Biotic predictors improve species distribution models for invasive plants in Western U.S. Forests at high but not low spatial resolutions

Invasions by non-native plants threaten forest health and sustainability. The ability to predict areas at greatest risk invasion is essential for informing both monitoring management of invasive species. Species distribution models (SDMs) are often used identify environmental correlates a species’ occurrence geographic that may be suitable its presence commonly constructed using solely abiotic predictors. However, mounting evidence implies not including biotic predictors in SDMs yield less accurate some resolutions typical landscape-scale models, although this possibility has rarely been evaluated plants. In study, we determined whether descriptors the environment improved accuracy built five decreasing spatial infestations common forests California, Oregon, Washington, USA described each presence. Predictors echoed those identified previous studies focal species, indicating our accurately important drivers occurrence. Including consistently model only highest resolution examined, which due scale interactions primarily act constrain distributions, particular or correlations between attributes environment. This finding suggests that, while practice building alone generally whose does differ substantially from also include predictors, effects on detectable larger scales than previously thought.