Potential Effects Of Aggression, Site, And Proximate Determinants That Facilitate Tree Swallow Range Expansion
Bibliographic record
Abstract
Breeding range expansion occurs when individuals disperse to novel environments over successive breeding seasons and it is expected that both range expanding and native species will be affected. Additionally, native species can experience increased agonistic interactions and competition for limited resources, but they may be able to adapt by adopting behaviors such as increased aggression. Currently, tree swallows, Tachycineta bicolor, are undergoing a range expansion to the southeastern US. In Chapter 2, I investigate the effect expansion may have on a native species of eastern bluebird, Sialia sialis, by comparing territorial defense behavior of bluebirds currently experiencing the tree swallow range expansion (North Carolina) and a more southern bluebird population that is not yet living in sympatry with tree swallows (Alabama). In Chapter 3, I investigate differences between behavior and physiology across tree swallow populations throughout their historical (Wisconsin, Ontario, Nova Scotia) and new (North Carolina, Indiana, Iowa) sites. My results support the prediction that tree swallows on the edge of expansion exhibit aggressive phenotypes and have elevated glucocorticoids. My thesis improves our understanding of differences between geographic populations, expansion effects on native species, and how individuals undergoing expansion are able to survive despite the assumed costs of novel colonization.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".