Challenges to conventional explanations of habitat specificity in migrant birds
Bibliographic record
Abstract
I considered the sufficiency of conventional niche theory as an explanation of breeding habitat specificity in migratory birds. In the field, I used transects, equal-effort sampling, and vegetation analysis in order to study use of space and foraging behaviours in a foliage-gleaning insectivore guild. Using multivariate techniques, I compared patterns among breeding per se, midsummer, and early fall. Habitat specificity and certain foraging traits differed among guild members during breeding, but as the summer progressed those differences declined, a pattern acutely exhibited by Dendroica warblers. Accordingly, habitat specificity in migrant birds is well developed during breeding per se, but it declines during the second part of the period spent in the breeding landscape. Using the same guild, I evaluated a matrix of 27 skeletal measures using principal components analysis. I found that conspecific sexes were commonly less similar morphologically than some heterospecific pairs of the guild, indicating that habitat preferences cannot be accounted for by subtle morphological differences among species. I next considered the biogeography of geographic breeding and winter range sizes for 89 passerine species breeding in North America. I found that latitudinal patterns of landmass availability in the Americas influence relative magnitudes of breeding and winter range sizes, with the latter almost universally smaller than the former. Populations wintering in areas with relatively little landmass appear to be compressed into such areas, strongly suggesting that New World landmass limitations in the latitudes of Central America and the Caribbean influence breeding population sizes. Despite this apparent limitation, breeding territories of migrant birds are commonly clustered. In the field, I broadcast territorial song during the Least Flycatcher spring settlement period and found that such treatments did influence where arriving males displayed, although treatments did not ultimately produce new clusters. I conclude by reviewing sexual selection models and I propose that intersexual behavioural interactions may play a role in the development of breeding habitat specificity, independent of ecological factors. The mechanics of indirect models as well as sexual conflict leading to territorial aggregations could generate sexually selected breeding habitat, by valuing habitat elements as sexual, rather than ecological, commodities.
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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 | 0.027 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.018 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".