Near-Complete Extinction of Native Small Mammal Fauna 25 Years After Forest Fragmentation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Tropical forests continue to be felled and fragmented around the world. A key question is how rapidly species disappear from forest fragments and how quickly humans must restore forest connectivity to minimize extinctions. We surveyed small mammals on forest islands in Chiew Larn Reservoir in Thailand 5 to 7 and 25 to 26 years after isolation and observed the near-total loss of native small mammals within 5 years from <10-hectare (ha) fragments and within 25 years from 10- to 56-ha fragments. Based on our results, we developed an island biogeographic model and estimated mean extinction half-life (50% of resident species disappearing) to be 13.9 years. These catastrophic extinctions were probably partly driven by an invasive rat species; such biotic invasions are becoming increasingly common in human-modified landscapes. Our results are thus particularly relevant to other fragmented forest landscapes and suggest that small fragments are potentially even more vulnerable to biodiversity loss than previously thought.
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.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it