Genetic Algorithm for Rule Set Production (GARP) is a computer program based on
genetic algorithm
In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to gene ...
that creates
ecological niche models for species. The generated models describe environmental conditions (precipitation, temperatures, elevation, etc.) under which the species should be able to maintain populations. As input, local observations of species and related environmental parameters are used which describe potential limits of the species' capabilities to survive. Such environmental parameters are commonly stored in
geographical information systems
A geographic information system (GIS) is a type of database containing geographic data (that is, descriptions of phenomena for which location is relevant), combined with software tools for managing, analyzing, and visualizing those data. In a br ...
. A GARP model is a random set of mathematical rules which can be read as limiting environmental conditions. Each rule is considered as a gene; the set of genes is combined in random ways to further generate many possible models describing the potential of the species to occur.
See also
*
Environmental niche modelling
References
* Stockwell, D. R. B. 1999. Genetic algorithms II. Pages 123–144 in A. H. Fielding, editor. Machine learning methods for ecological applications. Kluwer Academic Publishers, Boston
* Stockwell, D. R. B., and D. G. Peters. 1999. The GARP modelling system: Problems and solutions to automated spatial prediction. International Journal of Geographic Information Systems 13:143–158
Software
*
OpenModeller –
related GARP page
*
Lifemapper
Lifemapper is building a species diversity map of the world. It is similar to the SETI@Home client, in that it uses a volunteer computing client running primarily on home user's computers to correlate georeferenced biological samples with environm ...
Machine learning algorithms