Rapid Communication / Communication rapideArea-dependent patterns of finfish diversity in a large marine ecosystem
Bibliographic record
Abstract
The speciesarea relationship (SAR) is considered a cornerstone of terrestrial and freshwater ecology and conservation. It has rarely been examined in a large marine ecosystem because it has been assumed that sufficient data are lacking and (or) the scales of oceanic systems are too large. Using data drawn from fishery surveys, we show a positive relationship between the number of finfish species and the area of submarine, offshore banks on the continental shelf off eastern Canada. Banks of similar size yielded similar species richness regardless of the distance between them. Area per se had a stronger influence on species number than did habitat diversity. The slope of SAR observed is consistent with the tendency for many of the species to be highly migratory with widely dispersing offspring. This results in strong interactions among banks. The combined densities of all species increased with bank area, suggesting that larger banks have higher resources per unit area. Populations and species on larger banks should be more resilient to local extinctions relative to those on smaller banks, and natural or human-induced perturbations might be expected to impact the community structure of the small, extinction-prone populations at a faster rate.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".