Chapter

Machine Learning Methods for Ecological Applications

pp 123-144

Genetic Algorithms II

Species Distribution Modelling
  • David R. B. StockwellAffiliated withUniversity of California San Diego

* Final gross prices may vary according to local VAT.

Get Access

Abstract

This paper describes the application of genetic algorithms, or GAs, to the problem of species distribution modelling. The first section describes the GA algorithm, and a theoretical basis for applying it to spatial predictive modelling. The stages of analysis of a particular GA application follows. The Genetic Algorithm for Rule-set Production, or GARP, is described: including preparation of the base data, species location data, development of a set of models using GARP algorithm, verification and prediction. The final section contains two applications with ecological interpretations. The first is the prediction and explanation of the abundance of the Greater Glider Petauroides volons in Waratah Creek, Australia. The second is the prediction of the distribution of the Cerulean Warbler Dendroica cerulea through climate modelling in the continental United States.

Key words

climate GARP GIS Greater Glider museum data Cerulean Warbler