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Record W4408436198 · doi:10.5194/egusphere-egu25-7822

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

2025· preprint· en· W4408436198 on OpenAlexaffabout
Fares Mandour, Jazmin Greyeyes-Howell, Renae Shewan, Lauren Thompson, Mike Low, Matthew Munson, Ryan Connon, David Olefeldt

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsGovernment of Northwest TerritoriesMarch of Dimes CanadaAssembly of First NationsUniversity of Alberta
Fundersnot available
KeywordsPeatPermafrostEnvironmental scienceBiogeochemistryBorealWater qualityClimate changeDissolved organic carbonHydrology (agriculture)NutrientWatershedEcosystemEcologyEnvironmental chemistryGeologyChemistry

Abstract

fetched live from OpenAlex

Permafrost thaw, wildfires, and increased amplitude of floods and droughts are all aspects of climate change that risk affecting the downstream mobilization of dissolved organic carbon (DOC), the neurotoxin methylmercury (MeHg), and various nutrients from boreal peatlands. In this study, we monitored water chemistry at the outflow of eighteen peatland-rich catchments (125 – 1700 km2) across a climate gradient in boreal western Canada. Our study included a wetter year (2022) and two extreme drought years (2023 and 2024) which also resulted in extensive fires that affected nine of the watersheds in 2023. Flood conditions in 2022 resulted in high hydrological connectivity, particularly in comparison to 2023 and 2024, where drought conditions coupled with extensive wildfires limited connectivity and combusted existing carbon stores. This reduced the mobilization of the co-transported MeHg in streams during the drought years, as well as resulting in no observable effects of the wildfires overall on water chemistry due to this limited connectivity within the peatlands.Peatlands, covering over 30% of the Dehcho Region and Hay River watershed, are likely the primary source of these deleterious solutes due to the biogeochemistry of anoxic waterlogged soils. The goals of this monitoring program were developed collaboratively with the Dene Tha’, K'atl'odeeche, and Dehcho First Nations; their perspectives have been critical for this project. Community members expressed concerns about declining water quality potentially related to climate change, and the associated impacts on ecosystem health and fish resources. To assess the temporal variability of water quality, we studied four creeks with similar catchment sizes and peatland extent along a permafrost gradient using in-situ field sensors and grab samples. Additionally, a Before-After-Control-Impact methodology was used to evaluate the impacts of wildfires on water quality in eighteen streams along a permafrost gradient to assess northern vulnerability. Previous research has observed that peatlands in the discontinuous permafrost zone have poorer hydrological connection to the stream network compared to peatlands south of the permafrost boundary, resulting in higher solute concentrations in the southern region extent. Higher flow conditions during the spring resulted in minor peaks in MeHg and DOC concentrations, with decreasing concentrations as freshet ended. However, warmer temperatures that accelerate microbially associated DOC and MeHg generation resulted in the highest annual concentrations, despite extreme drought conditions that should’ve limited surface water sourcing.Understanding the interactive impacts of permafrost conditions, wildfire and inter-annual climate variability on water quality is essential for managing and protecting the health of northern communities, ecosystems, and food webs. This research provides vital data to inform decision-making, support the resilience of local First Nations, and guide effective environmental stewardship in the face of ongoing climate change. We believe our findings are likely representative of northern peatland-rich regions broadly and will thus be of great interest to understand the global impacts of permafrost thaw and wildfire on carbon and mercury cycling.

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 score0.058
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.235
Teacher spread0.221 · 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 routes2
Has abstractyes

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