Comspat: an R package to analyze within‐community spatial organization using species combinations. Issue 7 (14th April 2022)

• Record Type: Journal Article
• Authors: Tsakalos, James L.; Chelli, Stefano; Campetella, Giandiego; Canullo, Roberto; Simonetti, Enrico; Bartha, Sandor
• Is Part Of: Ecography. Volume 2022:Issue 7
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-04-14
• Subjects: beta diversity -- community assembly rules -- information theory -- multi-species co-occurrence -- Shannon diversity -- spatial scale; Ecology -- Periodicals; Biodiversity -- Periodicals; 574.5
• DOI: 10.1111/ecog.06216
• Languages: English
• ISSNs: 0906-7590

Abstract

Abstract : The diversity of species combinations observable in sampling units reflects a species' uneven distribution and preference for specific abiotic and biotic conditions – a phenomenon most commonly expressed in terms of ecological assembly rules of plant communities and other sessile organisms (e.g. subtidal algae, invertebrates and coral reefs). We present comspat, a new R package that uses grid or transect data sets to measure the number of realized (observed) species combinations (NRC) and the Shannon diversity of realized species combinations (compositional diversity; CD) as a function of spatial scale. NRC and CD represent two measures from a model family developed by Pál Juhász‐Nagy based on information theory. Classical Shannon diversity measures biodiversity based on the number and relative abundance of species, whereas the specific version of Shannon diversity presented here characterizes biodiversity and provides information on species coexistence relationships; both measures operate at fine‐scale within the sampling unit or within the community. comspat offers two commonly applied null models, complete spatial randomness and random shift, to disentangle the textural, intraspecific and interspecific effects on the observed spatial patterns. Combined, these models assist users in detecting and interpreting spatial associations and inferring assembly mechanisms. Our open‐sourced package provides a vignette that describes the method and reproduces the figures from this paper to help users contextualize and apply functions to their data.