Shared wilderness, shared responsibility, shared vision: Protecting migratory wildlife
Bibliographic record
Abstract
Wilderness plays a vital role in global and landscape-level conservation of wildlife. Millions of migratory birds and mammals rely on wilderness lands and waters during critical parts of their life. As large, ecologically intact landscapes, wilderness areas also play a vital role in addressing global climate change by increasing carbon sequestration, reducing fragmentation, and providing dispersal corridors. However, potential biome shifts, fragmentation, and the effects of urbanization threaten even remote wilderness areas. The National Wildlife Refuge System (U.S. Fish and Wildlife Service) protects over 18 million acres of designated wilderness in Alaska. Wildlife protected within this wilderness spend significant parts of their lives in Canada, Latin American, and other countries, which are also suffering the effects of global climate change. We briefly discuss three species that spend significant portions of their lives in the Arctic National Wildlife Refuge, but rely on habitat in other countries during other phases of their lives. Examples of successful international efforts are provided. We suggest that by enhancing hemispheric partnerships to preserve critical habitat as permanently protected wildlands, we can increase resiliency, redundancy, and representation of habitats for these shared species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".