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    Author(s): Kevin S. McKelveySamuel A. CushmanMichael K. Schwartz; Leonard F. Ruggiero
    Date: 2009
    Source: In: McRoberts, Ronald E.; Reams, Gregory A.; Van Deusen, Paul C.; McWilliams, William H., eds. Proceedings of the eighth annual forest inventory and analysis symposium; 2006 October 16-19; Monterey, CA. Gen. Tech. Report WO-79. Washington, DC: U.S. Department of Agriculture, Forest Service. 137-142.
    Publication Series: General Technical Report (GTR)
    Station: Washington Office
    PDF: View PDF  (511.0 KB)

    Description

    Recently, noninvasive genetic sampling has become the most effective way to reliably sample occurrence of many species. In addition, genetic data provide a rich data source enabling the monitoring of population status. The combination of genetically based animal data collected at known spatial coordinates with vegetation, topography, and other available covariates enables development of habitat relationships and evaluation of population attributes, such as connectivity. Colocating animal occurrence sampling on an extensive vegetation plot grid, such as the forest inventory and analysis grid, provides opportunities to develop statistical models and monitor animal populations.

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    Citation

    McKelvey, Kevin S.; Cushman, Samuel A.; Schwartz, Michael K.; Ruggiero, Leonard F. 2009. Wildlife monitoring across multiple spatial scales using grid-based sampling. In: McRoberts, Ronald E.; Reams, Gregory A.; Van Deusen, Paul C.; McWilliams, William H., eds. Proceedings of the eighth annual forest inventory and analysis symposium; 2006 October 16-19; Monterey, CA. Gen. Tech. Report WO-79. Washington, DC: U.S. Department of Agriculture, Forest Service. 137-142.

    Keywords

    sampling, estimation, remote sensing, modeling, information science, policy, analysis

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