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Record W3216183945 · doi:10.7939/r3-pjcm-aj83

Influence of permafrost characteristics on vegetation change in Yukon and Northwest Territories, Canada

2021· article· en· W3216183945 on OpenAlexaboutno aff
Nina S Vogt

Bibliographic record

VenueUniversity of Alberta Library · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsPermafrostVegetation (pathology)Physical geographyClimate changeGeologyGeographyOceanography

Abstract

fetched live from OpenAlex

Permafrost thaw is a significant contributor to landscape change and ecosystem disruption in northern systems. While previous studies have examined the impact of permafrost on vegetation change, few have investigated the connection of permafrost characteristics to the type and extent of vegetation change. Additionally, much of the literature investigating vegetation change due to permafrost thaw has been restricted to peatlands. This thesis investigates the impacts of permafrost thaw on vegetation characteristics and how permafrost characteristics may influence the type and severity of ecosystem change in the peatlands of Jean Marie River, Northwest Territories, and lowland boreal forests of the Whitehorse and Kluane regions of Southern Yukon, Canada. Ecological and geophysical field investigations were incorporated to examine how vegetation characteristics differ with permafrost thaw, how vegetation differences may indicate permafrost thaw, and what this may tell us about landscape transition and the availability of habitat for characteristic boreal species post-thaw. I hypothesized that post-thaw vegetation would shift to species supported by moister conditions and that permafrost characteristics would be linked to the type and extent of vegetation change. I further hypothesized that such changes could result in qualitative differences in the amount and distribution of future habitat available to woodland caribou (Rangifer tarandus tarandus) in these regions. Ecosystems and permafrost conditions varied considerably across the three study areas in Jean Marie River, Greater Whitehorse, and Kluane. However, with permafrost degradation, vegetation across all study sites shifted from species supported by drier, intact permafrost conditions to those supported in wetter environments. In general, there was a loss of characteristic boreal forest species, including lichens (Cladina, Cladonia, Cetraria), berries (Vaccinium vitis-idaea, Empetrum nigrum, Shepherdia canadensis), and forbs (Lupinus arcticus, Galium boreale), as well as loss of forest cover. Both permafrost characteristics and surrounding ecosystems influenced the shift of species. Type and severity of vegetation and ecosystem change appear to be linked to permafrost characteristics. Qualitative assessment suggests substantive implications from permafrost thaw for the amount and distribution of important seasonal habitats for woodland caribou in these systems, with related considerations of landscape connectivity for both boreal and northern mountain populations. This research fills a critical knowledge gap in how ecosystems in northwestern Canada may transition with permafrost thaw and helps reduce uncertainties concerning potential landscape change associated with climate change.

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)0.001
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 score0.017
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.170
Teacher spread0.159 · 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
Published2021
Admission routes1
Has abstractyes

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