生物性状预测物种对多种全球变化驱动因素的时变响应

Multiple drivers of global change are causing rapid biodiversity loss worldwide. However, predicting species' trajectories remains challenging due to the dynamic and state-dependent nature of ecological responses in real-world ecosystems. Here, we leverage nonlinear time series analysis of a multi-decadal, high-resolution dataset encompassing climate, freshwater, and sediment variables, alongside estuarine macroinvertebrate abundance. Our analysis shows that key biological traits, including body size, mobility, and lifespan predict the mean and variability of the time-varying sensitivity of species to specific environmental drivers. Species with smaller body sizes or lower mobility exhibit consistently negative responses to warming. The temporal variability of species sensitivity, an aspect often overlooked in previous studies of species' environmental responses, is strongly associated with lifespan, with shorter-lived species showing greater fluctuations over time. These findings did not always align with results from controlled laboratory or short-term field experiments, highlighting the complex, state-dependent responses of species shaped by multiple drivers of global change. We introduce a framework that links biological traits to long-term environmental responses, providing a predictive basis for trait-sensitivity relationships.