Species richness correlates of raw and standardized co‐occurrence metrics |
| |
Authors: | Werner Ulrich Yasuhiro Kubota Buntarou Kusumoto Andres Baselga Hanna Tuomisto Nicholas J Gotelli |
| |
Institution: | 1. Chair of Ecology and Biogeography, Nicolaus Copernicus University in Toruń, Poland;2. Faculty of Science, University of the Ryukyus, Nishihara, Okinawa, Japan;3. Marine and Terrestrial Field Ecology, Tropical Biosphere Research Center University of the Ryukyus, Nishihara, Japan;4. Center for Strategic Research Project, University of the Ryukyus, Nishihara, Okinawa, Japan;5. Facultad de Biología, Universidad de Santiago de Compostela, Santiago de Compostela, La Coru?a, Spain;6. Department of Biology, University of Turku, Turku, Finland;7. Department of Biology, University of Vermont, Burlington, Vermont |
| |
Abstract: | Measuring β‐diversity and changes in species composition across multiple sites and environments is a major research focus in macroecology, and a variety of metrics have been proposed to quantify species co‐occurrence patterns in a species × site occurrence matrix. However, indices of β‐diversity and species co‐occurrence are often statistically dependent on the number of species in an assemblage. We compared the results of several common co‐occurrence metrics with patterns generated by a spatially explicit neutral model simulation. We found that all measures of co‐occurrence and β‐diversity, whether raw, rescaled or standardized by a null model expectation, were highly correlated with the total species richness of the landscape. The one important exception were the effect sizes of the fixed–fixed null model algorithm, which preserves row and column sums of the original matrix during matrix randomization. Our results call for a careful interpretation of meta‐analyses of assemblages that differ widely in species richness. At a minimum, observed species richness should be used as a statistical covariate in regression analyses, and results of the fixed–fixed algorithm should be compared carefully with the results of other randomization tests. |
| |
Keywords: | community composition co‐occurrences diversity metacommunity null models statistical inference |
|
|