Connectivity of Forest Patches via Wooded Corridors Increases Biodiversity at Low, but Not High, Forest Amounts
Bibliographic record
Abstract
ABSTRACT To determine whether we can reduce the impacts of forest loss on biodiversity by altering forest pattern, we need to estimate the effects of forest pattern independent of forest amount. We evaluated the independent and interactive effects of forest amount, fragmentation, and connectivity (wooded corridors) on diversity of forest‐associated plants, small mammals, and birds. We selected 70 forest sites in eastern Ontario, Canada with low correlations between these landscape predictors. We found positive effects of forest amount, neutral or positive effects of forest fragmentation, and an interaction effect between connectivity and forest amount. In landscapes with low forest amount, biodiversity increased with connectivity, while at high forest amount, biodiversity decreased with connectivity. Thus, forest patches should be protected regardless of size, and conservation actions aimed at improving connectivity by adding wooded corridors should be prioritized in areas where forest is scarce, for example agricultural and urban areas.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".