Assessing the impact of landscapes on CSSV disease emergence

Several landscape variables such as climate, soil, vegetation, land use and the extent of cropping practice intensification may have a potential impact on CSSV and its vectors. Landscape ecology studies will therefore help determine which of these variables are involved in the emergence of CSSV outbreaks in Ivorian cocoa farms. This research will help characterize the CSSV and mealybug vector diversity, plant diversity and food webs, while focusing specifically on alternative plant hosts and natural enemies of mealybugs. 

Designing CSSV disease forecasting models

These models will be based on climatic variables to predict the development of the main mealybug vector species and their CSSV transmissibility. They will also be based on CSSV development and impacts on cocoa trees. The models developed will help gain further insight into the CSSV epidemiology while enhancing the potential development of tools for assessing the CSSV infection risks according to the cocoa stand climatic/microclimatic conditions.

Assessing the role of plot conditions on CSSV disease emergence

A forecasting model—focused on mealybug spatiotemporal dynamics—will make it possible to forecast the risk of CSSV outbreak propagation. This research will focus on cocoa farms managed with varying degrees of agroforestry so as to identify the agroecological factors involved in these dynamics. It will also characterize certain biophysical factors (soil, vegetation structure, ant communities, etc.) and cocoa farmers’ cultivation practices. A greater understanding of the impact of these factors on the spread of CSSV will facilitate the identification of regulatory levers that could underpin innovative control methods.

In situ assessment of the efficacy of barrier crops on CSSV

Growing cocoa in large uninterrupted areas with many unshaded cocoa farms is conducive to the spread of CSSV, as this layout provides no barriers to the spread of the disease. Yet planting barrier crops between cocoa farms would help stall this phenomenon. The method is being tested under Ivorian conditions (https://barco.cirad.fr/) to boost insight on the impact of the landscape on the dynamics of CSSV and its mealybug vectors in terms of barrier effects. This will facilitate assessment of the effectiveness of plant barriers to control CSSV.

Developing decision support tools

Modelling-based decision-making tools to control CSSV and its mealybug vectors will be developed. These tools will be specifically designed for cocoa farmers to enable them make decisions tailored to their situation with the aim of diversifying their cocoa farms: species to be planted, planting arrangements and long-term management of these species, etc. The tools will also generate recommendations for mealybug regulation by optimizing the microclimatic conditions and auxiliary insect populations.