High daily energy expenditure of incubating shorebirds on High Arctic tundra: a circumpolar study
Bibliographic record
Abstract
Summary Given the allometric scaling of thermoregulatory capacity in birds, and the cold and exposed Arctic environment, it was predicted that Arctic‐breeding shorebirds should incur high costs during incubation. Using doubly labelled water (DLW), daily energy expenditure (DEE) during incubation was measured in eight shorebird species weighing between 29 and 142 g at various sites in the Eurasian and Canadian High Arctic. The results are compared with a compilation of similar data for birds at lower latitudes. There was a significant positive correlation between species average DEE and body mass (DEE (kJ day−1) = 28·12 BM (g)0·524, r2 = 0·90). The slopes of the allometric regression lines for DEE on body mass of tundra‐breeding birds and lower latitude species (a sample mostly of passerines but including several shorebirds) are similar (0·548 vs 0·545). DEE is about 50% higher in birds on the tundra than in temperate breeding areas. Data for radiomarked Red Knots for which the time budgets during DLW measurements were known, indicated that foraging away from the nest on open tundra is almost twice as costly as incubating a four‐egg clutch. During the incubation phase in the High Arctic, tundra‐breeding shorebirds appear to incur among the highest DEE levels of any time of the year. The rates of energy expenditure measured here are among the highest reported in the literature so far, reaching inferred ceilings of sustainable energy turnover rates.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".