Editor Recommendation: Quantitative Evolutionary Patterns in Bipartite Networks

Post provided by ROB FRECKLETON

The study of interactions and their impacts on communities is a fundamental part of ecology. Much work has been done on measuring the interactions between species and their impacts on relative abundances of species. Progress has been made in understanding of the interactions at the ecological level, but we know that co-evolution is important in shaping the structure of communities in terms of the species that live there and their characteristics.

Laura Russo and colleagues have developed a new framework for analysing the co-evolutionary basis for interactions between species. This exciting new approach depends on simultaneous mapping of interactions between species (e.g. who pollinates who, or who eats who) and the relationships between them (via taxonomy or phylogeny). The framework tests for congruence in evolutionary history across interacting groups (co-phylogeny: e.g. does the phylogeny of pollinators map onto that of the plants?). This evolutionary pattern can then be dissected to look at the roles of evolutionary history and vicariance or even eliminate co-evolution as an explanation of the structure of interaction networks.

This framework has many possible applications in evolutionary ecology. The data and code to repeat, apply and extend the methods are provided. It’s an exciting approach and we look forward to seeing it widely used and the insights that will result.

To find out more about this framework, read the Robert May Prize winning article ‘Quantitative evolutionary patterns in bipartite networks: Vicariance, phylogenetic tracking or diffuse co‐evolution?

You can find Laura’s article and all of the articles that were shortlisted for the prize in the Robert May Prize 2018 Virtual Issue.

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