Data from: Hidden survival heterogeneity of three common eider populations in response to climate fluctuations
Bibliographic record
Abstract
(1) Understanding how individuals and populations respond to fluctuations in climatic conditions is critical to explain and anticipate changes in ecological systems. Most such studies focus on climate impacts on single populations without considering inter- and intra-population heterogeneity. However, comparing geographically dispersed populations limits the risk of faulty generalizations and helps to improve ecological and demographic models. (2) We aimed to determine whether differences in migration tactics among and within populations would induce inter- or intra-population heterogeneity in survival in relation to winter climate fluctuations. Our study species was the Common eider (Somateria mollissima), a marine duck with a circumpolar distribution, which is strongly affected by climatic conditions during several phases of its annual cycle. (3) Capture-mark-recapture (CMR) data were collected in two arctic (northern Canada and Svalbard) and one subarctic (northern Norway) population over a period of 18, 15 and 29 years, respectively. These three populations have different migration tactics and experience different winter climatic conditions. Using multi-event and mixture modelling, we assessed the association between adult female eider survival and winter conditions as measured by the North Atlantic Oscillation index. (4) We found that winter weather conditions affected survival of female eiders from each of these three populations. However, different mechanisms seemed to be involved. Survival of the two migrating arctic populations was impacted directly by changes in the NAO, whereas the subarctic resident population was affected by the NAO with time lags of two to three years. Moreover, we found evidence for intra-population heterogeneity in the survival response to the winter NAO in the Canadian eider population, where individuals migrate to distinct wintering areas. (5) Our results illustrate how individuals and populations of the same species can vary in their responses to climate variation. We suspect that the found variation in survival response of birds to winter conditions is partly explained by differences in migration tactic. Detecting and accounting for inter- and intra-population heterogeneity will improve our predictions concerning the response of wildlife to global changes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".