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

由于全球生物多样性的严重下降，以及由于害虫物种可能对农业和林业造成损害而造成的经济安全，化石对于生物多样性保护和经济安全都具有重要意义。在气候变化和全球贸易的情况下，虫害对林业造成的威胁预计将进一步恶化。需要有效的调查和检测工具，其中包括诱捕方案，以提供虫害暴发的早期预警，并提供信息，以指导关于是否需要采取虫害管理行动的决定。及早发现森林病虫害暴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，目前的检测计划在操作和概念上都是不够的，因为我们没有很好地了解昆虫陷阱的设计如何以及为什么会随着害虫种类的不同而不同。该项目旨在应用一种新的分析方法，根据森林害虫的特征，如身体大小和其他物理特征，而不是按照传统的分类方法，来评估陷阱设计对森林害虫检测的影响。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，但尚未在这方面得到应用。因此，这些发现将有助于在加拿大和全球制定更有效的森林病虫害检测方案，并满足英国和加拿大政府确定的改善森林病虫害检测和监测调查设计的研究需求。该项目将利用现有的数据集，其中包括已发布和未发布的森林病虫害捕获和诱捕器设计信息。将在该项目下开发一个新的特征数据库，使用加拿大林业局保存的森林有害生物储存标本和博物馆收藏品，以衡量森林有害生物物种的物理特征(特征)。这个新的数据库将被用来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会随着陷阱设计的不同而变化。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一个博士项目。该项目将设在多伦多大学，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.