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Record W4229449824 · doi:10.1002/ecs2.4059

Integrating microclimatic variation in phenological responses to climate change: A 28‐year study in a hibernating mammal

2022· article· en· W4229449824 on OpenAlexafffund
Anouch Tamian, Vincent A. Viblanc, F. Stephen Dobson, Peter Neuhaus, Tracey L. Hammer, Anna P. Nesterova, Shirley Raveh, Amy L. Skibiel, David Broussard, Theodore G. Manno, R. Nandini, Claire Saraux

Bibliographic record

VenueEcosphere · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCentre National de la Recherche ScientifiqueUniversité de StrasbourgAlberta Environment and ParksAmerican Society of MammalogistsAuburn UniversityFondation FyssenMinistère de l'Enseignement supérieur, de la Recherche et de l'InnovationNational Science Foundation
KeywordsMicroclimateClimate changePhenologyEcologyHibernation (computing)GeographyHabitatEnvironmental sciencePhysical geographyClimatologyBiology

Abstract

fetched live from OpenAlex

Abstract Phenological shifts associated with directional changes in climate, resulting in earlier spring activities, have been documented in several animal species. However, the extent to which species respond to overall climate change versus local climate variation is rarely studied. In addition, climate data are usually averaged over large spatial scales, even though local heterogeneity in habitats may be high, and species might be more susceptible to changes in local rather than global climate conditions. In this study, we examined the effects of spatiotemporal climate variation and climate change on the phenology of a hibernating mountain rodent, the Columbian ground squirrel ( Urocitellus columbianus ). Over 28 years of research (1992–2019), we studied the relationship between the microclimatic conditions experienced by adult and juvenile ground squirrels from four neighboring meadows, and their dates of emergence from hibernation. We used a microclimate model to calculate microclimate variables (local snow depth, soil temperature, air temperature, wind speed, and humidity) at an hourly scale, a 5‐m spatial resolution, and at animal height on the study sites over 28 years. Emergence dates varied with age and sex, among years, as well as among and within meadows, with some areas averaging up to 10 days earlier emergence dates from hibernation than others. While emergence dates tended to be delayed throughout the study period, long‐term temporal changes and interannual variability in emergence dates differed among meadows and depended on individual age and sex. Dates of hibernation emergence were correlated with local climate variables considered either during hibernation or during the preceding summer. Ground squirrels emerged earlier in years or at locations when/where snow melted earlier (years: all individuals excluding 2‐year‐old males, locations: yearlings and older females), and when the previous summer was less windy (≥3‐year‐old individuals) and more humid (2‐year‐old males). Two‐year‐old male ground squirrels also emerged later in locations where snow depth during winter was higher. Using a microclimate model allowed realistic predictions of phenological responses to climate, highlighting its potential for research on animal responses to abiotic change.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.037
GPT teacher head0.260
Teacher spread0.223 · 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 teacher head, not a consensus.

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

Citations11
Published2022
Admission routes2
Has abstractyes

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