Confronting herbicide resistance with cooperative management

Delaying quantitative resistance to pesticides and antibiotics

How can we best vary the application of pesticides and antibiotics to delay resistance evolution? Previous theoretical comparisons of deployment strategies have focused on qualitative resistance traits and have mostly assumed that resistance alleles are already present in a population. But many real resistance traits are quantitative, and the evolution of resistant genotypes in the field may depend on de novo mutation and recombination. Here, I use an individual-based, forward-time, quantitative-genetic simulation model to investigate the evolution of quantitative resistance. I evaluate the performance of four application strategies for delaying resistance evolution, to wit, the (1) sequential, (2) mosaic, (3) periodic, and (4) combined strategies. I find that which strategy is best depends on initial efficacy. When at the onset, xenobiotics completely prevent reproduction in treated demes, a combined strategy is best. On the other hand, when populations are partially resistant, the combined strategy is inferior to mosaic and periodic strategies, especially when resistance alleles are antagonistically pleiotropic. Thus, the optimal application strategy for managing against the rise of quantitative resistance depends on pleiotropy and whether or not partial resistance is already present in a population. This result appears robust to variation in pest reproductive mode and migration rate, direct fitness costs for resistant phenotypes, and the extent of refugial habitats.

Modeling the evolution of herbicide resistance in weed species with a complex life cycle

A growing number of weed species have evolved resistance to herbicides in recent years, which causes an immense financial burden to farmers. An increasingly popular method of weed control is the adoption of crops that are resistant to specific herbicides, which allows farmers to apply the herbicide during the growing season without harming the crop. If such crops are planted in the presence of closely related weed species, it is possible that resistance genes could transfer from the crop species to feral populations of the wild species via gene flow and become stably introgressed under ongoing selective pressure by the herbicide. We use a density-dependent matrix model to evaluate the effect of planting such crops on the evolution of herbicide resistance under a range of management scenarios. Our model expands on previous simulation studies by considering weed species with a more complex life cycle (perennial, rhizomatous weed species), studying the effect of environmental variation in herbicide effectiveness, and evaluating the role of common simplifying genetic assumptions on resistance evolution. Our model predictions are qualitatively similar to previous modeling studies using species with a simpler life cycle, which is, crop rotation in combination with rotation of herbicide site of action effectively controls weed populations and slows the evolution of herbicide resistance. We find that ignoring the effect of environmental variation can lead to an over- or under-prediction of the speed of resistance evolution. The effect of environmental variation in herbicide effectiveness depends on the resistance allele frequency in the weed population at the beginning of the simulation. Finally, we find that degree of dominance and ploidy level have a much larger effect on the predicted speed of resistance evolution compared to the rate of gene flow.

Does organizational participation affect farmers' behavior in adopting the joint mechanism of pest and disease control? A study of Meixian County, Shaanxi Province

BACKGROUND

In China, there are a lack of well-established relationships regarding farmers' behavior and participation in farmer organizations. The main objective of this study was to explore the effects and mechanisms of organizational participation in the joint control of pest and disease among kiwifruit growers (within the members of organizations). To fulfill this objective, the present study utilized survey data from 577 kiwifruit growers collected from Meixian County, Shaanxi Province, China. A combined method utilizing the instrumental variable (IV) ordered probit and bootstrap multiple mediation effect models were employed to determine the effects of participation by farmers' organizations in the joint control of pest and disease among kiwifruit growers.

RESULTS

A positive relationship was found between organizational participation and the joint control of pests and diseases. The empirical analysis of this study found that organizational support, organizational learning and organizational norms have mediating effects in the process of farmers' participation in the joint control of pests and disease. It is essential to go beyond individual behavior and tackle group decision-making at the farm level.

CONCLUSION

This study found a positive effect of organizational participation in joint pest and disease control mechanisms. Moreover, whether the farm is situated in the demonstration zone for kiwifruit cultivation, planting experience, planting area, whether there are people in the family who are village cadres, and the number of older adults in the family significantly positively affect the degree of pest and disease control. © 2020 Society of Chemical Industry.

To meet grand challenges, agricultural scientists must engage in the politics of constructive collective action

Agriculture now faces grand challenges, with crucial implications for the global future. These include the need to increase production of nutrient-dense food, to improve agriculture's effects on soil, water, wildlife, and climate, and to enhance equity and justice in food and agricultural systems. We argue that certain politics of constructive collective action-and integral involvement of agricultural scientists in these politics-are essential for meeting grand challenges and other complex problems facing agriculture in the 21st century. To spur reflection and deliberation about the role of politics in the work of agricultural scientists, we outline these politics of constructive collective action. These serve to organize forceful responses to grand challenges through coordinated and cooperative action taken by multiple sectors of society. In essence, these politics entail (1) building bonds of affinity within a heterogenous network, (2) developing a shared roadmap for collective action, and (3) taking sustained action together. These emerging politics differ markedly from more commonly discussed forms of political activity by scientists, e.g., policy advisory, policy advocacy, and protest. We present key premises for our thesis, and then describe and discuss a politics of constructive collective action, the necessary roles of agricultural scientists, and an agenda for exploring and expanding their engagement in these politics.

Evolution of Glyphosate-Resistant Weeds

Widespread adoption of glyphosate-resistant crops and concomitant reliance on glyphosate for weed control set an unprecedented stage for the evolution of herbicide-resistant weeds. There are now 48 weed species that have evolved glyphosate resistance. Diverse glyphosate-resistance mechanisms have evolved, including single, double, and triple amino acid substitutions in the target-site gene, duplication of the gene encoding the target site, and others that are rare or nonexistent for evolved resistance to other herbicides. This review summarizes these resistance mechanisms, discusses what is known about their evolution, and concludes with some of the impacts glyphosate-resistant weeds have had on weed management.

Rotations and mixtures of soil-applied herbicides delay resistance

BACKGROUND

Weed resistance to foliar herbicides has dramatically increased worldwide in the last two decades. As a consequence, current practices of weed management have changed, with an increased adoption of soil-applied herbicides to restore control of herbicide-resistant weeds. We foresee metabolism-based resistance and cross-resistance to soil-applied herbicides as a potential global consequence to the increased and widespread adoption of new and old soil-applied herbicides. Thus, the aim of this study is to use computer simulation modelling to quantify and rank the risk of weeds evolving resistance to soil-applied herbicides under different usage strategies (single herbicide use, rotations and mixtures) and population genetic hypotheses.

RESULTS

Simulations indicate that without rotation it takes twice as long to select for resistance to a particular soil-applied herbicide - trifluralin - than to any other herbicide option considered. Relative to trifluralin-only use, simple herbicide rotation patterns have no effect in delaying resistance, whereas more complex rotation patterns can delay resistance two- or three-fold. Herbicide mixtures further delay resistance up to six-fold in comparison to single use or simple herbicide rotations.

CONCLUSION

By computer modelling simulations we demonstrate that mixtures maximize herbicide effectiveness and the selection heterogeneity of soil-applied herbicides, and delay herbicide resistance evolution in weedy plants. Our study is consistent with previous state-of-art scientific evidence (i.e. epidemiological and modelling studies across different systems and pests) and extension efforts (i.e. 'rotate herbicide mixtures') to provide insight to manage the selection and evolution of weed resistance. © 2019 Society of Chemical Industry.