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On the methods for determining density-dependence by means of regression

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Summary

The determination of density-dependence of a mortality process is attempted by taking the linear regression of the logarithm of population density (or k defined by Varley and Gradwell, 1960) against the logarithm of previous density, based on the assumption that the slope, b, of the line is smaller than unity for log density-log density relationship or larger than zero for k-log density relationship. It was concluded, however, that the following three factors violate the basic assumption, providing no density-dependence.

  1. 1.

    In a Morris plot based on serial data, the value of b tends to be near the value of r. Thus, when the relationship is strongly affected by chance factors, giving remarkably scattered points on graph, the value of b tends to be always lower than unity.

  2. 2.

    When the independent variables (log previous density) are subject to sampling error, the value of b tends to be smaller than unity for density-density relations or larger than zero for k-density relations.

  3. 3.

    In Morris plot, where log densities are used twice as an independent and a dependent variables excepting the first and the last generation, the effect of timelag strongly reduces the value of b when the number of generations is not large.

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  1. Division of Entomology, National Institute of Agricultural Sciences, 114, Tokyo, Japan

    Yosiaki Itô

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Itô, Y. On the methods for determining density-dependence by means of regression. Oecologia 10, 347–372 (1972). https://doi.org/10.1007/BF00345737

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  • DOI: https://doi.org/10.1007/BF00345737

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