The Experts below are selected from a list of 8067 Experts worldwide ranked by ideXlab platform
Stephen B. Powles - One of the best experts on this subject based on the ideXlab platform.
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Social Costs of Herbicide Resistance: The Case of Resistance to Glyphosate
2020Co-Authors: Sally P. Marsh, Rick Llewellyn, Stephen B. PowlesAbstract:Social costs and externalities associated with Herbicide Resistance have not generally been considered by economists. The economics of managing Herbicide Resistance in weeds has focused on cost-effective responses by growers to the development of Resistance at the individual farm and field level. In this paper we argue that the increasing possibility of widespread glyphosate Resistance presents a case where social costs associated with glyphosate Resistance need to be considered when assessing optimal use of this Herbicide resource at the farm level. Social costs associated with the loss of glyphosate efficacy include potential failure of Herbicide-resistant crop systems, reduced use of conservation tillage techniques, and a potential greater reliance on Herbicides with greater health and environmental risks.
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Herbicide Resistance: an imperative for smarter crop weed management
2020Co-Authors: Michael J Walsh, Stephen B. PowlesAbstract:In most world cropping systems the evolution of Herbicide resistant weeds is becoming a major issue. This problem has become most severe in Australia. In the broad-area rain-fed cropping systems of southern Australian, Herbicide Resistance is a widespread problem threatening cropping profitability and sustainability. Widespread Herbicide Resistance has forced changes in agronomic and Herbicide practices towards more diversity. Judicious Herbicide mixtures and rotation can reduce the selection pressure for Resistance to any one specific Herbicide. Additionally, agronomic practices such as the adoption of delayed seeding and increased seeding rates can also reduce selection pressure by reducing in-crop weed populations. However, these techniques are not without problems or limitations. At grain harvest, the use of machinery to capture, collect and render weed seed non-viable is a very effective technique for reducing annual weed populations. The adoption by Australian farmers of the current limited technology is clear evidence of the value placed on the use of these alternative crop weed control practices. The continued march of Herbicide Resistance evolution more than justifies continuing research and development efforts to develop integrated strategies and smarter Herbicide use so as to achieve sustainable crop weed management.
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metabolism based Herbicide Resistance and cross Resistance in crop weeds a threat to Herbicide sustainability and global crop production
Plant Physiology, 2014Co-Authors: Qin Yu, Stephen B. PowlesAbstract:Weedy plant species that have evolved Resistance to Herbicides due to enhanced metabolic capacity to detoxify Herbicides (metabolic Resistance) are a major issue. Metabolic Herbicide Resistance in weedy plant species first became evident in the 1980s in Australia (in Lolium rigidum) and the United Kingdom (in Alopecurus myosuroides) and is now increasingly recognized in several crop-weed species as a looming threat to Herbicide sustainability and thus world crop production. Metabolic Resistance often confers Resistance to Herbicides of different chemical groups and sites of action and can extend to new Herbicide(s). Cytochrome P450 monooxygenase, glycosyl transferase, and glutathione S-transferase are often implicated in Herbicide metabolic Resistance. However, precise biochemical and molecular genetic elucidation of metabolic Resistance had been stalled until recently. Complex cytochrome P450 superfamilies, high genetic diversity in metabolic resistant weedy plant species (especially cross-pollinated species), and the complexity of genetic control of metabolic Resistance have all been barriers to advances in understanding metabolic Herbicide Resistance. However, next-generation sequencing technologies and transcriptome-wide gene expression profiling are now revealing the genes endowing metabolic Herbicide Resistance in plants. This Update presents an historical review to current understanding of metabolic Herbicide Resistance evolution in weedy plant species.
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evolved polygenic Herbicide Resistance in lolium rigidum by low dose Herbicide selection within standing genetic variation
Evolutionary Applications, 2013Co-Authors: Roberto Busi, Paul Neve, Stephen B. PowlesAbstract:The interaction between environment and genetic traits under selection is the basis of evolution. In this study, we have investigated the genetic basis of Herbicide Resistance in a highly characterized initially Herbicide-susceptible Lolium rigidum population recurrently selected with low (below recommended label) doses of the Herbicide diclofop-methyl. We report the variability in Herbicide Resistance levels observed in F1 families and the segregation of Resistance observed in F2 and back-cross (BC) families. The selected Herbicide Resistance phenotypic trait(s) appear to be under complex polygenic control. The estimation of the effective minimum number of genes (NE), depending on the Herbicide dose used, reveals at least three Resistance genes had been enriched. A joint scaling test indicates that an additive-dominance model best explains gene interactions in parental, F1, F2 and BC families. The Mendelian study of six F2 and two BC segregating families confirmed involvement of more than one Resistance gene. Cross-pollinated L. rigidum under selection at low Herbicide dose can rapidly evolve polygenic broad-spectrum Herbicide Resistance by quantitative accumulation of additive genes of small effect. This can be minimized by using Herbicides at the recommended dose which causes high mortality acting outside the normal range of phenotypic variation for Herbicide susceptibility.
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Simulation modelling identifies polygenic basis of Herbicide Resistance in a weed population and predicts rapid evolution of Herbicide Resistance at low Herbicide rates
Crop Protection, 2012Co-Authors: Sudheesh Manalil, Michael Renton, Art J. Diggle, Roberto Busi, Stephen B. PowlesAbstract:Abstract The potential for low rates of diclofop-methyl to result in rapid evolution of Herbicide Resistance in a Herbicide-susceptible Lolium rigidum (annual ryegrass) population was demonstrated in a recent crop-field study. In this present study, the data from the crop-field study was used together with simulation modelling to identify possible genetics of the Herbicide Resistance that was selected for. This analysis clearly indicated that the Herbicide Resistance was polygenic. Subsequently, the estimated genetic possibilities were used to parameterise a model of Herbicide Resistance evolution in a simulated crop-field situation, and the potential of different rates of diclofop-methyl (ACCase Herbicide) to cause Herbicide-Resistance evolution in L. rigidum was explored and compared using the calibrated model. The calibrated model outputs indicated that the evolution of diclofop-methyl Resistance would generally be faster at low Herbicide rates than at higher rates due to the rapid selection of minor gene Herbicide Resistance traits at low rates and their subsequent recombination by cross-pollination. The results of the study therefore indicate potential risks in Herbicide rate cutting and highlight the need for careful scientific evaluation of any Herbicide use rate for its potential to select for minor gene Herbicide Resistance from a weed population.
Roberto Busi - One of the best experts on this subject based on the ideXlab platform.
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Herbicide Resistance modelling past present and future
Pest Management Science, 2014Co-Authors: Michael Renton, Roberto Busi, Paul Neve, David Thornby, Martin M VilaaiubAbstract:Computer simulation modelling is an essential aid in building an integrated understanding of how different factors interact to affect the evolutionary and population dynamics of Herbicide Resistance, and thus in helping to predict and manage how agricultural systems will be affected. In this review, we first discuss why computer simulation modelling is such an important tool and framework for dealing with Herbicide Resistance. We then explain what questions related to Herbicide Resistance have been addressed to date using simulation modelling, and discuss the modelling approaches that have been used, focusing first on the earlier, more general approaches, and then on some newer, more innovative approaches. We then consider how these approaches could be further developed in the future, by drawing on modelling techniques that are already employed in other areas, such as individual-based and spatially explicit modelling approaches, as well as the possibility of better representing genetics, competition and economics, and finally the questions and issues of importance to Herbicide Resistance research and management that could be addressed using these new approaches are discussed. We conclude that it is necessary to proceed with caution when increasing the complexity of models by adding new details, but, with appropriate care, more detailed models will make it possible to integrate more current knowledge in order better to understand, predict and ultimately manage the evolution of Herbicide Resistance. © 2014 Society of Chemical Industry
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expanding the eco evolutionary context of Herbicide Resistance research
Pest Management Science, 2014Co-Authors: Paul Neve, Michael Renton, Roberto Busi, Martin M VilaaiubAbstract:The potential for human-driven evolution in economically and environmentally important organisms in medicine, agriculture and conservation management is now widely recognised. The evolution of Herbicide Resistance in weeds is a classic example of rapid adaptation in the face of human-mediated selection. Management strategies that aim to slow or prevent the evolution of Herbicide Resistance must be informed by an understanding of the ecological and evolutionary factors that drive selection in weed populations. Here, we argue for a greater focus on the ultimate causes of selection for Resistance in Herbicide Resistance studies. The emerging fields of eco-evolutionary dynamics and applied evolutionary biology offer a means to achieve this goal and to consider Herbicide Resistance in a broader and sometimes novel context. Four relevant research questions are presented, which examine (i) the impact of Herbicide dose on selection for Resistance, (ii) plant fitness in Herbicide Resistance studies, (iii) the efficacy of Herbicide rotations and mixtures and (iv) the impacts of gene flow on Resistance evolution and spread. In all cases, fundamental ecology and evolution have the potential to offer new insights into Herbicide Resistance evolution and management. © 2014 Society of Chemical Industry
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Expanding the eco‐evolutionary context of Herbicide Resistance research
Pest Management Science, 2014Co-Authors: Paul Neve, Michael Renton, Roberto Busi, Martin M. Vila-aiubAbstract:The potential for human-driven evolution in economically and environmentally important organisms in medicine, agriculture and conservation management is now widely recognised. The evolution of Herbicide Resistance in weeds is a classic example of rapid adaptation in the face of human-mediated selection. Management strategies that aim to slow or prevent the evolution of Herbicide Resistance must be informed by an understanding of the ecological and evolutionary factors that drive selection in weed populations. Here, we argue for a greater focus on the ultimate causes of selection for Resistance in Herbicide Resistance studies. The emerging fields of eco-evolutionary dynamics and applied evolutionary biology offer a means to achieve this goal and to consider Herbicide Resistance in a broader and sometimes novel context. Four relevant research questions are presented, which examine (i) the impact of Herbicide dose on selection for Resistance, (ii) plant fitness in Herbicide Resistance studies, (iii) the efficacy of Herbicide rotations and mixtures and (iv) the impacts of gene flow on Resistance evolution and spread. In all cases, fundamental ecology and evolution have the potential to offer new insights into Herbicide Resistance evolution and management. © 2014 Society of Chemical Industry
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evolved polygenic Herbicide Resistance in lolium rigidum by low dose Herbicide selection within standing genetic variation
Evolutionary Applications, 2013Co-Authors: Roberto Busi, Paul Neve, Stephen B. PowlesAbstract:The interaction between environment and genetic traits under selection is the basis of evolution. In this study, we have investigated the genetic basis of Herbicide Resistance in a highly characterized initially Herbicide-susceptible Lolium rigidum population recurrently selected with low (below recommended label) doses of the Herbicide diclofop-methyl. We report the variability in Herbicide Resistance levels observed in F1 families and the segregation of Resistance observed in F2 and back-cross (BC) families. The selected Herbicide Resistance phenotypic trait(s) appear to be under complex polygenic control. The estimation of the effective minimum number of genes (NE), depending on the Herbicide dose used, reveals at least three Resistance genes had been enriched. A joint scaling test indicates that an additive-dominance model best explains gene interactions in parental, F1, F2 and BC families. The Mendelian study of six F2 and two BC segregating families confirmed involvement of more than one Resistance gene. Cross-pollinated L. rigidum under selection at low Herbicide dose can rapidly evolve polygenic broad-spectrum Herbicide Resistance by quantitative accumulation of additive genes of small effect. This can be minimized by using Herbicides at the recommended dose which causes high mortality acting outside the normal range of phenotypic variation for Herbicide susceptibility.
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Simulation modelling identifies polygenic basis of Herbicide Resistance in a weed population and predicts rapid evolution of Herbicide Resistance at low Herbicide rates
Crop Protection, 2012Co-Authors: Sudheesh Manalil, Michael Renton, Art J. Diggle, Roberto Busi, Stephen B. PowlesAbstract:Abstract The potential for low rates of diclofop-methyl to result in rapid evolution of Herbicide Resistance in a Herbicide-susceptible Lolium rigidum (annual ryegrass) population was demonstrated in a recent crop-field study. In this present study, the data from the crop-field study was used together with simulation modelling to identify possible genetics of the Herbicide Resistance that was selected for. This analysis clearly indicated that the Herbicide Resistance was polygenic. Subsequently, the estimated genetic possibilities were used to parameterise a model of Herbicide Resistance evolution in a simulated crop-field situation, and the potential of different rates of diclofop-methyl (ACCase Herbicide) to cause Herbicide-Resistance evolution in L. rigidum was explored and compared using the calibrated model. The calibrated model outputs indicated that the evolution of diclofop-methyl Resistance would generally be faster at low Herbicide rates than at higher rates due to the rapid selection of minor gene Herbicide Resistance traits at low rates and their subsequent recombination by cross-pollination. The results of the study therefore indicate potential risks in Herbicide rate cutting and highlight the need for careful scientific evaluation of any Herbicide use rate for its potential to select for minor gene Herbicide Resistance from a weed population.
Martin M Vilaaiub - One of the best experts on this subject based on the ideXlab platform.
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Herbicide Resistance modelling past present and future
Pest Management Science, 2014Co-Authors: Michael Renton, Roberto Busi, Paul Neve, David Thornby, Martin M VilaaiubAbstract:Computer simulation modelling is an essential aid in building an integrated understanding of how different factors interact to affect the evolutionary and population dynamics of Herbicide Resistance, and thus in helping to predict and manage how agricultural systems will be affected. In this review, we first discuss why computer simulation modelling is such an important tool and framework for dealing with Herbicide Resistance. We then explain what questions related to Herbicide Resistance have been addressed to date using simulation modelling, and discuss the modelling approaches that have been used, focusing first on the earlier, more general approaches, and then on some newer, more innovative approaches. We then consider how these approaches could be further developed in the future, by drawing on modelling techniques that are already employed in other areas, such as individual-based and spatially explicit modelling approaches, as well as the possibility of better representing genetics, competition and economics, and finally the questions and issues of importance to Herbicide Resistance research and management that could be addressed using these new approaches are discussed. We conclude that it is necessary to proceed with caution when increasing the complexity of models by adding new details, but, with appropriate care, more detailed models will make it possible to integrate more current knowledge in order better to understand, predict and ultimately manage the evolution of Herbicide Resistance. © 2014 Society of Chemical Industry
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expanding the eco evolutionary context of Herbicide Resistance research
Pest Management Science, 2014Co-Authors: Paul Neve, Michael Renton, Roberto Busi, Martin M VilaaiubAbstract:The potential for human-driven evolution in economically and environmentally important organisms in medicine, agriculture and conservation management is now widely recognised. The evolution of Herbicide Resistance in weeds is a classic example of rapid adaptation in the face of human-mediated selection. Management strategies that aim to slow or prevent the evolution of Herbicide Resistance must be informed by an understanding of the ecological and evolutionary factors that drive selection in weed populations. Here, we argue for a greater focus on the ultimate causes of selection for Resistance in Herbicide Resistance studies. The emerging fields of eco-evolutionary dynamics and applied evolutionary biology offer a means to achieve this goal and to consider Herbicide Resistance in a broader and sometimes novel context. Four relevant research questions are presented, which examine (i) the impact of Herbicide dose on selection for Resistance, (ii) plant fitness in Herbicide Resistance studies, (iii) the efficacy of Herbicide rotations and mixtures and (iv) the impacts of gene flow on Resistance evolution and spread. In all cases, fundamental ecology and evolution have the potential to offer new insights into Herbicide Resistance evolution and management. © 2014 Society of Chemical Industry
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fitness costs associated with evolved Herbicide Resistance alleles in plants
New Phytologist, 2009Co-Authors: Martin M Vilaaiub, Paul Neve, Stephen B. PowlesAbstract:Predictions based on evolutionary theory suggest that the adaptive value of evolved Herbicide Resistance alleles may be compromised by the existence of fitness costs. There have been many studies quantifying the fitness costs associated with novel Herbicide Resistance alleles, reflecting the importance of fitness costs in determining the evolutionary dynamics of Resistance. However, many of these studies have incorrectly defined Resistance or used inappropriate plant material and methods to measure fitness. This review has two major objectives. First, to propose a methodological framework that establishes experimental criteria to unequivocally evaluate fitness costs. Second, to present a comprehensive analysis of the literature on fitness costs associated with Herbicide Resistance alleles. This analysis reveals unquestionable evidence that some Herbicide Resistance alleles are associated with pleiotropic effects that result in plant fitness costs. Observed costs are evident from Herbicide Resistance-endowing amino acid substitutions in proteins involved in amino acid, fatty acid, auxin and cellulose biosynthesis, as well as enzymes involved in Herbicide metabolism. However, these Resistance fitness costs are not universal and their expression depends on particular plant alleles and mutations. The findings of this review are discussed within the context of the plant defence trade-off theory and Herbicide Resistance evolution.
Paul Neve - One of the best experts on this subject based on the ideXlab platform.
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Adopting epidemiological approaches for Herbicide Resistance monitoring and management
Weed Research, 2020Co-Authors: David Comont, Paul NeveAbstract:The widespread use and increasing reliance on Herbicides for weed control has resulted in a global epidemic of evolved Herbicide Resistance in weed populations. In response, there has been a great deal of research effort to document Resistance cases, understand the genetic and physiological mechanisms of Resistance, and use models and model organisms to explore Resistance management strategies. Here, we argue that the field of epidemiology, which systematically studies the extent, distribution and determinants of a harmful organism or condition, can greatly contribute to our efforts to understand the emergence, selection and spread of Herbicide Resistance. By systematically collecting data on weed abundance and distribution, the frequency and mechanisms of Resistance, and agronomic and environmental metadata, it is possible to develop statistical models that identify the underlying relationships between these elements. In doing so, these approaches can provide novel insight into the relative importance, origin, and spread of different Resistance mechanisms, and the agronomic, ecological and evolutionary drivers that dictate the dynamics of Resistance evolution at local to global scales. Emerging technologies in weed surveillance, genomics and Resistance diagnostics, statistics, and data science will greatly facilitate the collection and analysis of large-scale data sets, providing unprecedented potential for epidemiological analyses of the evolution of Herbicide Resistance at landscape scales.
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A generalised individual-based algorithm for modelling the evolution of quantitative Herbicide Resistance in arable weed populations.
Pest Management Science, 2016Co-Authors: Melissa E. Bridges, Micheal D K Owen, Shiv S. Kaundun, Les Glasgow, Paul NeveAbstract:BACKGROUND: Simulation models are useful tools for predicting and comparing the risk of Herbicide Resistance in weed populations under different management strategies. Most existing models assume a monogenic mechanism governing Herbicide Resistance evolution. However, growing evidence suggests that Herbicide Resistance is often inherited in a polygenic or quantitative fashion. Therefore, we constructed a generalised modelling framework to simulate the evolution of quantitative Herbicide Resistance in summer annual weeds. RESULTS: Real-field management parameters based on Amaranthus tuberculatus (Moq.) Sauer (syn. rudis) control with glyphosate and mesotrione in Midwestern US maize-soybean agroecosystems demonstrated that the model can represent evolved Herbicide Resistance in realistic timescales. Sensitivity analyses showed that genetic and management parameters were impactful on the rate of quantitative Herbicide Resistance evolution, whilst biological parameters such as emergence and seed bank mortality were less important. CONCLUSION: The simulation model provides a robust and widely applicable framework for predicting the evolution of quantitative Herbicide Resistance in summer annual weed populations. The sensitivity analyses identified weed characteristics that would favour Herbicide Resistance evolution, including high annual fecundity, large Resistance phenotypic variance and pre-existing Herbicide Resistance. Implications for Herbicide Resistance management and potential use of the model are discussed. (C) 2016 Society of Chemical Industry
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Herbicide Resistance modelling past present and future
Pest Management Science, 2014Co-Authors: Michael Renton, Roberto Busi, Paul Neve, David Thornby, Martin M VilaaiubAbstract:Computer simulation modelling is an essential aid in building an integrated understanding of how different factors interact to affect the evolutionary and population dynamics of Herbicide Resistance, and thus in helping to predict and manage how agricultural systems will be affected. In this review, we first discuss why computer simulation modelling is such an important tool and framework for dealing with Herbicide Resistance. We then explain what questions related to Herbicide Resistance have been addressed to date using simulation modelling, and discuss the modelling approaches that have been used, focusing first on the earlier, more general approaches, and then on some newer, more innovative approaches. We then consider how these approaches could be further developed in the future, by drawing on modelling techniques that are already employed in other areas, such as individual-based and spatially explicit modelling approaches, as well as the possibility of better representing genetics, competition and economics, and finally the questions and issues of importance to Herbicide Resistance research and management that could be addressed using these new approaches are discussed. We conclude that it is necessary to proceed with caution when increasing the complexity of models by adding new details, but, with appropriate care, more detailed models will make it possible to integrate more current knowledge in order better to understand, predict and ultimately manage the evolution of Herbicide Resistance. © 2014 Society of Chemical Industry
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expanding the eco evolutionary context of Herbicide Resistance research
Pest Management Science, 2014Co-Authors: Paul Neve, Michael Renton, Roberto Busi, Martin M VilaaiubAbstract:The potential for human-driven evolution in economically and environmentally important organisms in medicine, agriculture and conservation management is now widely recognised. The evolution of Herbicide Resistance in weeds is a classic example of rapid adaptation in the face of human-mediated selection. Management strategies that aim to slow or prevent the evolution of Herbicide Resistance must be informed by an understanding of the ecological and evolutionary factors that drive selection in weed populations. Here, we argue for a greater focus on the ultimate causes of selection for Resistance in Herbicide Resistance studies. The emerging fields of eco-evolutionary dynamics and applied evolutionary biology offer a means to achieve this goal and to consider Herbicide Resistance in a broader and sometimes novel context. Four relevant research questions are presented, which examine (i) the impact of Herbicide dose on selection for Resistance, (ii) plant fitness in Herbicide Resistance studies, (iii) the efficacy of Herbicide rotations and mixtures and (iv) the impacts of gene flow on Resistance evolution and spread. In all cases, fundamental ecology and evolution have the potential to offer new insights into Herbicide Resistance evolution and management. © 2014 Society of Chemical Industry
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Expanding the eco‐evolutionary context of Herbicide Resistance research
Pest Management Science, 2014Co-Authors: Paul Neve, Michael Renton, Roberto Busi, Martin M. Vila-aiubAbstract:The potential for human-driven evolution in economically and environmentally important organisms in medicine, agriculture and conservation management is now widely recognised. The evolution of Herbicide Resistance in weeds is a classic example of rapid adaptation in the face of human-mediated selection. Management strategies that aim to slow or prevent the evolution of Herbicide Resistance must be informed by an understanding of the ecological and evolutionary factors that drive selection in weed populations. Here, we argue for a greater focus on the ultimate causes of selection for Resistance in Herbicide Resistance studies. The emerging fields of eco-evolutionary dynamics and applied evolutionary biology offer a means to achieve this goal and to consider Herbicide Resistance in a broader and sometimes novel context. Four relevant research questions are presented, which examine (i) the impact of Herbicide dose on selection for Resistance, (ii) plant fitness in Herbicide Resistance studies, (iii) the efficacy of Herbicide rotations and mixtures and (iv) the impacts of gene flow on Resistance evolution and spread. In all cases, fundamental ecology and evolution have the potential to offer new insights into Herbicide Resistance evolution and management. © 2014 Society of Chemical Industry
Michael Renton - One of the best experts on this subject based on the ideXlab platform.
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Modelling the effects of farm management on the spread of Herbicide Resistance
2020Co-Authors: F. Evans, Art J. Diggle, Michael RentonAbstract:Herbicide Resistance is an increasing problem in Australian cropping systems, but little is known about how Resistance spreads and how farmers can manage their paddocks to minimise its spread. This paper presents a modelling framework for predicting biological processes in agriculture, with particular emphasis on the spatial and temporal spread of Herbicide Resistance. It includes a model of the population dynamics of weeds growing in competition with crops, a polygenic model of the development of Herbicide Resistance and gene transfer by means of seed and pollen movement. The modelling framework is used to predict the long-term spread of resistant weeds given different integrated weed management choices combining tillage and Herbicide treatments, as well as new technologies such as seed capture at harvest and precision planting systems that allow different treatments for inter and intra-rows. The model's predictions are used to devise management options that minimise the spread of Herbicide resistant weeds.
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Herbicide Resistance modelling past present and future
Pest Management Science, 2014Co-Authors: Michael Renton, Roberto Busi, Paul Neve, David Thornby, Martin M VilaaiubAbstract:Computer simulation modelling is an essential aid in building an integrated understanding of how different factors interact to affect the evolutionary and population dynamics of Herbicide Resistance, and thus in helping to predict and manage how agricultural systems will be affected. In this review, we first discuss why computer simulation modelling is such an important tool and framework for dealing with Herbicide Resistance. We then explain what questions related to Herbicide Resistance have been addressed to date using simulation modelling, and discuss the modelling approaches that have been used, focusing first on the earlier, more general approaches, and then on some newer, more innovative approaches. We then consider how these approaches could be further developed in the future, by drawing on modelling techniques that are already employed in other areas, such as individual-based and spatially explicit modelling approaches, as well as the possibility of better representing genetics, competition and economics, and finally the questions and issues of importance to Herbicide Resistance research and management that could be addressed using these new approaches are discussed. We conclude that it is necessary to proceed with caution when increasing the complexity of models by adding new details, but, with appropriate care, more detailed models will make it possible to integrate more current knowledge in order better to understand, predict and ultimately manage the evolution of Herbicide Resistance. © 2014 Society of Chemical Industry
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expanding the eco evolutionary context of Herbicide Resistance research
Pest Management Science, 2014Co-Authors: Paul Neve, Michael Renton, Roberto Busi, Martin M VilaaiubAbstract:The potential for human-driven evolution in economically and environmentally important organisms in medicine, agriculture and conservation management is now widely recognised. The evolution of Herbicide Resistance in weeds is a classic example of rapid adaptation in the face of human-mediated selection. Management strategies that aim to slow or prevent the evolution of Herbicide Resistance must be informed by an understanding of the ecological and evolutionary factors that drive selection in weed populations. Here, we argue for a greater focus on the ultimate causes of selection for Resistance in Herbicide Resistance studies. The emerging fields of eco-evolutionary dynamics and applied evolutionary biology offer a means to achieve this goal and to consider Herbicide Resistance in a broader and sometimes novel context. Four relevant research questions are presented, which examine (i) the impact of Herbicide dose on selection for Resistance, (ii) plant fitness in Herbicide Resistance studies, (iii) the efficacy of Herbicide rotations and mixtures and (iv) the impacts of gene flow on Resistance evolution and spread. In all cases, fundamental ecology and evolution have the potential to offer new insights into Herbicide Resistance evolution and management. © 2014 Society of Chemical Industry
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Expanding the eco‐evolutionary context of Herbicide Resistance research
Pest Management Science, 2014Co-Authors: Paul Neve, Michael Renton, Roberto Busi, Martin M. Vila-aiubAbstract:The potential for human-driven evolution in economically and environmentally important organisms in medicine, agriculture and conservation management is now widely recognised. The evolution of Herbicide Resistance in weeds is a classic example of rapid adaptation in the face of human-mediated selection. Management strategies that aim to slow or prevent the evolution of Herbicide Resistance must be informed by an understanding of the ecological and evolutionary factors that drive selection in weed populations. Here, we argue for a greater focus on the ultimate causes of selection for Resistance in Herbicide Resistance studies. The emerging fields of eco-evolutionary dynamics and applied evolutionary biology offer a means to achieve this goal and to consider Herbicide Resistance in a broader and sometimes novel context. Four relevant research questions are presented, which examine (i) the impact of Herbicide dose on selection for Resistance, (ii) plant fitness in Herbicide Resistance studies, (iii) the efficacy of Herbicide rotations and mixtures and (iv) the impacts of gene flow on Resistance evolution and spread. In all cases, fundamental ecology and evolution have the potential to offer new insights into Herbicide Resistance evolution and management. © 2014 Society of Chemical Industry
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Simulation modelling identifies polygenic basis of Herbicide Resistance in a weed population and predicts rapid evolution of Herbicide Resistance at low Herbicide rates
Crop Protection, 2012Co-Authors: Sudheesh Manalil, Michael Renton, Art J. Diggle, Roberto Busi, Stephen B. PowlesAbstract:Abstract The potential for low rates of diclofop-methyl to result in rapid evolution of Herbicide Resistance in a Herbicide-susceptible Lolium rigidum (annual ryegrass) population was demonstrated in a recent crop-field study. In this present study, the data from the crop-field study was used together with simulation modelling to identify possible genetics of the Herbicide Resistance that was selected for. This analysis clearly indicated that the Herbicide Resistance was polygenic. Subsequently, the estimated genetic possibilities were used to parameterise a model of Herbicide Resistance evolution in a simulated crop-field situation, and the potential of different rates of diclofop-methyl (ACCase Herbicide) to cause Herbicide-Resistance evolution in L. rigidum was explored and compared using the calibrated model. The calibrated model outputs indicated that the evolution of diclofop-methyl Resistance would generally be faster at low Herbicide rates than at higher rates due to the rapid selection of minor gene Herbicide Resistance traits at low rates and their subsequent recombination by cross-pollination. The results of the study therefore indicate potential risks in Herbicide rate cutting and highlight the need for careful scientific evaluation of any Herbicide use rate for its potential to select for minor gene Herbicide Resistance from a weed population.