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Record W2789839203 · doi:10.1139/cjss-2017-0127

Soil organic matter dynamics in long-term temperate agroecosystems: rotation and nutrient addition effects

2018· article· en· W2789839203 on OpenAlexafffundvenueabout
Jichen Li, Guillermo Hernandez‐Ramirez, Mina Kiani, Sylvie A. Quideau, Elwin G. Smith, H. H. Janzen, Francis J. Larney, Dick Puurveen

Bibliographic record

VenueCanadian Journal of Soil Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of LethbridgeUniversity of Alberta
FundersUniversity of Alberta
KeywordsAgroecosystemSoil organic matterEnvironmental scienceCrop rotationOrganic matterAgronomySoil carbonSoil qualitySoil waterNutrientMicrobial population biologyBiomass (ecology)Temperate climateSoil scienceEcologyCropBiologyAgriculture

Abstract

fetched live from OpenAlex

Soil organic matter (SOM) is a major driver of key agroecosystem functions. Our objective was to examine the dynamics of organic matter in whole soil, particulate (POM; >53 μm size), and mineral-associated (MAOM) fractions under varying crop rotations and nutrient managements at two long-term experimental sites (Breton and Lethbridge). Soil samples were collected from simple (2 yr) and complex (5 or 6 yr) crop rotations at the 5–10 cm depth. We found associations between SOM pools versus microbial community and soil aggregation. Compared to cropped soils, an adjacent forest exhibited a significantly higher soil total organic carbon (TOC) and a shift in SOM fractions with substantially higher POM. However, the forest soil had the lowest microbial biomass C among all the assessed land use systems (P < 0.05), suggesting that other factors than the amount of labile SOM (i.e., POM-C) were controlling the microbial community. When contrasted to simple 2 yr rotations, the complex rotations including perennials and legumes significantly raised TOC and soil total nitrogen as well as the stable SOM fraction (i.e., MAOM-C and -N) consistently for both Breton and Lethbridge sites. Our findings highlight that varying land managements have profound feedbacks on soil quality as mediated by alterations in long-term SOM dynamics.

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 score0.662
Threshold uncertainty score0.999

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 studies0.0000.000
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 head0.194
Teacher spread0.188 · 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

Citations49
Published2018
Admission routes4
Has abstractyes

Explore more

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