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


Summary

A novel integrated modeling framework is developed to predict and analyze desert locust population dynamics and large-scale dispersal, incorporating environmental data, locust biology, and wind-assisted migration.

Highlights

  • The framework integrates locust breeding, development, and migration with environmental conditions.
  • It uses a machine learning approach to predict areas suitable for locust breeding.
  • The framework accounts for wind-assisted dispersal of locust swarms using the NAME atmospheric dispersion model.
  • It simulates locust feeding behavior based on land cover type and vegetation state.
  • The framework is tested using historic data from the 2019-2021 desert locust upsurge in East Africa.
  • The model can be used for short-term forecasting of swarm migration and for long-term predictions of locust population dynamics.
  • The framework can inform surveillance and control efforts to mitigate the impact of desert locust invasions.

Key Insights

  • The framework's ability to integrate multiple factors influencing locust population dynamics and migration makes it a valuable tool for understanding and predicting desert locust invasions.
  • The use of machine learning to predict breeding sites and the incorporation of wind-assisted dispersal enable the framework to capture the complex dynamics of locust migration.
  • The framework's consideration of locust feeding behavior and vegetation state allows for more accurate predictions of swarm movement and persistence.
  • The model's ability to simulate multiple generations of locusts enables the investigation of long-term population dynamics and the impact of environmental factors on locust invasions.
  • The framework's flexibility and adaptability make it a useful tool for researchers, policymakers, and practitioners seeking to understand and mitigate the impact of desert locust invasions.
  • The framework highlights the importance of considering the interplay between environmental factors, locust biology, and human activities in understanding and managing desert locust invasions.
  • The model's reliance on high-quality data and computational resources underscores the need for continued investment in data collection and infrastructure to support locust management efforts.



Mindmap


Citation

Retkute, R., Thurston, W., Cressman, K., & Gilligan, C. A. (2024). A framework for modelling desert locust population dynamics and large-scale dispersal. In R. Martinez-Garcia (Ed.), PLOS Computational Biology (Vol. 20, Issue 12, p. e1012562). Public Library of Science (PLoS). https://doi.org/10.1371/journal.pcbi.1012562

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