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.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Austin, M. P., Nicholls, A. O. and Margules, C. R. 1990. Measurement of the Realized Qualitative Niche: Environmental Niches of Five Eucalyptus Species, Ecological Monographs, 60: 161–177.
Bermingham, E., Rohwer, S., Freeman, S. and Wood, C. 1992. Vicariance biogeography in the Pleistocene and speciation in North American wood warblers: a test of Mengel’s model. Proceedings of the National Academy of Sciences, USA, 89: 6624–6628.
Braithwaite, L. W. 1984. On identifying important habitat characteristics and planning conservation strategy for arboreal marsupials within the Eden Woodpulp Concession area. pp 501–508 in A. P. Smith and I. P. Hume (editors) Possums and Gliders, Australian Mammal Society and Surrey Beatty and Sons, Sydney.
Busby, J. R. 1991. BIOCLIM — A bioclimatic analysis and prediction system, pp. 64–68 in C. R. Margules and M. P. Austin (editors) Biological conservation: cost effective biological surveys and analysis. CSIRO Publications, East Melbourne, Australia.
Curson, J., Quinn, D. and Beadle, D. 1994. Warblers of The Americas. Houghton Mifflin.
Cheeseman, P. 1990. On finding the most probable model, pp. 73–96 in J. Shrager and P. Langley (editors), Computational models of scientific discovery and theory formation. San Mateo, CA: aufmann.
Daly, C, Taylor, G. and Gibson, W. 1997. The PRISM Approach to Mapping Precipitation and Temperature, 10th Conference on Applied Climatology, Reno, NV, American Meteorological Society, 10–12.
Davey, S. M. 1989. The environmental relationships of arboreal marsupials in a eucalypt forest: a basis for Australian forest wildlife management. Unpublished Ph.D. thesis, Department of Forestry, Australian National University, Canberra.
Dunn, J. and Garrett, K. 1997. A Field Guide to the Warblers of North America. Houghton Mifflin: New York.
Grefenstette J. J. 1984. GENESIS: a system for using genetic search procedures, Proceedings of the Conference on Intelligent Systems and Machines, Rochester MI, 161–165.
Holland, J. H, Holyoak, K. J., Nisbett, R. E. and Thagard, P. R. 1986. Induction: processes of inference, learning and discovery, MIT Press, Cambridge, Massachusetts.
Kavenaugh, R. P. 1987. Floristic and phenological characteristics of a eucalyptus forest in relation to its use by arboreal marsupials. Unpublished M.Sc Thesis, Department of Forestry, Australian National University, Canberra.
Mendenhall, W., Scheaffer, R. L. and Wackerly, D. D. 1981. Mathematical Statistics with Applications. Wadsworth Inc., Belmont, CA.
Moore, D. M., Lees, B. G. and Davey, S. M. 1991. A new method for predicting vegetation distributions using decision tree analysis in a geographic information system, Environmental Management, 15: 59–71.
Nix, H. A. 1986. A biogeographic analysis of Australian Elapid snakes, pp. 4–15 in R. Longmore (ed.) Atlas of Elapid Snakes of Australia. Australian Flora and Fauna Series Number 7. Australian Government Publishing Service: Canberra.
Sauer, J. R., Hines, J. E., Gough, G., Thomas, I. and Peterjohn, B. G. 1997. The North American Breeding Bird Survey Results and Analysis. Version 96.3. Patuxent Wildlife Research Center, Laurel, MD.
Stockwell, D. R. B. 1992. Machine learning and the problem of prediction and explanation in ecological modelling. Unpublished PhD Thesis, Australian National University, Australia.
Stockwell, D. R. B. 1993. LBS: Bayesian learning system for rapid expert system development. Expert Systems with Applications. 6:137–148.
Stockwell, D. R. B., Davey S.M., Davis J. R. and Noble, I. R. 1990. Using inductions of decision trees to predict greater glider density, AI Applications in Natural Resource Management, 4: 33–43.
Stockwell, D. R. B. and Noble, I. R. 1992. Induction of sets of rules from animal distribution data: a robust and informative method of data analysis. Mathematics and Computers in Simulation. 32:249–254.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1999 Springer Science+Business Media New York
About this chapter
Cite this chapter
Stockwell, D.R.B. (1999). Genetic Algorithms II. In: Fielding, A.H. (eds) Machine Learning Methods for Ecological Applications. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5289-5_5
Download citation
DOI: https://doi.org/10.1007/978-1-4615-5289-5_5
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-7413-8
Online ISBN: 978-1-4615-5289-5
eBook Packages: Springer Book Archive