Sympatric Atlantic puffins and razorbills show contrasting responses to adverse marine conditions during winter foraging within the North Sea
Bibliographic record
Abstract
BACKGROUND: Natural environments are dynamic systems with conditions varying across years. Higher trophic level consumers may respond to changes in the distribution and quality of available prey by moving to locate new resources or by switching diets. In order to persist, sympatric species with similar ecological niches may show contrasting foraging responses to changes in environmental conditions. However, in marine environments this assertion remains largely untested for highly mobile predators outside the breeding season because of the challenges of quantifying foraging location and trophic position under contrasting conditions. METHOD: )) indicated that environmental conditions differed between 2007/08 (low survival and thus poor conditions) and 2014/15 (higher survival, favourable conditions). We used a combination of bird-borne data loggers and stable isotope analyses to test 1) whether these sympatric species showed consistent responses with respect to foraging location and trophic position to these contrasting winter conditions during periods when body and cheek feathers were being grown (moult) and 2) whether any observed changes in moult locations and diet could be related to the abundance and distribution of potential prey species of differing energetic quality. RESULTS: Puffins and razorbills showed divergent foraging responses to contrasting winter conditions. Puffins foraging in the North Sea used broadly similar foraging locations during moult in both winters. However, puffin diet significantly differed, with a lower average trophic position in the winter characterised by lower survival rates. By contrast, razorbills' trophic position increased in the poor survival winter and the population foraged in more distant southerly waters of the North Sea. CONCLUSIONS: Populations of North Sea puffins and razorbills showed contrasting foraging responses when environmental conditions, as indicated by overwinter survival differed. Conservation of mobile predators, many of which are in sharp decline, may benefit from dynamic spatial based management approaches focusing on behavioural changes in response to changing environmental conditions, particularly during life history stages associated with increased mortality.
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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 | 0.000 |
| 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) | 0.001 | 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".