Fine-scale taxonomic and spatiotemporal variability in the energy density of prey for juvenile Chinook salmon (Oncorhynchus tshawytscha)
Bibliographic record
Abstract
The growth and survival of juvenile Chinook salmon (Oncorhynchus tshawytscha) are determined in part by biotic and abiotic conditions experienced during their first marine summer. Of the biotic conditions, the quality of available prey is integral for optimal growth and survival. Current studies that investigate the effect of variable prey quality on salmon growth approximate energy density using literature values. This approach ignores fine-scale taxonomic as well as spatial and temporal differences in prey quality. To address these possible sources of error, monthly zooplankton tows were performed in Saanich Inlet, Cowichan Bay and Maple Bay off the coast of Vancouver Island, British Columbia in the summer of 2017. Individuals were separated to the species level and wet, dry and ash weights were measured for each zooplankter. Energy density was calculated from an established model, which relates the ash-free dry weight of individuals to energy density values. Early results suggest statistically significant differences in energy density between several species of hyperiid amphipods, which represent a large proportion of O. tshawytscha diet in some years. Other important species groups such as euphausiids, crab zoea and gammerid amphipods differed in energy density from previously reported studies in other locations suggesting spatial variability in energy density. These early results suggest that fine-scale taxonomic variability in energy density exists and that species-specific energy density may vary across space and time. Studies that draw conclusions from literature values of energy density without direct measurement should be cautious in extrapolating with these data in relation to their study system.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".