Introduction
Large-scale outbreaks of locusts cause severe damage to agriculture and have a significant impact on global food production. Although locust plagues have been recorded since ancient times, a fundamental solution has yet to be established.
Currently, the primary countermeasure against locust outbreaks is the application of insecticides. This approach is particularly effective during the nymph stage, when locust mobility is limited. However, once locusts reach adulthood, they can migrate over wide areas in a short period of time, making effective intervention difficult. In addition, the use of insecticides raises concerns about negative impacts on ecosystems.
Research Activities in Our Laboratory
To address this issue, we focus on the property that migratory locusts are attracted to the aggregation pheromone 4-vinylanisole (4VA), and explore new possibilities for controlling locust swarms. In 2024, we investigated control strategies for locust swarms using individuals lacking the olfactory receptor OR35, which specifically responds to 4VA, through simulation-based studies.
Skills Developed Through This Research
In locust control research, we reinterpret collective behavior in biological systems, an area that may initially appear distant from information science, as a controllable problem using mathematical models and algorithms. Through this research, our laboratory emphasizes the development of cross-disciplinary foundational skills in information science.
Understanding Collective Behavior as Information Processing
Locust outbreaks are collective phenomena that emerge from interactions among a large number of individuals. In this research, interactions between individuals and pheromone-based attraction are viewed from the perspective of information propagation and processing.
By acquiring this viewpoint, students can treat collective behavior not merely as a biological phenomenon, but as a system that can be analyzed and designed using information-science-based approaches.
Modeling Real-World Phenomena with Mathematics
Although locust movement and aggregation behavior can be observed through experimental data, they are not directly amenable to mathematical treatment. We therefore carefully examine which elements should be included in a model and which aspects can be simplified.
Through this process, students develop the ability to reconstruct complex real-world phenomena using the language of information science, an essential skill shared by many applied research fields.
Bridging Information Science and Biological Phenomena
Locust control research serves as a bridge between information science theories, such as swarm control, multi-agent systems, and complex systems science, and biological phenomena.
By engaging in this research, students learn to integrate knowledge from different fields when approaching a problem, thereby broadening their perspective on the applications of information science.