%0 Generic %A Barner, Allison %A Coblentz, Kyle %A Hacker, Sally %A Menge, Bruce %D 2017 %T Data from: Fundamental contradictions among observational and experimental estimates of non-trophic species interactions %U https://figshare.com/articles/dataset/Data_from_Fundamental_contradictions_among_observational_and_experimental_estimates_of_non-trophic_species_interactions/5727051 %R 10.6084/m9.figshare.5727051.v1 %2 https://ndownloader.figshare.com/files/10069741 %2 https://ndownloader.figshare.com/files/10069742 %2 https://ndownloader.figshare.com/files/10069743 %2 https://ndownloader.figshare.com/files/10069744 %2 https://ndownloader.figshare.com/files/10069745 %2 https://ndownloader.figshare.com/files/10069746 %2 https://ndownloader.figshare.com/files/10069748 %2 https://ndownloader.figshare.com/files/10069749 %K co-occurrence %K species associations %K species interactions %K rocky intertidal %K competition %K facilitation %K checkerboard pattern %K null models %K spatial patterns %K Community Ecology (excl. Invasive Species Ecology) %K Marine Biology %X Data to accompany Barner et al. 2018 Ecology

Please cite: Barner, AK, K Coblentz, SD Hacker, BA Menge. 2018. Fundamental contradictions among observational and experimental estimates of non-trophic species interactions. Ecology 99: 557-566.

Abstract
The difficulty of experimentally quantifying non-trophic species interactions has long troubled ecologists. Increasingly, a new application of the classic “checkerboard distribution” approach is used to infer interactions by examining the pairwise frequency at which species are found to spatially co-occur. However, the link between spatial associations, as estimated from observational co-occurrence, and species interactions, has not been tested. Here we used nine common statistical methods to estimate associations from surveys of rocky intertidal communities in the Northeast Pacific Ocean. We compared those inferred associations with a new dataset of experimentally-determined net and direct species interactions. Although association methods generated networks with aggregate structure similar to previously published interaction networks, each method detected a different set of species associations from the same dataset. Moreover, although association methods generally performed better than a random model, associations rarely matched empirical net or direct species interactions, with high rates of false positives and true positives, and many false negatives. Our findings cast doubt on studies that equate species co-occurrences to species interactions, and highlight a persistent, unanswered question: how do we interpret spatial patterns in communities? We suggest future research directions to unify the observational and experimental study of species interactions, and discuss the need for community standards and best practices in association analysis.

Files
environmental_variables.csv - All the abiotic variables associated with surveys conducted at the 25 x 25 cm2 spatial grain size (see Appendix S2: Table S1).
experimental_interactions.csv - Data from the literature on species interactions among rocky intertidal taxa encountered in the community survey.
taxon_names_key.csv - Key to translate among the species names found in the literature survey, the species names used in the community survey, and the numeric codes assigned for analysis.
community_survey_numxnum - Community survey data at the 5 spatial grain sizes: 5x5, 10x10, 15x15, 20x20, and 25x25 cm2. Unknown and rare taxa are included in these data, but were removed for analysis (see Appendix S2). Taxon names are the ones recorded during the survey and are purely descriptive; the formal taxon names for these columns can be found in taxon_names_key.csv.

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