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Effects of soil erosion and deposition on soil organic carbon dynamics at a sloping field in Black Soil region, Northeast China

2010· article· en· W2142469542 on OpenAlexaff
Shulan Cheng, Huajun Fang, Tianhong Zhu, Jiaojiao Zheng, Xueming Yang, Xiaoping Zhang, Guirui Yu

Bibliographic record

VenueSoil Science & Plant Nutrition · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil erosion and sediment transport
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsSoil carbonErosionSoil scienceEnvironmental scienceSoil waterSoil organic matterDeposition (geology)Soil horizonBulk soilSedimentary depositional environmentGeologySedimentGeomorphology

Abstract

fetched live from OpenAlex

Abstract Soil erosion transports light density and fine particle soil material from hills down to low-lying land areas, which can lead to carbon loss and subsequent sequestration. In the present paper, the profile distribution of soil organic carbon (SOC) and soil 13C natural abundance (δ13C) were analyzed across five geomorphic positions, distributed along a typical rolling farmland in the Black Soil region of Northeast China. The contents of particulate organic carbon (POC) and mineral-associated organic carbon (MOC) at each geomorphic position were measured with physical fraction method. The results showed that soil erosion decreased 5.3–22.4% of SOC and increased 4.0–6.1% of δ13C of surface soils at the eroding sites. At the typical depositional sites, SOC content and δ13C value in the buried surface layer were 1.5 times and 1.1 times as much as those of the current plough layer, respectively. Soil erosion did not change the POC content, but MOC content decreased by 9.3–35.2%. At the eroding sites, the coefficient of determination between soil δ13C and MOC (R 2 = 0.52) was higher than that between soil δ13C and POC (R 2 = 0.37). Our study indicated that soil erosion decreased SOC content and increased δ13CSOC in surface layer mainly through transferring fine sized and 13C-depleted SOC fraction. Deep burial and re-aggregation of eroded materials at depositional sites were in favor of stabilization and sequestration of SOC.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.582
Threshold uncertainty score0.969

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.006
GPT teacher head0.184
Teacher spread0.178 · 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 designBench or experimental
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

Citations51
Published2010
Admission routes1
Has abstractyes

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