Supplemental Feeding as a Driver of Population Expansion and Morphological Change in Anna's Hummingbirds
Bibliographic record
Abstract
Bird beaks are highly adaptable, with the potential to undergo rapid morphological shifts in response to environmental change such as climatic variation or food availability. Anna's Hummingbirds (Calypte anna) have undergone dramatic population range expansions over the last 160 years into novel climatic regimes, where supplemental feeders and introduced plant species are frequented. We used museum specimens to measure and characterize the shape of Anna's Hummingbird bills, hypothesizing that the introduction of novel food sources and the colonization of colder climates were associated with distinct dimensions of beak morphology. We estimated feeder and Eucalyptus availability using data from archived newspaper databases and found that these two abundances are linked to population increases in Anna's Hummingbirds, while feeders were associated with changes to beak morphology. We found that bill size and shape changed with feeder use, exhibiting a more tapered and longer bill and a distinct maxillary constriction. In males, dorsal bill shape increased in pointedness, which may have provided an advantage with increased agonistic encounters at feeders. In contrast, bill size decreased in association with lower temperatures at higher latitudes. Our data document rapid morphological changes in the Anna's Hummingbird's bill induced by human-caused environmental changes over the last century.
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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 | 0.000 | 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".