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Optimal regeneration planning for old-growth forest: addressing scientific uncertainty in endangered species recovery through adaptive management

Forest Science

6539_Moore.pdf
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Abstract

Stochastic and structural uncertainties about forest dynamics present challenges in the management of ephemeral habitat conditions for endangered forest species. Maintaining critical foraging and breeding habitat for the endangered red-cockaded woodpecker (Picoides borealis) requires an uninterrupted supply of old-growth forest. We constructed and optimized a dynamic forest growth model for the Piedmont National Wildlife Refuge (Georgia, USA) with the objective of perpetuating a maximum stream of old-growth forest habitat. Our model accommodates stochastic disturbances and hardwood succession rates, and uncertainty about model structure. We produced a regeneration policy that was indexed by current forest state and by current weight of evidence among alternative model forms. We used adaptive stochastic dynamic programming, which anticipates that model probabilities, as well as forest states, may change through time, with consequent evolution of the optimal decision for any given forest state. In light of considerable uncertainty about forest dynamics, we analyzed a set of competing models incorporating extreme, but plausible, parameter values. Under any of these models, forest silviculture practices currently recommended for the creation of woodpecker habitat are suboptimal. We endorse fully adaptive approaches to the management of endangered species habitats in which predictive modeling, monitoring, and assessment are tightly linked.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Optimal regeneration planning for old-growth forest: addressing scientific uncertainty in endangered species recovery through adaptive management
Series title:
Forest Science
Volume
52
Issue:
2
Year Published:
2006
Language:
English
Contributing office(s):
Patuxent Wildlife Research Center
Description:
155-172
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Forest Science
First page:
155
Last page:
172
Number of Pages:
18