Landscape-scale determinants of non-native fish communities

Aim Predicting and preventing invasions depends on knowledge of the factors that make ecosystems susceptible to invasion. Current studies generally rely on non-native species richness (NNSR) as the sole measure of ecosystem invasibility; however, species identity is a critical consideration, given that different ecosystems may have environmental characteristics suitable to different species. Our aim was to examine whether non-native freshwater fish community composition was related to ecosystem characteristics at the landscape scale. Location United States. Methods We described spatial patterns in non-native freshwater fish communities among watersheds in the Mid-Atlantic region of the United States based on records of establishment in the U. S. Geological Survey's Nonindigenous Aquatic Species Database. We described general relationships between non-native species and ecosystem characteristics using canonical correspondence analysis. We clustered watersheds by non-native fish community and described differences among clusters using indicator species analysis. We then assessed whether nonnative communities could be predicted from ecosystem characteristics using random forest analysis and predicted non-native communities for uninvaded watersheds. We estimated which ecosystem characteristics were most important for predicting non-native communities using conditional inference trees. Results We identified four non-native fish communities, each with distinct indicator species. Non-native communities were predicted based on ecosystem characteristics with an accuracy of 80.6%, with temperature as the most important variable. Relatively uninvaded watersheds were predicted to be invasible by the most diverse non-native community. Main conclusions Non-native species identity is an important consideration when assessing ecosystem invasibility. NNSR alone is an insufficient measure of invasibility because ecosystems with equal NNSR may not be equally invasible by the same species. Our findings can help improve predictions of future invasions and focus management and policy decisions on particular species in highly invasible ecosystems.