Publication Date:
2022-05-26
Description:
Author Posting. © The Author(s), 2017. This is the author's version of the work. It is posted here under a nonexclusive, irrevocable, paid-up, worldwide license granted to WHOI. It is made available for personal use, not for redistribution. The definitive version was published in Ecology 99 (2018): 690-699, doi:10.1002/ecy.2142.
Description:
Co-occurrence methods are increasingly utilized in ecology to infer networks of species interactions where detailed knowledge based on empirical studies is difficult to obtain. Their use is particularly common, but not restricted to, microbial networks constructed from metagenomic analyses. In this study, we test the efficacy of this procedure by comparing an inferred network constructed using spatially intensive co-occurrence data from the rocky intertidal zone in central Chile to a well-resolved, empirically-based, species interaction network from the same region. We evaluated the overlap in the information provided by each network and whether there is a bias for co-occurrence data to better detect known trophic or non-trophic, positive or negative interactions. We found a poor correspondence between the co-occurrence network and the known species interactions with overall sensitivity (probability of true link detection) equal to 0.469, and specificity (true non-interaction) equal to 0.527. The ability to detect interactions varied with interaction type. Positive non-trophic interactions such as commensalism and facilitation were detected at the highest rates. These results demonstrate that co-occurrence networks do not represent well classical ecological networks in which interactions are defined by direct observations or experimental manipulations. Co-occurrence networks provide information about the joint spatial effects of environmental conditions, recruitment, and, to some extent, biotic interactions, and among the latter, they tend to better detect niche-expanding interactions such as positive non-trophic interactions including habitat engineering. Detection of links (sensitivity or specificity) was not higher for well-known intertidal keystone species than for the rest of consumers in the community. Thus, as observed in previous empirical and theoretical studies, patterns of interactions in co-occurrence networks must be interpreted with caution, especially when extending interaction-based ecological theory to interpret network variability and stability. Co-occurrence networks may be particularly valuable for analysis of community dynamics that blends interactions and environment, rather than pairwise interactions alone.
Description:
MAF acknowledges support from a Fulbright Student Fellowship. BRB acknowledges support from the Millennium Nucleus Center for the Study of Multiple Drivers on Marine Socio-Ecological Systems (MUSELS) funded by MINECON NC120086. SAN acknowledges support from grant Fondecyt #1160289, EAW and SAN acknowledge support from the Center for Marine Conservation, grant ICM-CCM RC130004, Iniciativa Científica Milenio of the Ministerio de Economia, Fomento y Turismo, PAM acknowledges support from projects Fondecyt 1161023, ICM-MINECOM P05-002, Programa de Financiamiento Basal, CONICYT PFB-23, PIA-CONICYT-Chile, Anillo SOC-1405.
Keywords:
Species interactions
;
Non-trophic interactions
;
Food webs
;
Ecological networks
;
Co-occurrence
;
Intertidal
;
Keystone species
;
Anthropogenic impacts
Repository Name:
Woods Hole Open Access Server
Type:
Preprint
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