Analyses and suggestions on mechanisms of forestry and grassland administrations in China to achieve targets of Kunming-Montreal Global Biodiversity Framework
Bibliographic record
Abstract
Aims: There are 23 targets of Kunming-Montreal Global Biodiversity Framework (KMGBF) from the period up to 2030.China is among the mega biodiversity countries with largest human population and faces a lot of challenges on biodiversity conservation.It is very important to understand current biodiversity conservation status and gaps in order toachieve 2030 mission and 2050 vision.In addition, although forestry and grassland administrations in China (FGAC) are considered as the main body of China biodiversity conservation, especially on in situ conservation, ex situ conservation and trade control, there is no detail analysis about the lawful basis and implementation mechanisms of FGAC for the 23 targets.At the same time, there are many national strategic actions or plans on biodiversity conservation, it is very urgent to propose comments and suggestions on these actions or plans in order to make best usage of limited conservation resources.Here we aim to illustrate current biodiversity conservation status and gaps, lawful basis of FGAC's duties, and propose our suggestions on Chinese biodiversity conservation on 2030 targets.Methods: We analyzed the lawful basis and implementation mechanisms of FGAC for the 23 targets of KMGBF, from the aspects of ecosystem conservation, species conservation, genetic resources conservation and biosafety, support measures, and fairness requirements.We analyzed the typical route of implementing framework conventions through synergy among governmental sectors, and discussed four stages, i.e. to determine the whole goals, to identify detail targets, to implement relevant actions or plans, enforcement/supervision/evaluation.We also summarized the biodiversity conservation achievements and shortcomings of FGAC, and provided suggestions for future work.Results: Our analyses indicated that Chinese government attached high importance on biodiversity conservation.The mandate duties of FGAC well consist with 2030 mission.Many national strategic actions or plans on biodiversity were compiled and implemented by FGAC.Many special conservation measures of FGAC, such as ecological conservation compensation and Forestry-Leader Mechanism, had been established and received huge amount support.The conservation networks have been well established and improving across China.The system of in situ conservation, such as national parks, nature reserves, key habitats of wildlife, has been established and improving across all kinds ecosystem and received strong support from governments, local communities and non-governmental organizations (NGOs).The system of ex situ conservation, such as national botanical gardens, endangered species conservation and research centers, had been well designed and received strong support from national/provincial/municipal governments and scientists.Bilateral and multilateral international co-operations had launched many achievements and contributed to global biodiversity conservation.Public awareness is improved through wide spread communication.Many endangered species have been well protected and the quality of ecosystems is improved onwards.Inner problems related to biodiversity conservation are analyzed.Suggestions are provided regarding in situ conservation, ex situ conservation, enforcement/supervision/ evaluation, and mainstreaming of biodiversity.Conclusion: Biodiversity conservation has achieved great outcome and is becoming important part of Chinese government.However, there is high pressure for FGAC to implement relevant conservation actions or plans.We propose to improve biodiversity conservation networks, establish biodiversity monitoring system, enhance enforcement, supervision and evaluation, and mainstream biodiversity concept into Chinese culture.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".