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DesktopGarp
DesktopGarp
DesktopGarp is a software package for biodiversity and ecologic research that allows the user to predict and analyse wild species distributions.1
Description The acronym GARP stands for Genetic Algorithm for Rule-set Production. GARP was originally developed by David Stockwell, at ERIN in the Australian Department of the Environment and enhanced at the San Diego Supercomputer Center.
GARP is a genetic algorithm that creates an ecological niche model for a species that represents the environmental conditions where that species would be able to maintain populations. GARP uses as input 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' ability to survive.2
Function GARP tries, interactively, to find non-random correlations between the presence and absence of the species and the values of the environmental parameters, using several types of rules. Each rule type implements a different method for building species prediction models. Currently there are four types of rules implemented: atomic, logistic regression, bioclimatic envelope and negated bioclimatic envelope rules.3
Why use this tool? To predict and analyse the distribution of species.
Who will use this tool?
How will the tool be used?
Where in the data chain could this tool be used?
When could this tool be used?
Availability
Comments DesktopGarp comes with DatasetManager, a tool to prepare the data for use with DesktopGarp.
What does the DatasetManager application do? DatasetManager is a tool that helps the user prepare sets of geographic layers, or datasets, which will be used by DesktopGarp to build species prediction models. It does not do the entire job, though. It just converts the datasets and creates some metadata that is used by DesktopGarp during optimization. It requires support from a Geographic Information System (GIS), such as ESRI's ArcGIS, Arc/Info or ArcView GIS, to create new GARP datasets.4
If the DatasetManager can be used with ALA data, then this could possibly make DesktopGarp a powerful tool.
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