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Integrating forest stand projections with wildlife occupancy models to develop a decision support toolAuthor(s): Michelle F. Tacconelli; Edward F. Loewenstein
Source: In: Butnor, John R., ed. 2012. Proceedings of the 16th biennial southern silvicultural research conference. e-Gen. Tech. Rep. SRS-156. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 344-351.
Publication Series: Paper (invited, offered, keynote)
Station: Southern Research Station
PDF: Download Publication (533.03 KB)
DescriptionNatural resource managers must often balance multiple objectives on a single property. When these objectives are seemingly conflicting, the manager’s job can be extremely difficult and complex. This paper presents a decision support tool, designed to aid land managers in optimizing wildlife habitat needs while accomplishing additional objectives such as ecosystem restoration or timber production. A growth and yield model, the Forest Vegetation Simulator, is used to project future stand structure based on three management scenarios: no management, active manipulation of species composition through harvesting and underplanting, and single tree selection based on the Proportional-B method. At five-year time steps, predicted forest structure is input into species specific wildlife occupancy models to estimate probability of occurrence. This allows quantification of these species response to the silvicultural prescription. By integrating these two models a unique tool is available for land managers to both gauge the efficacy of their management plans before their implementation and to develop a predicted timeline of forest structure that can be used for comparison in adaptive management.
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CitationTacconelli, Michelle F.; Loewenstein, Edward F. 2012. Integrating forest stand projections with wildlife occupancy models to develop a decision support tool. In: Butnor, John R., ed. 2012. Proceedings of the 16th biennial southern silvicultural research conference. e-Gen. Tech. Rep. SRS-156. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 344-351.
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