Wheat Blast: Earth observation and climate forecasts for risk management
Wheat Blast (Magnaporthe oryzae Triticum or ‘MOT’) is a plant disease of global concern, threatening crop production and biosecurity. Known to favour humid, warmer climates, the disease is a severe problem in Bangladesh and South America. However, the consequences of climate change pose the risk of the disease infecting other wheat-growing areas. Coupled with its ability to spread rapidly through the air and seeds, Wheat Blast’s devastating effects and limited control options are leading to heavy yield losses and it is now a threat to global food security. This project brings together a project consortium, formed of experts in Earth observation, remote sensing, pest and disease modelling, datasets and information dissemination to produce Wheat Blast risk maps and actionable advice as part of a framework. The framework will be used by key stakeholders as part of a targeted management approach to the disease.
Developing beneficial nematode-based biocontrol solutions to fall armyworm in Africa
The fall armyworm is a major pest devastating more than 80 crops. However, it favours maize where it can cut yields by up to 90%. The pest has invaded Africa, Australia and Asia, and recently arrived in Europe. Existing pest management efforts against the maize pest include insecticides. But an overreliance on these has led to prolific increases in insecticide applications in maize cultivation in Africa, and detrimental health and environmental threats. The ineffective existing control method has highlighted the need for more effective, safer and more sustainable control practices. An expert team and CABI are developing practical, safe and effective techniques of entomopathogenic nematodes as biological control agents against armyworm caterpillars to help mitigate the impacts of fall armyworm on food security in Africa.
EU-China joint action to increase the development and adoption of IPM tools
The persistent threat of invasive agricultural pests and their chronic re-emergence underlines the importance of Integrated Pest Management (IPM) tools and their implementation. Pest management typically relies largely on chemical pesticides, increasing the risks to humans and wildlife. Despite European Union and Chinese policies promoting the use of IPM, widespread adoption by farmers is limited. This project will utilize existing knowledge and techniques to adapt and optimize future IPM tools and practices. The project will further develop high-potential IPM tools and design cost-effective, environmentally safe IPM packages for economically important crops. Together with partners, CABI will lead the development of a web-based IPM tool performance demonstrator. CABI will also make valuable contributions to the development and efficacy of IPM tools against fall armyworm and develop a biocontrol agent for common ragweed.
Collating and publishing datasheets on impactful invasive species
Invasive species are of significant concern to ecosystems. They are a key driver of global biodiversity loss and species extinctions. Together with climate change, invasive species are causing irreversible damage. Without any mitigation, the spread of invasives will continue and the persistent damaging effects will increase and remain. Having current and comprehensive data on the most harmful and impactful invasive species is necessary for predicting and preventing damage. This project will collate data and information on 72 invasive species threatening species on the Endangered Species Act and the International Union for the Conservation of Nature.
Earth observation to improve critical datasets for pest risk modelling
Rising temperatures have led to pests, diseases and weeds establishing in areas of the world that were previously uninhabitable. Furthermore, growth in global trade and new trade pathways increase the risk of accidental movement of pests. Earth Observation (EO) and climatic data can help by improving predictions about where potential agricultural pests and diseases may be a threat. Information produced by models can help decision makers understand and prepare for future risks. Working with a consortium of researchers, this project will use EO data to improve the data layers used in models that predict where pests can establish, including irrigation, areas under protected agriculture and climatic canopy conditions, demonstrating the improvements made to species distribution estimations for key pests and biological control agents.