Sites for priority biodiversity conservation in the Caribbean Islands Biodiversity Hotspot
Bibliographic record
Abstract
The Caribbean Islands Biodiversity Hotspot is exceptionally important for global biodiversity conservation due to high levels of species endemism and threat. A total of 755 Caribbean plant and vertebrate species are considered globally threatened, making it one of the top Biodiversity Hotspots in terms of threat levels. In 2009, Key Biodiversity Areas (KBAs) were identified for the Caribbean Islands through a regional-level analysis of accessible data and literature, followed by extensive national-level stakeholder consultation. By applying the Vulnerability criterion, a total of 284 Key Biodiversity Areas were defined and mapped as holding 409 (54%) of the region’s threatened species. Of these, 144 (or 51%) overlapped partially or completely with protected areas. Cockpit Country, followed by Litchfield Mountain - Matheson’s Run, Blue Mountains (all Jamaica) and Massif de la Hotte (Haiti) were found to support exceptionally high numbers of globally threatened taxa, with more than 40 such species at each site. Key Biodiversity Areas, building from Important Bird Areas, provide a valuable framework against which to review the adequacy of existing national protected-area systems and also to prioritize which species and sites require the most urgent conservation attention.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".