Biodiversity data synthesis is critical for realizing a functional post-2020 framework. (October 2022)

• Record Type: Journal Article
• Authors: Orr, Michael C.; Hughes, Alice C.; Costello, Mark J.; Qiao, Huijie
• Is Part Of: Biological conservation. Volume 274(2022)
• Publication Date: 2022-10
• Subjects: Convention on biological diversity -- Global biodiversity framework -- Biodiversity mapping -- Spatial ecology -- IUCN -- Data biases; Conservation of natural resources -- Periodicals; Nature conservation -- Periodicals; Ecology -- Periodicals; Environment -- Periodicals; Environmental Pollution -- Periodicals; Electronic journals; 333.9516
• DOI: 10.1016/j.biocon.2022.109735
• Languages: English
• ISSNs: 0006-3207

Abstract

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. Highlights: Biodiversity data underpin conservation, but they must be used more carefully. We must build a unified data system for indexing and improving biodiversity data. Automation throughout could greatly enhance and expedite biodiversity conservation. International funding schemes and enhanced career recognition for data generation are needed.