Spatiotemporal risk forecasting to improve locust management
Piou, Cyril | Marescot, Lucile | Centre de Biologie pour la Gestion des Populations (UMR CBGP) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD [Occitanie])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier ; Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM) | Département Systèmes Biologiques (Cirad-BIOS) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad) | This work was funded by ANR-JCJC (Agence Nationale de la Recherche, Programme Jeunes Chercheuses Jeunes Chercheurs, France) under the PEPPER project (ANR-18-CE32-0010-01). | ANR-18-CE32-0010,PEPPER,Etude de l'émergence du polyphénisme de phase et des risques associés(2018)
We wish to thank the participants of the Symposium on ‘Forecasting Locust Risks’, organized by C. Piou during the 13th International Conference of Orthopterology, in Agadir in March 2019: Ted Deveson, Keith Cressman, Robert A. Cheke, Mohammed F. Smiej, Eduardo Trumper, and Jørgen Aagaard Axelsen. Their inputs and discussion gave a good basis for this review.
Показать больше [+] Меньше [-]International audience
Показать больше [+] Меньше [-]Английский. Highlights: • Spatiotemporal forecasting is a key process in the management of locusts. • Forecasts can be used at different risk levels from locust presence to impacts. • Reproducible forecasting systems are still lacking, limiting operationality. • Ecology and human capacities should be at the heart of future forecasting efforts. • Evaluations of forecasting performance need to conducted.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.
Показать больше [+] Меньше [-]Библиографическая информация
Эту запись предоставил Institut national de la recherche agronomique