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Record W2131284209 · doi:10.1139/z02-143

Cyclic dynamics of snowshoe hares on a small island in the Yukon

2002· article· en· W2131284209 on OpenAlexafffundvenueabout
Charles J. Krebs, Todd N. Zimmerling, Claire M. Jardine, Kim A Trostel, Alice J. Kenney, Scott F. Gilbert, Elizabeth J. Hofer

Bibliographic record

VenueCanadian Journal of Zoology · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsYukon UniversityNorthwestern PolytechnicUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPredationSnowshoe hareMainlandBiologyEcologyJuvenilePopulationMainland ChinaZoologyGeographyDemography

Abstract

fetched live from OpenAlex

Snowshoe hare (Lepus americanus) populations were monitored from 1977 to 2001 on Jacquot Island (5 km 2 ) in Kluane Lake, southwestern Yukon, and on nearby mainland sites. Jacquot Island hares averaged twice the density of mainland control populations and, although they show 10-year cycles, fluctuate with much lower amplitude than mainland populations. Three separate intensive studies over 6 years attempted to determine what caused these differences. We tested two hypotheses to explain the dynamics. Reproductive rates of hares were similar on Jacquot Island and the mainland. Adult survival rates were higher on the island in most years, with the exception of years of population decline. Juvenile survival rates from 0 to 30 days of life were much higher on the island than on the mainland except for decline summers. The adult- and juvenile-survival differences between the island and the mainland were explained most consistently by predation. Improved survival on the island is correlated with a reduction in the numbers and types of predators found on Jacquot Island compared with the mainland. In particular, red squirrels were rare on Jacquot Island, arctic ground squirrels were absent, and the larger predators, like lynx and great-horned owls, were sporadic in occurrence on this small island.

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 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 score0.764
Threshold uncertainty score0.999

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)0.0020.000

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 head0.022
GPT teacher head0.210
Teacher spread0.188 · 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

Citations10
Published2002
Admission routes4
Has abstractyes

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