20. March 2025
Press Release
A new study published in Agriculture, Ecosystems and Environment shows that pests such as the fall armyworm (Spodoptera frugiperda) and grubs (Holotrichia serrata) could have a significant impact on maize cultivation in Nigeria in the coming decades. Researchers, including those from the Leibniz Centre for Agricultural Landscape Research (ZALF), used agro-ecosystem modeling to comprehensively depict, for the first time, how pest risks evolve under different climatic conditions and to provide economic estimates of yield losses. The simulations for the period 2021 to 2100 are based on climate projections, the MONICA yield model developed at ZALF, and environmental factors such as temperature and soil moisture. The results represent the first spatial estimation of pest impacts in sub-Saharan Africa and provide a critical foundation for targeted management strategies and the development of early warning systems.
Maize is a key crop in Nigeria and plays an essential role in food security. The new spatial simulations indicate that yield losses due to pest infestation could range regionally from 18% to 75% in the coming decades—more severe than previously assumed. This translates to an economic loss of US$72 to US$675 per hectare, posing a substantial burden for smallholder farmers in the affected regions who typically operate at subsistence levels and are uninsured.
"Our models show that pests such as the fall armyworm and grubs can have a greater impact on maize yields than direct climatic influences like droughts and floods," explains Dr. Esther Shupel Ibrahim, lead author of the study. "This means that preventive measures and improved monitoring are essential to ensure the sustainability of maize cultivation."
Optimal sowing times also play a crucial role. The simulations demonstrate that early sowing can lead to higher losses, while mid- or late-season sowing reduces the risk.
Data as the Basis for Early Warning Systems
The study not only provides new insights into the risks to maize cultivation but also practical applications. Currently, many Nigerian farmers lack access to scientific forecasts on pest outbreaks and climatic conditions, relying instead on traditional experiential knowledge. The new simulations could offer improved sowing recommendations and enable preventive pest management—something that has been difficult to implement until now.
The study introduces seven-day risk maps, a potential game changer for pest management. These maps utilize precipitation, temperature, and soil moisture data to predict pest outbreaks, allowing for more precise pesticide application, reducing unnecessary spraying, and promoting more environmentally friendly pest control methods.
To ensure that farmers benefit from these findings, the information should be disseminated through agricultural advisory services, government programs, and local agricultural organizations. Digital solutions such as SMS alert systems, agronomic apps, or the Internet of Things (IoT) could also help deliver real-time recommendations directly to farms. In the long term, adjusted sowing times, improved cultivation methods, and targeted monitoring could help minimize yield losses and strengthen food security.
Addressing Broader Challenges in Nigerian Agriculture
Farmers in Nigeria face numerous challenges, including climate change, population growth, conflicts, and the increasing spread of pests and plant diseases—all of which threaten food security. Many farmers work under challenging conditions, often on nutrient-poor soils and in volatile climates.
In such environments, scientifically based tools are essential to help integrate climate risk forecasting and pest control into farming practices. Beyond Nigeria, these findings could also benefit other regions in sub-Saharan Africa with similar smallholder-dominated agricultural systems.
However, for these innovations to succeed, a shift in perspective is necessary. Many communities do not view climate-related agricultural challenges as environmentally driven phenomena. Raising awareness about climate change, its causes, and sustainable pest management—combined with improved access to early warning systems—could help merge traditional practices with modern scientific insights and support the development of policies for climate adaptation and food security in sub-Saharan Africa.
Project Partners
- National Centre for Remote Sensing, Jos, National Space Research and Development Agency, Nigeria
- Humboldt-Universität zu Berlin, Deutschland
- Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF), Deutschland
- Department of Agricultural and Environmental Engineering, Federal University of Technology, Akure, Nigeria
Funding
This research was funded by the Nigerian-German Postgraduate Training Programme PhD, 2019 (57473408). Support was provided by the National Centre for Remote Sensing, Jos Plateau State, Nigeria, Humboldt Universität zu Berlin, Germany, and the Leibniz Centre for Agricultural Landscape Research (ZALF), Brandenburg, Germany.
Further Information
Link to original publication: https://www.sciencedirect.com/science/article/pii/S0167880925000660?via%3Dihub
Text Disclaimer
This is a summary of the original text created with the help of artificial intelligence: Ibrahim, E. S., Nendel, C., Ajayi, A. E., Berg-Mohnicke, M., & Schulz, S. (2025). Simulating and mapping the risks and impact of fall armyworm (Spodoptera frugiperda) and white grub (Holotrichia serrata) in maize production outlooks for Nigeria under climate change. Agriculture, Ecosystems and Environment, 385, 109534. https://doi.org/10.1016/j.agee.2025.109534, published Open Access under the license CC BY 4.0: https://creativecommons.org/licenses/by/4.0/.
The text has been carefully reviewed and revised in light of AI regulations at ZALF.
