From data to decisions: towards a biodiversity monitoring standards framework

Journal article

Achieving the goals of the Kunming–Montreal Global Biodiversity Framework (GBF) requires monitoring systems that can transform heterogeneous observations into consistent, decision-relevant knowledge. Yet current biodiversity data are fragmented, uneven in quality, and seldom comparable across space or time. Existing standards such as Darwin Core, Findable, Accessible, Interoperable, and Reusable (FAIR) and Collective Benefit, Authority to Control, Responsibility, and Ethics (CARE) principles provide important foundations, but they do not connect the full chain from field observation to policy reporting. We introduce the Biodiversity Monitoring Standards Framework (BMSF)—a unifying architecture that links ethical principles, standardized data collection, accredited analytical workflows, and transparent reporting into a single auditable “chain of evidence.” The framework’s novelty lies in its tiered and federated design, enabling national agencies, Indigenous knowledge holders, local communities, and private-sector actors to operate under shared principles while maintaining data sovereignty. By integrating Essential Variables, accredited analytical methods, and open-source implementation pathways, the BMSF allows locally generated data to be aggregated into credible, comparable indicators aligned with GBF targets. Concrete application, such as a national forest-connectivity assessment, demonstrates how the BMSF improves reproducibility, transparency, and policy relevance relative to existing approaches. Implemented generally, this framework would convert fragmented monitoring efforts into a coordinated, scalable system capable of tracking and guiding collective progress toward halting and reversing biodiversity loss.

Authors: Gonzalez, A; August, T; Bailey, S; Bobiwash, K; Boersch-Supan, PH

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: National Academy of Sciences
• Journal: Proceedings of the National Academy of Sciences
• Volume: 123
• Issue: 10
• Article number: e2519347123
• Publication date: 2026-03-04
• Acceptance date: 2026-01-06
• DOI: 10.1073/pnas.2519347123
• EISSN: 1091-6490
• ISSN: 0027-8424
• Language: English
• Keywords: indicators; standardization; conservation; biodiversity monitoring