The biogeography of the Peruvian Eastern Pacific coast has been described based on oceanographic parameters and qualitative species occurrence data. This has generated disagreement about the limits and existence of different biogeographic units. In this study, the distribution of rocky-shore macrobenthic communities were recorded over 41 sites along the Peruvian coastline (3.5S-13.5S) and analyzed together with historic abiotic data in order to quantitatively evaluate the biogeographic zonation of rocky intertidal communities throughout the region and its relationship with environmental variables to propose an update bioregionalization. Clusters and non-metric multidimensional scaling were performed using Bray-Curtis dissimilarity matrices from abundance data to evaluate biogeographic patterns of dissimilarities of rocky-shore communities. Significant turnover of taxa among defined biogeographical units was tested using permutational multivariate dispersion. Relationships between of the biogeographical community’s structure and environmental factors were examined using Random Forest analysis on datasets available at Bio-Oracle and Jet Propulsion Laboratory—California Institute of Technology. Variation of community structure of 239 taxa depicted three biogeographical units along the region matching Panamic, transitional and Humboldt provinces. Beta diversity analysis indicated a significant turnover of taxa within the transitional unit. Random forest analysis showed a strong correlation between biogeographic units with phosphate, sea surface temperature, nitrate, dissolved oxygen, cloud fraction, and silicates. Our results set the putative limits of three biogeographic units for rocky-shore communities along the coast of Peru, providing base-line information for understanding further biogeographic changes on communities associated with the ongoing regional coastal cooling and impacts of El Niño events.
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© 2018 Ibanez-Erquiaga et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.