An individual-based model of the evolution of pesticide resistance in heterogeneous environments : Control of meligethes aeneus population in oilseed rape crops

Copyright: © 2014 Stratonovitch et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Preventing a pest population from damaging an agricultural crop and, at the same time, preventing the development of pesticide resistance is a major challenge in crop protection. Understanding how farming practices and environmental factors interact with pest characteristics to influence the spread of resistance is a difficult and complex task. It is extremely challenging to investigate such interactions experimentally at realistic spatial and temporal scales. Mathematical modelling and computer simulation have, therefore, been used to analyse resistance evolution and to evaluate potential resistance management tactics. Of the many modelling approaches available, individual-based modelling of a pest population offers most flexibility to include and analyse numerous factors and their interactions. Here, a pollen beetle (Meligethes aeneus) population was modelled as an aggregate of individual insects inhabiting a spatially heterogeneous landscape. The development of the pest and host crop (oilseed rape) was driven by climatic variables. The agricultural land of the landscape was managed by farmers applying a specific rotation and crop protection strategy. The evolution of a single resistance allele to the pyrethroid lambda cyhalothrin was analysed for different combinations of crop management practices and for a recessive, intermediate and dominant resistance allele. While the spread of a recessive resistance allele was severely constrained, intermediate or dominant resistance alleles showed a similar response to the management regime imposed. Calendar treatments applied irrespective of pest density accelerated the development of resistance compared to ones applied in response to prescribed pest density thresholds. A greater proportion of springs own oilseed rape was also found to increase the speed of resistance as it increased the period of insecticide exposure. Our study demonstrates the flexibility and power of an individual-based model to simulate how farming practices affect pest population dynamics, and the consequent impact of different control strategies on the risk and speed of resistance development.Peer reviewe

Optimizing pesticide spray coverage using a novel web and smartphone tool, SnapCard

International audienceThe overuse of pesticides leads to contamination of water and food. Therefore, there is a need for tools and strategies to optimize pesticide application. Here we present SnapCard, a user-friendly and freely available decision support tool for farmers and agricultural consultants, available at snapcard.agric.wa.gov.au. SnapCard allows to predict, measure, and archive pesticide spray coverage quantified from water-sensitive spray cards. Variables include spray settings such as nozzle orifice size, sprayer speed, water carrier rate and adjuvant, and weather variables such as barometric pressure, relative humidity, temperature, and wind speed at ground level. We use separate regression models for four nozzles types. Our results showed that there are strong and positive correlations between water carrier rate and spray coverage for all four nozzle types. Moreover, sprayer speed is highly negatively correlated with obtained spray coverage. In addition, there is no consistent effect of either nozzle type or use of a particular adjuvant, across water carrier intervals. We conclude that varying combinations of spray settings and weather conditions caused marked ranges of spray coverages among the four nozzle types, thus highlighting the importance of selecting the right nozzle orifice size and type. We demonstrate that realistic scenarios of environmental conditions and spray settings can lead to predictions of very low spray coverage with at least one of the four nozzle types. We discuss how the novel and freely available smartphone app, SnapCard, can be used to optimize spray coverage, reduce spray drift, and minimize the risk of resistance development in target pest populations

Behavioral Avoidance - Will Physiological Insecticide Resistance Level of Insect Strains Affect Their Oviposition and Movement Responses?

Agricultural organisms, such as insect herbivores, provide unique opportunities for studies of adaptive evolutionary processes, including effects of insecticides on movement and oviposition behavior. In this study, Brassica leaves were treated with one of two non-systemic insecticides and exposed to two individual strains (referred to as single or double resistance) of diamondback moth (Plutella xylostella) (DBM) exhibiting physiological resistance. Behavioral responses by these two strains were compared as part of characterizing the relative effect of levels of physiological resistance on the likelihood of insects showing signs of behavioral avoidance. For each DBM strain, we used choice bioassays to quantify two possible types of behavioral avoidance: 1) females ovipositing predominantly on leaf surfaces without insecticides, and 2) larvae avoiding insecticide-treated leaf surfaces. In three-choice bioassays (leaves with no pesticide, 50% coverage with pesticide, or 100% coverage with pesticide), females from the single resistance DBM strain laid significantly more eggs on water treated leaves compared to leaves with 100% insecticide coverage (both gamma-cyhalothrin and spinetoram). Females from the double resistance DBM strain also laid significantly more eggs on water treated leaves compared to leaves with 100% gamma-cyhalothrin, while moths did not adjust their oviposition behavior in response to spinetoram. Larvae from the single resistance DBM strain showed a significant increase in mobility in response to both insecticides and avoided insecticide-treated portions of leaves when given a choice. On the other hand, DBM larvae from the double resistance strain showed a significant decrease in mobility in response to insecticides, and they did not avoid insecticide-treated portions of leaves when given a choice. Our results suggest that pest populations with physiological resistance may show behavioral avoidance, as resistant females avoided oviposition on leaves without gamma-cyhalothrin. Thus, physiological resistance and behavioral avoidance do not appear to be controlled by the same selection pressures, and the mechanisms responsible for behavioral avoidance may vary among life stages. Our analysis also suggested that a population with lesser physiological resistance to insecticides may be under a stronger selection pressure and therefore be more likely to develop avoidance behaviors than a population with higher levels of physiological resistance