Ecological Drivers of Molt‐Breeding Overlap, an Unusual Life‐History Strategy of Small‐Island Birds?
Bibliographic record
Abstract
Terrestrial bird populations on small, species depauperate islands often experience selection for generalist foraging traits via ecological release; however, it is unclear how island conditions may uniquely influence other life-history characteristics of small-island birds, such as the unusually high rates of molt-breeding overlap exhibited on the island of Grenada. To explore this question, we collected data on the life cycles and diets of 10 commonly occurring Grenadian bird species to assess the degree of generalist foraging and evaluate how seasonal patterns in diet niche breadth and diet overlap among species relates to the high rates of molt-breeding overlap. We evaluated three hypotheses explaining drivers of molt-breeding overlap (constraints on molt rate, unpredictable food abundance, and limited duration of food abundance), and suggest that widespread overlap in small-island tropical communities may be the result of generalist foraging adaptations and restricted time periods of sufficient invertebrate availability for successful breeding and molt to occur. We found that these species typically exhibited low breeding period seasonality followed by synchronized peaks in molt intensity and molt-breeding overlap during peak rainfall and high invertebrate abundance. There was also greater diet overlap and wider niche widths of invertebrate resources in the wet season when molt-breeding overlap occurred, and greater niche partitioning of invertebrate items among species in the dry season suggesting that competitive interactions for invertebrates were stronger in the dry season. Birds also shared more plant food sources in the dry season when invertebrate abundance is low, though seasonal differences in plant diet diversity and niche width varied by species. These results provide evidence that scarce invertebrate resources and competition likely limit productivity and molt/self-maintenance in these island-adapted, species-depauperate communities, and drive high rates of molt-breeding overlap, a relatively uncommon life-history strategy.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".