You are not currently logged in.
Access your personal account or get JSTOR access through your library or other institution:
Testing for Density Dependence Allowing for Weather Effects
Peter Rothery, Ian Newton, Lois Dale and Tomasz Wesolowski
Vol. 112, No. 4 (1997), pp. 518-523
Stable URL: http://www.jstor.org/stable/4221808
Page Count: 6
Preview not available
A test for density dependence in time-series data allowing for weather effects is presented. The test is based on a discrete time autoregressive model for changes in population density with a covariate for the effects of weather. The distribution of the test statistic on the null hypothesis of density independence is obtained by parametric bootstrapping. A computer simulation exercise is used to demonstrate the gain in statistical power by allowing for weather effects. Application of the method to time-series data on three species of butterflies and two species of songbirds showed stronger evidence of density dependence than two standard tests.
Oecologia © 1997 Springer