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Record W2100465167 · doi:10.5194/esd-1-1-2010

A new model of Holocene peatland net primary production, decomposition, water balance, and peat accumulation

2010· article· en· W2100465167 on OpenAlexafffundabout
Steve Frolking, Nigel T. Roulet, Eeva‐Stiina Tuittila, Jill L. Bubier, Anne Quillet, Julie Talbot, P. Richard

Bibliographic record

VenueEarth System Dynamics · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsUniversité de MontréalCenter for Diagnosis and Research on Alzheimer's DiseaseUniversité du Québec à MontréalMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Foundation for Climate and Atmospheric SciencesAcademy of FinlandUniversité du Québec à MontréalNational Science Foundation
KeywordsPeatWater tablePrimary productionHoloceneEnvironmental scienceWater balanceHydrology (agriculture)BogGeologySoil scienceGroundwaterEcosystemEcologyOceanography

Abstract

fetched live from OpenAlex

Abstract. Peatland carbon and water cycling are tightly coupled, so dynamic modeling of peat accumulation over decades to millennia should account for carbon-water feedbacks. We present initial results from a new simulation model of long-term peat accumulation, evaluated at a well-studied temperate bog in Ontario, Canada. The Holocene Peat Model (HPM) determines vegetation community composition dynamics and annual net primary productivity based on peat depth (as a proxy for nutrients and acidity) and water table depth. Annual peat (carbon) accumulation is the net balance above- and below-ground productivity and litter/peat decomposition – a function of peat hydrology (controlling depth to and degree of anoxia). Peat bulk density is simulated as a function of degree of humification, and affects the water balance through its influence on both the growth rate of the peat column and on peat hydraulic conductivity and the capacity to shed water. HPM output includes both time series of annual carbon and water fluxes, peat height, and water table depth, as well as a final peat profile that can be "cored" and compared to field observations of peat age and macrofossil composition. A stochastic 8500-yr, annual precipitation time series was constrained by a published Holocene climate reconstruction for southern Québec. HPM simulated 5.4 m of peat accumulation (310 kg C m-2) over 8500 years, 6.5% of total NPP over the period. Vascular plant functional types accounted for 65% of total NPP over 8500 years but only 35% of the final (contemporary) peat mass. Simulated age-depth and carbon accumulation profiles were compared to a radiocarbon dated 5.8 m, c.9000-yr core. The simulated core was younger than observations at most depths, but had a similar overall trajectory; carbon accumulation rates were generally higher in the simulation and were somewhat more variable than observations. HPM results were sensitive to century-scale anomalies in precipitation, with extended drier periods (precipitation reduced ∼10%) causing the peat profile to lose carbon (and height), despite relatively small changes in NPP.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.530
Threshold uncertainty score0.945

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.007
GPT teacher head0.215
Teacher spread0.208 · 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 designSimulation or modeling
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

Citations282
Published2010
Admission routes3
Has abstractyes

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