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Record W2763873481 · doi:10.1038/s41598-017-13658-9

Climate and permafrost effects on the chemistry and ecosystems of High Arctic Lakes

2017· article· en· W2763873481 on OpenAlexafffund
K. E. Roberts, Scott F. Lamoureux, Kurt Kyser, Derek C. G. Muir, Melissa J. Lafrenière, Debbie Iqaluk, Anna J. Pieńkowski, Alexandre Normandeau

Bibliographic record

VenueScientific Reports · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsGeological Survey of CanadaNatural Resources CanadaEnvironment and Climate Change CanadaMacEwan UniversityQueen's University
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les TechnologiesLinnean Society of LondonArcticNetQuaternary Research Association
KeywordsPermafrostArcticSalvelinusArctic charEnvironmental scienceEcosystemClimate changeThermokarstArctic ecologyOceanographyPrecipitationEcologyAquatic ecosystemPhysical geographyGlobal warmingHydrology (agriculture)GeologyFish <Actinopterygii>GeographyFisheryBiologyMeteorologyTrout

Abstract

fetched live from OpenAlex

Abstract Permafrost exerts an important control over hydrological processes in Arctic landscapes and lakes. Recent warming and summer precipitation has the potential to alter water availability and quality in this environment through thermal perturbation of near surface permafrost and increased mobility of previously frozen solutes to Arctic freshwaters. We present a unique thirteen-year record (2003–16) of the physiochemical properties of two High Arctic lakes and show that the concentration of major ions, especially SO 4 2− , has rapidly increased up to 500% since 2008. This hydrochemical change has occurred synchronously in both lakes and ionic ratio changes in the lakes indicate that the source for the SO 4 2− is compositionally similar to terrestrial sources arising from permafrost thaw. Record summer temperatures during this period (2003–16) following over 100 years of warming and summer precipitation in this polar desert environment provide likely mechanisms for this rapid chemical change. An abrupt limnological change is also reflected in the otolith chemistry and improved relative condition of resident Arctic char ( Salvelinus alpinus ) and increased diatom diversity point to a positive ecosystem response during the same period.

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)0.000
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 score0.016
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.019
GPT teacher head0.225
Teacher spread0.206 · 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

Citations67
Published2017
Admission routes2
Has abstractyes

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