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    Author(s): Ronald E. McRobertsDacia M. Meneguzzo
    Date: 2007
    Source: In: McRoberts, Ronald E.; Reams, Gregory A.; Van Deusen, Paul C.; McWilliams, William H., eds. Proceedings of the seventh annual forest inventory and analysis symposium; October 3-6, 2005; Portland, ME. Gen. Tech. Rep. WO-77. Washington, DC: U.S. Department of Agriculture, Forest Service: 275-279.
    Publication Series: Other
    Station: Washington Office
    PDF: View PDF  (916.82 KB)

    Description

    Montreal Process Criterion 1, Conservation of Biological Diversity, expresses species diversity in terms of number of forest dependent species. Species richness, defined as the total number of species present, is a common metric for analyzing species diversity. A crucial difficulty in estimating species richness from sample data obtained from sources such as inventory plots is that no assurance exists that all species occurring in a geographic area of interest are observed in the sample. Several model-based and nonparametric techniques have been developed to estimate tree species richness from sample data. Three such approaches were compared using data obtained from forest inventory plots in Minnesota, United States of America. The results indicate that an exponential model method and a nonparametric jackknife method were superior to the nonparametric bootstrap method.

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    Citation

    McRoberts, Ronald E.; Meneguzzo, Dacia M. 2007. Estimating tree species richness from forest inventory plot data. In: McRoberts, Ronald E.; Reams, Gregory A.; Van Deusen, Paul C.; McWilliams, William H., eds. Proceedings of the seventh annual forest inventory and analysis symposium; October 3-6, 2005; Portland, ME. Gen. Tech. Rep. WO-77. Washington, DC: U.S. Department of Agriculture, Forest Service: 275-279.

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https://www.fs.usda.gov/treesearch/pubs/17055