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Record W4321995178 · doi:10.5194/egusphere-egu23-9683

Ecohydrological and geological controls on contaminant reservoirs in degrading permafrost peatlands

2023· preprint· en· W4321995178 on OpenAlexaffabout
Jennifer M. Galloway, Mariusz Gałka, Graeme T. Swindles, Michael Parsons, Liam Taylor, Omid H. Ardakani, S A Wolfe, Peter Morse, Matt Amesbury, R. Timothy Patterson, Hendrik Falck, Michael J. Palmer

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsGovernment of Northwest TerritoriesCarleton UniversityGeological Survey of Canada
Fundersnot available
KeywordsPermafrostPeatThermokarstBedrockEarth scienceGeologyTundraVegetation (pathology)HoloceneEnvironmental sciencePhysical geographyMireSphagnumHydrology (agriculture)WeatheringSubarctic climateGeochemistryArcticGeomorphologyEcologyOceanography

Abstract

fetched live from OpenAlex

Peatlands are important sinks and/or sources of carbon, solutes, and elements of potential concern (e.g., Hg, As, Pb, Cu, Zn) to their surrounding environments. Minerogenic permafrost peatlands that receive input of elements from groundwater and weathering of bedrock and surficial materials accumulate substantial amounts of geogenic-derived elements over millennia, which are then frozen in place. As the Arctic cryosphere thaws due to 21st. c climate warming, understanding of permafrost contaminant reservoirs and tracking their release is a growing challenge due to a lack of knowledge on the cumulative and interacting influences of bedrock and surficial geology, vegetation, climate, fire, and ecohydrology on contaminant accumulation in permafrost peatlands. We examined the Holocene history of two permafrost peatlands from the Northwest Territories, Canada, that are underlain by mineralized volcanic and metasedimentary (Daigle Lake peatland) and unmineralized granitoid (Handle Lake peatland) bedrock. Laboratory methods included pyrolytic speciation to determine the quality and quantity of solid organic matter; plant macrofossil and macroscopic charcoal analysis to reconstruct vegetation, peatland development, and fire history; testate amoebae to reconstruct paleohydrological conditions; and inorganic geochemical analyses to determine elemental concentration over time. Both sites have undergone several marked and broadly coincident hydrological shifts and phases of ecohydrological development. During the early Holocene (ca. 8000-5000 cal BP) initial shallow lake environments at both sites transitioned to rich fen and were colonized by Picea. Elevated concentrations of Zn (up to 65 mg.kg-1), Cu (up to 52 mg.kg-1), As (up to 140 mg.kg-1), and Cr (up to 65 mg.kg-1) occur in the basal lacustrine sediments, particularly at the Daigle Lake peatland that is underlain by mineralized bedrock, but become lower in overlying material that accumulated in a fen setting. Depth to water table increased by almost 30 cm in the Handle Lake peatland between ca. 5900 and 4900 cal BP, coincident with the Holocene Thermal Maximum. At this time, local fires were severe and frequent at both sites and associated with elevated Hg (up to 50 µg.kg-1) in the peat. After this dry interval, the water table rose at ca. 3000 cal BP at the Handle Lake peatland and by ca. 2200 cal BP at the Daigle Lake peatland. Fire occurrence declined, coincident with the relatively cool and wet conditions of the Neoglacial interval. A bog was established at both sites between ca. 2700 and 2200 cal BP. Fire occurrence and the concentration of Hg (up to 175 µg.kg-1), As (up to 300 mg.kg-1), and Zn (up to 50 mg.kg-1) have increased over the past 1000 cal yrs, likely due to a combination of anthropogenic input of As and Hg associated with gold mining in the region and global industrialization as well as warming climate and permafrost thaw. This study illustrates the influence of ecohydrology and bedrock geology on the chemical stores of permafrost peatlands.

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 score0.172
Threshold uncertainty score0.342

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.095
GPT teacher head0.280
Teacher spread0.184 · 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
Published2023
Admission routes2
Has abstractyes

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