Piou C, Marescot L. Spatiotemporal risk forecasting to improve locust management.
CURRENT OPINION IN INSECT SCIENCE 2023;
56:101024. [PMID:
36958588 DOI:
10.1016/j.cois.2023.101024]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 03/14/2023] [Accepted: 03/15/2023] [Indexed: 05/03/2023]
Abstract
Locusts are among the most feared agricultural pests. Spatiotemporal forecasting is a key process in their management. The present review aims to 1) set a common language on the subject, 2) evaluate the current methodologies, and 3) identify opportunities to improve forecasting tools. Forecasts can be used to provide reliable predictions on locust presence, reproduction events, gregarization areas, population outbreaks, and potential impacts on agriculture. Statistical approaches are used for the first four objectives, whereas mechanistic approaches are used for the latter. We advocate 1) to build reliable and reproducible spatiotemporal forecasting systems for the impacts on agriculture, 2) to turn scientific studies into operational forecasting systems, and 3) to evaluate the performance of these systems.
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