Crop, semi-natural, and water features of the cotton agroecosystem as indicators of risk of infestation of two plant bug (Hemiptera: Miridae) pests.

IF 2.4 Q1 ENTOMOLOGY
Frontiers in insect science Pub Date : 2024-11-25 eCollection Date: 2024-01-01 DOI:10.3389/finsc.2024.1496184
Michael J Brewer
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Abstract

Introduction: This study considers concepts and tools of landscape ecology and geographic information systems (GIS) to prioritize insect monitoring in large-scale crops, using the cotton agroecosystem of the Texas Gulf Coast and two plant bug species (Creontiades signatus Distant and Pseudatomoscelis seriatus (Reuter) [Hemiptera: Miridae]) as a case study. The two species differed in host plants and time span as cotton pests.

Methods: C. signatus and P. seriatus abundance in early growth of cotton were regressed on landscape metrics. Comparisons of three approaches to select landscape variables in stepwise multiple regressions were made across spatial scales and two weeks of insect data extracted from monitoring of 21 cotton fields, years 2010 through 2013.

Results and discussion: The spatial variation of plant bug abundance and the landscape features were substantial, aiding the regression approach. For full stepwise regression models using 18 landscape variables, regression model fit using C. signatus data was modestly better in week one of sampling when C. signatus adults and young nymphs were detected (R 2 range of 0.56 to 0.82), as compared with model fit at week two (R 2 range of 0.49 to 0.77). The smallest scale (2.5 km radius) models had the greatest number of variables selected and highest R 2, while two broader scales (5 and 10 km) and truncating the models to three variables produced a narrower range of R 2s (0.49 to 0.62) and more consistent entry of variables. Wetland composition had a consistent positive association with C. signatus abundance, supporting its association with seepweeds which are common in coastal wetlands. When selected, the composition of cotton and grassland/shrubland/pasture also had a positive association with C. signatus abundance. Aggregation metrics were also relevant, but composition metrics in the models were arguably more easily utilized in prioritizing insect monitoring. In contrast, there were few significant regressions using P. seriatus data, possibly due to the widespread distribution of its weedy host plants and lower abundance. Overall, selected landscape features served as indicators of C. signatus infestation potential in cotton particularly grown near coastal wetlands, but landscape features were not useful for P. seriatus infestation potential in cotton.

棉花农业生态系统的作物、半天然和水分特征作为两种植物害虫(半翅目:盲蝽科)侵害风险的指标。
摘要:本研究以德克萨斯州墨西哥湾沿岸的棉花农业生态系统和两种植物昆虫(Creontiades signatus Distant和Pseudatomoscelis seriatus (Reuter)[半翅目:Miridae])为例,结合景观生态学和地理信息系统(GIS)的概念和工具,对大规模作物昆虫进行优先监测。两种作为棉花害虫的寄主植物和时间跨度不同。方法:采用景观指标对棉花生长早期的信号假单胞菌和系列假单胞菌丰度进行回归分析。以2010 ~ 2013年21块棉田2周昆虫监测数据为样本,在空间尺度上比较了3种选择景观变量的逐步多元回归方法。结果与讨论:植物昆虫丰度和景观特征的空间变异较大,有利于回归分析。对于采用18个景观变量的全逐步回归模型,在采样第1周,当检测到白桦成虫和幼若虫时,使用白桦数据的回归模型拟合(r2范围为0.56 ~ 0.82)略好于第2周的模型拟合(r2范围为0.49 ~ 0.77)。最小尺度(2.5 km半径)模式选择的变量数量最多,r2最高,而两个更大尺度(5 km和10 km)模式截断为3个变量,r2范围更窄(0.49 ~ 0.62),变量输入更一致。湿地组成与C. signatus丰度呈一致的正相关,支持其与滨海湿地常见的海藻的关联。棉花和草地/灌丛/牧场的组成也与柽柳的丰度呈正相关。聚集指标也是相关的,但模型中的组成指标可以更容易地用于昆虫监测的优先级。相比之下,seriatus数据几乎没有显著的回归,可能是由于其杂草寄主植物分布广泛且丰度较低。总体而言,所选景观特征可作为棉花特别是滨海湿地附近生长的棉花棉铃虫侵染潜力的指标,但景观特征对棉铃虫侵染潜力的影响不大。
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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1.80
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