 ; Halmschlager and Katzensteiner, 2017 ). In P. menziesii seedlings fertilization with potassium and nitrogen had no impact on mortality due tolaminated root rot ( Phellinus weirii ) ( Thies et al., 2006 ), and potassium, nitrogen and sulfur fertilizers had no impact on Armillaria spp. root disease in mixed conifer forests in Oregon ( Filip et al., 2002 ).

Overall, removal or treatment of tree stumps as a source or receptor of pathogen inoculum has a positive effect on forest resilience to tree disease, through reduced infection of trees retained on the site or newly planted trees. However, studies are concentrated on root rots. Stumps, and other dead wood material, are also known to be important in survival of populations of a number of invertebrate forest pests, and there is an evidence gap about their significance as a source of inoculum of a wider range of pathogens with airborne spores that infect the shoots of trees. We found that studies of root fragment removal and burning give more mixed results and are under-researched. A future research priority is to assess the trade-offs between reducing inoculum levels using such treatments and the damage they cause to retained trees (e.g., through wounding), which can increase their susceptibility to infection.

Management of Sources of Secondary Infection

Secondary infection [cf. Equation (1)] refers to transmission of a pathogen between trees within a region of interest (forest unit). Secondary infection therefore captures the direct transmission component of epidemics that depends upon the number of currently infected individuals. Although this typically relates to an outbreak situation between trees of a similar age, of particular concern for forest management is secondary infection from mature trees to seedlings, often planted to form the crop in the next forest rotation. Actions that increase environmental stress on a tree, thus reducing its vigor, are also likely to increase the rate of secondary infection.

Tree Species Mixture and Diversity

Effects of tree species mixture, i.e., planting two or more species rather than a monoculture, or increasing tree species diversity, i.e., through the number of species planted together or as an indirect result of other silvicultural actions, on forest resilience to tree diseases have been extensively studied, with good coverage of both tree and pathogen species in sites across Europe and North America. Tree species diversity effects have been the subject of recent review papers. These recognize that greater diversity is associated with decreased tree mortality caused by pests and pathogens, identifying reduced access to hosts and increased distance between hosts as potential mechanisms for reducing secondary transmission as an epidemic progresses ( Pautasso et al., 2005 ; Bauhus et al., 2017 ; Jactel et al., 2017 ; Prospero and Cleary, 2017 ), as well as potentially providing habitat for more species that deliver natural biocontrol ( Bauhus et al., 2017 ). However, such results may be context-specific ( Heybroek, 1982 ), and depend on whether the invading pathogen is a host specialist or generalist. We have included within this section observational studies of variation in pathogen incidence with tree species diversity as well as experimental studies with species mixtures. Their coverage is summarized in more detail in Tables 2 , 3 . Provenance and breeding of trees for resistance is also an important aspect of forest resilience to tree pathogens, but was outside the scope of this review.

Table 3 . Summary of studies in tree species diversity/mixture effects.

There is general agreement across studies that increases in tree species diversity are associated with an increase in forest resilience with respect to invasive pathogens. In sites across Europe, more diverse forests were associated with lower levels of disease incidence ( Nguyen et al., 2017 ). These findings are supported by experimental units of broadleaf trees in Germany, where fungal infections of the most susceptible tree species were reduced as species diversity increased ( Hantsch et al., 2014a ). This pattern was also recorded in studies in North America, where higher tree diversity was associated with lower occurrence of Fusarium sp. canker in Acer saccharum (sugar maple; Bergdahl et al., 2002 ), and higher tree species diversity was linked to a lower incidence of P. ramorum in Californian oak forests ( Haas et al., 2011 , 2016 ). Stands with higher tree diversity were also found to have lower mortality rates of P. menziesii caused by P. ramourm ( Ramage et al., 2012 ). In an experiment in Germany, planted with individual tree-scale species combinations in 5 × 5 m plots, high tree species diversity in the same plot reduced the amounts of fungal infection in trees of Quercus petraea (sessile oak; Hantsch et al., 2014a ). Only a single study contradicted these results, showing in Spain and Italy that Armillaria spp. presence and abundance in pure A. alba stands was lower than in mixed-species stands ( Oliva et al., 2009 ).

Diversity amongst clones in monocultures can also affect resilience to tree disease. Willow rust ( Melampsora epitea) causes decline in many short rotation Salix spp. (willow) crops. In an experiment in Northern Ireland, UK, McCracken and Dawson (1998) found that increasing the diversity of clones reduced mortality due to rust in the most susceptible clones only, but no further improvements in survival were seen when moving from 5- to 20-clone mixtures. Mixed-clone sites were also found to have later onset of disease during the first 4 years of growth, but showed no difference after this time ( McCracken and Dawson, 1997 ). However, following observations of a subsequent experiment over two 3-year harvesting cycles, Begley et al. (2009) found no consistent effects of mixtures on reducing M. epitea on the most susceptible Salix genotype. They concluded that any benefit of mixture planting will be dependent on there being sufficient genetic diversity between the genotypes.

An important mechanism cited for the benefit of species mixture is the dilution of trees of species susceptible to a given pathogen by individuals of non-host species. However, experimental results of this effect are variable, and the specific composition of species in a mixture is found to be important. In an experimental study in Minnesota with seedlings of six conifer and four hardwood tree species planted in three mixtures differing in the proportion of individual tree species, the relative proportion of susceptible conifers or resistant broadleaves had a significant effect on mortality associated with Armillaria sp. root infection ( Gerlach et al., 1997 ). These findings were supported by longer-term experiments in British Columbia, in which P. contorta var. latifolia had lower mortality, due predominantly to A. ostoyae , when grown in mixture with Betula papyrifera (paper birch) and T. plicata both of which have low susceptibility to this pathogen ( Morrison et al., 2014 ). However, no benefit was found when growing it in mixture with the highly susceptible host species P. menziesii . In contrast, for 30-year-old P. menziesii no reduction in root pathogen-caused mortality rate was found from growing it in mixture with non-host species. Also in British Columbia, experimental removal of naturally regenerated broadleaves B. papyrifera and Populus tremuloides (quaking aspen) generally caused a 1.5- to 4-fold increase in mortality of planted P. menziesii for 3–5 years due to A. ostoyae infection, though the effect depended on removal method ( Gerlach et al., 1997 ; Baleshta et al., 2005 ; Simard et al., 2005 ). In Southwest Lapland and in North Karelia, Finland, modeling of observational data showed that the incidence of M. pinitorqua on young P. sylvestris was greater in the presence of both Populus tremula (aspen, also a host species), and Salix spp. (willows, not known to be host species but said to be indicators of higher soil moisture and fertility) ( Mattila et al., 2001 ; Mattila, 2002 ).

There is variation amongst conifer species in their susceptibility to H. annosum butt rot, and in southern Sweden the presence of less susceptible P. sylvestris was found to decrease the incidence of this pathogen in trees of the more susceptible P. abies ( Linden and Vollbrecht, 2002 ). This effect increased notably up to a relative abundance of 50% of P. sylvestris but not above that proportion. Experimental plantings in Germany showed that, overall, tree species diversity in mixtures of 30 mono-specific 8 × 8 m sub-plots reduced the level of foliar pathogen infestation of susceptible Quercus spp. by Erysiphe alphitoides and E. hypophylla (powdery mildew) at the plot level ( Hantsch et al., 2013 ). The presence of the highly susceptible Quercus spp. increased the plot-level pathogen load but resistant species such as P. abies decreased it.

Variation in the impacts of tree diversity on resistance to tree pathogens is likely related to tree species identity in the same forest unit (on a scale from individual adjacent trees up to ca. 50 m), with tree characteristics beyond simply host or non-host being important. Indeed, this may also be the main driver of any detected effects of species diversity within forest stands. Severity of infection of Fraxinus spp. to the pathogen H. fraxineus was highest in the presence of Quercus robur (pedunculate oak) and lowest in the presence of Acer spp. and Abies spp., both non-hosts. However, this result from an observational study of forests across the Czech Republic does not prove causation by the tree species themselves, but may be linked to variation in site environments ( Havdova et al., 2017 ). In the rigorously-designed planted experiment studied by Hantsch et al. (2013) , for trees of Tilia cordata (small-leaved lime) both fungal species richness and infestation level (predominantly of Passalora microsora and Asteromella tiliae ) were reduced by tree diversity in the plot. For non-host tree species the effect of their proportion in the plot on infestation level in T. cordata varied from significantly positive (for Fagus sylvatica , European beech) to negative (for P. sylvestris and in some years for P. abies ). Similarly, infestation of the leaves of Q. petraea increased with the proportion of Fraxinus excelsior (European ash) in the plot and decreased with P. abies . In a rehabilitated bauxite mine site in Western Australia, experimental mixed planting with non-host species reduced mortality of the susceptible host tree species Banksia grandis caused by soil inoculation with the pathogen Phytophthora cinnamomi only when grown in mixture with Acacia pulchella , but not with four other non-host Acacia species ( D'Souza et al., 2004 ). The mechanism was suggested to be that mixture with A. pulchella reduced the soil inoculum level. These results provide strong evidence of the importance of tree species-identity effects.

In general, higher tree diversity improves forest resilience to tree diseases. However, a major mechanism in this effect has been found to be linked to the identity of the tree species present (i.e., species composition). Highly susceptible species show the largest reductions in pathogen presence and impact with increases in tree diversity. There is also evidence that greater benefit for such susceptible tree species can be obtained if they are mixed with trees not susceptible to the pathogen. It is important that future experiments are designed in a way that allows separation of effects due to species identity from those due to species diversity per se through careful consideration of species and mixtures tested. There would also be benefit in future studies determining the role of alternative mechanisms causing species mixture or diversity effects on pathogen infection, such as relative levels of inter- and intra-specific competition and their impacts on tree condition. While the resilience of mixed-species forests to individual host-specific tree pathogens may increase at the whole-forest ecosystem scale, the sum of components of these ecosystems are vulnerable to a larger number of tree pathogens than is the case for single-species forests. More work needs to be done to understand how the dynamics of different classes of pathogen affect the trade-off associated with the epidemiological risks and benefits of mixed cropping at different scales. Mixed-species forests generally increase the costs and complexity of management. Therefore, in reaching evidence-based forest management decisions, biological, and ecological considerations need to be combined with economic analysis that explicitly considers the multiple costs and benefits over time of alternative management responses to invasive pathogens.

Tree Establishment Under Different Silvicultural Systems

For many tree species, planting or natural regeneration under shelterwood leads to better establishment than in open conditions (e.g., after clearcutting; Raymond and Bédard, 2017 ). This form of silviculture can also be beneficial for plant ( Hannerz and Hanell, 1997 ) and bird ( King and DeGraaf, 2000 ) biodiversity. Increased vigor of trees grown in shelterwood sites may increase resistance to tree disease, however the retained canopy trees may also act as a source of inoculum.

Across studies, the relative incidence of pathogen infection between shelterwood and clearcut sites shows high variation even within sites, and between tree and pathogen species. In study locations across the USA, Pinus strobus (eastern white pine) experienced either increase ( Ostry, 2000 ), decrease ( Katovich et al., 2004 ) or no change ( Katovich et al., 2004 ) in incidence of C. ribicola when grown in shelterwood compared with clearcut sites. Across the same locations, Armillaria sp. root rot of P. strobus was less common in shelterwood than in clearcut sites ( Ostry, 2000 ). A history of clearcutting increased the incidence of Neonectria ditissima in trees of Betula spp. (birch; Ward et al., 2010 ).

Amongst selection or retention systems, the size of felling gap has been suggested to influence forest resilience to tree diseases, but it is acknowledged that this varies with tree and pathogen species. The most rigorous experimental study was carried out in a pine forest in Minnesota (USA), in which Pinus resinosa, P. strobus , and P. banksiana (red, eastern white and jack pine) were planted within felling gaps of 0.3 and 0.1 ha, within plots with evenly-spaced retained overstorey trees or in an unfelled control. Incidence of shoot blight (predominantly Diplodia pinea ) in dead seedlings was significantly less in the 0.3 ha gap treatment than in the control for both P. strobus and P. banksiana , but not for P. resinosa . In contrast, Armillaria solidipes incidence was significantly greater in one or both of the two gap sizes than the control for all three tree species. Gall rust (likely caused by Cronartium quercuum f. sp. banksianae ) was observed only in P. banksiana , and its incidence was significantly greater in the small gaps than the control ( Ostry et al., 2012 ). In no cases were any significant differences in pathogen incidence found amongst the two gap sizes and the evenly-spaced retention systems. Similar variability in response to silvicultural treatments was seen in an experimental study of Pinus radiata (Monterey pine) forest infected by Fusarium circinatum (a causal organism of pitch canker) in California. Here, incidence of the disease was greater in seedlings growing in intermediate-size (0.10 ha) gaps than in smaller (0.05 ha) or larger (0.20 ha) gaps ( Ferchaw et al., 2013 ). However, gap size was not found to affect the odds of seedling survival. Tree position with respect to a long-term forest edge has been found to influence crown dieback caused by the pathogen H. fraxineus in retained trees of F. excelsior in an observational study following a tree harvest in Estonia ( Rosenvald et al., 2015 ). The level of dieback and mortality resulting from H. fraxineus was less for trees adjacent to the pre-existing forest edge than those in the center of the harvest gap. Such effects of tree position need to be considered in studies of other pathogens and locations.

Understanding of the impacts of the range of alternative silvicultural systems on forest resilience to tree diseases is poor, with relatively few studies. It is not surprising that the available evidence shows little consistency across pathogen and tree species, given the wide variation in their transmission pathways and modes of infection. Transmission to seedlings of pathogens that spread via root contact is expected to be greater in shelterwood or other even-retention or small-gap selection systems. This effect may be less so for pathogens that disperse via airborne or water dispersal. Similarly, amongst trees, light-demanding species that show greatest vigor in open clearcut or large gap sites are likely to be less susceptible to infection in such site conditions. In contrast, more shade-tolerant species may be less susceptible in shelterwood or small gap systems where they are less vulnerable to environmental stress. However, such deductions, and in particular the net effects of any trade-offs between the effect of site conditions on the rate of pathogen infection and on the level of seedling vigor, need further empirical research. It can be expected that the net outcome will vary amongst tree and pathogen species.

Individual silvicultural systems differ from each other in several different component silvicultural operations and resulting stand conditions, which are addressed in turn in the sections below.

Canopy Cover

Differences in forest canopy cover at different stages of the forest growth cycle is one of the obvious distinctions amongst different silvicultural systems. It is also influenced by decisions over specific silvicultural operations, e.g., tree species selection, planting density, and thinning. Canopy cover affects microclimate, solar irradiation and air flow, all of which can alter the survival and dispersal of pathogens within a forest. Although it could not be distinguished as a separate effect in the reviewed literature, canopy cover would also be expected to affect movement of animal vectors of disease. We found only three studies explicitly investigating the impacts of canopy cover and their results conformed to the expectation for the different types of pathogen species, given that greater canopy cover is associated with higher air humidity, but lower sub-canopy wind speeds. Two studies in California mixed evergreen forest found a positive relationship between canopy cover and severity of infection by P. ramorum , a species whose dispersal and colonization is dependent on high humidity ( Condeso and Meentemeyer, 2007 ; Ellis et al., 2010 ). In contrast, in British Columbia, C. ribicola , a species whose spores can disperse successfully through dry air, was reduced in sites with higher canopy cover ( Campbell and Antos, 2000 ). As the effects of canopy cover clearly differ so much between different species it is not possible to draw conclusions across tree pathogens in general. In order to provide a stronger evidence base for the relative effect of different silvicultural systems in limiting the rate of secondary infection of tree pathogens, new research into the mechanisms by which canopy cover alters pathogen dispersal and infection is a high priority.

Tree Density

High tree density reduces the distance between potential host individuals and would therefore be expected to increase rates of pathogen spread by secondary infection within a forest. This effect is likely to vary among pathogen species, with a greater effect seen for pathogens that spread via root contact than for those with only airborne dispersal. Dispersal via animal vectors is also likely to be affected by tree density, though this could not be distinguished as a separate effect in the reviewed literature. Variation in total tree density can result from many causes, e.g., initial density of planting or natural regeneration or reduction in density due to intensity of thinning or other forms of selective felling. Reduction in density of individual host species can occur as a result of mixture with other species (reviewed in section Tree Species Mixture and Diversity). Studies that reported on the effects of thinning as an operation are reviewed in the following section Thinning.

We found only one study testing the relationship between tree density and the incidence of a pathogen species that spreads through root contact. In Minnesota, USA, broadleaf and conifer seedlings were planted in several species mixtures in recently logged sites at four different densities, ranging from 0.25 to 2 m spacing. In this study the effect of closer spacing on mortality was not significant ( Gerlach et al., 1997 ). Airborne pathogens have been subject to much more extensive study. The intensity of P. ramorum infection increased in an observational study of mixed evergreen stands in California with higher densities of the three primary host species ( Dillon et al., 2014 ). This positive relationship between tree density and pathogen incidence or impact has been observed for a range of other tree and airborne pathogen species and locations, including crown dieback of F. excelsior due to H. fraxineus in forests across the Czech Republic ( Havdova et al., 2017 ), mortality of P. sylvestris due to snow blight ( Phacidium infestans ) in Sweden ( Burdon et al., 1992 ), and infection level by M. pinitorqua of both P. sylvestris in Southwest Lapland and in Northern Karelia, Finland ( Mattila et al., 2001 ; Mattila, 2002 ), and P. pinaster in France ( Desprez-Loustau and Wagner, 1997 ). However a number of other studies find no relationship between pathogen incidence and tree density ( McCracken and Dawson, 1998 ; Bishaw et al., 2003 ; Piirto and Valkonen, 2005 ).

High tree densities increase susceptibility to a broad range of tree pathogens, both those spread by root contact and airborne spores, although this effect is not universal, with many studies showing no relationship. It is likely that the relationship between tree density and pathogen prevalence is not linear but characterized by thresholds at both low and high densities. For most pathogen species forests with a high load are unlikely to see changes in pathogen spread through reduction in tree density, as the probability of secondary infection is likely to remain high even with relatively large distances between trees. Similarly, once distance between trees exceeds the normal dispersal distance of a pathogen, further increases in distance would be expected to have a smaller effect. We found no clear evidence of effects of forest structure per se , though many studies did report on the progression of disease during the development of planted stands. Priorities for future applied research would be to improve understanding of the mechanisms of tree density effects and identify thresholds in tree density related to pathogen load. In considering the role of tree density as a factor in species diversity effects on susceptibility to pathogens, an important source of evidence from future research would be to distinguish the influence of absolute tree density from that of the relative density of individual species and from the effect of forest structure (e.g., tree size heterogeneity). Thus, research should specifically compare the effects of reducing host species density by increased spacing in monoculture vs. dilution by planting in mixture with non-host species.

Thinning may be carried out as a planned action to increase production of the highest value timber from a forest, to improve other components of stand condition, or in response to damaging disturbance events, including tree pathogen outbreaks. In the latter case, thinning can take the form of salvage cutting, where dead or dying trees are removed, or sanitation cutting, which targets trees highly susceptible to disease, with the intention of reducing forest inoculum load. The latter type of thinning to remove susceptible trees will be considered in the next section Diseased Tree Removal. Thinning to improve growth or other components of tree vigor, through reduction in tree density (section Tree Density), could also be expected to improve resilience to tree diseases. However, studies show a large variation in forest response to thinning actions. Negative impacts could be attributed to the resulting stumps, whose cut surfaces are susceptible to infection (compare section Site Preparation), wounding of remaining trees, or due to increased traffic within managed areas, increasing pathogen spread by vectors ( Jules et al., 2002 ; Cushman and Meentemeyer, 2008 ; Goheen et al., 2012 ).

Armillaria sp. root rots have been the best studied pathogen with regards to thinning impacts, with studies consistently finding evidence that thinning increases pathogen infection. Weights of Armillaria sp. isolated from the soil increased with past thinning intensity in A. alba stands in the Spanish Pyrenees ( Oliva et al., 2009 ) and incidence of A. ostoyae infection was higher in experimental units that had been thinned for a range of conifer species in British Columbia, compared with paired unthinned stands ( Morrison et al., 2001 ). This result was also observed in experimental P. menziesii plantations in Oregon ( Rosso and Hansen, 1998 ) and Idaho ( Entry et al., 1991 ), as well as for A. luteobubalina infection of Eucalyptus diversicolor (karri) in Western Australia, with no increased growth rate of trees retained after thinning ( Robinson, 2003 ). In P. radiata plantations in New Zealand thinning also increased stand-level infection of retained trees by A. novae-zelandiae partly through infection from stumps, however the incidence of infection diminished as the stumps decomposed, leaving no effect of thinning after 6 years ( Hood et al., 2002 ; Hood and Kimberley, 2009 ).

Studies of other species of root rot also predominantly show an increase in infection with thinning. In 15 year old P. menziesii stands in northern California, incidence of L. wageneri was much higher in thinned than in unthinned stands ( Harrington et al., 1983 ). This finding was confirmed in a much more extensive survey of P. menziesii plantations in southwest Oregon, which found that incidence of L. wageneri was significantly higher in thinned than unthinned stands, though this effect was not apparent in all the studied forests ( Hessburg, 2001 ). In an experimental study of P. abies stands in Sweden, the probability of stump infection was much higher following thinning in the summer than the winter ( Thor and Stenlid, 2005 ). This pattern persisted following a second thinning of these plots ( Oliva et al., 2010 ). However, infection rates following summer thinning were greatly reduced by a range of chemical and biological (spores of P. gigantea ) treatments of the cut stumps ( Thor and Stenlid, 2005 ), and plots with stumps treated with urea had much lower overall mortality ( Oliva et al., 2008 ). Only a single study recorded a decrease in infection following thinning, with reduced mortality of P. ponderosa due to L. wageneri 10 years after experimental thinning in north-eastern California ( Otrosina et al., 2007 ). Thinning may also be accompanied by measures to remove root fragments, particularly where thinning was carried out with the intention of tackling root rots. However, intensive root removal can be associated with wounding the roots of retained trees, which increased the risk of infection of P. tremuloides by Armillaria spp. ( Pankuch et al., 2003 ).

Thinning has highly variable effects on tree diseases besides root rots. The most frequently studied pathogens infecting tree shoots have been dothistroma needle blight of Pinus spp. caused by D. septosporum and D. pini . A comprehensive review of management and control of these pathogens was provided by Bulman et al. (2016) . They found that in Australia, Chile, New Zealand and USA, reducing stand density by thinning reduced disease levels. However, ongoing experiments in the generally wetter climates of Great Britain and British Columbia have not shown a notable effect on disease incidence. No benefits were found of thinning for control of these pathogens, or Lecanosticta acicula , in P. radiata plantations in northern Spain ( de Urbina et al., 2017 ). Thinning was reported to reduce damage of P. contorta var. latifolia due to E. harknessii across 27 plantations in southeastern British Columbia ( Roach et al., 2015 ). However, no significant effect of thinning of P. contorta var. latifolia on incidence of E. harknessii infection had been found in a previous multi-site study in British Columbia, though thinning was associated with a large increase in the incidence of infection by stalactiform blister rust ( Cronartium coleosporioides ; van der Kamp, 1994 ). Similarly, in Idaho, thinning was related to an increase in the number of new lethal infections per tree of Pinus monticola (western white pine) by C. ribicola 5 years after treatment ( Hungerford et al., 1982 ). In an experiment in a forest in Missouri, USA, where a range of oak species are subject to “oak decline” that may be caused by a range of root pathogens or insects, thinning in the form of “improvement harvests” (selective cutting to remove trees that were declining and to reduce tree density) did not significantly alter the incidence of oak decline after 10 ( Meadows et al., 2013 ) or 14 years ( Dwyer et al., 2007 ; Meadows et al., 2013 ).

As well as being a legacy of the harvesting of mature trees, stumps are also present throughout growing stands as a result of thinning operations. Chemical or biological treatment of stumps resulting from thinning can be effective at reducing pathogen incidence, as is the case for final harvest tree stumps (section Site Preparation). In Sweden, following thinning, the proportion of P. abies stump area colonized by H. annosum after 6–7 weeks was reduced by 88–99% in stumps treated with either 35% urea solution, 5% disodium octaborate tetrahydrate solution or spores of Phlebiopsis gigantea , compared with untreated stumps ( Thor and Stenlid, 2005 ).

In the majority of cases, forests that have undergone thinning have a higher incidence of tree disease than unthinned sites. However, results are variable, even within the same site, pathogen or tree species. Such variation likely arises not from thinning itself, but from other changes within the forest associated with thinning regimes. Pathogen loads can increase due to increased movement of machinery and human vectors into a forest to carry out thinning ( Jules et al., 2002 ; Cushman and Meentemeyer, 2008 ; Goheen et al., 2012 ) and wounding of stems and roots of retained trees that can provide entry points for pathogens. More complex effects can be mediated by changes in forest species composition and structural composition resulting from thinning. Therefore, to provide a more robust basis for management recommendations, future studies should focus on identifying and accounting for the sources of this variation, and determining how impacts vary during the course of a pathogen invasion.

Diseased Tree Removal

Removal of diseased trees is often one of the criteria applied for tree selection in thinning of diseased stands. In some cases it is the sole focus of a control programme, either restricted to trees already showing disease symptoms or extended to trees considered to be at high risk of infection, e.g., because of their species and proximity to diseased trees. The effectiveness of this measure has been assessed in a number of studies, though not through rigorous experimentation. Examples include the spatial spread of Dutch elm disease ( Ophiostoma novo -ulmi) in New Zealand ( Ganley and Bulman, 2016 ) and Gotland Island, Sweden ( Menkis et al., 2016 ), and P. ramorum in the coastal forests of Oregon ( Kanaskie et al., 2006 ). In 35-year-old coppiced Castanea sativa (sweet chestnut) in Italy, thinning that targeted the cutting of infected stems did result in a reduction in the severity of damage due to C. parasitica 2 years later ( Amorini et al., 2001 ). In all of these studies, while some evidence was found that removal of infected and adjacent trees slowed the spread of the pathogen, it had only delayed, rather than prevented, eventual infection. The cryptic nature of the pathogens that prevents sufficiently early identification of infected trees to enable their removal before they become a source of inoculum, and the occasional occurrence of long-distance inoculum dispersal events through vectors, e.g., human or animal movement, are among the major constraints. The potential for removal of diseased trees to disrupt natural biocontrol, e.g., hypovirulence of C. parasitica caused by virus infection of the fungus, merits future research.

Pruning and Coppicing

Pruning of lateral branches is usually carried out to improve timber quality by reducing knots in the subsequent radial wood growth. Analogous to thinning, pruning may also be carried out to reduce pathogen incidence by targeting infected or susceptible damaged branches or to reduce sub-canopy humidity in the forest. However, pruning wounds also create potential sites for pathogen entry and, as with thinning, pruning operations may increase traffic and potential of cross-infection on tools, acting as vectors of pathogens.

Positive impacts of pruning Pinus spp. on resistance to C. ribicola rust have been largely consistent across North America. In Idaho pruning of P. monticola in addition to thinning greatly reduced the total number of new lethal and non-lethal infections per tree after 5 years compared with thinning-only treatment and controls ( Hungerford et al., 1982 ). Incidence and severity of C. ribicola infection of young P. strobus was reduced by preventative pruning of susceptible lower branches in sites across the eastern USA ( Ostry, 2000 ). Pruning of infected branches of P. strobus also reduced the incidence of disease and tree mortality in Quebec, Canada ( Lavallee, 1991 ).

For other pathogens, results of pruning have not been so positive. Pruning increased F. circinatum canker symptoms in P. radiata plantations in Cantabria, Spain, which was attributed to the role of pruning wounds in permitting the pathogen to infect the tree ( Bezos et al., 2012 ). Pruning increased D. pinea infection in P. radiata trees in New Zealand that were experimentally inoculated, with a large increase in infection rates with intensity of pruning (percentage of crown removed; Chou and MacKenzie, 1988 ). Infection by D. pinea and by Seiridium cardinale was also positively associated with pruning of Cupressus sempervirens (cypress) trees in Israel ( Madar et al., 1991 ). No effect of pruning was observed on control of D. septosporum, D. pini , or L. acicula in P. radiata plantations in northern Spain ( de Urbina et al., 2017 ), nor Armillaria spp. infection in New Zealand P. radiata plantations ( Hood et al., 2002 ). For stands of P. abies in Baden-Württemburg, Germany, careful pruning of branches up to 10 m height was found to produce only a low risk of wood deterioration, however it did lead to an increase in heartwood infection by a range of pathogens, especially Nectria fuckeliana ( Metzler, 1997 ). The review of studies in Australia and New Zealand on Dothistroma spp. infection of Pinus spp. by Bulman et al. (2016) reported mixed results of pruning, particularly beyond short-term impacts.

Shoot removal to reduce multiple stems to a single stem was carried out on Acacia mangium and A. crassicarpa plantation trees in South Africa, and was followed by experimental inoculation by pathogenic Ceratocystis acaiivora and Lasiodiplodia theobromae fungi ( Tarigan et al., 2011 ). Careful pruning resulted in reduced lesion size compared with trees pruned less carefully, causing tearing of the bark, which suffered infection from naturally spreading spores even if not inoculated. Pathogen impacts are of particular concern for short-rotation coppice systems with fast-growing trees that are particularly susceptible to infection. In an experiment in Northern Ireland, McCracken and Dawson (2003) found that coppicing produced mixed results amongst genotypes of Salix spp. In one genotype, levels of the M. epitea rust pathogen were much higher in the first 3-year harvest cycle than during the second cycle. However, for a number of other genotypes, M. epitea infection was more severe on the regrowth from freshly coppiced stools.

Phytophthora ramorum is able to persist in, and produce spores from, resprouted stumps (effectively increasing the inoculum load available for secondary infection within a plantation thus generating secondary infection). A benefit of sprout cutting was shown, as isolation of P. ramorum from the sprouts growing from cut stumps of U. californica was reduced in sprouts that had been cut 1-year previously compared with those left to grow for 7 years, however there was no treatment effect for sprouts growing on stumps of N. densiflorus ( Valachovic et al., 2013a ).

Pruning, coppicing and shoot removal have a highly variable impact on resilience of forests to tree pathogens. Some of the literature on the subject points to an increase in susceptibility caused by pruning wounds and increased vector or air movement of the pathogen within the forest. However, other studies show a decrease in susceptibility to some pathogens, linked to removal of susceptible branch material and reduced sub-canopy humidity. There is a lack of experimental studies that enable testing of these mechanisms and their trade-offs. While pruning is less common as a forest management practice than is thinning, it should be a priority for future studies. There is good potential to link knowledge of the effects of pruning practice on tree pathogens in arboriculture with the evidence required to inform forest management. A priority is to understand more about what controls the risk of entry into pruning wounds of the main airborne pathogens of commercial tree species.

The processes described above in terms of primary and secondary infection capture the first element of forest resilience, its resistance to an invading pathogen. The second element, the capacity of the forest to recover, is discussed in this section. As explained above, we considered rates of tree growth and natural regeneration following the onset of pathogen infection, which were the only measures of the recovery of the forest ecosystem reported in the reviewed studies. Within our working definition of resilience, we did not include changes in pathogen inoculum or infection level in the ecosystem as measures of recovery, in order to avoid mixing up “cause” and “effect.” The capacity for forest ecosystem recovery can be assessed over a wide range of temporal and spatial scales. For entire managed forests it is extremely likely that, over the long term, the decisions of forest managers will be crucial in determining the rate and trajectory of forest recovery. Gibbs et al. (2002) provide an insightful account of how successive generations of managers have experimented and adapted the management of a forest (Thetford, UK) to promote recovery and longer-term forest resilience to the threat posed by H. annosum . A number of studies have investigated at a smaller and shorter-term scale the effect of individual management actions on the capacity for forest recovery from pathogen impacts through natural regeneration or tree growth. They have researched some of the forest management options already considered in terms of their impact on primary and secondary infection (above), and we review their evidence on forest recovery below, with a summary in Table 2 .

Species Diversity and Mixtures

In a large experiment in British Columbia forests subject to infection by A. ostoyae and P. sulphurascens , mixed species plots had lower basal area after 40 years growth compared with monocultures, but the effect on stem diameter and on dominant tree height was variable ( Morrison et al., 2014 ). Interpretation of other experimental studies in British Columbia crosses over between the effects of species mixture and of thinning as a treatment. In British Columbia forests where P. menziesii is subject to infection by A. ostoyae , mean diameter increment and height:diameter ratio increased significantly in stands where B. papyrifera was removed or partly thinned ( Baleshta et al., 2005 ). This was linked to increases in light and soil moisture levels caused by the thinning. In higher altitude British Columbia forests infested with A. ostoyae , the diameter growth of planted P. menziesii was 27% greater after experimental removal of the naturally regenerated broadleaves B. papyrifera and P. tremuloides compared with untreated controls, and the increase was greater with higher intensity removal treatments, however height growth was not significantly affected ( Gerlach et al., 1997 ; Baleshta et al., 2005 ; Simard et al., 2005 ). In a second experiment, diameter growth of P. contorta var. latifolia (but not P. menziesii ) was increased by removal of broadleaves. These results indicate the importance of the identity of tree species in a mixture for tree growth recovery from pathogen infection.

In a complex mixture experiment of many Salix spp. varieties in a short rotation coppice system in Northern Ireland subject to the M. epitea rust pathogen, tree growth rate was invariably greater in mixtures compared with monoculture, even when a majority of varieties in the mixture were killed by the pathogen ( McCracken et al., 2001 ). However, in a subsequent experimental study of Salix viminalis genotypes subject to infection by M. epitea , whilst at the harvest at the end of the first 3-year growth cycle mixtures showed a higher yield compared with monocultures, this difference did not persist to the harvest at the end of the second cycle ( Begley et al., 2009 ).

Inoculum removal prior to planting has had mixed effects on subsequent tree growth. A large-scale experiment in a British Columbia forest infested with the root pathogens P. sulphurascens and A. ostoyae showed that stump removal increased plot basal area by an average of 1.3 times after 40 years of growth of the rotation following treatment, and increased dominant tree height, but did not alter stem diameter ( Morrison et al., 2014 ). In forests infested by P. sulphurascens in Washington State and Oregon, pre-planting stump removal produced mixed results on the growth of P. menziesii ( Thies and Westlind, 2005 ). It increased seedling height in two study sites, and reduced the final measured volume at one site, but there were no significant effects at the other sites studied.

There are insufficient studies of alternative silvicultural systems to draw any clear conclusions about the implications for recovery. In P. radiata forest infected by F. circinatum in California, gap size was positively associated with seedling height and diameter growth rates, showing a pattern that did not correspond to that of the variation in disease incidence with gap size ( Ferchaw et al., 2013 ). In mixed conifer forest in Oregon subject to infection by A. ostoyae , experimental harvesting treatments of group selection and shelterwood were compared with unharvested forest ( Filip et al., 2010 ). Diameter growth of retained trees 10 years after infection by A. ostoyae was not significantly altered by the silvicultural harvesting treatments, and there were no consistent effects on the density of natural regeneration amongst species.

In a P. monticola forest infected by C. ribicola in Washington State, tree height at 16 years of age was not significantly affected by tree spacing over a range from 3 to 5 m, however it was lower with very close spacing (2 m) and very wide spacing (6 m) ( Bishaw et al., 2003 ). Tree diameter increased with spacing from 2 to 5 m. Plot basal area and volume decreased with spacing over the whole range from 2 to 6 m. Thus, response to variation in tree density differed amongst measures of forest growth. Results from this single study of one tree-pathogen species combination do not provide a sufficient basis for any generalization.

Studies of thinning impacts have consistently shown that it results in increased tree growth rates in infected stands sufficient to promote forest recovery. In P. radiata plantations in New Zealand subject to severe infection by A. novae-zelandiae , thinning treatments were followed by long-term increase in growth (and assumed associated resistance) in the retained trees at a level sufficient to counter the effects of increased inoculum potential following treatment ( Hood and Kimberley, 2009 ). As a result, it is expected that thinning of these diseased stands will not lead to any reduction in final crop volume. Similarly, in coppiced C. sativa forest infected by C. parasitica in Italy, a thinning treatment that targeted the cutting of infected stems increased the growth rate of the retained stems, resulting in the same stand volume growth rate as pre-thinning ( Amorini et al., 2001 ). In Mississippi, USA, where red oaks ( Quercus spp.) are infected with the canker decay fungus Inonotus hispidus , experimental improvement thinning that removed smaller and diseased trees significantly increased the diameter growth of the retained trees ( Meadows et al., 2013 ).

One study was notable for providing evidence of natural regeneration as a process of forest recovery, but its results were mixed. In British Columbia selective cutting, a silvicultural treatment somewhat akin to thinning, in forests infested with A. ostoyae , resulted in a large increase in rates of subsequent natural regeneration of a range of conifer species, compared with uncut control plots, but in only two of the four studied forest sites. Less than 30% of the naturally regenerated trees were killed by the pathogen in these two sites ( Morrison et al., 2001 ).

Conclusions

Coverage of published studies.

Published studies on forest resilience to tree diseases have uneven coverage with regard to geographical locations, management options, and pathogen species. The majority of studies have been restricted to a single forest area, while larger-scale studies often find inconsistent results across locations. This patchy coverage, and a lack of detail in reporting of the management options tested or the scale of their effects, hampers our ability to produce a systematic assessment of the similarities and differences in the impacts of management on tree resilience to different tree pathogens. Insufficient evidence is provided to enable comparison of effectiveness between options. Individual studies are limited to considering a single, or small number of related, pathogens, and therefore do not provide an adequate evidence base for forest managers who need to decide how best to increase forest resilience against multiple known and unknown future threats. Determining general conclusions to best inform forest management in the face of such a diversity of (and likely increasing pressure from) future pathogen risks is therefore challenging. Most management actions have been responsive, seeking to combat specific pathogens that are either established in a forest or new outbreaks after they have reached a region. Interventions thus tend to focus on reducing sources of inoculum or the rate of secondary infection, including the transmission of inoculum and the susceptibility of trees. Because most studies have researched forests managed for timber production, their evidence should not simply be extrapolated to forests managed for other benefits (for which different measures of resilience, linked to other ecosystem services, would be more relevant).

Evidence of Forest Management That Increases Resilience to Forest Pathogens

Although the published studies included in this review were very uneven in their coverage and did not produce consistent results, they provided stronger evidence of the benefit of certain management options for forest resilience to pathogens. The reduction of primary infection by limiting the connectivity of forest units and by the removal or treatment of stumps during site preparation, and the reduction of secondary infection by planting mixed species forests, are the management options with the strongest evidence for improving forest resilience to pathogens. Despite this, in each case the effects are strongly modified by the particular methods used and tree species involved, so this evidence can only be taken as a first indication to inform management decision-making. Forest managers must also consider the scale of the effect of each management option and trade-offs with other impacts on the forest system, such as the effects on environmental conditions and thus tree health and vigor.

Commercial timber production is the dominant management objective in the studied forests, with the need to reduce the risk to this posed by tree pathogens and pests increasingly recognized. However, even in commercial forests biodiversity conservation is also an increasingly important objective. Therefore, the potential negative impacts of connectivity on risk of spread of pathogens and pests needs to be weighed against the demonstrated benefits of higher connectivity for biodiversity ( Lindenmayer et al., 2006 ). For many tree pathogens, connectivity through vehicular and human movement may be more significant than a continuity of habitat cover, depending on how specific pathogens spread. Therefore, controlling primary infection rate via human vectors may provide a reduction in functional connectivity for some pathogens, with little impact on other organisms. Stump removal as a method to reduce sources of pathogen innocuum also presents an interesting trade-off with habitat management for the benefit of biodiversity. Dead wood such as stumps are recognized as important habitat components for a wide range of forest biodiversity, including many forest specialist species ( Hartley, 2002 ). Providing adequate evidence to inform the management response to this trade-off is also a research priority.

Perhaps the most consistent finding of the reviewed research, supported by multiple studies across a range of pathogen species, although still not ubiquitous, is that the rate of secondary infection of trees of a given species is reduced if these trees are growing in a mixed, species-diverse forest rather than a monoculture. In this sense, higher species diversity has an insurance value against future income risks due to disease, which will be positively valued by risk-averse forest managers ( Finger and Buchmann, 2015 ). However, this outcome depends on the species within the mixture, with only non-host species increasing forest resilience to pathogens. In fact, the presence of secondary host species can make infection worse and may increase the rate of primary infection ( Power and Mitchell, 2004 ). This finding points to a need to extend the importance of tree species selection in strategies to combat tree diseases. Beyond considering the susceptibility of candidate primary crop species to pathogen species known to be present in the region (or at risk of arriving during the forest rotation), forest managers also need to consider the potential role of each tree species in a mixed forest for how it may influence the risk of infection (by a broad range of pathogens) of the other crop species present.

In seeking to achieve the most economically efficient solution to exploiting the benefits of higher tree species diversity for increasing forest system resilience to tree pathogens, a key consideration is the spatial scale at which such mixing occurs. If the economic benefit of including within the forest a portfolio of different tree crop species can be achieved by establishing large monoculture blocks of each species, then this may only cause a small increase in management costs compared with a whole-forest monoculture. However, knowledge of ecological mechanisms would suggest that the larger the monoculture blocks the smaller will be the ecological benefit through diluting the individual trees of susceptible species. It is also possible that resilience of susceptible trees is increased due to interaction with other tree species, which is unlikely to occur if mixing takes place only at the landscape scale ( Bauhus et al., 2017 ). It is therefore striking that we found no studies reporting results on the effect of the spatial scale of tree species mixing on rates of pathogen infection. Similarly, for the studies that researched at a landscape scale, we did not find any that reported the effects of the heterogeneity (e.g., in tree species composition) between adjacent forest patches. These evidence gaps limit our ability to draw detailed conclusions regarding how mixed-species forests should be designed to maximize this benefit, and we therefore identify these as high priorities for future research.

With reference to recovery of forest ecosystems, there are a number of studies of the effects of silvicultural treatments on the growth of mostly conifer crop trees in pathogen-infested forests. The results generally indicate that tree growth increased following silvicultural treatments, irrespective of the fact that the studies were carried out in forests where the trees were subject to pathogen infection. However, there are very few studies reporting on the effect of silvicultural treatments on forest recovery through natural regeneration.

Implications for Epidemiological and Bioeconomic Modeling

The findings of this review have several implications for epidemiological modeling of emergence, spread, and persistence of tree pathogens and for capturing the resilience of forests in response to such threats. However, we identified many important evidence gaps in the empirical literature that should be a priority for new primary research to fill. Our review aimed at providing a foundation for linking the processes and parameters used in models, specifically the epidemiological components of primary and secondary infection, and the ecological components of forest recovery, to the published observational and experimental data. This has several important implications for this area of modeling. Firstly, while our review showed the importance of tree species mixture effects, most models consider a forest comprising only a single host species ( Kleczkowski et al., 2019 ). Secondly, our review showed the importance of connectivity between forest units. While there has been significant progress in recent years on spatial and meta-population modeling of plant pathogens, to our knowledge these have not yet been combined with ecological models to improve understanding of the trade-offs between the benefits of connectivity for biodiversity ( Lindenmayer et al., 2006 ) and the reduction of pathways for pathogens to spread between and within forests. Thirdly, in models the effects of management options on epidemiological processes are often described as a simple reduction of primary or secondary infection rate. In reality, many of these processes may involve non-linearities and threshold behavior, though these have not been thoroughly studied. Fourthly, our findings on the importance of persistent inoculum for certain pathogens, from reservoirs such as tree stumps and root fragments of felled trees, suggest that infection rates in a forest unit may be “path-dependent,” for example on the forest unit's history of infection and control options adopted, with implications for the structure of models. Fifthly, the implications of the reviewed empirical studies for epidemiological modeling are limited by their generally small sample size and, in many cases, weakness in the capacity of the experimental design to test the influence of environmental variables and interaction effects.

We hope that this paper will contribute to a dialogue between forest managers and ecologists on one hand and epidemiological and bioeconomic modelers on the other, to establish criteria for experimentation that can be used to better parameterize models and rigorously test their results.

Data Availability Statement

All datasets generated for this study are included in the article/ Supplementary Material .

Author Contributions

JH conceived the study. AK, NH, CG, and JH acquired funding for the project. JH and MR designed the study. MR carried out data collection, performed the analysis and led the drafting of the manuscript, with input from JH. All authors discussed and interpreted the results and contributed to the writing of the final manuscript.

This work is from the project titled Modeling economic impact and strategies to increase resilience against tree disease outbreaks . This is one of seven projects in the Tree Health and Plant Biosecurity Initiative (phase 2) funded by BBSRC, Defra, ESRC, Forestry Commission, NERC, and Scottish Government. The Rural & Environment Science & Analytical Services Division of the Scottish Government provided supporting capacity to MR for final editing of the paper.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

The authors thank the other members of the FOREMOD project team (Chris Quine, Morag Macpherson, Ciara Dangerfield, and Oleg Sheremet) for valuable discussions and insights which have contributed to the development of this paper in many ways.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/ffgc.2020.00007/full#supplementary-material

Amorini, E., Manetti, M. C., Turchetti, T., Sansotta, A., and Villani, F. (2001). Impact of silvicultural system on Cryphonectria parasitica incidence and on genetic variability in a chestnut coppice in Central Italy. For. Ecol. Manag. 142, 19–31. doi: 10.1016/S0378-1127(00)00337-6

CrossRef Full Text | Google Scholar

Anglberger, H., and Halmschlager, E. (2003). The severity of Sirococcus shoot blight in mature Norway spruce stands with regard to tree nutrition, topogrpahy and stand age. For. Ecol. Manag. 177, 221–230. doi: 10.1016/S0378-1127(02)00440-1

Baleshta, K. E., Simard, S. W., Guy, R. D., and Chanway, C. R. (2005). Reducing paper birch density increases Douglas-fir growth rate and Armillaria root disease incidence in southern interior British Columbia. For. Ecol. Manag. 208, 1–13. doi: 10.1016/j.foreco.2004.07.076

Bauhus, J., Forrester, D., Gardiner, B., Jactel, H., Vallejo, R., and Pretzsch, H. (2017). “Ecological stability of mixed-species forests,” in Mixed-Species Forests - Ecology and Management , eds H. Pretzsch, D. I. Forrester, and J. Bauhus (Verlag: Heidelberg), 337–382. doi: 10.1007/978-3-662-54553-9_7

Bauman, J. M., Keiffer, C. H., and McCarthy, B. C. (2014). Growth performance and chestnut blight incidence ( Cryphonectria parasitica ) of backcrossed chestnut seedlings in surface mine restoration. N. Forests 45, 813–828. doi: 10.1007/s11056-014-9439-3

Begley, D., McCracken, A. R., Dawson, W. M., and Watson, S. (2009). Interaction in Short Rotation Coppice willow, Salix viminalis genotype mixtures. Biomass Bioenergy 33, 163–173. doi: 10.1016/j.biombioe.2008.06.001

Beh, M. M., Metz, M. R., Frangioso, K. M., and Rizzo, D. M. (2012). The key host for an invasive forest pathogen also facilitates the pathogen's survival of wildfire in California forests. N Phytol. 196, 1145–1154. doi: 10.1111/j.1469-8137.2012.04352.x

PubMed Abstract | CrossRef Full Text | Google Scholar

Bendz-Hellgren, M., and Stenlid, J. (1998). Effects of clear-cutting, thinning, and wood moisture content on the susceptibility of Norway spruce stumps to Heterobasidion annosum. Canad. J. Forest Res. 28, 759–765. doi: 10.1139/x98-043

Benedict, W. V. (1981). History of White Pine Blister Rust Control - A Personal Account . Washington, DC: Department of Agriculture Forest Service.

Google Scholar

Bergdahl, D. R., Sendak, P. E., Tobi, D. R., Bove, J. R., and Tritton, L. M. (2002). Incidence of annual canker of sugar maple studied with the aid of a geographic information system. North. J. Appl. Forest. 19, 73–79. doi: 10.1093/njaf/19.2.73

Bezos, D., Lomba, J. M., Martinez-Alvarez, P., Fernandez, M., and Diez, J. J. (2012). Effects of pruning in Monterrey pine plantations affected by Fusarium circinatum . Forest Syst. 21, 481–488. doi: 10.5424/fs/2012213-02262

Bishaw, B., DeBell, D. S., and Harrington, C. A. (2003). Patterns of survival, damage, and growth for western white pine in a 16-year-old spacing trial in western Washington. West. J. Appl. Forest. 18, 35–43. doi: 10.1093/wjaf/18.1.35

Blodgett, J. T., Kruger, E. L., and Stanosz, G. R. (1997). Sphaeropsis sapinea and water stress in a red pine plantation in central Wisconsin. Phytopathology 87, 429–434. doi: 10.1094/PHYTO.1997.87.4.429

Boyd, I. L., Freer-Smith, P. H., Gilligan, C. A., and Godfray, H. C. (2014). The consequence of tree pests and diseases for ecosystem services. Science 342:1235773. doi: 10.1126/science.1235773

Brassett, P. R., and Gilligan, C. A. (1988). A model for primary and secondary infection in botanical epidemics. Zeitschrift für Pflanzenkrankheiten und Pflanzenschutz 95, 352–360.

Bulman, L. S. (2008). Pest detection surveys on high-risk sites in New Zealand. Austr. Forest. 71, 242–244. doi: 10.1080/00049158.2008.10675042

Bulman, L. S., Bradshaw, R. E., Fraser, S., Martin-Garcia, J., Barnes, I., Musolin, D. L., et al. (2016). A worldwide perspective on the management and control of Dothistroma needle blight. Forest Pathol. 46, 472–488. doi: 10.1111/efp.12305

Burdon, J. J., Wennstrom, A., Ericson, L., Muller, W. J., and Morton, R. (1992). Density dependent mortality in Punis sylvestris cause by snow blight pathogen Phacidium infestans . Oecologia 90, 74–79. doi: 10.1007/BF00317811

Campbell, E. A., and Antos, J. (2000). Distribution and severity of white pine blister rust and mountain pine beetle on whitebark pine in British Colombia. Canad. J. Forest Res. 30, 1051–1059. doi: 10.1139/x00-020

Carey, M., Sanderson, B., Barnas, K., and Olden, J. (2012). Native invaders - challenges for science, management, policy, and society. Front. Ecol. Environ. 10, 373–381. doi: 10.1890/110060

Chou, C. M., and MacKenzie, M. (1988). Effect of pruning intensity and season on Diplodia pinea infection of Pinus radiata stem through pruning wounds. Euro. J. Forest Pathol. 18, 437–444. doi: 10.1111/j.1439-0329.1988.tb00233.x

Cleary, M. R., Arhipova, N., Morrison, D. J., Thomsen, I. M., Sturrock, R. N., Vasaitis, R., et al. (2013). Stump removal to control root disease in Canada and Scandinavia: a synthesis of results from long-term trials. For. Ecol. Manag. 290, 5–14. doi: 10.1016/j.foreco.2012.05.040

Condeso, T. M., and Meentemeyer, R. K. (2007). Effects of landscape heterogeneity on the emerging forest disease sudden oak death. J. Ecol. 95, 364–375. doi: 10.1111/j.1365-2745.2006.01206.x

Cram, M. S., Shea, D., and Forbus, K. (2010). “Case study to examine the effects of a growing-season burn and Annosum root disease on mortality in a longleaf pine stand,” in Proceedings of the 14th Biennial Souther Silivicultural Research Conference (Asheville, NC).

Crone, M., McComb, J. A., O'Brien, P. A., and Hardy, G. E. S. (2014). Host removal as a potential control method for Phytophthora cinnamomi on severely impacted black gravel sites in the jarrah forest. Forest Pathol. 44, 154–159. doi: 10.1111/efp.12080

Cushman, J. H., and Meentemeyer, R. K. (2008). Multi-scale patterns of human activity and the incidence of an exotic forest pathogen. J. Ecol. 96, 766–776. doi: 10.1111/j.1365-2745.2008.01376.x

Davidson, J. M., Patterson, H. A., Wickland, A. C., Fichtner, E. J., and Rizzo, D. M. (2011). Forest type influences transmission of Phytophthora ramorum in California Oak Woodlands. Phytopathology 101, 492–501. doi: 10.1094/PHYTO-03-10-0064

de Urbina, E. O., Mesanza, N., Aragones, A., Raposo, R., Elvira-Recuenco, M., Boque, R., et al. (2017). Emerging needle blight diseases in atlantic pinus ecosystems of Spain. Forests 8:18. doi: 10.3390/f8010018

Desprez-Loustau, M. L., Aguayo, J., Dutech, C., Hayden, K. J., Husson, C., Jakushkin, B., et al. (2016). An evolutionary ecology perspective to address forest pathology challenges of today and tomorrow. Ann Forest Sci. 73, 45–67. doi: 10.1007/s13595-015-0487-4

Desprez-Loustau, M. L., and Wagner, K. (1997). Influence of silvicultural practices on twisting rust infection and damage in maritime pine, as related to growth. For. Ecol. Manag. 98, 135–147. doi: 10.1016/S0378-1127(97)00079-0

Dillon, W. W., Haas, S. E., Rizzo, D. M., and Meentemeyer, R. K. (2014). Perspectives of spatial scale in a wildland forest epidemic. Euro. J. Plant Pathol. 138, 449–465. doi: 10.1007/s10658-013-0376-3

D'Souza, N. K., Colquhoun, I. J., Shearer, B. L., and Hardy, G. E. S. (2004). The potential of five Western Australian native Acacia species for biological control of Phytophthora cinnamomi . Austr. J. Bot. 52, 267–279. doi: 10.1071/BT03089

Dwyer, J. P., Kabrick, J. M., and Wetteroff, J. (2007). Do improvement harvests mitigate oak decline in Missouri Ozark forests? North. J. Appl. Forest. 24, 123–128. doi: 10.1093/njaf/24.2.123

Ellis, A. M., Vaclavik, T., and Meentemeyer, R. K. (2010). When is connectivity important? A case study of the spatial pattern of sudden oak death. Oikos 119, 485–493. doi: 10.1111/j.1600-0706.2009.17918.x

Entry, J. A., Cromack, K., Kelsey, R. G., and Martin, N. E. (1991). Response of douglas-fir to infection by Armillaria ostoyae after thinning or thinning plus fertilisation. Phytopathogy 81, 682–689. doi: 10.1094/Phyto-81-682

Ferchaw, V. A. L., Goldsworthy, E., Pinkerton, J., Yun, D. I., Lund, U. J., Mark, W., et al. (2013). Management strategies for pitch canker infected Ano Nuevo stands of Monterey pine. For. Ecol. Manag. 308, 101–115. doi: 10.1016/j.foreco.2013.07.032

Fichtner, E. J., Rizzo, D. M., Kirk, S. A., and Webber, J. F. (2011). Root infections may challenge management of invasive Phytophthora spp. in UK Woodlands. Plant Dis. 95, 13–18. doi: 10.1094/PDIS-03-10-0236

Filip, G. M., Ganio, L. M., Oester, P. T., Mason, R. R., and Wickman, B. E. (2002). Ten-year effect of fertilization on tree growth and mortality associated with armillaria root disease, fir engravers, dwarf mistletoe, and western spruce budworm in Northeastern Oregon. West. J. Appl. Forest. 17, 122–128. doi: 10.1093/wjaf/17.3.122

Filip, G. M., Maffei, H. M., Chadwick, K. L., and Max, T. A. (2010). Armillaria root disease-caused tree mortality following silvicultural treatments (shelterwood or group selection) in an oregon mixed-conifer forest: insights from a 10-year case study. West. J. Appl. Forest. 25, 136–143. doi: 10.1093/wjaf/25.3.136

Finger, R., and Buchmann, N. (2015). An ecological economic assessment of risk-reducing effects of species diversity in managed grasslands. Ecol. Econ. 110, 89–97. doi: 10.1016/j.ecolecon.2014.12.019

Ganley, R. J., and Bulman, L. S. (2016). Dutch elm disease in New Zealand: impacts from eradication and management programmes. Plant Pathol. 65, 1047–1055. doi: 10.1111/ppa.12527

Gerlach, J. P., Reich, P. B., Puettmann, K., and Baker, T. (1997). Species, diversity, and density affect tree seedling mortality from Armillaria root rot. Canad. J. Forest Res. 27, 1509–1512. doi: 10.1139/x97-098

Ghelardini, L., Luchi, N., Pecori, F., Pepori, A. L., Danti, R., Della Rocca, G., et al. (2017). Ecology of invasive forest pathogens. Biol. Invas. 19, 3183–3200. doi: 10.1007/s10530-017-1487-0

Gibbs, J. N., Greig, B. J. W., and Pratt, J. E. (2002). Fromes root rot in thetford forest, east anglia: past, present and future. Forestry 75, 191–202. doi: 10.1093/forestry/75.2.191

Goheen, D. J., Mallams, K., Betlejewski, F., and Hansen, E. (2012). Effectiveness of vehicle washing and roadside sanitation in decreasing spread potential of port-orford-cedar root disease. West. J. Appl. Forest. 27, 170–175. doi: 10.5849/wjaf.11-011

Greene, T. A., Reemts, C. M., and Appel, D. N. (2008). Efficacy of basal girdling to control oak wilt fungal mat production in Texas Red Oak ( Quercus buckleyi ) in Central Texas. South. J. Appl. Forest. 32, 168–172. doi: 10.1093/sjaf/32.4.168

Grimm, V., and Wissel, C. (1997). Babel, or the ecological stability discussions: an inventory and analysis of terminology and a guide for avoiding confusion. Oecologia 109, 323–334. doi: 10.1007/s004420050090

Haas, S. E., Cushman, J. H., Dillon, W. W., Rank, N. E., Rizzo, D. M., and Meentemeyer, R. K. (2016). Effects of individual, community, and landscape drivers on the dynamics of a wildland forest epidemic. Ecology 97, 649–660. doi: 10.1890/15-0767.1

Haas, S. E., Hooten, M. B., Rizzo, D. M., and Meetenmeyer, R. K. (2011). Forest species diversity reduces disease risk in a generalist plant pathogen invasion. Ecol. Lett. 14, 1108–1116. doi: 10.1111/j.1461-0248.2011.01679.x

Hagle, S. K., and Grasham, J. L. (1988). Biological and Economic Feasibility of Pruning and Excising White Pines for Blister Rust Control . United States Department of Agriculture Forest Service.

Halmschlager, E., and Katzensteiner, K. (2017). Vitality fertilisation balanced tree nutrition and mitigated severity of Sirococcus shoot blight on mature Norway spruce. For. Ecol. Manag. 389, 96–104. doi: 10.1016/j.foreco.2016.12.019

Hannerz, M., and Hanell, B. (1997). Effects on the flora in Norway spruce forests following clearcutting and shelterwood cutting. For. Ecol. Manag. 90, 29–49. doi: 10.1016/S0378-1127(96)03858-3

Hantsch, L., Bien, S., Radatz, S., Braun, U., Auge, H., and Bruelheide, H. (2014a). Tree diversity and the role of non-host neighbour tree species in reducing fungal pathogen infestation. Journal of Ecology 102, 1673–1687. doi: 10.1111/1365-2745.12317

Hantsch, L., Braun, U., Haase, J., Purschke, O., Scherer-Lorenzen, M., and Bruelheide, H. (2014b). No plant functional diversity effects on foliar fungal pathogens in experimental tree communities. Fung. Divers. 66, 139–151. doi: 10.1007/s13225-013-0273-2

Hantsch, L., Braun, U., Scherer-Lorenzen, M., and Bruelheide, H. (2013). Species richness and species identity effects on occurrence of foliar fungal pathogens in a tree diversity experiment. Ecosphere 4, 1–12. doi: 10.1890/ES13-00103.1

Harrington, T. C., Reinhart, C., Thornburgh, D. A., and Cobb, F. W. Jr. (1983). Association of black-stain root disease with precommercial thinning of Douglas-fir. Forest Sci. 29, 12–14.

Hartley, M. J. (2002). Rationale and methods for conserving biodiversity in plantation forests. For. Ecol. Manag. 155, 81–95. doi: 10.1016/S0378-1127(01)00549-7

Havdova, L. Z. D., Romportl, D., Peskova, V., and Cerny, K. (2017). Environmental and silvicultural characteristics influencing the extent of ash diebakc in forest stands. Baltic Forest. 23, 168–182.

Hessburg, P. (2001). Association of black stain root disease with roads, skid trails, and precommercial thinning in southwest Oregon. West. J. Appl. Forest. 16, 127–135. doi: 10.1093/wjaf/16.3.127

Heybroek, H. M. (1982). “Monoculture versus mixture: interactions between susceptible and resistant trees in a mixed stand,” Proceedings the Third International Workshop on the Genetics of Host-Parasite Interactions In Forestry (Wageningen).

Hill, L., Jones, G., Atkinson, N., Hector, A., Hemery, G., and Brown, N. (2019). The £15 billion cost of ask dieback in Britian. Curr. Biol. 29, 315–316. doi: 10.1016/j.cub.2019.03.033

Holling, C. S. (1996). “Engineering resilience versus ecological resilience,” in Engineering Within Ecological Constraints , ed P.C. Schulze (Washington, DC: National Academy Press), 31–43.

Holzmueller, E. J., Jose, S., and Jenkins, M. A. (2008). The relationship between fire history and an exotic fungal disease in a deciduous forest. Oecologia 155, 347–356. doi: 10.1007/s00442-007-0908-7

Hood, I. A., and Kimberley, M. O. (2009). Impact of armillaria root disease and the effect of thinning in a late-rotation Pinus radiata plantation. Forest Pathol. 39, 415–427. doi: 10.1111/j.1439-0329.2009.00602.x

Hood, I. A., Kimberley, M. O., Gardner, J. F., and Sandberg, C. J. (2002). Armillaria root disease of Pinus radiata in New Zealand. Influence of thinning and pruning. N Zeal. J. Forest. Sci. 32, 116–132.

Hungerford, R. D., Williams, R. E., and Marsden, M. A. (1982). Thinning and Pruning Western White Pine: A Potential for Reducing Mortality Due to Blister Rust. Ogden, UT: United States Department of Agriculture Forest Service.

Hunt, R. S., Geils, B. W., and Hummer, K. E. (2010). White pines, ribes, and blister rust: integration and action. Forest Pathol. 40, 402–417. doi: 10.1111/j.1439-0329.2010.00665.x

Jactel, H., Bauhus, J., Boberg, J., Bonal, D., Castagneyrol, B., Gardiner, B., et al. (2017). Tree diversity drives forest stand resistance to natural disturbances. Curr. Forest. Rep. 3, 223–243. doi: 10.1007/s40725-017-0064-1

Jactel, H., Nicoll, B. C., Branco, M., Gonzalez-Olabarria, J. R., Grodzki, W., Langstrom, B., et al. (2009). The influences of forest stand management on biotic and abiotic risks of damage. Ann. Forest Sci. 66:2009054. doi: 10.1051/forest/2009054

Jules, E. S., Kauffman, M. J., Ritts, W. D., and Carroll, A. L. (2002). Spread of an invasive pathogen over a variable landscape: A nonnative root rot on Port Orford Cedar. Ecology 83, 3167–3181. doi: 10.1890/0012-9658(2002)083[3167:SOAIPO]2.0.CO;2

Kaitera, J. (2002). Short-term effect of thinning on pinus sylvestris damage and sporulation caused by Cronartium flaccidum . Scand. J. Forest Res. 17, 158–165. doi: 10.1080/028275802753626809

Kanaskie, A., Osterbauer, N., McWilliams, M., Goheen, E., Hansen, E., and Sutton, W. (2006). “Eradication of Phytophthora ramorum in Oregon forests - status after 3 years,” in Proceedings of the Sudden Oak Death Second Science Symposium: the State of our Knowledge .

Katovich, S., O'Brien, J. G., Mielke, M. E., and Ostry, M. (2004). “Restoration and management of Eastern white pine within high blister rust hazard zones in the lake states,” in USDA Forest Service Proceeding (Fort Collins, CO), 135–145.

King, D. I., and DeGraaf, R. M. (2000). Bird species diversity and nesting success in mature, clearcut and shelterwood forest in northern New Hampshire, USA. For. Ecol. Manag. 129, 227–235. doi: 10.1016/S0378-1127(99)00167-X

Kleczkowski, A., Hoyle, A., and McMenemy, P. (2019). One model to rule them all? Modelling approaches across OneHealth for human, animal and plant epidemics. Philos. Trans. R. Soc. B 374:20180225. doi: 10.1098/rstb.2018.0255

Kwon, T. S., Shin, J. H., Lim, J. H., Kim, Y. K., and Lee, E. J. (2011). Management of pine wilt disease in Korea through preventative silvicultural control. For. Ecol. Manag. 261, 562–569. doi: 10.1016/j.foreco.2010.11.008

Lavallee, A. (1991). “White pine blister rust control in a 5 year old eastern white pine plantation at Vercheres, Quebec (1984-88 results),” Proceedings of the IUFRO Rusts of Pine Working Party Conference (Banff, AB).

Leak, W. B. (2006). Fifty-year impacts of the beech bark disease in the Bartlett Experimental Forest, New Hampshire. North. J. Appl. Forest. 23, 141–143. doi: 10.1093/njaf/23.2.141

Liebhold, A. M., Brockerhoff, E. G., Kalisz, S., Nuñez, M. A., Wardle, D. A., and Wingfield, M. J. (2017). Biological invasions in forest ecosystems. Biol. Invasions. 19, 3073–3077. doi: 10.1007/s10530-017-1458-5

Linden, M. L., and Vollbrecht, G. (2002). Sensitivirt of Picea abies to Butt Rot in pure stands and mixed stands with Pinus sylvestric in Southern Sweden. Silva Fennica 36, 767–778. doi: 10.14214/sf.519

Lindenmayer, D. B., Franklin, J. F., and Fischer, J. (2006). General management principles and a checklist of strategies to guide forest biodiversity conservation. Biol. Conserv. 131, 433–445. doi: 10.1016/j.biocon.2006.02.019

Macpherson, M. F., Kleczkowski, A., Healey, J. R., and Hanley, N. (2017a). Payment for multiple forest benefits alters the effect of tree disease on optimal forest rotation length. Ecol. Econ. 134, 82–94. doi: 10.1016/j.ecolecon.2017.01.008

Macpherson, M. F., Kleczkowski, A., Healey, J. R., and Hanley, N. (2018). The effects of disease on optimal forest rotation: a generalisable analytical framework. Environ. Res. Econ. 70, 565–588. doi: 10.1007/s10640-016-0077-4

Macpherson, M. F., Kleczkowski, A., Healey, J. R., Quine, C. P., and Hanley, N. (2017b). The effects of invasive pests and pathogens on strategies for forest diversification. Ecol. Model. 350, 87–99. doi: 10.1016/j.ecolmodel.2017.02.003

Madar, Z., Solel, Z., Sztejnberg, A., and Kimchi, M. (1991). Effect of pruning of trunk side-branches of cypress on infection by seiridium-cardinale and diplodia-pinea F-SP cupressi. For. Ecol. Manag. 44, 255–260. doi: 10.1016/0378-1127(91)90012-K

Martin, J., Cabezas, J., Buyolo, T., and Paton, D. (2005). The relationship between Cerambyx spp. damage and subsequent Biscogniauxia mediterranum infection on Quercus suber forests. For. Ecol. Manag. 216, 166–174. doi: 10.1016/j.foreco.2005.05.027

Matsushita, K., Taki, H., Yamane, F., and Asano, K. (2018). Shadow value of ecosystem resilience in complex natural land as a wild pollinator habitat. Am. J. Agr. Econ. 100, 829–843. doi: 10.1093/ajae/aax075

Mattila, U. (2002). The risk of pine twisting rust damage in young Scots pines: a multilevel logit model approach. For. Ecol. Manag. 165, 151–161. doi: 10.1016/S0378-1127(01)00657-0

Mattila, U., Jalkanen, R., and Nikula, A. (2001). The effects of forest structure and site characteristics on probability of pine twisting rust damage in young Scots pine stands. For. Ecol. Manag. 142, 89–97. doi: 10.1016/S0378-1127(00)00342-X

McCracken, A. R., and Dawson, W. M. (1997). Growing clonal mixtures of willow to reduce effect of Melampsora epitea var. epitea. Euro. J. Forest Pathol. 27, 319–329. doi: 10.1111/j.1439-0329.1997.tb01086.x

McCracken, A. R., and Dawson, W. M. (1998). Short rotation coppic willow in Northern Ireland since 1973: development of the use of mixtures in the control of foliar rust ( Melampsora spp.). Euro. J. Forest Pathol. 28, 241–250. doi: 10.1111/j.1439-0329.1998.tb01179.x

McCracken, A. R., and Dawson, W. M. (2003). Rust disease ( Melamspora epitea ) of willow ( Salix spp.) grown in short rotation coppice (SRC) in inter- and intra-species mixtures. Ann. Appl. Biol. 143, 381–393. doi: 10.1111/j.1744-7348.2003.tb00308.x

McCracken, A. R., Dawson, W. M., and Bowden, G. (2001). Yield response of willow (Salix) grown in mixtures in short rotation coppice (SRC). Biomass Bioenergy 21, 311–319. doi: 10.1016/S0961-9534(01)00046-0

Meadows, J. S., Leininger, T. D., Montwe, D., and Nebeker, T. E. (2013). “Thinning to improve growth, bole quality, and forest health in an Inonotus hispidus infected red oak-sweetgum stand in the Mississippi delta: 10 year results,” in Proceedings of the 15th Biennial Southern Silvicultural Research Conference (Asheville, NC).

Meentemeyer, R. K., Rank, N. E., Anacker, B. L., Rizzo, D. M., and Cushman, J. H. (2008a). Influence of land-cover change on the spread of an invasive forest pathogen. Ecol. Appl. 18, 159–171. doi: 10.1890/07-0232.1

Meentemeyer, R. K., Rank, N. E., Shoemaker, D. A., Oneal, C. B., Wickland, A. C., Frangioso, K. M., et al. (2008b). Impact of sudden oak death on tree mortality in the Big Sur ecoregion of California. Biol. Invas. 10, 1243–1255. doi: 10.1007/s10530-007-9199-5

Menkis, A., Ostbrant, I. L., Wagstrom, K., and Vasaitis, R. (2016). Dutch elm disease on the island of Gotland: monitoring disease vector and combat measures. Scand. J. For. Res. 31, 237–241. doi: 10.1080/02827581.2015.1076888

Metzler, B. (1997). Quantitative assessment of fungal colonisation in Norway spruce after green pruning. Euro. J. Forest Pathol. 27, 1–11. doi: 10.1111/j.1439-0329.1997.tb00848.x

Millar, C. I., and Stephenson, N. L. (2015). Temperate forest health in an era of emerging megadisturbance. Science 349, 823–826. doi: 10.1126/science.aaa9933

Morrison, D. J., Cruickshank, M. G., and Lalumiere, A. (2014). Control of laminated and Armillaria root diseases by stump removal and tree species mixtures: Amount and cause of mortality and impact on yield after 40 years. For. Ecol. Manag. 319, 75–98. doi: 10.1016/j.foreco.2014.02.007

Morrison, D. J., Pellow, K. W., Nemec, A. F. L., Norris, D. J., and Semenoff, P. (2001). Effects of selective cutting on the epidemiology of armillaria root disease in the southern interior of British Columbia. Canad. J. Forest Res. 31, 59–70. doi: 10.1139/x00-144

Morrison, D. J., Wallis, G. W., and Weir, L. C. (1988). Control of Armillaria and Phellinus Root Diseases: 20 Year Results From the Skimikin Stump Removal Experiment . Victoria, BC: Canadian Forestry Service.

Muzika, R. M. (2017). Opportunities for silviculture in management and restoration of forests affected by invasive species. Biol. Invas . 19, 3419–3435. doi: 10.1007/s10530-017-1549-3

Nebeker, T. E., Leininger, T. D., and Meadows, J. S. (1999). “Silvicultural practices in forests of the Southern United States: Insect and disease considerations,” in Tenth Biennial Southern Silvicultural Research Conference (Shreveport, LA).

Newton, A. C., and Cantarello, E. (2015). Restoration of forest resilience: an achievable goal? N. Forests 46, 645–668. doi: 10.1007/s11056-015-9489-1

Nguyen, T. P., Wright, E. P., Nguyen, T. T., Schuiling-Veninga, C. C., Bijlsma, M. J., Nguyen, T. B., et al. (2016). Cost-effectiveness analysis of screening for and managing identified hypertension for cardiovascular disease prevention in Vietnam. PLoS ONE 11:e155699. doi: 10.1371/journal.pone.0155699

Nguyen, T. V., Park, Y. S., Jeoung, C. S., Choi, W. I., Kim, Y. K., Jung, I. H., et al. (2017). Spatially explicit model applied to pine wilt disease dispersal based on host plant infestation. Ecol. Model. 353, 54–62. doi: 10.1016/j.ecolmodel.2016.10.022

Oliva, J., Samils, N., Johansson, U., Bendz-Hellgren, M., and Stenlid, J. (2008). Urea treatment reduced Heterobasidion annosum sl root rot in Picea abies after 15 years. For. Ecol. Manag. 255, 2876–2882. doi: 10.1016/j.foreco.2008.01.063

Oliva, J., Suz, L. M., and Colinas, C. (2009). Ecology of Armillaria species on silver fir ( Abies alba ) in the Spanish Pyrenees. Ann. Forest Sci. 66:2009046. doi: 10.1051/forest/2009046

Oliva, J., Thor, M., and Stenlid, J. (2010). Long-term effects of mechanized stump treatment against Heterobasidion annosum root rot in Picea abies . Canad. J. Forest Res. 40, 1020–1033. doi: 10.1139/X10-051

Ostry, M. (2000). Restoration of white pine in Minnesota, Wisconsin, and Michigan. Hort Techol. 10, 542–543. doi: 10.21273/HORTTECH.10.3.542

Ostry, M. E., Laflamme, G., and Katovich, S. A. (2010). Silvicultural approaches for management of eastern white pine to minimize impacts of damaging agents. Forest Pathol. 40, 332–346. doi: 10.1111/j.1439-0329.2010.00661.x

Ostry, M. E., Moore, M. J., Kern, C. C., Venette, R. C., and Palik, B. J. (2012). Multiple diseases impact survival of pine species planted in red pine stands harvested in spatially variable retention patterns. For. Ecol. Manag. 286, 66–72. doi: 10.1016/j.foreco.2012.08.017

Otrosina, W. J., Kliejunas, J. T., Smith, S., Cluck, D. R., Sung, S. S., and Cook, C. D. (2007). Black stain root disease studies on Ponderosa pine- Parameters and disturbanc treatments affecting infection and mortality. Acta Silva. Lign. Hung. Spec. Edn , 247–251.

Pankuch, J. M., Blenis, P. V., Lieffers, V. J., and Mallett, K. I. (2003). Fungal colonization of aspen roots following mechanical site preparation. Canad. J. Forest Res. 33, 2372–2379. doi: 10.1139/x03-172

Pautasso, M., Aas, G., Queloz, V., and Holdenrieder, O. (2013). European ash ( Fraxinus excelsior ) dieback - a conservation biology challenge. Biol. Conserv. 158, 37–49. doi: 10.1016/j.biocon.2012.08.026

Pautasso, M., Holdenrieder, O., and Stenlid, J. (2005). “Susceptibility to fungal pathogens of forests differing in tree diversity,” in Forest Diversity and Function , eds M. Scherer-Lorenzen, C. H. Körner, and E. D. Schulze (Berlin; Heidelberg: Springer), 63–289. doi: 10.1007/3-540-26599-6_13

Peacock, L., Hunter, T., Turner, H., and Brain, P. (2001). Does host genotype diversity affect the distribution of insect and disease damage in willow cropping systems? J. Appl. Ecol. 38, 1070–1081. doi: 10.1046/j.1365-2664.2001.00655.x

Peterson, E., Hansen, E., and Kanaskie, A. (2014). Spatial relationship between Phytophthora ramorum and roads or streams in Oregon tanoak forests. For. Ecol. Manag. 312, 216–224. doi: 10.1016/j.foreco.2013.10.002

Piirto, D. D., and Valkonen, S. (2005). Structure and development of pitch canker infected Monterey pine stands at Ano Nuevo, California. For. Ecol. Manag. 213, 160–174. doi: 10.1016/j.foreco.2005.03.026

Pimm, S. L. (1984). The complexity and stability of ecosystems. Nature 307, 321–326. doi: 10.1038/307321a0

Pleysier, C. E., Bayliss, K. L., Dell, B., and Hardy, G. E. S. (2006). Temperature, humidity, wounding and leaf age influence the development of Alternaria alternata lesions on leaves of Paulownia fortunei. Austr. Plant Pathol. 35, 329–333. doi: 10.1071/AP06030

Power, A. G., and Mitchell, C. E. (2004). Pathogen spillover in disease epidemics. Am. Natur. 164, S79–S89. doi: 10.1086/424610

Poyatos, R., Latron, J., and Llorens, P. (2002). Land use and land cover change after agricultural abandonment. Mount. Res. Dev. 23, 362–368. doi: 10.1659/0276-4741(2003)023[0362:LUALCC]2.0.CO;2

Prospero, S., and Cleary, M. (2017). Effects of host variability on the spread of invasive forest diseases. Forests 8, 1–21. doi: 10.3390/f8030080

Puddu, A., Luisi, N., Capretti, P., and Santini, A. (2003). Environmental factors related to damage by Heterobasidion abietinum in Abies alba forests in Southern Italy. For. Ecol. Manag. 180, 37–44. doi: 10.1016/S0378-1127(02)00607-2

Ramage, B. S., Forrestel, A. B., Moritz, M. A., and O'Hara, K. L. (2012). Sudden oak death disease progression across two forest types and spatial scales. J. Vegetat. Sci. 3, 151–163. doi: 10.1111/j.1654-1103.2011.01340.x

Raymond, P., and Bédard, S. (2017). The irregular shelterwood system as an alternative to clearcutting to achieve compositional and structural objectives in temperate mixedwood stands. For. Ecol. Manag. 398, 91–100. doi: 10.1016/j.foreco.2017.04.042

Richter, B. S., Benson, D. M., and Ivors, K. L. (2011a). Microbial profiling of cultural systems for suppression of phytophthora root rot in fraser fir. Plant Dis. 95, 537–546. doi: 10.1094/PDIS-03-10-0238

Richter, B. S., Ivors, K., Shi, W., and Benson, D. M. (2011b). Cellulase activity as a mechanism for suppression of phytophthora root rot in mulches. Phytopathology 101, 223–230. doi: 10.1094/PHYTO-04-10-0125

Roach, W. J., Simard, S. W., and Sachs, D. L. (2015). Evidence against planting lodgepole pine monocultures in the cedar-hemlock forests of southeastern British Columbia. Forestry 88, 345–358. doi: 10.1093/forestry/cpv005

Robinson, R. M. (2003). Short-term impact of thinning and fertilizer application on Armillaria root disease in regrowth karri ( Eucalyptus diversicolor F. Muell .) in Western Australia. For. Ecol. Manag. 176, 417–426. doi: 10.1016/S0378-1127(02)00231-1

Ronnberg, J. (2000). Logging operation damage to roots of clear-felled Picea abies and subsequent spore infection by Heterobasidion annosum . Silva Fennica 34, 29–36. doi: 10.14214/sf.642

Rosenvald, R., Drenkhan, R., Riit, T., and Lohmus, A. (2015). Towards silvicultural mitigation of the European ash ( Fraxinus excelsior ) dieback: the importance of acclimated trees in retention forestry. Canad. J. Forest Res. 45, 1206–1214. doi: 10.1139/cjfr-2014-0512

Rosso, P., and Hansen, E. (1998). Tree vigour and the susceptibility of Douglas fir to Armillaria root disease. Forest Pathol. 28, 43–52. doi: 10.1111/j.1439-0329.1998.tb01164.x

Sakamoto, K., Tamesa, T., Yukio, T., Tokuhisa, Y., Maeda, Y., and Oka, M. (2016). Risk factors and managements of bile leakage after hepatectomy. World J. Surg. 40, 182–189. doi: 10.1007/s00268-015-3156-8

Santini, A., Pepori, A., Ghelardini, L., and Capretti, P. (2008). Persistence of some pine pathogens in coarse woody debris and cones in a Pinus pinea forest. For. Ecol. Manag. 256, 502–506. doi: 10.1016/j.foreco.2008.05.010

Schoettle, A. W., and Sniezko, R. A. (2007). Proactive intervention to sustain high-elevation pine ecosystems threatened by white pine blister rust. J. For. Res. 12, 327–336. doi: 10.1007/s10310-007-0024-x

Shaw, C. G., Omdal, D. W., Ramsey-Kroll, A., and Roth, L. F. (2012). Inoculum reduction measures to manage armillaria root disease in a severely infected stand of ponderosa pine in south-Central Washington: 35-year results. West. J. Appl. Forest. 27, 25–29. doi: 10.1093/wjaf/27.1.25

Simard, S. W., Hagerman, S. M., Sachs, D. L., Heineman, J. L., and Mather, W. J. (2005). Conifer growth, Armillaria ostoyae root disease, and plant diversity responses to broadleaf competition reduction in mixed forests of southern interior British Columbia. Canad. J. Forest Res. 35, 843–859. doi: 10.1139/x05-010

Staudhammer, C. L., Jokela, E. J., and Martin, T. A. (2009). Competition dynamics in pure- versus mixed-family stands of loblolly and slash pine in the southeastern United States. Canad. J. Forest Res. 39, 396–409. doi: 10.1139/X08-184

Swedjemark, G., and Stenlid, J. (1993). Population dynamics of the root rot fungus Heterobasidion annosum following thinning of Picea abies . Oikos 247–254. doi: 10.2307/3544811

Tarigan, M., Wingfield, M. J., van Wyk, M., Tjahjono, B., and Roux, J. (2011). Pruning quality affects infection of Acacia mangium and A. crassicarpa by Ceratocystis acaciivora and Lasiodiplodia theobromae . Southern Forests 73, 187–191. doi: 10.2989/20702620.2011.639498

Thies, W. G., Kelsey, R. G., Westlind, D. J., and Madsen, J. (2006). Potassium fertilizer applied immediately after planting had no impact on Douglas-fir seedling mortality caused by laminated root rot on a forested site in Washington State. For. Ecol. Manag. 229, 195–201. doi: 10.1016/j.foreco.2006.03.028

Thies, W. G., and Westlind, D. J. (2005). Stump removal and fertilization of five Phellinus weirii-infested stands in Washington and Oregon affect mortality and growth of planted Douglas-fir 25 years after treatment. For. Ecol. Manag. 219, 242–258. doi: 10.1016/j.foreco.2005.08.050

Thor, M., and Stenlid, J. (2005). Heterobasidion annosuminfection ofPicea abiesfollowing manual or mechanized stump treatment. Scand. J. Forest Res. 20, 154–164. doi: 10.1080/02827580510008338

Valachovic, Y., Cobb, R. C., Rizzo, D., Twieg, B., Lee, C., and Glebocki, R. (2013a). “Is stump sprout treatment necessary to effectively control Phytophthora ramorum in California;s wildlands, in Proceedings of the Sudden Oak Death Fifth Science Symposium (Albany, NY).

Valachovic, Y., Lee, C., Marshall, J., and Scanlon, H. (2010). “Forest treatment strategies for Phytophthora ramorum ,” in Proceedings of the Sudden Oak Death Fourth Science Symposium (Santa Cruz, CA), 239.

Valachovic, Y., Lee, C., Twieg, B., Rizzo, D., Cobb, R. C., and Glebocki, R. (2013b). “Suppression of Phytophthora ramorum infestation through silvicultural treatment in California's north coast,” in Proceedings of the Sudden Oak Death Fifth Science Symposium (Albany, NY).

van der Kamp, B. J. (1994). Lodgepole pine stem disease and management of stand density in the British Colombia interior. Forest. Chron. 70, 773–779. doi: 10.5558/tfc70773-6

Walker, B., Pearson, L., Harris, M., Maler, K. G., Li, C., Biggs, R., et al. (2010). Incorporating resilience in the assessment of inclusive wealth. Environ. Res. Econ. 45, 183–202. doi: 10.1007/s10640-009-9311-7

Ward, J. S., Anagnostakis, S., and Ferrandino, F. J. (2010). Nectria canker incidence on birch ( Betula spp.) in Connecticut. North. J. Appl. Forest. 27, 85–91. doi: 10.1093/njaf/27.3.85

Waring, K. M., and O'Hara, K. L. (2005). Silvicultural strategies in forest ecosystems affected by introduced pests. For. Ecol. Manag. 209, 27–41. doi: 10.1016/j.foreco.2005.01.008

Warren, C. (2007). Perspectives on the 'alien' vs 'native' species debate: a critique of concepts, language and practice. Progr. Hum. Geogr. 31, 427–446. doi: 10.1177/0309132507079499

Whitney, R. D., and Irwin, R. N. (2005). Comparison of Armillaria root disease on burned and unburned, harvested sites in Ontario. Forest. Chron. 81, 56–60. doi: 10.5558/tfc81056-1

Wingfield, M. J., Brockerhoff, E. G., Wingfield, B. D., and Slippers, B. (2015). Planted forest health: The need for a global strategy. Science 349, 832–836. doi: 10.1126/science.aac6674

Wingfield, M. J., Slippers, B., Wingfield, B. D., and Barnes, I. (2017). The unified framework for biological invasions: a forest fungal pathogen perspective. Biol. Invas . 19, 3201–3214. doi: 10.1007/s10530-017-1450-0

Wingfield, M. J., and Swart, W. J. (1994). Integrated management of forest tree diseasesin South-Africa For. Ecol. Manag. 65, 11–16. doi: 10.1016/0378-1127(94)90253-4

Woodward, S., Stenlid, J., Karjalainen, R., and Huttermann, A. (1998). Heterobasidion annosum Biology, Ecology, Impact and Control. Wallingford, CT: CAB International.

Zeglen, S., Pronos, J., and Merler, H. (2010). Silvicultural management of white pines in western North America. Forest Pathol. 40, 347–368. doi: 10.1111/j.1439-0329.2010.00662.x

Keywords: tree disease, epidemiology, forestry, pathogen, silviculture, forest management, invasive species, species diversity

Citation: Roberts M, Gilligan CA, Kleczkowski A, Hanley N, Whalley AE and Healey JR (2020) The Effect of Forest Management Options on Forest Resilience to Pathogens. Front. For. Glob. Change 3:7. doi: 10.3389/ffgc.2020.00007

Received: 25 June 2019; Accepted: 16 January 2020; Published: 10 February 2020.

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*Correspondence: Michaela Roberts, Michaela.roberts@hutton.ac.uk

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• Published: 09 November 2020

A global analysis of the social and environmental outcomes of community forests

• Reem Hajjar   ORCID: orcid.org/0000-0003-0219-7313 1 , 2   na1 ,
• Johan A. Oldekop   ORCID: orcid.org/0000-0003-0565-812X 2 , 3   na1 ,
• Peter Cronkleton 4 ,
• Peter Newton   ORCID: orcid.org/0000-0002-3992-0483 2 , 5 ,
• Aaron J. M. Russell   ORCID: orcid.org/0000-0002-0433-496X 6 , 7 &
• Wen Zhou 8  

Nature Sustainability volume  4 ,  pages 216–224 ( 2021 ) Cite this article

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Community forest management (CFM) has been promoted for decades as a way to merge environmental conservation with economic development and natural resource rights agendas. Yet many of these initiatives have also led to substantial socioeconomic and environmental trade-offs. We present a comprehensive global analysis of environmental, income and natural resource rights outcomes of CFM, using data from 643 cases in 51 countries. We find that while the majority of cases reported positive environmental and income-related outcomes, forest access and resource rights were often negatively affected by policies to formalize CFM, countering one of CFM’s principal goals. Positive outcomes across all three dimensions were rare. We show that biophysical conditions, de facto tenure rights, national context, user-group characteristics and intervention types are key predictors of joint positive outcomes. These findings highlight key conducive conditions for CFM interventions, which can inform CFM design to ensure positive outcomes across multiple sustainability dimensions.

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Houghton, R. A., Byers, B. & Nassikas, A. A. A role for tropical forests in stabilizing atmospheric CO 2 . Nat. Clim. Change 5 , 1022–1023 (2015).

Google Scholar  

Newton, P., Oldekop, J. A., Brodnig, G., Karna, B. K. & Agrawal, A. Carbon, biodiversity, and livelihoods in forest commons: synergies, trade-offs, and implications for REDD+. Environ. Res. Lett. 11 , 044017 (2016).

Angelsen, A. et al. Environmental income and rural livelihoods: a global-comparative analysis. World Dev. 64 , S12–S28 (2014).

Lund, J. F., Rutt, R. L. & Ribot, J. Trends in research on forestry decentralization policies. Curr. Opin. Environ. Sustain. 32 , 17–22 (2018).

At a Crossroads: Consequential Trends in Recognition of Community-Based Forest Tenure (Rights and Resources Initiative, 2018).

Ribot, J. C., Agrawal, A. & Larson, A. M. Recentralizing while decentralizing: how national governments reappropriate forest resources. World Dev. 34 , 1864–1886 (2006).

Charnley, S. & Poe, M. R. Community forestry in theory and practice: where are we now? Annu. Rev. Anthropol. 36 , 301–337 (2007).

Cronkleton, P., Pulhin, J. M. & Saigal, S. Co-management in community forestry: how the partial devolution of management rights creates challenges for forest communities. Conserv. Soc. 10 , 91–102 (2012).

Gilmour, D. Forty Years of Community-Based Forestry: A Review of Its Extent and Effectiveness (FAO, 2016).

Baynes, J., Herbohn, J., Smith, C., Fisher, R. & Bray, D. Key factors which influence the success of community forestry in developing countries. Glob. Environ. Change 35 , 226–238 (2015).

Chhatre, A. & Agrawal, A. Trade-offs and synergies between carbon storage and livelihood benefits from forest commons. Proc. Natl Acad. Sci. USA 106 , 17667–17670 (2009).

CAS   Google Scholar  

Persha, L., Agrawal, A. & Chhatre, A. Social and ecological synergy: local rulemaking, forest livelihoods, and biodiversity conservation. Science 331 , 1606–1608 (2011).

Rasolofoson, R. A. et al. Impacts of community forest management on human economic well-being across Madagascar. Conserv. Lett. 10 , 346–353 (2017).

Oldekop, J. A., Sims, K. R. E., Karna, B. K., Whittingham, M. J. & Agrawal, A. Reductions in deforestation and poverty from decentralized forest management in Nepal. Nat. Sustain. 2 , 421–428 (2019).

Agrawal, A. & Benson, C. S. Common property theory and resource governance institutions: strengthening explanations of multiple outcomes. Environ. Conserv. 38 , 199–210 (2011).

Larson, A., Barry, D. & Dahal, G. R. New rights for forest-based communities? Understanding processes of forest tenure reform. Int. For. Rev. 12 , 78–96 (2010).

Hajjar, R., Kozak, R. A. & Innes, J. L. Is decentralization leading to ‘real’ decision-making power for forest-dependent communities? Case studies from Mexico and Brazil. Ecol. Soc. 17 , 12 (2012).

Newton, P. et al. What Are the Biophysical, Institutional, and Socioeconomic Contextual Factors Associated with Improvements in Livelihood and Environmental Outcomes in Forests Managed by Communities? A Systematic Review Protocol Working Paper 9 (CIFOR, 2015); https://doi.org/10.17528/cifor/005494

Hajjar, R. et al. The data not collected on community forestry. Conserv. Biol. 30 , 1357–1362 (2016).

Vyamana, V. Participatory forest management in the Eastern Arc Mountains of Tanzania: who benefits? Int. For. Rev. 11 , 239–253 (2009).

Mohammed, A. J. & Inoue, M. Forest-dependent communities’ livelihood in decentralized forest governance policy epoch: case study from West Shoa zone, Ethiopia. J. Nat. Resour. Policy Res. 5 , 49–66 (2013).

Nielsen, M. Improving the conservation status of the Udzungwa Mountains, Tanzania? The effect of joint forest management on bushmeat hunting in the Kilombero Nature Reserve. Conserv. Soc. 9 , 106–118 (2011).

Gobeze, T., Bekele, M., Lemenih, M. & Kassa, H. Participatory forest management and its impacts on livelihoods and forest status: the case of Bonga Forest in Ethiopia. Int. For. Rev. 11 , 346–358 (2009).

Mishra, T., Mandal, D. & Maiti, S. Evaluation of regeneration of Shorea robusta forests under joint forest management in West Bengal, India. Int. J. Environ. Sustain. Dev. 5 , 12–22 (2006).

Oyono, P., Samba, S. & Biyong, M. Beyond the decade of policy and community euphoria: the state of livelihoods under new local rights to forest in rural Cameroon. Conserv. Soc. 10 , 173–181 (2012).

Oldekop, J. A., Holmes, G., Harris, W. E. & Evans, K. L. A global assessment of the social and conservation outcomes of protected areas. Conserv. Biol. 30 , 133–141 (2016).

White, I., Royston, P. & Wood, A. Multiple imputation by chained equations: issues and guidance for practice. Stat. Med. 30 , 377–399 (2011).

Leuschner, C., Moser, G., Bertsch, C., Röderstein, M. & Hertel, D. Large altitudinal increase in tree root/shoot ratio in tropical mountain forests of Ecuador. Basic Appl. Ecol. 8 , 219–230 (2007).

Thanichanon, P., Schmidt-Vogt, D., Messerli, P., Heinimann, A. & Epprecht, M. Secondary forests and local livelihoods along a gradient of accessibility: a case study in northern Laos. Soc. Nat. Resour. 26 , 1283–1299 (2013).

Schlager, E. & Ostrom, E. Property-rights regimes and natural resources: a conceptual analysis. Land Econ. 68 , 249–262 (1992).

Place, F. & Hazell, P. Productivity effects of Indigenous land tenure systems in sub-Saharan Africa. Am. J. Agric. Econ. 75 , 10–19 (1993).

Gibson, C., Lehoucq, F. & Williams, J. Does privatization protect natural resources? Property rights and forests in Guatemala. Soc. Sci. Q. 83 , 206–225 (2002).

Bugri, J. T. The dynamics of tenure security, agricultural production and environmental degradation in Africa: evidence from stakeholders in north-east Ghana. Land Use Policy 25 , 271–285 (2008).

Cronkleton, P. & Larson, A. Formalization and collective appropriation of space on forest frontiers: comparing communal and individual property systems in the Peruvian and Ecuadoran Amazon. Soc. Nat. Resour. 28 , 496–512 (2015).

Nayak, P. K. & Berkes, F. Politics of co-optation: community forest management versus joint forest management in Orissa, India. Environ. Manage. 41 , 707–718 (2008).

Berkes, F., George, P. & Preston, R. J. Co-management: the evolution in theory and practice of the joint administration of living resources. Alternatives 18 , 12–18 (1991).

Humphries, S., Holmes, T., de Andrade, D. F. C., McGrath, D. & Dantas, J. B. Searching for win–win forest outcomes: learning-by-doing, financial viability, and income growth for a community-based forest management cooperative in the Brazilian Amazon. World Dev. https://doi.org/10.1016/j.worlddev.2018.06.005 (2018).

Bray, D. B. et al. Mexico’s community-managed forests as a global model for sustainable landscapes. Conserv. Biol. 17 , 672–677 (2003).

Balooni, K., Pulhin, J. & Inoue, M. When is Decentralization in Forest Management a Success and when is it a Failure? Case Studies from the Philippines (Indiana Univ., 2007).

Oldekop, J. A., Bebbington, A. J., Brockington, D. & Preziosi, R. F. Understanding the lessons and limitations of conservation and development. Conserv. Biol. 24 , 461–469 (2010).

Rudel, T. K. et al. Forest transitions: towards a global understanding of land use change. Glob. Environ. Change 15 , 23–31 (2005).

Erbaugh, J. T. & Oldekop, J. A. Forest landscape restoration for livelihoods and well-being. Curr. Opin. Environ. Sustain. 32 , 76–83 (2018).

Honey-Rosés, J., Maurer, M., Ramírez, M. I. & Corbera, E. Quantifying active and passive restoration in Central Mexico from 1986–2012: assessing the evidence of a forest transition. Restor. Ecol. 26 , 1180–1189 (2018).

Oldekop, J. A., Sims, K. R. E., Whittingham, M. J. & Agrawal, A. An upside to globalization: international outmigration drives reforestation in Nepal. Glob. Environ. Change 52 , 66–74 (2018).

Peluso, N. L. & Purwanto, A. B. The remittance forest: turning mobile labor into agrarian capital. Singap. J. Trop. Geogr. 39 , 6–36 (2018).

Sikor, T. & Nguyen, T. Q. Why may forest devolution not benefit the rural poor? Forest entitlements in Vietnam’s central highlands. World Dev. 35 , 2010–2025 (2007).

Pulhin, J. M. & Dressler, W. H. People, power and timber: the politics of community-based forest management. J. Environ. Manage. 91 , 206–214 (2009).

Jones, J. P. G. et al. Human migration to the forest frontier: implications for land use change and conservation management. Geo 5 , e00050 (2018).

Robson, J. P. & Berkes, F. Exploring some of the myths of land use change: can rural to urban migration drive declines in biodiversity? Glob. Environ. Change 21 , 844–854 (2011).

Brooks, J. S., Waylen, K. A. & Borgerhoff Mulder, M. How national context, project design, and local community characteristics influence success in community-based conservation projects. Proc. Natl Acad. Sci. USA 109 , 21265–21270 (2012).

Larson, A. M. & Soto, F. Decentralization of natural resource governance regimes. Annu. Rev. Environ. Resour. 33 , 213–239 (2008).

Anderson, J., Mehta, S., Epelu, E. & Cohen, B. Managing leftovers: does community forestry increase secure and equitable access to valuable resources for the rural poor? For. Policy Econ. 58 , 47–55 (2015).

Thanh, T. N. & Sikor, T. From legal acts to actual powers: devolution and property rights in the Central Highlands of Vietnam. For. Policy Econ. 8 , 397–408 (2006).

Larson, A. M., Cronkleton, P., Barry, D. & Pacheco, P. Tenure Rights and Beyond: Community Access to Forest Resources in Latin America (CIFOR, 2008).

Scheba, A. & Mustalahti, I. Rethinking ‘expert’ knowledge in community forest management in Tanzania. For. Policy Econ. 60 , 7–18 (2015).

Ameha, A., Nielsen, O. J. & Larsen, H. O. Impacts of access and benefit sharing on livelihoods and forest: case of participatory forest management in Ethiopia. Ecol. Econ. 97 , 162–171 (2014).

Lescuyer, G. Sustainable forest management at the local scale: a comparative analysis of community forests and domestic forests in Cameroon. Small-scale For. 12 , 51–66 (2013).

Guiang, E. S. & Castillo, G. Trends in forest ownership, forest resoures tenure and institutional arrangements in the Philippines: Are they contributing to better forest management and poverty reduction? (FAO, 2007).

Blackman, A., Corral, L., Lima, E. S. & Asner, G. P. Titling Indigenous communities protects forests in the Peruvian Amazon. Proc. Natl Acad. Sci. USA 114 , 4123–4128 (2017).

Sikor, T. et al. Community Forestry in Asia and the Pacific: Pathway to Inclusive Development (RECOFTC - The Center for People and Forests, 2013).

Wren-Lewis, L., Becerra-Valbuena, L. & Houngbedji, K. Formalizing land rights can reduce forest loss: experimental evidence from Benin. Sci. Adv. 6 , eabb6914 (2020).

Ostrom, E. Governing the Commons: The Evolution of Institutions for Collective Action (Cambridge Univ. Press, 1990).

Varughese, G. & Ostrom, E. The contested role of heterogeneity in collective action: some evidence from community forestry in Nepal. World Dev. 29 , 747–765 (2001).

Lambin, E. F. & Meyfroidt, P. Global land use change, economic globalization, and the looming land scarcity. Proc. Natl Acad. Sci. USA 108 , 3465–3472 (2011).

Scherr, S. J., White, A. & Kaimowitz, D. Making markets work for forest communities. Int. For. Rev. 5 , 67–73 (2003).

Agrawal, A. Forests, governance, and sustainability: common property theory and its contributions. Int. J. Commons 1 , 111–136 (2007).

Pagdee, A., Kim, Y. & Daugherty, P. J. What makes community forest management successful: a meta-study from community forests throughout the world. Soc. Nat. Resour. 19 , 33–52 (2006).

Hajjar, R. & Oldekop, J. A. Research frontiers in community forest management. Curr. Opin. Environ. Sustain. 32 , 119–125 (2018).

Methods (IFRI, 2013); http://ifri.forgov.org/resources/methods/

Persha, L., Fischer, H., Chhatre, A., Agrawal, A. & Benson, C. Biodiversity conservation and livelihoods in human-dominated landscapes: forest commons in South Asia. Biol. Conserv. 143 , 2918–2925 (2010).

Geist, H. J. & Lambin, E. F. Proximate causes and underlying driving forces of tropical deforestation. BioScience 52 , 143–150 (2002).

Rana, E., Thwaites, R. & Luck, G. Trade-offs and synergies between carbon, forest diversity and forest products in Nepal community forests. Environ. Conserv. 44 , 5–13 (2017).

Liaw, A. & Wiener, M. R Package ‘randomForest’ (The Comprehensive R Archive Network, 2018).

Breiman, L. Random forests. Mach. Learn. 45 , 5–32 (2001).

Genuer, R., Poggi, J. & Tuleau-Malot, C. Variable selection using random forests. Pattern Recognit. Lett. 31 , 2225–2236 (2010).

Harrell, F. Regression Modelling Strategies (Springer, 2015).

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Acknowledgements

We thank the Evidence Based Forestry Initiative at the Centre for International Forestry Research (CIFOR) and the UK Department for International Development (DfID) for financing this research through its KNOWFOR programme grant. J.A.O. was supported through an EU FP7 Marie Curie Fellowship (FORCONEPAL). P.C. was supported through the CGIAR Research Program on Forest, Trees and Agroforestry (FTA), led by CIFOR. We also thank M. Vikas, M. Burbidge, A. Langeland and K. Gregory for their help in screening papers and extracting data and G. Steward, M. Grainger, M. Whittingham, R. Preziosi and E. W. Harris for their help with the statistical analysis.

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These authors contributed equally: Reem Hajjar, Johan A. Oldekop.

Authors and Affiliations

Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR, USA

Reem Hajjar

Forests and Livelihoods: Assessment, Research, and Engagement (FLARE) network, School for Environment and Sustainability, University of Michigan, Ann Arbor, MI, USA

Reem Hajjar, Johan A. Oldekop & Peter Newton

Global Development Institute, The University of Manchester, Manchester, UK

Johan A. Oldekop

Center for International Forestry Research, La Molina, Lima, Peru

Peter Cronkleton

Environmental Studies Program, University of Colorado Boulder, Sustainability, Energy and Environment Community, Boulder, CO, USA

Peter Newton

Center for International Forestry Research, Jalan CIFOR, Situ Gede, Bogor Barat, Indonesia

Aaron J. M. Russell

Global Green Growth Institute, Naypyitaw, Myanmar

Yale School of the Environment and Department of Anthropology, Yale University, New Haven, CT, USA

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R.H., J.A.O., P.N., A.J.M.R. and W.Z. conceived and designed the systematic review. R.H., J.A.O. and W.Z. conducted the review and data extraction. R.H. and J.A.O. conducted the analysis and drafted the manuscript. R.H., J.A.O., P.C., P.N., A.J.M.R. and W.Z. contributed to results interpretation and finalizing of the paper.

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Hajjar, R., Oldekop, J.A., Cronkleton, P. et al. A global analysis of the social and environmental outcomes of community forests. Nat Sustain 4 , 216–224 (2021). https://doi.org/10.1038/s41893-020-00633-y

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• Bettley, A.; Burnley, S. Towards sustainable operations management integrating sustainability management into operations management strategies and practices. In Handbook of Performability Engineering ; Springer: London, UK, 2008; pp. 875–904. [ Google Scholar ]
• Gunasekaran, A.; Irani, Z. Sustainable operations management: Design, modelling and analysis. J. Oper. Res. Soc. 2014 , 65 , 801–805. [ Google Scholar ] [ CrossRef ]
• Kleindorfer, P.R.; Singhal, K.; Van Wassenhove, L.N. Sustainable operations management. Prod. Oper. Manag. 2005 , 14 , 482–492. [ Google Scholar ] [ CrossRef ]
• Solomon, B.D.; Krishna, K. The coming sustainable energy transition: History, strategies, and outlook. Energy Policy 2011 , 39 , 7422–7431. [ Google Scholar ] [ CrossRef ]
• Environmental Protection Agency. Global Greenhouse Gas Overview. 2023. Available online: https://www.epa.gov/ghgemissions/global-greenhouse-gas-overview (accessed on 25 July 2024).
• Intergovernmental Panel on Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Mitigation of Climate Change, Chapter 2; IPCC, 2022. Data from IPCC (2022); Based on Global Emissions from 2019, Details on the Sectors and Individual Contributing Sources. Available online: https://www.ipcc.ch/report/ar6/wg3/ (accessed on 25 July 2024).
• Fouquet, R. The slow search for solutions: Lessons from historical energy transitions by sector and service. Energy Policy 2010 , 38 , 6586–6596. [ Google Scholar ] [ CrossRef ]
• Kuzemko, C.; Lockwood, M.; Mitchell, C.; Hoggett, R. Governing for sustainable energy system change: Politics, contexts and contingency. Energy Res. Soc. Sci. 2016 , 12 , 96–105. [ Google Scholar ] [ CrossRef ]
• Atasu, A.; Corbett, C.J.; Huang, X.; Toktay, L.B. Sustainable operations management through the perspective of manufacturing & service operations management. Manuf. Serv. Oper. Manag. 2020 , 22 , 146–157. [ Google Scholar ]
• Seuring, S.; Müller, M. Core issues in sustainable supply chain management–a Delphi study. Bus. Strategy Environ. 2008 , 17 , 455–466. [ Google Scholar ] [ CrossRef ]
• Rajeev, A.; Pati, R.K.; Padhi, S.S.; Govindan, K. Evolution of sustainability in supply chain management: A literature review. J. Clean. Prod. 2017 , 162 , 299–314. [ Google Scholar ] [ CrossRef ]
• Touboulic, A.; Walker, H. Theories in sustainable supply chain management: A structured literature review. Int. J. Phys. Distrib. Logist. Manag. 2015 , 45 , 16–42. [ Google Scholar ] [ CrossRef ]
• Kraus, S.; Breier, M.; Lim, W.M.; Dabić, M.; Kumar, S.; Kanbach, D.; Mukherjee, D.; Corvello, V.; Piñeiro-Chousa, J.; Liguori, E.; et al. Literature reviews as independent studies: Guidelines for academic practice. Rev. Manag. Sci. 2022 , 16 , 2577–2595. [ Google Scholar ] [ CrossRef ]
• Dabić, M.; Vlačić, B.; Kiessling, T.; Caputo, A.; Pellegrini, M. Serial entrepreneurs: A review of literature and guidance for future research. J. Small Bus. Manag. 2023 , 61 , 1107–1142. [ Google Scholar ] [ CrossRef ]
• Ghazanfari, A. An analysis of circular economy literature at the macro level, with a particular focus on energy markets. Energies 2023 , 16 , 1779. [ Google Scholar ] [ CrossRef ]
• Giri, B.K.; Roy, S.K. Fuzzy-random robust flexible programming on sustainable closed-loop renewable energy supply chain. Appl. Energy 2024 , 363 , 123044. [ Google Scholar ] [ CrossRef ]
• Annunziata, E.; Rizzi, F.; Frey, M. How do firms interpret extended responsibilities for a sustainable supply chain management of innovative technologies? An analysis of corporate sustainability reports in the energy sector. Sinergie Ital. J. Manag. 2019 , 37 , 57–74. [ Google Scholar ] [ CrossRef ]
• Le Luu, Q.; Longo, S.; Cellura, M.; Riva Sanseverino, E.; Cusenza, M.A.; Franzitta, V. A conceptual review on using consequential life cycle assessment methodology for the energy sector. Energies 2020 , 13 , 3076. [ Google Scholar ] [ CrossRef ]
• Pender, K.; Romoli, F.; Fuller, J. Lifecycle assessment of strategies for decarbonising wind blade recycling toward net zero 2050. Energies 2024 , 17 , 3008. [ Google Scholar ] [ CrossRef ]
• Yudha, S.W.; Tjahjono, B. Stakeholder mapping and analysis of the renewable energy industry in Indonesia. Energies 2019 , 12 , 602. [ Google Scholar ] [ CrossRef ]
• Yudha, S.W.; Tjahjono, B.; Longhurst, P. Sustainable transition from fossil fuel to geothermal energy: A multi-level perspective approach. Energies 2022 , 15 , 7435. [ Google Scholar ] [ CrossRef ]
• Ahmad, W.; Rezaei, J.; de Brito, M.P.; Tavasszy, L.A. The influence of external factors on supply chain sustainability goals of the oil and gas industry. Resour. Policy 2016 , 49 , 302–314. [ Google Scholar ] [ CrossRef ]
• Barton, J.; Davies, L.; Dooley, B.; Foxon, T.J.; Galloway, S.; Hammond, G.P.; O’Grady, A.; Robertson, E.; Thomson, M. Transition pathways for a UK low-carbon electricity system: Comparing scenarios and technology implications. Renew. Sustain. Energy Rev. 2018 , 82 , 2779–2790. [ Google Scholar ] [ CrossRef ]
• Subtil Lacerda, J.; Van den Bergh, J.C. International diffusion of renewable energy innovations: Lessons from the lead markets for wind power in China, Germany and USA. Energies 2014 , 7 , 8236–8263. [ Google Scholar ] [ CrossRef ]
• Krishankumar, R.; Ramanujam, N.; Zavadskas, E.K.; Ravichandran, K.S.; Gandomi, A.H. Ranking barriers impeding sustainability adoption in clean energy supply chains: A hybrid framework with Fermatean fuzzy data. IEEE Trans. Eng. Manag. 2024 , 71 , 5506–5522. [ Google Scholar ] [ CrossRef ]
• Hecht, A.D.; Miller, C.A. Perspectives on achieving sustainable energy production and use. J. Renew. Sustain. Energy 2010 , 2 , 031002. [ Google Scholar ] [ CrossRef ]
• Yassin, A.M.M.; Hassan, M.A.; Elmesmary, H.M. Key elements of green supply chain management drivers and barriers empirical study of solar energy companies in South Egypt. Int. J. Energy Sect. Manag. 2022 , 16 , 564–584. [ Google Scholar ] [ CrossRef ]
• Duggal, K.; Rangachari, R.; Gupta, K. Consequences of crisis and the great re-think: COVID-19’s impact on energy investment, sustainability and the future of international investment agreements. J. World Energy Law Bus. 2021 , 14 , 133–146. [ Google Scholar ] [ CrossRef ]
• Rehme, J.; Nordigården, D.; Chicksand, D. Public policy and electrical-grid sector innovation. Int. J. Energy Sect. Manag. 2015 , 9 , 565–592. [ Google Scholar ] [ CrossRef ]
• Vavatsikos, A.P.; Tsesmetzis, E.; Koulinas, G.; Koulouriotis, D. A robust group decision making framework using fuzzy TOPSIS and Monte Carlo simulation for wind energy projects multicriteria evaluation. Oper. Res. 2022 , 22 , 6055–6073. [ Google Scholar ] [ CrossRef ]
• Attia, A.M. A multi-objective robust optimization model for upstream hydrocarbon supply chain. Alex. Eng. J. 2021 , 60 , 5115–5127. [ Google Scholar ] [ CrossRef ]
• Ziolo, M.; Bak, I.; Spoz, A. Incorporating ESG risk in companies’ business models: State of research and energy sector case studies. Energies 2023 , 16 , 1809. [ Google Scholar ] [ CrossRef ]
• Gamarra, A.R.; Lechón, Y.; Escribano, G.; Lilliestam, J.; Lázaro, L.; Caldés, N. Assessing dependence and governance as value chain risks: Natural gas versus concentrated solar power plants in Mexico. Environ. Impact Assess. Rev. 2022 , 93 , 106708. [ Google Scholar ] [ CrossRef ]
• Balaman, S.Y.; Scott, J.; Matopoulos, A.; Wright, D.G. Incentivising bioenergy production: Economic and environmental insights from a regional optimization methodology. Renew. Energy 2019 , 130 , 867–880. [ Google Scholar ] [ CrossRef ]
• Sun, I.; Kim, S.Y. Energy R&D towards sustainability: A panel analysis of government budget for energy R&D in OECD countries (1974–2012). Sustainability 2017 , 9 , 617. [ Google Scholar ] [ CrossRef ]
• Papageorgiou, K.; Carvalho, G.; Papageorgiou, E.I.; Bochtis, D.; Stamoulis, G. Decision-making process for photovoltaic solar energy sector development using fuzzy cognitive map technique. Energies 2020 , 13 , 1427. [ Google Scholar ] [ CrossRef ]
• Subramanian, A.S.R.; Gundersen, T.; Adams, T.A. Modeling and simulation of energy systems: A review. Processes 2018 , 6 , 238. [ Google Scholar ] [ CrossRef ]
• Jelti, F.; Allouhi, A.; Buker, M.S.; Saadani, R.; Jamil, A. Renewable power generation: A supply chain perspective. Sustainability 2021 , 13 , 1271. [ Google Scholar ] [ CrossRef ]
• Generalov, O. Analysis of modern trends and opportunities in the logistics channels of energy products producers. Balt. J. Econ. Stud. 2024 , 10 , 39–43. [ Google Scholar ] [ CrossRef ]
• Halldórsson, A.; Svanberg, M. Energy resources: Trajectories for supply chain management. Supply Chain.-Manag.- Int. J. 2013 , 18 , 66–73. [ Google Scholar ] [ CrossRef ]
• Goodwin, D.; Gale, F.; Lovell, H.; Beasy, K.; Murphy, H.; Schoen, M. Sustainability certification for renewable hydrogen: An international survey of energy professionals. Energy Policy 2024 , 192 , 114231. [ Google Scholar ] [ CrossRef ]
• Hasheminasab, H.; Gholipour, Y.; Kharrazi, M.; Streimikiene, D. Life cycle approach in sustainability assessment for petroleum refinery projects with fuzzy-AHP. Energy Environ. 2018 , 29 , 1208–1223. [ Google Scholar ] [ CrossRef ]
• Sueyoshi, T.; Wang, D. Radial and non-radial approaches for environmental assessment by data envelopment analysis: Corporate sustainability and effective investment for technology innovation. Energy Econ. 2014 , 45 , 537–551. [ Google Scholar ] [ CrossRef ]
• Balaman, S.Y. Investment planning and strategic management of sustainable systems for clean power generation: An ϵ -constraint based multi objective modelling approach. J. Clean. Prod. 2016 , 137 , 1179–1190. [ Google Scholar ] [ CrossRef ]
• Yu, J. Factors affecting return on assets in the renewable energy sector during supply chain disruptions. J. Risk Financ. Manag. 2024 , 17 , 253. [ Google Scholar ] [ CrossRef ]
• Mastrocinque, E.; Ramírez, F.J.; Honrubia-Escribano, A.; Pham, D.T. Industry 4.0 enabling sustainable supply chain development in the renewable energy sector: A multi-criteria intelligent approach. Technol. Forecast. Soc. Chang. 2022 , 182 , 121813. [ Google Scholar ] [ CrossRef ]
• Ma, J.Q.; Yuan, Y.; Zhao, S.N.; Wu, W. Research on sustainability evaluation of China’s coal supply chain from the perspective of dual circulation new development pattern. Sustainability 2022 , 14 , 9129. [ Google Scholar ] [ CrossRef ]
• Smith, A.D. Alternative energy supply chain management issues: Wind generation considerations in Ohio. Int. J. Serv. Oper. Manag. 2015 , 21 , 200–216. [ Google Scholar ] [ CrossRef ]
• Lundie, S.; Wiedmann, T.; Welzel, M.; Busch, T. Global supply chains hotspots of a wind energy company. J. Clean. Prod. 2019 , 210 , 1042–1050. [ Google Scholar ] [ CrossRef ]
• Vilkaite-Vaitone, N.; Skackauskiene, I.; Diaz-Meneses, G. Measuring green marketing: Scale development and validation. Energies 2022 , 15 , 718. [ Google Scholar ] [ CrossRef ]
• Biswal, J.N.; Muduli, K.; Satapathy, S.; Yadav, D.K. A TISM based study of SSCM enablers: An Indian coal- fired thermal power plant perspective. Int. J. Syst. Assur. Eng. Manag. 2019 , 10 , 126–141. [ Google Scholar ] [ CrossRef ]
• Xu, X.L.; Chen, H.H. Exploring the relationships between environmental management and financial sustainability in the energy industry: Linear and nonlinear effects. Energy Environ. 2020 , 31 , 1281–1300. [ Google Scholar ] [ CrossRef ]
• Matos, S.; Silvestre, B.S. Managing stakeholder relations when developing sustainable business models: The case of the Brazilian energy sector. J. Clean. Prod. 2013 , 45 , 61–73. [ Google Scholar ] [ CrossRef ]
• Okongwu, U.; Morimoto, R.; Lauras, M. The maturity of supply chain sustainability disclosure from a continuous improvement perspective. INternational J. Product. Perform. Manag. 2013 , 62 , 827–855. [ Google Scholar ] [ CrossRef ]
• Ghobakhloo, M.; Fathi, M. Industry 4.0 and opportunities for energy sustainability. J. Clean. Prod. 2021 , 295 , 126427. [ Google Scholar ] [ CrossRef ]
• Labaran, M.J.; Masood, T. Industry 4.0 driven green supply chain management in renewable energy sector: A critical systematic literature review. Energies 2023 , 16 , 6977. [ Google Scholar ] [ CrossRef ]
• Dudin, M.N.; Frolova, E.E.; Protopopova, O.V.; Mamedov, A.A.; Odintsov, S.V. Study of innovative technologies in the energy industry: Nontraditional and renewable energy sources. Entrep. Sustain. Issues 2019 , 6 , 1704–1713. [ Google Scholar ] [ CrossRef ]
• Li, B. Leading role of natural resources, eco-efficiency assessment, and energy transition in environmental sustainability: A depth of digital transformation. Resour. Policy 2024 , 94 , 105145. [ Google Scholar ] [ CrossRef ]
• Chen, H.H.; Lee, A.H.; Chen, S. Strategic policy to select suitable intermediaries for innovation to promote PV solar energy industry in China. Appl. Energy 2014 , 115 , 429–437. [ Google Scholar ] [ CrossRef ]
• Annunziata, E.; Rizzi, F.; Frey, M. The supporting role of business models in the promotion of sustainable innovations in the energy sector: An explorative study in the Italian SMEs. Sinergie Ital. J. Manag. 2020 , 38 , 131–146. [ Google Scholar ] [ CrossRef ]
• Haiyun, C.; Zhixiong, H.; Yüksel, S.; Dinçer, H. Analysis of the innovation strategies for green supply chain management in the energy industry using the QFD-based hybrid interval valued intuitionistic fuzzy decision approach. Renew. Sustain. Energy Rev. 2021 , 143 , 110844. [ Google Scholar ] [ CrossRef ]
• García-Orozco, S.; Vargas-Gutiérrez, G.; Ordóñez-Sánchez, S.; Silva, R. Using multi-criteria decision making in quality function deployment for offshore renewable energies. Energies 2023 , 16 , 6533. [ Google Scholar ] [ CrossRef ]
• Masoomi, B.; Sahebi, I.G.; Ghobakhloo, M.; Mosayebi, A. Do industry 5.0 advantages address the sustainable development challenges of the renewable energy supply chain? Sustain. Prod. Consum. 2023 , 43 , 94–112. [ Google Scholar ] [ CrossRef ]
• Nassani, A.A.; Hussain, H.; Condrea, E.; Grigorescu, A.; Yousaf, Z.; Haffar, M. Zero waste management: Investigation of green technology, the green supply chain, and the moderating role of CSR intentions. Sustainability 2023 , 15 , 4169. [ Google Scholar ] [ CrossRef ]
• Efthymiopoulos, N.; Makris, P.; Tsaousoglou, G.; Steriotis, K.; Vergados, D.J.; Khaksari, A.; Herre, L.; Lacort, V.; Martinez, G.; Lorente, E.L.; et al. FLEXGRID–a novel smart grid architecture that facilitates high-RES penetration through innovative flexibility markets towards efficient stakeholder interaction. Open Res. Eur. 2021 , 1 , 128. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Aziz, N.; Hanafiah, M.M.; Gheewala, S.H.; Ismail, H. Bioenergy for a cleaner future: A case study of sustainable biogas supply chain in the Malaysian energy sector. Sustainability 2020 , 12 , 3213. [ Google Scholar ] [ CrossRef ]
• Ibn-Mohammed, T.; Koh, S.C.L.; Reaney, I.M.; Acquaye, A.; Schileo, G.; Mustapha, K.B.; Greenough, R. Perovskite solar cells: An integrated hybrid lifecycle assessment and review in comparison with other photovoltaic technologies. Renew. Sustain. Energy Rev. 2017 , 80 , 1321–1344. [ Google Scholar ] [ CrossRef ]
• Dobrowolski, Z. Internet of things and other e-solutions in supply chain management may generate threats in the energy sector—The quest for preventive measures. Energies 2021 , 14 , 5381. [ Google Scholar ] [ CrossRef ]
• Wu, Y.; Wu, Y.; Cimen, H.; Vasquez, J.C.; Guerrero, J.M. Towards collective energy community: Potential roles of microgrid and blockchain to go beyond P2P energy trading. Appl. Energy 2022 , 314 , 119003. [ Google Scholar ] [ CrossRef ]
• Cader, J.; Koneczna, R.; Smol, M. Corporate social responsibility as a significant factor of competitive advantage-a case study of energy companies in Poland. Energy Rep. 2022 , 8 , 7989–8001. [ Google Scholar ] [ CrossRef ]
• Hmouda, A.M.O.; Orzes, G.; Sauer, P.C. Sustainable supply chain management in energy production: A literature review. Renew. Sustain. Energy Rev. 2024 , 191 , 114085. [ Google Scholar ] [ CrossRef ]
• Nair, P.U.; Thankamony, P. Social issues in supply chain sustainability–focus areas for energy and manufacturing sectors in India and USA. Eur. J. Sustain. Dev. 2021 , 10 , 495. [ Google Scholar ] [ CrossRef ]
• AlKhars, M.; Masoud, M.; AlNasser, A.; Alsubaie, M. Sustainable practices and firm competitiveness: An empirical analysis of the Saudi Arabian energy sector. Discov. Sustain. 2024 , 5 , 146. [ Google Scholar ] [ CrossRef ]
• Gardas, B.B.; Mangla, S.K.; Raut, R.D.; Narkhede, B.; Luthra, S. Green talent management to unlock sustainability in the oil and gas sector. J. Clean. Prod. 2019 , 229 , 850–862. [ Google Scholar ] [ CrossRef ]
• Afshari, H.; Agnihotri, S.; Searcy, C.; Jaber, M.Y. Social sustainability indicators: A comprehensive review with application in the energy sector. Sustain. Prod. Consum. 2022 , 31 , 263–286. [ Google Scholar ] [ CrossRef ]
• Muduli, K.; Kusi-Sarpong, S.; Yadav, D.K.; Gupta, H.; Jabbour, C.J.C. An original assessment of the influence of soft dimensions on implementation of sustainability practices: Implications for the thermal energy sector in fast growing economies. Oper. Manag. Res. 2021 , 14 , 337–358. [ Google Scholar ] [ CrossRef ]
• Botnar, W.L.; Frederico, G.F. Industry 4.0 in the electric sector: Findings from a systematic review of the literature. Electr. J. 2023 , 36 , 107337. [ Google Scholar ] [ CrossRef ]

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Losada-Agudelo, M.; Souyris, S. Sustainable Operations Management in the Energy Sector: A Comprehensive Review of the Literature from 2000 to 2024. Sustainability 2024 , 16 , 7999. https://doi.org/10.3390/su16187999

Losada-Agudelo M, Souyris S. Sustainable Operations Management in the Energy Sector: A Comprehensive Review of the Literature from 2000 to 2024. Sustainability . 2024; 16(18):7999. https://doi.org/10.3390/su16187999

Losada-Agudelo, Mariana, and Sebastian Souyris. 2024. "Sustainable Operations Management in the Energy Sector: A Comprehensive Review of the Literature from 2000 to 2024" Sustainability 16, no. 18: 7999. https://doi.org/10.3390/su16187999

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A global systematic review of forest management institutions: towards a new research agenda

Jude ndzifon kimengsi.

1 Forest Institutions and International Development (FIID) Research Group, Chair of Tropical and International Forestry, Faculty of Environmental Sciences, Technische Universität Dresden, Dresden, Germany

2 Department of Geography, The University of Bamenda, Bamenda, Cameroon

Raphael Owusu

Shambhu charmakar, gordon manu.

3 Food and Agricultural Organization (FAO), Rome, Italy

Lukas Giessen

4 Chair of Tropical and International Forestry, Faculty of Environmental Sciences, Technische Universität Dresden, Dresden, Germany

Associated Data

Globally, forest landscapes are rapidly transforming, with the role of institutions as mediators in their use and management constantly appearing in the literature. However, global comparative reviews to enhance comprehension of how forest management institutions (FMIs) are conceptualized, and the varying determinants of compliance, are lacking. And so too, is there knowledge fragmentation on the methodological approaches which have and should be prioritized in the new research agenda on FMIs.

We review the regional variations in the conceptualization of FMIs, analyze the determinants of compliance with FMIs, and assess the methodological gaps applied in the study of FMIs.

A systematic review of 197 empirically conducted studies (491 cases) on FMIs was performed, including a directed content analysis.

First, FMIs literature is growing; multi-case and multi-country studies characterize Europe/North America, Africa and Latin America, over Asia. Second , the structure-process conceptualization of FMIs predominates in Asia and Africa. Third , global south regions report high cases of compliance with informal FMIs, while non-compliance was registered for Europe/North America in the formal domain. Finally, m ixed-methods approaches have been least employed in the studies so far; while the use of only qualitative methods increased over time, the adoption of only quantitative approaches witnessed a decrease.

Future research should empirically ground informality in the institutional set-up of Australia while also valorizing mixed-methods research globally. Crucially, future research should consider multidisciplinary and transdisciplinary approaches to explore the actor and power dimensions of forest management institutions.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10980-022-01577-8.

Introduction

Globally, forests are at a crossroads—characterized by rapid transformation (Garcia et al. 2020 ). For instance, Global Forest Watch estimated that forest loss around the globe reached 29.7 million hectares as of 2016, indicating a 51% increase since 2015. For tropical forests, the loss was estimated at 12 million hectares (the size of Belgium) in 2018 (Weisse and Goldman 2017 ; Garcia et al. 2020 ). While such changes are linked to natural (e.g., climate change) and human-induced drivers such as land-use change (Rounsevell et al. 2006 ; Meyfroidt and Lambin 2011 ; Aguiar et al. 2016 ; Houghton and Nassikas 2018 ), they form part of a complex transformation system—mediated by socio-economic, political, and institutional forces (Malhi et al. 2014 ). This validates the role of institutions as a key enhancing or constraining factor in determining forest resources access, use and management (Cleaver 2017 ). Institutions are viewed as highly abstract and invisible conditions in the political environment. They constitute cognitive, normative, and regulatory structures which provide stability and meaning to social behaviour. Institutions are carried across multiple vehicles, including cultures, structures and routines, operating at multiple levels of jurisdiction (Scott 1995 ). The transformation of forest landscapes at various timescales is characterized by net tropical forest loss (Geist and Lambin 2002 ; Kissinger et al. 2012 ; Song et al. 2018 ). Furthermore, regional variations in the drivers (Curtis et al. 2018 ) exist: in Latin America, transformations are largely rooted in ranching and soybean expansion (Rudel et al. 2009 ; Verburg et al. 2014 ; Tyukavina et al. 2017 ), while subsistence agriculture drives the transformation process in Africa (Hosonuma et al. 2012 ; Tyukavina et al. 2018 ). Transformations in Asia are significantly linked to industrial processes and small-holder farming (Rudel et al. 2009 ; Turubanova et al. 2018 ).

While forests are declining (Weisse and Goldman 2017 ), their roles in the resolution of global socio-ecological challenges (e.g., climate change mitigation and poverty reduction) remain unrivalled (Oldekop et al. 2020 ; Nerfa et al. 2020 ). Scholars submit that governance mechanisms, especially the role of institutions, remain primordial in shaping forests access, use, and management. For this reason, institutions—the rules of the game—continually gain relevance (Agrawal and Gupta 2005 ; Dixon and Wood 2007 ; Kimengsi et al. 2021 ). Variations exist in the way institutions are conceptualized. For instance, following the structure process dichotomy (Fleetwood 2008a , b ), institutions relate to tissues of social relations linking groups and communities (structures) and a set of rules, conventions and values, among others (processes) (Fleetwood 2008a ; Bernardi et al. 2007 ). It is, however, difficult to provide a dividing line between the processes and structures; processes (rules) guide the formation of structures, while structures, on the other hand, oversee and enforce rules (Fleetwood 2008a ; Ntuli et al. 2021 ). However, structures differ from processes in terms of their functioning; structures could represent forest management organizations as an entity, and not the rules (processes) which they produce (Ntuli et al. 2021 ). Both structures and processes are subjected to a categorization as either formal (written and codified laws, largely state driven) and informal (unwritten or uncodified rules that transcend generations) (Osei-Tutu et al . 2014 ; Yeboah-Assiamah et al. 2017 ). Furthermore, and on the basis of source, institutions could be categorized following the endogenous—exogenous dichotomy; the former relates to community-specific complex and embedded rules, while the latter denotes institutions introduced by the state and international agencies (Yeboah-Assiamah et al. 2017 ; Kimengsi et al. 2022a , b , c ). By and large, these categories of institutions exist to provide order in the midst of ‘chaos’, with regards to the sustainable management of forest resources (Beunen and Patterson 2019 ).

While forest landscapes are transforming, institutions have also been subjected to several dimensions of change. Their evolution over time manifests through formation, reformation, disintegration, and modification in several contexts, including Africa (Haller et al. 2016 ; Friman 2020 ; Kimengsi et al. 2022a , b , c ), Asia (Haapal and White 2018 ; Steenbergen and Warren 2018 ), and Latin America (Faggin and Behagel 2018 ; Gebara 2019 ). This brings to fore the notion of ephemeral, intermittent and perennial institutions (Kimengsi et al. 2021 )—borrowed from the geographic classification of streams (Gomes et al. 2020 ). Ephemeral refers to short-term stream movements (institutional arrangements), intermittent is analogous to medium-term/seasonal streams (medium-term institutional arrangements), and perennial relates to streams that flow all through—analogous to more long-term, enduring institutions (Kimengsi et al. 2021 ). Therefore, the search for perennial (enduring) institutions is top on the scientific and policy agenda (Ostrom 1990 ; Kimengsi et al. 2021 ). This is important to support the attainment of objectives such as halting forest loss and improving forest cover and species diversity (Bare et al. 2015 ; Assa 2018 ), sustaining livelihoods and economic welfare (Buchenrieder and Balgah 2013 ; Foundjem-Tita et al. 2018 ), and engendering equity and fairness in the distribution of proceeds from forest systems (Faye et al. 2017 ). However, studies on institutions and institutional change are seemingly at an impasse; it seems difficult to proceed with the framing of forward-looking research questions linked to forest management institutions (FMIs). The impasse is rooted in the largely fragmented and unstructured institutional analysis around forest settings that harbor conflicts linked to emerging and persistent resource use inequalities (Gautam et al. 2004 ; Soliev et al. 2021 ). Additionally, the multiplicity of institutional variables and the lack of a consensus on which of the methods—qualitative or quantitative—is best suited for analyzing institutions and institutional change (Kimengsi et al. 2022a , b , c ) further validate the need to surmount this impasse. In this regard, a systematic review of the global knowledge base on FMIs is imminent. Furthermore, details on the methods to prioritize in future studies further validates the need for a review. Consequently, we seek answers to the following questions: (1) How have FMIs been conceptualized and analyzed globally? (2) How varied are the (non)compliance determinants and outcomes of FMIs? (3) How can we conceptually and methodologically advance research on FMIs? To provide answers to these interrogations, we undertake a review of FMIs. The study is inspired by an earlier review conducted in the context of sub-Saharan Africa (Kimengsi et al. 2022b ).

Materials and methods

Analytical framework.

In this review, we make use of the socio-ecological co-evolution framework (Pretzsch et al. 2014 ). The framework serves as a useful theoretical fundament to enhance understanding of the dynamics around forests and rural development. While allowing for the differentiation between humans and ecological subsystems, the framework also outlines the dynamic interactions between these two systems (Berkes et al. 1998 ; Pretzsch et al. 2014 ). The socio-ecological co-evolution framework is designed to enhance comprehension of the interactions between the social system (e.g., the community of forest users), the institutions that shape them, and the ecological system—forests. These interactions occur at the interface (management segment) of the framework. Besides providing a useful analytical lens to appreciate current levels of engagement in decision-making and the enforcement of institutional provisions, it also serves as a useful framework to understand how institutional change triggers the co-evolution of both ecological and social systems. The socio-ecological co-evolution framework is informed by the earlier works of Berkes et al. ( 1998 ), which bridged the hitherto divide between social research (centred around institutions), and ecological research, which emphasized cross-scale ecosystem dynamics. Worthy of note is the fact that other frameworks exist; for instance, the socio-ecological systems (SES) framework (Ostrom 2009 ) was proposed to explain complex systems involving resource systems (forests in this case), their resource units (e.g., timber), appropriators (e.g., timber exploiters), and governance systems (e.g., forest management rules) that continually interact to produce differential outcomes (Ostrom 2009 ). It explains that socio-ecological systems are constantly subjected to change. Some of these changes are rooted in institutions and institutional change processes (Rammel et al. 2007 ; Pretzsch et al. 2014 ). The socio-ecological co-evolution framework is employed for the following reasons: (1) with rapid transformations experienced in forest landscapes across the globe, scientific and policy circles need to extend their breadth of knowledge on how to further ‘marry’ social and ecological systems in forest management. (2) Institutional change is reflected through the decisions and actions of resource users at the interface of the framework. Therefore, understanding how these changes and their determinants precipitate (non)compliance is helpful in today’s dispensation, where forests are seen as crucial in stemming the upsurge of environmental crises. (3) The outcomes associated with the myriads of institutions need to be further appreciated to inform policy actors on the orientation of future FMIs. The socio-ecological co-evolution framework (Fig.  1 ) explains how changing societal demands and choices, influenced by the institutions in place, shape the type and magnitude of societal intervention in socio-ecological systems (e.g., forests).

Analytical framework for the systematic review.

Source: Based on Cleaver ( 2017 ), Haller et al. ( 2016 ), North ( 1990 ), Ostrom ( 1990 , 2005), and Pretzsch et al. ( 2014 ). NTFPs Non-Timber Forest Product

The review, guided by the research questions, focuses on the management phase and the social segment of the socio-ecological co-evolution framework. The management phase represents an interface—a point where management decisions under different forest categories such as plantation forests, forest reserves, community forests and landscapes in want of restoration, are implemented. Institutions and institutional change processes drive such decisions. The management operations are construed as forest-linked activities which are informed by institutions regulating timber and NTFPs exploitation, ecotourism, medicinal plants’ extraction and forest conservation. Institutional arrangements in this socio-ecological system culminate in the derivation of different management approaches, such as co-management and community-based forestry with a focus on livelihoods and conservation. The social segment of the framework focuses on the conceptualization of forest management institutions (for instance, structures vs processes, formal vs informal, and endogenous vs exogenous). This segment also captured forest management institutional compliance with an emphasis on the variations and determinants. The segment on outcomes explored the ecological, economic, socio-cultural, and political outcomes of FMIs. The framework also has a segment which explores methodological approaches employed in the study of FMIs.

Methodology

Data collection.

The systematic review approach (Nightingale 2009a , b ; Mengist et al. 2019 ) was employed in this study. Systematic reviews follow an established and standardized protocol for the search, appraisal and inclusion (or exclusion) of literature for subsequent analysis (Boell and Cecez-Kecmanovic 2015 ). This is different from the general review of literature which consists of a non-structured and highly subjective method of literature search and analysis (Kraus et al. 2020 ). The procedure was employed as follows: First a list of search terms (Appendix) was developed and used in the article search process. We targeted the following databases: Scopus, Science Direct, Google Scholar and Web of Science. Search terms such as forest management, forest governance, institutions, rules, norms, norms, laws, policies, community-based organizations, NGOs, associations, compliance, determinants, and outcomes were repeatedly employed in the search. The terms were combined with the respective regions (Africa, Asia, Australia, Europe/North America, Latin America), over a 15-year period (2006–2021). It should be noted that Europe and North America were clustered due to the observed similarity in their societal fabric and culture. We considered this timespan good enough to mirror contemporary evidence on the question of forest management institutions (FMIs). The search led to the initial identification of 920 articles. Four hundred thirty articles were identified from Web of Science, 104 from Google Scholar, 348 from Scopus and 38 from the Science Direct database. The search on Google Scholar did not produce a lot of articles. This is because grey literature was not considered during the search. Our emphasis was to derive literature which were published in internationally recognized databases. We then proceeded to deduplicate the articles—the deduplication process led to a reduction to 680 articles. Furthermore, article screening was performed with emphasis on the abstracts. This informed the decision to include or exclude the paper. In the selection, we targeted journal articles that were published in English and were empirically grounded. In cases where the abstract could not provide these details, we proceeded to review the methods and conclusions to inform inclusion (or exclusion). We excluded all grey literature during the article selection. This reduced the number of manuscripts to 197 (see Supplementary Excel Sheet), from which we derived 491 case studies; the cases were derived by considering the number of study areas that were included for analysis. We use ArcMap 10.5 to generate the map of the globe and the regions and/or countries where most of the case studies in this review paper were concentrated.

Data analysis

The articles retained were further read, and following the analytical framework (Fig.  1 ), a directed content analysis was performed (Hsieh and Shannon 2005 ). The directed content analysis began with a relevant theoretical framework—in this case, the socio-ecological coevolution framework. This framework provided a clear focus for the research questions under review. The key variables which were outlined in the framework (Fig.  1 ) informed the clustering of the data generated from the selected articles. For the selected articles, we read the abstract, methods and conclusion sections to generate data. The dataset was compiled in an excel sheet and further read; key texts which contained variables of interest were highlighted. These variables were then clustered following the established questions and themes for further analysis (Mayring 2000 ). Therefore, the highlighted texts, which contained data corresponding to the four thematic sections, were extracted from each article and organized under the main themes: conceptualization of institutions, institutional compliance, outcomes of forest management institutions and methodological approaches . We approached the conceptualization of institutions following the structure-process dimension (Fleetwood 2008a ), the formal and informal dichotomy (North 1990 ), the endogenous vs exogenous institutional lens (Kimengsi et al. 2021 ) and the state vs community-based institutional dichotomy (Ntuli et al. 2021 ). Compliance denotes the extent to which forest users adhere to the institutional provisions in their communities. This translates to forest management outcomes which could be ecological, socio-economic and even political (Haller et al. 2016 ).

These were recorded in a Microsoft Excel sheet (Artmann and Sartison 2018 ). We considered this approach appropriate, considering that software extraction might ignore salient details owing to the complex nature of institutional variables. Besides narratives and content analysis, we used descriptive statistics to report the variations across the five regions. The descriptive analysis further aided in establishing institutional compliance and its determinants, the ecological, socio-cultural, economic, and political outcomes linked to forest management institutions, and the variations in methodological approaches employed.

Attributes of reviewed papers and case studies

The review indicated that most of the articles emanate from Africa and Latin America—home to two of the world’s major forest ecosystems. This was followed by Asia. Case-wise, the study captured a total of 491 cases drawn from 99 countries across the globe (Fig.  2 ). The highest number of cases emanate from Europe/North America and Africa. This suggests that multi-case and multi-country studies have been significantly prioritized in these regions compared to single case/country studies for Asia and Australia.

Spatial distribution of case studies on forest management institutions (2006–2021)

In parts of Central Europe, studies to explore shifts towards new governance established that recent changes in institutional arrangements result from macro-political trends and the geopolitical strategy of some states (Sergent et al. 2018 ). In the United States and Canada, forest certification led to substantial changes in practices as enterprises embraced changes in forestry, environmental, social, and economic/system practices in the realm of forest certification (Moore et al. 2012 ). In the case of Africa, a comparative study of 38 countries reported that the activities of multinational corporations are associated with differential losses in forest cover—linked to weak governance (institutions) (Assa 2018 ). The review clearly shows that while political, geostrategic and religious forces defined the institutional change process in Europe/North America, economic interests through multinational companies shaped institutional change in Africa. The review established that some of the significant countries with regards to cases include Australia, Ecuador, and Germany (21 + cases). In addition, Bolivia, Brazil, Cameroon, Ghana, and Canada, India registered between 8 and 14 cases, while the remaining countries registered between 1 and 7 cases (Fig.  2 ).

Temporal evolution of papers and cases on forest management institutions

On the whole, the literature on institutions has grown over the last 15 years(Fig.  3 ). This could be linked to renewed interests to understand governance mishaps and to engage in getting institutions (including FMIs) right . In all, while the number of publications increased from 2006, the review shows that it witnessed a decline in 2009 and 2012. The growth in the literature is possibly explained by the interest to uncover institutional ‘relicts’ (in Africa) and rising environmental challenges in Latin America (bushfires and migration). Formal forest management institutions (structure and process) for forest products have received much attention in the 2000s literature. However, significant growth was observed in the literature of the 2010s, which included both formal (international) and informal (traditional and local) institutions and concepts such as ecosystem services, sustainable forest management, farm forestry, biodiversity, REDD + , and forest certification. This classification increasingly accommodated the use of endogenous and exogenous institutions, as well as state and community-based institutions. However, both classifications have been (mis)construed to represent formal and informal institutions.

Temporal evolution of papers on forest institutions across the globe for the past 15 years

Conceptualization of forest management institutions

From a structural dimension, institutions have been most conceptualized as structures in Asia and Africa. These predominate the informal structures where Asia and Africa account for 35% and 28%, respectively, of the review’s literature reporting on informal institutional structures. Latin America closely follows them with 22%. Literature from Asia and Africa further dominates in the classification of formal institutional structures with 28% and 25%, respectively. This is closely followed by Europe/North America (23%). Asia and Africa are ‘pace-setters” in the implementation of new forest management paradigms such as community-based forest management (Kimengsi and Bhusal, 2022 ). The introduction of these models saw the multiplication of management structures to oversee them. This explains why the literature significantly captures the structural dimension of institutions. Process-wise, literature from Asia and Africa accounts for 48% and 30%, respectively, of the literature on informal institutions, while Australia surprisingly reports none. In the formal domain, Asia, Europe/North America, and Latin America account for over 60% of the literature reporting the formal conceptualization of institutions (Table ​ (Table1 1 ).

Total number of papers (studies) = 197

Literature from Africa and Asia showed similarities in the conceptualization of institutions (Table ​ (Table2); 2 ); informal structures, for instance, chieftaincy and women groups, define and enforce processes (rules) which are conceived, for example, as taboos, beliefs, traditions, and customary rules. Studies in Cameroon and Burkina Faso in Africa report on bricolage manifestations involving formal and informal institutions (Kimengsi and Balgah 2021 ; Friman 2020 ), and the spatial variations in traditional institutions (Kimengsi et al. 2021 , 2022b ). In Europe/North America, the literature shows that informal structural institutions are conceptualized sparingly to include community leadership and inter-community forestry associations. Formally, they are reported as forest owners’ associations, political parties, protected area management, timber industry associations, resident associations, and state forest management. Informally, processes are conceived as local rules, while formally, they represent forest management policy, regulations, legal framework, local community forest governance, forest management strategies and forest marketing strategies. In Latin America, forest user groups, indigenous organizations and community management committees are frequently used in informal characterization, while labour unions, national services of protected areas, REDD + working group and Community general assemblies are used formally.

Global conceptualization of forest management institutions

Local land management rules constitute the key informal process in Latin America, while conservation laws, community-based forest policy, forest codes, forest laws, forest tenure agreements, and decentralized environmental policy appear in the formal conception of institutions. On the whole, a more diverse conceptualization of institutions (structures and processes) appear in the literature from Africa and Asia, followed by Latin America. The diversity is rooted in the diverse ethnic arrangements which characterize these regions. Africa, is the most ethnically diverse region in the world (Fearon 2003 ). This diversity accounts for the diversity in the nomenclature employed for forest management institutions—leading to the diversity in their conceptualization. With more empirical cases emanating from these settings, it is plausible to suggest that more in-depth and varied analysis about forest management institutions has been explored in these settings. Furthermore, the plethora of governance challenges in the management of natural resources (forest in this case) which is associated with such settings further explains the multifarious typification of institutions. In another dimension, structures and processes are surprisingly only conceptualized formally in the context of Australia—suggesting a significant drift away from informality to the pursuit of more formal, state-sanctioned institutions.

Compliance with forest management institutions

From the review, Africa, Asia, and Latin America report the highest cases of compliance in the informal institutional set-up. These settings have had a history linked to traditional institutions which were made to interact with colonially shaped institutions during their history. However, some degree of closeness to cultural institutions could be reported for these regions. The existence of compliance in the literature for Africa, Asia and Latin America is enough pointer to the multiplicity of institutional structures and processes which require monitoring against (non)compliance. Additionally, the interaction between formal and informal institutions, including the fallouts of colonial influence, led to the multiplicity of institutions. This possibly explains why compliance predominates the literature in the three regions. In Africa, for instance, pre-colonial types of resource use included the royal hunting preserves of the amaZulu and amaSwati people, and the kgotla system of land management practiced by the Batswana people (Ghai 1992 ; Fabricius 2004 ). Further, the making of access and use rules for natural resources in Mali (Moorehead 1989 ) and Botswana (Ostrom 1990 ), all indicate how endogenous cultural institutions shaped forest use. Likewise, Khasi, Garo and Jaintia tribes in Meghalaya of India, and traditional customary organization “Lembaga Adat” in Indonesia have not only conserved forest resources but also ensured its capacity to deliver ecosystem goods and services in sustainable manner (Mehring et al. 2011 ; Tiwari et al. 2013 ). Europe/North America registered few studies on informal institutional compliance, while this was non-existent for Australia—apparently due to the non-reported case of informal arrangements. Regarding non-compliance, articles from Latin America reported the highest case of non-compliance. This could be explained by the progressive decline in the informal institutions due to globalization and market forces which seemed to have permeated communities around the Amazon (Blundo-Canto et al. 2020 ). In the formal domain, non-compliance was significantly registered for Europe/North America, Africa, and Latin America (Fig.  4 ).

Global statistics of institutional compliance and non-compliance by regions. Left chart—papers ( N  = 197, n for compliance = 133, n for non-compliance = 64, Right chart—Cases ( N  = 491, n for compliance = 362, n for non-compliance = 129). Note Some papers reported compliance/compliance to formal and informal institutions simultaneously

It is important to note that some of the evoked reasons behind (non)compliance still require further investigation. For example, significant contextual variations in peoples’ attitudes and adherence to forest-sector institutions and governance in Asia, Africa, Latin America, and North America are directly linked to the disparities of key underlying and broader factors such as institutional models and policy frameworks for decentralization (Shackleton et al. 2002 ; Ribot 2003 ; Larson 2012 ; Mustalahti et al. 2020 ). Thus, a broader focus on institutional factors—rather than isolated reasons—is important to sufficiently explain (non-)compliance dynamics.

Forest management Institutional compliance determinants

From the analysis, political and economic factors were recurrent in the literature as key forces that influence institutional compliance. For instance, in Europe/North America, Latin America and Australia, political factors significantly influenced compliance (Table ​ (Table3). 3 ). Some of these key determinants include conflicts, policy enforcement, power relations and governance structure (Latin America) and actor network, policy development, and governance structure (Europe/North America). Politics and geostrategy contributed to defining natural resource (forest in this case) institutions in Europe and North America. However, in Latin America, the rise in challenges linked to migration and bush fires also stand as key determinants of forest management institutional compliance. Economic factors in Europe/North America and Africa determined compliance. In Africa, economic factors linked to private enterprises and market-based mechanisms significantly featured in the literature as determinants of institutional compliance. For instance, aspects linked to donor income/investment and material aid, community forest expenditure and benefits, poverty were common. In Europe/North America, the economic viability of forest land use, forest certification, amongst others, were reported in the articles. In Nigeria, economic incentives (incomes) from farming activities, NTFPs use and non-traditional employment shaped compliance (Ezebilo 2011 ). On the whole, ecological, socio-cultural and demographic factors did not significantly explain compliance with forest management institutions. The case of ecological determinants in surprising given the litany of ecological campaigns which have been introduced in Africa (e.g., Leventon et al. 2014 ; Senganimalunje et al. 2016 ), Asia (Gilani et al. 2017 ) and Latin America (Entenmann and Schmitt 2013 ; Kowler et al. 2020 ) for instance, to foster conservation. Furthermore, socio-cultural diversity as viewed in Africa warrants some diversity in the way people adhere to institutions—both formal and informal. In Tanzania, trust in institutions was a significant predictor of participation intensity of the households in forest management (Luswaga and Nuppenau 2020 ). However, in Europe, differences in the attitudes of actors with regard to pursuing sustainable development significantly shaped compliance with forest management institutions (Jankovska et al. 2010 ).

Forest management institutional compliance determinants to by regions

Forest management institutional outcomes

The review indicates that political outcomes were the most significant for Europe/North America, followed by Latin America and Australia (Table ​ (Table4). 4 ). Some key political outcomes included policy fragmentation, market formation failures, and reduced legitimacy of FSC certification (Europe/North America). This is understandable, considering that political and geostrategic forces were key determinants of institutional compliance. In Latin America,the setting up of provincial regulations which undermine enforcement of forest regime, rule breaking, challenges with the day-to-day operational institutions, inequitable benefit-sharing mechanism; the absence of law enforcement on sustainability of and access to non-wood forest products were common. Rule breaking is potentially triggered by increasing in-migration and the upsurge of bushfires. Bottazzi et al. ( 2014 ) showed how incentive-based systems of institutions facilitated the allocation and use of funds in REDD + programmes. In all these, deforestation persisted in the midst of lost and/or bypassed institutions (Carvalho et al. 2019 ). In Australia, divergent views characterized the seeking of solutions to enhance inter-departmental and inter-municipal coordination (Ordóñez et al. 2020 ). Positive ecological outcomes were significantly reported for Africa (forest or biodiversity protection/conservation, improved forest condition and surface water quality, sustainable forest or ecosystem management, planting of timber and fruit trees) and Latin America (fostering forest conservation, stabilization and/or decrease of deforestation, sustainable forest management). Furthermore, Europe/North America, Africa and Asia respectively reported positive economic outcomes linked to the generation of net monetary gains from parks, and from the wood harvesting and marketing (Europe/North America), higher incomes derived from certification, profits derived under community forestry, and the augmentation of household cash income (Africa). In Asia, studies report the positive outcomes linked to the forests’ substantial contribution to local livelihoods and income (Muhammed et al. 2008 ; Harada and Wiyono 2014 ; Barnes and van Laerhoven 2015 ).

Forest management institutional outcomes by regions

Some case studies have multiple institutional outcomes

Australia witnessed the most negative ecological outcomes. For instance, regional forest agreements were characterized by poor governance, leading to failures in biodiversity protection and ecosystem maintenance. This further precipitated the over-commitment of forest resources to wood production (Lindenmayer 2018 ). In Latin America, significant deforestation was observed for the Guarayos Indigenous Territory from 2000 to 2017—primarily driven by agricultural commodity production (He et al. 2019 ), while in Africa, Garekae et al. ( 2020 ) reported forest and wildlife decline in Botswana, linked to sectoral bias. Furthermore, the articles reported significant negative economic outcomes for Latin America, Asia, and Africa. Some of the reported outcomes include financial resource decline (Latin America), the timber-centric and market-oriented nature of community forests (Asia) (Bhusal et al. 2020 ), and the manifestations of elite capture in Africa. In Malawi, for instance, co-management programmes did not lead to positive outcomes, i.e., community organization, forest access, forest product availability and commercialization of forest products (Senganimalunje et al. 2016 ). On the whole socio-cultural outcomes were prevalent in Australia, Europe/North America, and Asia. Here, reported issues were linked to public acceptance of plantation policy, the improvement in communication of forest owners' associations and increased reliance on informal relationships. A case in point is linked to forest policy in Australia which led to several negative social impacts, including uncertainty, perceived injustice, and financial stress (Loxton et al. 2014 ). In the case of Asia, it was linked to inequalities among local actors, demographic changes and transformations in local social structures, gender inequality, successful collaboration between NGOs and community-based organizations , conflicts between communities and state forest enterprises (Adhikari and Lovett 2006 ; Barnes and van Laerhoven 2015 ).

Methodological approaches

The analysis reveals that globally mixed methods approaches have been least prioritized in the study of forest management institutions. For instance, between 2006 and 2021, we observed a growing trend in the application of qualitative methods; only 2 articles were reported in 2007, while this peaked to 99 in 2021. However, the use of quantitative and mixed methods approaches was significantly lower (Fig.  5 ). Considering the intricacies linked to the study of institutions, the prioritization of qualitative approaches is understandable. However, with growing interest in employing more robust data collection and analysis methods, it is only germane to report that studies have not prioritized mixed methods approaches so far (Malina et al. 2011 ; Karolina et al. 2021 ).

Cumulative distribution of paper and adoption of methods

A slight increase in the application of mixed methods approaches is observed (Table ​ (Table5) 5 ) from 22% between 2006 and 2010 to 26% between 2016 and 2021, while there was a progressive decline in the sole application of quantitative methods from 37 to 23% within this time period. A slight decrease is also observed for qualitative methods, from 54 to 51% between 2011 and 2021.

Methods employed over time in the study of forest management institutions (% in parenthesis)

On the whole, while the use of only qualitative methods in the study of forest management institutions increased over time, the adoption of only quantitative approaches witnessed a decrease (Table ​ (Table5). 5 ). Studies in Africa have largely prioritized the sole application of quantitative methods, as 42% of the papers reported this approach (Table ​ (Table6), 6 ), while mixed methods (25%) were least prioritized. This could be linked to the growing ‘quantification revolution’ in research across the region. While quantitative analysis provides some pointers to institutional questions, they hide significant intricacies which could be revealed by solely qualitative or, better still, mixed methods analytical approaches. In Latin America, however, a significant proportion of the studies (40%) employed solely qualitative methods, followed by mixed methods (35%) and then quantitative methods (26%). Likewise, the highest proportion (58%) of studies draw from qualitative methods in Asia and Australia, whereas mixed-methods were prioritized as the second highest (37%) in Asia and the least (10%) in Australia (Table ​ (Table6 6 ).

Methods used by different continents (percentage in parenthesis)

On the whole, while studies in Africa employed more of only quantitative methods over qualitative ones, research on forest management institutions in Europe and North America prioritized only qualitative methods over only quantitative ones. In North America/Europe, 73% of the studies employed the qualitative approach, followed by quantitative (19%). The least employed approach is mixed-methods, as only 8% used this approach (Table ​ (Table6). 6 ). Overall, qualitative methods have been significantly employed globally except in Africa, while mixed methods were the least adopted in all regions except Asia and Latin America.

Perspectives on the conceptual and methodological advancement of research on FMIs

The literature so far presents a fragmented conceptualization of forest management institutions. For instance, institutions are broadly categorized as formal or informal on the one hand and as exogenous and endogenous on the other hand. This is based on the premise that not all endogenous institutions are informal institutions. A more detailed conceptualization which captures the formal and informal dimension, including the endogenous and exogenous categorization, is helpful to advance theoretical developments in the field of institutions in relation to forest management. Additionally, institutions seem to exhibit stream-like attributes; an approach which further conceptualizes them as ephemeral (very short-term arrangements made by forest actors to facilitate forest resource use conflict minimization), partially enduring ( arrangements that temporarily become a norm but fizzle out as new actors take over (Kimengsi et al. 2022b ); and enduring ( institutions are either codified (formal) and/or take the status of customs and values which transcend several generations (Ostrom 1990 ). In both cases, empirical studies geared towards establishing these proposed conceptual approaches are needed. Future research also needs to advance the “marriage” between actors and institutions.

From a methodological standpoint, further studies should prioritize methods based reviews (Palmatier et al. 2018 ) to enable researchers synthesize in detail, the design and instruments used so far, the approaches employed in data collection approaches and pros and cons linked to the methods employed. This will further inform the application of methodological approaches and instruments for future empirical studies on forest management institutions. Also, multi-country studies, employing mixed-methods approaches are needed to analyze institutions in forest use and management.

Review Limitations

This review provides an initial synthesis of the literature on forest management institutions from a global perspective. It is helpful in the identification of region-specific research needs in the ever-evolving field of institutions. A couple of limitations could be raised: Firstly, the conceptual analysis of institutions does not incorporate the exogenous versus endogenous dichotomy. With growing interest to further explore the typology and source of institutions, including whether management outcomes are a function of more endogenous or exogenous institutional arrangements (Kimengsi et al. 2022b ), future reviews and empirical studies should incorporate this dimension. Secondly, the regional clustering of institutions might shade details linked to how institutions are conceptualized and the outcomes they effectively produce. Although case studies are used, it is not possible in a single review to derive all these conceptual details, which might vary even within regions. Taking Africa, for instance, diversity in the region’s culture requires country-specific analysis of institutions. Latin America’s diversity precipitates ‘institutional shopping’ (Wartmann et al. 2016 Thirdly, institutions do not operate in isolation—therefore an actor-centred/power dimension is required to better appreciate institutional arrangements (Giessen et al. 2014 ; Ongolo et al. 2021 ). Therefore, a review of the actor and power dimensions of institutions is required to inform subsequent empirical studies. Fourthly, while the paper reports on compliance, the level of compliance is not reported, and the factors which militate for or against compliance. Fifthly, we selected articles which were exclusively published in English language and indexed in certain data bases. In doing so, we ignored papers which might have been published in French, Spanish, Amharic, Kiswahili, Nepali and other languages; such articles might have provided further compelling details on the region-specific dynamics of forest management institutions. We call for subsequent reviews to aim at valorizing such studies.

The current socio-ecological outcomes linked to the upsurge of pandemics (e.g. COVID-19) further justify the need to pay more attention to the management of forests and forest resources (Tollefson 2020 ; Saxena et al. 2021). These details, which vary over space and time, and may potentially assume a different dimension under the current COVID-19 scenario (Saxena et al. 2021), require extensive review and further empirical grounding. When pandemic prevention hinges on forest management to some extent, it is imperative to further explore the role of FMIs. Further reviews could emphasize the extent of compliance and the conditions under which (non)compliance prevails in the context of pandemics. Additionally, institutional change which is triggered by health crises (e.g., pandemics) still needs to be further established.

Finally, our review of the methods focused on providing a snapshot of the approaches, following the broad categorization of qualitative, quantitative and methods. This does not provide details on the specific qualitative methods employed (e.g., key informant interviews, participant observations, vignettes, focus group discussions). Future methods-based reviews should consider these.

To define conceptual and methodological pathways for future studies on forest management institutions (FMIs), this study undertakes a systematic review of the literature on FMIs using 197 papers (491 cases). From the study, the following conclusions are plausible: Firstly, while forest management institutions literature has witnessed a growth, this is most significant in Africa and Latin America. Secondly, the structure-process conceptualization of institutions (formal and informal) predominates in Asia and Africa. Process-wise, studies from Australia surprisingly did not report on a single process-linked institution. This merits further studies which pays attention to the identification of such institutions. The literature also reports on the drift away from informality to the pursuit of more formal, state-sanctioned institutional arrangements in Australia. Thirdly , global south regions—Africa, Asia, and Latin America—report the highest cases of compliance in the informal institutional set-up, while non-compliance was significantly registered for Europe/North America in the formal domain. Fourthly , politico-economic factors significantly influence institutional compliance in Europe/North America, while economic factors shape compliance in Africa. On the whole, ecological, socio-cultural, and demographic factors were reported to less significantly explain compliance with forest management institutions (FMIs). Fifthly , while forest management institutions in Europe/North America significantly contributed to determining politico-economic outcomes, those in Africa and Latin America contributed to positive ecological and negative economic outcomes. Finally, mixed methods approaches have been least prioritized in the study of forest management institutions; in Africa, the sole application of quantitative methods was prioritized. Future research needs to (1) extend the conceptualization of institutions, (2) increase multi-case and multi-country studies on FMIs especially for Asia and Australia, (3) empirically ground informality in the institutional set up of forest management in Australia, (4) establish in detail, the extent of (non)compliance, their spatio-temporal variations, and determinants, and (5) valorize the application of mixed-methods approaches in the study of FMIs across the globe.

Below is the link to the electronic supplementary material.

Open Access funding enabled and organized by Projekt DEAL. This research was funded by the Deutsche Forschungsgemeinschaft (DFG)—Projektnummer (437116427), Grant ID: F-010300-541-000-1170701.

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Contributor Information

Jude Ndzifon Kimengsi, Email: [email protected]_eduj , Email: [email protected] .

Raphael Owusu, Email: moc.oohay@usuwo60leahpar .

Shambhu Charmakar, Email: [email protected] .

Gordon Manu, Email: [email protected] .

Lukas Giessen, Email: [email protected] .

• Agrawal A, Gupta K. Decentralization and participation: the governance of common pool resources in Nepal’s Terai. World Dev. 2005; 33 (7):1101–1114. doi: 10.1016/j.worlddev.2005.04.009. [ CrossRef ] [ Google Scholar ]
• Aguiar APD, Vieira ICG, Assis TO, Dalla-Nora EL, Toledo PM, Santos-Junior RA, Batistella M, Coelho AS, Savaget EK, Aragaõ LEOC, et al. Land use change emission scenarios: anticipating a forest transition process in the Brazilian Amazon. Glob Change Biol. 2016; 22 :1821–1840. doi: 10.1111/gcb.13134. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Adhikari B, Lovett JC. Institutions and collective action: does heterogeneity matter in community-based resource management? J Dev Stud. 2006; 42 (3):426–445. doi: 10.1080/00220380600576201. [ CrossRef ] [ Google Scholar ]
• Artmann M, Sartison K. The role of urban agriculture as a nature-based solution: a review for developing a systemic assessment framework. Sustainability. 2018; 10 (6):1937. doi: 10.3390/su10061937. [ CrossRef ] [ Google Scholar ]
• Assa BSK. Foreign direct investment, bad governance and forest resources degradation: evidence in Sub-Saharan Africa. Economia Politica. 2018; 35 (1):107–125. doi: 10.1007/s40888-017-0086-y. [ CrossRef ] [ Google Scholar ]
• Bare M, Kauffman C, Miller DC. Assessing the impact of international conservation aid on deforestation in sub-Saharan Africa. Environ Res Lett. 2015; 10 (12):125010. doi: 10.1088/1748-9326/10/12/125010. [ CrossRef ] [ Google Scholar ]
• Barnes C, van Laerhoven F. Making it last? Analysing the role of NGO interventions in the development of institutions for durable collective action in Indian community forestry. Environ Sci Policy. 2015; 53 :192–205. doi: 10.1016/j.envsci.2014.06.008. [ CrossRef ] [ Google Scholar ]
• Berkes F, Colding J, Folke C, editors. Linking social and ecological systems. Management practices and social mechanisms for building resilience. Cambridge: Cambridge University Press; 1998. [ Google Scholar ]
• Bernardi F, Gonzalez JJ, Requena M. The sociology of social structure. In: Bryant B, Peck D, editors. 21st Century sociology: a reference handbook. Newbury: Sage; 2007. pp. 162–170. [ Google Scholar ]
• Beunen R, Patterson JJ. Analysing institutional change in environmental governance: exploring the concept of ‘institutional work’ J Environ Plan Manage. 2019; 62 (1):12–29. doi: 10.1080/09640568.2016.1257423. [ CrossRef ] [ Google Scholar ]
• Bhusal P, Karki P, Kimengsi JN. Timber distribution dynamics in scientifically managed community forests: learning from Nepal. Forests. 2020; 11 (10):1032. doi: 10.3390/f11101032. [ CrossRef ] [ Google Scholar ]
• Blundo-Canto G, Cruz-Garcia GS, Talsma EF, Francesconi W, Labarta R, Sanchez-Choy J, et al. Changes in food access by mestizo communities associated with deforestation and agrobiodiversity loss in Ucayali, Peruvian Amazon. Food Secur. 2020; 12 (3):637–658. doi: 10.1007/s12571-020-01022-1. [ CrossRef ] [ Google Scholar ]
• Boell SK, Cecez-Kecmanovic D. On being ‘systematic’ in literature reviews. In: Willcocks LP, Sauer C, Lacity MC, editors. Formulating Research Methods for Information Systems. London: Palgrave Macmillan; 2015. [ Google Scholar ]
• Bottazzi P, Crespo D, Soria H, Dao H, Serrudo M, Benavides JP, et al. Carbon sequestration in community forests: trade-offs, multiple outcomes and institutional diversity in the Bolivian Amazon. Dev Chang. 2014; 45 (1):105–131. doi: 10.1111/dech.12076. [ CrossRef ] [ Google Scholar ]
• Buchenrieder G, Balgah RA. Sustaining livelihoods around community forests: What is the potential contribution of wildlife domestication? J Modern Afr Stud. 2013; 51 (1):57–84. doi: 10.1017/S0022278X12000596. [ CrossRef ] [ Google Scholar ]
• Carvalho WD, Mustin K, Hilário RR, Vasconcelos IM, Eilers V, Fearnside PM. Deforestation control in the Brazilian Amazon: a conservation struggle being lost as agreements and regulations are subverted and bypassed. Perspect Ecol Conserv. 2019; 17 (3):122–130. [ Google Scholar ]
• Cleaver F. Development through bricolage: rethinking institutions for natural resource management. London: Routledge; 2017. [ Google Scholar ]
• Curtis PG, Slay CM, Harris NL, Tyukavina A, Hansen MC. Classifying drivers of global forest loss. Science. 2018; 361 :1108–1111. doi: 10.1126/science.aau3445. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Dixon AB, Wood AP. Local institutions for wetland management in Ethiopia: sustainability and state intervention. In: van Koppen B, Giordano M, Butterworth J, editors. Community-based water law and water resource management reform in developing countries. Wallingford: CABI International; 2007. pp. 130–145. [ Google Scholar ]
• Entenmann SK, Schmitt CB. Actors’ perceptions of forest biodiversity values and policy issues related to REDD+ implementation in Peru. Biodivers Conserv. 2013; 22 (5):1229–1254. doi: 10.1007/s10531-013-0477-5. [ CrossRef ] [ Google Scholar ]
• Ezebilo EE. Local participation in forest and biodiversity conservation in a Nigerian rain forest. Int J Sust Dev World. 2011; 18 (1):42–47. doi: 10.1080/13504509.2011.544389. [ CrossRef ] [ Google Scholar ]
• Fabricius C. Historical background to community-based natural resource management. In: Fabricius C, Koch E, editors. Rights, Resources and Rural Development Community-based Natural Resource Management in Southern Africa. Oxfordshire, New York: Earthscan; 2004. [ Google Scholar ]
• Faggin J, Behagel J. Institutional bricolage of sustainable forest management implementation in rural settlements in Caatinga biome. Brazil. International Journal of the Commons. 2018; 12 (2):275–299. doi: 10.18352/ijc.872. [ CrossRef ] [ Google Scholar ]
• Faye P, Haller T, Ribot R. Shaping rules and practice for more justice? Local conventions and local resistance in eastern Senegal. Hum Ecol. 2017; 8 (2017):1–11. [ Google Scholar ]
• Fearon JD. Ethnic structure and cultural diversity by country. J Econ Growth. 2003; 8 (June):195–222. doi: 10.1023/A:1024419522867. [ CrossRef ] [ Google Scholar ]
• Fleetwood S. Institutions and social structures. J Theory Soc Behav. 2008; 38 :30021–38308. doi: 10.1111/j.1468-5914.2008.00370.x. [ CrossRef ] [ Google Scholar ]
• Fleetwood S. Structure, institution, agency, habit and reflexive deliberation. J Inst Econ. 2008; 4 (2):183–203. [ Google Scholar ]
• Foundjem-Tita D, Duguma LA, Speelman S, Piabuo SM. Viability of community forests as social enterprises. Ecol Soc. 2018 doi: 10.5751/ES-10651-230450. [ CrossRef ] [ Google Scholar ]
• Friman J. Gendered woodcutting practices and institutional bricolage processes: the case of woodcutting permits in Burkina Faso. For Policy Econ. 2020; 111 :102045. doi: 10.1016/j.forpol.2019.102045. [ CrossRef ] [ Google Scholar ]
• Garcia CA, Savilaakso S, Verburg RW, Gutierrez V, Wilson SJ, Krug CB, Sassen M, Robinson BE, Moersberger H, Naimi B, Rhemtulla JM, Dessard H, Gond V, Vermeulen C, Trolliet F, Oszwald J, Quétier F, Pietsch SA, Bastin JF, Dray A, Araújo MB, Ghazoul J, Waeber PO. The global forest transition as a human affair. One Earth. 2020; 2 (5):417–428. doi: 10.1016/j.oneear.2020.05.002. [ CrossRef ] [ Google Scholar ]
• Gautam AP, Shivakoti GP, Webb EL. A review of forest policies, institutions, and changes in the resource condition in Nepal. Int for Rev. 2004; 6 (2):136–148. [ Google Scholar ]
• Gebara MF (2019) Understanding institutional bricolage: what drives behavior change towards sustainable land use in the Eastern Amazon? Int J Commons 13(1)
• Geist HJ, Lambin EF. Proximate causes and underlying driving forces of tropical deforestation. Bioscience. 2002; 52 :143–150. doi: 10.1641/0006-3568(2002)052[0143:PCAUDF]2.0.CO;2. [ CrossRef ] [ Google Scholar ]
• Ghai D (1992) Conservation, livelihood and democracy: social dynamics of environmental changes in Africa. Discussion Paper 33, United Nations Research Institute for Social Development. http://www.unrisd.org/unrisd/website/document.nsf/(httpPublications)/ . Accessed 10 Sept 2021
• Giessen L, Krott M, Möllmann T. Increasing representation of states by utilitarian as compared to environmental bureaucracies in international forest and forest-environmental policy negotiations. Forest Policy Econ. 2014; 38 :97–104. doi: 10.1016/j.forpol.2013.08.008. [ CrossRef ] [ Google Scholar ]
• Gilani HR, Yoshida T, Innes JL. A collaborative forest management user group's perceptions and expectations on REDD+ in Nepal. Forest Policy Econ. 2017; 80 :27–33. doi: 10.1016/j.forpol.2017.03.004. [ CrossRef ] [ Google Scholar ]
• Gomes PIA, Wai OWH, Dehini GK. Vegetation dynamics of ephemeral and perennial streams in mountainous headwater catchments. J Mater Sci. 2020; 17 :1684–1695. [ Google Scholar ]
• Haapal J, White P. Development through bricoleurs: portraying local personnel’s role in implementation of water resources development in rural Nepal. Water Alternat. 2018; 11 (3):979–998. [ Google Scholar ]
• Harada K, Wiyono (2014) Certification of a community-based forest enterprise for improving institutional management and household income: a case from Southeast Sulawesi, Indonesia. Small-Scale For 13(1):47–64
• Haller T, Acciaioli G, Rist S. Constitutionality: conditions for crafting local ownership of institution-building processes. Soc Nat Resour. 2016; 29 (1):68–87. doi: 10.1080/08941920.2015.1041661. [ CrossRef ] [ Google Scholar ]
• He Y, Baldiviezo JP, Agrawal A, Candaguira V, Perfecto I. Guardians of the forests: how should an indigenous community in eastern bolivia defend their land and forests under increasing political and economic pressures? Case Stud Environ. 2019; 3 :1–14. doi: 10.1525/cse.2019.sc.946307. [ CrossRef ] [ Google Scholar ]
• Hosonuma N, Herold M, De Sy V, De Fries RS, Brockhaus M, Verchot L, Angelsen A, Romijn E. An assessment of deforestation and forest degradation drivers in developing countries. Environ Res Lett. 2012; 7 :044009. doi: 10.1088/1748-9326/7/4/044009. [ CrossRef ] [ Google Scholar ]
• Houghton RA, Nassikas AA. Negative emissions from stopping deforestation and forest degradation, globally. Glob Change Biol. 2018; 24 :350–359. doi: 10.1111/gcb.13876. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hsieh HF, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res. 2005; 15 (9):1277–1288. doi: 10.1177/1049732305276687. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Jankovska ILZE, Straupe INGA, Panagopoulos THOMAS. Professionals awareness in promotion of conservation and management of urban forests as green infrastructure of Riga, Latvia. WSEAS Trans Environ Dev. 2010; 6 (8):614–623. [ Google Scholar ]
• Karolina V, Alif M, Sudharni S. The advantages and disadvantages of quantitative and qualitative approach for investigating washback in English language testing. EDUKATIF. 2021; 3 (5):2299–2310. [ Google Scholar ]
• Kimengsi JN, Abam CE. Forje GW (2021) Spatio-temporal analysis of the ‘last vestiges’ of endogenous cultural institutions: implications for Cameroon’s protected areas. GeoJournal. 2021 doi: 10.1007/s10708-021-10517-z. [ CrossRef ] [ Google Scholar ]
• Kimengsi JN, Balgah RA. Colonial hangover and institutional bricolage processes in forest use practices in Cameroon. Forest Policy Econ. 2021; 125 :102406. doi: 10.1016/j.forpol.2021.102406. [ CrossRef ] [ Google Scholar ]
• Kimengsi JN, Mairomi HW. COVID-19 and natural resource use practices in Cameroon. In: Akumbu PW, Nzweundji JG, editors. Responding to disease outbreak in Cameroon: lessons from COVID-19. Köln: Rüdiger Köppe; 2021. [ Google Scholar ]
• Kimengsi JN and Bhusal P (2022) Community forestry governance: lessons for Cameroon and Nepal. Soc Nat Resour 35(4):447–464
• Kimengsi JN, Grabek J, Giessen L, Balgah RA, Buchenrieder G (2022a) Forest management institutions and actor-centered conflicts in sub-Saharan Africa: contemporary realities and future avenues for research and policy. Forest Policy Econ 144:102846
• Kimengsi JN, Mukong AK, Giessen L, Pretzsch J. Institutional dynamics and forest use practices in the Santchou Landscape of Cameroon. Environ Sci Policy. 2022; 128 (2022):68–80. doi: 10.1016/j.envsci.2021.11.010. [ CrossRef ] [ Google Scholar ]
• Kimengsi JN, Owusu R, Djenontin INS, Pretzsch J, Giessen L, Buchenrieder G, Pouliot M, Acosta AN. What do we (not) know on forest management institutions in sub-Saharan Africa? A regional comparative review. Land Use Policy. 2022; 114 :105931. doi: 10.1016/j.landusepol.2021.105931. [ CrossRef ] [ Google Scholar ]
• Kissinger G, Herold M, De Sy V (2012) Drivers of deforestation and forest degradation: a synthesis report for REDD+ policymakers (Lexeme Consulting). https://www.cifor.org/knowledge/publication/5167/ . Accessed 18 Sept 2021
• Kowler L, Kumar Pratihast A, Ojeda P, del Arco A, Larson AM, Braun C, Herold M. Aiming for sustainability and scalability: community engagement in forest payment schemes. Forests. 2020; 11 (4):444. doi: 10.3390/f11040444. [ CrossRef ] [ Google Scholar ]
• Kraus S, Breier M, Dasí-Rodríguez S. The art of crafting a systematic literature review in entrepreneurship research. Int Entrep Manag J. 2020; 16 :1023–1042. doi: 10.1007/s11365-020-00635-4. [ CrossRef ] [ Google Scholar ]
• Larson AM (2012) Democratic decentralization in the forestry sector: lessons learned from Africa, Asia and Latin America. In: The politics of decentralization. Routledge, London, pp 46–76
• Leventon J, Kalaba FK, Dyer JC, Stringer LC, Dougill AJ. Delivering community benefits through REDD+: Lessons from joint forest management in Zambia. Forest Policy Econ. 2014; 44 :10–17. doi: 10.1016/j.forpol.2014.03.005. [ CrossRef ] [ Google Scholar ]
• Lindenmayer DB. Flawed forest policy: flawed regional forest agreements. Aust J Enviro Manag. 2018; 25 (3):258–266. doi: 10.1080/14486563.2018.1466372. [ CrossRef ] [ Google Scholar ]
• Loxton E, Schirmer J, Kanowski P. Social impacts of forest policy changes in Western Australia on members of the natural forest industry: implications for policy goals and decision-making processes. Forestry. 2014; 87 (3):363–376. doi: 10.1093/forestry/cpu011. [ CrossRef ] [ Google Scholar ]
• Luswaga H, Nuppenau EA. Participatory forest management in West Usambara Tanzania: what is the community perception on success? Sustainability. 2020; 12 (3):921. doi: 10.3390/su12030921. [ CrossRef ] [ Google Scholar ]
• Malhi Y, Gardner TA, Goldsmith GR, Silman MR, Zelazowski P. Tropical forests in the Anthropocene. Annu Rev Environ Resour. 2014; 39 :125–159. doi: 10.1146/annurev-environ-030713-155141. [ CrossRef ] [ Google Scholar ]
• Malina MA, Nørreklit HSO, Selto FH. Lessons learned: advantages and disadvantages of mixed method research. Qual Res Account Manag. 2011; 8 :59–71. doi: 10.1108/11766091111124702. [ CrossRef ] [ Google Scholar ]
• Mayring P (2000) Qualitative content analysis. Forum 1(2)
• Mehring M, et al. Local institutions: regulation and valuation of forest use-evidence from Central Sulawesi, Indonesia. Land Use Policy. 2011; 28 (4):736–747. doi: 10.1016/j.landusepol.2011.01.001. [ CrossRef ] [ Google Scholar ]
• Mengist W, Soromessa T, Legese G. Method for conducting systematic literature review and meta-analysis for environmental science research. MethodsX. 2019; 7 :100777. doi: 10.1016/j.mex.2019.100777(accessedon19.09.2021). [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Meyfroidt P, Lambin EF. Global forest transition: prospects for an end to deforestation. Annu Rev Environ Resour. 2011; 36 :343–371. doi: 10.1146/annurev-environ-090710-143732. [ CrossRef ] [ Google Scholar ]
• Moore SE, Cubbage F, Eicheldinger C. Impacts of forest stewardship council (FSC) and sustainable forestry initiative (SFI) forest certification in North America. J Forest. 2012; 110 (2):79–88. doi: 10.5849/jof.10-050. [ CrossRef ] [ Google Scholar ]
• Moorehead R. Changes taking place in common-property resource management in the Inland Niger Delta of Mali. In: Berkes F, editor. Common property resources. London: Belhaven; 1989. pp. 256–272. [ Google Scholar ]
• Muhammed N, Koike M, Haque F. Forest policy and sustainable forest management in Bangladesh: an analysis from national and international perspectives. New for. 2008; 36 (2):201–216. doi: 10.1007/s11056-008-9093-8. [ CrossRef ] [ Google Scholar ]
• Mustalahti I, Gutiérrez-Zamora V, Hyle M, Devkota BP, Tokola N. Responsibilization in natural resources governance: a romantic doxa? Forest Policy Econ. 2020; 111 :102033. doi: 10.1016/j.forpol.2019.102033. [ CrossRef ] [ Google Scholar ]
• Nerfa L, Rhemtulla JM, Zerriffi H. Forest dependence is more than forest income: Development of a new index of forest product collection and livelihood resources. World Dev. 2020; 125 (2020):104689. doi: 10.1016/j.worlddev.2019.104689. [ CrossRef ] [ Google Scholar ]
• Nightingale A. A guide to systematic literature reviews. Surg Infect (larchmt) 2009; 27 (9):381–384. [ Google Scholar ]
• Nightingale A. A guide to systematic literature reviews. Surgery. 2009; 27 (9):381–384. [ Google Scholar ]
• North D. Institutions, institutional change and economic performance. Cambridge: Cambridge University Press; 1990. [ Google Scholar ]
• Ntuli H, Mukong AK, Kimengsi JN. Institutions and environmental resource extraction within local communities in Mozambique. Forest Policy Econ. 2021; 139 :102724. doi: 10.1016/j.forpol.2022.102724. [ CrossRef ] [ Google Scholar ]
• Ordóñez C, Kendal D, Threlfall CG, Hochuli DF, Davern M, Fuller RA, et al. How urban forest managers evaluate management and governance challenges in their decision-making. Forests. 2020; 11 (9):963. doi: 10.3390/f11090963. [ CrossRef ] [ Google Scholar ]
• Oldekop JA, Rasmussen LV, Agrawal A, et al. Forest-linked livelihoods in a globalized world. Nat Plants. 2020; 6 :1400–1407. doi: 10.1038/s41477-020-00814-9. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Ongolo S, Giessen L, Karsenty A, Tchamba M, Krott M. Forestland policies and politics in Africa: recent evidence and new challenges. For Policy Econ. 2021; 127 (2021):102438. doi: 10.1016/j.forpol.2021.102438. [ CrossRef ] [ Google Scholar ]
• Osei-Tutu P, Pregernig M, Pokorny B. Legitimacy of informal institutions in contemporary local forest management: insights from Ghana. Biodivers Conserv. 2014; 23 (14):3587–3605. doi: 10.1007/s10531-014-0801-8. [ CrossRef ] [ Google Scholar ]
• Ostrom E. Governing the commons: the evolution of institutions for collective action. New York: Cambridge University Press; 1990. [ Google Scholar ]
• Ostrom E. A general framework for analyzing sustainability of social-ecological systems. Science. 2009; 2009 (325):419–422. doi: 10.1126/science.1172133. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Palmatier RW, Houston MB, Hulland J. Review articles: Purpose, process, and structure. J Acad Market Sci. 2018; 46 (1):1–5. doi: 10.1007/s11747-017-0563-4. [ CrossRef ] [ Google Scholar ]
• Pretzsch J, Darr D, Uibrig H, Auch E, editors. Forests and rural development. Berlin Heidelberg: Springer-Verlage; 2014. [ Google Scholar ]
• Rammel C, Stagl S, Wilfing H. Managing complex adaptive systems: a co-evolutionary perspective on natural resource management. Ecol Econ. 2007; 63 :9–21. doi: 10.1016/j.ecolecon.2006.12.014. [ CrossRef ] [ Google Scholar ]
• Ribot JC. Democratic decentralization of natural resources: institutional choice and discretionary power transfers in Sub-Saharan Africa. Public Admin Develop. 2003; 23 (1):53–65. doi: 10.1002/pad.259. [ CrossRef ] [ Google Scholar ]
• Rounsevell MDA, Reginster I, Araújo MB, Carter TR, Dendoncker N, Ewert F, House JI, Kankaapãã S, Leemans R, Metzger MJ, et al. A coherent set of future land-use change scenarios for Europe. Agric Ecosyst Environ. 2006; 114 :57–68. doi: 10.1016/j.agee.2005.11.027. [ CrossRef ] [ Google Scholar ]
• Rudel TK, Defries R, Asner GP, Laurance WF. Changing drivers of deforestation and new opportunities for conservation. Conserv Biol. 2009; 23 :1396–1405. doi: 10.1111/j.1523-1739.2009.01332.x. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Scott WR. Organizations, rational, natural and open systems. 4. New Jersey: Prentice Hall; 1995. [ Google Scholar ]
• Senganimalunje TC, Chirwa PW, Babalola FD, Graham MA. Does participatory forest management program lead to efficient forest resource use and improved rural livelihoods? Experiences from Mua-Livulezi Forest Reserve, Malawi. Agroforest Syst. 2016; 90 (4):691–710. doi: 10.1007/s10457-015-9826-6. [ CrossRef ] [ Google Scholar ]
• Sergent A, Arts B, Edwards P. Governance arrangements in the European forest sector: Shifts towards ‘new governance’or maintenance of state authority? Land Use Policy. 2018; 79 :968–976. doi: 10.1016/j.landusepol.2016.08.036. [ CrossRef ] [ Google Scholar ]
• Shackleton S, Campbell B, Wollenberg E, Edmunds D. Devolution and community-based natural resource management: creating space for local people to participate and benefit. Nat Resour Perspect. 2002; 76 (1):1–6. [ Google Scholar ]
• Soliev I, Theesfeld I, Abert E, Schramm W. Benefit sharing and conflict transformation: Insights for and from REDD+ forest governance in sub-Saharan Africa. For Policy Econ. 2021; 133 :102623. doi: 10.1016/j.forpol.2021.102623. [ CrossRef ] [ Google Scholar ]
• Song XP, Hansen MC, Stehman SV, Potapov PV, Tyukavina A, Vermote EF, Townshend JR. Global land change from 1982 to 2016. Nature. 2018; 560 :639–643. doi: 10.1038/s41586-018-0411-9. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Steenbergen DJ, Warren C. Implementing strategies to overcome social-ecological traps. Ecol Soc. 2018 doi: 10.5751/ES-10256-230310. [ CrossRef ] [ Google Scholar ]
• Tiwari BK, et al. Institutional arrangement and typology of community forests of Meghalaya, Mizoram and Nagaland of North-East India. J for Res. 2013; 24 (1):179–186. doi: 10.1007/s11676-013-0337-x. [ CrossRef ] [ Google Scholar ]
• Tollefson J. Why deforestation and extinctions make pandemics more likely. Nature. 2020; 584 (13):175–176. doi: 10.1038/d41586-020-02341-1. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Turubanova S, Potapov PV, Tyukavina A, Hansen MC. Ongoing primary forest loss in Brazil, Democratic Republic of the Congo, and Indonesia. Environ Res Lett. 2018; 13 :074028. doi: 10.1088/1748-9326/aacd1c. [ CrossRef ] [ Google Scholar ]
• Tyukavina A, Hansen MC, Potapov PV, Stehman SV, Smith-Rodriguez K, Okpa C, Aguilar R. Types and rates of forest disturbance in Brazilian Legal Amazon, 2000–2013. Sci Adv. 2017; 3 :e1601047. doi: 10.1126/sciadv.1601047. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Tyukavina A, Hansen MC, Potapov P, Parker D, Okpa C, Stehman SV, Kommareddy I, Turubanova S. Congo Basin forest loss dominated by increasing smallholder clearing. Sci Adv. 2018; 4 :t2993. doi: 10.1126/sciadv.aat2993. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Verburg R, Rodrigues Filho S, Lindoso D, Debortoli N, Litre G, Bursztyn M. The impact of commodity price and conservation policy scenarios on deforestation and agricultural land use in a frontier area within the Amazon. Land Use Policy. 2014; 37 :14–16. doi: 10.1016/j.landusepol.2012.10.003. [ CrossRef ] [ Google Scholar ]
• Wartmann FM, Haller T, Backhaus N. “ Institutional shopping” for natural resource management in a protected area and indigenous territory in the Bolivian Amazon. Hum Organ. 2016; 75 (3):218–229. doi: 10.17730/1938-3525-75.3.218. [ CrossRef ] [ Google Scholar ]
• Weisse M, Goldman ED (2017). Global tree cover loss rose 51 percent in 2016, World Resources Institute blog, October 23, 2017. http://www.wri.org/blog/2017/10/global-tree-cover-loss-rose-51-percent-2016 . Accessed 15 Sept 2021.
• Yeboah-Assiamah E, Muller K, Domfeh KA. Institutional assessment in natural resource governance: a conceptual overview. Forest Policy Econ. 2017; 74 :1–12. doi: 10.1016/j.forpol.2016.10.006. [ CrossRef ] [ Google Scholar ]

The importance of different forest management systems for people’s dietary quality in Tanzania

• Research article
• Open access
• Published: 11 September 2024
• Volume 39 , article number  176 , ( 2024 )

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• R. S. Olesen   ORCID: orcid.org/0000-0003-1463-1906 1 ,
• F. Reiner 1 ,
• B. den Braber 1 ,
• C. Hall 1 , 2 ,
• C. J. Kilawe 3 ,
• J. Kinabo 4 ,
• J. Msuya 4 &
• L. V. Rasmussen 1  

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A large body of literature has shown that forests provide nutritious foods in many low- and middle-income countries. Yet, there is limited evidence on the contributions from different types of forest and tree systems.

Here, we focus on individual trees and smaller forest patches outside established forest reserves as well as different forest management systems.

We do so by combining novel high-resolution data on tree cover with 24-h dietary recall surveys from 465 women in Tanzania.

We show that people with more unclassified tree cover (i.e., individual trees and small forest patches) in their nearby surroundings have more adequate protein, iron, zinc, and vitamin A intakes. We also find that having a nearby forest under Participatory Forest Management (PFM) system is associated with higher adequacy levels of energy, iron, zinc and vitamin A. By contrast, tree cover within other types of forest (e.g., Government Forest Reserves and Government Forest Plantations) is not positively associated with people’s dietary quality.

Conclusions

Our key finding is that having individual trees, smaller forest patches and/or forest under PFM in close proximity is more beneficial for people’s diets than other types of established forests. Our results highlight the nutritional importance of trees outside established forests and question the often-assumed benefits of forests if these are made inaccessible by social barriers (e.g., legislation). Finally, our results emphasize the need to distinguish between different forest management systems when studying forest-diet linkages.

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Introduction

Recent literature has established positive linkages between forests and food and nutrition security in low- and middle-income countries, both based on large-scale datasets (Ickowitz et al. 2014 ; Galway et al. 2018 ; Rasolofoson et al. 2018 ; Den Braber et al. 2024 ) as well as site-specific case studies (Baudron et al. 2017 ; Cheek et al. 2022 ). There are four overarching pathways by which forests and trees can positively affect people’s food and nutrition security (Baudron et al. 2019b ; Gergel et al. 2020 ): (1) The direct provision of food as forests often host numerous and nutrient-rich wild plants and animals that are consumed by local communities (Powell et al. 2013 ; Asprilla-Perea and Díaz-Puente 2019 ), (2) the provision of ecosystem services (e.g., soil protection, water provision, pollination, access to manure and biomass), which can improve the productivity of surrounding agricultural lands (Baudron et al. 2019a ; Yang 2020 ), (3) the provision of fuelwood, which is vital for cooking and boiling water in many countries (Karki et al. 2018 ), and (4) income generation from sale of forest and tree products, which can facilitate the purchase of nutritious foods from markets (Miller et al. 2020 ).

Despite the well-established positive linkages between forests and people’s diets, little is known about (1) the potential contribution of trees outside of established forest reserves beyond agroforestry systems, which are well-studied (Babu and Rhoe 2002 ; Bostedt et al. 2016 ; Afentina et al. 2021 ), and (2) different types of forest management systems. We note that trees outside of established forest reserves differ from agroforestry as they are not limited to being located in or around farmland but include trees growing across all types of non-forest landscapes (e.g., urban settlements, roads, lakes). One potential reason behind the limited knowledge on the role of trees outside forests is that large-scale landscape studies tend to apply binary forest/non-forest classifications based on either moderate spatial resolution data (Johnson et al. 2013 ; Rasmussen et al. 2019 ) or larger political forest units (Kumeh et al. 2021 ). Consequently, most knowledge on tree-diet relationships comes from local case studies that examine the effects of agroforestry systems on people’s diets (Ghosh-Jerath et al. 2021 ; Jemal et al. 2021 ; Zahoor et al. 2021 ; Kulsum and Susandarini 2023 ). Such studies tend to find positive linkages between agroforestry and dietary quality (Jamnadass et al. 2013 ; Montagnini 2017 ; Dagar et al. 2020 ). For example, a cross-sectional study among 170 farmers in India estimated that a 1% increase in tree density and tree diversity on farms would increase people’s food consumption score (mean level: 28) by 0.2% point and 0.1% point, respectively (Singh et al. 2023 ). A recent review covering 36 publications on the linkages between tree-based farming systems and food and nutrition security in low- and middle-income countries found that trees located around farmland had generally positive effects on people’s diets, directly through provision of wild and cultivated foods, and indirectly through improved income opportunities (Vansant et al. 2022 ). Another review assessing 207 case studies from sub-Saharan Africa found that 68% of the studies indicated an increase in food availability due to the presence of trees on farms (Kuyah et al. 2016 ). Yet, a study among 399 farmers in six agroecological zones in Rwanda found that trees on farms mainly represented a safety net for the poorest households rather than an important contributor to overall food security (Ndoli et al. 2021 ). Also, there is mixed evidence on the effects of agroforestry on crop production with some studies pointing to the positive effects on yields (Baier et al. 2023 ) and soil quality (Kuyah et al. 2019 ), whereas other studies indicate that trees on farms may also be associated with lower yields of crops such as wheat (Khan et al. 2023 ).

Even though more than one quarter of Africa’s tree cover is found outside areas previously classified as forest (Reiner et al. 2023 ), the role of individual trees outside forests (beyond agroforestry) has long been overlooked due to a lack of high-resolution satellite imagery (Schnell et al. 2015 ). However, in the past few years progress has been made through the combination of new high-resolution satellite imagery and deep learning methods, which has enabled large-scale mapping of non-forest trees at the individual tree level. This includes the detection of 1.8 billion trees in West African Sahara and Sahel covering areas that had previously been perceived and categorized as bare dry lands or deserts (Brandt et al. 2020 ). Therefore, it is now possible—and needed—to examine more closely how trees outside of forests are related to people’s food and nutrition security in low- and middle-income countries.

The second knowledge gap that we aim to address is how different forest management systems can contribute to people’s diets, as management systems around forests can influence how people use forests and trees as a food source (Adhikari et al. 2016 ; Andrieu et al. 2019 ). For example, enforcement of environmental policies in Nepal combined with increased timber extraction has caused reductions in local livestock holdings due to lack of fodder resources, resulting in a worsening of people’s food security (Dhakal et al. 2011 ). The authors of this study suggested that policies could alternatively promote agroforestry systems combined with community-based forest management to gain both forest protection and better food security for local communities. This suggestion was later supported by another Nepalese study which, based on national survey data from 3064 rural households, found that households who used resources from community-based forests experienced higher levels of calorie adequacy compared to households using government-owned forests (Paudel 2018 ). Furthermore, a study from Tanzania assessed the effects of community-based forestry on wealth, food security and child health, and found improvements in household food security (measured by meals/day and fish and meat consumption) in areas with community-based forest management compared to areas without (Pailler et al. 2015 ). Also, a study in Cameroon reported that more than half of the community forest users were highly dependent on the forest resources, as these resources provided 61–100% of their income, food, energy and material needs (Ngang et al. 2018 ).

While these case studies from Nepal, Tanzania and Cameroon go beyond broad-scale studies that treat forests as a homogenous landscape feature, they tend to use broad food security metrics as opposed to more detailed measures of dietary quality. This absence of detailed dietary quality metrics was highlighted by a recent review of 30 publications on linkages between social forestry (the term was used by the authors to describe initiatives linking communities with sustainable forest management) and food security in Asia. The authors found that none of the publications examined how different forest management systems affect the dietary quality of local communities (Yahya et al. 2022 ). When examining the forest-diet relationship, it is important to move beyond crude measures of food security in favour of more detailed dietary quality metrics (where the data allows), as these measures provide more insight into the mechanisms driving the observed positive relationships.

In this study, we examined the effects of (1) unclassified tree cover (i.e., individual trees and small forest patches outside established forests) and (2) different types of forest management systems (e.g., Government Forest Reserve, Government Forest Plantation, Private Forest, Participatory Forest Management (PFM)) on people’s dietary quality, measured by macro- and micronutrient adequacy levels. By doing so, we demonstrate how different tree and forest systems can have varying effects on diets—and we thereby contribute to a more nuanced understanding of forest-tree-diet linkages.

Material and methods

Study sites.

Tanzania is an appropriate country for studying the linkages between forests, trees, and people’s diets for a number of reasons. First, the country hosts several large bio-diverse forests (Capitani et al. 2019 ; Kacholi et al. 2015 ) and around 30% of the population live within 5 km of a forest (Newton et al. 2020 ). Second, case studies from different parts of the country have shown how communities rely on forest-based resources in their diet (Murray et al. 2001 ; Ceppi and Nielsen 2014 ; Kaya and Lyana 2014 ; Pollom et al. 2020 ). For example, a study in the North Uluguru and the West Usambara Mountains revealed that local communities consumed 114 different indigenous forest plant foods (Msuya et al. 2010 ). Another study among women living in close proximity to forests in the East Usambara Mountains identified 92 wild food species and found these wild foods to be an important source of vitamin A (31% of intake), vitamin C (20%), and iron (19%) for both women and children (Powell et al. 2013 ). Furthermore, deforestation in rural areas of Tanzania has been shown to reduce people’s fruit and vegetable consumption, with negative effects on vitamin A adequacy (Hall et al. 2022 ). Tanzania’s forests are also under increasing pressure from agricultural expansion and logging activities (Doggart et al. 2020 ). Finally, despite more than 20 years of sustained economic growth, culminating in its transition from low-income to lower middle-income status in 2020, the proportion of people suffering from severe food insecurity has increased from 21 to 26% between 2016 and 2022 (FAO et al. 2022 ). In addition, the number of people not able to afford a healthy diet increased from 49 to 52 million between 2017 and 2020, corresponding to 88% of the country’s population (FAO et al. 2022 ).

In this study, we collected data from eight villages in East Usambara Mountains and Uluguru Mountains in Tanzania from October to December 2021 (Fig.  1 ). The villages were selected to represent different forest management systems, while being relatively similar in terms of people’s living standards, agricultural practices, and climatic conditions.

Forest management systems, position coordinates, elevation and mean Multidimensional Poverty Index (MPI) Living Standard dimension across the eight villages included in the study. The red dots represent the survey respondents’ homes and show variation in vitamin A adequacy levels within and across sites. The locations have been randomly displaced up to 300 m for confidentiality purposes

Within each of the eight villages, we surveyed women with at least one child under the age of five years, since this group is particularly vulnerable to nutritional deficiencies (Lartey 2008 ). We selected 60 women from each village using a random stratified sampling technique. That is, every village consisted of four to eight hamlets, and we selected respondents from each hamlet proportional to its relative population size. For example, when 25% of the village’s total population lived in one hamlet, we would randomly select 25% (or 15 women) of our respondents from that hamlet.

Forest management classification

We base our forest categories on Tanzania’s official forest classifications (United Republic of Tanzania, 1998 , 2002 ). The country’s forests are grouped into the following categories of ownership: (1) Central Government Forest Reserve —owned and managed by the central government, including both forest reserves and forest plantations), (2) Local Authority Forest Reserve— owned and managed by district authorities, (3) Village Forest Reserve— owned and managed by a village government, (4) Private Forest owned and managed by private companies, and (5) forest patches in non-reserved forest land —covering small tree plots less than 10 hectares, sometimes owned by the Central Government but most often with open access.

In addition, Community Based Forest Management (CBFM) takes place on village land. Villagers take full ownership and management responsibilities for the forest, and they also collect forest royalties from the sales of forest products and services. Finally, Joint Forest Management is based on a partnership between communities and the government and has typically been introduced in Central Government Forest Reserves that were previously under the management of the central government (United Republic of Tanzania 2008 ). The partnership means that communities are given more responsibilities in terms of managing the use of forest resources, while the central government continues to hold ownership (Mbwambo et al. 2012 ).

We regrouped these categories based on the actors managing the forest. Village Forest Reserve , CBFM and Joint Forest Management were combined into one category named Participatory Forest Management (PFM) . This regrouping is reasonable because (1) forest access was similar across these three types, and (2) forest management is given to local communities—yet with some differences in forest ownership (Khatun et al. 2015 ; Luswaga and Nuppenau 2020 ). Also, PFM is formally used as an umbrella term in Tanzania to cover the above-mentioned categories (United Republic of Tanzania 1998 ). Using QGIS and shapefiles showing official forest boundaries provided by the Central Government of Tanzania, we renamed and divided Central Government Forest Reserves into two groups: Government Forest Reserves and Government Forest Plantations. We renamed forest patches in non-reserved forest land to unclassified tree cover and expanded the category to include all trees outside of the above-mentioned forest categories, regardless of the plot size to also capture scattered trees in the landscape. Private Forest was maintained as a separate category. We did not include Local Authority Forest Reserve since this type of ownership was not present in any of our study sites.

Forest and tree data

We collected GPS coordinates of the respondents’ homes, allowing us to measure the amount of tree cover in each respondent’s nearby surroundings. In this study, a tree is defined as a plant with a more or less permanent shoot system that is supported by a single trunk of wood (Mbuya et al. 1994 ). We used a Very High Resolution (VHR) map of African tree cover in 2019 (Reiner et al. 2023 ), which was created using a deep learning model to segment tree cover at the individual tree level, based on 3-m resolution PlanetScope. We spatially aggregated the binary tree cover data to extract the percentage tree cover in 2000-m radius buffer circles around each respondent’s house. We used a radius of 2000 m since this is the distance most wild foods are collected from people’s homes (Layton et al. 1991 ; Powell et al. 2011 ). We then overlaid this with shapefiles provided by the Tanzanian government on polygons of Government Forest Reserves, Government Forest Plantations, Private Forests, and PFMs. For each respondent, we thus obtained the percentage tree cover within each of the five forest/tree categories: Government Forest Reserve, Government Forest Plantation, Private Forest, PFM, and unclassified tree cover.

Outcome variables

Most studies on forest-tree-diet linkages use food security metrics such as days without food, the household food insecurity access scale (Donn et al. 2016 ; Tata Ngome et al. 2019 ), or dietary diversity scores (Galway et al. 2018 ; Rasolofoson et al. 2018 ). Here, we go beyond these metrics by estimating people’s macro- and micronutrient intake, with our main outcome variables being people’s energy, protein, iron, zinc, and vitamin A adequacy. Nutrient adequacy ratios (NAR) were calculated from detailed dietary recall surveys, which aim to record every food item that the respondent has consumed within the past 24 hours. The 24-h dietary recalls were carried out twice within a week on two non-consecutive days to account for unusual dietary intakes (Gibson 2005 ). Quantities of each food item were estimated using local serving size aids (e.g., cups, plates, spoons) and photo aids.

We then estimated macro- and micronutrient contents of all reported food items using nutritional information from food composition tables (FCTs). A number of FCTs were used due to missing or incomplete nutrient information. We used data from the Tanzanian tables (Lukmanji and Hertzmark 2008 ) as much as possible. When data were missing, we sourced data from the FCTs for Kenya (FAO 2018a ), Malawi (MAFOODS 2019 ), Zambia (NFNC 2009 ) and West Africa (Vincent et al. 2020 )—in that order.

Since all of our respondents were interviewed twice within one week, we were able to calculate the usual intake with a Multiple Source Method (MSM) (Tooze 2020 ). The methodology consists of three sequential steps: Initially, the probability of consuming a particular food on a given day is estimated for each individual. Subsequently, the usual amount of food intake on days when consumption occurs is estimated individually. Finally, the overall usual food intake across all days is computed by multiplying the probability of food consumption with the usual amount of food intake on consumption days (Harttig et al. 2011 ). We then calculated mean NAR by comparing the estimated nutrient intakes with average recommended nutrient intakes for energy (FAO et al. 2002 ), protein (WHO 2007 ), iron, zinc and vitamin A (WHO and FAO 2004 ). The adequacy ratios accounted for whether women were pregnant or breastfeeding. We note that our final adequacy ratios might be underestimated due to known issues with underreporting of certain food items, for example in cases where respondents eat from a shared bowl (Gibson 2005 ). Therefore, we interpret the calculated adequacy levels as relative values between respondents rather than total values to be compared with national or international averages.

We calculated dietary diversity scores (DDS) given that more diverse diets are a good proxy for micronutrient intake and overall dietary quality (Kennedy et al. 2007 ; Verger et al. 2019 ). To measure dietary diversity, we used the Minimum Dietary Diversity Score for Women (MDD-W), which categorizes foods into ten groups: (1) Grains, white roots and tubers, and plantains, (2) pulses (beans, peas and lentils), (3) nuts and seeds, (4) dairy, (5) meat, poultry and fish, (6) eggs, (7) dark green leafy vegetables, (8) other vitamin A-rich fruits and vegetables, (9) other vegetables, and (10) other fruits (FAO 2021 ; FAO and FHI 360 2016 ).

In addition to calculating DDS, we focused specifically on the consumption of each of the six most nutritionally important food groups (‘grains, white roots and tubers, and plantains’, ‘pulses’, ‘meat, poultry and fish’, ‘dark green leafy vegetables’, ‘other vitamin A-rich fruits and vegetables’, and ‘other fruits’). Together, these six groups represent 99% of respondents’ nutrient intake (i.e., for protein, iron, zinc, and vitamin A) (Fig. S2 ).

We controlled for a number of variables known to affect people’s diets and thus confound the relationship between forests, trees, and diets. We controlled for agricultural practices (i.e., total crop count, homegarden presence, tropical livestock units (TLU))—as more diverse crop and/or livestock production can lead to better overall dietary quality (Ali and Khan 2013 ; Jones 2017 ; Headey et al. 2018 ; Sibhatu and Qaim 2018 ; Christian et al. 2019 ). We calculated TLU using conversion factors for each livestock owned by the household according to FAO’s guidelines (FAO 2018b ). We also controlled for individual and household characteristics known to affect diets, including age (Malapit et al. 2015 ), education level measured as years of schooling (Torheim et al. 2004 ), living standards, region, and household size (Workicho et al. 2016 ; Powell et al. 2017 ). To assess living standards, we used the Multidimensional Poverty Index (MPI) Living Standard dimension, ranging from 1 (deprived) to 0 (not deprived) and based on six indicators; cooking fuel, sanitation, drinking water, electricity, housing, and assets (Alkire et al. 2021 ). We used the distance to the nearest road from the household (based on respondents’ estimated walking time) as a proxy for market access, which is known to influence people’s consumption of specific foods (Ickowitz et al. 2019 ). We used distance to the nearest road rather than other variables such as distance to the nearest market as local people had different perceptions of market definitions (e.g., minor stand by the road, permanent market, travelling market). Finally, when using one of the five tree or forest categories as the ‘treatment’ variable (e.g., unclassified tree cover), we controlled for the other four categories (e.g., Government Forest Reserve, Government Forest Plantation, Private Forest, and PFM). Table S1 provides an overview of all covariates.

Statistical approach

We tested whether tree cover (%) within our five tree and forest categories was associated with people’s dietary adequacy and dietary diversity. We employed Covariate Balancing Generalized Propensity Score (CBGPS) matching, which is a quasi-experimental technique. CBGPS was chosen because it is robust to model misspecifications and applicable in the case of a continuous treatment (Imai and Ratkovic 2014 ). The weights produced by CBGPS minimize the correlation between treatment and observable pre-treatment covariates when included in the subsequent regression models. This reduces the dependence (endogeneity) between treatment assignment and outcome given covariates. If not addressed, this dependence may lead to biased estimates of the effects of tree cover on people’s dietary quality. CBGPS extends traditional propensity score methods used for binary treatments by creating inverse propensity score weights (Fong et al. 2018 ). To calculate CBGPS weights, we used the control variables mentioned earlier as pre-treatment variables: Crop count, homegarden presence, TLU, age and educational level of the respondent, MPI living standards, household size, region, distance to nearest road and the remaining four forest and tree categories not acting as the treatment. We used the CBPS package (Fong et al. 2022 ) in R (version 4.3.2) to perform the matching analyses. Correlations between treatment (tree cover inside Government Forest Reserve, Government Forest Plantation, Private Forest, and PFM and unclassified tree cover included one by one controlling for the other types) and covariates were sufficiently reduced after matching (Fig. S1 ). When using NAR as the outcome variable (i.e., adequacy levels for energy, protein, iron, zinc and vitamin A), we fitted a linear model using the CBGPS weights, with tree cover within the five different types of tree and forest systems as the key predictor of interest. When using the consumption of the six focus food groups (grams of unique food items consumed within each food group), we used the same model specification. When using DDS as the outcome, we applied a quasipoisson generalized linear model to account for the non-continuous categorical outcome variable (Warton et al. 2016 ). We checked for overdispersion using the ‘dispersiontest’ function in the AER package in R, but found no overdispersion in our models and therefore did not use the negative binomial distribution (Kleiber et al. 2020 ). Finally, we used the sandwich package to compute cluster-robust standard errors at the village level to adjust for the lack of independence of households within the same village (Zeileis et al. 2020 ).

We used both a pairwise correlation matrix as well as the variance inflation factor (VIF) to assess potential collinearity among independent variables included in our models. All correlation coefficients were < 0.5 and VIF did not exceed a value of 5. Lastly, to check the robustness of our results, we re-ran all models using a 1000-m radius instead of 2000-m radius (Table S2 ).

Our study has two main findings: (1) People living in areas with more unclassified tree cover (covering individual trees and forest patches) appear to have higher adequacy levels of protein, iron, zinc, and vitamin A. (2) People living in areas with greater tree cover within PFM appear to have higher adequacy levels of energy, iron, zinc, and vitamin A (Fig.  2 ; Table S1 ).

Post-matching results for how tree cover within five different types of tree and forest management systems is associated with people’s A macro- and micronutrient adequacy, and B intake of four key food groups. Results are not shown for the two food groups ‘grains, white roots and tubers, and plantains’ and ‘pulses’ as no significant results were found. P-values: * < 0.05, ** < 0.01, *** < 0.001. N = 465

Positive associations between unclassified tree cover and dietary quality

We found that the amount of unclassified tree cover is positively associated with people’s adequacy levels of protein and all three micronutrients. That is, a 1% increase in unclassified tree cover translates into higher adequacy levels of 0.6% for protein (p < 0.001), 0.2% for iron (p < 0.05), 0.3% for zinc (p < 0.05), and 0.5% for vitamin A (p < 0.001) (Fig.  2 A).

With the mean unclassified tree cover being 28.9%, an increase from no tree cover to this level would translate into 16.4%, 4.7%, 9.8%, and 14% higher adequacy levels of protein, iron, zinc, and vitamin A, respectively. Although such increases may not appear substantial, they are notable given that dietary adequacy is very low in our study area. For example, only 22% of our respondents meet protein requirements, no respondents meet iron requirements, 4% meet zinc requirements, and 14% meet vitamin A requirements.

However, such translation should be considered with caution since it assumes a continuous linear effect between increases in unclassified tree cover and people’s nutrient adequacy. Recent studies have shown how forests and trees can be linked to diets in non-linear ways (Friant et al. 2019 ; Rasmussen et al. 2019 ; Kumeh et al. 2022 ). Likewise, the potential underestimation of our respondents’ nutrient adequacy levels merits caution when interpreting these estimates.

Along with effects on nutrient adequacy levels, we also examined the effects of unclassified tree cover on people’s intake of six key food groups. We found a positive association with the intake of three food groups: ‘meat, poultry and fish’ (p < 0.05), ‘other vitamin A-rich fruits and vegetables’ (p < 0.001) and ‘other fruits’ (p < 0.001) (Fig.  2 B). Respondents with above median levels of unclassified tree cover on average consumed 111 g per day of ‘meat, poultry and fish’ compared to only 40 g for those respondents with below median tree cover (Table  1 ; Fig.  3 ). Given that 91% of the total amount of ‘meat, poultry and fish’ consumed was fish (Fig. S2 ), it is likely that this was the main driver of higher protein, iron and zinc intakes for those respondents living in areas with higher unclassified tree cover. This is in line with other studies that have documented the importance of fish consumption for dietary quality in East Africa (Wessels et al. 2023 ). Furthermore, it is likely that higher intakes of ‘other vitamin A-rich fruits and vegetables’ (especially mangos and papayas (Fig. S2 )) explain the observed positive associations between unclassified tree cover and the higher adequacy levels of vitamin A.

Share of energy, protein and micronutrients coming from the different MDD-W food groups, broken down into respondents living in areas with above vs below median unclassified tree cover. We have merged ‘nuts and seeds’, ‘dairy’, ‘eggs’ and ‘other vegetables’ into ‘other’ because these food groups contributed less than 1% of total nutrient intake. The category ‘sugar sweetened beverages’ was added to the figure as it contributed 4.5% and 3.5% of energy intake for respondents living in areas with above and below median unclassified tree cover, respectively. N = 465

Positive associations between participatory forest management and dietary quality

We also found that the extent of tree cover classified as PFM is positively associated with higher adequacy levels of energy, iron, zinc, and vitamin A as well as higher dietary diversity scores (Fig. S3 ). That is, a 1% increase in tree cover within PFM translates into increases of nutrient adequacy levels of 0.7% for energy (p < 0.05), 0.4% for iron (p < 0.001), 0.8% for zinc (p < 0.01), and 1.3% for vitamin A (p < 0.001) (Fig.  2 A). This is likely driven by higher consumption of fish, other vitamin A-rich fruits and vegetables, and other fruits, as the consumption of these food groups was also significantly positively associated with tree cover within PFM (Fig.  2 B).

By contrast, tree cover within Government Forest Plantations was negatively associated with adequacy levels of zinc (− 1.3%, p < 0.05) and vitamin A (− 1.9%, p < 0.001). Similarly, we found negative associations between tree cover within Government Forest Reserves and vitamin A (− 0.4%, p < 0.05) and Private Forests and people’s adequacy level of zinc (− 5.1%, p < 0.05). These results might be explained by lower consumption of vitamin A-rich fruits and vegetables and dark green leafy vegetables by people living in areas with more tree cover within Government Forest Plantation (− 5.9%, p < 0.01, − 1.6%, p < 0.05, respectively). Likewise, people living in areas with more tree cover within Government Forest Reserves had lower consumption of vitamin A-rich fruits and vegetables (− 3.1%, p < 0.05).

Trees and forest patches outside forests are beneficial for dietary quality

Our findings suggest that trees and small forest patches outside of established forest reserves can improve people’s nutrient adequacy. These findings demonstrate the importance of moving beyond forest/non-forest dichotomies, which have been a common approach in the forest-diet literature (e.g. Johnson et al. 2013 ; Galway et al. 2018 ). Also, the existing bulk of research on relationships between tree-based farming systems and food and nutrition security (Vansant et al. 2022 ) tends to focus on trees in croplands and thereby dismisses the potential contributions from individual trees in fallows, pasture, around settlements or along roads, lakes and rivers. By using VHR satellite data, we were able to include trees that would not be accounted for otherwise—both on farms and scattered trees outside of forests. While existing studies attending to on-farm trees often rely on self-reported counts or time-consuming field measurements, our method can be extrapolated and potentially up-scaled to cover even greater areas.

However, we were not able to distinguish between different types of trees (e.g., timber trees vs fruit trees), which limits the ability to tease apart causal mechanisms between tree cover and dietary quality. For example, we found a positive significant relationship between unclassified tree cover and people’s vitamin A adequacy levels as well as their consumption of vitamin A-rich fruits and vegetables (Fig.  2 and Table S1 ). These relationships indicate that people living in areas with higher tree cover might be consuming more vitamin A-rich fruits harvested from trees, such as mango and papaya. When looking at where people source their vitamin A-rich fruits and vegetables, we observe that people living in areas with above median tree cover source a higher proportion of this food group from the wild (4.5% as compared to 0% for people living in areas with below median tree cover) as well as from cultivated fields (61% as compared to 52%) (Table  2 ). Such explanation would be in line with other studies that have established a positive role of fruit trees for diets (Jamnadass et al. 2011 ; Bostedt et al. 2016 ; Mathewos et al. 2018 ; Omotayo and Aremu 2020 ; Kulsum and Susandarini 2023 ). For example, a study from Ethiopia found that growing fruit trees was positively associated with higher dietary diversity among women and young children in the households (Desalegn and Jagiso 2020 ).

We also found a positive association between unclassified tree cover and adequacy levels of protein, iron, and zinc. This may be explained by higher fish consumption among people living in areas with high tree cover. Positive associations between tree cover and fish consumption have also been documented in both Indonesia (Ickowitz et al. 2023 ) and Nigeria (Lo et al. 2019 ), suggesting that trees provide ecosystem services that enhance the availability of fish stocks. While we do observe a marginal higher proportion of fish being sourced from the wild among people living in areas with higher tree cover (1.8% as compared to 1.4% among people living in areas with below median tree cover), most of the consumed fish is purchased from the market rather than caught in local rivers and lakes (Table  2 ). Nevertheless, the nutritional importance of fish in East Africa is notable (Béné et al. 2016 ). It has been estimated that utilizing the entire amount of the potential sustainable catch of Silver cyprinid (small pelagic fish) in Lake Victoria would provide a sufficient daily source of vitamin B12, calcium, zinc and iron to approximately 33 million people in the region (Wessels et al. 2023 ). Twenty-five percent of our respondents consumed less than 100 g of fish relish per day. Thus, a relatively small increase in fish consumption may be a promising avenue to increase nutrient adequacy levels.

Linkages between forest management systems and dietary quality

It is well established that the type of forest management system in place matters for the type and quantity of products that people can harvest from the forest—and thereby influence the potential of forests to alleviate poverty (Miller et al. 2020 ). Yet, the role of forest management systems in relation to dietary quality has been somewhat overlooked, especially in quantitative studies. Here, we find substantial variations across different forest management systems, with positive effects seen in PFM systems and negative effects of other forest management systems (Government Forest Reserves and Government Forest Plantations).

These negative effects on people’s diets exemplify how forest conservation initiatives and profit-oriented forestry might have unintended consequences for food and nutrition security when people’s access to these forests is restricted. For example, the respondents in our study sites were only allowed to enter the Government Forest Reserves and Government Forest Plantations once a week to collect fuelwood and wild plants. When entering the Government Forest Reserves, they were not allowed to bring a machete, which made the dense part of the forests impenetrable. Also, the Government Forest Plantations were dominated by one exotic teak tree species ( Tectona grandis ) with low levels of biodiversity and relatively few wild foods to find. Multiple studies from various parts of the world have described how forest conservation can lead to negative social outcomes if local people are not appropriately compensated or included in the management regimes (Blaney et al. 2009 ; Ibarra et al. 2011 ; Sylvester et al. 2016 ; Nakamura and Hanazaki 2017 ; Campbell et al. 2021 ). For example, Hall et al. ( 2014 ) assessed both ecological and livelihood consequences of the newly established Derema Forest, a large protected forest corridor in East Usambara Mountains. Two years after establishment, the area appeared to succeed in terms of functioning as an ecologically important corridor but failed to mitigate livelihood losses especially for the poorest people (Hall et al. 2014 ). Likewise, forest conservation in Oaxaca, Mexico was perceived to make indigenous communities more food insecure as local community members found a decrease in subsistence crop yields, land available for agriculture and shortened fallow cycles to be a result of implemented conservation policies (Ibarra et al. 2011 ). More recently, a study from Southwestern Ghana suggested that forest conservation initiatives should be combined with so-called ‘food security corridors’ in degraded forest-fringes to ensure that local populations benefit from both forests and cultivated resources—which in turn can reduce exploitation of the inner forest reserve (Kumeh et al. 2022 ). Yet, we note that previous studies have also shown how mixed plantations and private forests can provide a variety of beneficial ecosystem services, including local food provision (Liu et al. 2018 ). For example, a study from the Congo Basin examined land use competition between timber concessions and fruit trees harvested by local communities and found that both interests could co-exist as long as timber harvesting only targeted the largest trees and allowed appropriate minimum distances between the remaining trees to ensure gene flow for future forest regeneration (Snook et al. 2015 ).

It is also important to emphasize that PFM is an umbrella term that covers different sub-management systems (e.g., Joint Forest Management, Community Forest Management and Village Forest Management). Although we found it reasonable to group these into one category based on similarities in terms of access to resources, these sub-systems may differ in other aspects that may affect dietary quality. For example, a study from Tanzania comparing Community Forest Management and Joint Forest Management found that the level of participation was higher among communities with Joint Forest management (Luswaga and Nuppenau 2020 ), yet the study did not measure differences in resource use. Also, PFM is not always found to have the anticipated positive effects on local livelihoods, and potential co-benefits are most often dependent on site-specific contextual factors (Duguma et al. 2018 ; Hajjar and Oldekop 2018 ). For example, participatory forest initiatives in Nepal have been centred around timber extraction and biodiversity conservation, while disregarding food security outcomes for local people (Khatri et al. 2017 ). In other words, while the results of this study suggest that the inclusion of local communities in forest management systems is more likely to produce dietary benefits, as compared to more exclusive and inaccessible forests management systems, PFM should not be perceived as a panacea to improve food and nutrition security.

Policy implications and future research directions

Our findings have policy relevance in terms of future strategies for improving local people’s food and nutrition security, particularly in rural areas of low- and middle-income countries. In particular, our findings have two key policy implications:

Decision-makers should support initiatives towards multi-functional and nutrition-rich landscapes through the promotion of trees and forest patches outside established forest reserves and in near surroundings of the targeted populations.

Because we show positive effects of PFM systems on local people’s diets, but negative effects of other forest management systems, decision-makers should attend to sustainable food extraction from community-based forests (e.g., apiculture and foraging of wild foods and medical plants).

Moreover, our study allows us to point to a number of directions for future research. Firstly, future research on linkages between forests, trees and dietary quality should move beyond dichotomies of forest versus non-forest. Trees grow not only in established forest blocks or on farmlands but are scattered across the landscape and are present along roads, rivers, and lakes. Secondly, while we have shown the potential importance of these scattered trees (not constituting a forest) in Tanzania, more work is needed to examine whether these relationships hold in other countries and contexts. Thirdly, our approach does not allow us to tease apart the dietary contributions from different tree species. Future research efforts would benefit from identification of and distinction between different tree species and their effect on people’s diets.

Data availability

The data are available from the authors upon reasonable request and with the permission of University of Copenhagen.

Adhikari J, Ojha H, Bhattarai B (2016) Edible forest? Rethinking Nepal’s forest governance in the era of food insecurity. Int for Rev 18:265–279

Article   Google Scholar  

Afentina Y, Indrayanti L, Rotinsulu JA, Hidayat N, Sianipar J (2021) The potential of agroforestry in supporting food security for peatland community—a case study in the Kalampangan village, central Kalimantan. J Ecol Eng 22:123–130

Ali A, Khan MA (2013) Livestock ownership in ensuring rural household food security in Pakistan. J Anim Plant Sci 1:133

Google Scholar  

Alkire S, Kanagaratnam U, Suppa N (2021) The global multidimensional poverty index (MPI) 2021

Andrieu N, Blundo-Canto G, Cruz-Garcia GS (2019) Trade-offs between food security and forest exploitation by mestizo households in Ucayali, Peruvian Amazon. Agric Syst 173:64–77

Asprilla-Perea J, Díaz-Puente JM (2019) Importance of wild foods to household food security in tropical forest areas. Food Secur 11:15–22

Babu SC, Rhoe V (2002) Agroforestry systems for food and nutrition security—potentials, pathways and policy research needs. J Crop Prod 6:177–192

Baier C, Gross A, Thevs N, Glaser B (2023) Effects of agroforestry on grain yield of maize ( Zea mays L.)—a global meta-analysis. Front Sustain Food Syst 7:1167686

Baudron F, Chavarria J-YD, Remans R, Yang K, Sunderland T (2017) Indirect contributions of forests to dietary diversity in Southern Ethiopia. Ecol Soc 22:28

Baudron F, Schultner J, Duriaux J-Y, Gergel SE, Sunderland T (2019a) Agriculturally productive yet biodiverse: human benefits and conservation values along a forest-agriculture gradient in Southern Ethiopia. Landsc Ecol 34:341–356

Baudron F, Tomscha SA, Powell B, Groot JCJ, Gergel SE, Sunderland T (2019b) Testing the various pathways linking forest cover to dietary diversity in tropical landscapes. Front Sustain Food Syst. https://doi.org/10.3389/fsufs.2019.00097

Béné C, Arthur R, Norbury H, Allison EH, Beveridge M, Bush S, Campling L, Leschen W, Little D, Squires D, Thilsted SH, Troell M, Williams M (2016) Contribution of fisheries and aquaculture to food security and poverty reduction: assessing the current evidence. World Dev 79:177–196

Blaney S, Beaudry M, Latham M (2009) Contribution of natural resources to nutritional status in a protected area of Gabon. Food Nutr Bull 30:49–62

Article   PubMed   Google Scholar  

Bostedt G, Hörnell A, Nyberg G (2016) Agroforestry extension and dietary diversity—an analysis of the importance of fruit and vegetable consumption in West Pokot. Kenya Food Secur 8:271–284

Brandt M, Tucker CJ, Kariryaa A, Rasmussen K, Abel C, Small J, Chave J, Rasmussen LV, Hiernaux P, Diouf AA, Kergoat L, Mertz O, Igel C, Gieseke F, Schöning J, Li S, Melocik K, Meyer J, Sinno S, Romero E, Glennie E, Montagu A, Dendoncker M, Fensholt R (2020) An unexpectedly large count of trees in the West African Sahara and Sahel. Nature 587:78–82

Article   CAS   PubMed   Google Scholar  

Campbell D, Moulton AA, Barker D, Malcolm T, Scott L, Spence A, Tomlinson J, Wallace T (2021) Wild food harvest, food security, and biodiversity conservation in Jamaica: a case study of the Millbank farming region. Front Sustain Food Syst. https://doi.org/10.3389/fsufs.2021.663863

Capitani C, van Soesbergen A, Mukama K, Malugu I, Mbilinyi B, Chamuya N, Kempen B, Malimbwi R, Mant R, Munishi P, Njana MA, Ortmann A, Platts PJ, Runsten L, Sassen M, Sayo P, Shirima D, Zahabu E, Burgess ND, Marchant R (2019) Scenarios of land use and land cover change and their multiple impacts on natural capital in Tanzania. Environ Conserv 46:17–24

Ceppi SL, Nielsen MR (2014) A comparative study on bushmeat consumption patterns in ten tribes in Tanzania. Trop Conserv Sci 7:272–287

Cheek J, Lambrecht N, den Braber B, Rasmussen L, Akanchha N, Govindarajulu D, Jones A, Chhatre A (2022) Wild foods contribute to higher dietary diversity in India (preprint). https://doi.org/10.21203/rs.3.rs-2053935/v1

Christian AK, Wilson ML, Aryeetey RNO, Jones AD (2019) Livestock ownership, household food security and childhood anaemia in rural Ghana. PLoS ONE 14:e0219310

Article   CAS   PubMed   PubMed Central   Google Scholar  

Dagar JC, Gupta SR, Teketay D (2020) Agroforestry for degraded landscapes: recent advances and emerging challenges. Springer Singapore, Singapore

Book   Google Scholar  

Den Braber B, Hall C, Brandt M, Reiner F, Mugabowindekwe M, Rasmussen LV (2024) Even low levels of tree cover improve dietary quality in West Africa. PNAS Nexus 3:067

Article   CAS   Google Scholar  

Desalegn BB, Jagiso B (2020) Low diet diversity and its associated factors among the mothers and their children in agroforestry land use systems of Sidama, Ethiopia: a community-based cross-sectional study. Cogent Food Agric. https://doi.org/10.1080/23311932.2020.1818367

Dhakal B, Bigsby H, Cullen R (2011) Forests for food security and livelihood sustainability: policy problems and opportunities for small farmers in Nepal. J Sustain Agric 35:86–115

Doggart N, Morgan-Brown T, Lyimo E, Mbilinyi B, Meshack CK, Sallu SM, Spracklen DV (2020) Agriculture is the main driver of deforestation in Tanzania. Environ Res Lett 15:034028

Donn P, Ngondi JL, Tieguhong JC, Iponga DM, Tchingsabe O, Fungo R, Tchatat M, Kahindo JM (2016) Poverty and poor education are key determinants of high household food insecurity among populations adjoining forest concessions in the Congo Basin. BMC Nutr. https://doi.org/10.1186/s40795-016-0070-x

Duguma LA, Atela J, Ayana AN, Alemagi D, Mpanda M, Nyago M, Minang PA, Nzyoka JM, Foundjem-Tita D, Ngo Ntamag-Ndjebet C (2018) Community forestry frameworks in sub-Saharan Africa and the impact on sustainable development. Ecol Soc 23:art21

FAO (2018a) Kenya Food Composition Tables. FAO & Government of Kenya, Nairobi

FAO (2018b) Guidelines on methods for estimating livestock production and productivity

FAO (2021) Minimum dietary diversity for women. FAO. https://doi.org/10.4060/cb3434en

FAO, FHI 360 (2016) Minimum dietary diversity for women—a guide to measurement. Rome FAO

FAO, WHO, UNU, (2002) Human energy requirements (No. 1), Food and Nutrition Technical Report Series. FAO/WHO/UNU Expert Consultation, Rome.

FAO, IFAD, UNICEF, WFP, WHO (2022) The State of Food Security and Nutrition in the World 2022. Repurposing food and agricultural policies to make healthy diets more affordable. Rome, FAO. https://doi.org/10.4060/cc0639en

Fong C, Hazlett C, Imai K (2018) Covariate balancing propensity score for a continuous treatment: application to the efficacy of political advertisements. Ann Appl Stat. https://doi.org/10.1214/17-AOAS1101

Fong C, Ratkovic M, Kosuke I, Hazlett C (2022) Covariate balancing propensity score. R Package “CBPS”

Friant S, Ayambem WA, Alobi AO, Ifebueme NM, Otukpa OM, Ogar DA, Alawa CBI, Goldberg TL, Jacka JK, Rothman JM (2019) Life on the rainforest edge: food security in the agricultural-forest frontier of cross river state, Nigeria. Front Sustain Food Syst. https://doi.org/10.3389/fsufs.2019.00113

Galway LP, Acharya Y, Jones AD (2018) Deforestation and child diet diversity: a geospatial analysis of 15 Sub-Saharan African countries. Health Place 51:78–88

Gergel SE, Powell B, Baudron F, Wood SLR, Rhemtulla JM, Kennedy G, Rasmussen LV, Ickowitz A, Fagan ME, Smithwick EAH, Ranieri J, Wood SA, Groot JCJ, Sunderland TCH (2020) Conceptual links between landscape diversity and diet diversity: a roadmap for transdisciplinary research. Bioscience 70:563–575

Article   PubMed   PubMed Central   Google Scholar  

Ghosh-Jerath S, Kapoor R, Singh A, Nilima Downs S, Goldberg G, Fanzo J (2021) Agroforestry diversity, indigenous food consumption and nutritional outcomes in Sauria Paharia tribal women of Jharkhand, India. Matern Child Nutr. https://doi.org/10.1111/mcn.13052

Gibson RS (2005) Principles of nutritional assessment. Oxford University Press, USA

Hajjar R, Oldekop JA (2018) Research frontiers in community forest management. Curr Opin Environ Sustain 32:119–125

Hall JM, Burgess ND, Rantala S, Vihemaeki H, Jambiya G, Gereau RE, Makonda F, Njilima F, Sumbi P, Kizaji A (2014) Ecological and social outcomes of a new protected area in Tanzania. Conserv Biol 28:1512–1521

Hall CM, Rasmussen LV, Powell B, Dyngeland C, Jung S, Olesen RS (2022) Deforestation reduces fruit and vegetable consumption in rural Tanzania. Proc Natl Acad Sci USA 119:e2112063119

Harttig U, Haubrock J, Knüppel S, Boeing H, on behalf of the EFCOVAL Consortium (2011) The MSM program: web-based statistics package for estimating usual dietary intake using the multiple source method. Eur J Clin Nutr 65:S87–S91

Headey D, Hirvonen K, Hoddinott J (2018) Animal sourced foods and child stunting. Am J Agric Econ 100:1302–1319

Ibarra JT, Barreau A, del Campo C, Camacho CI, Martin GJ, McCandless SR (2011) When formal and market-Based conservation mechanisms disrupt food sovereignty: impacts of community conservation and payments for environmental services on an indigenous community of Oaxaca, Mexico. Spec Issue for Biodivers Food Secur 13:318–337

Ickowitz A, Powell B, Salim MA, Sunderland TCH (2014) Dietary quality and tree cover in Africa. Glob Environ Change 24:287–294

Ickowitz A, Powell B, Rowland D, Jones A, Sunderland T (2019) Agricultural intensification, dietary diversity, and markets in the global food security narrative. Glob Food Secur 20:9–16

Ickowitz A, Lo MGY, Nurhasan M, Maulana AM, Brown BM (2023) Quantifying the contribution of mangroves to local fish consumption in Indonesia: a cross-sectional spatial analysis. Lancet Planet Health 7:e819–e830

Imai K, Ratkovic M (2014) Covariate balancing propensity score. J R Stat Soc Ser B Stat Methodol 76:243–263

Jamnadass RH, Dawson IK, Franzel S, Leakey RRB, Mithöfer D, Akinnifesi FK, Tchoundjeu Z (2011) Improving livelihoods and nutrition in sub-Saharan Africa through the promotion of indigenous and exotic fruit production in smallholders’ agroforestry systems: a review. Int for Rev 13:338–354

Jamnadass R, Place F, Torquebiau E, Malézieux E, Iiyama M, Sileshi GW, Kehlenbeck K, Masters E, McMullin S, Dawson IK (2013) Agroforestry for food and nutritional security. Unasylva 64:23–29

Jemal OM, Callo-Concha D, van Noordwijk M (2021) Coffee agroforestry and the food and nutrition security of small farmers of south–western Ethiopia. Front Sustain Food Syst. https://doi.org/10.3389/fsufs.2021.608868

Johnson KB, Jacob A, Brown ME (2013) Forest cover associated with improved child health and nutrition: evidence from the Malawi demographic and health survey and satellite data. Glob Health Sci Pract 1:237–248

Jones AD (2017) On-farm crop species richness is associated with household diet diversity and quality in subsistence- and market-oriented farming households in Malawi. J Nutr 147:86–96

Kacholi DS, Whitbread AM, Worbes M (2015) Diversity, abundance, and structure of tree communities in the Uluguru forests in the Morogoro region. Tanzania J for Res 26:557–569

Karki R, Shrestha KK, Ojha H, Paudel N, Khatri DB, Nuberg I, Adhikary A (2018) From forests to food security: pathways in Nepal’s community Forestry. Small-Scale for 17:89–104

Kaya HO, Lyana A (2014) Knowledge and perceptions of rural communities on wild food resources consumption in Tanzania. J Hum Ecol 48:53–60

Kennedy GL, Pedro MR, Seghieri C, Nantel G, Brouwer I (2007) Dietary diversity score is a useful indicator of micronutrient intake in non-breast-feeding Filipino children2. J Nutr 137:472–477

Khan A, Bajwa GA, Yang X, Hayat M, Muhammad J, Ali F, Quddoos A, Amin M, Khan TU, Khan AU (2023) Determining effect of tree on wheat growth and yield parameters at three tree-base distances in wheat/Jand ( Prosopis cineraria ) agroforestry systems. Agrofor Syst 97:187–196

Khatri D, Shrestha K, Ojha H, Paudel G, Paudel N, Pain A (2017) Reframing community forest governance for food security in Nepal. Environ Conserv 44:174–182. https://doi.org/10.1017/S0376892916000369

Khatun K, Gross-Camp N, Corbera E, Martin A, Ball S, Massao G (2015) When participatory forest management makes money: insights from Tanzania on governance, benefit sharing, and implications for REDD. Environ Plan A 47:2097–2112

Kleiber C, Zeileis A, Zeileis MA (2020). Package ‘aer.’ R Package Version 1

Kulsum NNS, Susandarini R (2023) Diversity of wild edible fruits in the agroforestry area of Cigalontang Village, Tasikmalaya, Indonesia. Biodiversitas J Biol Divers. https://doi.org/10.13057/biodiv/d240755

Kumeh EM, Bieling C, Birner R (2021) Food-security corridors: a crucial but missing link in tackling deforestation in southwestern Ghana. Land Use Policy. https://doi.org/10.1016/j.landusepol.2021.105862

Kumeh EM, Bieling C, Birner R (2022) Food-security corridors: a crucial but missing link in tackling deforestation in southwestern Ghana. Land Use Policy. https://doi.org/10.1016/j.landusepol.2021.105862

Kuyah S, Öborn I, Jonsson M, Dahlin AS, Barrios E, Muthuri C, Malmer A, Nyaga J, Magaju C, Namirembe S, Nyberg Y, Sinclair FL (2016) Trees in agricultural landscapes enhance provision of ecosystem services in Sub-Saharan Africa. Int J Biodivers Sci Ecosyst Serv Manag. https://doi.org/10.1080/21513732.2016.1214178

Kuyah S, Whitney CW, Jonsson M, Sileshi GW, Öborn I, Muthuri CW, Luedeling E (2019) Agroforestry delivers a win-win solution for ecosystem services in sub-Saharan Africa. A Meta-Anal Agron Sustain Dev 39:47

Lartey A (2008) Maternal and child nutrition in Sub-Saharan Africa: challenges and interventions. Proc Nutr Soc 67:105–108

Layton R, Foley R, Williams E, Chang C, Ingold T, Olszewski DI, Rosenberg M, Shackley MS, Smith EA, Zvelebil M (1991) The transition between hunting and gathering and the specialized husbandry of resources: a socio-ecological approach [and comments and reply]. Curr Anthropol 32:255–274

Liu CLC, Kuchma O, Krutovsky KV (2018) Mixed-species versus monocultures in plantation forestry: development, benefits, ecosystem services and perspectives for the future. Glob Ecol Conserv 15:e00419

Lo M, Narulita S, Ickowitz A (2019) The relationship between forests and freshwater fish consumption in rural Nigeria. PLoS ONE 14:e0218038

Lukmanji Z, Hertzmark E (2008) Tanzania food composition tables. MUHAS, TFNC and HSPH, Dar es Salaam, Tanzania

Luswaga H, Nuppenau E-A (2020) Participatory forest management in west Usambara Tanzania: what is the community perception on success? Sustainability 12:921

MAFOODS (2019) Malawian food composition table. Lilongwe, Malawi

Malapit HJL, Kadiyala S, Quisumbing AR, Cunningham K, Tyagi P (2015) Women’s empowerment mitigates the negative effects of low production diversity on maternal and child nutrition in Nepal. J Dev Stud 51:1097–1123

Mathewos M, Hundera K, Biber-Freudenberger L (2018) Planting fruits and vegetables in homegarden as a way to improve livelihoods and conserve plant biodiversity. Agric Switz. https://doi.org/10.3390/agriculture8120190

Mbuya LP, Msanga HP, Ruffo CK, Birnie A, Tengnas BO (1994) Useful trees and shrubs for Tanzania. Identification, propagation and management for agricultural and pastoral communities. Regional Soil Conservation Unit (RSCU)/Swedish International Development Authority (SIDA). Swedish Embassy, Nairobi

Mbwambo L, Eid T, Malimbwi RE, Zahabu E, Kajembe GC, Luoga E (2012) Impact of decentralised forest management on forest resource conditions in Tanzania. For Trees Livelihoods 21:97–113

Miller DC, Mansourian S, Wildburger C (2020) Forests, trees and the eradication of poverty: potential and limitations. A global assessment report. International Union of Forest Research Organizations (IUFRO)

Montagnini F (2017) Integrating landscapes: agroforestry for biodiversity conservation and food sovereignty, advances in agroforestry. Springer, Cham

Msuya TS, Kideghesho JR, Mosha TCE (2010) Availability, preference, and consumption of indigenous forest foods in the eastern arc mountains, Tanzania. Ecol Food Nutr 49:208–227

Murray SS, Schoeninger MJ, Bunn HT, Pickering TR, Marlett JA (2001) Nutritional composition of some wild plant foods and honey used by hadza foragers of Tanzania. J Food Compos Anal 14:3–13

Nakamura EM, Hanazaki N (2017) Protected area establishment and its implications for local food security. Hum Ecol Rev 23:101–122

Ndoli A, Mukuralinda A, Schut AGT, Iiyama M, Ndayambaje JD, Mowo JG, Giller KE, Baudron F (2021) On-farm trees are a safety net for the poorest households rather than a major contributor to food security in Rwanda. Food Secur 13:685–699

Newton P, Kinzer AT, Miller DC, Oldekop JA, Agrawal A (2020) The number and spatial distribution of forest-proximate people globally. One Earth 3:363–370

NFNC (2009) Zambia food composition tables (No. 4th edition). National Food and Nutrition Commission (NFNC), Republic of Zambia

Ngang FD, Azinwie AG, Tellen AV, Nchang CL (2018) Community forest use and dependence for livelihoods in Fako division, south west region of Cameroon. Greener J Agron for Hortic. 5:1–11

Omotayo AO, Aremu AO (2020) Underutilized African indigenous fruit trees and food–nutrition security: opportunities, challenges, and prospects. Food Energy Secur. https://doi.org/10.1002/fes3.220

Pailler S, Naidoo R, Burgess ND, Freeman OE, Fisher B (2015) Impacts of community-based natural resource management on wealth, food security and child health in Tanzania. PLoS ONE 10:e0133252

Paudel J (2018) Community-managed forests, household fuelwood use and food consumption. Ecol Econ 147:62–73

Pollom TR, Herlosky KN, Mabulla IA, Crittenden AN (2020) Changes in juvenile foraging behavior among the hadza of Tanzania during early transition to a mixed-subsistence economy. Hum Nat 31:123–140

Powell B, Hall J, Johns T (2011) Forest cover, use and dietary intake in the east usambara mountains. Tanzania Int for Rev 13:305–317

Powell B, Maundu P, Kuhnlein HV, Johns T (2013) Wild foods from farm and forest in the east Usambara mountains, Tanzania. Ecol Food Nutr 52:451–478

Powell B, Bezner Kerr R, Young SL, Johns T (2017) The determinants of dietary diversity and nutrition: ethnonutrition knowledge of local people in the east Usambara mountains, Tanzania. J Ethnobiol Ethnomed. https://doi.org/10.1186/s13002-017-0150-2

Rasmussen LV, Fagan ME, Ickowitz A, Wood SLR, Kennedy G, Powell B, Baudron F, Gergel S, Jung S, Smithwick EAH, Sunderland T, Wood S, Rhemtulla JM (2019) Forest pattern, not just amount, influences dietary quality in five African countries. Glob Food Secur. https://doi.org/10.1016/j.gfs.2019.100331

Rasolofoson RA, Hanauer MM, Pappinen A, Fisher B, Ricketts TH (2018) Impacts of forests on children’s diet in rural areas across 27 developing countries. Sci Adv. https://doi.org/10.1126/sciadv.aat2853

Reiner F, Brandt M, Tong X, Skole D, Kariryaa A, Ciais P, Davies A, Hiernaux P, Chave J, Mugabowindekwe M, Igel C, Oehmcke S, Gieseke F, Li S, Liu S, Saatchi S, Boucher P, Singh J, Taugourdeau S, Dendoncker M, Song X-P, Mertz O, Tucker CJ, Fensholt R (2023) More than one quarter of Africa’s tree cover is found outside areas previously classified as forest. Nat Commun 14:2258

Schnell S, Kleinn C, Ståhl G (2015) Monitoring trees outside forests: a review. Environ Monit Assess 187:600

Sibhatu KT, Qaim M (2018) Review: Meta-analysis of the association between production diversity, diets, and nutrition in smallholder farm households. Food Policy 77:1–18

Singh P, Choudhary BB, Dwivedi RP, Arunachalam A, Kumar S, Dev I (2023) Agroforestry improves food security and reduces income variability in semi-arid tropics of central India. Agrofor Syst 97:509–518

Snook LK, Donn P, Duminil J, Fungo R, Kahindo JM, Loo J, Maukonen P, Midoko Iponga D, Mikolo Yobo C, Monthe Kameni F, Muvatsi P (2015). Trees for food and timber: are community interests in conflict with those of timber concessions in the Congo Basin? 11.

Sylvester O, Segura A, Davidson-Hunt I (2016) The protection of forest biodiversity can conflict with food access for indigenous people. Conserv Soc 14:279

Tata Ngome PI, Shackleton C, Degrande A, Nossi EJ, Ngome F (2019) Assessing household food insecurity experience in the context of deforestation in Cameroon. Food Policy 84:57–65

Tooze JA (2020) Estimating usual intakes from dietary surveys: methodologic challenges, analysis approaches, and recommendations for low- and middle-income countries. Intake—Center for Dietary Assessment/FHI Solutions, Washington, DC

Torheim LE, Ouattara F, Diarra MM, Thiam FD, Barikmo I, Hatløy A, Oshaug A (2004) Nutrient adequacy and dietary diversity in rural Mali: association and determinants. Eur J Clin Nutr 58:594–604

United Republic of Tanzania (1998) Tanzania National Forest Policy. Dar es Salaam, Tanzania

United Republic of Tanzania (2002) The National Forest Act No. 14 of 2002. Dar es Salaam, Tanzania

United Republic of Tanzania (2008) Participatory forest management. Dar es Salaam, Tanzania

Vansant EC, Mausch K, Ickowitz A, McMullin S, Karanja A, Rasmussen LV (2022) What are the links between tree-based farming and dietary quality for rural households? A review of emerging evidence in low- and middle-income countries. People Nat 4:296–311

Verger EO, Ballard TJ, Dop MC, Martin-Prevel Y (2019) Systematic review of use and interpretation of dietary diversity indicators in nutrition-sensitive agriculture literature. Glob Food Secur 20:156–169

Vincent A, Grande F, Compaore E, Amponsah G, Addy PA, Aburime LC, Ahmed D (2020) FAO/INFOODS Food Composition Table for Western Africa (2019) User guide & condensed food composition table/table de composition des aliments FAO/INFOODS pour l’Afrique de l’Ouest (2019) Guide d’utilisation & table de composition des aliments condensée. FAO, Rome

Warton DI, Lyons M, Stoklosa J, Ives AR (2016) Three points to consider when choosing a LM or GLM test for count data. Methods Ecol Evol 7:882–890

Wessels L, Kjellevold M, Kolding J, Odoli C, Aakre I, Reich F, Pucher J (2023) Putting small fish on the table: the underutilized potential of small indigenous fish to improve food and nutrition security in East Africa. Food Secur 15:1025–1039

WHO (2007) Protein and amino acid requirements in human nutrition. World Health Organization

WHO, FAO (2004) Vitamin and mineral requirements in human nutrition, 2nd ed. ed. World Health Organization; FAO, Geneva: Rome.

Workicho A, Belachew T, Feyissa GT, Wondafrash B, Lachat C, Verstraeten R, Kolsteren P (2016) Household dietary diversity and Animal Source Food consumption in Ethiopia: evidence from the 2011 Welfare Monitoring Survey. BMC Public Health 16:1192

Yahya H, Mohd Amir H, Lintangah W, Mohd Hamdan DD, Mohd Fadzwi F, Thomas GJ (2022) A systematic review on linking community livelihood in social forestry with food security. IOP Conf Ser Earth Environ Sci. https://doi.org/10.1088/1755-1315/1053/1/012018

Yang KF (2020) Forest edges near farms enhance wheat productivity measures: a test using high spatial resolution remote sensing of smallholder farms in southern Ethiopia. Front Sustain Food Syst 4:12

Zahoor S, Dutt V, Mughal AH, Pala NA, Qaisar KN, Khan PA (2021) Apple-based agroforestry systems for biomass production and carbon sequestration: implication for food security and climate change contemplates in temperate region of Northern Himalaya. India Agrofor Syst 95:367–382

Zeileis A, Köll S, Graham N (2020) Various versatile variances: an object-oriented implementation of clustered covariances in R. J Stat Softw 95:1–36

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Acknowledgements

We like to thank our research assistants Anna Peter Tesha, Hope Masanja, Kudra Ally, Maria Machilu, Mercy Mtaita, Monica Chande and Naamani Mwaisenye.

Open access funding provided by Copenhagen University. The research for this paper was funded by the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation Programme (Grant Agreement No. 853222 FORESTDIET).

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R.S.O. conceived the idea. R.S.O., C.J.K., J.K., J.M. and L.V.R designed the data collection process. R.S.O. carried out data collection. R.S.O., F.R. and C.J.K. conducted the spatial forest and tree classifications. R.S.O., L.V.R., C.H. and B.d.B. designed the analysis. R.S.O. conducted the analysis. F.R., L.V.R., B.d.B., C.H. and C.J.K. contributed with interpretations of results. All authors contributed to the writing of the paper. All authors reviewed the manuscript.

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Olesen, R.S., Reiner, F., den Braber, B. et al. The importance of different forest management systems for people’s dietary quality in Tanzania. Landsc Ecol 39 , 176 (2024). https://doi.org/10.1007/s10980-024-01961-6

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