Assessing an age-old ecogeographical rule in nightjars across the full annual cycle
Bibliographic record
Abstract
Abstract Bergmann’s rule states that homeotherms are larger in colder climates (which occur at higher latitudes and elevations) due to thermoregulatory mechanisms. Despite being perhaps the most extensively studied biogeographical rule across all organisms, consistent mechanisms explaining which species or taxa adhere to Bergmann’s rule have been elusive. Furthermore, evidence for Bergmann’s rule in migratory animals has been mixed, and it was difficult to assess how environmental conditions across the full annual cycle impact body size until the recent miniaturization of tracking technology. Nightjars (Family Caprimulgidae), nocturnal birds with physiological and behavioral adaptations (e.g., torpor) to cope with the environmental extremes they often experience, offer a unique opportunity to elucidate the mechanisms underpinning Bergmann’s rule. Many nightjar species are strongly migratory and have large breeding ranges, offering the opportunity to look at variation in potential drivers within and across seasons of the annual cycle. Furthermore, variation in migration strategy within the family provides an opportunity to separate adaptations for migration strategy from adaptations for thermal tolerance. In this study, we use cross-continental data from three species of nightjars (Common nighthawk, Eastern whip-poor-will, and European nightjar) to assess 1) whether migratory species in this clade adheres to Bergmann’s rule, 2) which environmental factors are the best predictors of body size, and 3) the extent to which environmental conditions across the full annual cycle determine body size. For each species, we use breeding and winter location data from GPS tags to compare competing hypotheses explaining variation in body size: temperature regulation, productivity, and seasonality (during both the breeding and wintering periods), and migration distance. We found that Common nighthawk and Eastern whip-poor-will exhibit Bergmannian patterns in body size while European nightjar does not, although the spread of tag deployment sites on the breeding grounds was minimal for the European nightjar. Predictor variables associated with nightjar breeding locations more often explained body size than did variables on the wintering grounds. Surprisingly, models representing the geography hypothesis were best represented among important models in our final data set. Latitude and longitude correlated strongly with environmental variables and migratory distance; thus, these geographical variables offer a composite variable of sorts, summarizing many factors that likely influence body size in nightjars. Leveraging multi-species and cross-continental data across the full annual cycle, along with global environmental data, can provide insight into long-standing questions and will be important for understanding the generalizability of Bergmann’s rule.
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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 | 0.000 |
| 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".