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Record W2138605364 · doi:10.5558/tfc80598-5

Forest management guidelines for forest-dwelling caribou in Québec

2004· article· en· W2138605364 on OpenAlexaffvenueabout
Réhaume Courtois, Jean‐Pierre Ouellet, Claude Dussault, André Gingras

Bibliographic record

VenueThe Forestry Chronicle · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsMinistère des Ressources naturelles et des ForêtsUniversité LavalMinistère des Ressources naturelles et des Forêts (Québec)Université du Québec à Rimouski
Fundersnot available
KeywordsWoodland caribouHabitatForest managementGeographyForest ecologySnagEcologyTaigaOld-growth forestWildlifeBlack spruceSalvage loggingAgroforestryBiological dispersalEcosystemEnvironmental scienceForestryPopulationBiology

Abstract

fetched live from OpenAlex

The forest-dwelling ecotype of woodland caribou (Rangifer tarandus caribou) is vulnerable to predation, hunting, and disturbances due to anthropogenic activities. Its strategies of space and habitat use are oriented towards reducing the effects of these limiting factors. Caribou occupy large home ranges, undertake extensive movements, and avoid fragmented areas. They use various habitats, but especially mature and over-mature conifer stands with irregular structure, which are less suitable for other ungulates, wolves and black bears. In order to protect habitat for forest-dwelling caribou, we suggest an ecosystem approach based on the protection of large forested blocks, the concentration of forest harvesting in large management blocks, and the maintenance of habitat connectivity. This strategy focuses on short-term conservation of minimum caribou habitats in the protected blocks, a medium-term habitat recovery in the management blocks, the maintenance of forest activities, and facilitation of seasonal and dispersal movements. Within the management blocks, we recommend creation of an irregular forest structure similar to the pattern created by natural disturbances inherent to spruce-moss forests. These guidelines have been tested in Québec for the last few years and were well received by forest and wildlife agencies as well as the forest industry. Key words: adaptive management, boreal forest, ecosystem management, forest-dwelling ecotype, forest management, spruce forest, woodland caribou

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.481
Threshold uncertainty score0.990

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)0.0000.000

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 head0.027
GPT teacher head0.265
Teacher spread0.238 · 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

Citations43
Published2004
Admission routes3
Has abstractyes

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