Contrasting phenological and demographic responses of Atlantic Puffin (<i>Fratercula arctica</i>) and Razorbill (<i>Alca torda</i>) to climate change in the Gulf of Maine
Bibliographic record
Abstract
The Gulf of Maine is warming faster than most of the world’s ocean and is also the southern-most limit for nesting, cold-adapted Atlantic Puffin (Fratercula arctica) and Razorbill (Alca torda). Beginning in 1995, the Atlantic Laboratory for Avian Research has collected annual data on phenology, productivity, and fledgling body condition for puffins and Razorbills nesting at Machias Seal Island. Here, we aimed to quantify changes in these measures of breeding performance and assess whether they are related to environmental conditions. As predicted, we found that all measures of breeding performance (except puffin fledge date) have changed between 1995 and 2020, and in many cases, puffins and Razorbills are responding differently. Specifically, hatch date has retreated for puffins (occurring approximately 1 week later in 2011–2020 than in 1995–2004) and advanced for Razorbills (occurring approximately 1 week earlier in 2011–2020 than in 1995–2004). We found that environmental conditions were important predictors for measures of breeding performance, but importance of environmental conditions differ both between the species and among the measures of breeding performance. As the climate continues to warm, we expect continued changes in breeding performance of puffins and Razorbills. Further research is needed to understand the reasons for differences between the 2 species and the impacts of continued warming.
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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 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".