An evaluation of the robustness of global amphibian range maps

Amphibians are in decline worldwide. However, their patterns of diversity, especially in the tropics, are not well understood, mainly because of incomplete information on taxonomy and distribution. We assess morphological, bioacoustic, and genetic variation of Madagascar's amphibians, one of the first near-complete taxon samplings from a biodiversity hotspot. Based on DNA sequences of 2,850 specimens sampled from over 170 localities, our analyses reveal an extreme proportion of amphibian diversity, projecting an almost 2-fold increase in species numbers from the currently described 244 species to a minimum of 373 and up to 465. This diversity is widespread geographically and across most major phylogenetic lineages except in a few previously well-studied genera, and is not restricted to morphologically cryptic clades. We classify the genealogical lineages in confirmed and unconfirmed candidate species or deeply divergent conspecific lineages based on concordance of genetic divergences with other characters. This integrative approach may be widely applicable to improve estimates of organismal diversity. Our results suggest that in Madagascar the spatial pattern of amphibian richness and endemism must be revisited, and current habitat destruction may be affecting more species than previously thought, in amphibians as well as in other animal groups. This case study suggests that worldwide tropical amphibian diversity is probably underestimated at an unprecedented level and stresses the need for integrated taxonomic surveys as a basis for prioritizing conservation efforts within biodiversity hotspots.

Data on the occurrence of species are widely used to inform the design of reserve networks. These data contain commission errors (when a species is mistakenly thought to be present) and omission errors (when a species is mistakenly thought to be absent), and the rates of the two types of error are inversely related. Point locality data can minimize commission errors, but those obtained from museum collections are generally sparse, suffer from substantial spatial bias and contain large omission errors. Geographic ranges generate large commission errors because they assume homogenous species distributions. Predicted distribution data make explicit inferences on species occurrence and their commission and omission errors depend on model structure, on the omission of variables that determine species distribution and on data resolution. Omission errors lead to identifying networks of areas for conservation action that are smaller than required and centred on known species occurrences, thus affecting the comprehensiveness, representativeness and efficiency of selected areas. Commission errors lead to selecting areas not relevant to conservation, thus affecting the representativeness and adequacy of reserve networks. Conservation plans should include an estimation of commission and omission errors in underlying species data and explicitly use this information to influence conservation planning outcomes.