Predicting Invasions of North American Basses in Japan Using Native Range Data and a Genetic Algorithm

Abstract

Largemouth bass Micropterus salmoides and smallmouth bass M. dolomieu have been introduced into freshwater habitats in Japan, with potentially serious consequences for native fish populations. In this paper we apply the technique of ecological niche modeling using the genetic algorithm for rule-set prediction (GARP) to predict the potential distributions of these two species in Japan. This algorithm constructs a niche model based on point occurrence records and ecological coverages. The model can be visualized in geographic space, yielding a prediction of potential geographic range. The model can then be tested by determining how well independent point occurrence data are predicted according to the criteria of sensitivity and specificity provided by receiver–operator curve analysis. We ground-truthed GARP's ability to forecast the geographic occurrence of each species in its native range. The predictions were statistically significant for both species (P < 0.001). We projected the niche models onto the Japanese landscape to visualize the potential geographic ranges of both species in Japan. We tested these predictions using known occurrences from introduced populations of largemouth bass, both in the aggregate and by habitat type. All analyses robustly predicted known Japanese occurrences (P < 0.001). The number of smallmouth bass in Japan was too small for statistical tests, but the 10 known occurrences were predicted by the majority of models.