Geographical sampling bias on the assessment of endemism areas for marine meiobenthic fauna.

Species distribution patterns are constrained by historical and ecological processes in space and time, but very often the species range sizes are geographical sampling biases resulting from unequal sampling effort. One of the most common definitions of endemism is based on the "congruence of distributional areas" criterion, when two or more species have the same distributional limits. By acknowledging that available data of marine meiobenthic species are prone to geographical sampling bias and that can affect the accuracy of the biogeographical signals, the present study combines analyses of inventory incompleteness and recognition of spatial congruence of Gastrotricha, Kinorhyncha, meiobenthic Annelida and Tardigrada in order to better understand the large-scale distribution of these organisms in coastal and shelf areas of the world. We used the marine bioregionalization framework for geographical operative units to quantify the inventory incompleteness effect (by modelling spatial predictions of species richness) and to recognize areas of endemism. Our models showed that the difference between observed and expected species richness in the Southern Hemisphere is much higher than in the Northern Hemisphere. Parsimony Analysis of Endemicity delimited 20 areas of endemism, most found in the Northern Hemisphere. Distribution patterns of meiobenthic species are shown to respond to events of geographical barriers and abiotic features, and their distribution is far from homogeneous throughout the world. Also, our data show that ecoregions with distinct biotas have at least some cohesion over evolutionary time. However, we found that inventory incompleteness may significantly affect the explanatory power of areas of endemism delimitation in both hemispheres. Yet, whereas future increases in sampling efforts are likely to change the spatial congruence ranges in the Southern Hemisphere, patterns for the Northern Hemisphere may prove to be relatively more resilient.