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Details of Award

NERC Reference : NE/V019333/1

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

Grant Award

Principal Investigator:
Dr RD Girling, University of Reading, Sch of Agriculture Policy and Dev
Science Area:
None
Overall Classification:
Unknown
ENRIs:
None
Science Topics:
Forestry, sylviculture
Agricultural systems
Crop protection
Chemical ecology
Invertebrate pests
Population Ecology
Biodiversity
Abstract:
NERC : Tom Staton : NE/R012229/1 Insects 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will utilise existing datasets containing information on forest pest captures and trap design, both published and unpublished.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.
Period of Award:
1 Jun 2021 - 31 May 2022
Value:
£8,369
Authorised funds only
NERC Reference:
NE/V019333/1
Grant Stage:
Completed
Scheme:
NC&C NR1
Grant Status:
Closed

This grant award has a total value of £8,369  

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FDAB - Financial Details (Award breakdown by headings)

Exception - Other Costs
£8,369

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