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Record W2164429113 · doi:10.1139/z00-027

Geographic variation in population cycles of Canadian muskrats (<i>Ondatra zibethicus</i>)

2000· article· en· W2164429113 on OpenAlexvenueaboutno aff
John D. Erb, Nils Chr. Stenseth, Mark S. Boyce

Bibliographic record

VenueCanadian Journal of Zoology · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
FundersNorges ForskningsrådUniversitetet i Oslo
KeywordsVulpesTrophic levelBayBiologyArcticPopulationPredationPopulation densityEcologyPopulation cycleGeographyDemography

Abstract

fetched live from OpenAlex

We investigated the dynamic properties of population cycles in Canadian muskrats (Ondatra zibethicus). Ninety-one historic time series of muskrat-harvest data obtained from the Hudson's Bay Company Archives were analyzed. Most series were 25 years in length (1925–1949) and were distributed primarily throughout five ecozones. For each series, we estimated period length and coefficients for a second-order autoregressive model. Estimated period length varied between 3 and 13 years, with 3- to 5-year periods located in Subarctic-Arctic ecozones. We hypothesize that the 4-year cycles are largely a result of predation by red fox (Vulpes vulpes), which exhibit 4-year cycles in Arctic regions. The remaining ecozones generally averaged 8–9 years in period length. However, the relative contributions of direct and delayed density dependence varied along a latitudinal gradient. We hypothesize that both social and trophic interactions are necessary to produce the observed dynamics, but that shifts in the nature of mink predation were responsible for the changes in the relative contribution of direct and delayed density dependence. Essentially, there is a tension between population-intrinsic and trophic interactions that may bound the length of the cycle.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.116
Threshold uncertainty score0.234

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.008
GPT teacher head0.192
Teacher spread0.184 · 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 source (direct Gemma or distilled Codex), 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

Citations37
Published2000
Admission routes2
Has abstractyes

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