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Record W4385794345 · doi:10.1002/wwp2.12138

A comparison of riparian buffer designs incorporating short‐rotation <scp><i>Salix viminalis</i></scp> to mitigate surface water pollution in the Dunk River watershed on Prince Edward Island

2023· article· en· W4385794345 on OpenAlexafffundabout
Holly D.M. Wilts, David L. Burton, Aitazaz A. Farooque

Bibliographic record

VenueWorld Water Policy · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsDalhousie UniversityUniversity of Prince Edward Island
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWillowEnvironmental scienceRiparian bufferRiparian zoneSedimentWatershedHydrology (agriculture)Riparian forestWater qualitySedimentationParticulatesShrubNutrient pollutionPollutionSurface runoffNutrientEcologyGeologyBiology

Abstract

fetched live from OpenAlex

Abstract Riparian buffers protect surface water from diffuse pollutants, mitigating sediment, nutrient, and chemical losses from agricultural landscapes. Prince Edward Island, Canada, has legislated 15‐m riparian buffers, yet stream contamination from agriculture remains widespread. The Soil and Water Assessment Tool and Riparian Ecosystem Management Model were used to simulate 12 years of nutrient and sediment loads from five potato Hydrologic Response Units in the Dunk River watershed on PEI and evaluate water quality impacts of 30 m three‐zone buffers incorporating shrub willow relative to existing 15 m grass and forest buffers and assess optimal buffer width. Willow buffers (30 m) removed 49.9 T ha −1 year −1 sediment, 18.5 kg ha −1 year −1 total N (TN) and 7.8 kg ha −1 year −1 total P (TP). This was 5.6% and 4.1% more sediment and TP than existing 15 m grass buffers and 7.5%, 12.6%, and 16.8% more sediment, TP, and TN than existing 15 m forest buffers. Willow buffers removed significantly more particulate contaminants than forest and significantly more soluble than grass. Optimal willow buffer width downslope of potato fields was 40 m. Overall, incorporating shrub willow and/or riparian widening can have considerable water quality benefits, particularly in regard to sediment retention, and maximize both soluble and particulate pollutant removal on PEI.

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 score0.428
Threshold uncertainty score1.000

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)0.0000.001

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 head0.028
GPT teacher head0.284
Teacher spread0.256 · 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

Citations3
Published2023
Admission routes3
Has abstractyes

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