Integrating Network and Meta-Ecosystem Models for Developing a Zoogeochemical Theory

Human activities have caused significant changes in animal abundance, interactions, movement and diversity at multiple scales. Growing empirical evidence reveals the myriad ways that these changes can alter the control that animals exert over biogeochemical cycling. Yet a theoretical framework to coherently integrate animal abundance, interactions, movement and diversity to predict when and how animal controls over biogeochemical cycling (i.e., zoogeochemistry) change is currently lacking. We present such a general framework that provides guidance on linking mathematical models of species interaction and diversity (network theory) and movement of organisms and non-living materials (meta-ecosystem theory) to account for biotic and abiotic feedback by which animals control biogeochemical cycling. We illustrate how to apply the framework to develop predictive models for specific ecosystem contexts using a case study of a primary producer-herbivore bipartite trait network in a boreal forest ecosystem. We further discuss key priorities for enhancing model development, data-model integration and application. The framework offers an important step to enhance empirical research that can better inform and justify broader conservation efforts aimed at conserving and restoring animal populations, their movement and critical functional roles in support of ecosystem services and nature-based climate solutions.