Targeted Synergistic Priorities for Conserving Biodiversity, Carbon, and Water on the Qinghai‐Tibetan Plateau
Bibliographic record
Abstract
Abstract The Kunming‐Montreal Global Biodiversity Framework (GBF) highlights developing effective targets to halt and reverse the biodiversity and ecosystem services crisis. Although biodiversity and ecosystem services are tightly interlinked and interact in complex ways, a uniform global or national target has long ignored their interdependencies and uneven distribution to guide region‐ or ecoregion‐specific planning. Here, we use a flexible and stepwise approach, incorporating high conservation values of biodiversity, carbon and water and their complex interactions, to identify three targeted priority areas at regional and ecological jurisdictions on the Qinghai‐Tibetan Plateau (QTP). We find that 49% of the targeted priority areas could effectively protect about 60% of biodiversity, carbon, and water at the ecoregion scale. However, at the regional scale, 48% of the targeted priority areas have the potential to conserve up to 70% of biodiversity, carbon and water. Although the QTP has achieved the target three of the Kunming‐Montreal GBF (i.e., to protect 30% of areas), more than 75% and 70% of priority areas remain unprotected at the regional and ecoregion scales, respectively. More importantly, over 55% of the unprotected priority areas at the regional scale are under moderate to high human pressure. Our spatially explicit insights demonstrate the importance of expanding existing protected areas on the QTP, while highlighting the potential of targeted conservation initiatives at the subnational level to ensure the Kunming‐Montreal GBF in a more efficient manner.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".