Predictive multi-scale occupancy models at range-wide extents: effects of habitat and human disturbance on distributions of wetland birds

Aim: Predicting distributions is fundamental to ecology, yet hindered by spatially-restricted sampling, scale-dependent relationships, and detection error associated with field surveys. Predictive species distribution models (SDMs) are nonetheless vital for conservation of many species. We developed a framework for building predictive SDMs with multi-scale data, and used it to develop range-wide breeding-season SDMs for 14 marsh bird species of concern.

Location: USA.

Methods: We built SDMs using data from range-wide surveys conducted over 14 years, and habitat and disturbance covariates measured at multiple spatial scales. We built hierarchical occupancy models that included heterogeneity in detectability during sampling, and used Bayesian model selection to regulate model complexity (covariates and scales) based explicitly on spatial predictive abilities. We thus integrated model selection for optimizing out-of-sample prediction, range-wide sampling over broad conditions, multi-...