Using patch studies to link mesoscale patterns of feeding and growth in larval fish to environmental variability
Bibliographic record
Abstract
We present results from a series of three patch studies designed to examine links between environmental variability and mesoscale patterns of feeding and growth of larval radiated shanny ( Ulvaria subbifurcata ). We examine the effects of variability in temperature, turbulence and prey concentration on both the mean (i.e. population level) and the variance (i.e. individual level) of larval feeding and growth rates among the three bays. Although both gut fullness and growth rates differ significantly between bays, our results show only weak environmental influences. When larvae are pooled across bays (i.e. treated as independent observations), environmental factors generally explain <4% of the variability in gut fullness. When treated as daily mean residuals, however, temperature accounts for 41% of the variability in mean gut fullness, while both temperature and prey concentration also explain significant portions of the variance in gut fullness (38 and 43%, respectively). Between‐bay differences in larval growth rates are consistent with patterns of temperature variation but not with patterns of prey availability. Studies relying on tracking a single patch of larvae typically suffer from having too few observations to detect significant relationships between feeding or growth and environmental variables. By following three patches we collected a larger number of observations. However, as we encountered only a limited range of environmental conditions it remains difficult to adequately assess the role of environmental factors. In part, this problem stems from the inability of fisheries oceanographers to track the recent environmental history of individual larvae on the same fine scales currently employed to collect biological data (e.g. guts and otoliths) on individuals.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".