Combining mesocosms with models to unravel the effects of global warming and ocean acidification on temperate marine ecosystems

Ocean warming and species exploitation have already caused large-scale reorganization of biological communities across the world. Accurate projections of future biodiversity change require a comprehensive understanding of how entire communities respond to global change. We combined a time-dynamic integrated food web modelling approach (Ecosim) with a community-level mesocosm experiment to determine the independent and combined effects of ocean warming and acidification, and fisheries exploitation, on a temperate coastal ecosystem. The mesocosm enabled important physiological and behavioural responses to climate stressors to be projected for trophic levels ranging from primary producers to top predators, including sharks. We show that under current-day rates of exploitation, warming and ocean acidification will benefit most species in higher trophic levels (e.g. mammals, birds, demersal finfish) in their current climate ranges, with the exception of small pelagic fish, but these benefits will be reduced or lost when these physical stressors co-occur. We show that increases in exploitation will, in most instances, suppress any positive effects of human-driven climate change, causing individual species biomass to decrease at high-trophic levels. Species diversity at the trailing edges of species distributions is likely to decline in the face of ocean warming, acidification and exploitation.We showcase how multi-level mesocosm food web experiments can be used to directly inform dynamic food web models, enabling the ecological processes that drive the responses of marine ecosystems to scenarios of global change to be captured in model projections and their individual and combined effects to be teased apart. Our approach for blending theoretical and empirical results from mesocosm experiments with computational models will provide resource managers and conservation biologists with improved tools for forecasting biodiversity change and altered ecosystem processes due to climate change.