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Record W4408921735 · doi:10.1111/ele.70101

Consistent Individual Differences and Plasticity in Migration Behaviour of Three North American Ungulates

2025· letter· en· W4408921735 on OpenAlexafffund
Michel P. Laforge, Eric Vander Wal, Quinn M. R. Webber, Chris Geremia, Matthew J. Kauffman, Douglas E. McWhirter, Arthur D. Middleton, Tony W. Mong, Kevin L. Monteith, Anna C. Ortega, Hall Sawyer, Jerod A. Merkle

Bibliographic record

VenueEcology Letters · 2025
Typeletter
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversity of GuelphLakehead UniversityMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaMitacsFulbright CanadaUniversity of Wyoming
KeywordsUngulateHerbivoreEcologyForageRange (aeronautics)BiologyPhenotypic plasticityHome rangeHabitat

Abstract

fetched live from OpenAlex

Migratory herbivores often time spring migration to coincide with the green-up of plants. When the timing of green-up changes across years, herbivores can respond directly and be plastic to changing conditions or populations may adapt via inherent differences among individuals that may allow for an evolutionary response. We quantified plasticity and individual variation in the timing of spring migration and selection for high-quality forage as a function of the timing of spring green-up using behavioural reaction norms for three North American ungulate species. The timing of arrival to summer range (but not departure from winter range) was plastic to the timing of green-up, and both arrival and departure timing were repeatable. Our results suggest that herbivores synchronise migration with the timing of green-up by adjusting the pace of migration and may be buffered against change via individual differences. Quantifying plasticity and differences in responses represents a crucial step to elucidating the fate of species in a changing world.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.127
Threshold uncertainty score0.887

Codex and Gemma teacher scores by category

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

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 head0.011
GPT teacher head0.198
Teacher spread0.187 · 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.

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

Citations4
Published2025
Admission routes2
Has abstractyes

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