Environmental conditions and individual characteristics influence movement patterns of juvenile <i>Passerculus sandwichensis</i> (Savannah sparrow) throughout the post-fledging period
Bibliographic record
Abstract
Abstract Movements in the post-fledging period, an important first stage of natal dispersal that occurs after juveniles fledge from the nest but before they depart for fall migration, have important implications for survival. However, relatively little is known about movements during this vulnerable period. Here, we used daily radio telemetry data from 137 juvenile Passerculus sandwichensis (Savannah Sparrow) between 2022 and 2024 and hierarchical generalized additive models to examine the relationship between movement and age across a 90-day period. We evaluated how movement—distance from the nest and between consecutive daily locations—was influenced by age post-fledging, sex, brood number, year, age at fledging, local nest density, nestling mass, and weather variables. Both the distance of fledglings from their natal nest and the distance moved between days increased with age post-fledging, most steeply when fledglings became independent, then remained steady for the remainder of the post-fledging period. Movement varied among individuals: some fledglings remained near the nest for extended periods, and others traveled long distances soon after fledging. Offspring from second broods traveled greater distances than those from first broods. Nest density also influenced movement, with fledglings from high-density areas traveling farther from their nests but, on average, less far between days. Movement patterns were also influenced by year and sex, and weakly influenced by mass and daily precipitation. Our results demonstrate how movement patterns can change between the early post-fledging period and the relatively understudied late post-fledging period.
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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) | 0.001 | 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".