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Record W2329720371 · doi:10.1139/cjss-2015-0089

Soil quality attributes, soil resilience, and legacy effects following topsoil removal and one-time amendments

2016· article· en· W2329720371 on OpenAlexaffvenueabout
Francis J. Larney, Lin Li, H. H. Janzen, Denis A. Angers, Barry M. Olson

Bibliographic record

VenueCanadian Journal of Soil Science · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil erosion and sediment transport
Canadian institutionsAlberta Ministry of Agriculture and ForestryAgriculture Food and Rural DevelopmentAgriculture and Agri-Food Canada
Fundersnot available
KeywordsTopsoilManureEnvironmental scienceSoil qualityAmendmentErosionNitrogenAgronomyFertilizerAnimal scienceSoil scienceChemistrySoil waterGeologyBiology

Abstract

fetched live from OpenAlex

Inter-relationships among soil erosion, soil quality, soil resilience, and legacy effects of organic amendments have not been adequately quantified. Topsoil was mechanically removed (cuts) to simulate erosion in semiarid southern Alberta in 1990. Three cuts (0, 10, and 20 cm) superimposed with three one-time (1990 only) amendment treatments (check, N + P fertilizer, and manure) were chosen for this study. In the absence of amendments, light fraction C (C LF ) and mineralizable C (C min ) recovered sufficiently by 2004 to render the cut effect nonsignificant. Organic C (C org ) responded more slowly with the 10-cm cut recovering to the 0-cm cut concentration by 2004, and the 20-cm cut (13.9 g kg −1 ) remaining significantly lower than the 0-cm cut concentration (16.3 g kg −1 ) through to 2012. Nitrogen fractions behaved similarly. Among cuts and years (2004 and 2012), C fraction values were 19–27% greater on the manure versus check treatment (17.5 vs. 14.7 g kg −1 for C org , 1.38 vs. 1.09 g kg −1 for C LF , and 650 vs. 531 mg kg −1 for C min ) demonstrating a strong legacy effect of manure. Water-stable aggregation exhibited a 22-yr legacy effect of manure. Our findings help quantify soil resilience following major disturbance and legacy effects of one-time manure application under semiarid 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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.785
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.022
GPT teacher head0.234
Teacher spread0.212 · 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

Citations33
Published2016
Admission routes3
Has abstractyes

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