Effects of Atlantic butterfish ( Peprilus triacanthus ) in diets of Common Terns ( Sterna hirundo ): a case study of climate change effects in the Gulf of Maine
Bibliographic record
Abstract
Climate change and associated shifts in marine prey communities can alter food availability for foraging seabirds. This issue is illustrated in the Gulf of Maine by the northward shift of Atlantic butterfish (Peprilus triacanthus; hereafter butterfish) and their subsequent increase in seabird diets. Here, we examine effects of butterfish in diets of the Common Tern (Sterna hirundo), a threatened species in this region. Our objectives were to evaluate butterfish suitability for tern chick diet through observing handling time and feeding success, to examine effects of butterfish on tern chick growth, and to explore signs of adaptive foraging in adults. The diet and growth of Common Tern chicks were studied for three breeding seasons on Seavey Island, New Hampshire, USA in the Gulf of Maine. Prey items were identified during feedings and were grouped into five prey categories: butterfish, herring, hake, other fish, and invertebrates. Chicks were weighed to calculate growth rate, which was examined as a response to diet. Across prey categories, butterfish were handled by chicks for the greatest amount of time (P < 0.001) but were swallowed the least (P < 0.001). Furthermore, chick growth rates were negatively associated with proportion of butterfish in the diet (P < 0.001). There was significant variation in chick diet across different nests in two of the three years studied (P < 0.05 in 2018 and 2019), and some breeding pairs were never observed provisioning butterfish to their young. Although the mechanism underlying individual specialization is not known, chicks that are fed fewer butterfish are at an advantage. The provisioning (or not) of unsuitable prey is particularly important because seawater warming in the Gulf of Maine is expected to increase, and butterfish are likely to become even more prevalent in seabird diets.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".