Abstract

Aim Phylogenetically related species share attributes that lead to common responses to environmental conditions, but which could also produce the exclusion of species by its relatives. These processes could generate the patterns of phylogenetic attraction or repulsion in local communities, where related species would tend to coexist more or less than expected by chance. This paper aims to (1) analyse the phylogenetic structure of a benthic gastropod assemblage in the south-western Atlantic Ocean (SAO); (2) explore the linkages between phylogenetic structure and spatial distribution patterns; (3) compare outcomes driven by the analysis of presence-only data and predictive species distribution models; and (4) explore which aspects of the gained knowledge can be useful to the design of sound conservation and/or management actions. Location Uruguayan shelf and slope in the SAO. Methods Spatial patterns in taxonomical relatedness were assessed using (1) raw presence/absence data (i.e. realized niche approach) and (2) reconstruction of the potential composition of the assemblage from niche modelling (i.e. fundamental niche approach). Null models were used to test hypotheses on assemblage structure. Results Significant departures from the null hypothesis that all species were drawn from the same assemblage were observed irrespectively of the approach, indicating the existence of non-random structures. However, a high proportion of local communities can be thought as random subsets of the regional species pool. This lack of a strong signal of a taxonomic effect could be related to the absence of a linkage between taxonomic distances and ecological similarities. Main conclusions Our results suggest a random assembly of local communities from the regional species pool and/or niche filtering independent of phylogeny as main determinants of local community composition. We also suggest that local assemblages displaying significantly higher (or lower) than expected taxonomic relatedness should be taken into consideration for designing spatially explicit conservation measures.

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