McGillMaurerWeiser2006

Référence

McGill, B.J., Maurer, B.A., Weiser, M.D. (2006) Empirical evaluation of neutral theory. Ecology, 87(6):1411-1423.

Résumé

We describe a general framework for testing neutral theory. We summarize similarities and differences between ten different versions of neutral theory. Two central predictions of neutral theory are that species abundance distributions will follow a zero-sum multinomial distribution and that community composition will change over space due to dispersal limitation. We review all published empirical tests of neutral theory. With the exception of one type of test, all tests fail to support neutral theory. We identify and perform several new tests. Specifically, we develop a set of best practices for testing the fit of the zero-sum multinomial (ZSM) vs. a lognormal null hypothesis and apply this to a data set, concluding that the lognormal outperforms neutral theory on robust tests. We explore whether a priori parameterization of neutral theory is possible, and we conclude that it is not. We show that non-curve-fitting predictions readily derived from neutral theory are easily falsi. able. In toto, there is a current overwhelming weight of evidence against neutral theory. We suggest some next steps for neutral theory.

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@ARTICLE { McGillMaurerWeiser2006,
    AUTHOR = { McGill, B.J. and Maurer, B.A. and Weiser, M.D. },
    TITLE = { Empirical evaluation of neutral theory },
    JOURNAL = { Ecology },
    YEAR = { 2006 },
    VOLUME = { 87 },
    PAGES = { 1411-1423 },
    NUMBER = { 6 },
    MONTH = { jun },
    ABSTRACT = { We describe a general framework for testing neutral theory. We summarize similarities and differences between ten different versions of neutral theory. Two central predictions of neutral theory are that species abundance distributions will follow a zero-sum multinomial distribution and that community composition will change over space due to dispersal limitation. We review all published empirical tests of neutral theory. With the exception of one type of test, all tests fail to support neutral theory. We identify and perform several new tests. Specifically, we develop a set of best practices for testing the fit of the zero-sum multinomial (ZSM) vs. a lognormal null hypothesis and apply this to a data set, concluding that the lognormal outperforms neutral theory on robust tests. We explore whether a priori parameterization of neutral theory is possible, and we conclude that it is not. We show that non-curve-fitting predictions readily derived from neutral theory are easily falsi. able. In toto, there is a current overwhelming weight of evidence against neutral theory. We suggest some next steps for neutral theory. },
    OWNER = { brugerolles },
    TIMESTAMP = { 2007.12.18 },
}

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