Peer Review #1 of "Times and partners are a-changin’: relationships between declining food abundance, breeding success, and divorce in a monogamous seabird species (v0.1)"
Bibliographic record
Abstract
Seabirds exhibit considerable adjustment capacity to cope with environmental changes during the breeding season and to maximize lifetime reproductive output.For example, divorce has been proposed to be an adaptive behavioral strategy in social monogamous species, as a response to poor conditions and low breeding success.Here, we studied divorce at the population and individual levels in northern gannets (Morus bassanus, hereafter gannets) nesting at Bonaventure island (Quebec, Canada).At the population level, we used Granger's method for detecting and quantifying temporal causality between time series (from 2009 to 2019) of divorce rate and breeding success of gannets (n = 809) and we evaluated the relationship between breeding success and biomass of their two principal prey (Atlantic mackerel, Scomber scombrus, and Atlantic herring, Clupea harengus).Our results indicated that breeding success is mainly influenced by the biomass of Atlantic mackerel, and a decrease in breeding success is followed by an increase in divorce rate with a one-year lag.However, the effect of the interaction between breeding success and year on the proportion of individuals that divorced showed significant inter-annual variation.At the individual level, our results support the adaptive strategy hypothesis of divorce.Indeed, gannets that changed partners did so following a reproductive failure, and there was an increase in breeding success one year following the divorce.Being central place foragers, opportunities for dispersal and adaptation are often limited for breeding seabirds in a context of low food abundance.We suggest that behavioral flexibility expressed as divorce would be an attractive short-term strategy for maintaining reproductive performance.
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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 | 0.008 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.180 | 0.090 |
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".