Elevation has contrasting effects on avian and mammalian nest traits in the Andean temperate mountains
Bibliographic record
Abstract
Abstract Nest building is a widespread breeding strategy across taxa. Nest composition and structure can play a critical role in the breeding success and/or adult survival of nest‐building vertebrates. Although nest traits are expected to vary adaptively across elevational gradients, few studies address this relationship. We studied the variation in nest traits (composition and structure) across elevation for two taxa with two different functions in the Andean temperate forests of southern Chile: a bird (Aphrastura spinicauda, Furnariidae, 170 breeding nests) and a marsupial mammal (Dromiciops gliroides, Microbiotheriidae, 91 winter torpor nests). ForA. spinicauda, we further assessed how nest traits influenced clutch size and hatching success. Both species used fewer types of nest materials (items) with increasing elevation, and a greater proportion of leaves were used in highland compared to lowland forests.Aphrastura spinicaudaused feathers and hair, andD. gliroidesused bryophytes more frequently in lowland forests. The mass and volume of nests decreased with increasing elevation forA. spinicaudaand increased forD. gliroides. Nest traits had subsequent fitness consequences forA. spinicauda, such that: (i) greater cup volume and depth were associated with larger clutch sizes, (ii) more items used during nest building were linked to improved clutch size at high elevation only, and (iii) nest wall thickness was negatively associated with hatching success. Thus, in temperate mountain ecosystems, elevation may be an important factor influencing nest‐building behaviour for cavity‐using vertebrates. However, the direction of the elevational effects may vary among taxa and nest functions in these ecosystems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".