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

Area of Science:

• Ecology
• Biogeochemistry
• Theoretical Ecology

Background:

• Human activities significantly alter animal populations, interactions, movement, and diversity.
• These alterations impact the control animals exert over biogeochemical cycles.
• A unified theoretical framework is lacking to predict changes in animal-mediated biogeochemical cycling (zoogeochemistry).

Purpose of the Study:

• To present a general theoretical framework integrating animal abundance, interactions, movement, and diversity to predict zoogeochemical changes.
• To guide the development of mathematical models linking network theory and meta-ecosystem theory for zoogeochemistry.
• To inform conservation efforts by understanding animal functional roles in ecosystem services.

Main Methods:

• Developed a framework linking network theory (species interactions, diversity) and meta-ecosystem theory (organism and material movement).
• Incorporated biotic and abiotic feedbacks to model animal control over biogeochemical cycling.
• Applied the framework to a case study of a primary producer-herbivore network in a boreal forest.

Main Results:

• The framework provides a method to coherently integrate diverse ecological factors influencing zoogeochemistry.
• Demonstrated application of the framework for predictive modeling in specific ecosystem contexts.
• Identified priorities for enhancing model development, data integration, and application of the framework.

Conclusions:

• The proposed framework is a significant step towards understanding and predicting animal impacts on biogeochemical cycles.
• Enhancing empirical research and model development will better inform conservation and restoration efforts.
• This work supports conserving animal populations and their roles in ecosystem services and climate solutions.