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Record W2120452851 · doi:10.14430/arctic4097

Connections between River Runoff and Limnological Conditions in Adjacent High Arctic Lakes: Cape Bounty, Melville Island, Nunavut

2011· article· en· W2120452851 on OpenAlexafffundvenueabout
K Stewart, Scott F. Lamoureux

Bibliographic record

VenueARCTIC · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaArcticNet
KeywordsSnowmeltSurface runoffHydrology (agriculture)Environmental scienceArcticProductivityWatershedStreamflowSnowOceanographyDrainage basinEcologyGeologyGeography

Abstract

fetched live from OpenAlex

Hydrological and hydrochemical monitoring of paired watersheds in the High Arctic was conducted in 2003–04 to investigate the influence of seasonal runoff on lake water chemistry and productivity. Despite similar limnological conditions overall between the two lakes, marked differences in aquatic productivity were attributed to watershed and basin morphology and the resultant influences on lake ice deterioration and growing season length. A switch from allochthonous to autochthonous sources of carbon late in the season reflected the simultaneous decline in river runoff and increase in aquatic productivity as the growing season progressed. However, low air temperatures and protracted snowmelt and ponding in the deeply incised channel of one river in 2003 led to greater solute accumulation in runoff that was discernable in hydrochemical profiles of that lake, even though runoff was greater in 2004. Notwithstanding, calculated nutrient fluxes were greater during the higher-flow year (2004), but mixing was impeded by underflow conditions in the lakes. Despite these differences, connections between river and lake water chemistry appeared weak even with marked seasonal changes in the volume of runoff. Our results highlight the interconnection between site-specific features and hydroclimatic factors like snowmelt and lake ice conditions in influencing limnological conditions and suggest that similar systems may respond differently to the same hydroclimatic conditions.

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 score0.295
Threshold uncertainty score0.978

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)0.0230.001

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 head0.051
GPT teacher head0.237
Teacher spread0.186 · 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

Citations23
Published2011
Admission routes4
Has abstractyes

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Same venueARCTICSame topicClimate change and permafrostFrench-language works237,207