Kleynhans E, Barton M G, Conlong D E, Terblanche J S
Centre for Invasion Biology,Department of Conservation Ecology and Entomology,Faculty of AgriSciences,Stellenbosch University,Stellenbosch,South Africa.
Bull Entomol Res. 2018 Jun;108(3):283-294. doi: 10.1017/S0007485317000712. Epub 2017 Aug 8.
Understanding pest population dynamics and seasonal phenology is a critical component of modern integrated pest-management programs. Accurate forecasting allows timely, cost-effective interventions, including maximum efficacy of, for example, biological control and/or sterile insect technique. Due to the variation in life stage-related sensitivity toward climate, insect pest population abundance models are often not easily interpreted or lack direct relevance to management strategies in the field. Here we apply a process-based (biophysical) model that incorporates climate data with life stage-dependent physiology and life history to attempt to predict Eldana saccharina life stage and generation turnover in sugarcane fields. Fitness traits are modelled at two agricultural locations in South Africa that differ in average temperature (hereafter a cold and a warm site). We test whether the life stage population structures in the field entering winter and local climate during winter directly affect development rates, and therefore interact to determine the population dynamics and phenological responses of E. saccharina in subsequent spring and summer seasons. The model predicts that: (1) E. saccharina can cycle through more generations at the warm site where fewer hours of cold and heat stress are endured, and (2) at the cold site, overwintering as pupae (rather than larvae) confer higher relative fitness and fecundity in the subsequent summer adult moths. The model predictions were compared with a large dataset of field observations from scouting records. Model predictions for larval presence (or absence) generally overlapped well with positive (or negative) scout records. These results are important for integrated pest management strategies by providing a useful foundation for future population dynamics models, and are applicable to a variety of agricultural landscapes, but especially the sugarcane industry of South Africa.
了解害虫种群动态和季节性物候是现代综合害虫管理计划的关键组成部分。准确的预测能够实现及时且具有成本效益的干预措施,包括例如生物防治和/或不育昆虫技术的最大功效。由于害虫在不同生命阶段对气候的敏感性存在差异,害虫种群丰度模型往往难以解释,或者与田间管理策略缺乏直接相关性。在此,我们应用一种基于过程(生物物理)的模型,该模型将气候数据与依赖于生命阶段的生理学和生活史相结合,试图预测甘蔗田中埃氏蔗螟的生命阶段和世代更替。在南非两个平均温度不同的农业地点(以下简称一个寒冷地点和一个温暖地点)对适合度性状进行建模。我们测试进入冬季时田间的生命阶段种群结构以及冬季当地气候是否直接影响发育速率,进而相互作用以确定埃氏蔗螟在随后春季和夏季的种群动态和物候响应。该模型预测:(1)在温暖地点,埃氏蔗螟能够经历更多世代,因为在那里遭受寒冷和热应激的时间较少;(2)在寒冷地点,以蛹(而非幼虫)越冬会使随后夏季成虫蛾具有更高的相对适合度和繁殖力。将模型预测结果与来自侦察记录的大量田间观测数据集进行了比较。幼虫存在(或不存在)的模型预测通常与积极(或消极)的侦察记录有很好的重叠。这些结果对于综合害虫管理策略非常重要,为未来的种群动态模型提供了有用的基础,并且适用于各种农业景观,尤其是南非的甘蔗产业。