Using comparative extinction risk analysis to prioritize the IUCN Red List reassessments of amphibians

Author:

Lucas Pablo Miguel12ORCID,Di Marco Moreno1ORCID,Cazalis Victor34ORCID,Luedtke Jennifer56ORCID,Neam Kelsey56ORCID,Brown Mary H.6ORCID,Langhammer Penny F.6ORCID,Mancini Giordano1ORCID,Santini Luca1ORCID

Affiliation:

1. Department of Biology and Biotechnologies "Charles Darwin" Sapienza University of Rome Rome Italy

2. Departamento de Biología Vegetal y Ecología Universidad de Sevilla Sevilla Spain

3. German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany

4. Leipzig University Leipzig Germany

5. IUCN SSC Amphibian Specialist Group Toronto Ontario Canada

6. Re:wild Austin Texas USA

Abstract

AbstractAssessing the extinction risk of species based on the International Union for Conservation of Nature (IUCN) Red List (RL) is key to guiding conservation policies and reducing biodiversity loss. This process is resource demanding, however, and requires continuous updating, which becomes increasingly difficult as new species are added to the RL. Automatic methods, such as comparative analyses used to predict species RL category, can be an efficient alternative to keep assessments up to date. Using amphibians as a study group, we predicted which species are more likely to change their RL category and thus should be prioritized for reassessment. We used species biological traits, environmental variables, and proxies of climate and land‐use change as predictors of RL category. We produced an ensemble prediction of IUCN RL category for each species by combining 4 different model algorithms: cumulative link models, phylogenetic generalized least squares, random forests, and neural networks. By comparing RL categories with the ensemble prediction and accounting for uncertainty among model algorithms, we identified species that should be prioritized for future reassessment based on the mismatch between predicted and observed values. The most important predicting variables across models were species’ range size and spatial configuration of the range, biological traits, climate change, and land‐use change. We compared our proposed prioritization index and the predicted RL changes with independent IUCN RL reassessments and found high performance of both the prioritization and the predicted directionality of changes in RL categories. Ensemble modeling of RL category is a promising tool for prioritizing species for reassessment while accounting for models’ uncertainty. This approach is broadly applicable to all taxa on the IUCN RL and to regional and national assessments and may improve allocation of the limited human and economic resources available to maintain an up‐to‐date IUCN RL.

Funder

Deutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-Leipzig

Microsoft

Junta de Andalucía

Sapienza Università di Roma

Publisher

Wiley

Reference120 articles.

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