Forecasting interannual abundance of Helicoverpa zea (Lepidoptera: Noctuidae).

IF 1.8 3区 农林科学 Q2 ENTOMOLOGY
Samuel T Wallace, Natalie G Nelson, Dominic D Reisig, Anders S Huseth
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引用次数: 0

Abstract

Corn earworm, Helicoverpa zea Boddie (Lepidoptera: Noctuidae), is a common herbivore that causes economic damage to agronomic and specialty crops across North America. The interannual abundance of H. zea is closely linked to climactic variables that influence overwintering survival, as well as within-season host plant availability that drives generational population increases. Although the abiotic and biotic drivers of H. zea populations have been well documented, prior temporal H. zea modeling studies have largely focused on mechanistic/simulation approaches, long term distribution characterization, or degree day-based phenology within the growing season. While these modeling approaches provide insight into H. zea population ecology, growers remain interested in approaches that forecast the interannual magnitude of moth flights which is a key knowledge gap limiting early warning before crops are planted. Our study used trap data from 48 site-by-year combinations distributed across North Carolina between 2008 and 2021 to forecast H. zea abundance in advance of the growing season. To do this, meteorological data from weather stations were combined with crop and soil data to create predictor variables for a random forest H. zea forecasting model. Overall model performance was strong (R2 = 0.92, RMSE = 350) and demonstrates a first step toward development of contemporary model-based forecasting tools that enable proactive approaches in support of integrated pest management plans. Similar methods could be applied at a larger spatial extent by leveraging national gridded climate and crop data paired with trap counts to expand forecasting models throughout the H. zea overwintering range.

玉米螺旋蚧年际丰度预测(鳞翅目:夜蛾科)。
玉米耳虫,Helicoverpa zea Boddie(鳞翅目:夜蛾科),是一种常见的食草动物,对整个北美的农艺和特种作物造成经济损失。玉米玉米的年际丰度与影响越冬生存的气候变量密切相关,也与季节内寄主植物的可用性密切相关,后者驱动代际种群增加。尽管玉米玉米种群的非生物和生物驱动因素已经得到了很好的记录,但之前的玉米玉米模型研究主要集中在生长季节的机械/模拟方法、长期分布特征或基于天数的物候学上。虽然这些建模方法提供了对玉米螟种群生态的深入了解,但种植者仍然对预测飞蛾年际飞行幅度的方法感兴趣,这是限制作物种植前预警的关键知识差距。我们的研究使用了2008年至2021年间分布在北卡罗来纳州的48个站点按年组合的陷阱数据,以预测玉米玉米生长季节之前的丰度。为了做到这一点,气象站的气象数据与作物和土壤数据相结合,为随机森林玉米瘟预测模型创建预测变量。总体而言,模型表现良好(R2 = 0.92, RMSE = 350),表明朝着开发基于模型的现代预测工具迈出了第一步,这些工具能够采用主动方法来支持害虫综合管理计划。类似的方法可以在更大的空间范围内应用,利用国家网格化的气候和作物数据与陷阱计数配对,以扩展整个玉米玉米越冬范围的预测模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Environmental Entomology
Environmental Entomology 生物-昆虫学
CiteScore
3.90
自引率
5.90%
发文量
97
审稿时长
3-8 weeks
期刊介绍: Environmental Entomology is published bimonthly in February, April, June, August, October, and December. The journal publishes reports on the interaction of insects with the biological, chemical, and physical aspects of their environment. In addition to research papers, Environmental Entomology publishes Reviews, interpretive articles in a Forum section, and Letters to the Editor.
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