Exploring the role of groups in ecological networks for stability, functioning, and ecosystem management

Ecosystems are complex networks of interacting species.

One of the corner stone in network science is community detection - mathematical methods for identifying important groups of nodes, which aid the understanding of network functionality.

In this project we will use two different community detection approaches; one detects groups based on network topology and one based on flows.

First, we will use species traits to disentangle the ecological relevance of the groups detected and identify latent factors important for ecosystem structure.

Second, we will analyze dissimilarity between identified group structures with specific focus on spatially or temporally separated networks.

Third, as ecological data in general, and data on species interactions in particular, are ambiguous, we will explore how such uncertainties affect group structure. Fourth, we will analyze how disturbances are affecting the ecosystem depending on groups targeted. Finally, we will analyze how species groups are coupled to ecological functioning.

The project capitalize on the rapid advancement in network science, the complimentary expertise of the applicants and the increasing availability of high-quality ecological data.

The structure of ecological networks are crucial for their stability and functioning, and by disentangling the ecological role of groups, identified by species interactions, we can use that knowledge for systems where data are scarce and thereby aid effective ecosystem management.