Obstruction of biodiversity conservation by minimum patch size criteria
Bibliographic record
Abstract
Minimum patch size criteria for habitat protection reflect the conservation principle that a single large (SL) patch of habitat has higher biodiversity than several small (SS) patches of the same total area (SL > SS). Nonetheless, this principle is often incorrect, and biodiversity conservation requires placing more emphasis on protection of large numbers of small patches (SS > SL). We used a global database reporting the abundances of species across hundreds of patches to assess the SL > SS principle in systems where small patches are much smaller than the typical minimum patch size criteria applied for biodiversity conservation (i.e., ∼85% of patches <100 ha). The 76 metacommunities we examined included 4401 species in 1190 patches. From each metacommunity, we resampled species-area accumulation curves to evaluate how biodiversity responded to habitat existing as a few large patches or as many small patches. Counter to the SL > SS principle and consistent with previous syntheses, species richness accumulated more rapidly when adding several small patches (45.2% SS > SL vs. 19.9% SL > SS) to reach the same cumulative area, even for the very small patches in our data set. Responses of taxa to habitat fragmentation differed, which suggests that when a given total area of habitat is to be protected, overall biodiversity conservation will be most effective if that habitat is composed of as many small patches as possible, plus a few large ones. Because minimum patch size criteria often require larger patches than the small patches we examined, our results suggest that such criteria hinder efforts to protect biodiversity.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".