Elements of disease in a changing world: modelling feedbacks between infectious disease and ecosystems

An overlooked effect of ecosystem eutrophication is the potential to alter disease dynamics in primary producers, inducing disease‐mediated feedbacks that alter net primary productivity and elemental recycling. Models in disease ecology rarely track organisms past death, yet death from infection can alter important ecosystem processes including elemental recycling rates and nutrient supply to living hosts. In contrast, models in ecosystem ecology rarely track disease dynamics, yet elemental nutrient pools (e.g. nitrogen, phosphorus) can regulate important disease processes including pathogen reproduction and transmission. Thus, both disease and ecosystem ecology stand to grow as fields by exploring questions that arise at their intersection. However, we currently lack a framework explicitly linking these disciplines. We developed a stoichiometric model using elemental currencies to track primary producer biomass (carbon) in vegetation and soil pools, and to track prevalence and the basic reproduction number (R0) of a directly transmitted pathogen. This model, parameterised for a deciduous forest, demonstrates that anthropogenic nutrient supply can interact with disease to qualitatively alter both ecosystem and disease dynamics. Using this element‐focused approach, we identify knowledge gaps and generate predictions about the impact of anthropogenic nutrient supply rates on infectious disease and feedbacks to ecosystem carbon and nutrient cycling. In spite of the rich potential for new insights at the intersection of disease and ecosystem ecology, we currently lack a framework for predicting the breadth of ways that infectious disease, particularly in autotrophs, could impact elemental fluxes and stocks and, conversely, the ways in which recycling of nutrients from dead hosts could alter disease dynamics in living hosts. Here, we consider why this impasse has occurred and overcome it by developing a stoichiometric model with disease. We show that integrating these subdisciplines of ecology using a stoichiometric modelling framework provides a common currency, opening the door to new questions and insights into the interplay of disease dynamics, ecosystem processes and changing biogeochemical cycles.