An integrative assessment of the diversity, phylogeny, distribution, and conservation of the terrestrial reptiles (Sauropsida, Squamata) of the United Arab Emirates.

In the present study we use an unprecedented database of 5,535 distributional records to infer the diversity, ecological preferences and spatial distribution of the 60 species of terrestrial reptiles of the United Arab Emirates (UAE), and use the 57 native species to test the effectiveness of the protected areas' network in conserving this unique vertebrate fauna. We infer a time-calibrated phylogeny with 146 species of squamates and 15 genes including all UAE terrestrial reptile species to determine the phylogenetic diversity (PD) and evolutionary distinctiveness (ED) of the native species and to compare it with the distribution of the hotspots of native species richness. The results of this study indicate that the sampling effort is remarkable, covering 75% of the country's territory representing nearly the entire climatic space of the UAE defined by the mean annual temperature and the total annual precipitation, as well as the multivariate climatic space defined by a principal component analysis (PCA).

Diversity, distribution and conservation of the terrestrial reptiles of Oman (Sauropsida, Squamata).

In the present work, we use an exceptional database including 5,359 records of 101 species of Oman's terrestrial reptiles together with spatial tools to infer the spatial patterns of species richness and endemicity, to infer the habitat preference of each species and to better define conservation priorities, with especial focus on the effectiveness of the protected areas in preserving this unique arid fauna. Our results indicate that the sampling effort is not only remarkable from a taxonomic point of view, with multiple observations for most species, but also for the spatial coverage achieved. The observations are distributed almost continuously across the two-dimensional climatic space of Oman defined by the mean annual temperature and the total annual precipitation and across the Principal Component Analysis (PCA) of the multivariate climatic space and are well represented within 17 out of the 20 climatic clusters grouping 10% of the explained climatic variance defined by PC1 and PC2.