An accessible, integrated treatment of mathematical models in biology, the statistical techniques for fitting and testing them, and associated computer methods. Properties of models, and of methods of fitting and testing them, are demonstrated by computer simulation and illustrated by biological examples.

An accessible, integrated treatment of mathematical models in biology, the statistical techniques for fitting and testing them, and associated computer methods. Properties of models, and of methods of fitting and testing them, are demonstrated by computer simulation and illustrated by biological examples.

A test for density dependence in time-series data allowing for weather effects is presented. The test is based on a discrete time autoregessive model for changes iu 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 boot strapping, 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.