Fine-scale taxonomic and temporal variability in the energy density of invertebrate prey of juvenile Chinook salmon Oncorhynchus tshawytscha
Bibliographic record
Abstract
Variation in the energy content of prey can drive the diet choice, growth and ultimate survival of consumers. In Pacific salmon species, obtaining sufficient energy for rapid growth during early marine residence is hypothesized to reduce the risk of size-selective mortality. In order to determine the energetic benefit of feeding choices for individuals, accurate estimates of energy density (ED) across prey groups are required. Frequently, a single species is assumed to be representative of a larger taxonomic group or related species. Further, single-point estimates are often assumed to be representative of a group across seasons, despite temporal variability. To test the validity of these practices, we sampled zooplankton prey of juvenile Chinook salmon to investigate fine-scale taxonomic and temporal differences in ED. Using a recently developed model to estimate the ED of organisms using percent ash-free dry weight, we compared energy content of several groups that are typically grouped together in growth studies. Decapod megalopae were more energy rich than zoeae and showed family-level variability in ED. Amphipods showed significant species-level variability in ED. Temporal differences were observed, but patterns were not consistent among groups. Bioenergetic model simulations showed that growth rate of juvenile Chinook salmon was almost identical when prey ED values were calculated on a fine scale or on a taxon-averaged coarse scale. However, single-species representative calculations of prey ED yielded highly variable output in growth depending on the representative species used. These results suggest that the latter approach may yield significantly biased results.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".