Climate change and Arctic charr (Salvelinus alpinus) in North America: modelling possible changes in range with different climate scenarios and interspecific interactions
Bibliographic record
Abstract
Abstract One of the greatest challenges for researchers today is understanding climate-change impacts on fish populations, particularly in vulnerable and understudied ecosystems such as the Canadian Arctic. Among other impacts, northern fishes will undergo thermal stress as atmospheric and sea surface temperatures are projected to rise globally. Models that consider how both environmental factors such as temperature and potential species interactions will impact population extirpation and species’ range contraction can help project the future distribution of a species in the face of a warming climate. Here, we investigate the climate-change impacts of rising temperatures and the potential northward distributional shift of brook charr ( Salvelinus fontinalis ) on Arctic charr ( Salvelinus alpinus ), Canada’s northernmost freshwater fish species. Specifically, we used a logistic regression model to establish baseline relationships between the current distribution of Arctic charr and the variables, degree-days (a key climate variable), geographical location, and brook charr occurrence. We developed the model applying the expected changes in degree-days to 2050 (25–50% increase from the average of 1976–2005) and 2080 (50–100% increase) while incorporating the historical distribution of Arctic charr to estimate the change in Arctic charr distribution over that time. We found that growing degree-days, longitude, latitude, and brook charr occurrences correctly classified 93% of Arctic charr historical occurrences in Canada. We estimate that in a high-carbon scenario, where degree-days are expected to increase by 50 to 100%, Arctic charr range is projected to decrease by 18% in Canada by 2051–2080 and decrease even further by 3% with the presence of brook charr. The Canadian high Arctic may provide refuge for Arctic charr, likely maintaining temperatures optimal for species persistence. Regardless, management that considers the climate stresses on Arctic charr populations will be important to preserve this highly valued resource that is pivotal for food security and traditional ways of life for northerners.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".