Development of a novel trait-based approach to understand how and why optimal trap design for forest pests varies across taxa

开发一种基于性状的新型方法，以了解森林害虫的最佳诱捕器设计如何以及为何因类群而异

• 批准号: NE/V019333/1
• 负责人: Robbie Girling
• 金额: $ 1.07万
• 依托单位: University of Reading
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FV019333%2F1
• 关键词: Development; novel; trait; based; approach

NERC : Tom Staton : NE/R012229/1Insects are of significant importance for both biodiversity conservation, due to severe global declines, and economic security, due to the potential for pest species to cause damage to agriculture and forestry. The threat caused by insect pests to forestry is predicted to worsen under a changing climate and global trade. Effective survey and detection tools, which include trapping programmes, are needed to provide early warnings of pest outbreaks and provide information to guide decisions about the need for pest management action. Early detection of forest pest outbreaks is critical to maximize the likelihood of control measures being successful. However, detection programs are currently operationally and conceptually inadequate because we do not have a good understanding as to how and why the design of insect traps varies with pest species. This project aims to apply a novel analytical approach to evaluate the effect of trap design on the detection of forest pests according to their traits, such as body size and other physical characteristics, rather than according to traditional taxonomic classifications. Trait approaches are becoming increasingly popular in ecological studies because they help to improve the interpretability and predictability of ecological processes, but have yet to be applied in this context. The findings will therefore inform the development of more effective detection programmes for forest insect pests in Canada and globally, and meets identified research needs by both the UK and Canadian governments to improve detection and monitoring survey designs for forest pests. The project will utilise existing datasets containing information on forest pest captures and trap design, both published and unpublished. A new trait database will be developed under the project, using stored specimens of forest pests held by the Canadian Forestry Service and in museum collections, to measure physical characteristics (traits) of forest pest species. This new database will be used to carry out the novel trait-based analysis to investigate how and why insect pest captures vary with trap design. The database could also have wider applications for other studies, including an ongoing PhD project at the University of Toronto. The project will be based at the University of Toronto, in collaboration with the Canadian Forestry Service and the University of Reading.

NERC：汤姆·斯塔顿：NE/R 012229/1昆虫对生物多样性保护（由于全球严重衰退）和经济安全（由于有害物种可能对农业和林业造成损害）都具有重要意义。在气候变化和全球贸易的影响下，虫害对林业的威胁预计将进一步加剧。需要有效的调查和检测工具，包括诱捕方案，以提供虫害爆发的早期警报，并提供信息，指导关于虫害管理行动的必要性的决定。及早发现森林虫害的爆发对于最大限度地提高控制措施取得成功的可能性至关重要。然而，检测程序目前在操作和概念上是不够的，因为我们没有一个很好的理解，如何以及为什么昆虫陷阱的设计与害虫物种的变化。该项目旨在采用一种新的分析方法，根据其特征，如身体大小和其他物理特征，而不是根据传统的分类学分类，评估诱捕器设计对检测森林害虫的影响。特征方法在生态学研究中越来越受欢迎，因为它们有助于提高生态过程的可解释性和可预测性，但尚未在此背景下应用。因此，研究结果将为加拿大和全球制定更有效的森林害虫检测计划提供信息，并满足英国和加拿大政府确定的研究需求，以改善森林害虫的检测和监测调查设计。该项目将利用现有的数据集，其中包括已公布和未公布的关于森林害虫捕获和诱捕器设计的信息。将在该项目下开发一个新的特征数据库，利用加拿大林业局保存的和博物馆收藏的森林害虫标本，测量森林害虫物种的物理特征（特征）。这个新的数据库将用于进行新的基于特征的分析，以调查昆虫害虫捕获量如何以及为什么随着诱捕器设计而变化。该数据库还可以更广泛地应用于其他研究，包括多伦多大学正在进行的博士项目。该项目将设在多伦多大学，与加拿大林业局和阅读大学合作。