%0 Conference Paper %1 Hughell97simulatedadaptive %A Hughell, David A. %A Roise, Joseph P. %B Proceedings of the 1997 Symposium on Systems Analysis in Forest Resources %D 1997 %K RCW adaptive-management forestry optimization %T Simulated adaptive management for timber and wildlife under uncertainty %U http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.119.2151 %X ABSTRACT.—A spatially explicit stochastic behavior simulation model for the endangered red-cockaded woodpeckers (Picoides borealis) is coupled with a forest management optimization algorithm to simulate adaptive (feedback) management within an uncertain environment. To update the adaptive forest harvest schedule in a timely manner during each management planning period, a genetic algorithm heuristic is employed. This model is used to evaluate management policies for the production of timber and red-cockaded woodpeckers. Forest management plans are typically based on an “optimal ” activity schedule which can be rendered infeasible during implementation due to changes in the resources being managed and management goals. Thus in practice, such an activity schedule is evaluated periodically during implementation, and is often replaced with a newly generated “optimal ” schedule. This paper describes an analytical tool for evaluating management strategies that take into account this adaptive implementation of activity schedules. Computer simulation models offer valuable, and often the only, tools for testing and examining intricate theories concerning the response of wildlife to management activities. This is especially true for species that depend on a variety of resources in specific spatial patterns at the landscape level. In this study a spatially explicit wildlife behavior simulation model is coupled with forest management optimization algorithm to simulate adaptive management (feedback) for timber and wildlife benefits. Uncertainty is introduced into the system through the

@inproceedings{Hughell97simulatedadaptive, abstract = {ABSTRACT.—A spatially explicit stochastic behavior simulation model for the endangered red-cockaded woodpeckers (Picoides borealis) is coupled with a forest management optimization algorithm to simulate adaptive (feedback) management within an uncertain environment. To update the adaptive forest harvest schedule in a timely manner during each management planning period, a genetic algorithm heuristic is employed. This model is used to evaluate management policies for the production of timber and red-cockaded woodpeckers. Forest management plans are typically based on an “optimal ” activity schedule which can be rendered infeasible during implementation due to changes in the resources being managed and management goals. Thus in practice, such an activity schedule is evaluated periodically during implementation, and is often replaced with a newly generated “optimal ” schedule. This paper describes an analytical tool for evaluating management strategies that take into account this adaptive implementation of activity schedules. Computer simulation models offer valuable, and often the only, tools for testing and examining intricate theories concerning the response of wildlife to management activities. This is especially true for species that depend on a variety of resources in specific spatial patterns at the landscape level. In this study a spatially explicit wildlife behavior simulation model is coupled with forest management optimization algorithm to simulate adaptive management (feedback) for timber and wildlife benefits. Uncertainty is introduced into the system through the}, added-at = {2010-02-27T04:54:04.000+0100}, author = {Hughell, David A. and Roise, Joseph P.}, biburl = {https://www.bibsonomy.org/bibtex/275247e8911921c0d75b7b827b6f00718/kiyan}, booktitle = {Proceedings of the 1997 Symposium on Systems Analysis in Forest Resources}, description = {Uses a simplified simulation model of RCW dispersion to perform simulations that test the effect of management decisions on timber production and RCW population in a timber farm. The simulation model does not simulate RCW movement, but rather simulates random "budding" or RCW clusters. This model does take into account issues such as foraging area for the RCW when budding new clusters. Includes good references to techniques used to estimate foraging suitability for the RCW in a territory (Smith and Coles 1993).}, interhash = {7e11ee21e094073d374a518b6027d035}, intrahash = {75247e8911921c0d75b7b827b6f00718}, keywords = {RCW adaptive-management forestry optimization}, timestamp = {2010-02-27T05:54:49.000+0100}, title = {Simulated adaptive management for timber and wildlife under uncertainty}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.119.2151}, year = 1997 }