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Record W7106007111 · doi:10.7939/83022

Drought and permafrost thaw: interactive effects on dissolved organic carbon, mercury, and nutrients in peatland-rich watersheds of boreal western Canada

2025· dissertation· en· W7106007111 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2025
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsPermafrostHydrology (agriculture)Dissolved organic carbonBiogeochemical cycleWater qualityBiogeochemistrySurface runoffTaigaSTREAMSEcosystem

Abstract

fetched live from OpenAlex

Creeks and rivers are critical conduits of a myriad of solutes and are a representation of the catchment processes happening on the ecosystem scale. Changes in hydrological and permafrost conditions within the Taiga Plains have had significant impacts on water quality. Permafrost thaw as well as floods and droughts threaten to alter the downstream delivery of dissolved organic carbon (DOC) and the bound/co-transported neurotoxin methylmercury (MeHg), as well as various other solutes. While several studies have researched the influence of permafrost condition on water quality, the impact of hydrological conditions on water quality and biogeochemical dynamics remains unknown in the Taiga Plains. In this study, we sampled twenty-seven streams in the Northwest Territories and Alberta over a five-year period from 2020 – 2024 approximately monthly across a variety of permafrost and hydrological conditions, as well as four smaller creeks more intensively from 2023 – 2024. The objectives were to: 1) determine the impact of permafrost and hydrological conditions on water biogeochemistry, including the export of Hg, MeHg and DOC, 2) assess the vulnerability of different streams during floods and droughts with regard to permafrost thaw, catchment size, and wildfires, and 3) assess the dominating diel environmental processes within ecosystems during drought conditions with respect to DOM generation, degradation, and transportation. MeHg and DOC exhibited a flushing response during high flows, however this was only in watersheds with little to no permafrost. On average, MeHg and DOC concentrations in southern catchments significantly increased by 80% and 50%, respectively, when comparing concentrations at the 10th and 90th flow percentile, whilst colder, more northern catchments experienced zero change to increased discharge and responded chemostatically. Peatland compositional differences driven by increasing permafrost extent in more northern catchments likely acted to limit the production of MeHg and DOC, but more importantly limited the transportation of these solutes by fragmenting the landscape via permafrost peat plateaus, which inhibited water and subsequent solute mobility. On a diel scale, photic processes were the primary driver of diel patterns within streams across a permafrost gradient, with consistent photodegradation occurring of fluorescent dissolved organic matter (fDOM) during extensive drought periods. With daytime fDOM values being 2% - 8% lower than nighttime values, this indicates that significant mobilization of fDOM, and other strongly associated solutes such as MeHg (R2 = 0.57), is occurring during dark hours , with limited differences in diel magnitude between the creeks that were along a permafrost gradient. The diel patterns suggests that we may be systematically underestimating carbon and mercury export in the Taiga Plains, given typical daytime sampling regimes. The findings of this study further recognize the complexities of hydrological and permafrost condition on water quality and catchment biogeochemistry. As northern regions continue to face more landscape disturbances associated with climate change, continued monitoring is needed to inform management and future research directions to ensure traditional land use can occur safely.

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)0.001
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 score0.051
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.005
GPT teacher head0.174
Teacher spread0.169 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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