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Record W4220755456 · doi:10.5194/egusphere-egu22-10953

Peatbogs to the rescue! Opportunities and challenges in using ombrotrophic peat cores for a reconstruction of paleo-storms during the Holocene in eastern Canada

2022· preprint· en· W4220755456 on OpenAlexaffabout
Antoine Lachance, Matthew Peros, Jeannine‐Marie St‐Jacques

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicCoastal wetland ecosystem dynamics
Canadian institutionsBishop's UniversityConcordia University
Fundersnot available
KeywordsOmbrotrophicPeatStormHoloceneGeologyOceanographyClimatologyPhysical geographyBogGeographyArchaeology

Abstract

fetched live from OpenAlex

Tropical cyclones and winter storms are pervasive dangers to coastal communities in eastern Canada and, under future climate change regimes, these extreme weather events are projected to increase. However, it remains challenging to establish the relationship between external forcing mechanisms, such as the North-Atlantic Oscillation (NAO) and the Atlantic Multidecadal Oscillation (AMO), and temporal variability of past storms on short timescales in this region. This is due to the scarce availability of and difficulty of producing high-resolution paleo-storm records. Here, we contribute to Northeast Atlantic paleo-storm research by showing how to leverage the advantages of using ombrotrophic peatlands in building a high-resolution paleo-storm reconstruction. Ombrotrophic peatlands receive water and minerals exclusively from atmospheric deposition and often accumulate sediments rapidly, making them excellent repositories of past storms. Our reconstruction is based on a multi-proxy analysis of two peat sequences of 3.25 m (TAC – Tourbière-de-l’Anse-à-la-Cabane) and 7.00 m (TLM – Tourbière-du-lac-Maucôque) that were recovered from two ombrotrophic peat bogs on Île du Havre-Aubert, the southernmost island of the Magdalen Islands archipelago, in eastern Canada. The samples cover the entire peat sequence, with the base of the cores ending in sediments of glacial or marine origin. The cores were dated by 14C and 210Pb.The bottommost peat sediments date to ~8500 BP for TLM and ~4200 BP for TAC, with mean accumulation rates of 10 years/cm and 20 years/cm, respectively. We used a combination of X-ray microfluorescence (μ-XRF) measurements, computerized-tomography density, and Aeolian Sand Influx (ASI) measurements to identify allochthonous material from the ocean and surrounding beaches and sandstone cliffs in the peat cores. Analyses show high frequency variability in bromine and chlorine, which we hypothesize to be associated to sea-spray, and in terrigenous elements (potassium, titanium, manganese, iron), which we hypothesize to be associated to surrounding beaches and cliff sediments. ASI variations in the core closely match variations in terrigenous elements. It is hypothesized that mineral particles were deposited in the peat bogs during extreme weather events; this is suported by short-term peaks in chemical elements and aeolian sand from the topmost portion of the core that are correlated to known extreme events from modern instrumental data. High frequency (decadal) variability seen in the elemental and aeolian sand data throughout the core could possibly result from variation in storminess. By applying a multi-proxy approach that combines μ-XRF geochemistry, density measurements, aeolian sand influx, and modern instrumental data on the full peat sequence, we were able to identify storm-derived materials with confidence while building a high-resolution paleo-storm reconstruction. With this data, we can establish the relationship between external forcing mechanisms and past storms.

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 score0.061
Threshold uncertainty score0.123

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.070
GPT teacher head0.232
Teacher spread0.162 · 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
Published2022
Admission routes2
Has abstractyes

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