The area–heterogeneity tradeoff applied to spatial protection of rockfish ( <i>Sebastes</i> spp.) species richness
Bibliographic record
Abstract
Abstract The “area–heterogeneity tradeoff” hypothesis predicts unimodal effects of habitat heterogeneity on species richness, implying that habitats with intermediate heterogeneity may be priority for spatial protection. Alternatively, if heterogeneity effects are positive, then protecting the most heterogeneous habitats may take precedence. We tested for unimodal effects of habitat heterogeneity on the species density (area‐corrected richness) of rockfishes ( Sebastes spp.): long‐lived, benthic fishes vulnerable to overexploitation. Inconsistent with predictions, topographic structural complexity had a strong linear effect on species density; other heterogeneity measures had weaker, positive effects and the only unimodal effect (depth range) was weak. The clear implication is that, to protect the highest density of rockfish species, marine protected areas should include the most topographically complex substrates. Our results can also help refine and test species distribution models needed to inform spatial planning where in situ surveys are lacking. The area–heterogeneity tradeoff generates useful predictions for which support may be context‐dependent.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".