The Prediction of Locusta migratoria (Linnaeus, 1758) Outbreak under Climate Change Scenario in Indonesia

Abstract

Locusta migratoria (Linnaeus, 1758) is one of the locusts known as important pests of food crops. Outbreaks of this species can cause catastrophic damage to maize, paddy, and many other crops. A species distribution model was used to identify the probability of the locust's current and future potential distribution in the Indonesian archipelago. The study relied on the machine learning method Maximum Entropy (Maxent) Model to forecast the future spread of the species in the Indonesian archipelago and to find the climate variable that influenced the distribution of Locusta migratoria. The results showed an Area Under Curve (AUC) value of 0.956 for the Locusta migratoria model, indicating a highly reliable model. The important variable for the distribution of this species was precipitation, especially during the dry season. A low amount of rainfall increases the possibility of the species existing and being distributed. Maxent prediction models showed the potential distribution in the southern part of the Indonesian archipelago under both middle and worst-case scenarios for 2070. This model can become one of the baselines for early warning systems, targeted monitoring and surveillance, and the use of specific pesticides or biological control agents to prevent or minimize the harm of Locusta migratoria outbreak to agricultural lands in the future.