Habitat modulates population‐level responses of freshwater salmon growth to a century of change in climate and competition
Bibliographic record
Abstract
The impacts of climate change are widespread and threaten natural systems globally. Yet, within regions, heterogeneous physical landscapes can differentially filter climate, leading to local response diversity. For example, it is possible that while freshwater lakes are sensitive to climate change, they may exhibit a diversity of thermal responses owing to their unique morphology, which in turn can differentially affect the growth and survival of vulnerable biota such as fishes. In particular, salmonids are cold-water fishes with complex life histories shaped by diverse freshwater habitats that are sensitive to warming temperatures. Here we examine the influence of habitat on the growth of sockeye salmon (Oncorhynchus nerka) in nursery lakes of Canada's Skeena River watershed over a century of change in regional temperature and intraspecific competition. We found that freshwater growth has generally increased over the last century. While growth tended to be higher in years with relatively higher summer air temperatures (a proxy for lake temperature), long-term increases in growth appear largely influenced by reduced competition. However, habitat played an important role in modulating the effect of high temperature. Specifically, growth was positively associated with rising temperatures in relatively deep (>50 m) nursery lakes, whereas warmer temperatures were not associated with a change in growth for fish among shallow lakes. The influence of temperature on growth also was modulated by glacier extent whereby the growth of fish from lakes situated in watersheds with little (i.e., <5%) glacier cover increased with rising temperatures, but decreased with rising temperatures for fish in lakes within more glaciated watersheds. Maintaining the integrity of an array of freshwater habitats-and the processes that generate and maintain them-will help foster a diverse climate-response portfolio for important fish species, which in turn can ensure that salmon watersheds are resilient to future environmental change.
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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 | 0.000 | 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) | 0.001 | 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".