five

Data for Roadside Surveys as a Method for Nonlethal Insect MonitoringPsyche: A Journal of Entomology

收藏
DataCite Commons2025-06-30 更新2026-04-25 收录
下载链接:
https://figshare.com/articles/dataset/Data_for_b_Roadside_surveys_as_a_method_for_sustainable_long-term_insect_monitoring_b_/28370162/3
下载链接
链接失效反馈
官方服务:
资源简介:
Insects are a group of megadiverse and highly dynamic organisms, which makes them difficult to survey. At the same time, we have increasing concerns about declines in insect biomass and diversity, which could have serious implications for ecosystem functioning. Current methods of insect monitoring are high in cost and labor and expertise intensive, often requiring large amounts of physical storage space that must be maintained indefinitely, making them difficult to sustain to the degree and extent that would be required to track population level changes in insect species at local or regional scales. Moreover, there are concerns about the potential role of destructive sampling methods in exacerbating already declining groups of insects. Because of this, sustainable, low-cost methods of monitoring and surveying are needed. I combined modern technological methods, including photographic vouchers and community science programs (i.e. iNaturalist), and surveys of insect roadkill to test as a potential sustainable method of monitoring insect populations. I repeated these surveys on a weekly basis under appropriate weather conditions along a highway bridge for the duration of a year and recorded 4,917 specimens representing 264 species and genera. I found this method promising for sustainable monitoring because photographic vouchers required less time and space to use and maintain, and using the expertise of community scientists lowered initial barriers to participation. This method was also straightforward to repeat without adding significant bias. Finally, the roadkill surveys avoided additional insect mortality as they involved insects that have already been killed by vehicular traffic.
提供机构:
figshare
创建时间:
2025-06-30
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