Rasoul Yousefpour

A review of decision-making approaches to handle uncertainty and risk in adaptive forest management under climate change

Abstract• ContextThis review paper provides an overview of approaches to which we may resort for handling the complex decision problems involving uncertainty and risk that climate change implies for forest managers. Modelling approaches that could support adaptive management strategies seem to be called for, not only as climate change denotes increased economic uncertainty but also because new and more reliable information becomes available as time passes and climate changes.• AimsThe paper (1) provides a broad overview of state-of-the-art methods for optimal decision making under risk and uncertainty in forestry and (2) elaborates on the possible use of these methods in adaptive forest management under climate change.• MethodA survey of the current literature is carried out to identify approaches and developments that may prove most promising in relation to different challenges to the adaptive management of forest ecosystems under climate change.• ResultsMost studies focusing on changing, typically increasing, risks in forest management under climate change tend to build on existing approaches about changes in risk levels contingent on climate change scenarios.• ConclusionFinally, we discuss what to emphasise in future studies to improve the understanding of adaptive forest management and decision support tools needed to cope with climate change.

Are forest disturbances amplifying or canceling out climate change-induced productivity changes in European forests?

Recent studies projecting future climate change impacts on forests mainly consider either the effects of climate change on productivity or on disturbances. However, productivity and disturbances are intrinsically linked because 1) disturbances directly affect forest productivity (e.g. via a reduction in leaf area, growing stock or resource-use efficiency), and 2) disturbance susceptibility is often coupled to a certain development phase of the forest with productivity determining the time a forest is in this specific phase of susceptibility. The objective of this paper is to provide an overview of forest productivity changes in different forest regions in Europe under climate change, and partition these changes into effects induced by climate change alone and by climate change and disturbances. We present projections of climate change impacts on forest productivity from state-of-the-art forest models that dynamically simulate forest productivity and the effects of the main European disturbance agents (fire, storm, insects), driven by the same climate scenario in seven forest case studies along a large climatic gradient throughout Europe. Our study shows that, in most cases, including disturbances in the simulations exaggerate ongoing productivity declines or cancel out productivity gains in response to climate change. In fewer cases, disturbances also increase productivity or buffer climate-change induced productivity losses, e.g. because low severity fires can alleviate resource competition and increase fertilization. Even though our results cannot simply be extrapolated to other types of forests and disturbances, we argue that it is necessary to interpret climate change-induced productivity and disturbance changes jointly to capture the full range of climate change impacts on forests and to plan adaptation measures.

Knowledge update in adaptive management of forest resources under climate change: a Bayesian simulation approach

ContextWe develop a modelling concept that updates knowledge and beliefs about future climate changes, to model a decision-maker’s choice of forest management alternatives, the outcomes of which depend on the climate condition.AimsApplying Bayes’ updating, we show that while the true climate trajectory is initially unknown, it will eventually be revealed as novel information become available. How fast the decision-maker will form firm beliefs about future climate depends on the divergence among climate trajectories, the long-term speed of change, and the short-term climate variability.MethodsWe simplify climate change outcomes to three possible trajectories of low, medium and high changes. We solve a hypothetical decision-making problem of tree species choice aiming at maximising the land expectation value (LEV) and based on the updated beliefs at each time step.ResultsThe economic value of an adaptive approach would be positive and higher than a non-adaptive approach if a large change in climate state occurs and may influence forest decisions.ConclusionUpdating knowledge to handle climate change uncertainty is a valuable addition to the study of adaptive forest management in general and the analysis of forest decision-making, in particular for irreversible or costly decisions of long-term impact.

Climate Change and Decision-Making Under Uncertainty

This paper highlights the main risks and uncertainties associated with climate change in forest management. The overarching challenge is the deep uncertainty about the future direction of changes in climate denoted by representative concentration pathways (RCPs). Moreover, climate change poses new sources of risk from frequent, more intensive, and even novel disturbances in forest ecosystems. Adaptation strategies have been developed to guarantee resistance of forests to climate change and impacts, but they are mostly valid for a restricted set of climate outcomes in the future. Therefore, alternative decision-making approaches should be found to overcome the deep uncertainty about future climate development and adapt forests to future environmental conditions. We propose two decision-making approaches; portfolio diversification and robust decision-making (RDM) to solve both problems. Portfolio management is an established concept in forest utilization and requires diversification of forest structures by e.g., admixing new species, or applying different sets of silvicultural interventions. Robust decision-making is a unique approach to deal with the deep uncertainty in general, but has rarely been applied to forest management. Recent adaptations of RDM to risk management under climate change provide a good basis for application in forestry. We outline the details of RDM to this end with an example, and highly recommend its application. Finally, a consensus among politicians on a climate target, e.g., Paris agreement, may diminish the deep uncertainty about the degree of climatic change at the end of the century. However, actions pathways, i.e., scenarios to meet the climate target would stay deeply uncertain for long.

A framework for modeling adaptive forest management and decision making under climate change

Adapting the management of forest resources to climate change involves addressing several crucial aspects to provide a valid basis for decision making. These include the knowledge and belief of decision makers, the mapping of management options for the current as well as anticipated future bioclimatic and socioeconomic conditions, and the ways decisions are evaluated and made. We investigate the adaptive management process and develop a framework including these three aspects, thus providing a structured way to analyze the challenges and opportunities of managing forests in the face of climate change. We apply the framework for a range of case studies that differ in the way climate and its impacts are projected to change, the available management options, and how decision makers develop, update, and use their beliefs about climate change scenarios to select among adaptation options, each being optimal for a certain climate change scenario. We describe four stylized types of decision-making processes that differ in how they (1) take into account uncertainty and new information on the state and development of the climate and (2) evaluate alternative management decisions: the “no-change,” the “reactive,” the “trend-adaptive,” and the “forward-looking adaptive” decision-making types. Accordingly, we evaluate the experiences with alternative management strategies and recent publications on using Bayesian optimization methods that account for different simulated learning schemes based on varying knowledge, belief, and information. Finally, our proposed framework for identifying adaptation strategies provides solutions for enhancing forest structure and diversity, biomass and timber production, and reducing climate change-induced damages. They are spatially heterogeneous, reflecting the diversity in growing conditions and socioeconomic settings within Europe.

Pertinence of reactive, active, and robust adaptation strategies in forest management under climate change

Key messagePertinence of alternative adaptation strategies to business as usual, namely reactive, active, and robust adaptation strategies, can be evaluated by incorporating the expected costs and benefits of adaptation, climate change uncertainty, and the risk attitudes of decision-makers.ContextForest management is used to coping with risky and uncertain projections and estimates. However, climate change adds a major challenge and necessitates adaptation in many ways.AimsThis paper highlights the dependency of the decisions on adaptation strategies to four aspects of forest management: (i) the costs of mitigating undesirable climate change impacts on forests, (ii) the value of ecosystem goods and services to be sustained, (iii) uncertainties about future climate trajectories, and (iv) the attitude of decision-makers towards risk (risk aversion level).MethodsWe develop a framework to evaluate the pertinence of reactive, active, and robust adaptation strategies in forest management in response to climate change.ResultsBusiness as usual may still be retained if the value of the forest and cost of climate impacts are low. Otherwise, it is crucial to react and facilitate the resilience of affected forest resources or actively adapt in advance and improve forest resistance. Adaptation should be robust under any future climate conditions, if the value of the ecosystem, the impacts from climatic changes, and the uncertainty about climate scenarios are very high.ConclusionThe decision framework for adaptation should take into account multiple aspects of forest management under climate change towards an active and robust strategy.

Adopting robust decision-making to forest management under climate change

Key messageMulti-objective robust decision making is a promising decision-making method in forest management under climate change as it adequately considers deep uncertainties and handles the long-term, inflexible, and multi-objective character of decisions. This paper provides guidance for application and recommendation on the design.ContextRecent studies have promoted the application of robust decision-making approaches to adequately consider deep uncertainties in natural resource management. Yet, applications have until now hardly addressed the forest management context.AimsThis paper seeks to (i) assemble different definitions of uncertainty and draw recommendation to deal with the different levels in decision making, (ii) outline those applications that adequately deal with deep uncertainty, and (iii) systematically review the applications to natural resources management in order to (iv) propose adoption in forest management.MethodsWe conducted a systematic literature review of robust decision-making approaches and their applications in natural resource management. Different levels of uncertainty were categorized depending on available knowledge in order to provide recommendations on dealing with deep uncertainty. Robust decision-making approaches and their applications to natural resources management were evaluated based on different analysis steps. A simplified application to a hypothetical tree species selection problem illustrates that distinct robustness formulations may lead to different conclusions. Finally, robust decision-making applications to forest management under climate change uncertainty were evaluated and recommendations drawn.ResultsDeep uncertainty is not adequately considered in the forest management literature. Yet, the comparison of robust decision-making approaches and their applications to natural resource management provide guidance on applying robust decision making in forest management regarding decision contexts, decision variables, robustness metrics, and how uncertainty is depicted.ConclusionAs forest management is characterized by long decision horizons, inflexible systems, and multiple objectives, and is subject to deeply uncertain climate change, the application of a robust decision-making framework using a global, so-called satisficing robustness metric is recommended. Further recommendations are distinguished depending on the decision context.

Realizing Mitigation Efficiency of European Commercial Forests by Climate Smart Forestry

European temperate and boreal forests sequester up to 12% of Europe’s annual carbon emissions. Forest carbon density can be manipulated through management to maximize its climate mitigation potential, and fast-growing tree species may contribute the most to Climate Smart Forestry (CSF) compared to slow-growing hardwoods. This type of CSF takes into account not only forest resource potentials in sequestering carbon, but also the economic impact of regional forest products and discounts both variables over time. We used the process-based forest model 4 C to simulate European commercial forests’ growth conditions and coupled it with an optimization algorithm to simulate the implementation of CSF for 18 European countries encompassing 68.3 million ha of forest (42.4% of total EU-28 forest area). We found a European CSF policy that could sequester 7.3–11.1 billion tons of carbon, projected to be worth 103 to 141 billion euros in the 21st century. An efficient CSF policy would allocate carbon sequestration to European countries with a lower wood price, lower labor costs, high harvest costs, or a mixture thereof to increase its economic efficiency. This policy prioritized the allocation of mitigation efforts to northern, eastern and central European countries and favored fast growing conifers Picea abies and Pinus sylvestris to broadleaves Fagus sylvatica and Quercus species.

Diversification of forest management regimes secures tree microhabitats and bird abundance under climate change

The loss of biodiversity in temperate forests due to combined effect of climate change and forest management poses a major threat to the functioning of these ecosystems in the future. Climate change is expected to modify ecological processes and amplify disturbances, compromising the provisioning of multiple ecosystem services. Here we investigate the impacts of climate change and forest management on the abundance of tree microhabitats and forest birds as biodiversity proxies, using an integrated modelling approach. To perform our analysis, we calibrated tree microhabitat and bird abundance in a forest landscape in Southwestern Germany, and coupled them with a climate sensitive forest growth model. Our results show generally positive impacts of climate warming and higher harvesting intensity on bird abundance, with up to 30% increase. Conversely, climate change and wood removals above 5% of the standing volume led to a loss of tree microhabitats. A diversified set of management regimes with different harvesting intensities applied in a landscape scale was required to balance this trade-off. For example, to maximize the expected bird abundance (up to 11%) and to avoid tree microhabitat abundance loss of >20% necessitates setting aside 10.2% of the forest area aside and application of harvesting intensities < 10.4% of the standing volume. We conclude that promoting forest structural complexity by diversifying management regimes across the landscape will be key to maintain forest biodiversity in temperate forests under climate change.

Multiple uncertainties require a change of conservation practices for saproxylic beetles in managed temperate forests

In Europe, intensive forest management has severely compromised the habitat of forest insects, especially saproxylic beetles, due to the removal of deadwood and veteran trees. The loss of insect diversity may disrupt ecosystem functioning and affect the provision of important ecosystem goods and services in the future. Here we propose a novel approach for the implementation of conservation policies, by optimally allocating forest reserves and deadwood islands under multiple sources of uncertainty and minimizing economic risk. We use the saproxylic beetle Lucanus cervus as umbrella species, requiring that deadwood islands were spaced within its dispersal capacity. We show that current management and conservation practices are increasingly inefficient under changing environmental conditions and that the consideration of uncertainty requires a major expansion of conservation areas. Moreover, our results indicate that a strong diversification of management regimes, with a focus on selection forest systems, is required to reduce economic risk of forest management. We conclude that the integration of uncertainty into conservation planning may reduce the trade-off between production and conservation objectives in forest landscapes and is key to increase the efficiency of forest management in the future.