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Record W3104366882 · doi:10.2981/wlb.00736

Patterns of decadal, seasonal and daily visitation to mineral licks, a critical resource hotspot for mountain goats <i>Oreamnos americanus</i> in the Rocky Mountains

2020· article· en· W3104366882 on OpenAlexafffundabout
Laura P. Kroesen, David S. Hik, Seth G. Cherry

Bibliographic record

VenueWildlife Biology · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsParks CanadaSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaSimon Fraser UniversityParks Canada
KeywordsHome rangeGeographyEcologyHabitatPopulationRange (aeronautics)BiologyDemography

Abstract

fetched live from OpenAlex

Concentrated resources or hotspots, within an individual's usual home range may be strong determinates of movement behavior. We evaluated the patterns of mineral lick use by a population of mountain goats Oreamnos americanus displaying high site fidelity at two mineral licks along the Trans‐Canada Highway in the Rocky Mountains, British Columbia, Canada. Access to these mineral licks was characterized by deliberate and repetitive movements into marginal habitat. We describe the patterns of mineral lick use over decadal, seasonal and daily periods by using dendrochronological analysis of trampling scars along mountain goat trails, movements determined from GPS collar locations, and camera traps placed along trails and at mineral licks, respectively. Our findings suggest that mountain goats have strong trans‐generational behavioral traditions and that they predictably access mineral licks using the same trails, seasons and daily patterns. Differences in the patterns of mineral lick visitation between males and females may be related to reproductive and nutritional status, while their nocturnal use appears to be a response to disturbance at the mineral licks. Understanding how animals adjust their behavior in response to highly localized resource hotspots outside their usual home range can provide valuable information for the management of these critical habitat features and the wider conservation of mountain goat 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.

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)0.001
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 score0.023
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.016
GPT teacher head0.269
Teacher spread0.253 · 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

Citations13
Published2020
Admission routes3
Has abstractyes

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