five

Curtiss et al. Plume Reach Data file

收藏
DataCite Commons2024-11-05 更新2024-07-13 收录
下载链接:
https://rex.libraries.wsu.edu/esploro/outputs/dataset/99900972040801842
下载链接
链接失效反馈
官方服务:
资源简介:
<strong>ABSTRACT: </strong><em>Cydia pomonella </em>(L.) dispersion in mating disrupted commercial apple orchards has been little studied. Males’ dispersion is better understood from non-mating disrupted orchards; female dispersion is not well explored, nor if mating disruption alters male dispersion. Sterile <em>C. pomonella</em> recapture data from single-trap multiple-release experiments using PHEROCON® CM-DA COMBO™ Lure + AA Lure-baited orange Pherocon VI delta traps was interpreted to determine pheromone/kairomone lure-baited trap effective area, trap deployment density for effective monitoring, and absolute male and female <em>C. pomonella</em> density in mating disrupted Washington commercial apple orchards. The maximum plume reach of the pheromone/kairomone lure in mating disrupted orchards was < 5 meters from the baited trap for both sexes. Maximum dispersive distances for 95% of the released <em>C. pomonella</em> in mating disrupted orchards was 106 and 135 meters for males and females, yielding trapping areas of 3.87 ha and 6.16 ha, respectively. Estimates were consistent across three growing seasons and represent the first records of male and female dispersal distance and monitoring trap efficacy from commercial <em>C. pomonella</em> mating disrupted apple orchards. With relevance to commercial monitoring programs and economic thresholds in mating disrupted orchards, traps should be deployed at a density of one per 3-6 hectares; capture of a single male or female <em>C. pomonella</em> corresponds to at least 82-104 <em>C. pomonella</em> within the 3-6 ha trapping area. This refined <em>C. pomonella</em> capture interpretation in pheromone/kairomone-baited traps in mating disrupted commercial apple orchards yields more precise damage estimates and assists in insecticide-use decision making.
提供机构:
Washington State University
创建时间:
2023-05-10
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作