National-scale multispecies connectivity models represent movements for a majority of species tested

Context: Ideally, connectivity models would be developed using animal movement data because connectivity is fundamentally specific to species and movement processes. However, it can take years to collect sufficient data for all species of interest. Generalized multispecies connectivity models developed from expert opinion might help in the meantime. Objectives: We aimed to evaluate how well two common types of circuit theory-based generalized multispecies connectivity models (park-to-park and omnidirectional) predict areas important for animal movement for many species and movement processes. Methods: Using GPS locations from 3525 individuals belonging to 17 species from 46 study areas across Canada and five tests, we assessed connectivity model prediction accuracy against movement processes measured at different scales, from within home range to presumed dispersal. Results: Areas important for movement were accurately predicted for 52 to 78% of the datasets and movement processes. Prediction accuracy was lower for fast movements. The omnidirectional model was slightly better at predicting areas important for multiple movement processes. Both models were more accurate for species known to be more averse to human disturbance (72–78% of tests were accurate) compared to species less averse to human disturbance, steep slopes, and/or high elevations (38–41% of tests were accurate). Conclusions: Our study demonstrates that both park-to-park and omnidirectional multispecies connectivity models can predict areas important for various movements for many species and can be used for time-sensitive projects aimed at landscape-scale connectivity conservation. However, because the models were less accurate for some species and faster movements, species-specific connectivity models may be required for informing land management decisions.