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Special Issue "Decision Support Approaches in Adaptive Forest Management—Selected Papers from the IUFRO 125th Anniversary Congress"

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Ecology and Management".

Deadline for manuscript submissions: closed (31 December 2017)

Special Issue Editors

Guest Editor
Dr. Jan Kašpar

Department of Forest Management, Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 165 00, Prague, Czech Republic
Website | E-Mail
Interests: sustainable forest management; decision support systems; optimization; spatial harvest scheduling
Guest Editor
Prof. Dr. Pete Bettinger

Warnell School of Forestry and Natural Resources, University of Georgia, 180 East Green Street, Athens, GA 30602, USA
Website | E-Mail
Interests: forest management and planning; combinatorial optimization; spatial harvest scheduling; landscape planning; geographic information systems; global positioning systems; urban forests
Guest Editor
Prof. Dr. Harald Vacik

Institute of Silviculture, University of Natural Resources and Applied Life Sciences, Vienna, Austria
Website | E-Mail
Interests: sustainable forest management; decision support systems; biodiversity; silviculture
Guest Editor
Prof. Dr. Róbert Marušák

Department of Forest Management, Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 165 00, Prague, Czech Republic
Website | E-Mail
Interests: optimization techniques and decision support systems for forest management; forestry planning; forest mensuration; forest monitoring and inventories; forest yield in changing climate and ecological conditions
Guest Editor
Dr. Jordi Garcia-Gonzalo

Forest Sciences Centre of Catalonia (CTFC), Ctra. De St Llorenç de Morunys km 2. Solsona. Spain
Head of program / Landscape Dynamics and Biodiversity
Website | E-Mail
Phone: +34 973 48 17 52 ext 211
Interests: forest planning; decision support systems; climate change impacts; conservation planning

Special Issue Information

Dear Colleagues,

Forest management today can be characterized as an operational environment with a significant amount of ecological, economic and social uncertainties that influence the long-term planning. Decision makers face several challenges in making a choice for the best management strategy, as external factors are often stochastic in nature and the options for adaption are numerous. Rising demands from society regarding a sustainable provision of ecosystems services increase the complexity of forest decision problems as well. The potential for the development of decision support approaches in forest management is facilitated by decision theory, technology, and operations research methods. Demands for decision support are emerging as a result of the challenges and problems facing forest management, and these demands act as stimuli for the research community. As objectives and approaches in forest management change throughout history, the demand for approaches to support planning and decision making will change as well.  Given large uncertainties regarding to future environmental conditions, and given evolutions in societal demands, decision support approaches are seen as very promising for facilitating strategic ecosystem management planning processes. Nowadays, Decision Support Systems (DSS) can play a significant role in analysing the needs of adaptation of forest management strategies and can support policy makers in making appropriate decisions. DSS are important to adjust present management to mitigate the impacts of climate change on forests and forest management. At the same time, the influence of adaptive management on ecosystem services and forest multifunctionality is the task of DSS use.

For this Special Issue of Forests, we encourage original manuscripts from all fields, yet specifically those involving forest management decision support systems, approaches, and models, in order to promote and advance knowledge about decision-making processes used in adaptive and sustainable forest management planning.

Dr. Jan Kašpar
Prof. Dr. Pete Bettinger
Prof. Dr. Harald Vacik
Prof. Dr. Róbert Marušák
Dr. Jordi Garcia-Gonzalo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forests is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Decision Support Systems
  • Temporal and Spatial Uncertainties
  • Operation Research
  • Management Scenarios

Published Papers (7 papers)

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Editorial

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Open AccessEditorial Decision Support Approaches in Adaptive Forest Management
Forests 2018, 9(4), 215; https://doi.org/10.3390/f9040215
Received: 9 April 2018 / Revised: 14 April 2018 / Accepted: 16 April 2018 / Published: 18 April 2018
Cited by 1 | PDF Full-text (670 KB) | HTML Full-text | XML Full-text
Abstract
Climate and social changes place strong demands on forest managers. Forest managers need powerful approaches and tools, which could help them to be able to react to the rapidly changing conditions. However, the complexity of quantifying forest ecosystems services as well as the [...] Read more.
Climate and social changes place strong demands on forest managers. Forest managers need powerful approaches and tools, which could help them to be able to react to the rapidly changing conditions. However, the complexity of quantifying forest ecosystems services as well as the complexity of current decision theories, technologies and operation research methods, complicate the creation of one general tool. The continuous research and development in this area is an indispensable part of the success of adaptive management as well as the sharing of knowledge and information between research teams around the world. The Community of Practice of Forest Management Decision Support Systems provides a platform for broad discussion among scientists, researchers as well as forest professionals. This special issue provides papers which resulted from a conference session of the International Union of Forest Research Organizations’ (IUFRO) 125th Anniversary Congress in Freiburg, Germany in 2017. The joint sessions and other meetings (and resulting publications) are appropriate opportunities for knowledge sharing on these important methods and systems for protecting and managing forest ecosystems in the future. Full article

Research

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Open AccessArticle Allocation of Storage Yards in Management Plans in the Amazon by Means of Mathematical Programming
Forests 2018, 9(3), 127; https://doi.org/10.3390/f9030127
Received: 19 November 2017 / Revised: 2 February 2018 / Accepted: 17 February 2018 / Published: 8 March 2018
Cited by 1 | PDF Full-text (2303 KB) | HTML Full-text | XML Full-text
Abstract
The present study aimed to optimize the location of wood storage yards in forest management for the production of wood in the Brazilian Amazon. The area of forest management studied was 638.17 ha, with 1478 trees selected for harvest with a diameter at [...] Read more.
The present study aimed to optimize the location of wood storage yards in forest management for the production of wood in the Brazilian Amazon. The area of forest management studied was 638.17 ha, with 1478 trees selected for harvest with a diameter at breast height of at least 50 cm in accordance with Brazilian legislation. Taking the topography into account—permanent preservation areas, restricted areas, and remaining trees—and using GIS tools, 7896 sites were identified that could be used as wood storage yards. By using mathematical programming techniques, more specifically binary integer linear programming, and based on the classical p-median model, optimal locations for the opening of yards were defined. Four scenarios were proposed combining distance and volume constraints. The scenarios evaluated promoted reductions in infrastructure investment compared with traditional planning. The results showed reductions in the number of forest roads (–6.33%) and trails to extract logs (–15.49%) when compared to traditional planning. The best performing scenario was that with the maximum volume restriction. It was concluded that the application of mathematical programming was able to promote significant gains in the harvest planning of native forests of the Amazon with the potential to reduce environmental damage. Full article
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Open AccessArticle A Bayesian Belief Network Approach to Predict Damages Caused by Disturbance Agents
Forests 2018, 9(1), 15; https://doi.org/10.3390/f9010015
Received: 29 October 2017 / Revised: 11 December 2017 / Accepted: 20 December 2017 / Published: 26 December 2017
Cited by 1 | PDF Full-text (2473 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
In mountain forests of Central Europe, storm and snow breakage as well as bark beetles are the prevailing major disturbances. The complex interrelatedness between climate, disturbance agents, and forest management increases the need for an integrative approach explicitly addressing the multiple interactions between [...] Read more.
In mountain forests of Central Europe, storm and snow breakage as well as bark beetles are the prevailing major disturbances. The complex interrelatedness between climate, disturbance agents, and forest management increases the need for an integrative approach explicitly addressing the multiple interactions between environmental changes, forest management, and disturbance agents to support forest resource managers in adaptive management. Empirical data with a comprehensive coverage for modelling the susceptibility of forests and the impact of disturbance agents are rare, thus making probabilistic models, based on expert knowledge, one of the few modelling approaches that are able to handle uncertainties due to the available information. Bayesian belief networks (BBNs) are a kind of probabilistic graphical model that has become very popular to practitioners and scientists mainly due to considerations of risk and uncertainties. In this contribution, we present a development methodology to define and parameterize BBNs based on expert elicitation and approximation. We modelled storm and bark beetle disturbances agents, analyzed effects of the development methodology on model structure, and evaluated behavior with stand data from Norway spruce (Picea abies (L.) Karst.) forests in southern Austria. The high vulnerability of the case study area according to different disturbance agents makes it particularly suitable for testing the BBN model. Full article
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Open AccessArticle Modeling Fuel Treatment Leverage: Encounter Rates, Risk Reduction, and Suppression Cost Impacts
Forests 2017, 8(12), 469; https://doi.org/10.3390/f8120469
Received: 4 October 2017 / Revised: 16 November 2017 / Accepted: 21 November 2017 / Published: 29 November 2017
Cited by 5 | PDF Full-text (4872 KB) | HTML Full-text | XML Full-text
Abstract
The primary theme of this study is the cost-effectiveness of fuel treatments at multiple scales of investment. We focused on the nexus of fuel management and suppression response planning, designing spatial fuel treatment strategies to incorporate landscape features that provide control opportunities that [...] Read more.
The primary theme of this study is the cost-effectiveness of fuel treatments at multiple scales of investment. We focused on the nexus of fuel management and suppression response planning, designing spatial fuel treatment strategies to incorporate landscape features that provide control opportunities that are relevant to fire operations. Our analysis explored the frequency and magnitude of fire-treatment encounters, which are critical determinants of treatment efficacy. Additionally, we examined avoided area burned, avoided suppression costs, and avoided damages, and combined all three under the umbrella of leverage to explore multiple dimensions with which to characterize return on investment. We chose the Sierra National Forest, California, USA, as our study site, due to previous work providing relevant data and analytical products, and because it has the potential for large, long-duration fires and corresponding potential for high suppression expenditures. Modeling results generally confirmed that fire-treatment encounters are rare, such that median suppression cost savings are zero, but in extreme years, savings can more than offset upfront investments. Further, reductions in risk can expand areas where moderated suppression response would be appropriate, and these areas can be mapped in relation to fire control opportunities. Full article
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Open AccessArticle Decision Support System for Adaptive Regional-Scale Forest Management by Multiple Decision-Makers
Forests 2017, 8(11), 453; https://doi.org/10.3390/f8110453
Received: 27 October 2017 / Revised: 13 November 2017 / Accepted: 15 November 2017 / Published: 17 November 2017
Cited by 1 | PDF Full-text (1635 KB) | HTML Full-text | XML Full-text
Abstract
Various kinds of decision support approaches (DSAs) are used in adaptive management of forests. Existing DSAs are aimed at coping with uncertainties in ecosystems but not controllability of outcomes, which is important for regional management. We designed a DSA for forest zoning to [...] Read more.
Various kinds of decision support approaches (DSAs) are used in adaptive management of forests. Existing DSAs are aimed at coping with uncertainties in ecosystems but not controllability of outcomes, which is important for regional management. We designed a DSA for forest zoning to simulate the changes in indicators of forest functions while reducing uncertainties in both controllability and ecosystems. The DSA uses a Bayesian network model based on iterative learning of observed behavior (decision-making) by foresters, which simulates when and where zoned forestry activities are implemented. The DSA was applied to a study area to evaluate wood production, protection against soil erosion, preservation of biodiversity, and carbon retention under three zoning alternatives: current zoning, zoning to enhance biodiversity, and zoning to enhance wood production. The DSA predicted that alternative zoning could enhance wood production by 3–11% and increase preservation of biodiversity by 0.4%, but decrease carbon stock by 1.2%. This DSA would enable to draw up regional forest plans while considering trade-offs and build consensus more efficiently. Full article
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Review

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Open AccessReview Multicriteria Decision Analysis and Participatory Decision Support Systems in Forest Management
Forests 2017, 8(4), 116; https://doi.org/10.3390/f8040116
Received: 17 February 2017 / Revised: 5 April 2017 / Accepted: 5 April 2017 / Published: 10 April 2017
Cited by 6 | PDF Full-text (1230 KB) | HTML Full-text | XML Full-text
Abstract
Growing concern about issues such as environmental quality or the sustainability of natural resources has led to the use of the Decision Support System (DSS), which originated in the business field, and is now part of environmental decision-making processes. The presence of environmental, [...] Read more.
Growing concern about issues such as environmental quality or the sustainability of natural resources has led to the use of the Decision Support System (DSS), which originated in the business field, and is now part of environmental decision-making processes. The presence of environmental, social, or economic dimensions has helped decision support systems to evolve to be able to tackle investigations that can contemplate all these variables, such as in the case of multicriteria decision analyses. In addition, new lifestyles, in which society recognizes more and more the contribution of forests to its welfare, have led to the need to involve stakeholders in decision-making processes. This article presents a review of different Multicriteria Decision Analysis (MCDA) and participatory decision support systems applied to forest environments. This last point is presented from the perspective of stakeholder participation in the processes and from the point of view of procedures or tools used. To do this, some of the research performed in forest environments within this current century is reviewed. Full article
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Other

Open AccessOpinion Forest Planning Heuristics—Current Recommendations and Research Opportunities for s-Metaheuristics
Forests 2017, 8(12), 476; https://doi.org/10.3390/f8120476
Received: 16 October 2017 / Revised: 15 November 2017 / Accepted: 1 December 2017 / Published: 3 December 2017
Cited by 1 | PDF Full-text (1128 KB) | HTML Full-text | XML Full-text
Abstract
Adaptive forest management requires planning and implementation of activities designed to maintain or improve forest conditions, and in support of these endeavors knowledge of silviculture, economics, operations research, and other allied fields are necessary. With regard to forest planning, traditional (exact) mathematical techniques [...] Read more.
Adaptive forest management requires planning and implementation of activities designed to maintain or improve forest conditions, and in support of these endeavors knowledge of silviculture, economics, operations research, and other allied fields are necessary. With regard to forest planning, traditional (exact) mathematical techniques along with heuristics have been demonstrated as useful in developing alternative courses of action for forest managers to consider. In this discussion paper, we present six areas of future work with regard to investigations into the development of heuristics, along with several recommendations that are based on our experiences. These areas include process improvements, reversion strategies, destruction and reconstruction strategies, intelligent or dynamic parameterization approaches, intelligent termination or transitioning approaches, and seeding strategies. We chose the six areas based on our experiences in developing forest planning heuristics. These areas reflect our opinion of where future research might concentrate. All of these areas of work have the potential to enhance the capabilities and effectiveness of heuristic approaches when applied to adaptive forest management problems. Full article
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