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Record W4407972294 · doi:10.1016/j.ejrh.2025.102253

Widespread pH increase and geochemical trends in fifty boreal lakes: Evidence, prediction and plausible attribution to climate and permafrost thaw impacts across northeastern Alberta

2025· article· en· W4407972294 on OpenAlexafffundabout
J. J. Gibson, Adrian Jäggi, Francisco Castrillon-Munoz

Bibliographic record

VenueJournal of Hydrology Regional Studies · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaInnotech AlbertaAlberta Environment and Parks
KeywordsPermafrostBorealPhysical geographyAttributionEnvironmental scienceTaigaClimate changeGeographyClimatologyGeologyOceanographyForestryArchaeologyPsychology

Abstract

fetched live from OpenAlex

Study region This study focuses on 50 boreal lakes and catchments situated in northeastern Alberta, Canada between 55.68°N – 59.72°N and 110.02°W – 115.46°W. Study focus Evidence for trends in chemical composition of lakes, including pH increases are provided using Mann-Kendall statistics, geochemical modelling, δ 18 O, δ 2 H, and δ 13 C, which are compared to trend statistics for climate, water balance, and groundwater indicators. New hydrological insights for the region Groundwater contributions are generally found to be increasing with water yield and carbon inputs as sites advance along the thaw trajectory. The exception to this is shield lakes which continue to be surface water dominant. Statistical analyses suggest widespread trends, both significant and non-significant, in geochemical parameters across the lake network including pH increases in 46 of 50 lakes. In shale-dominated plateau areas, pH trends are adequately described by changes in HCO 3 - , attributed mainly to carbon input associated with permafrost thaw. For these lakes, prediction improves little if other variables are considered, whereas for post thaw areas, prediction of pH trends improves if water yield trends are also considered. In sub-regions with appreciable carbonate, pH trend prediction improves significantly if values of δ 13 C DIC and Dissolved Inorganic Carbon (DIC) are also considered. We postulate that recent pH trends across the region may only be temporary and that lake acidification may yet occur once permafrost thaw and related carbon imports diminish.

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 score0.137
Threshold uncertainty score0.875

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.049
GPT teacher head0.322
Teacher spread0.272 · 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

Citations4
Published2025
Admission routes3
Has abstractyes

Explore more

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