Abstract
To inform policy at national and European scales, Defra needs to be well informed about the many variables that influence the sustainability and environmental footprint of arable production. This can be achieved most efficiently by identification, collation and analysis of robust data resources. This project will continue elements of the output from project AR0503 (Crop Health and Crop Protection Practice in UK Combineable Crops), to provide Defra with statistically sound data sources that have the resolution and flexibility necessary to inform a wide range of policy questions now and for the future. Defra has previously funded annual monitoring of disease and pest levels and agronomic practice in winter wheat and winter oilseed rape. The databases generated currently hold up to 30 years’ data on the incidence of pests and diseases on wheat and oilseed rape. The monitoring initiatives will be continued within the current project in order to maintain and extend these unique data resources for the two most important combinable crops in the UK. The historical reference datasets identified are used and quoted widely across government, academia and industry and form a reliable evidence base to inform Defra initiatives. In line with Defra’s need, this evidence base is dynamic, changing as research delivers new tools and understanding, and provides a mechanism to analyse issues that were previously thought to be unconnected. This project will provide the only impartial and statistically robust source of evidence for policy making which aims to mitigate the impacts of crop diseases and pests and unsustainable management practices on the environment. The data collected are also a key resource for monitoring impacts of climate change on UK agriculture by measuring indicator species. As well as addressing future research and policy needs this project will continue existing collaborations with a wide range of Defra and levy funded research and industry projects through provision of samples or data to support monitoring for food safety, development and validation of models for disease and pest forecasting and identification of sustainable management strategies for the industry.
United Kingdom