MétaCan
Menu
Back to cohort
Record W2059094525 · doi:10.2136/sssaj2004.6900

Carbon Accumulation and Storage in Mineral Subsoil beneath Peat

2004· article· en· W2059094525 on OpenAlexaff
Tim R. Moore, Jukka Turunen

Bibliographic record

VenueSoil Science Society of America Journal · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsMcGill University
Fundersnot available
KeywordsPeatSubsoilSoil waterDissolved organic carbonEnvironmental chemistrySorptionGeologyTotal organic carbonSoil scienceChemistryMineralogyEcology

Abstract

fetched live from OpenAlex

We showed that sandy subsoils beneath peat near Ramsey Lake, MI, contained 7.5 to 8.0 kg organic C (OC) m −2 to a depth of 70 cm, compared with 1.6 to 3.6 kg m −2 in adjacent forest soils, from which the peatland had evolved through paludification. Compared with the soils beneath the forest, those beneath the peat contained similar amounts of oxalate‐extractable Al (Al o ) and less Fe, owing to loss of Fe under reduced leached conditions beneath the peat. Most of the extractable Al in the mineral horizons beneath peat was organically bound. Atomic pyrophosphate‐extractable (Fe p + Al p ) Fe + Al/C ratios were smaller (<0.2:1) in the mineral horizons beneath peat than in the forest mineral subsoils (generally >0.2:1), indicating larger inputs and retention in the mineral subsoils beneath peat. Concentration of OC in subsoil samples was strongly ( r 2 = 0.58, p < 0.001) related to the subsoil Al, null‐point dissolved organic C (DOC) and clay concentrations. A DOC sorption study using peat pore water ranging from 0 to 117 mg DOC L −1 revealed null‐point DOC (DOC np ) concentrations (at which there is neither gain nor loss of OC by the soil) varied from <1 to 417 mg DOC L −1 and was primarily related to Fe o (negatively), Al o (negatively), and C (positively). We suggest that the increase in mineral subsoil OC beneath peat is related to the sorption of DOC carried by pore water percolating through the mineral subsoil, combined with slow rates of mineralization of sorbed DOC under anoxic conditions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.089
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.012
GPT teacher head0.251
Teacher spread0.239 · 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 teacher head, 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

Citations45
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueSoil Science Society of America JournalSame topicPeatlands and Wetlands EcologyFrench-language works237,207