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Record W2174914845 · doi:10.1579/0044-7447-33.8.482

Long-term Interactions between Migratory Caribou, Wildfires and Nunavik Hunters Inferred from Tree Rings

2004· article· en· W2174914845 on OpenAlexaffabout
Serge Payette, Stéphane Boudreau, Claude Morneau, Nadia Pitre

Bibliographic record

VenueAMBIO · 2004
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsTundraWoodland caribouGeographyTramplingBorealEcologyTaigaArcticRange (aeronautics)Physical geographyForestryPredationBiologyGrazing

Abstract

fetched live from OpenAlex

Barren-ground caribou (Rangifer tarandus) herds in North America may reach considerable size and undertake large-scale seasonal migrations from the Arctic tundra to the boreal forest. To test the caribou decline hypothesis associated with native harvesting and fire, we have documented the long-term trends of caribou activity based on a novel approach which uses tree-ring dated trampling scars produced by caribou hooves in the extensive trails distributed over the summer and winter ranges of the Rivièreaux-Feuilles herd (RAF herd, east of Hudson Bay in northern Quebec). The age structure data of trampling scars from lichen woodlands distributed over the entire RAF range confirmed the overall trends of caribou activity from the late 1700s to present time. Over the last 200 years, the RAF herd has undergone two highs in the late 1700s and 1900s separated by a moderate activity pattern in the late 1800s. Native harvesting was possibly involved in the early 1900s decline, although at a moderate level. The reduced magnitude of caribou activity during this period has not modified the natural cycle of highs and lows, which suggests that other demographic factors were controlling the changing caribou abundance. Our data also show that only exceptionally large fires may have a minor, short-lived impact on caribou migrations but not on caribou numbers.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
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 studies0.0020.000
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 head0.036
GPT teacher head0.364
Teacher spread0.328 · 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

Citations27
Published2004
Admission routes2
Has abstractyes

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Same venueAMBIOSame topicIndigenous Studies and EcologyFrench-language works237,207