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Using landscape disturbance and succession models to support forest management

Informally Refereed

Abstract

Managers of forested landscapes must account for multiple, interacting ecological processes operating at broad spatial and temporal scales. These interactions can be of such complexity that predictions of future forest ecosystem states are beyond the analytical capability of the human mind. Landscape disturbance and succession models (LDSM) are predictive and analytical tools that can integrate these processes and provide critical decision support information. We briefly review the state of the art of LDSMs and provide two case studies to illustrate the application and utility of one LDSM, LANDIS. We conclude that LDSMs are able to provide useful information to support management decisions for a number of reasons: (i) they operate at scale that is relevant to many forest management problems, (ii) they account for interactions among ecological and anthropogenic processes, (iii) they can produce objective and comparable projections of alternative management options or various global change scenarios, (iv) LDSMs are based on current ecological knowledge and theory, (v) LDSMs provide a vehicle for collaboration among decision-makers, resource experts and scientists, (vi) LDSMs are the only feasible research tool that can be used to investigate long-term, large area dynamics.

Keywords

Landscape models, disturbance, decision support, scale

Citation

Gustafson, Eric J.; Sturtevant, Brian R.; Shvidenko, Anatoly S.; Scheller, Robert M. 2010. Using landscape disturbance and succession models to support forest management. In: Li, Chao; Lafortezza, Raffaele; Chen, Jiquan. Landscape Ecology in Forest Management and Conservation, Challenges and Solutions for Global Change. Dordrecht, The Netherlands; Springer: 99-118. Chapter 5.
Citations
https://www.fs.usda.gov/research/treesearch/37353