Population vulnerability to climate change linked to timing of breeding in boreal ducks
Bibliographic record
Abstract
Abstract Identifying and understanding why traits make species vulnerable to changing climatic conditions remain central problems in evolutionary and applied ecology. We used spring snow cover duration as a proxy for phenological timing of wetland ecosystems, and examined how snow cover duration during spring and during the entire snow season affected population dynamics of duck species breeding in the western boreal forest of N orth A merica, 1973–2007. We predicted that population level responses would differ among duck species, such that late‐nesting species with reduced flexibility in their timing of breeding, i.e. scaup ( A ythya spp.) and scoter ( M elanitta spp.), would be more strongly affected by changing snow cover conditions relative to species better able to adjust timing of breeding to seasonal phenology, i.e. mallard ( A nas platyrhynchos ) and A merican wigeon ( A nas americana ). Population growth rates of scaup and scoter were positively linked to spring snow cover duration; after accounting for effects of density dependence, larger populations resulted after springs with long snow cover duration than after springs with short snow cover duration. In contrast, population growth rates of mallard and wigeon were either negatively or only weakly associated with snow cover duration. Duck population models were then incorporated with snow cover duration derived from climate model simulations under the A2 emission scenario, and these predictions suggested that late‐nesting duck species will experience the most severe population declines. Results are consistent with a hypothesis that the gradual climatic warming observed in the western boreal forest of N orth A merica has contributed to and may continue to exacerbate population declines of scaup and scoter.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".