Ideas and ways for agricultural sectors to implement the Convention on Biological Diversity: Insights from the management of Important Agricultural Heritage Systems
Bibliographic record
Abstract
Backgrounds: Biodiversity is critical to support sustainable development and ecosystem stability.The Conference of the Parties to the Convention on Biological Diversity has repeatedly proposed goals and pathways for the conservation and sustainable use of global biodiversity.Despite numerous global actions, the trend of biodiversity loss has not been effectively curbed or reversed.With the approaching deadline of the "3030" global target under the Kunming-Montreal Global Biodiversity Framework, it is essential to mainstream biodiversity within the Chinese institutional contexts.In particular, the transformation of key economic sectors, such as the agricultural sector, toward sustainability and their role in fulfilling commitments are crucial for advancing the vision of "harmonious coexistence of humans and nature" by 2050.Results: Important Agricultural Heritage Systems (IAHS), as institutionalised protections of traditional agricultural •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 昆蒙框架如何在中国体制下成为主流工作目标专题 郭旋等: 农业部门履行《生物多样性公约》的思路与途径--来自重要农业文化遗产管理的启示 2025年 | 33卷 | 3期 | 24527 | 第2页systems, possess unique advantages in biodiversity conservation, ecological product development, and regional development coordination.These systems align closely with the objectives outlined in the Kunming-Montreal Global Biodiversity Framework, which include reducing threats to biodiversity, meeting human needs through sustainable use and benefit-sharing, and promoting mainstreaming tools and solutions.As such, IAHS have the potential to drive a mainstreaming compliance model with Chinese characteristics.Perspectives: This study, based on the concepts of systematic conservation and adaptive management of IAHS, proposes specific tasks for mainstreaming biodiversity into agricultural sectors.These tasks include: (1) conducting biodiversity surveys, identifying key biodiversity areas, and recognising traditional agricultural ecological landscapes to promote in-situ biodiversity conservation; (2) promoting nature-friendly ecological agricultural models, exploring and utilising local traditional ecological knowledge, and integrating agricultural production standards with nature conservation goals to strengthen the mutualistic relationship between nature and humans; and (3) developing policy frameworks and evaluation procedures, establishing long-term dynamic monitoring networks, creating financial incentive mechanisms, and setting up special funds to further enhance institutional support for IAHS, thereby constructing implementation tools and solutions.In response to these specific tasks, the study proposes concrete compliance indicators for the agricultural sector, calling for enhanced collaboration between environmental and agricultural sectors.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.022 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".