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Record W2131477786 · doi:10.7557/2.25.4.1777

Climate change and woodland caribou in Northwestern Ontario: a risk analysis

2005· article· en· W2131477786 on OpenAlexaffabout
G. D. Racey

Bibliographic record

VenueRangifer · 2005
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsMinistry of Natural Resources and Forestry
Fundersnot available
KeywordsWoodland caribouClimate changeForest managementGeographyWoodlandLoggingForest restorationAgroforestryEcologyEnvironmental scienceForest ecologyEnvironmental resource managementEcosystemForestryHabitatBiology

Abstract

fetched live from OpenAlex

Woodland caribou (Rangifer tarandus caribou) range occupancy and populations have declined in northwestern (NW) Ontario over the last 100 years primarily due to human-induced factors. Recovery efforts are underway to halt this decline by reducing risk factors. Climate forecasts suggest a 4—5 oC increase in May—August mean temperature over the next century with little change in precipitation. Resulting increases in extreme weather events and increased fire weather severity will likely increase the amount of forest burned, reduce the area of older forest, alter distribution and abundance of forest tree species and plant communities, and increase abundance of alternate prey. The reduced amount of older forest preferred by caribou will be in greater demand by the forest industry leading to more conflict over ecological and economic values. Most of these factors will increase risk to caribou survival. Although forests may experience enhanced productivity, forest management practices will try to adapt harvest, regeneration, silviculture and fire management practices to both maintain economic benefits and increase the ability of forests to sequester carbon. The interaction of climate-induced forest change and forest management practices adds uncertainty to caribou conservation efforts at the southern edge of its current range. This uncertainty reinforces the need for a precautionary approach to forest management, increased research and monitoring effort, sustained emphasis on caribou recovery, and careful rationalization of restoration efforts where greatest opportunities for success may be realized.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score0.864

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 studies0.0010.000
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 head0.039
GPT teacher head0.334
Teacher spread0.295 · 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

Citations12
Published2005
Admission routes2
Has abstractyes

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