10 research outputs found
Predicting invasions of North American basses in Japan using native range data and a genetic algorithm
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