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Record W2967532869 · doi:10.3389/fevo.2019.00325

Prevalence and Mechanisms of Partial Migration in Ungulates

2019· article· en· W2967532869 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFrontiers in Ecology and Evolution · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversity of Alberta
FundersParks CanadaRocky Mountain Elk FoundationAlberta Environment and ParksSafari Club International FoundationDivision of Environmental BiologyNational Aeronautics and Space AdministrationUniversity of MontanaUniversity of AlbertaAlberta Conservation AssociationNational Science Foundation
KeywordsUngulatePopulationEcologyHerbivoreGeographyBiologyDemographyHabitatSociology

Abstract

fetched live from OpenAlex

Partial migration, a phenomenon wherein only some individuals within a population migrate, is taxonomically widespread. While well-studied in birds and fish, partial migration in large herbivores has come into the spotlight only recently due to the decline of migratory behavior in ungulate species around the world. We reviewed studies describing these trends to explore both population- and individual-level mechanisms for partial migration in ungulates. We addressed how density-dependent and -independent factors, alone or together, could maintain both migrants and residents within a population. We then searched for evidence that intrinsic and extrinsic factors could combine with genetic predispositions and individual differences in temperament or life experience to promote migratory tendencies of individuals. Despite the long-held assumption that migration is a fixed behavior of individuals, evidence suggested that changes in migratory behavior result from state-dependent responses of individuals. Data are needed to demonstrate empirically which factors determine the relative costs and benefits to using migratory versus resident tactics. We outline what types of long-term data could address this need and urge those studying migration to meet these challenges in the interest of conserving partially migratory populations.

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.

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 score0.035
Threshold uncertainty score0.188

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.003
GPT teacher head0.176
Teacher spread0.173 · 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