Decision Support Systems in Forest Management

Abstract Project COST Action FP 0804 - FORSYS summarizes European experiences in developing and applying decision support systems for forest management. This paper introduces FORSYS methodology for the classification of current forest management problems and for the description of existing decision support systems. The paper identifies the general forestry planning problems that need to be solved in Slovakia, lists the DSS tools available in Slovakia and evaluate their ability for addressing the identified problems. Finally, the research needs and gaps in this field were identified. A comparison of the situation regarding decision support in Slovakia and both in Europe and neighbouring countries (Austria, Hungary) is introduced in order to justify the identified needs. The paper is focused on the overview of models, methods and knowledge management techniques which are available in Slovakia now. We found out that the Slovak decision support research follows the state in Europe with a significant time delay and a lack of adequate instruments for addressing the contemporary planning problems exists. Consequently, there is a strong need for the development and application of computer-based tools to support decision-making problems in forest management.

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Past, current and future drivers for the development of decision support systems in forest management

Scandinavian Journal of Forest Research ◽

10.1080/02827581.2013.830768 ◽

2013 ◽

Vol 29 (sup1) ◽

pp. 2-19 ◽

Cited By ~ 27

Author(s):

Harald Vacik ◽

Manfred J. Lexer

Keyword(s):

Decision Support ◽

Forest Management ◽

Decision Support Systems ◽

Support Systems

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The forest management decision support system project

The Forestry Chronicle ◽

10.5558/tfc67622-6 ◽

1991 ◽

Vol 67 (6) ◽

pp. 622-628 ◽

Cited By ~ 5

Author(s):

Dan Bulger ◽

Harold Hunt

Keyword(s):

Decision Making ◽

Decision Support ◽

Forest Management ◽

Decision Support System ◽

Decision Support Systems ◽

Support System ◽

Support Systems ◽

Decision Makers ◽

Management Decision ◽

Management Decision Support

The focus of a decision support system is much different from Management Information Systems (MIS) and data-based "decision support systems". Decision support systems, as defined by the authors, focus on decisions and decision makers, and on information. Technology is treated as a tool and data as the raw material. In many traditional systems the focus is on the technology, and the data is the "information", while decision makers are, to some extent, externalized.The purpose of the Forest Management Decision Support System (FMDSS) project is to develop a set of software tools for creating forest management decision support systems. This set of tools will be used to implement a prototype forest management decision support system for the Plonski forest, near Kirkland Lake, Ontario.There are three critical ingredients in building the FMDSS, these are: (1) knowledge of the decision making process, (2) knowledge of the forest, and (3) the functionality of underlying support technology. The growing maturity of the underlying technology provides a tremendous opportunity to develop decision support tools. However, a significant obstacle to building FMDSS has been the diffuse nature of knowledge about forest management decision making processes, and about the forest ecosystem itself. Often this knowledge is spread widely among foresters, technicians, policy makers, and scientists, or is in a form that is not easily amenable to the decision support process. This has created a heavy burden on the project team to gather and collate the knowledge so that it could be incorporated into the function and design of the system. It will be difficult to gauge the success of this exercise until users obtain the software and begin to experiment with its use.

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Spatial Pattern of Climate Change Effects on Lithuanian Forestry

Forests ◽

10.3390/f10090809 ◽

2019 ◽

Vol 10 (9) ◽

pp. 809 ◽

Cited By ~ 2

Author(s):

Gintautas Mozgeris ◽

Vilis Brukas ◽

Nerijus Pivoriūnas ◽

Gintautas Činga ◽

Ekaterina Makrickienė ◽

...

Keyword(s):

Climate Change ◽

Decision Support ◽

Ecosystem Services ◽

Forest Management ◽

Decision Support Systems ◽

Tree Species ◽

Support Systems ◽

Forest Growth ◽

Climate Change Scenarios ◽

Climate Change Effects

Research Highlights: Validating modelling approach which combines global framework conditions in the form of climate and policy scenarios with the use of forest decision support system to assess climate change impacts on the sustainability of forest management. Background and Objectives: Forests and forestry have been confirmed to be sensitive to climate. On the other hand, human efforts to mitigate climate change influence forests and forest management. To facilitate the evaluation of future sustainability of forest management, decision support systems are applied. Our aims are to: (1) Adopt and validate decision support tool to incorporate climate change and its mitigation impacts on forest growth, global timber demands and prices for simulating future trends of forest ecosystem services in Lithuania, (2) determine the magnitude and spatial patterns of climate change effects on Lithuanian forests and forest management in the future, supposing that current forestry practices are continued. Materials and Methods: Upgraded version of Lithuanian forestry simulator Kupolis was used to model the development of all forests in the country until 2120 under management conditions of three climate change scenarios. Selected stand-level forest and forest management characteristics were aggregated to the level of regional branches of the State Forest Enterprise and analyzed for the spatial and temporal patterns of climate change effects. Results: Increased forest growth under a warmer future climate resulted in larger tree dimensions, volumes of growing stock, naturally dying trees, harvested assortments, and also higher profits from forestry activities. Negative impacts were detected for the share of broadleaved tree species in the standing volume and the tree species diversity. Climate change effects resulted in spatially clustered patterns—increasing stand productivity, and amounts of harvested timber were concentrated in the regions with dominating coniferous species, while the same areas were exposed to negative dynamics of biodiversity-related forest attributes. Current forest characteristics explained 70% or more of the variance of climate change effects on key forest and forest management attributes. Conclusions: Using forest decision support systems, climate change scenarios and considering the balance of delivered ecosystem services is suggested as a methodological framework for validating forest management alternatives aiming for more adaptiveness in Lithuanian forestry.

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Role and potential of decision support systems in forestry

Plants and Environment ◽

10.22271/2582-3744.2020.sep.108 ◽

2020 ◽

Vol 2 (3) ◽

pp. 108-112

Author(s):

Rajesh Kumar Mishra ◽

◽

Sharad Tiwari ◽

Rekha Agarwal ◽

◽

...

Keyword(s):

Decision Support ◽

Forest Management ◽

Decision Support Systems ◽

Statistical Methods ◽

Significant Relationship ◽

Support Systems ◽

Multiple Criteria Decision Making ◽

Quality Of Data ◽

Considerable Difficulty ◽

Goods And Services

Decision Support Systems (DSS) are essential tools for forest management practitioners to help take account of the many environmental, economic, administrative, legal and social aspects in forest management. This paper is concerned with the technique to develop DSS for forest management system to evaluate models and methods considering all the important factors to categorize the problem. The problem is based on temporal and spatial parameters, number of objectives, decision makers and goods and services. Some of these problem dimensions are inter-related, and we also found a significant relationship between various methods and problem dimensions, all of which have been analysed using contingency tables. The results showed that 63% of forest DSS use simulation modeling methods and these are particularly related to the spatial context and spatial scale and the number of people involved in taking a decision. The analysis showed how closely Multiple Criteria Decision Making is linked to problem types involving the consideration of the number of objectives, also with the goods and services. On the other hand, there was no significant relationship between optimization and statistical methods and problem dimensions, although they have been applied to approximately 60% and 16% of problems solved by DSS for forest management, respectively. Metaheuristics and spatial statistical methods are promising new approaches to deal with certain problem formulations and data sources. Nine out of ten DSS used an associated information system, but the availability and quality of data continue to be an important constraining issue, and one that could cause considerable difficulty in implementing DSS in practice. Very often DSS is used largely based to study market economy. The results suggest a strong need to improve the capabilities of DSS in this regard, developing and applying MCDM models and incorporating them in the design of DSS for forest management in coming years.

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