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Record W4360991760 · doi:10.1139/as-2022-0036

Greening on the Bathurst caribou range in northern Canada: are erect shrubs responsible for remotely sensed trends?

2023· article· en· W4360991760 on OpenAlexafffundvenueabout
Carolyn Bonta, Gregory King, Ryan K. Danby

Bibliographic record

VenueArctic Science · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of AlbertaQueen's University
FundersQueen's UniversityCanadian Federation of University WomenUniversity of AlbertaWeston Family FoundationPolar Knowledge Canada
KeywordsGreeningShrubDeciduousVegetation (pathology)TundraProductivityRange (aeronautics)GeographyEcologyPhysical geographySubarctic climatePopulationEnvironmental scienceEcosystemBiologyDemography

Abstract

fetched live from OpenAlex

Remote sensing has detected recent trends of increased vegetation productivity on the Bathurst caribou herd’s range. The cause of this spectral greening is unknown but is hypothesized to be the result of a change in the composition, establishment, structure, and/or growth of erect deciduous shrubs. We combined field investigation and dendroecology to compare shrubs between areas where productivity has increased (Greening sites) and areas where productivity has remained stable (No Change sites) based on a Moderate Resolution Imaging Spectroradiometer time series for the period from 2000 to 2017. Contrary to expectations, species composition, timing of stem establishment, stem density, stem length, and vertical and diameter growth rates did not differ between the two site types. However, shrub cover was 13% greater at Greening sites and shrubs at No Change sites had 9% more dead stems regardless of the size of the shrub. This suggests that the differences observed remotely are due to a combination of increased foliage production or survival at Greening sites and a dimming of the vegetation index at No Change sites. Our findings offer a population-level validation of specific shrub characteristics contributing to trends in spectral greening in an understudied region of the southern Arctic tundra.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.299
Threshold uncertainty score0.439

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.078
GPT teacher head0.260
Teacher spread0.182 · 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

Citations3
Published2023
Admission routes4
Has abstractyes

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