Prefledging Growth and Recruitment of Female Lesser Scaup
Bibliographic record
Abstract
ABSTRACT Annual variation in juvenile recruitment is an important component of duck population dynamics, yet little is known about the factors affecting the probability of surviving and breeding in the first year of life. Two hypothesized mechanisms to explain annual variability are indirect carry‐over effects (COEs) from conditions experienced during the prefledging period and direct effects from climatic conditions during the postfledging period. We used Cormack‐Jolly‐Seber models to estimate apparent survival and detection rates of 643 juvenile female lesser scaup (Aythya affinis) marked just prior to fledging at Red Rock Lakes National Wildlife Refuge in southwestern Montana, USA, 2010–2018. We evaluated COEs from hatch date, a hatch date × spring phenology interaction, and conspecific duckling density in addition to a direct climatic effect of winter conditions (indexed by the El Niño Southern Oscillation [ENSO]) and spring habitat conditions on the study area. We used growth data from a subset (n = 190) of known‐aged ducklings to estimate the influence of hatch date and conspecific density on prefledging growth to help identify mechanisms underlying COEs. Prefledging growth and juvenile apparent survival were negatively related to measures of conspecific duckling density. We found evidence that detection probability varied annually for juvenile (but not adult) scaup, possibly representing decisions to delay breeding and not return to or remain at the study site in their first year of life. Like with apparent survival, there was suggestive evidence that detection probability decreased with increasing duckling density in the previous year. Hatching date was weakly negatively related to detection probability, but unrelated to apparent survival, whereas neither vital rate was related to winter ENSO index. Our results are consistent with a process where density‐dependent growth rates in the prefledging period carry over to influence fitness in subsequent life‐cycle stages. If this pattern generalizes to other systems, this density COE may have important implications for our understanding of duck population dynamics and reaffirms the importance of maintaining abundant brood‐rearing habitats in conservation and management of ducks. © 2021 The Wildlife Society.
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.
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 | 0.000 | 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".