Can Logging in Equatorial Africa Affect Adjacent Parks?
Bibliographic record
Abstract
Tropical deforestation can cause fundamental regional-scale shifts in vegetation structure and diversity.This is particularly true in Africa.Although national parks are being established to protect areas from deforestation and to conserve biodiversity, these parks are not immune to disturbances outside their boundaries.We used regional-scale atmospheric simulation experiments to investigate how deforestation in timber concessions might affect precipitation inside adjacent, undisturbed national parks in the equatorial African countries of Gabon and the Republic of Congo.The experiments revealed a complex response.Some parks showed rainfall reduced as much as 15%, while others showed slight increases.Rainfall inside parks was particularly sensitive to upwind deforestation along the path of airborne moisture traveling inland from the ocean.A variety of shortcomings in the current modeling procedures limit the ability to extrapolate from experiments such as ours to provide spatially explicit, long-term forecasts of climate.We describe what advances in modeling are needed to produce regional-scale predictions that are robust enough to be useful to managers and policy makers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".