Evaluating the effectiveness of conservation priorities in mitigating agricultural threats to China’s vertebrates
Bibliographic record
Abstract
Conservation priorities (CPs), considered at least 44 % of the terrestrial area globally, would be a critical tool for avoiding a dramatic collapse of biodiversity. Agriculture is widely recognized as the largest driver of biodiversity loss. However, in China, where the demand for food production and croplands is the highest, the threats posed by agricultural activities to endangered vertebrates–particularly across different taxonomic classes–have not been thoroughly assessed. Additionally, the effectiveness of CPs in addressing these threats needs quantification across the country. In this study, we utilized high-resolution cropland data and information on threatened vertebrates to analyze the threats posed by croplands, while also evaluating the effectiveness of CPs in China. Our findings indicate that croplands in the Middle-Lower Yangtze Plain and Northeast China represent the most significant threats to threatened birds, with 1,346 and 751 identified risk spots, respectively. Furthermore, croplands in Southwest China pose considerable threats to threatened mammals and amphibians, with 851 and 469 risk spots, respectively. Importantly, many of these risk spots are not covered by CPs, revealing a significant gap of 1.2 × 10 5 km 2 , primarily in the Middle-Lower Yangtze Plain (3.6 × 10 5 km 2 ) and Southwest China (3.5 × 10 5 km 2 ). These findings provide critical insights that can inform strategies aimed at achieving the goals of the Kunming-Montreal Framework in China.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".