Integrating ecosystem and contaminant models to predict the effects of ecosystem fluxes on contaminant dynamics

Abstract

Environmental contamination is one of the major drivers of ecosystem change in the Anthropocene. Toxic chemicals are not constrained to their source of origin as they cross ecosystem boundaries via biotic (e.g., animal migration) and abiotic (e.g., water flow) vectors. Meta‐ecology has led to important insights on how spatial flows or subsidies of matter across ecosystem boundaries can have broad impacts on local and regional ecosystem dynamics but has not yet addressed the dynamics of pollutants in recipient ecosystems. Incorporating meta‐ecosystem processes (i.e., flux of materials across ecosystem boundaries) into contaminant dynamics can elucidate how contaminants may reverberate among local food chains. Here, we derive a modeling framework to predict how spatial ecosystem fluxes can influence contaminant dynamics and how this influence is dependent on the type of ecosystem flux (e.g., herbivore movement vs. abiotic chemical flows). We mix an analytical and numerical approach to analyze our integrative model which couples two subcomponents that have previously been studied independently of each other—an ecosystem model and a contaminant model. We observe an array of dynamics for how chemical concentrations change with increasing nutrient input and loss rate across trophic levels. When we tailor our range of chemical parameter values (e.g., environmental uptake of contaminant and assimilation efficiency of the contaminant) to specific organic chemicals, our results demonstrate that increasing nutrient input rates can lead to trophic dilution in pollutants such as polychlorinated biphenyls across trophic levels. However, increasing nutrient loss rate causes an increase in the concentrations of chemicals across all trophic levels. A sensitivity analysis demonstrates that nutrient recycling is an important ecosystem process impacting contaminant concentrations, generating predictions to be addressed by future empirical studies. Importantly, our model demonstrates the utility of our framework for identifying drivers of contaminant dynamics in connected ecosystems including the importance that (1) ecosystem processes and (2) movement, especially movement of lower trophic levels, have on contaminant concentrations.