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    Statistical Detection of Density Dependence from a Series of Sequential Censuses

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    Slade_1977.pdf (16.54Mb)
    Issue Date
    1977-09-01
    Author
    Slade, Norman A.
    Publisher
    Ecological Society of America
    Type
    Article
    Article Version
    Scholarly/refereed, publisher version
    Rights
    Copyright by the Ecological Society of America
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    Abstract
    The use of simple linear regression to estimate slopes of plots of N(t + 1) against N(t) as a test of density dependence has been criticized because such data violate the assumption of negligible measurement error in the independent variable and because they represent a time series rather than independent pairs of points. Of the several alternatives which have been suggested, ordinary and standard major axes and the coefficient of first-order autoregression behave in accordance with the logic of detecting density dependence in such plots. The power of the test of the slopes' being equal to 1 d epends on the magnitude of density-dependent and independent (random) influences and on the type of error, measurement or environmental. However, slopes of major axes appear to be unbiased estimators of the true slopes, when sequential population estimates include values sufficiently displaced from equilibrium conditions. If data follow a purely autoregressive process, density dependence can be detected without such displacement.
    URI
    http://hdl.handle.net/1808/17975
    DOI
    https://doi.org/10.2307/1936929
    Collections
    • Ecology & Evolutionary Biology Scholarly Works [1492]
    Citation
    Slade, Norman A. (1977). "Statistical Detection of Density Dependence from a Series of Sequential Censuses." Ecology, 58(5):1094-1102. http://dx.doi.org/10.2307/1936929.

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    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

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