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Record W3097506628 · doi:10.1007/s10021-020-00577-6

Plant–Environment Interactions in the Low Arctic Torngat Mountains of Labrador

2020· article· en· W3097506628 on OpenAlexafffundabout
Emma L. Davis, Andrew J. Trant, Luise Hermanutz, Robert G. Way, Antoni G. Lewkowicz, Laura Siegwart Collier, Alain Cuerrier, Darroch M. Whitaker

Bibliographic record

VenueEcosystems · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversité de MontréalGovernment of Newfoundland and LabradorParks CanadaEspace pour la vieUniversity of OttawaQueen's UniversityMemorial University of NewfoundlandUniversity of WaterlooEnvironment and Climate Change Canada
FundersArcticNet
KeywordsPermafrostEcotoneClimate changeTundraVegetation (pathology)Environmental sciencePhysical geographyArcticSubarctic climateShrubContext (archaeology)Environmental changeSnowmeltSnowEcologyGeography

Abstract

fetched live from OpenAlex

Abstract The eastern Canadian Subarctic and Arctic are experiencing significant environmental change with widespread implications for the people, plants, and animals living there. In this study, we integrate 10 years of research at the Nakvak Brook watershed in Torngat Mountains National Park of Canada, northern Labrador, to assess the sensitivity of ecological and geomorphological systems to regional climate warming. A time series of the Normalized Difference Vegetation Index indicates that the area has undergone a significant greening trend over the past four decades. Analyses of shrub cross sections suggest that greening has been caused by a combination of rapid establishment and growth that began in the late 1990’s and coincided with warmer growing season temperatures. Recent (2010–2015) vegetation change has been subtle and heavily moderated by soil moisture status. Plant canopy height is greater in wet areas and has an insulating effect on ground surface temperatures during the winter, a consequence of snow trapping by shrub canopies. Observations of subsurface conditions indicate that the study site is best characterized as having discontinuous near-surface permafrost. The importance of subsurface conditions for above-ground vegetation depends on the geomorphological context, with plants in wet areas underlain by fine materials being the most likely to be growth-limited by permafrost, thus being potential hot-spots for future change. With the expectation of sustained climate change, loss of adjacent sea ice, and proximity to the forest-tundra ecotone, it is likely that the Torngat Mountains will continue to be an area of rapid environmental change in the coming decades.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score0.997

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)0.0050.001

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 head0.044
GPT teacher head0.224
Teacher spread0.180 · 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

Citations38
Published2020
Admission routes3
Has abstractyes

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