How The information structure of ecological communities quantitatively affects their ecological function

Biodiversity is more than the number of species. Information embodied in the particular network of interactions among them may also influence ecological function and should be accounted for. This project uses mathematical models of functional networks and information / causal analysis to determine the importance of such structural information.

Biodiversity / ecosystem function relationships (BEFs) quantify the contribution of diversity among organism types to overall functioning but no account has yet been taken of the structural information embodied in the particular relationships among the organism types. If ecological communities are more than mere assemblages of populations, there must be a community structure that sets rules for interactions among the populations, collectively amounting to system-wide information instantiated by the relationships. This project aims to quantify the formative constraints of organism types which determine the way they fit together to make a functioning whole. It will use advanced information theoretic metrics such as Integrated Information (IIT) and Dynamic Causal Modelling to quantify system-level causality.

The project will work with simulated ecological communities for which BEFs will be calculated, as system-level information / causality is manipulated. It will include a search for closure to efficient causation - the cyclic ontology of self-making systems that is an essential feature of life. This will involve the development and use of advanced network analysis, statistical