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Record W4412448992 · doi:10.56369/tsaes.6100

IMPACTS OF SOIL MOISTURE AND TILLAGE ON SHORT-TERM EROSION IN AGRICULTURAL LANDS OF NORTH CENTRAL MEXICO

2025· article· en· W4412448992 on OpenAlex
Palmira Bueno Hurtado, Ousmane Seidou, Armando López-Santos

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTropical and Subtropical Agroecosystems · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil erosion and sediment transport
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsTillageEnvironmental scienceErosionTerm (time)AgricultureAgroforestryCentral HighlandsMoistureSoil conservationWater contentHydrology (agriculture)GeographyAgronomyGeologyArchaeologyGeotechnical engineeringGeomorphology

Abstract

fetched live from OpenAlex

<p><strong>Background</strong>: Soil erosion is a natural process accelerated by anthropogenic activities such as agriculture, leading to increased runoff and erosion, resulting in global environmental and economic losses. Addressing this issue through conservation agriculture is critical, particularly in arid regions where soil degradation is prevalent. This study adds value by evaluating the combined effects of tillage practices and antecedent soil moisture conditions (AMC) on runoff and soil erosion under controlled rainfall simulation. <strong>Objective</strong>: To assess the effects of tillage practices and AMC on runoff and soil erosion, hypothesizing that conservation-oriented practices would reduce erosion and runoff. <strong>Methodology</strong>: A randomized complete block design experiment was conducted in an arid zone of North-central Mexico. Four tillage treatments were evaluated: 1) no crop (NC), 2) maize with conventional tillage and crop residues (CTR), 3) maize with conventional tillage (CT), and 4) maize sown by handspike (HS). Each treatment was tested under two AMC scenarios: dry and wet. Runoff and soil erosion were measured, and results were analyzed using ANOVA. <strong>Results</strong>: Dry AMC significantly reduced erosion in HS (p ≤ 0.01) and CTR (p ≤ 0.05) compared to wet AMC. CT and CTR produced the lowest erosion under wet AMC (p ≤ 0.05). For total runoff, CTR and HS produced the lowest values under dry AMC. These findings highlight the effectiveness of crop residue cover in CTR and no-tillage cropping (HS) in reducing both erosion and runoff. <strong>Implications</strong>: The study demonstrates the importance of soil moisture conditions and tillage practices in managing erosion. Limitations include the use of simulated rainfall, which may not fully capture natural variability. However, the findings provide valuable insights for conservation agriculture in arid regions. <strong>Conclusion</strong>: Crop residue cover and no-tillage cropping are effective in reducing soil erosion and runoff, especially under dry AMC. These practices are crucial for sustainable soil management in arid agroecosystems.</p>

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.

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 score0.036
Threshold uncertainty score0.966

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 head0.010
GPT teacher head0.207
Teacher spread0.197 · 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