Assessing Patterns and Risk to Chilean Freshwater Fish Distributions Using Multi-Species Occupancy Models

To advance our understanding of freshwater biodiversity in data-limited systems, this study used multispecies occupancy models to predict species richness and individual species occupancy, providing critical insights for the conservation of these rapidly declining ecosystems. Chilean watersheds were chosen as the study system as they support a highly endemic and vulnerable assemblage of freshwater fishes in need of increased research and management. We tested several model types and ultimately pursued latent spatial multispecies occupancy models, which gained popularity in wildlife ecology, but are relatively underutilized in fisheries ecology. Advantages include simultaneously modeling multiple species to infer both species-specific and assemblage-level responses to hydro-geomorphological conditions while also accounting for imperfect species detections. Model results showed that fish species richness is primarily driven by negative relationships with elevation; however, individual species responses were variable across all environmental drivers. We present maps of predicted occupancies, representing niche model results for selected native and nonnative species. Finally, to put our results in the context of the rapid development in hydropower taking place throughout Chile, we analyzed predicted species richness and occupancy patterns in relation to aquatic ecosystem fragmentation risk from current and planned dams throughout Chile. Results showed a large number of dams are planned for the diverse lower elevation areas of the Biobio, Valdivia, and Puelo River Basins, highlighting the potential for negative impacts to the species that inhabit them. As over half the species modeled are currently listed as endangered, critically endangered, or data deficient by the International Union for Conservation of Nature (IUCN), model outputs could aid in conservation planning. This approach not only enhances our ability to protect Chile's unique and vulnerable freshwater fish species but also provides a robust framework for integrating modeled ecological insights of data-limited systems into conservation planning.