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Record W7097860184

Trophic Dynamics of the Boreal Forests of the Kluane Region

2014· article· en· W7097860184 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSnowshoe harePredationTaigaHerbivoreTrophic levelMicrotusHabitatArcticTrophic cascade
DOInot available

Abstract

fetched live from OpenAlex

ABSTRACT. The trophic dynamics of the Yukon boreal forest have been under investigation at the Kluane Lake Research Station since 1973. We monitored and conducted experiments on the major species in this ecosystem, except the large mammals (for logistic reasons). The central problem has been to determine the causes of the 9 – 10 year cycle of snowshoe hares, and to achieve this we carried out several large-scale experiments manipulating food supplies, predator pressure, and soil nutrient availability to test hypotheses that food, predation, or habitat quality regulate populations. The hare cycle is driven top-down by predators, and most hares die because they are killed by predators. Predators also cause stress in female hares, and the stress response seems to be responsible for the loss of reproductive potential in the decline and low phases of the hare cycle. Many of the specialist predators and some herbivores in this ecosystem fluctuate with the hare cycle. Arctic ground squirrels do, but red squirrels do not, being linked closely to white spruce seed masting years. Small rodents fluctuate in numbers in two patterns. Red-backed voles and four species of Microtus voles have a 3 – 4 year cycle that seems to be driven by food supplies and social behaviour. Deer mice, in contrast, have fluctuated dramatically in the 38 years we have monitored them, but not cyclically. White spruce seed production varies with temperature and rainfall, but was not affected by adding nutrients in fertilizer. Global warming and reduced hare browsing in the last 20 years have helped to increase the abundance of shrubs in these forests. It will be challenging to predict how this system will change as climatic warming proceeds, because even closely related species in the same trophic level respond differently to perturbations. We recommend continued monitoring of the

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)0.000
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 score0.956
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.208
Teacher spread0.200 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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