Assessing the effect of seasonal agriculture on the condition and winter survival of a migratory songbird in Mexico
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Migratory birds can spend 8 months of the year on their wintering grounds and the conversion of natural habitats to agriculture in Latin America has been implicated in population declines of several Neotropical migrants. Despite this, few studies have directly assessed the value of agricultural habitat for wintering migrants. We compared the condition and survival of Yellow Warblers ( Setophaga petechia ) occupying natural (riparian forest, scrub‐mangrove) and agricultural habitat (annually cropped sorghum, corn, and chili‐peppers separated by hedgerow) in western Mexico. We assessed condition with five metrics (daily and seasonal changes in size‐adjusted body mass, leukocyte profiles, rectrix regrowth rate, rectrix quality, and dates of departure on spring migration). We used Cormack–Jolly–Seber models fitted to mark‐resighting data collected over 4 years (2012–2015) to estimate January–May monthly survival rates. We found that birds occupying agricultural habitat and riparian forest had higher monthly apparent survival between January and May than birds in scrub‐mangrove. Birds in agricultural habitat also grew higher quality feathers (i.e., rectrices with a higher barbule density) than those in natural habitat. In contrast, birds in agricultural habitat were lighter than those in riparian habitat. We found no detectable effect of winter habitat use on daily or season changes in size‐adjusted mass and H/L ratios, although the effect of winter habitat use on departure rates differed for males and females. Our results demonstrate that agricultural habitat may provide suitable winter habitat for a long‐distance migrant and suggest that feather quality can be an indicator of winter habitat quality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it