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Article: Biodiversity data synthesis is critical for realizing a functional post-2020 framework

TitleBiodiversity data synthesis is critical for realizing a functional post-2020 framework
Authors
KeywordsBiodiversity mapping
Convention on biological diversity
Data biases
Global biodiversity framework
IUCN
Spatial ecology
Issue Date14-Sep-2022
PublisherElsevier
Citation
Biological Conservation, 2022, v. 274 How to Cite?
Abstract

The Post-2020 Global Biodiversity Framework currently is under development as part of the Convention of Biodiversity's aim to prevent global biodiversity losses by 2050, but targets can only be effectively developed and assessed if the data used for them are fit for purpose. The monitoring framework has been discussed at length and ensuring appropriate data use is critical to target effectiveness, enabling the monitoring of global biodiversity trends and assessment of target success. We outline a vision for how conservation data resources can be improved via automation and other routes to greatly enhance both ease of use and effectiveness for conservation. Synthesis across different types of data is urgently needed and could be enabled by a unified data system and automated workflows for cross-validation between data types, with downstream products such as grades for expert range maps that reflect their underlying bases and data quality and reliability to determine their fit for analysis, as well as automated preliminary IUCN assessments to expedite conservation. Capacity building and collaboration rooted in international agreements will be necessary for these initiatives to effectively function globally to enable new global targets to be achieved for effective conservation and targeted resource mobilization at all scales.


Persistent Identifierhttp://hdl.handle.net/10722/333942
ISSN
2021 Impact Factor: 7.497
2020 SCImago Journal Rankings: 2.227

 

DC FieldValueLanguage
dc.contributor.authorOrr, M-
dc.contributor.authorHughes, A-
dc.contributor.authorCostello, M-
dc.contributor.authorQiao, H-
dc.date.accessioned2023-10-10T03:14:46Z-
dc.date.available2023-10-10T03:14:46Z-
dc.date.issued2022-09-14-
dc.identifier.citationBiological Conservation, 2022, v. 274-
dc.identifier.issn0006-3207-
dc.identifier.urihttp://hdl.handle.net/10722/333942-
dc.description.abstract<p>The Post-2020 Global Biodiversity Framework currently is under development as part of the Convention of Biodiversity's aim to prevent global biodiversity losses by 2050, but targets can only be effectively developed and assessed if the data used for them are fit for purpose. The monitoring framework has been discussed at length and ensuring appropriate data use is critical to target effectiveness, enabling the monitoring of global biodiversity trends and assessment of target success. We outline a vision for how conservation data resources can be improved via automation and other routes to greatly enhance both ease of use and effectiveness for conservation. Synthesis across different types of data is urgently needed and could be enabled by a unified data system and automated workflows for cross-validation between data types, with downstream products such as grades for expert range maps that reflect their underlying bases and data quality and reliability to determine their fit for analysis, as well as automated preliminary IUCN assessments to expedite conservation. Capacity building and collaboration rooted in international agreements will be necessary for these initiatives to effectively function globally to enable new global targets to be achieved for effective conservation and targeted resource mobilization at all scales.<br></p>-
dc.languageeng-
dc.publisherElsevier-
dc.relation.ispartofBiological Conservation-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectBiodiversity mapping-
dc.subjectConvention on biological diversity-
dc.subjectData biases-
dc.subjectGlobal biodiversity framework-
dc.subjectIUCN-
dc.subjectSpatial ecology-
dc.titleBiodiversity data synthesis is critical for realizing a functional post-2020 framework-
dc.typeArticle-
dc.identifier.doi10.1016/j.biocon.2022.109735-
dc.identifier.scopuseid_2-s2.0-85138053031-
dc.identifier.volume274-
dc.identifier.eissn1873-2917-
dc.identifier.issnl0006-3207-

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