Jack A. Brand, Jake Mitchell Martin, Marcus Michelangeli, Eli Thoré, Natalia Sandoval-Herrera, Erin S. McCallum, Drew Szabo, Damien L. Callahan, Timothy D Clark, Michael Grant Bertram, Tomas Brodin

Chemical pollution is a pervasive problem and is now considered the fastest-growing agent of global environmental change. Numerous pollutants are known to disrupt animal behaviour, alter ecological interactions, and shift evolutionary trajectories. Crucially, both chemical pollutants and individual organisms are non-randomly distributed throughout the environment. Despite this, the current evidence for chemical-induced impacts largely stems from tests that restrict organism movement and force homogenous exposures. While such approaches have provided pivotal ecotoxicological insights, they ignore the spatiotemporal dimension of wildlife–pollution interactions, which are key to accurately predicting the impacts of chemical pollutants on free-roaming wildlife. Indeed, the seemingly simple notion that pollutants and animals move non-randomly in the environment creates a complex of dynamic interactions, many of which have never been theoretically modelled or experimentally tested. Here, we conceptualise potential dynamic interactions between spatiotemporal variation in pollutants and individual organisms, and highlight how these processes could scale up to have substantial ecological and evolutionary impacts across populations, communities, and whole ecosystems. We conclude by outlining technological advancements and approaches that will facilitate the necessary spatiotemporal integration in ecotoxicology, and a three-pronged approach—in silico modelling, laboratory approaches, and field approaches—to guide future research.