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Record W4409536290 · doi:10.1016/j.catena.2025.109057

Nutrient inputs control the carbon sequestration efficiency of peatlands in the northern margins of the East Asian Summer Monsoon

2025· article· en· W4409536290 on OpenAlexaff
Mingming Zhang, John P. Smol, Wenkai Liu, Li Wang

Bibliographic record

VenueCATENA · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsQueen's University
FundersNational Natural Science Foundation of China
KeywordsEnvironmental scienceCarbon sequestrationPeatNutrientMonsoonHydrology (agriculture)GeologyClimatologyCarbon dioxideGeographyEcology

Abstract

fetched live from OpenAlex

The peatlands at the northern margins of the East Asian Summer Monsoon (EASM) are an important carbon pool for the global carbon cycle. However, the major factors that influence the carbon flux and carbon sequestration of these peatlands remains unclear. In this study, we investigate the carbon flux and carbon sequestration history of the Gangwayao peatland at the northern margins of the EASM to explore these issues. Macrofossil evidence indicates that this peatland developed from a fen to a bog over the past 4700 years. Carbon flux parameters, such as net carbon pool (NCP) representing the carbon sequestration potential, net carbon uptake (NCU) representing carbon input, net carbon release (NCR) indicating carbon loss and net carbon accumulation rate (NCAR) of this peatland were mainly controlled by nutrient inputs. Additionally, correlation analysis suggested that the NCU has significant impact on the NCAR and NCAR, further affecting the NCP. The NCU and NCAR were controlled by nitrogen and phosphorus inputs released by human activity and tephra deposition. The carbon sequestration modes in the study area can be identified as two types. The first type is a high carbon sequestration efficiency mode, when human activities and frequent volcanic eruptions provided nutrients such as nitrogen and phosphorus, which promoted the high productivity of peat vegetation and the high carbon sequestration efficiency of the peatland. The second type is a low carbon sequestration efficiency mode, when fewer nutrient additions from human activities resulted in low productivity of peat vegetation and the low carbon sequestration efficiency of the peatland. These results extend our understanding of the connections between human activity, volcanic activity and carbon sequestration in peatlands, which provide a foundation for future predictions of the carbon sequestration potential of peatlands at the northern margins of the EASM.

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)0.000
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 score0.023
Threshold uncertainty score0.264

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.007
GPT teacher head0.209
Teacher spread0.202 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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