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一种针对科罗拉多州麦田中小麦茎蜂(膜翅目:茎蜂科)的新的生长度日物候模型。

A new growing degree-day phenology model for wheat stem sawfly (Hymenoptera: Cephidae) in Colorado wheat fields.

作者信息

Vieira Henrique V, Bradford Benjamin Z, Osterholzer Adam, Peirce Erika S, Cockrell Darren, Peairs Frank, Frost Kenneth, Groves Russell, Nachappa Punya

机构信息

Department of Agricultural Biology, Colorado State University, Fort Collins, Colorado, United States of America.

Department of Entomology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.

出版信息

PLoS One. 2025 Apr 7;20(4):e0320497. doi: 10.1371/journal.pone.0320497. eCollection 2025.

DOI:10.1371/journal.pone.0320497
PMID:40193348
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11975124/
Abstract

Wheat stem sawfly (WSS), Cephus cinctus (Hymenoptera: Cephidae), is a native grass-feeding insect and one of the most important pests of wheat in North America. Yield losses from WSS can be due to stem boring and/or stem cutting which causes plants to lodge. Current methods, such as solid stem varieties and insecticides, do not effectively control WSS. A better understanding of WSS emergence, population size, and related environmental factors is critical to building efficient and effective integrated pest management (IPM) strategies for this pest. In this study, wheat fields were sampled for adult WSS from mid-April to the end of June between 2011 and 2023 in several field sites in two locations in Colorado. This multi-year data created a phenology model that predicts adult WSS emergence and population peak based on growing degree-day (GDD). The inter-annual variability in emergence timing based on calendar date was substantially reduced when using a GDD model with a base temperature of 10°C, an upper threshold of 30°C, and a biofix of Jan 1. The model predicted initial WSS emergence at 148 GDD, population peak at 224 GDD, and decline at 354 GDD. We also modeled the effects of environmental factors on mean WSS populations at each field site, finding that higher WSS populations are associated with longer emergence periods, less precipitation before emergence, milder temperatures during emergence, and milder maximum temperatures before and during emergence. By analyzing multiple years of comprehensive phenology data, we provide robust models to guide adult WSS forecasting and monitoring for the first time. Further, this data will aid in decision-making related to timely and effective management strategies to suppress populations of WSS.

摘要

小麦茎蜂(WSS),Cephus cinctus(膜翅目:茎蜂科),是一种以禾本科植物为食的本土昆虫,也是北美小麦最重要的害虫之一。小麦茎蜂造成的产量损失可能是由于茎部蛀食和/或茎部切断,从而导致植株倒伏。目前的方法,如实心茎品种和杀虫剂,无法有效控制小麦茎蜂。更好地了解小麦茎蜂的羽化、种群规模及相关环境因素,对于制定针对该害虫的高效综合虫害管理(IPM)策略至关重要。在本研究中,于2011年至2023年期间,在科罗拉多州两个地点的多个田间地头,从4月中旬至6月底对成年小麦茎蜂进行了采样。这些多年的数据创建了一个物候模型,该模型基于生长度日(GDD)预测成年小麦茎蜂的羽化和种群峰值。当使用基础温度为10°C、上限温度为30°C且生物固定日为1月1日的GDD模型时,基于日历日期的羽化时间的年际变异性显著降低。该模型预测小麦茎蜂初始羽化时间为148 GDD,种群峰值为224 GDD,种群数量下降时间为354 GDD。我们还对环境因素对每个田间地头小麦茎蜂平均种群数量的影响进行了建模,发现较高的小麦茎蜂种群数量与较长的羽化期、羽化前较少的降水量、羽化期间较温和的温度以及羽化前和羽化期间较温和的最高温度相关。通过分析多年的综合物候数据,我们首次提供了强大的模型来指导成年小麦茎蜂的预测和监测。此外,这些数据将有助于制定与及时有效管理策略相关的决策,以抑制小麦茎蜂的种群数量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3131/11975124/186b9b083796/pone.0320497.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3131/11975124/5952c49eccd8/pone.0320497.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3131/11975124/bc80dff630e2/pone.0320497.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3131/11975124/ca55de26cbcb/pone.0320497.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3131/11975124/3c3e4444877e/pone.0320497.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3131/11975124/186b9b083796/pone.0320497.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3131/11975124/5952c49eccd8/pone.0320497.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3131/11975124/bc80dff630e2/pone.0320497.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3131/11975124/ca55de26cbcb/pone.0320497.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3131/11975124/3c3e4444877e/pone.0320497.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3131/11975124/186b9b083796/pone.0320497.g005.jpg

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