## GARP (single run) - DesktopGARP implementation

openModeller id: DG_GARP

**Current version:** 1.1 alpha **Developer(s):** Ricardo Scachetti Pereira

**Accepts Categorical Maps:** no

**Requires absence points:** yes

**Author(s):** Stockwell, D. R. B., modified by Ricardo Scachetti Pereira

### Description

GARP is a genetic algorithm that creates ecological niche models for species. The models describe environmental conditions under which the species should be able to maintain populations. For input, GARP uses a set of point localities where the species is known to occur and a set of geographic layers representing the environmental parameters that might limit the species' capabilities to survive.

### Bibliography

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. P. Peters. 1999. The GARP modelling system: Problems and solutions to automated spatial prediction. International Journal of Geographic Information Systems 13:143-158.
Stockwell, D. R. B., and I. R. Noble. 1992. Induction of sets of rules from animal distribution data: A robust and informative method of analysis. Mathematics and Computers in Simulation 33:385-390.

### Parameters

**Max generations**

openModeller id: MaxGenerations

Maximum number of iterations (generations) run by the Genetic Algorithm.

**Data type:** integer **Domain:** [1.0, oo] **Typical value:** 400

**Convergence limit**

openModeller id: ConvergenceLimit

Defines the convergence value that makes the algorithm stop (before reaching MaxGenerations).

**Data type:** real **Domain:** [0.0, 1.0] **Typical value:** 0.01

**Population size**

openModeller id: PopulationSize

Maximum number of rules to be kept in solution.

**Data type:** integer **Domain:** [1.0, 500.0] **Typical value:** 50

**Resamples**

openModeller id: Resamples

Number of points sampled (with replacement) used to test rules.

**Data type:** integer **Domain:** [1.0, 100000.0] **Typical value:** 2500