Substrate and structure of ground nests have fitness consequences for an alpine songbird
Bibliographic record
Abstract
Songbird nests are an important life‐history component with multiple functions, including the creation of a suitable microclimate for offspring development. Thus, functional nest characteristics may influence fitness correlates, such as nestling size traits, and may co‐vary with prevailing environmental conditions. We investigated among‐ and within‐female variation in nest substrate, lining and decoration structures with associated fitness consequences (hatching success, nestling size traits, nest survival) across two breeding seasons for an alpine population of Horned Lark Eremophila alpestris. We combined these observations with explicit measures of nest temperature to address the influence of nest characteristics on microclimate. Nests in heather substrate had the coldest microclimates compared with grass and bare‐ground substrate, but also the greatest nest survival rates (68% versus 37–44% in other substrates), indicating the potential for substrate use decisions to reflect a trade‐off between microclimate and nest survival in response to prevailing weather and predation risk conditions. Furthermore, nest lining and nest decoration patterns indicated some support for a thermoregulatory function. Nests that were lined with willow (Salix sp.) seed‐down were associated with larger, heavier nestlings and the use of down lining decreased in frequency as the season warmed up. Nest decoration placed in front of the nest (e.g. stones or dirt clumps varying in mass from 5.3 to 186.6 g) was positively associated with warmer nest microclimates. Females demonstrated high phenotypic flexibility, as 61–94% of the observed variance in nest characteristics was explained by within‐female rather than among‐female differences. Such flexible nesting behaviour suggests the capacity to adjust to changing environmental conditions to maintain vital fitness correlates such as nest survival and nestling size development.
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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".