Demography-environment relationships improve mechanistic understanding of range dynamics under climate change

Abstract

Species responses to climate change are widely detected as range and abundance changes. To better explain and predict them, we need a mechanistic understanding of how the underlying demographic processes are shaped by climatic conditions. We built spatially-explicit, process-based models for eight Swiss breeding bird populations. They jointly consider dispersal, population dynamics and the climate-dependence of three demographic processes - juvenile survival, adult survival and fecundity. The models were calibrated to two-decade abundance time-series in a Bayesian framework. We assessed goodness-of-fit and discriminatory power of the models with different metrics, indicating fair to excellent model fit. The most influential climatic predictors for population performance were the mean breeding-season temperature and the total winter precipitation. Maps of overall growth rate highlighted demographically suitable areas. Further, benefits from contemporary climate change were detected for typical mountain birds, whereas lowland birds were adversely affected. Embedding generic process-based models in a solid statistical framework improves our mechanistic understanding of range dynamics and allows disentangling the underlying abiotic and biotic processes. For future research, we advocate a stronger integration of experimental and empirical measurements and more detailed predictors in order to generate precise insights into the processes by which climate affects populations.