Macroecology of rocky intertidal benthic communities along the southwestern Atlantic: Patterns of spatial variation and associations with natural and anthropogenic variables.

Assessing spatial variability in biodiversity and its relationships with potential drivers is necessary for understanding and predicting changes in ecosystems. Here, we evaluated spatial patterns in sessile macrobenthic communities in rocky intertidal habitats along the southwestern Atlantic (SE Brazil), spanning over 500 km of coastline. We applied a rapid-survey approach focusing on the main space occupiers and habitat-forming taxa. We partitioned community variance into spatial scales ranging from metres to hundreds of kilometres and assessed whether community patterns were associated with variation in shore topography, nearshore ocean, and human influence. The communities from the mid-midlittoral level exhibited equivalent variation (31-35%) at the scales of quadrats (metres), sites (kilometres), and sub-regions (tens of kilometres). For the communities from the low-midlittoral and infralittoral fringe levels, most variability occurred at the scales of quadrats and sites (30-42%), followed by sub-regions (22%). Wave fetch, sea surface temperature (SST), and shore inclination were the variables that best explained community structure at the mid-midlittoral. At the low-midlittoral and infralittoral fringe, the most influential variables were related to oceanic forcing (SST, total suspended solids, particulate organic carbon, chlorophyll-a concentration) and human influence. Univariate analyses also revealed strong associations between the abundance of the main components of the communities and the predictor variables evaluated. Our results suggest that urbanised estuarine bays and coastal upwelling regimes have a strong influence on adjacent benthic communities, driving macroecological patterns in the study area. This study advances the knowledge in macroecology and biogeography of rocky shores in an understudied coastline and globally and provides valuable insights for future assessments of ecological changes resulting from unfolding human impacts.