Biogeographic variation in environmental and biotic resistance modifies predicted risk of marine invasions by ships

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Introduction Global shipping has accelerated the spread of non-native species. Factors such as environmental filtering and interactions with local biota can affect invasion likelihood, yet their relative contribution to predicting invasion risk remains unresolved. To test how abiotic filters and an experimentally-derived measure of biotic resistance interact with propagule pressure, we developed an integrated model to evaluate their relative effects on invasion risk of marine biofouling organisms to different focal port regions. We predicted that environmental filtering impacts invasion risk when fewer but stronger connections are part of the network. Further, predation is a mechanism of biotic resistance, which can reduce invasion risk, with most pronounced effects predicted in the tropics that decline at higher latitudes. Methods We examined shipping traffic and predation impact at three coastal bioregions spanning 47-degrees of latitude al range in the Northeast Pacific (Alaska, California, and Panama). We used vessel traffic databases to characterize propagule pressure and construct a worldwide port network of marine shipping routes and ports. Environmental resistance was estimated using temperature and salinity data from donor and recipient regions. We further used standardized predator exposure experiments to quantify predation impact on fouling community biomass as an estimate of potential for biotic resistance. We then expanded on existing models of relative invasion risk to incorporate the probability that propagules will survive predation by local predators and overcome environmental filtering to generate a predicted invasion risk for each port. Results Environmental filtering in all regions and predation pressure in the tropics worked to reduce the invasion risk, resulting in markedly different cumulative risk profiles over time among regions. Discussion In an increasingly connected world with more vessel traffic, our results highlight that while the number and distribution of shipping routes are important to understand risk, abiotic and biotic filters can modify model predictions.

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