A Multistage Stochastic Programming Model for Sustainable Forest-Level Timber Supply Under Risk of Fire
Abstract:Forest management planning models are highly developed and used extensively, but few explicitly consider the effects of fire and other uncertain losses which can be significant. Previous studies recommended contradictory responses to potential fire loss. We developed forest-level timber management optimization models with deterministic average and stochastic fire loss and used them to develop insight into the impact of uncertainty on forest management planning. Our analysis indicated that producing a stable timber supply requires the establishment of a buffer stock of timber. This strategy reduces the short-term harvest quantity, but increases the expected long-term harvest quantity. Paradoxically, the timber supply is both more stable, and larger. The results are sensitive to the method of regulating timber production: profit maximizing behavior of future producers requires a much greater buffer stock. In addition, bounds on the effect of transportation were developed, conditions where the mean value problem is adequate were identified, and the effect of a downward sloping demand curve was investigated. For. Sci. 42(1):10-26.
Document Type: Journal Article
Affiliations: Associate Professor, Faculty of Forestry, University of Toronto, Earth Sciences Centre, 33 Willcocks St, Toronto, Ontario, Canada M5S 3B3 (416-978-6960)
Publication date: 1996-02-01
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- Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
Forest Science is published bimonthly in February, April, June, August, October, and December.
2015 Impact Factor: 1.702
Ranking: 16 of 66 in forestry
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