Title: Forbidden versus permitted interactions: Disentangling processes from patterns in ecological network analysis
Publication Year: 2017
JRC N°: JRC102400
ISSN: 2045-7758
URI: http://onlinelibrary.wiley.com/doi/10.1002/ece3.3102/abstract
DOI: 10.1002/ece3.3102
Type: Articles in periodicals and books
Abstract: 1. Previous research has suggested that complexity in ecological networks emerges and is maintained when species share (are linked to) increasing numbers of other species. However, assessing this pattern has proved challenging in several regards, such as finding proper metrics to assess node overlap (sharing), and using robust null modeling to disentangle significance from randomness. 2. In a recent paper (Strona & Veech, Methods in Ecology and Evolution 2015), we introduced a new metric aimed at assessing whether species in ecological networks and food webs tend to share interacting partners/resources more (or less) than random expectation. The metric is computed as the average, normalized deviation between the observed and the expected number of partners shared by any pair of nodes, with the expected number of partners being computed using a probabilistic approach based on combinatorics. 3. Herein, we clarify some confusion created by a recent paper purporting to correct our equations. In doing this, we also bring attention to a neglected challenge in assessing species’ tendency to share interacting partners. In particular, we discuss how identifying the set of ‘possible’ interactions for a given species (i.e. interactions that are not impeded, for example, by lack of functional trait compatibility) is paramount in distinguishing the potential causes of observed patterns of node overlap and segregation. 4. As a demonstration, we used a set of simulated bipartite networks of antagonistic (host-parasite) interactions to show how taking into account permitted interactions makes it possible to disentangle the effect of co-evolution (host-parasite arms race) from the effect of ecological processes (resource availability) when examining network structural patterns.
JRC Directorate:Sustainable Resources

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