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首页|A data-driven geospatial workflow to improve mapping species distributions and assessing extinction risk under the IUCN Red List

A data-driven geospatial workflow to improve mapping species distributions and assessing extinction risk under the IUCN Red List

A data-driven geospatial workflow to improve mapping species distributions and assessing extinction risk under the IUCN Red List

来源:bioRxiv_logobioRxiv
英文摘要

ABSTRACT Species distribution maps are essential for assessing extinction risk and guiding conservation efforts. Here, we developed a data-driven, reproducible geospatial workflow to map species distributions and evaluate their conservation status consistent with the guidelines and criteria of the IUCN Red List. Our workflow follows five automated steps to refine the distribution of a species starting from its Extent of Occurrence (EOO) to Area of Habitat (AOH) within the species range. The ranges are produced with an Inverse Distance Weighted (IDW) interpolation procedure, using presence and absence points derived from primary biodiversity data. As a case-study, we mapped the distribution of 2,273 bird species in the Americas, 55% of all terrestrial birds found in the region. We then compared our produced species ranges to the expert-drawn IUCN/BirdLife range maps and conducted a preliminary IUCN extinction risk assessment based on criterion B (Geographic Range). We found that our workflow generated ranges with fewer errors of omission, commission, and a better overall accuracy within each species EOO. The spatial overlap between both datasets was low (28%) and the expert-drawn range maps were consistently larger due to errors of commission. Their estimated Area of Habitat (AOH) was also larger for a subset of 741 forest-dependent birds. We also found that incorporating geospatial data increased the number of threatened species by 52% in comparison to the 2019 IUCN Red List, and 103 species could be placed in threatened categories (VU, EN, CR) pending further assessment. The implementation of our geospatial workflow provides a valuable alternative to increase the transparency and reliability of species risk assessments and improve mapping species distributions for conservation planning and decision-making.

Negret Pablo Jose、Palacio Ruben Dario、Jacobson Andrew P.、Vel¨¢squez-Tibat¨¢ Jorge

Centre for Biodiversity and Conservation Science, University of Queensland||School of Earth and Environmental Sciences, University of QueenslandNicholas School of the Environment, Duke University||Fundaci¨?n EcotonosDepartment of Environment and SustainabilityCentre NASCA Conservation Program, The Nature Conservancy

10.1101/2020.04.27.064477

环境科学技术现状生物科学现状、生物科学发展环境科学基础理论

geospatial analysisIUCN Red Listspecies range mapsRed List assessment

Negret Pablo Jose,Palacio Ruben Dario,Jacobson Andrew P.,Vel¨¢squez-Tibat¨¢ Jorge.A data-driven geospatial workflow to improve mapping species distributions and assessing extinction risk under the IUCN Red List[EB/OL].(2025-03-28)[2025-08-02].https://www.biorxiv.org/content/10.1101/2020.04.27.064477.点此复制

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