| Literature DB >> 32429003 |
F Guillaume Blanchet1, Kevin Cazelles2, Dominique Gravel1.
Abstract
There is a rich amount of information in co-occurrence (presence-absence) data that could be used to understand community assembly. This proposition first envisioned by Forbes (1907) and then Diamond (1975) prompted the development of numerous modelling approaches (e.g. null model analysis, co-occurrence networks and, more recently, joint species distribution models). Both theory and experimental evidence support the idea that ecological interactions may affect co-occurrence, but it remains unclear to what extent the signal of interaction can be captured in observational data. It is now time to step back from the statistical developments and critically assess whether co-occurrence data are really a proxy for ecological interactions. In this paper, we present a series of arguments based on probability, sampling, food web and coexistence theories supporting that significant spatial associations between species (or lack thereof) is a poor proxy for ecological interactions. We discuss appropriate interpretations of co-occurrence, along with potential avenues to extract as much information as possible from such data.Keywords: Co-occurrence analysis; co-occurrence networks; ecological interactions; presence-absence data; statistical inference
Year: 2020 PMID: 32429003 DOI: 10.1111/ele.13525
Source DB: PubMed Journal: Ecol Lett ISSN: 1461-023X Impact factor: 9.492