Prioritizing the reassessment of data-deficient species on the IUCN Red List.

Anfibios IUCN Red List Lista Roja UICN Odonata amphibians conocimiento ecológico ecological knowledge extinction risk fish mammals mamíferos peces reptiles riesgo de extinción

Journal

Conservation biology : the journal of the Society for Conservation Biology
ISSN: 1523-1739
Titre abrégé: Conserv Biol
Pays: United States
ID NLM: 9882301

Informations de publication

Date de publication:
Dec 2023
Historique:
revised: 05 06 2023
received: 04 11 2022
accepted: 08 06 2023
medline: 11 12 2023
pubmed: 3 7 2023
entrez: 3 7 2023
Statut: ppublish

Résumé

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. Priorización de la reevaluación de las especies con datos deficientes en la Lista Roja de la UICN Resumen No obstante que es fundamental para la implementación de políticas de conservación, la utilidad de la Lista Roja de Especies Amenazadas de la Unión Internacional para la Conservación de la Naturaleza (UICN) está limitada por el 14% de especies clasificadas con datos deficientes (DD) debido a que la información para evaluar el riesgo de extinción de estas especies no existía cuando fueron evaluadas la última vez o porque los evaluadores no consideraron la incertidumbre apropiadamente. Se requieren métodos robustos para identificar las especies DD con mayor probabilidad de ser reclasificadas en alguna de las categorías en la Lista Roja UICN con datos suficientes. Diseñamos un método reproducible para ayudar a que los evaluadores de la lista roja prioricen la reevaluación de especies DD y lo probamos con 6,887 especies DD de mamíferos, reptiles, anfibios, peces y Odonata (libélulas y caballitos del diablo). Para cada una de las especies DD en estos grupos, calculamos la probabilidad de ser clasificadas en una categoría con datos suficientes si fuera reevaluada hoy a partir de covariables que miden el conocimiento disponible (e.g., número de registros de ocurrencia o artículos publicados disponibles), sustitutos de conocimiento (e.g., extensión del rango de distribución) y características de la especie ((e.g., nocturnidad); calculamos el cambio en tal probabilidad desde la última reevaluación a partir del incremento en el conocimiento disponible (e.g., registros de ocurrencia nuevos); y determinamos si las especies podrían calificar como amenazadas con base en pérdidas de hábitat recientes a partir de mapas globales de cobertura de suelo recientes. Identificamos 1,907 especies con una probabilidad >0.5 de ser reclasificados en una categoría con datos suficientes; 624 especies cuya probabilidad aumentó en >0.25 desde la última evaluación, y 77 especies que podrían ser reclasificadas como casi en peligro con base en la pérdida de hábitat. Combinando estos 3 elementos, nuestros resultados proporcionaron una lista de especies probablemente con datos suficientes de tal modo que la exhaustividad y la representatividad de la Lista Roja de la UICN pueden ser mejoradas.

Autres résumés

Type: Publisher (spa)
Priorización de la reevaluación de las especies con datos deficientes en la Lista Roja de la UICN Resumen No obstante que es fundamental para la implementación de políticas de conservación, la utilidad de la Lista Roja de Especies Amenazadas de la Unión Internacional para la Conservación de la Naturaleza (UICN) está limitada por el 14% de especies clasificadas con datos deficientes (DD) debido a que la información para evaluar el riesgo de extinción de estas especies no existía cuando fueron evaluadas la última vez o porque los evaluadores no consideraron la incertidumbre apropiadamente. Se requieren métodos robustos para identificar las especies DD con mayor probabilidad de ser reclasificadas en alguna de las categorías en la Lista Roja UICN con datos suficientes. Diseñamos un método reproducible para ayudar a que los evaluadores de la lista roja prioricen la reevaluación de especies DD y lo probamos con 6,887 especies DD de mamíferos, reptiles, anfibios, peces y Odonata (libélulas y caballitos del diablo). Para cada una de las especies DD en estos grupos, calculamos la probabilidad de ser clasificadas en una categoría con datos suficientes si fuera reevaluada hoy a partir de covariables que miden el conocimiento disponible (e.g., número de registros de ocurrencia o artículos publicados disponibles), sustitutos de conocimiento (e.g., extensión del rango de distribución) y características de la especie ((e.g., nocturnidad); calculamos el cambio en tal probabilidad desde la última reevaluación a partir del incremento en el conocimiento disponible (e.g., registros de ocurrencia nuevos); y determinamos si las especies podrían calificar como amenazadas con base en pérdidas de hábitat recientes a partir de mapas globales de cobertura de suelo recientes. Identificamos 1,907 especies con una probabilidad >0.5 de ser reclasificados en una categoría con datos suficientes; 624 especies cuya probabilidad aumentó en >0.25 desde la última evaluación, y 77 especies que podrían ser reclasificadas como casi en peligro con base en la pérdida de hábitat. Combinando estos 3 elementos, nuestros resultados proporcionaron una lista de especies probablemente con datos suficientes de tal modo que la exhaustividad y la representatividad de la Lista Roja de la UICN pueden ser mejoradas.

Identifiants

pubmed: 37394972
doi: 10.1111/cobi.14139
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e14139

Subventions

Organisme : Volkswagen Foundation
ID : A118199
Organisme : Juan de la Cierva-Incorporación grant
ID : IJCI-2017-31419
Organisme : Deutsche Forschungsgemeinschaft
ID : FZT 118
Organisme : Deutsche Forschungsgemeinschaft
ID : 202548816
Organisme : EMERGIA grant
ID : EMERGIA20_00252

Informations de copyright

© 2023 The Authors. Conservation Biology published by Wiley Periodicals LLC on behalf of Society for Conservation Biology.

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Auteurs

Victor Cazalis (V)

German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.
Leipzig University, Leipzig, Germany.

Luca Santini (L)

Department of Biology and Biotechnologies "Charles Darwin", Sapienza Università di Roma, Rome, Italy.

Pablo M Lucas (PM)

Department of Biology and Biotechnologies "Charles Darwin", Sapienza Università di Roma, Rome, Italy.

Manuela González-Suárez (M)

Ecology and Evolutionary Biology, School of Biological Sciences, University of Reading, Reading, UK.

Michael Hoffmann (M)

Zoological Society of London, London, UK.

Ana Benítez-López (A)

Integrative Ecology Group, Estación Biológica de Doñana (EBD-CSIC), Sevilla, Spain.
Department of Zoology, Faculty of Science, University of Granada, Granada, Spain.

Michela Pacifici (M)

Global Mammal Assessment Programme, Department of Biology and Biotechnologies "Charles Darwin", Sapienza Università di Roma, Rome, Italy.

Aafke M Schipper (AM)

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 (M)

Global Center for Species Survival, Indianapolis Zoological Society, Indianapolis, Indiana, USA.

Alexander Zizka (A)

Department of Biology, Philipps-University Marburg, Marburg, Germany.

Viola Clausnitzer (V)

Senckenberg Research Institute, Görlitz, Germany.

Carsten Meyer (C)

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 (M)

Biodiversity, Ecology and Conservation Group, Biodiversity and Natural Resources Management Programme, International Institute for Applied Systems Analysis, Laxenburg, Austria.

Stuart H M Butchart (SHM)

BirdLife International, David Attenborough Building, Cambridge, UK.
Department of Zoology, University of Cambridge, Cambridge, UK.

Pedro Cardoso (P)

Laboratory for Integrative Biodiversity Research (LIBRe), Finnish Museum of Natural History Luomus, University of Helsinki, Helsinki, Finland.

Giordano Mancini (G)

Department of Biology and Biotechnologies "Charles Darwin", Sapienza Università di Roma, Rome, Italy.

H Reşit Akçakaya (HR)

Department of Ecology and Evolution, Stony Brook University, Stony Brook, New York, USA.
IUCN Species Survival Commission (SSC), Gland, Switzerland.

Bruce E Young (BE)

NatureServe, Arlington, Virginia, USA.

Guillaume Patoine (G)

German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.
Institute of Biology, Leipzig University, Leipzig, Germany.

Moreno Di Marco (M)

Department of Biology and Biotechnologies "Charles Darwin", Sapienza Università di Roma, Rome, Italy.

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