Persistent Disparities between Recent Rates of Habitat Conversion and Protection and Implications for Future Global Conservation Targets
Bibliographic record
Abstract
Abstract Anthropogenic conversion of natural habitats is the greatest threat to biodiversity and one of the primary reasons for establishing protected areas (PAs). Here, we show that PA establishment outpaced habitat conversion between 1993 and 2009 across all biomes and the majority ( n = 567, 71.4%) of ecoregions globally. However, high historic rates of conversion meant that 447 (56.2%) ecoregions still exhibit a high ratio of conversion to protection, and of these, 127 (15.9%) experienced further increases in this ratio between 1993 and 2009. We identify 41 “crisis ecoregions” in 45 countries where recent habitat conversion is severe and PA coverage remains extremely low. While the recent growth in PAs is a notable conservation achievement, international conventions and associated finance mechanisms should prioritize areas where habitat is being lost rapidly relative to protection, such as the crisis ecoregions identified here.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".