Coffee berry borer modelling for Kenyan coffee production
The coffee berry borer is a major coffee pest worldwide, threatening farmers’ livelihoods and the production of coffee. In Kenya, the pest is a particular problem in low-altitude zones and can cause up to 80% losses. Erratic rainfall and other effects of climate change are making it hard to break the pest lifecycle. In this project, CABI is using its tried and tested PRISE model to compile a comprehensive risk assessment of the Kenyan coffee sector and create a model specific to the coffee berry borer in Kenya. With partners, the project aims to empower farmers and stakeholders within the coffee value chain with actionable advice derived from data and modelling.
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.
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.
Juno Evidence Alliance: Transforming Evidence for Agriculture, Food and Climate
The Juno Evidence Alliance is a global platform working to ensure better evidence drives better decisions across agriculture and food systems. It provides high-quality evidence to help decision-makers address key challenges and create a more nutritious, food-secure, and climate-resilient future.