A framework for modelling desert locust population dynamics and large-scale dispersal

Area of Science:

• Mathematical modeling
• Pest management
• Ecological forecasting

Background:

• Transboundary pest invasions pose significant threats to agriculture, particularly for smallholder farmers.
• Desert locusts are highly destructive migratory pests capable of forming large swarms that disperse over long distances.
• Effective surveillance, early warning, and management systems are needed to mitigate pest impacts.

Purpose of the Study:

• To introduce a novel integrated modeling framework for predicting gregarious desert locust populations.
• To develop a tool for forecasting short- and long-term swarm movements.
• To provide a practical starting point for managing future desert locust upsurges.

Main Methods:

• Integration of breeding site selection, population maturation (egg, hopper, adult stages), and swarm dispersal.
• Application of epidemiological modeling concepts.
• Incorporation of weather and environmental data with atmospheric transport models for swarm movement prediction.

Main Results:

• A comprehensive framework for predicting gregarious locust populations and their movements has been developed.
• The model integrates various ecological and meteorological factors to forecast swarm behavior.
• The tool is designed for practical application in pest management scenarios.

Conclusions:

• The developed integrated modeling framework offers a significant advancement in predicting desert locust invasions.
• This tool can enhance the effectiveness of surveillance, early warning, and management systems.
• The framework provides a vital resource for proactive strategies against future desert locust outbreaks.