Predicting the effects of climate change on the microbial and chemical control of agricultural pests such as obliquebanded leafroller in apple

控制农业害虫对加拿大农业部门的成功和可持续性至关重要。然而，气候变化威胁着这一目标。 据预测，气候变化将改变杀虫剂杀死农业害虫的能力。例如，热浪在加拿大的频率正在增加（加拿大气候地图集，https://climateatlas.ca），其可以影响昆虫害虫对化学品的敏感性（例如Janssens等人，2017）和微生物（例如Seehausen等人，2017）控制剂。我们建议演示热浪将如何影响化学和微生物控制剂的有效性Obliqebanded Leafroller（OBLR）（Choristoneura rosaceana），苹果树的害虫。 为了能够预测热浪对OBLR和其他害虫的影响，我们需要了解热浪如何改变昆虫的生理机能。 我们将使用分子，生物化学和生理学方法来量化这种影响。 我们还将直接测试农药对OBLR的影响，并将这些数据与生理数据相关联。 我们将利用这些信息为苹果种植者开发一个预测模型。它将允许农民在热浪期间和之后调整杀虫剂的使用，以最低限度的杀虫剂提供最大的控制。 我们将以易于使用的格式为苹果种植者提供这些信息（例如iPhone应用程序）。 虽然这项建议的重点将是OBLR，但这项研究将为极端天气事件（即热浪）期间其他农业害虫的类似模型的开发提供一个框架。 我们已经组建了一个拥有必要的科学和数学专业知识的团队。 我们与AAFC的科学家合作，他们将对实验室开发的解决方案进行严格的现场测试，以确定其对真实的世界情况的适用性。 该团队的AAFC成员还与食品生产商有联系，可以将实验室和实地研究转化为有用的解决方案（即改变害虫管理实践）。

Controlling agricultural pests is critical for the success and sustainability of Canada's agricultural sector. However, climate change threatens this goal. Climate change is predicted to alter the ability of pesticides to kill agricultural pests. For example, heat waves, whose frequency in Canada is increasing (Climate Atlas of Canada, https://climateatlas.ca), can affect the sensitivity of insect pests to chemical (e.g. Janssens et al., 2017) and microbial (e.g. Seehausen et al., 2017) control agents. We propose to demonstrate how heat waves will impact the effectiveness of chemical and microbial control agents of the Obliqebanded Leafroller (OBLR) (Choristoneura rosaceana), a pest of apple trees. To be able to predict the effect of heat waves on OBLR, and other pests, we need to understand how heat waves alter insect physiology. We will use molecular, biochemical, and physiological methods to quantify this effect. We will also test the effect of pesticides on OBLR directly and correlate these data with the physiological data. We will use this information to develop a predictive model for apple growers. It will allow farmers to adjust their pesticide use during and after a heat wave to provide maximum control with the minimum required pesticide. We will provide this information in an easy-to-use format for apple growers (e.g. iPhone app). Although the focus of this proposal will be on OBLR, this study will provide a framework for the development of similar models for other agricultural pests during extreme weather events (i.e. heat waves). We have assembled a team that has the necessary scientific and mathematical expertise. We have partnered with scientists from AAFC who will rigorously field test solutions that are developed in the lab to determine their applicability to real world situations. The AAFC members of the team also have connections to food producers and can translate lab and field research into useful solutions (i.e. changes in pest management practice).