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Record W4408431948 · doi:10.5194/egusphere-egu25-12881

Holocene development and recent vegetation and carbon storage dynamics in polygonal permafrost peatlands of the Hudson Bay Lowlands, Canada

2025· preprint· en· W4408431948 on OpenAlexaffabout
Tiina H. M. Kolari, Frédéric Bouchard, Alison Cassidy, Adam Collingwood, Lucile Cosyn Wexsteen, Jason Duffe, Sylvain Ferrant, Laure Gandois, Nicole K. Sanderson, Michelle Garneau

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsEnvironment and Climate Change CanadaParks CanadaUniversité de SherbrookeUniversité du Québec à Montréal
Fundersnot available
KeywordsPeatHolocenePermafrostBayVegetation (pathology)Physical geographyGeologyOceanographyClimatologyGeographyArchaeology

Abstract

fetched live from OpenAlex

The Hudson Bay Lowlands peatland complex in Canada, the world’s second-largest peatland complex, is experiencing the impacts of climate change, potentially threatening its carbon sink capacity; however, the direction and magnitude of recent changes are uncertain, particularly in response to ongoing permafrost thaw, climate change, and isostatic rebound. In this project, we aim to document the vegetation changes and carbon (C) storage dynamics, in both the long- (millennial) and short-term (decadal to centennial), of polygonal permafrost peatlands in Wapusk National Park (WNP), located on the northwestern coast of Hudson Bay.First, we aim to estimate the total C stored in peatlands in WNP and study the Holocene development history of polygonal permafrost peatlands. During 2023–2024, we collected twenty complete peat cores across the different land cover types and ecoregions within WNP. The twenty peat cores will be dated with radiocarbon (14C) and analyzed for total organic C. The peat cores collected from permafrost peat plateaus will also be examined for paleoecological and palaeoclimatological reconstructions, providing insights into major shifts in plant communities, climate, and permafrost dynamics during the Holocene. Preliminary results show that in WNP, peatland initiation and C accumulation connect to undergoing isostatic rebound. Peat accumulation began ca. 5705 cal. BP in the forest-tundra region and 2390 cal. BP in the coastal fen ecoregion. Permafrost peat plateaus store approximately 80.7 kg C m-2, with an average long-term apparent rate of carbon accumulation (LORCA) of 26.1 g C m-2 yr-1. At several sites, spruce and larch forests preceded contemporary, lichen-dominated peat plateaus.Second, we will explore why the numerous ponds within the permafrost peatlands are now being infilled by Sphagnum mosses, the most important genus for storing C as peat, and whether this is linked to recent permafrost thaw. Twenty surface peat monoliths were collected along transects at the edges of seven ponds and will be dated with coupled 14C and lead-210 (210Pb) age-depth modeling and analyzed for total organic C, plant macrofossils, and diatom communities. Preliminary results from plant macrofossil analyses indicate infilling and a subsequent increase in Sphagnum cover over fen vegetation rather than thawing-induced subsidence of permafrost peat plateaus. However, this may differ between ecoregions (forest-tundra vs. subarctic peat plateau region), and the timing of the transitions from moss-sedge to Sphagnum peat will be verified with age-depth modeling and remote sensing techniques. These early results show that vegetation changes along the pond edges can significantly affect peatland C accumulation.

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 score0.055
Threshold uncertainty score0.111

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 science0.0010.000
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 head0.016
GPT teacher head0.210
Teacher spread0.194 · 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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