Key issues and advancement strategies for China’s OECMs in alignment with the Kunming-Montreal Global Biodiversity Framework
Bibliographic record
Abstract
Background & Aims: The 15th Meeting of the Conference of the Parties (COP15) to the United Nations Convention on Biological Diversity (CBD) proposed the Kunming-Montreal Global Biodiversity Framework and "3030 target" with the most attention.Other effective area-based conservation measures (OECMs) are widely recognized as a cost-effective new type of conservation management tool that can achieve the 3030 targets by significantly increasing the protected areas on land and in the ocean while considering social and economic factors.The study takes the compliance work under the Kunming-Montreal Global Biodiversity Framework as the background in China, seizes the relevant requirements of the Third Plenary Session of the 20th Central Committee of the Communist Party of China as an opportunity, leverages the characteristic advantages of OECMs and China's institutional advantages, then analyzes the current status of China's OECMs actions to identify key issues in advancing OECMs implementation (including significant opportunities and practical challenges), finally proposes strategic recommendations for advancing the work.Results: Key opportunities for OECMs implementation in China lie in closely aligning with the integrated optimization goals of the "ecological-living-production spaces", proactively identifying OECMs types that not only achieve conservation outcomes under government leadership but also attract market participation.By leveraging their advantage of balancing production, living, and ecological needs, which makes them more appealing under market economy •保护与治理对策• 昆蒙框架如何在中国体制下成为主流工作目标专题 王晓倩和邓毅: 与《昆明-蒙特利尔全球生物多样性框架》衔接的中国OECMs关键问题与推进策略 2025年 | 33卷 | 3期 | 24569 | 第2页 conditions, these OECMs can effectively address current shortcomings such as lack of funding and insufficient specialized planning support.The practical challenges in the implementation of OECMs in China include unclear identification authorities and procedures, unaligned identification criteria and policy frameworks, insufficient financial and technical incentives for social participation, and the lack of research and promotion of the Chinese model.Proposed strategies include clarifying the identification authorities and procedures for OECMs at the national level, developing adaptive criteria and OECMs management guidelines, encouraging diversified social participation and financing mechanisms for OECMs, and initiating cost-benefit research on OECMs as a model with Chinese characteristics. Conclusion & Recommendation:In the logical analysis of key issues and corresponding advancement strategies for OECMs implementation in China, the conclusions of this study are illustrated through typical cases, reflecting a novel perspective that integrates scientific research, policy analysis, and practical experience.This study anticipates leveraging the distinctive features of China's institutional framework-clear objectives, effective measures, robust safeguards, and rigorous oversight-to strategically harness OECMs, thereby supporting the achievement of China's implementation goals and fostering a new model for fulfilling its commitments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".