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Record W4386413660 · doi:10.1101/2023.08.30.555574

Assessing an age-old ecogeographical rule in nightjars across the full annual cycle

2023· preprint· en· W4386413660 on OpenAlexaff
A. Skinner, AM Korpach, Susanne Åkesson, Marja H. Bakermans, TJ Benson, R. Mark Brigham, GJ Conway, CM Davy, Ruben Evens, K.C. Fraser, Anders Hedenström, IG Henderson, Juha Honkala, Lars Jacobsen, Gabriel Norevik, Kasper Thorup, Christopher M. Tonra, Andrew C. Vitz, Michael P. Ward, Emma Knight

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsCarleton UniversityAlberta Biodiversity Monitoring InstituteUniversity of ReginaUniversity of ManitobaUniversity of British Columbia
Fundersnot available
KeywordsBergmann's ruleEcologyAnnual cycleBiologyHomeothermyGeographyLatitudeThermoregulation

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.019
GPT teacher head0.266
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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