Shared principles for area-based biodiversity conservation
Bibliographic record
Abstract
Recent international agreements have strengthened and expanded commitments to protect and restore native habitats. Nevertheless, biodiversity conservation is hindered because how such commitments should be implemented has been strongly debated. By bringing together researchers on both sides of the habitat fragmentation debate, we identify three incontrovertible principles for area-based biodiversity conservation. Such principles are related to habitat geographic coverage, amount, and connectivity. They emerge from our fundamental agreement that, while large areas of nature are important and must be protected, conservation or restoration of multiple small habitat patches is also critical for global conservation, particularly in regions with high land use. We contend that the many area-based conservation initiatives expected in the coming decades should follow the principles we propose. Considering the importance of biodiversity for maintenance of ecosystem services, we suggest that this would bring unequivocal societal benefits.
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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 | 0.042 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.049 |
| Scholarly communication | 0.014 | 0.013 |
| Open science | 0.006 | 0.016 |
| Research integrity | 0.009 | 0.021 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".