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Record W2147619265 · doi:10.1088/1748-9326/9/2/024003

The cascade of C:N:P stoichiometry in an ombrotrophic peatland: from plants to peat

2014· article· en· W2147619265 on OpenAlexaffabout
Meng Wang, Tim R. Moore, Julie Talbot, Pierre J. H. Richard

Bibliographic record

VenueEnvironmental Research Letters · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsUniversité de MontréalMcGill University
Fundersnot available
KeywordsPeatOmbrotrophicBogBiogeochemistryEcological stoichiometryPhosphorusNutrientBiogeochemical cycleBotanyEnvironmental chemistryChemistryLitterAnimal scienceBiologyAgronomyEcology

Abstract

fetched live from OpenAlex

Northern peatlands are important carbon (C) sinks and while the patterns of C accumulation have been frequently investigated, nitrogen (N) and phosphorus (P) accumulation are often neglected. Here we link the C:N:P stoichiometry from foliar plant tissues, through senescent litters to peat, and determine C, N and P accumulation rates at Mer Bleue Bog, eastern Canada. Average C:N:P ratios changed from 794:17:1 in the foliar tissues to 911:10:1 in litter and 1285:32:1 in acrotelm peat. The increase in C:N and C:P ratios from mature to senescent tissues is related to nutrient resorption. The increase in C:P and N:P ratios in peat, which was contrary to that observed in Canadian forest soils, may be related to plant/mycorrhizae uptake of P. The longterm apparent rates of C, N and P accumulation were 29:5±2:1 (SE) g C, 0:87±0:01 g N and 0:017±0:002 g P m-2yr-1, respectively. The significant correlation between the accumulation rates of N and P and that of C suggests more attention be placed on C:N:P stoichiometry in peatland biogeochemistry, in particular in understanding why C:P ratios are so large in the lower parts of the profile.

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 score0.257
Threshold uncertainty score0.717

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.019
GPT teacher head0.284
Teacher spread0.265 · 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

Citations68
Published2014
Admission routes2
Has abstractyes

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