Climate and conspecific density inform phenotypic forecasting of juvenile Pacific salmon body size
Bibliographic record
Abstract
Abstract Predicting effects of climate on fitness‐linked phenotypic traits, such as body size, is important for the management and conservation of species in the face of global change. During sensitive life stages, small changes in mean trait values can have large effects on survival and population productivity. The transition from freshwater to saltwater by migrating anadromous fishes such as Pacific salmon (genus Oncorhynchus ) is a critical life history transition, where survival is mediated by the size of migrating individuals. For salmon that spend extended periods rearing in freshwater, the size at ocean entry (i.e., smolt length) may be sensitive to changes in freshwater conditions shaped by biotic and abiotic factors, yet long‐term phenotypic time series for exploring these responses are rare. We reconstructed a four‐decade time series of smolt length from archives of returning adult scales to quantify population‐specific responses to climate and conspecific density in a small watershed. Dynamic linear modeling found that the relationship between a proxy for cohort density and smolt length at ocean entry was consistently negative, suggestive of competition. In contrast, there was a positive, yet dynamic, relationship between a proxy for density of emerging fry during the second summer of growth and smolt length. The effect of temperature on smolt length was not consistent between two populations of sockeye salmon O . nerka that likely use distinct habitats within the watershed. A positive relationship between smolt length and temperature was only detected for the less abundant, early returning population. Predictions of smolt length showed variable responses under scenarios of increasing temperature and high and low densities of conspecifics. Collectively, these results reveal population‐specific responses to temperature and density, suggesting that local habitat conditions may filter larger‐scale climate drivers.
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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 | 0.000 |
| 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) | 0.002 | 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".