Regional analysis of body size and population density in stream fish assemblages: testing predictions of the energetic equivalence rule
Bibliographic record
Abstract
The energetic equivalence rule predicts that body mass (W) and population density (β) within an assemblage are negatively correlated and will exhibit a W0.75 = β relationship. Bergmann's rule predicts that body size among species will increase with increasing latitude. If species body size increases with latitude, the shape of the body size population density distribution among assemblages may also vary. This change in the body size population density distribution, when viewed in the context of the energetic equivalence rule, may indicate an alteration in the use of available energy by individuals of different sizes within an assemblage. Twenty-eight streams were sampled across four geographically distinct regions to determine if stream fish assemblages conform to the prediction of the energetic equivalence rule. Body size in stream fish assemblages did not support the pattern predicted by Bergmann's rule, but rather was negatively correlated with latitude. Stream fish assemblages generally did not conform to the relationship predicted by the energetic equivalence rule. Moreover, these results, coupled with the predictions of the energetic equivalence rule, suggest that larger individuals tended to control a disproportionately greater amount of energy than smaller individuals in stream fish assemblages, which may be partially due to predation pressure on smaller individuals.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".