Narrow thresholds of canopy disturbance determine the microclimate buffering potential of tropical forests
Bibliographic record
Abstract
The importance of protecting logged and recovering tropical forests has gained much attention. Disturbed forests can, however, have hotter microclimates, exacerbating the effects of future climate change. Using thermal imaging we captured understory surface temperatures along a gradient of tropical forest disturbance, and compared these to the upper thermal limits (CT max ) of invertebrates within the same forests. Surface temperatures exceeding the CT max of invertebrate groups occurred once canopy cover fell below 76%. In highly degraded forests, surface niche space was reduced by 22% for the most sensitive taxa, and this doubled following simulated warming of +3°C. In contrast, all invertebrate groups were buffered in sites that retained 80% canopy cover or higher even following severe warming. We demonstrate a narrow threshold of canopy disturbance beyond which microclimate buffering is significantly diminished. These findings illustrate the importance of conserving high canopy cover forests to protect tropical biodiversity in a hotter future.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 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".