Evaluating ecosystem protection and fragmentation of the world's major mountain regions
Bibliographic record
Abstract
Conserving mountains is important for protecting biodiversity because they have high beta diversity and endemicity, facilitate species movement, and provide numerous ecosystem benefits for people. Mountains are often thought to have lower levels of human modification and contain more protected area than surrounding lowlands. To examine this, we compared biogeographic attributes of the largest, contiguous, mountainous region on each continent. In each region, we generated detailed ecosystems based on Köppen-Geiger climate regions, ecoregions, and detailed landforms. We quantified anthropogenic fragmentation of these ecosystems based on human modification classes of large wild areas, shared lands, and cities and farms. Human modification for half the mountainous regions approached the global average, and fragmentation reduced the ecological integrity of mountain ecosystems up to 40%. Only one-third of the major mountainous regions currently meet the Kunming-Montreal Global Biodiversity Framework target of 30% coverage for all protected areas; furthermore, the vast majority of ecosystem types present in mountains were underrepresented in protected areas. By measuring ecological integrity and human-caused fragmentation with a detailed representation of mountain ecosystems, our approach facilitates tracking progress toward achieving conservation goals and better informs mountain conservation.
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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 | 0.000 | 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".