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Record W4413629079 · doi:10.1016/j.aeolia.2025.101000

Off-season wind-induced soil erosion from potato fields under varying bedding preparations

2025· article· en· W4413629079 on OpenAlexafffundabout
Matt Ball, Guillermo Hernandez‐Ramirez, Rezvan Karimi Dehkordi, Willemijn M. Appels, Sheng Li

Bibliographic record

VenueAeolian Research · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAeolian processes and effects
Canadian institutionsAgriculture and Agri-Food CanadaLethbridge CollegeUniversity of LethbridgeUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaMitacsUniversity of Alberta
KeywordsBeddingAeolian processesErosionEnvironmental scienceGeologyHydrology (agriculture)Soil scienceGeotechnical engineeringGeomorphologyBiologyHorticulture

Abstract

fetched live from OpenAlex

Annually, global soil erosion is estimated at 75 billion tonnes, costing approximately US$400 billion in lost agricultural productivity, highlighting the economic and environmental significance of effective soil management. Potato fields are particularly susceptible to wind erosion during the off-season, due to extensive soil exposure. In Southern Alberta, fall bedding is a common management practice, involving bedding preparation in the fall rather than spring. Fall bedding presents logistical and economic advantages to producers, but it may increase the risk of off-season wind erosion due to increased soil disturbance. To investigate this, wind erosion was measured using Modified Wilson and Cook (MWAC) samplers and modelled with the Wind Erosion Prediction System (WEPS) model across three off-seasons (2021–2024) at the Lethbridge Polytechnic Irrigation Demo Farm. Rates of wind-induced soil erosion were evaluated under three bedding types: spring bedding, spring bedding following a winter cover crop, and fall bedding. The measured and modelled rates indicate that fall bedding experienced the greatest rates of wind-induced erosion across all three off-season periods. On average, off-season wind-induced erosion under fall bedding was 20 times higher than that under both spring beddings. The study found that the WEPS model closely aligns with measured data, showing high model accuracy (R 2 = 0.9327, Nash–Sutcliffe efficiency (NSE) = 0.9058). Statistical analyses revealed significant differences in erosion rates across bedding types (P < 0.05), with fall bedding consistently leading to higher erosion. The benefits of winter cover crops prior to spring bedding were less pronounced, suggesting that winter cover cropping may offer minimal additional erosion reduction compared to spring bedding alone when following a cereal crop. These findings advocate for the adoption of spring bedding to reduce off-season wind erosion and its associated economic and environmental costs. The results also underscore the importance of considering both economic and long-term sustainability when selecting bedding practices in potato cultivation.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.337
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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.059
GPT teacher head0.353
Teacher spread0.294 · 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.

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

Citations0
Published2025
Admission routes3
Has abstractyes

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