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- W2997409674 abstract "Abstract Describing how communities change over space and time is crucial to better understand and predict the functioning of ecosystems. We propose a new methodological framework, based on network theory and modularity concept, to determine which type of mechanisms (i.e. deterministic versus stochastic processes) has the strongest influence on structuring communities. This framework is based on the computation and comparison of two networks: the co-occurrence (based on species abundances) and the functional networks (based on the species traits values). In this way we can assess whether the species belonging to a given functional group also belong to the same co-occurrence group. We adapted the Dg index of Gauzens et al . (2015) to analyze congruence between both networks. This offers the opportunity to identify which assembly rule(s) play(s) the major role in structuring the community. We illustrate our framework with two datasets corresponding to different faunal groups and ecosystems, and characterized by different scales (spatial and temporal scales). By considering both species abundance and multiple functional traits, our framework improves significantly the ability to discriminate the main assembly rules structuring the communities. This point is critical not only to understand community structuring but also its response to global changes and other disturbances." @default.
- W2997409674 created "2020-01-10" @default.
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- W2997409674 date "2019-12-27" @default.
- W2997409674 modified "2023-10-18" @default.
- W2997409674 title "Assessment of congruence between co-occurrence and functional networks: A new framework for revealing community assembly rules" @default.
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- W2997409674 doi "https://doi.org/10.1038/s41598-019-56515-7" @default.
- W2997409674 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6934466" @default.
- W2997409674 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31882755" @default.
- W2997409674 hasPublicationYear "2019" @default.
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