scholarly journals Risk Assessment of Glyphosate Resistance in Western Canada

2011 ◽  
Vol 25 (1) ◽  
pp. 159-164 ◽  
Author(s):  
Hugh J. Beckie ◽  
K. Neil Harker ◽  
Linda M. Hall ◽  
Frederick A. Holm ◽  
Robert H. Gulden
Keyword(s):  
Best Management Practices ◽  
Management Practices ◽  
Cropping Systems ◽  
Resistance Management ◽  
Decision Support Tool ◽  
Glyphosate Resistance ◽  
Western Canada ◽  
Support Tool ◽  
Resistance Evolution ◽  
Risk Rating

With increasing incidence of glyphosate-resistant weeds worldwide, greater farmer awareness of the importance of glyphosate stewardship and proactive glyphosate-resistance management is needed. A Web-based decision-support tool (http://www.weedtool.com) comprising 10 questions has been developed primarily for farmers in western Canada to assess the relative risk of selection for glyphosate-resistant weeds on a field-by-field basis. We describe the rationale for the questions and how a response to a particular question influences the risk rating. Practices with the greatest risk weighting in western Canadian cropping systems are lack of crop-rotation diversity (growing mainly oilseeds) and a high frequency of glyphosate-resistant crops in the rotation. Three case scenarios are outlined—low, moderate, and high risk of glyphosate-resistance evolution. Based on the overall risk rating, three best-management practices are recommended to reduce the risk of glyphosate resistance in weeds.

Glyphosate- and Acetolactate Synthase Inhibitor–Resistant Kochia (Kochia scoparia) in Western Canada

Weed Science ◽  
2013 ◽  
Vol 61 (2) ◽  
pp. 310-318 ◽  
Author(s):  
Hugh J. Beckie ◽  
Robert E. Blackshaw ◽  
Ryan Low ◽  
Linda M. Hall ◽  
Connie A. Sauder ◽  
...  
Keyword(s):  
Dose Response ◽  
Best Management Practices ◽  
Management Practices ◽  
Acetolactate Synthase ◽  
Glyphosate Resistance ◽  
Western Canada ◽  
Wild Oat ◽  
Green Foxtail ◽  
Inhibitor Resistance ◽  
Als Inhibitor

In summer, 2011, we investigated suspected glyphosate-resistant (GR) kochia in three chem-fallow fields (designated F1, F2, F3, each farmed by a different grower) in southern Alberta. This study characterizes glyphosate resistance in those populations, based on data from dose–response experiments. In a greenhouse experiment, the three populations exhibited a resistance factor ranging from 4 to 6 based on shoot biomass response (GR50ratios), or 5 to 7 based on survival response (LD50ratios). Similar results were found in a field dose–response experiment at Lethbridge, AB, in spring 2012 using the F2 kochia population. In fall 2011, we surveyed 46 fields within a 20-km radius of the three chem-fallow fields for GR kochia. In the greenhouse, populations were screened with glyphosate at 900 g ae ha−1. Seven populations were confirmed as GR, the farthest site located about 13 km from the three originally confirmed populations. An additional GR population more than 100 km away was later confirmed. Populations were screened for acetolactate synthase (ALS)–inhibitor (thifensulfuron : tribenuron) and dicamba resistance in the greenhouse, with molecular characterization of ALS-inhibitor resistance in the F1, F2, and F3 populations. All GR populations were resistant to the ALS-inhibiting herbicide, but susceptible to dicamba. ALS-inhibitor resistance in kochia was conferred by Pro197, Asp376, or Trp574amino acid substitutions. Based upon a simple empirical model with a parameter for selection pressure, calculated from weed relative abundance and glyphosate efficacy, and a parameter for seedbank longevity, kochia, wild oat, and green foxtail were the top three weeds, respectively, predicted at risk of selection for glyphosate resistance in the semiarid Grassland region of the Canadian prairies; wild oat, green foxtail, and cleavers species were predicted at greatest risk in the subhumid Parkland region. This study confirms the first occurrence of a GR weed in western Canada. Future research on GR kochia will include monitoring, biology and ecology, fitness, mechanism of resistance, and best management practices.

scholarly journals An Innovative Tool for the Management of the Surface Drinking Water Resources at European Level: GOWARE—Transnational Guide Towards an Optimal WAter REgime

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 370 ◽  
Author(s):  
Angela Rizzo ◽  
Primoz Banovec ◽  
Ajda Cilenšek ◽  
Guido Rianna ◽  
Monia Santini
Keyword(s):  
Drinking Water ◽  
Best Management Practices ◽  
Water Regime ◽  
Management Practices ◽  
Risk Mitigation ◽  
Decision Support Tool ◽  
Drought Risk ◽  
Support Tool ◽  
Drinking Water Resources ◽  
Innovative Tool

GOWARE (transnational Guide toward an Optimal WAter REgime) represents a Decision Support Tool (DST) developed to support the implementation of innovative Best Management Practices (BMPs) for drinking water protection and flood/drought risk mitigation. The tool is one of the main outputs of the PROLINE-CE Project, an EU project funded within the Interreg Central Europe (CE) Programme (2014–2020). The aim of this paper is illustrating the design and the methodological approaches proposed for the operative development of the tool. Furthermore, the paper provides the results of a number of tests carried out to evaluate the understandability of the analysis’s processes and assessing the stakeholders’ acceptance. Specifically, GOWARE-DST has been developed for supporting single users or groups of users in the decision-making process. The tool has been provided with a catalogue of 92 BMPs to handle water issues in different land use contexts. The selection of practices suitable for addressing the specific user’s requirements is supported by the Analytic Hierarchy Process, a method that allows filtering a subset of BMPs by accounting for the relative importance that the user assigns to each characterizing criterion. GOWARE-DST represents an innovative tool for supporting users at different levels of planning (operational and strategic) by promoting sustainable land and water management and defining long-term governance activities.

scholarly journals Developing a decision support tool for assessing land use change and BMPs in ungauged watersheds based on decision rules provided by SWAT simulation

2018 ◽  
Vol 22 (7) ◽  
pp. 3789-3806 ◽  
Author(s):  
Junyu Qi ◽  
Sheng Li ◽  
Charles P.-A. Bourque ◽  
Zisheng Xing ◽  
Fan-Rui Meng
Keyword(s):  
Land Use ◽  
Decision Support ◽  
Land Use Change ◽  
Best Management Practices ◽  
Management Practices ◽  
Hydrological Modeling ◽  
Decision Support Tool ◽  
Decision Makers ◽  
Support Tool ◽  
Ungauged Watersheds

Abstract. Decision making on water resources management at ungauged, especially large-scale watersheds relies on hydrological modeling. Physically based distributed hydrological models require complicated setup, calibration, and validation processes, which may delay their acceptance among decision makers. This study presents an approach to develop a simple decision support tool (DST) for decision makers and economists to evaluate multiyear impacts of land use change and best management practices (BMPs) on water quantity and quality for ungauged watersheds. The example DST developed in the present study was based on statistical equations derived from Soil and Water Assessment Tool (SWAT) simulations and applied to a small experimental watershed in northwest New Brunswick. The DST was subsequently tested against field measurements and SWAT simulations for a larger watershed. Results from DST could reproduce both field data and model simulations of annual stream discharge and sediment and nutrient loadings. The relative error of mean annual discharge and sediment, nitrate–nitrogen, and soluble-phosphorus loadings were −6, −52, 27, and −16 %, respectively, for long-term simulation. Compared with SWAT, DST has fewer input requirements and can be applied to multiple watersheds without additional calibration. Also, scenario analyses with DST can be directly conducted for different combinations of land use and BMPs without complex model setup procedures. The approach in developing DST can be applied to other regions of the world because of its flexible structure.

scholarly journals Site-Scale Integrated Decision Support Tool (i-DSTss) for Stormwater Management

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2022 ◽  
Author(s):  
Shojaeizadeh ◽  
Geza ◽  
McCray ◽  
Hogue
Keyword(s):  
Decision Support ◽  
Best Management Practices ◽  
Life Cycle Cost ◽  
Management Practices ◽  
Decision Support Tool ◽  
Green Roofs ◽  
Optimization Approach ◽  
Small Catchment ◽  
Support Tool ◽  
A Site

A site-scale integrated decision support tool (i-DSTss) is developed for selection and sizing of stormwater Best Management Practices (BMPs). The tool has several component modules—hydrology, BMP selection, BMP sizing, and life-cycle cost analysis (LCCA)—integrated into a single platform. The hydrology module predicts runoff from small catchment on event and continuous basis using the Green-Ampt and Curve Number methods. The module predicted runoff from a small residential area and a parking lot with R2 value of 0.77 and 0.74, respectively. The BMP selection module recommends a BMP type appropriate for a site based on economic, technical, social and environmental criteria using a multi-criteria optimization approach. The BMP sizing module includes sizing options for green roofs, infiltration-based BMPs, and storage-based BMPs. A mass balance approach is implemented for all types of BMPs. The tool predicted outflow rates from a permeable pavement with R2 value of 0.89. A cost module is included where capital, operation and maintenance, and rehabilitation costs are estimated based on BMP size obtained from the sizing module. The i-DSTss is built on an accessible platform (Microsoft Excel VBA) and can be operated with a basic skillset. The i-DSTss is intended for designers, regulators, and municipalities for quick analysis of scenarios involving interaction among several factors.

Optimization Strategies for Agricultural Non-Point Source Reduction

2012 ◽  
Vol 518-523 ◽  
pp. 1184-1187
Author(s):  
Dong Wang ◽  
Ya Juan Yu ◽  
Xiang Wang ◽  
Kai Huang ◽  
Shu Xia Yu
Keyword(s):  
Point Source ◽  
Best Management Practices ◽  
Management Practices ◽  
Management Strategies ◽  
Decision Support Tool ◽  
Point Source Pollution ◽  
Lake Dianchi ◽  
Source Reduction ◽  
Support Tool ◽  
Non Point Source Pollution

A methodological framework is brought forward, with the aim of reducing the agricultural non-point source (ANPS) pollution from the overuse of fertilizers and pesticides in rural area of the lake Dianchi watershed. In order to build a bridge connecting the public and the authority, a simplified decision support tool is conceived to realize the management target. Firstly, a rapid calculation method for the agricultural non-point source pollution is given called factor - coefficient method. Multiple kinds of agricultural non-point loads are calculated from both the pollution factors and the pollution coefficients. The sources include the farmland runoff, rural life, livestock and poultry, and so on. Then a checklist of engineering and management strategies to reduce ANPS are listed. Finally, according to the specific flowchart, the Best Management Practices (BMPs) to control the agricultural non-point source pollution of Lake Dianchi would be built, adapting with the real conditions of the watershed.

Distribution and validation of genotypic and phenotypic glyphosate and PPO-nhibitor resistance in Palmer amaranth (Amaranthus palmeri) from southwestern Nebraska

2020 ◽  
pp. 1-12 ◽  
Author(s):  
Maxwel C Oliveira ◽  
Darci A Giacomini ◽  
Nikola Arsenijevic ◽  
Gustavo Vieira ◽  
Patrick J Tranel ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Gene Amplification ◽  
Cropping Systems ◽  
Resistance Mechanism ◽  
Geographic Area ◽  
Glyphosate Resistance ◽  
Resistance Mechanisms ◽  
Palmer Amaranth ◽  
Resistance Evolution ◽  
Inhibitor Resistance

Abstract Failure to control Palmer amaranth with glyphosate and protoporphyrinogen IX oxidase (PPO)-inhibitor herbicides was reported across southwestern Nebraska in 2017. The objectives of this study were to 1) confirm and 2) validate glyphosate and PPO-inhibitor (fomesafen and lactofen) resistance in 51 Palmer amaranth accessions from southwestern Nebraska using genotypic and whole-plant phenotypic assay correlations and cluster analysis, and 3) determine which agronomic practices might be influencing glyphosate resistance in Palmer amaranth accessions in that location. Based on genotypic assay, 88% of 51 accessions contained at least one individual with amplification (>2 copies) of the 5-enolypyruvyl-shikimate-3-phosphate synthase (EPSPS) gene, which confers glyphosate resistance; and/or a mutation in the PPX2 gene, either ΔG210 or R128G, which endows PPO-inhibitor resistance in Palmer amaranth. Cluster analysis and high correlation (0.83) between genotypic and phenotypic assays demonstrated that EPSPS gene amplification is the main glyphosate resistance mechanism in Palmer amaranth accessions from southwestern Nebraska. In contrast, there was poor association between genotypic and phenotypic responses for PPO-inhibitor resistance, which was attributed to segregation for PPO-inhibitor resistance within these accessions and/or the methodology that was adopted herein. Genotypic assays can expedite the process of confirming known glyphosate and PPO-inhibitor resistance mechanisms in Palmer amaranth from southwestern Nebraska and other locations. Phenotypic assays are also a robust method for confirming glyphosate resistance but not necessarily PPO-inhibitor resistance in Palmer amaranth. Moreover, random forest analysis of glyphosate resistance in Palmer amaranth indicated that EPSPS gene amplification, county, and current and previous crops are the main factors influencing glyphosate resistance within that geographic area. Most glyphosate-susceptible Palmer amaranth accessions were found in a few counties in areas with high crop diversity. Results presented here confirm the spread of glyphosate resistance and PPO-inhibitor resistance in Palmer amaranth accessions from southwestern Nebraska and demonstrate that less diverse cropping systems are an important driver of herbicide resistance evolution in Palmer amaranth.

Modeling Glyphosate Resistance Management Strategies for Palmer Amaranth (Amaranthus palmeri) in Cotton

2011 ◽  
Vol 25 (3) ◽  
pp. 335-343 ◽  
Author(s):  
Paul Neve ◽  
Jason K. Norsworthy ◽  
Kenneth L. Smith ◽  
Ian A. Zelaya
Keyword(s):  
Weed Management ◽  
Management Strategies ◽  
Resistance Management ◽  
Glyphosate Resistance ◽  
Palmer Amaranth ◽  
Case Scenario ◽  
Management Options ◽  
Worst Case ◽  
Resistance Risk ◽  
Resistance Evolution

A simulation model is used to explore management options to mitigate risks of glyphosate resistance evolution in Palmer amaranth in glyphosate-resistant cotton in the southern United States. Our first analysis compares risks of glyphosate resistance evolution for seven weed-management strategies in continuous glyphosate-resistant cotton monoculture. In the “worst-case scenario” with five applications of glyphosate each year and no other herbicides applied, evolution of glyphosate resistance was predicted in 74% of simulated populations. In other strategies, glyphosate was applied with various combinations of preplant, PRE, and POST residual herbicides. The most effective strategy included four glyphosate applications with a preplant fomesafen application, and POST tank mixtures of glyphosate plusS-metolachlor followed by glyphosate plus flumioxazin. This strategy reduced the resistance risk to 12% of populations. A second series of simulations compared strategies where glyphosate-resistant cotton was grown in one-to-one rotations with corn or cotton with other herbicide resistance traits. In general, crop rotation reduced risks of resistance by approximately 50% and delayed the evolution of resistance by 2 to 3 yr. These analyses demonstrate that risks of glyphosate resistance evolution in Palmer amaranth can be reduced by reducing glyphosate use within and among years, controlling populations with diverse herbicide modes of action, and ensuring that population size is kept low. However, no strategy completely eliminated the risk of glyphosate resistance.

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