A temporally stable spatial pattern in the spawner density of a freshwater fish: evidence for an ideal despotic distribution
Bibliographic record
Abstract
We explore the causal basis for a temporally stable spatial pattern in the density of spawning individuals of a freshwater fish. Based on a comparatively long-term set of data spanning one decade, reproductively active brook trout (Salvelinus fontinalis) inhabiting a near-pristine river on Cape Race, southeastern Newfoundland, occupy areas of either high or low density. Compared with their low-density counterparts, high-density aggregations are typically more than 30 times denser despite occupying only 4% of the available habitat. High-density areas are characterized by slower flow and suspected groundwater or bog-water seepage, attributes likely to increase the probability of offspring survival in Freshwater River. Disparity in density between high- and low-density aggregations declined as total population size increased, a pattern consistent with the predictions of the ideal free distribution. The larger body sizes of trout in the high-density aggregations may prevent others from occupying the most preferred spawning habitat. This spatial pattern in spawner density is consistent with that predicted by an ideal despotic distribution, although we cannot discount the influence that Allee effects might have on the distributional patterns of spawning individuals at low population sizes.
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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 | 0.001 | 0.004 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".