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Lucas PM, Di Marco M, Cazalis V, Luedtke J, Neam K, Brown MH, Langhammer PF, Mancini G, Santini L. Using comparative extinction risk analysis to prioritize the IUCN Red List reassessments of amphibians. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2024:e14316. [PMID: 38946355 DOI: 10.1111/cobi.14316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 03/25/2024] [Accepted: 03/27/2024] [Indexed: 07/02/2024]
Abstract
Assessing 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.
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Affiliation(s)
- Pablo Miguel Lucas
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza University of Rome, Rome, Italy
- Departamento de Biología Vegetal y Ecología, Universidad de Sevilla, Sevilla, Spain
| | - Moreno Di Marco
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza University of Rome, Rome, Italy
| | - Victor Cazalis
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Leipzig University, Leipzig, Germany
| | - Jennifer Luedtke
- IUCN SSC Amphibian Specialist Group, Toronto, Ontario, Canada
- Re:wild, Austin, Texas, USA
| | - Kelsey Neam
- IUCN SSC Amphibian Specialist Group, Toronto, Ontario, Canada
- Re:wild, Austin, Texas, USA
| | | | | | - Giordano Mancini
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza University of Rome, Rome, Italy
| | - Luca Santini
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza University of Rome, Rome, Italy
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Mancini G, Santini L, Cazalis V, Akçakaya HR, Lucas PM, Brooks TM, Foden W, Di Marco M. A standard approach for including climate change responses in IUCN Red List assessments. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2024; 38:e14227. [PMID: 38111977 DOI: 10.1111/cobi.14227] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 09/18/2023] [Accepted: 10/05/2023] [Indexed: 12/20/2023]
Abstract
The International Union for Conservation of Nature (IUCN) Red List is a central tool for extinction risk monitoring and influences global biodiversity policy and action. But, to be effective, it is crucial that it consistently accounts for each driver of extinction. Climate change is rapidly becoming a key extinction driver, but consideration of climate change information remains challenging for the IUCN. Several methods can be used to predict species' future decline, but they often fail to provide estimates of the symptoms of endangerment used by IUCN. We devised a standardized method to measure climate change impact in terms of change in habitat quality to inform criterion A3 on future population reduction. Using terrestrial nonvolant tetrapods as a case study, we measured this impact as the difference between the current and the future species climatic niche, defined based on current and future bioclimatic variables under alternative model algorithms, dispersal scenarios, emission scenarios, and climate models. Our models identified 171 species (13% out of those analyzed) for which their current red-list category could worsen under criterion A3 if they cannot disperse beyond their current range in the future. Categories for 14 species (1.5%) could worsen if maximum dispersal is possible. Although ours is a simulation exercise and not a formal red-list assessment, our results suggest that considering climate change impacts may reduce misclassification and strengthen consistency and comprehensiveness of IUCN Red List assessments.
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Affiliation(s)
- Giordano Mancini
- Department of Biology and Biotechnologies "Charles Darwin,", Sapienza University of Rome, Rome, Italy
| | - Luca Santini
- Department of Biology and Biotechnologies "Charles Darwin,", Sapienza University of Rome, Rome, Italy
| | - Victor Cazalis
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Leipzig University, Leipzig, Germany
| | - H Reşit Akçakaya
- Department of Ecology and Evolution, Stony Brook University, New York, New York, USA
- IUCN Species Survival Commission (SSC), Gland, Switzerland
| | - Pablo M Lucas
- Department of Biology and Biotechnologies "Charles Darwin,", Sapienza University of Rome, Rome, Italy
- Departamento de Biología Vegetal y Ecología, Universidad de Sevilla, Sevilla, Spain
| | - Thomas M Brooks
- IUCN Species Survival Commission (SSC), Gland, Switzerland
- World Agroforestry Center (ICRAF), University of The Philippines Los Baños, Los Baños, Philippines
- Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, Tasmania, Australia
| | - Wendy Foden
- Cape Research Centre, South African National Parks, Cape Town, South Africa
- Global Change Biology Group, Department of Botany and Zoology, University of Stellenbosch, Stellenbosch, South Africa
| | - Moreno Di Marco
- Department of Biology and Biotechnologies "Charles Darwin,", Sapienza University of Rome, Rome, Italy
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Henry EG, Santini L, Butchart SHM, González-Suárez M, Lucas PM, Benítez-López A, Mancini G, Jung M, Cardoso P, Zizka A, Meyer C, Akçakaya HR, Berryman AJ, Cazalis V, Di Marco M. Modelling the probability of meeting IUCN Red List criteria to support reassessments. GLOBAL CHANGE BIOLOGY 2024; 30:e17119. [PMID: 38273572 DOI: 10.1111/gcb.17119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 12/02/2023] [Indexed: 01/27/2024]
Abstract
Comparative extinction risk analysis-which predicts species extinction risk from correlation with traits or geographical characteristics-has gained research attention as a promising tool to support extinction risk assessment in the IUCN Red List of Threatened Species. However, its uptake has been very limited so far, possibly because existing models only predict a species' Red List category, without indicating which Red List criteria may be triggered. This prevents such approaches to be integrated into Red List assessments. We overcome this implementation gap by developing models that predict the probability of species meeting individual Red List criteria. Using data on the world's birds, we evaluated the predictive performance of our criterion-specific models and compared it with the typical criterion-blind modelling approach. We compiled data on biological traits (e.g. range size, clutch size) and external drivers (e.g. change in canopy cover) often associated with extinction risk. For each specific criterion, we modelled the relationship between extinction risk predictors and species' Red List category under that criterion using ordinal regression models. We found criterion-specific models were better at identifying threatened species compared to a criterion-blind model (higher sensitivity), but less good at identifying not threatened species (lower specificity). As expected, different covariates were important for predicting extinction risk under different criteria. Change in annual temperature was important for criteria related to population trends, while high forest dependency was important for criteria related to restricted area of occupancy or small population size. Our criteria-specific method can support Red List assessors by producing outputs that identify species likely to meet specific criteria, and which are the most important predictors. These species can then be prioritised for re-evaluation. We expect this new approach to increase the uptake of extinction risk models in Red List assessments, bridging a long-standing research-implementation gap.
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Affiliation(s)
- Etienne G Henry
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- École Normale Supérieure, Paris, France
| | - Luca Santini
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza Università di Roma, Rome, Italy
| | - Stuart H M Butchart
- BirdLife International, Cambridge, UK
- Department of Zoology, University of Cambridge, Cambridge, UK
| | - Manuela González-Suárez
- Ecology and Evolutionary Biology, School of Biological Sciences, University of Reading, Reading, UK
| | - Pablo M Lucas
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza Università di Roma, Rome, Italy
- Departamento de Biología Vegetal y Ecología, Universidad de Sevilla, Sevilla, Spain
| | - Ana Benítez-López
- Department of Biogeography and Global Change, Museo Nacional de Ciencias Naturales (MNCN-CSIC), Madrid, Spain
| | - Giordano Mancini
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza Università di Roma, Rome, Italy
| | - Martin Jung
- Biodiversity, Ecology and Conservation Group, Biodiversity and Natural Resources Management Programme, International Institute for Applied Systems Analysis, Laxenburg, Austria
| | - Pedro Cardoso
- Faculty of Sciences, CE3C - Centre for Ecology, Evolution and Environmental Sciences, CHANGE - Institute for Global Change and Sustainability, University of Lisbon, Lisbon, Portugal
- Laboratory for Integrative Biodiversity Research (LIBRe), Finnish Museum of Natural History Luomus, University of Helsinki, Helsinki, Finland
| | - Alexander Zizka
- Department of Biology, Philipps-University Marburg, Marburg, Germany
| | - Carsten Meyer
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Institute of Geosciences and Geography, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
- Institute of Biology, Leipzig University, Leipzig, Germany
| | - H Reşit Akçakaya
- Department of Ecology and Evolution, Stony Brook University, New York, USA
- IUCN Species Survival Commission (SSC), Gland, Switzerland
| | | | - Victor Cazalis
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Leipzig University, Leipzig, Germany
| | - Moreno Di Marco
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza Università di Roma, Rome, Italy
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Cazalis V, Santini L, Lucas PM, González-Suárez M, Hoffmann M, Benítez-López A, Pacifici M, Schipper AM, Böhm M, Zizka A, Clausnitzer V, Meyer C, Jung M, Butchart SHM, Cardoso P, Mancini G, Akçakaya HR, Young BE, Patoine G, Di Marco M. Prioritizing the reassessment of data-deficient species on the IUCN Red List. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2023; 37:e14139. [PMID: 37394972 DOI: 10.1111/cobi.14139] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 06/05/2023] [Accepted: 06/08/2023] [Indexed: 07/04/2023]
Abstract
Despite being central to the implementation of conservation policies, the usefulness of the International Union for Conservation of Nature (IUCN) Red List of Threatened Species is hampered by the 14% of species classified as data-deficient (DD) because information to evaluate these species' extinction risk was lacking when they were last assessed or because assessors did not appropriately account for uncertainty. Robust methods are needed to identify which DD species are more likely to be reclassified in one of the data-sufficient IUCN Red List categories. We devised a reproducible method to help red-list assessors prioritize reassessment of DD species and tested it with 6887 DD species of mammals, reptiles, amphibians, fishes, and Odonata (dragonflies and damselflies). For each DD species in these groups, we calculated its probability of being classified in a data-sufficient category if reassessed today from covariates measuring available knowledge (e.g., number of occurrence records or published articles available), knowledge proxies (e.g., remoteness of the range), and species characteristics (e.g., nocturnality); calculated change in such probability since last assessment from the increase in available knowledge (e.g., new occurrence records); and determined whether the species might qualify as threatened based on recent rate of habitat loss determined from global land-cover maps. We identified 1907 species with a probability of being reassessed in a data-sufficient category of >0.5; 624 species for which this probability increased by >0.25 since last assessment; and 77 species that could be reassessed as near threatened or threatened based on habitat loss. Combining these 3 elements, our results provided a list of species likely to be data-sufficient such that the comprehensiveness and representativeness of the IUCN Red List can be improved.
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Affiliation(s)
- Victor Cazalis
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Leipzig University, Leipzig, Germany
| | - Luca Santini
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza Università di Roma, Rome, Italy
| | - Pablo M Lucas
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza Università di Roma, Rome, Italy
| | - Manuela González-Suárez
- Ecology and Evolutionary Biology, School of Biological Sciences, University of Reading, Reading, UK
| | | | - Ana Benítez-López
- Integrative Ecology Group, Estación Biológica de Doñana (EBD-CSIC), Sevilla, Spain
- Department of Zoology, Faculty of Science, University of Granada, Granada, Spain
| | - Michela Pacifici
- Global Mammal Assessment Programme, Department of Biology and Biotechnologies "Charles Darwin", Sapienza Università di Roma, Rome, Italy
| | - Aafke M Schipper
- Department of Environmental Science, Radboud Institute for Biological and Environmental Sciences (RIBES), Radboud University, Nijmegen, The Netherlands
- PBL Netherlands Environmental Assessment Agency, The Hague, The Netherlands
| | - Monika Böhm
- Global Center for Species Survival, Indianapolis Zoological Society, Indianapolis, Indiana, USA
| | - Alexander Zizka
- Department of Biology, Philipps-University Marburg, Marburg, Germany
| | | | - Carsten Meyer
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Institute of Geosciences and Geography, Martin Luther University Halle-Wittenberg, Halle, Germany
- Institute of Biology, Leipzig University, Leipzig, Germany
| | - Martin Jung
- Biodiversity, Ecology and Conservation Group, Biodiversity and Natural Resources Management Programme, International Institute for Applied Systems Analysis, Laxenburg, Austria
| | - Stuart H M Butchart
- BirdLife International, David Attenborough Building, Cambridge, UK
- Department of Zoology, University of Cambridge, Cambridge, UK
| | - Pedro Cardoso
- Laboratory for Integrative Biodiversity Research (LIBRe), Finnish Museum of Natural History Luomus, University of Helsinki, Helsinki, Finland
| | - Giordano Mancini
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza Università di Roma, Rome, Italy
| | - H Reşit Akçakaya
- Department of Ecology and Evolution, Stony Brook University, Stony Brook, New York, USA
- IUCN Species Survival Commission (SSC), Gland, Switzerland
| | | | - Guillaume Patoine
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
- Institute of Biology, Leipzig University, Leipzig, Germany
| | - Moreno Di Marco
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza Università di Roma, Rome, Italy
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