Spatiotemporal risk forecasting to improve locust management

Area of Science:

• Agricultural Entomology
• Pest Management
• Ecological Forecasting

Background:

• Locusts pose a significant threat to global agriculture, necessitating effective management strategies.
• Spatiotemporal forecasting is a critical component for predicting locust behavior and mitigating agricultural damage.

Purpose of the Study:

• To establish a unified terminology for locust spatiotemporal forecasting.
• To critically assess existing forecasting methodologies.
• To identify avenues for enhancing locust forecasting tools.

Main Methods:

• Review of current scientific literature on locust spatiotemporal forecasting.
• Categorization of forecasting approaches into statistical (for presence, reproduction, gregarization, outbreaks) and mechanistic (for agricultural impacts).

Main Results:

• Forecasts can predict locust presence, reproduction, gregarization, population outbreaks, and agricultural impacts.
• Statistical methods are primarily used for ecological predictions, while mechanistic models address agricultural consequences.

Conclusions:

• There is a need to develop reliable, reproducible spatiotemporal forecasting systems specifically for agricultural impacts.
• Transitioning scientific research into operational forecasting systems is essential.
• Rigorous evaluation of forecasting system performance is recommended for continuous improvement.