Predicting the InvasionTrend of Raccoon Invasive Species in North of Iran Using Genetic Algorithm Rule-set Prediction (GARP)
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Abstract
Nowadays, invasive species are a major threat to biodiversity and create many economic losses. Modeling for predict the distribution trends of invasive species is considered as a biodiversity management tool. Raccoon is a native species in North and Central America, and nowadays it is an invasive species in many countries such as Japan, Germany and Russia. Raccoon was observed for the first time in Gilan province in Iran in 1991. We simulated distribution of the species in Gilan province using Genetic Algorithm rule-set Prediction method (GARP). The results showed that the Raccoon invasion trend threats many ecosystems and 36% of the area, including 25% of protected areas is at invasion risk. Many protected areas are fully exposed to invasion. In many cases, these areas are unique in support of plant and animal species, such as Amirkolaye and Lavandevil wildlife refuges. So the species invasion trend could bring irreparable damages. Areas characterized by a low slope and high density of vegetation are more exposed to invasion. A large part of these areas is with slops between 0°-10° and altitudes between 0-500 m.
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