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

NERC: Tom Staton: NE/ r012229 /1昆虫在生物多样性保护和经济安全方面都具有重要意义，这是由于全球范围内昆虫数量的严重下降，而害虫物种可能对农业和林业造成损害。在气候变化和全球贸易的影响下，虫害对林业造成的威胁预计会加剧。需要有效的调查和检测工具，包括诱捕方案，以提供病虫害爆发的早期预警，并提供信息，指导关于需要采取病虫害管理行动的决定。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充分的，因为我们没有很好地理解昆虫陷阱的设计如何以及为什么随着害虫种类的不同而变化。本项目旨在应用一种新的分析方法，根据森林害虫的特征（如体型和其他物理特征）来评估陷阱设计对检测害虫的影响，而不是根据传统的分类分类。性状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，但尚未在这一背景下应用。因此，这些发现将为制定加拿大和全球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，以改进森林害虫的检测和监测调查设计。该项目将利用现有数据集，包括已公布和未公布的森林害虫捕获和捕集器设计信息。将在该项目下开发一个新的特征数据库，利用加拿大林业局和博物馆收藏的森林害虫标本来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，以调查害虫捕获如何以及为什么随陷阱设计而变化。该数据库还可以广泛应用于其他研究，包括多伦多大学正在进行的一个博士项目。该项目将以多伦多大学为基地，与加拿大林业局和雷丁大学合作。

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.