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Record W3128476734 · doi:10.1038/s41598-021-82234-z

Water column gradients beneath the summer ice of a High Arctic freshwater lake as indicators of sensitivity to climate change

2021· article· en· W3128476734 on OpenAlexafffundabout
Paschale Noël Bégin, Yukiko Tanabe, Milla Rautio, Maxime Wauthy, Isabelle Laurion, Masaki Uchida, Alexander I. Culley, Warwick F. Vincent

Bibliographic record

VenueScientific Reports · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsInstitut National de la Recherche ScientifiqueUniversité du Québec à ChicoutimiBio-K+ International (Canada)Université LavalCenter for Northern Studies
FundersFonds de recherche du Québec – Nature et technologiesMinistry of Education, Culture, Sports, Science and TechnologyCanada First Research Excellence FundArcticNetSentinelle Nord, Université LavalNatural Sciences and Engineering Research Council of CanadaInternational Arctic Science CommitteeParks Canada
KeywordsWater columnArcticEnvironmental scienceClimate changeOceanographyThe arcticClimatologySensitivity (control systems)Arctic ice packPhysical geographyGeologyHydrology (agriculture)Geography

Abstract

fetched live from OpenAlex

Ice cover persists throughout summer over many lakes at extreme polar latitudes but is likely to become increasingly rare with ongoing climate change. Here we addressed the question of how summer ice-cover affects the underlying water column of Ward Hunt Lake, a freshwater lake in the Canadian High Arctic, with attention to its vertical gradients in limnological properties that would be disrupted by ice loss. Profiling in the deepest part of the lake under thick mid-summer ice revealed a high degree of vertical structure, with gradients in temperature, conductivity and dissolved gases. Dissolved oxygen, nitrous oxide, carbon dioxide and methane rose with depth to concentrations well above air-equilibrium, with oxygen values at > 150% saturation in a mid-water column layer of potential convective mixing. Fatty acid signatures of the seston also varied with depth. Benthic microbial mats were the dominant phototrophs, growing under a dim green light regime controlled by the ice cover, water itself and weakly colored dissolved organic matter that was mostly autochthonous in origin. In this and other polar lakes, future loss of mid-summer ice will completely change many water column properties and benthic light conditions, resulting in a markedly different ecosystem regime.

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)0.000
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 score0.419
Threshold uncertainty score0.833

Distilled classifier scores by category (both heads)

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

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 head0.014
GPT teacher head0.208
Teacher spread0.194 · 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

Citations27
Published2021
Admission routes3
Has abstractyes

Explore more

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