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 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.

Highlights

  • The concept of adaptive forest management allows forest managers and landowners to adjust their approaches to the management of forest resources through information obtained via monitoring programs regarding the capacity of a forest to react to activities and events [1,2]

  • Given the amount of computer programming effort necessary to monitor these conditions, at this time we offer no concrete recommendations for improving the search behavior of an s-metaheuristic

  • Advances in computational methods that involve the use of metaheuristics for the development of forest plans can still be made by motivated individuals who can identify the untested gaps in science and design tests that address important hypotheses

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Summary

Introduction

The concept of adaptive forest management allows forest managers and landowners to adjust their approaches to the management of forest resources through information obtained via monitoring programs (system reactions) regarding the capacity of a forest to react to activities and events [1,2]. Many very interesting problems in modern conservation of landscapes and adaptive forest management can be difficult to represent as linear integer programming problems due either to the spatial nature of the issue or to complex evaluation processes that link proposed activities to measureable outcomes, which we refer to as functional relationships. Forests 2017, 8, 476 former can be modeled as a shifting mosaic of early seral stage forests These problems are inherently nonlinear, yet can be represented mathematically with integer programming relationships in either approximate or exact methods; their solution may require heuristic techniques. Appropriately designed heuristics have the ability to represent complex functional relationships between human and natural activities and the outcomes of desire to society (economic, ecological, and social) This characteristic is not unique to heuristic methods, as some traditional mathematical methods may be conditioned to address difficult problems. A heuristic can be viewed as a tool to support the decision maker though the rapid creation and display of a number of solutions

Recommendations
Process Improvements to s-Metaheuristics
Search
Search Destruction and Reconstruction Strategies
Intelligent and Dynamic Parameterization of a Search Process
Intelligent Termination or Integration Criteria for a Search Process
Seeding the Search with a High-Quality Solution
Discussion
Conclusions
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