AH News: Rethinking the Reclassification of Italian Urodeles
The first Global Amphibian Assessment (GAA1) evaluated the conservation status of amphibian populations based on empirical data regarding distribution, abundance, range and documented episodes of species decline. Recently, a second assessment (GAA2) used criterion E (projected extinction risk) as a further parameter, leading to a substantial worsening of the conservation status for five urodele species inhabiting the italian peninsula.
Such elevation in the risk classification (with three species moving for Least Concern to Endangered, one form Near Threatened to Critically Endangered, and one from Vulnerable to Critically Endangered) is mostly lead by an almost complete overlap between the species’ distribution and the spread area of the pathogen Batrachochytrium salamandrivorans (Bsal), that has been linked to severe population decline of salamanders in the Netherlands and in Germany.
A paper that has recently been accepted for publication on Acta Herpetologica, however, warns to take this reclassification with caution. The use of a model-based criterion in GAA2, indeed, adds a burden of uncertainty to species assessment, possibly overestimating the risk of severe population decline. The authors, in particular, note that the environmental suitability for Bsal has been considered maximum in model development. By disregarding any potential factor limiting Bsal spread, the projection might result in unrealistically high risk levels.
Despite such consideration, the authors acknowledge the importance of integrating model-based projections in conservation assessments. In a rapidly evolving climate, indeed, modelling future threats is fundamental, not only to predict the impact of emerging pathogens, but also to forecast the impact of biologic invasions, climate change and modifications in land use. They conclude by reinforcing the need to clearly declare all sources of uncertainty in the model results, by expliciting assumptions, describing alternative scenarios and integrating the model outcomes with empirical observations.
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