title: Testing for density dependence allowing for weather effects.
abstract: 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.
authors.affiliation: Institute of Terrestrial Ecology, Monks Wood, Abbots Ripton, Huntingdon, Cambridgeshire, PE17 2LS, UK Fax: +44 (0) 1487 773 487, , , , , , GB.
authors.forename: Peter
authors.initials: P
authors.lastname: Rothery
authors.affiliation: Institute of Terrestrial Ecology, Monks Wood, Abbots Ripton, Huntingdon, Cambridgeshire, PE17 2LS, UK Fax: +44 (0) 1487 773 487, , , , , , GB.
authors.forename: Ian
authors.initials: I
authors.lastname: Newton
authors.affiliation: Institute of Terrestrial Ecology, Monks Wood, Abbots Ripton, Huntingdon, Cambridgeshire, PE17 2LS, UK Fax: +44 (0) 1487 773 487, , , , , , GB.
authors.forename: Lois
authors.initials: L
authors.lastname: Dale
authors.affiliation: Department of Avian Ecology, Wroclaw University, Sienkiewicza 21, 50 335 Wroclaw, Poland, , , , , , PL.
authors.forename: Tomasz
authors.initials: T
authors.lastname: Wesolowski
keywords: Autoregressive model; Butterfly and songbird populations; Key words Density dependence; Statistical power; Weather effects