Global rarity of high-integrity tropical rainforests for threatened and declining terrestrial vertebrates
Bibliographic record
Abstract
Structurally intact native forests free from major human pressures are vitally important habitats for the persistence of forest biodiversity. However, the extent of such high-integrity forest habitats remaining for biodiversity is unknown. Here, we quantify the amount of high-integrity tropical rainforests, as a fraction of total forest cover, within the geographic ranges of 16,396 species of terrestrial vertebrates worldwide. We found up to 90% of the humid tropical ranges of forest-dependent vertebrates was encompassed by forest cover. Concerningly, however, merely 25% of these remaining rainforests are of high integrity. Forest-dependent species that are threatened and declining and species with small geographic ranges have disproportionately low proportions of high-integrity forest habitat left. Our work brings much needed attention to the poor quality of much of the forest estate remaining for biodiversity across the humid tropics. The targeted preservation of the world's remaining high-integrity tropical rainforests that are currently unprotected is a critical conservation priority that may help alleviate the biodiversity crisis in these hyperdiverse and irreplaceable ecosystems. Enhanced efforts worldwide to preserve tropical rainforest integrity are essential to meet the targets of the Convention on Biological Diversity's 2022 Kunming-Montreal Global Biodiversity Framework which aims to achieve near zero loss of high biodiversity importance areas (including ecosystems of high integrity) by 2030.
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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".