Using movement, diet, and genetic analyses to understand Arctic charr responses to ecosystem change
Bibliographic record
Abstract
Arctic charr Salvelinus alpinus are a commercially and culturally valued species for northern Indigenous peoples. Climate shifts could have important implications for charr and those that rely on them, but studies that evaluate responses to ecosystem change and the spatial scales at which they occur are rare. We compare marine-phase habitat use, long-term diet patterns, and trends in effective population size of Arctic charr from 2 areas (Nain and Saglek) of Nunatsiavut, Labrador, Canada. Tagged charr in both areas frequently occupied estuaries but some also used other habitats that extended to the headland environments outside of their natal fjords. Despite the relatively small distances separating these study areas (<200 km), we observed differences in habitat use and diet. Northern stocks (including Saglek) were more reliant on invertebrates than southern stocks (e.g. Nain), for which capelin and sand lance were important prey. The use of coastal headlands also varied, with Saglek charr occupying these environments more frequently than those from Nain, which only used these habitats in 1 year of the study. Long-term commercial catches also indicate that the tendency for Nain charr to stay within fjords varies annually and relates to capelin availability. Despite the demonstrated capacity to alter diet and habitat use to changing environmental conditions, notable declines in effective population size were associated with the regime shift of the 1990s in the northwest Atlantic. Collectively, these results demonstrate that behavioral plasticity of Arctic charr may be insufficient to deal with the large environmental perturbations expected to arise from a changing climate.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".