Temporal constraints influence reproductive characteristics that are related to the pace‐of‐life continuum in geese
Bibliographic record
Abstract
Among avian species, particularly those with altricial young, life‐history strategies are characterized by a ‘slow’ pace‐of‐life at lower latitudes, where relatively low annual investments in reproduction are traded‐off for increased survival. Evidence for this pattern in precocial species, however, is equivocal, and questions about ecological drivers of latitudinal variation in reproduction remain. To better understand spatial variation in pace‐of‐life and related reproductive traits across bird species and to test a hypothesis that might explain observed spatial patterns, we analysed breeding data from closely related Canada Geese Branta canadensis and Cackling Geese Branta hutchinsii, hereafter Canada‐type geese, comprising eight sub‐species from 16 sites across a broad gradient of latitude (32°N to 69°N) and season length. Unlike the pattern reported for many altricial species, Canada‐type geese did not show reduced annual fecundity at lower latitudes, and instead this reduced reproductive investment was at higher latitudes. For three of five reproductive traits, the relative influence of growing season length (GSL; an index of the time available to breed) was greater than that of latitude. A shorter GSL resulted in later nest initiations, shorter pre‐laying intervals and higher seasonal rates of clutch size decline. Our results suggest that these and other species of geese are able to circumvent nutritional and temporal constraints imposed by shorter GSL by storing and using nutrient reserves for egg laying and incubation. Relative flexibility in reproductive traits may permit Canada‐type geese to accommodate predicted increases in climatic variability, compared to species with more rigid reproductive strategies.
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 | 0.001 | 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".