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Although necessary to promote conservation, defining evolutionary units and naming biodiversity remain a difficult task, especially in problematic species groups that experienced a dynamic biogeographic history. In this article, we undertake such task for midwife toads of the Alytes obstetricans complex by integrating recent molecular studies altogether—multilocus phylogenies and population genetic barcoding. Despite a partly unresolved phylogeny underlain by deep cyto‐nuclear discordances, nuclear and mitochondrial evidence support the validity of six genuine lineages assigned to two different species (A. obstetricans and A. almogavarii), which could be accurately mapped across most of their ranges. In particular, we demonstrate the existence for an overlooked yet genetically distinct lineage previously confounded with A. almogavarii, confined to the northern part of Huesca Province in the Spanish Central Pyrenees. We describe this micro‐endemic as the subspecies Alytes almogavarii inigoi ssp. nov., with reports on the mating call and the larvae. Conservation genetics of eight populations of this new taxon revealed two independent conservation units, separated by topographic barriers. In the wait for upcoming genomic analyses to unravel many elusive aspects of the evolution, diversity and systematics of Alytes, the present paper offers an integrative phylogeographic overview to guide future investigations and generally illustrates how multiple lines of molecular evidence can be combined to clarify the confusing taxonomy of complex species groups.

Background: Island species are vulnerable to rapid extinction, so it is important to develop accurate methods to determine their occurrence and habitat preferences. In this study, we assessed two methods for modeling the occurrence of the Corsican endemic Salamandra corsica, based on macro-ecological and fine habitat descriptors. We expected that models based on habitat descriptors would better estimate S. corsica occurrence, because its distribution could be influenced by micro-environmental gradients. The occurrence of S. corsica was modeled according to two ensembles of variables using random forests. Results: Salamandra corsica was mainly found in forested habitats, with a complex vertical structure. These habitats are associated with more stable environmental conditions. The model based on fine habitat descriptors was better able to predict occurrence, and gave no false negatives. The model based on macro-ecological variables underestimated the occurrence of the species on its ecological boundary, which is important as such locations may facilitate interpopulation connectivity. Conclusions: Implementing fine spatial resolution models requires greater investment of resources, but this is advisable for study of microendemic species, where it is important to reduce type II error (false negatives).

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