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Forests provide multiple ecosystem services, some of which are competitive, while others are complementary. Pareto frontier approaches are often used to assess the trade-offs among these ecosystem services. However, when dealing with spatial optimization problems, one is faced with problems that are computationally complex. In this paper, we study the sources of this complexity and propose an approach to address adjacency conflicts while analyzing trade-offs among wood production, cork, carbon stock, erosion, fire resistance and biodiversity. This approach starts by sub-dividing a large landscape-level problem into four smaller sub-problems that do not share border stands. Then, it uses a Pareto frontier method to get a solution to each. A fifth sub-problem included all remaining stands. The solution of the latter by the Pareto frontier method is constrained by the solutions of the four sub-problems. This approach is applied to a large forested landscape in Northwestern Portugal. The results obtained show the effectiveness of using Pareto frontier approaches to analyze the trade-offs between ecosystem services in large spatial optimization problems. They highlight the existence of important trade-offs, notably between carbon stock and wood production, alongside erosion, biodiversity and wildfire resistance. These trade-offs were particularly clear at higher levels of these optimized services, while spatial constraints primarily affected the magnitude of the services rather than the underlying trade-off patterns. Moreover, in this paper, we study the impact of the size and complexity of the spatial optimization problem on the accuracy of the Pareto frontiers. Results suggest that the number of stands, and the number of adjacency conflicts do not affect accuracy. They show that accuracy decreases in the case of spatial optimization problems but it is within an acceptable range of discrepancy, thus showing that our approach can effectively support the analysis of trade-offs between ecosystem services.

Dracaena ombet, a flagship tree species in arid ecosystems, holds a significant ecological, economic, and socio-cultural value. However, its persistence is currently under threat from both anthropogenic and natural factors. Consequently, the species has been listed as an endangered tree species on the IUCN Red List, requiring urgent conservation actions for its continued existence. To develop effective conservation actions, it is necessary to have information on the population dynamics of the species. A study was conducted in the lowland and midland agroecological zones (sites) within the Desa'a dry Afromontane forest, northern Ethiopia to analyze the population status of D. ombet and identify its site-specific threats. At each site, abundance, health status, diameter, height and threats of the species were collected using 60 sample plots (20 m × 20 m) distributed over six transects (500 m × 20 m) spaced one km apart. The study showed that the D. ombet population was characterized by low abundance and unstable structure. It was further characterized by a substantial number of unhealthy damaged and dead trees. The low abundance of the species with unstable age structure in the dry Afromontane forests can be attributed to various factors such as stem cutting and debarking, leaf defoliation, overgrazing, soil erosion, and competition from expansive shrubs. Alternative livelihood options for the local inhabitants should be introduced to minimize the overexploitation of D. ombet for subsistence use in the dry Afromontane forests. The impacts of overgrazing and soil erosion on D. ombet and its Desa'a habitats should also be addressed through the introduction of community-based exclosures and in-situ soil and water conservation practices, respectively.

This research aims at presenting landscape management planning methods to help stakeholders select forest ecosystem management plans that may address concerns with wildfire risk and with the environmental impacts of clearcuts. Specifically, we develop mixed integer programming models for spatial optimization that incorporate a wildfire resistance index as well as constraints on the size of clearcut openings. The former is used to enforce a minimum level of resistance to wildfire while the latter limits the size of openings, in each period of the planning horizon. Timber volume even flow is another concern that is also taken into account. This research is applied to the Zonas de Intervenção Florestal (ZIF) de Paiva and de Entre-Douro e Sousa (ZIF_VS) which are located in northwestern Portugal.

The forest-based sector plays a significant role in supporting Europe on its pathway towards a more integrated and bio-based circular economy. Beyond the supply of timber, forest ecosystems offer a wide range of products and services beneficial to human wellbeing. Non-wood forest products (NWFPs) play an integral role in provisioning forest ecosystem services and constitute a huge portfolio of species from various taxonomic kingdoms. As diverse as the resources themselves is the list of end-products that may be derived from raw non-wood materials. Multiple value-chains of NWFPs provide benefits to actors across all stages of the supply chain. Forest management has not yet directed full attention towards NWFPs, since timber production remains the main management objective, although multi-purpose management is recognised as a key principle of the sector’s sustainability paradigm. Lack of knowledge of the socio-economic relevance of NWFPs for European societies and diverse property rights frameworks increase the complexity in forest-based decision making additionally. In this study, the future potential of 38 NWFPs for diversifying the forest bioeconomy is investigated by means of multi-criteria analysis, including stakeholder interaction and expert involvement. The results for six case studies in different biogeographical zones in Europe indicate the latent opportunities NWFPs provide to forest owners who are willing to focus their management on the joint production of wood and non-wood resources as well as their value networks. This study intends to unravel perspectives for forest owners in particular, as they often represent principal decision makers in forest ecosystem management, act as main suppliers of NWFP raw materials, and thus can be understood as key stakeholders in a forest bioeconomy. Even though regional perspectives differ, due to varying socio-economic and ecological environments, there is huge potential to strengthen the economic viability of rural areas. Furthermore, sustainable co-production may foster the ecological integrity of forest ecosystems across Europe. Results show that wild mushrooms constitute the most widespread opportunity to increase additional income from forest management, but the most promising NWFPs can be found in the tree product, understorey plant and animal origin categories.

Forest road pavement needs an evaluation methodology based on a comprehensive assessment of road conditions. This research was conducted to evaluate the performance of a method for rating the surface condition of forest roads and eventually to adapt the method to the situation prevailing in a forest road network. The rating method selected as the basis for this experiment was the pavement condition index (PCI) developed by the U.S. Army Corps of Engineers for urban roads. In addition, unpaved road condition index (URCI) that has a good index for unpaved road evaluation used for comparison. A 53 km of forest roads were selected containing the most influential factors and variability of conditions. Eventually, 201 road segments were delineated between 150–300 m in length. Within the given segments, sample plots were set 20 m in length consecutively. It was concluded that the panel scores for distress and surface condition of sample unit and section differed from the forest road pavement condition index (FRPCI), URCI, and PCI. Linear regression was used to derive equations between distress and URCI and PCI scores to determine effective FRPCI parameters that provide a numerical rating for the condition of road segments within the road network, where 0 worlds are the worst possible condition, and 100 is the best possible condition best. In addition, regression analysis showed that the FRPCI model with a 0.77 correlation for the total of the road is a performance index used for the first time in forest roads. This study showed a range of FRPCI from 7.8 to 96.3, different from PCI and URCI ratings (0.85–45 and 1.2–53). The FRPCI index helps forest managers in road maintenance, harvesting, and planning to use road information.

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.

Climate change is driving worldwide efforts to mitigate and reverse the increasing anthropogenic emissions of greenhouse gases. Forests can uptake considerable amounts of carbon from the atmosphere, but management decisions and resultant silvicultural practices can largely influence these ecosystems’ carbon balance. This research presents an approach to help land managers cope with the need to ensure the provision of forest products and services while contributing to mitigating climate change via carbon sequestration. The emphasis is on combining a landscape-level resource capability model with a mathematical programming (LP) optimization method to model and solve a land management problem involving timber production, carbon sequestration, and resistance to wildfire targets. The results of an application on a forested landscape in Northwest Portugal showed that this approach may contribute to analyzing and discussing synergies and trade-offs between these targets. They revealed important trade-offs between carbon sequestration and both timber production and fire resistance.

Abstract Background Soil erosion is still identified as the main cause of land degradation worldwide, threatening soil functions and driving several research and policy efforts to reverse it. Trees are commonly associated to some of the most successful land-use systems to achieve soil protection goals, but the extent to which forest ecosystems reduce erosion risks can largely depend on management decisions and associated silvicultural practices. Optimization tools can assist foresters in solving the complex planning problem they face, concerning the demand for different, and often conflicting, ecosystem services. A resource capability model (RCM), based on a linear programming approach, was built and solved for a forest landscape management problem in Northwest Portugal, over a 90-years planning horizon, divided in 10-years periods. Results Timber provision and soil erosion were found to be in trade-off. The management alternatives included in the model were proven to be sufficiently flexible to obtain the desired level of timber yield, both in volume and even distribution along the planning horizon, while ensuring lower levels of soil loss estimates (below 35 Mg∙ha− 1∙year− 1). However, under climate change conditions, compatible with an increasing greenhouse gases emission scenario, potential landscape soil erosion may be enhanced up to 46 Mg∙ha− 1∙year− 1 in critical periods. Conclusions Soil conservation concerns in landscape-level forest management planning can be addressed by LP-based optimization methods. Besides providing an optimal management solution at landscape level, this approach enables a comprehensive analysis of the RCM, possible trade-offs and potential changes towards uncertainties.

Forest management can be seen as a sequential decision-making problem to determine an optimal scheduling policy, e.g., harvest, thinning, or do-nothing, that can mitigate the risks of wildfire. Markov Decision Processes (MDPs) offer an efficient mathematical framework for optimizing forest management policies. However, computing optimal MDP solutions is computationally challenging for large-scale forests due to the curse of dimensionality, as the total number of forest states grows exponentially with the numbers of stands into which it is discretized. In this work, we propose a Deep Reinforcement Learning (DRL) approach to improve forest management plans that track the forest dynamics in a large area. The approach emphasizes on prevention and mitigation of wildfire risks by determining highly efficient management policies. A large-scale forest model is designed using a spatial MDP that divides the square-matrix forest into equal stands. The model considers the probability of wildfire dependent on the forest timber volume, the flammability, and the directional distribution of the wind using data that reflects the inventory of a typical eucalypt (Eucalyptus globulus Labill) plantation in Portugal. In this spatial MDP, the agent (decision-maker) takes an action at one stand at each step. We use an off-policy actor-critic with experience replay reinforcement learning approach to approximate the MDP optimal policy. In three different case studies, the approach shows good scalability for providing large-scale forest management plans. The results of the expected return value and the computed DRL policy are found identical to the exact optimum MDP solution, when this exact solution is available, i.e., for low dimensional models. DRL is also found to outperform a genetic algorithm (GA) solutions which were used as benchmarks for large-scale model policy.

Abstract Background Climate change may strongly influence soil erosion risk, namely through variations in the precipitation pattern. Forests may contribute to mitigate the impacts of climate change on soil erosion and forest managers are thus challenged by the need to define strategies that may protect the soil while addressing the demand for other ecosystem services. Our emphasis is on the development of an approach to assess the impact of silvicultural practices and forest management models on soil erosion risks under climate change. Specifically, we consider the annual variation of the cover-management factor (C) in the Revised Universal Soil Loss Equation over a range of alternative forest management models to estimate the corresponding annual soil losses, under both current and changing climate conditions. We report and discuss results of an application of this approach to a forest area in Northwestern Portugal where erosion control is the most relevant water-related ecosystem service. Results Local climate change scenarios will contribute to water erosion processes, mostly by rainfall erosivity increase. Different forest management models provide varying levels of soil protection by trees, resulting in distinct soil loss potential. Conclusions Results confirm the suitability of the proposed approach to address soil erosion concerns in forest management planning. This approach may help foresters assess management models and the corresponding silvicultural practices according to the water-related services they provide.

Considering in situ carbon storage in forest management has gained momentum under increasing pressure to decarbonize our economies. Here, we present results from case studies in Portugal and Germany showing the opportunity costs of in situ carbon storage derived by multiple-objective optimization. We used a stand-level model to optimize land expectation value under uncertainty as a reference, then derived opportunity costs by including the enhancement of the average carbon storage in aboveground biomass as a second objective. Using the optimal (compromise) solution when considering both objectives simultaneously, we show opportunity costs of EUR 119 (Portugal) and EUR 68 (Germany) per Mg CO2eq. These opportunity costs are higher than conservative, but lower than alternative cost estimates for future damages caused by current CO2 emissions. An important result was that suggested reference solutions in both countries (though only for low discount rates in Portugal) were mixed forests without clearfelling. In Germany, this implicitly elevated carbon storage. Such “closer-to-nature-forest-management” systems were also mostly suggested by the optimization tool when carbon storage was an objective.

Forest management planning is often challenged by the need to address contrasting preferences from several actors. Participatory approaches may help integrate actors’ preferences and demands and thus address this challenge. Workshops that encompass a participatory approach may further influence actors’ opinions and knowledge through social interaction and facilitate the development of collaborative landscape-level planning. Nevertheless, there is little experience of formal assessment of impacts of workshops with participatory approaches. This research addresses this gap. The emphasis is on the development of an approach (a) to quantify actors’ preferences for forest management models, post-fire management options, forest functions, and ecosystem services; (b) to assess the impact of participatory discussions on actors’ opinions; and (c) to evaluate the effect of social interaction on the actors’ learning and knowledge. The methodology involves a workshop with participatory approach, matched pre- and post-questionnaires, a non-parametric test, the Wilcoxon Signed-rank test for paired samples, and a self-evaluation questionnaire.We report results from an application to a joint forest management area in Vale do Sousa, in North-Western Portugal. Findings suggest that workshop and participatory discussions do contribute to social knowledge and learning about forest management models. Actors debated alternatives that can address their financial and wildfire risk-resistance concerns. Also, during the participatory discussions, actors expressed their interest in multifunctional forestry. These findings also suggest an opportunity to enhance forest management planning by promoting landscape-level collaborative forest management plans that may contribute to the diversification of forest management models and to the provision of a wider range of ecosystem services. However, more research is needed to strengthen the pre- and post-questionnaire approach, giving more time to actors to reflect on their preferences, to improve methods for quantifying social learning and to develop actors’ engagement strategies.

The conversion of fertile croplands to Eucalyptus woodlots in Ethiopian highlands, due to its business attractiveness to smallholders, raises concerns related to food production, water resources, carbon and other ecosystem services. This study was therefore designed to examine land allocation and plantation management decisions. Our emphasis was on the analysis of tradeoffs between the economic gains obtained from harvesting Eucalyptus timber and food production, carbon and water use. For that purpose, we considered a 1987 ha agroforest landscape in the Amhara region, Northern Ethiopia. With a planning horizon covering nine one-year periods, we developed and used nine Model I single objective linear programming (LP) models, and analyzed tradeoffs between objectives (e.g., land expectation value (LEV), Carbon, volume of ending inventory (VolEI), crop production and water use) using an LP-based Pareto frontier approach. The study revealed that the objective of maximizing the total economic gain from the sale of Eucalyptus wood poles favored a complete conversion of the available cropland into Eucalyptus woodlots. To meet the minimum annual crop production/consumption/requirements of households in the study area, the land under Eucalyptus should be limited to 1772 ha, with a sequestration potential of 1.5 to 1.57 × 107 kg yr−1 of carbon in the aboveground biomass. However, this land cover limit should be decreased to 921 ha so as to limit the total annual water use (for biomass production) below the amount available from rainfall (11,000 m3 ha−1 yr−1). Moreover, the study highlighted that maximizing the harvested wood volume or LEV would come at the cost of a decreased aboveground carbon stock and volume of ending inventory and higher total water use. It also provided alternative optimal Pareto-front points, among which decision makers will be able to select their preferred targets. The current study also showed the potential for the application of Pareto frontier approaches to support the development of effective ecological/economic management strategies and the design of land use policies in an Ethiopian context.

Europe's forests provide vital habitat for biodiversity and essential ecosystem services whose provision must be sustained or enhanced over the coming century. However, the potential to secure or increase forest ecosystem services, while securing the habitat requirements of taxa remains unclear, especially within the context of uncertain climate and socio-economic developments. To tease out the associated trade-offs and synergies, we used 10 case study landscapes within nine countries throughout Europe. Starting with the current status of the forests in the case study landscapes, we simulated forest development 100 years into the future. Simulations were embedded in three combined climate and socio-economic frame scenarios based on global and European policies which varied in their climate change mitigation efficiency. Scenarios were translated into country specific projections of climate variables, and resultant demands for wood products. Forest management regimes were projected to vary in response to these scenarios at local scales. The specific combinations of alternative forest management practices were based on parallel research and input from local forest stakeholders. For each case study, a specific forest growth simulator was used. In general, the climate scenarios applied did not cause fundamentally different ecosystem service outputs at the case study level. Our results revealed almost no reduction in outcomes for biodiversity indicators with an increase in wood production, and in some cases synergistic results occurred when diversity was actively promoted as part of the management concept. Net carbon uptake was not strongly correlated with biodiversity, indicating that biodiversity-friendly forest management doesn't need to curtail carbon sequestration. Notably, we obtained heterogeneous results for the relation between sustainable wood production and net carbon uptake. Most scenarios resulted in a more or less reduced net carbon uptake over the long term, often due to stand age class distribution shifts. Levels of sustainable wood production varied widely during the simulation period, from significant increases (Sweden, Lithuania) to minor changes (Slovakia, Turkey) and slight decreases (Ireland, Netherlands). We place our results within the larger context of European forest policy and the challenges of simulating and contrasting forest biodiversity and the ecosystem services that societies depend on.

Wildfires threaten and kill people, destroy urban and rural property, degrade air quality, ravage forest ecosystems, and contribute to global warming. Wildfire management decision support models are thus important for avoiding or mitigating the effects of these events. In this context, this paper aims at providing a review of recent applications of machine learning methods for wildfire management decision support. The emphasis is on providing a summary of these applications with a classification according to the case study type, machine learning method, case study location, and performance metrics. The review considers documents published in the last four years, using a sample of 135 documents (review articles and research articles). It is concluded that the adoption of machine learning methods may contribute to enhancing support in different fire management phases.

Decision making in modern forest management planning is challenged by the need to recognize multiple ecosystem services and to address the preferences and goals of stakeholders. This research presents an innovative a posteriori preference modeling and multi-objective integer optimization (MOIP) approach encompassing integer programming models and a new technique for generation and interactive visualization of the Pareto frontier. Due to the complexity and size of our management problems, a decomposition approach was used to build the Pareto frontier of the general problem using the Pareto frontiers of its sub-problems. The emphasis was on the approximation of convex Edgeworth–Pareto hulls (EPHs) for the sub-problems by systems of linear inequalities; the generation of Edgeworth–Pareto hulls by the convex approximation of the Pareto frontier evinced a very small discrepancy from the real integer programming solutions. The results thus highlight the possibility of generating the Pareto frontiers of large multi-objective integer problems using our approach. This research innovated the generation of Pareto frontier methods using integer programming in order to address multiple objectives, locational specificity requirements and product even-flow constraints in landscape-level management planning problems. This may contribute to enhancing the analysis of tradeoffs between ecosystem services in large-scale problems and help forest managers address effectively the demand for forest products while sustaining the provision of services in participatory management planning processes.

Forest management planning can be challenging when allocating multiple ecosystem services (ESs) to management units (MUs), given the potentially conflicting management priorities of actors. We developed a methodology to spatially allocate ESs to MUs, according to the objectives of four interest groups—civil society, forest owners, market agents, and public administration. We applied a Group Multicriteria Spatial Decision Support System approach, combining (a) Multicriteria Decision Analysis to weight the decision models; (b) a focus group and a multicriteria Pareto frontier method to negotiate a consensual solution for seven ESs; and (c) the Ecosystem Management Decision Support (EMDS) system to prioritize the allocation of ESs to MUs. We report findings from an application to a joint collaborative management area (ZIF of Vale do Sousa) in northwestern Portugal. The forest owners selected wood production as the first ES allocation priority, with lower priorities for other ESs. In opposition, the civil society assigned the highest allocation priorities to biodiversity, cork, and carbon stock, with the lowest priority being assigned to wood production. The civil society had the highest mean rank of allocation priority scores. We found significant differences in priority scores between the civil society and the other three groups, highlighting the civil society and market agents as the most discordant groups. We spatially evaluated potential for conflicts among group ESs allocation priorities. The findings suggest that this approach can be helpful to decision makers, increasing the effectiveness of forest management plan implementation.

Auctions offer potential cost-effectiveness improvements over other mechanisms for payments for ecosystem services (PES) contract allocation. However, evidence-based guidance for matching design to application is scarce and research priorities are unclear. To take stock of the current state of the art, we conducted a systematic review and thematic content analysis of 56 peer-reviewed journal articles discussing ES auctions published in the last decade. Auctions were approached from three overlapping perspectives: mechanism design, PES, and policy analysis. Five major themes emerged: (1) performance, including measures like cost-effectiveness and PES criteria like additionality; (2) information dynamics like price discovery and communication effects; (3) design innovations like risk-integrating and spatially coordinated mechanisms; (4) contextual variables like policy context and cultural values; and (5) participation factors. Additional attention from policymakers and continued efforts to coordinate research in this diverse and interdisciplinary subfield may be beneficial.

Forest management planning is a challenge due to the diverse criteria that need to be considered in the underlying decision-making process. This challenge becomes more complex in joint collaborative management areas (ZIF) because the decision now may involve numerous actors with diverse interests, preferences, and goals. In this research, we present an approach to identifying and quantifying the most relevant criteria that actors consider in a forest management planning process in a ZIF context, including quantifying the performance of seven alternative stand-level forest management models (FMM). Specifically, we developed a combined multicriteria decision analysis and group decision-making process by (a) building a cognitive map with the actors to identify the criteria and sub-criteria; (b) structuring the decision tree; (c) structuring a questionnaire to elicit the importance of criteria and sub-criteria in a pairwise comparison process, and to evaluate the FMM alternatives; and (d) applying a Delphi survey to gather actors’ preferences. We report results from an application to a case study area, ZIF of Vale do Sousa, in North-Western Portugal. Actors assigned the highest importance to the criteria income (56.8% of all actors) and risks (21.6% of all actors) and the lowest to cultural services (27.0% of all actors). Actors agreed on their preferences for the sub-criteria of income (diversification of income sources), risks (wildfires) and cultural services (leisure and recreation activities). However, there was a poor agreement among actors on the sub-criteria of the wood demand and biodiversity criteria. For 27.0% of all actors the FMM with the highest performance was the pedunculate oak and for 43.2% of all actors the eucalypt FMM was the least preferable alternative. The findings indicate that this approach can support ZIF managers in enhancing forest management planning by improving its utility for actors and facilitating its implementation.

Sustainable forest management needs to address biodiversity conservation concerns. For that purpose, forest managers need models and indicators that may help evaluate the impact of management options on biodiversity under the uncertainty of climate change scenarios. In this research we explore the potential for designing mosaics of stand-level forest management models to address biodiversity conservation objectives on a broader landscape-level. Our approach integrates (i) an effective stand-level biodiversity indicator that reflect tree species composition, stand age, and understory coverage under divergent climate conditions; and (ii) linear programming optimization techniques to guide forest actors in seeing optimal forest practices to safeguard future biodiversity. Emphasis is on the efficiency and effectiveness of an approach to help assess the impact of forest management planning on biodiversity under scenarios of climate change. Results from a resource capability model are discussed for an application to a large-scale problem encompassing 14,765 ha, extending over a 90-years planning horizon and considering two local-climate scenarios. They highlight the potential of the approach to help assess the impact of both stand and landscape-level forest management models on biodiversity conservation goals. They demonstrate further that the approach provides insights about how climate change, timber demand and wildfire resistance may impact plans that target the optimization of biodiversity values. The set of optimized long-term solutions emphasizes a multifunctional forest that guarantees a desirable local level of biodiversity and resilience to wildfires, while providing a balanced production of wood over time at the landscape scale.

This research expands the applicability of the Feasible Goals (FGoal) Pareto frontier multiple criteria method to display the Edgeworth–Pareto hull using interactive decision maps (IDMs). Emphasis is placed upon the development of a communication architecture to display the Pareto frontiers, which includes a client device, a web server, and a dedicated computation server implemented with sockets. A standalone application on the latter processes client-server requests and responses to display updated information on the client. Specifically, the dedicated computation server is responsible for calculating the information needed to generate the Edgeworth–Pareto hull. This is delivered to the web server to generate the IDM to be displayed on the client device. The key innovation of this work is a tool that is developed to aid decision-makers with a network-based computational architecture that includes a computational server constantly in communication with a web server for fast responses to client requests to represent IDMs. Results show that this innovation avoids time-consuming communication, and this approach to represent IDMs on the web facilitates collaboration among decision-makers because they can analyze several complex problems in different browser windows and decide which problem and solution better correspond to their aims.

Including biodiversity assessments in forest management planning is becoming increasingly important due to the importance of biodiversity for forest ecosystem resilience provision and sustainable functioning. Here we investigated the potential to include biodiversity indicators into forest management planning in Europe. In particular, we aimed to (i) identify biodiversity indicators and data collection methods for biodiversity assessments at the stand and landscape levels, and (ii) evaluate the practicality of those indicators for forest management planning. We performed a literature review in which we screened 188 research studies published between 1990 and 2020. We selected 94 studies that fulfilled the inclusion criteria and examined in more detail. We considered three aspects of biodiversity: structure, composition, and function, and four forest management categories: unmanaged, managed, plantation, and silvopastoral. We used three criteria to evaluate the practicality of forest biodiversity indicators: cost-effectiveness, ease of application, and time-effectiveness. We identified differences in the practicality of biodiversity indicators for their incorporation into management plans. Stand-level indicators are more practical than landscape-level indicators. Moreover, structural biodiversity indicators (e.g., large trees, canopy openness, and old forest stands) are more useful in management plans than compositional indicators, as these are easily observable by non-professionals and can be obtained by forest inventories. Compositional indicators such are vascular plants, fungi, bryophyte, lichens, and invertebrate species are hard to identify by non-professionals and thus are impractical. Functional indicators (e.g., nutrient cycling) are not sufficiently addressed in the literature. Using recently updated existing databases (e.g., national forest inventories and bird atlases) is very time and cost-efficient. Remote sensing and other technology (e.g., smartphone applications) are promising for efficient data collection in the future. However, more research is needed to make these tools more accurate and applicable to a variety of ecological conditions and scales. Until then, forest stand structural variables derived from inventories can help improve management plans to prepare European forests towards an uncertain future.

The Special Issue “Providing Ecosystem Services under Climate Change: Community of Practice of Forest Decision Support Systems” is based on the presentations given at the 24th World Congress of the International Union of Forest Research Organizations and provides an overview on Forest Management Decision Support Systems currently designed and applied for the sustained provision of ecosystem services within the context of climate change. The contributions provide an overview on models, methods, techniques used in decision support and the proposed frameworks to support decision making. With populations and economies growing worldwide, the demands on forest resources increase, and sustaining the supply of ecosystem services becomes crucial. Through growing public participation in decisions regarding the management of natural resources, new demands have emerged for tools that support our understanding of environmental issues, and for the development and evaluation of alternative management options; there is a desire to project the consequences of different courses of action. Decision Support Systems (DSS) have been proven to solve such ill-structured decision problems by integrating database management systems with analytical and operational research models, thus providing various reporting capabilities. Several case studies focus on decision problems, the development and evaluation of alternative management options, and on projecting the consequences of different courses of action in the provision of ecosystem services. Conclusions on the state-of-the-art in decision support and the needed advances in research are drawn.

Cork oak (Quercus suber L.) and holm oak (Quercus rotundifolia) ecosystems are characteristic of Mediterranean forestry in Portugal. Even though cork is the most valuable product, these ecosystems provide multiple products and services. Assessing trade-offs between multiple goals is thus critical for the effectiveness of oak ecosystem management planning. This paper focuses on the development of a decision support system for oak ecosystems’ scenario analysis including multiple criteria. It includes an innovative decision support systems (DSS) functionality to assess trade-offs between the criteria that may support negotiation and consensus building between decision-makers and forest stakeholders. Specifically, a module that encapsulates the Feasible Goals Method/Interactive Decision Maps (FGM/IDM) technique is developed for interactive visualization of the Pareto frontier. The Pareto frontier illustrates the degree to which improving one particular criterion requires accepting sacrifices in the achievements of others. It thus provides information about trade-offs between competing decision-makers’ preferences. Results are discussed for a large-scale application encompassing over 1 million ha of cork and holm oak forest ecosystems in Southern Portugal. This study demonstrates the potential of the new DSS functionality to enhance multi-objective forest planning, namely by facilitating participation by stakeholders and providing transparency to the decision-making processes.

This study examines the potential of combining decision support approaches to identify optimal bundles of ecosystem services in a framework characterized by multiple decision-makers. A forested landscape, Zona de Intervenção Florestal of Paiva and Entre-Douro and Sousa (ZIF_VS) in Portugal, is used to test and demonstrate this potential. The landscape extends over 14,388 ha, representing 1976 stands. The property is fragmented into 376 holdings. The overall analysis was performed in three steps. First, we selected six alternative solutions (A to F) in a Pareto frontier generated by a multiple-criteria method within a web-based decision support system (SADfLOR) for subsequent analysis. Next, an aspatial strategic multicriteria decision analysis (MCDA) was performed with the Criterium DecisionPlus (CDP) component of the Ecosystem Management Decision Support (EMDS) system to assess the aggregate performance of solutions A to F for the entire forested landscape with respect to their utility for delivery of ecosystem services. For the CDP analysis, SADfLOR data inputs were grouped into two sets of primary criteria: Wood Harvested and Other Ecosystem Services. Finally, a spatial logic-based assessment of solutions A to F for individual stands of the study area was performed with the NetWeaver component of EMDS. The NetWeaver model was structurally and computationally equivalent to the CDP model, but the key NetWeaver metric is a measure of the strength of evidence that solutions for specific stands were optimal for the unit. We conclude with a discussion of how the combination of decision support approaches encapsulated in the two systems could be further automated in order to rank several efficient solutions in a Pareto frontier and generate a consensual solution.

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.