Publications

Challenges in forest management are increasing due to climate change and its associated risks. Considering the needs and demands of various stakeholders leads to more complex decision-making. The increasing amount and quality of available geographic, forest and individual tree data, the combination of this data, and the use of forest growth simulators make it possible to support forest managers in this decision-making process. Our aim was to develop a strong visualization instrument that can be used in both forest planning and stakeholder communication. We present a solution based on a game engine, where data from multiple sources (terrain data, satellite imagery, tree data) is combined into a virtual environment. The user can move freely inside this virtual forest, look at the forest from arbitrary perspectives, and observe its development over the years under different management scenarios. We demonstrate the usefulness of this approach with a study region in Switzerland. © 2024 The Authors

Thinning plays a key role in regulating the stand spatial structure (SpS) to improve the development of stand quality, and the stand has different characteristics of stand structure (SS) at different growth and development stages (DSs), so it is most important to reasonably determine the stage of growth and development of the stand to optimize the stand structure. We applied the TWINSPAN two-way indicator species analysis method to classify the different development stages of mixed hard broadleaf forests. We provided a comprehensive stand spatial structure optimization model for three selected plots at different development stages, respectively, to optimize the SpS. The results demonstrated the classified DS of 29 mixed hard broadleaf plots for three forest stages: the establishment stage, competitive stage, and quality selection stage. We then applied the SpS optimization model to our three plots; the Q(x) increased by 124.04%, 333.74%, and 116.83% when compared with those with no harvest, in which, upon the removal of 10% of the trees from the three plots, the maximum RIP values were all observed. Our results indicated that the SpS optimization model could regulate the SS for different growth stages and DSs. © 2024 by the authors.

This study evaluated vegetation management (VM) strategies under electricity distribution lines (EDLs) through ecosystem service (ES) criteria. Deforestation, worsened by insufficient VM practices, poses a threat to ecosystem stability. Using a hybrid FAHP (Fuzzy Analytic Hierarchy Process) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach, ten VM strategies were assessed based on 15 ES criteria. The FAHP results identified biodiversity, timber resources, and erosion control as the most crucial criteria due to their significant weights. The TOPSIS analysis determined that VM6 (creation and restoration of scrub edges) was the most effective strategy, achieving a value of 0.744 for reducing deforestation and enhancing energy security. VM6 helps preserve forest cover and protect infrastructure by creating a “V”-shaped structures within the EDLs corridor. This study underscores the importance of ES-oriented VM strategies for sustainable vegetation management and deforestation mitigation. It also highlights the need for incorporating scientific, ES-based decision support mechanisms into VM strategy development. Future research should expand stakeholder perspectives and conduct a comprehensive assessment of ESs to ensure that VM strategies align with ecological and socio-economic sustainability. This study provides a framework for improving VM practices and offers directions for future sustainable energy management research. This study focuses exclusively on ecological criteria for evaluating VM strategies, neglecting other dimensions. Future research should use methods like ANP and fuzzy cognitive maps to explore inter-dimension relationships and their strengths. Additionally, employing SWARA, PIPRECIA, ELECTRE, and PROMETHEE for ranking VM strategies is recommended. © 2024 by the author.

Surveys of forestry professionals who actively manage, or advise upon the management of, forest lands were conducted to determine their opinions of the usefulness of a forest management decision support model. The surveys were aimed at evaluating attitudes and concerns about the eYield model, which was developed to assist in the examination of management options for eastern United States forests. The coronavirus issue that began in 2020 necessitated a virtual workshop environment to illustrate the potential usefulness of the eYield model. Pre- and post-workshop assessment surveys suggested that there was an interest by land managers in tools like eYield that are straightforward to use. The results suggested that the instructions associated with eYield were generally clearly presented, and the outcomes produced by eYield were generally representative of real-world conditions. The surveys also indicated that people represented by the sample frame were willing to consider new technology that may be used to address complex forest land management issues. Improvements suggested by survey participants may result in greater user interaction with Internet-based decision support systems that focus on the management of land. © 2024 by the authors.

Forest ecosystems deliver multiple services crucial for human wellbeing and welfare, with complex relationships among forest ecosystem services (FESs). Implementing sustainable forest management (SFM) policy requires insights into trade-offs, conflicts and synergies among key FESs, necessitating decision-support tools for multiple objectives. However, uncertainty in key parameters adds complexity. We formulated a tri-objective optimization problem concentrating on three vital ecosystem services in Nordic boreal forests: timber supply, climate change mitigation, and biodiversity conservation. Furthermore, future timber price uncertainty was integrated into the optimization model. Utilizing the TreeSim individual-tree growth and yield simulator, we simulated forest growth and yields, carbon stocks, and biodiversity values. Pareto-optimal solutions were found for four distinct management strategies using the epsilon-constrain method to solve the optimization problem. These management strategies differed in spatial restrictions on harvest location and timing, including considerations like harvest adjacency, green-up and maximum harvest opening area (MOA). The analysis revealed trade-offs among all three objectives, with variations influenced by management intensity. Furthermore, within the Pareto solutions for each strategy, a compromise solution was identified based on the knee-point method. The study demonstrated nuanced impacts of green-up constraints related to harvest practices, showing minor effects on harvesting, carbon sequestration, and biodiversity conservation when MOA was restricted to 35 hectares or less. However, more substantial impacts were observed with a MOA limited to 60 hectares or in a strategy without spatial restrictions. Our results underscore the importance of considering multiple objectives in forest management and policy under uncertain wood prices, preventing undesired effects from a singular or deterministic approach. This work provides insights into trade-offs and synergies, contributing to strategic planning and policy design. © 2024 The Author(s)

Wildfires represent a major concern for the forests in the Mediterranean basin regions since global climate change enhances the frequency and the severity of this natural ecological disturbance agent. Wildfire models (fire spread or fire behavior models) can be of valuable help for fire risk assessment as well as for planning mitigation actions which mainly concern forest management. These models need generalized vegetation (fuel) data sets at the scales which are significant for fire/forest management. However, despite of the efforts to develop methods for generating global fuel data sets, there is a lack of fine resolution regional scale fuel data sets for the Mediterranean basin. The aim of this work is to build a fuel data set based on existing data sources for fire/forest management, risk assessment and decision-support purposes. Thus, this paper presents a database (building methods and data) of wildland fuels for Mediterranean basin vegetation stands types and in particular for those in Corsica, which gathers together most common input parameters needed by wildfire's models at several vegetation scales (i.e., stand, elements, particles). Moreover, an example is provided where simulations are run with a specific wildfire model by using the fuel input data extracted from the database. Fuel attributes have been defined to be meaningful at regional/landscape scales and are representative of stand-level characteristics. National (French) Forest Inventory (NFI) data have been mainly used for determining the fuel attributes for forest stand types. The harmonization of European NFIs generates a reliable data source available to extend and generalize the methodology presented herein to other regions or countries. © 2024 Elsevier B.V.

Changes to US wildfire policy in 2009 blurred the distinction between fires managed for resource benefits and fires with primarily suppression objectives, making management strategies difficult to track. Here, qualitative text is coded from a sample of 282 Wildland Fire Decision Support System Relative Risk Assessments completed on wildfires between 2010 and 2017 to examine the prevalence of different strategies and their associations with risk. Suppression is used most, associated with high risk. Managers discuss intent to suppress even when it is untenable. Monitoring, confine, or point protection are used much less commonly and when risk is low. The Southwest region discusses a diversity of strategies, leveraging landscape barriers from past management to support them; the Northwest discusses suppression or monitoring and rarely links strategy selection to barriers. Based on associations between physical barriers to fire spread, risk, and strategy, creating more barriers may provide a path forward to better implement fire policy. © 2024 Oxford University Press. All rights reserved.

Wildfires have become more frequent and intense in recent years, threatening terrestrial and aquatic ecosystems and neighboring urban communities. As a result, those responsible for managing wildland fires face increasing pressure to address this challenge strategically. Over the past 20 years, these managers have turned to decision support tools (DSTs) to help guide their actions. We conducted a systematic literature review to explore the landscape of decision support tools (DSTs) for wildfire management, focusing on their functionalities. We additionally examined potential gaps in their design and implementation. The systematic review led us to group decision support tools into categories for all DSTs, such as, Fire Behavior Models or Post Fire Models. These categories are not discrete and can be nested to address land management and fire response questions. Moreover, our findings highlighted a significant gap in tools that effectively integrate ease of use with collaborative capabilities, underscoring the urgency for developing more user-friendly and collaborative decision-making tools. Our research also revealed a disconnect between the academic literature's focus and the tools' actual field usage, emphasizing the need for more accurate documentation and a streamlined approach to wildfire management tool selection. We proposed further social science research to understand the real-world use and preferences of DSTs, aiming to bridge the gap between theoretical robustness and practical utility. This comprehensive analysis of DSTs addresses current wildfire management challenges and sets the stage for future advancements in developing more effective and user-oriented decision support systems. © 2024 The Author(s)

Management planning for forests in Turkey has undergone gradual evolution over the last century. Developing and implementing a comprehensive management planning framework present significant challenges. This paper evaluates the effectiveness of various forest management planning approaches implemented across the country over different time periods, with overarching planning principles. It formulates a robust planning framework and proposes improvements grounded in scientific advancements and international standards. The assessment indicated that the management plans were developed using reputable scientific methods and principles aimed at ensuring the sustainable management of forest resources with certain strengths and opportunities presented by SWOT analysis. All management plans shared a common planning concept primarily focused on maximizing wood production through the area-control harvest scheduling method (except for continuous cover forest, which employed the single tree selection method). Each management plan established its unique vision, targets, policies, objectives, and planning guidelines. Forest inventory data were gathered through a combination of ground surveys and remotely sensed data to characterize and stratify the landscape. A robust in-house management authority and governance system with appropriate technical capacity and guidelines were developed and implemented, fostering a sound common working culture and tools. However, some notable drawbacks were identified, including political pressure, biomass/carbon accounting, growth-yield modelling, economic analysis, limited characterization of the full range of ecosystem services, risk and uncertainty analysis, food security and, particularly, long-term sustainability and scenario analysis with the appropriate decision-making tools and methods. Despite a few strengths, these limitations may raise concerns about the far-sighted design and application, potentially jeopardizing the sustainable management of forest ecosystems. Proposed improvement strategies for an efficient forest ecosystem management planning system include characterization of ecosystem services, modelling their productivity, scenario analysis with a decision support system, stakeholder involvement, balancing utilization and conservation targets, conducting risk and uncertainty analysis and economic analysis of management actions. © 2024 Elsevier B.V.