Decision Making In Forest Management
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Decision Making In Forest Management
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Author : Michael Robert Wale Williams
language : en
Publisher: Research Studies Press Limited
Release Date : 1981
Decision Making In Forest Management written by Michael Robert Wale Williams and has been published by Research Studies Press Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 1981 with Business & Economics categories.
Time-scales in financial calculation. Using various compound interest/discount rates. The price/size relationship. The money yield table. Discounted revenue and expenditure. Net discounted revenue. The internal rate of return. Other financial tools. The planting decision. The site-improvement decision. The thinning decision. The felling decision. The pruning decision. The roading decision.
Decision Making In Forest Management
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Author : R. W. Williams
language : en
Publisher:
Release Date : 1988-01-01
Decision Making In Forest Management written by R. W. Williams and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988-01-01 with categories.
Decision Support For Forest Management
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Author : Annika Kangas
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-04-01
Decision Support For Forest Management written by Annika Kangas and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-01 with Technology & Engineering categories.
The goal of Kangas, Kangas and Kurttila's Decision Support for Forest Management is to provide students and researchers with a toolbox of methods for approaching the different planning situations that may arise in practice. It draws together a wide range of methods used in planning forest management regimes and presents a systematic overview of current methodological approaches. While earlier books concerning forest planning have tended to focus on linear programming, economic aspects, or specific multi-criteria decision aid tools, this book provides a much broader range of tools to meet a variety of planning situations. The methods themselves cover a range of decision situations – from cases involving single decision makers, through group decision making, to participatory planning. They include traditional decision support tools, from optimization to utility functions, as well as methods that are just gaining ground in forest planning – such as problem structuring methods and social choice theory. Including examples which illustrate the application of each technique to specific management planning problems, the book offers an invaluable resource for both researchers and advanced students specializing in management and planning issues relating to forestry.
Consideration Of Uncertainty In Forest Management Decision Making
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Author : Emmett Frank Thompson
language : en
Publisher:
Release Date : 1966
Consideration Of Uncertainty In Forest Management Decision Making written by Emmett Frank Thompson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1966 with Decision making categories.
Management decisions are generally considered to be made under one of three categories of future knowledge: certainty, risk, or uncertainty. All three categories occur in forest management. However, forest management decisions whose outcomes are dependent upon future levels of timber yields, prices, utilization standards, or social and legal institutions are made under uncertainty. Forest managers have always recognized that uncertainty existed; however, they have not systematically included it in their decision- making process. The objectives of the study were to: (1) establish the importance of systematically considering uncertainty in forest management decision-making and (2) illustrate and evaluate a model or procedure, for the systematic consideration of uncertainty in forest management decision-making. A review of the present status of forest management decision-making constituted fulfillment of the first objective. Theoretical decision-making models which are currently used in forest management, e. g., present worth analysis, capital budgeting, financial maturity, and linear programming, while conceptually capable of considering uncertainty, imply certainty That is, forestry applications of these models have employed single-valued expectations. Fulfillment of the second objective consisted initially of a review of recent developments in the theory of decision-making under uncertainty. All decision-making problems have some common components. These components are: decision-alternatives, the actions which the decision-maker deems possible to take; states of nature, the future events which determine the outcome of the actions; and consequences, the result of taking a specific action and finding that a particular state occurs. The more popular theoretical models for decision-making under uncertainty were reviewed: minimax, minimax regret, Hurwicz index, and Laplace. While useful in some cases, each of these models has specific disadvantages. In addition, all the models have one common major disadvantage, they contain the implicit assumption that the decision-maker is completely ignorant about the states of nature which influence his problem. In reality, forest managers and other decision-makers usually possess some information, although it may be vague, about their problems. If a decision-maker is not willing to assume complete ignorance about the occurrence of the states of nature, he cannot apply any of the above models. There is a theoretical decision-making model which appears compatible with reality. The model, Bayesian decision theory, allows the decision-maker to arrive at a solution which is compatible with his opinions or judgements about the states of nature. Also, he can combine these opinions or judgements with experimental data to derive a solution using all available information, both subjective and objective. Fulfillment of the second objective was completed by illustrating the application of Bayesian decision theory to a hypothetical problem. The problem, optimal degree of land ownership for an industrial forestry firm, was defined within the Bayesian model and a solution derived. Since the problem was hypothetical, the actual solution is not the primary result of the study. The resulting implications for actual situations is the primary contribution. If forest managers are to make decisions which contain uncertainty, the uncertainty should be systematically recognized in the decision-making process. The Bayesian model is a logical procedure for such recognition. By adopting and applying such models, the efficiency of forest management decision-making will be increased.
Multiple Criteria Decision Making In Forest Management Planning
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Author : Carsten Nico Portefée Hjortsø
language : en
Publisher:
Release Date : 1997
Multiple Criteria Decision Making In Forest Management Planning written by Carsten Nico Portefée Hjortsø and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with categories.
Multiple Criteria Decision Making In Forest Management Planning
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Author : C. N. P. Hjortsø
language : en
Publisher:
Release Date : 2000
Multiple Criteria Decision Making In Forest Management Planning written by C. N. P. Hjortsø and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with categories.
Robust Decision Making For Forest Management Under Climate Change And Uncertainty
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Author : Naomi Radke
language : en
Publisher:
Release Date : 2021
Robust Decision Making For Forest Management Under Climate Change And Uncertainty written by Naomi Radke and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Climatic changes categories.
Abstract: Due to its long-term nature, forest management faces various uncertainties that may negatively impact the forest and its provision of services to nature and humans. The most prominent uncertainty that raises a lot of attention in forest science is climate change. The recent drought years have strongly impacted the forest and increased mortality, leading to forest diebacks in Germany and many other parts of the world. This intensified public awareness regarding forest mortality and raised the need to deal with adaptive forest management. Climate change and many other uncertainties that strongly impact the delivery of ecosystem goods and services from forests can be considered as deep and dynamic over time. Deep uncertainty is characterized by the inability to attach a single probability distribution to a set of possible outcomes. In order to integrate it in decision-making it requires non-probabilistic approaches that explore the decision and uncertainty space under a large set of plausible scenarios of the uncertain factors. The question how to deal with deeply uncertain situations and how to integrate deep uncertainties in decision making processes, analytically and methodologically, has opened up a whole new field of research that is known as "robust decision making under deep uncertainty" that especially found a rise since the early 2000's. Originally settled in the field of water resources management, it finds increasing application in other fields of natural resources management under uncertain (climate) change both in science and in practice. The core design principles of these Robust Decision Making (RDM) approaches include i) the use of Exploratory Modelling over large uncertainty and management scenarios to explore the uncertainty and decision space and ii) the dynamic nature of decision making, which bases decisions and actions on so-called observed signposts that signal when and how to adapt. Until today it has found only very limited application in forest management. Few studies have applied similar concepts with simplified methods or have applied Robust Optimization, which is viewed as critical when applied under deep uncertainty. Against this background, this thesis explores the application of RDM approaches to the field of forest management as a new application domain. What robust decision making approaches exist and how have they been successfully applied to other fields of natural resources management? How could they be adapted to forest management as a new context? In order to design dynamic decision rules that adapt decision to observed signposts: What uncertainties can critically impact the performance of forest management and, based on the critical uncertainties, what could be potential signposts that signal the need to adapt current management? On that basis: How can dynamic adaptive decision rules be formulated and how could they improve the performance of current management and its robustness to climate change and other deep uncertainties? We started answering these questions by reviewing existing approaches to RDM and their application to natural resources management under climate change uncertainty (among other uncertainties). Next we used Exploratory Modelling, as an essential part of RDM, and a global sensitivity analysis in combination with a beech growth model to identify the relative impact of different sources of uncertainties on the management objectives and to identify potential signposts for adaptation. The analysis was conducted for an even-aged beech stand in South-West Germany, a test plot under classical beech management that is based on stand basal area at different time steps. We generally chose beech management (desired stand basal area) for our analysis as beech is the dominant tree species in Germany and considered as relatively robust to climate change. Based on the results we again used Exploratory Modelling and the growth model, as well as multi-objective optimization to derive adaptive decision rules based on observed signposts. We explored how they could improve robustness and performance in multiple objectives compared to a continuation of current management for different growth regions in Germany when facing climate change and other sources of deep uncertainty. We especially focused on past mortality as a signpost and mortality reduction as an objective, since the recent drought years have shifted the management focus in this direction. We found a number of RDM that follow a similar pattern. These approaches can easily be mixed and matched, depending on the decision context and analysis goal. With regard to measuring robustness we found that a global satisficing robustness metric is especially suited for forest management, since forest management is often tied to minimum performance standards. The sensitivity analysis revealed that different sources of uncertainties have a different relative impact, depending on the management objectives. For example, climate change showed the most critical impact on carbon sequestration, while it had a negligible impact on the Net Present Value of timber yield. We recommended, next to economic signposts, the use of past stand basal area or volume increment as a promising signpost for adaptation, since it is highly affected by climate change and is regularly tracked during forest inventories. Conversely, multi-objective optimization under uncertainty showed no clear relationship between past basal area increment and decisions regarding stand basal area (the decision lever). The reason might be that stand basal area does not send a strong signal regarding the change in management compared to a lever such as the amount of basal area per hectare removed. Yet, using past mortality as a signpost for an adaptive decision rule led to substantial increases in robustness and overall performance (except for carbon sequestration which was barely affected) for different growth regions in Germany. We observed that the potential for the adaptive decision rule is very region-specific. For the Norther growth regions robustness could not be increased to a high level, while for the central and southern German regions the adaptive decision rule led to total robustness. In conclusion, the results suggest a high potential for adaptive decision making based on signposts in forest management to achieve a higher robustness to climate change and other uncertainties. Extended research on the efficacy of different signposts and potential integration of multiple signposts into an adaptive decision rule could further improve the performance and robustness of adaptive decision making in forest management
Planning And Decision Making For Forest Management In The Market Economy
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Author : Max Krott
language : en
Publisher: Cuvillier Verlag
Release Date : 1997
Planning And Decision Making For Forest Management In The Market Economy written by Max Krott and has been published by Cuvillier Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Capitalism categories.
Best Decision Making Technique In Forest Management Using Analytic Hierarchy Process
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Author : Nur Ilyana Mohd. Zukki
language : en
Publisher:
Release Date : 2010
Best Decision Making Technique In Forest Management Using Analytic Hierarchy Process written by Nur Ilyana Mohd. Zukki and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.
Making decision about the environment, especially forest resources management, often involves the balancing of conflicting, incommensurate and incompatible values of many users and uses of a resource. Therefore, one of the most fundamental and difficult tasks involved is the effective integration or synthesis of all values - environmental, economic and social, which is a necessary first step to achieve and maintain ecologically sustainable development. This research shows Analytic Hierarchy Process (AHP) as a potential decision-making tool in forest resources management. Three levels of hierarchy were developed with goal at the highest level, followed by criteria and alternative. Criteria were chosen based on the Malaysian Criteria and Indicator (2002) for assessment of sustainable forest management. Using this technique, the determination of priority for all the alternatives will be considered and where the option of forest resources use with highest priority value is more suitable to be implemented will be verified.
Decision Making In Timber Production Harvest And Marketing
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Author : Marion Clawson
language : en
Publisher: Routledge
Release Date : 2016-03-17
Decision Making In Timber Production Harvest And Marketing written by Marion Clawson and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-17 with Nature categories.
Clawson explores the issues related to timber management with a particular focus on the harvesting of timber stands in Decision Making in Timber Production, Harvest and Marketing. Originally published in 1977, her study considers biological, economic and management implications of timber growing as well as the decision-making process in U.S forest Situations including methods of analysis. This title will be of interest to students of Environmental studies and professionals.