Spatial Distribution of Diaphorina citri and Climate Suitability Prediction Using the MaxEnt Model in Indonesia

Area of Science:

• Agricultural Entomology
• Ecological Modeling
• Pest Management

Background:

• The Asian citrus psyllid (Diaphorina citri, ACP) is a primary vector for Huanglongbing disease, a significant threat to global citrus production.
• Effective management of ACP relies on accurate population distribution data for targeted surveillance and control.
• Traditional mapping methods face limitations, highlighting the need for advanced predictive tools like the maximum entropy model (MaxEnt).

Purpose of the Study:

• To investigate the current distribution of ACP in Indonesia.
• To predict the potential distribution of ACP based on climatic suitability using the MaxEnt model.
• To identify key environmental factors influencing ACP distribution in Indonesia.

Main Methods:

• Field surveys were conducted across major Indonesian citrus-producing regions (Bali, Java, Sumatra, Kalimantan) over two years (2022-2023).
• Occurrence data were compiled from surveys and existing literature.
• The MaxEnt model was employed, utilizing 19 bioclimatic variables and altitude data for Indonesia (1970-2000).

Main Results:

• ACP was detected in at least 38 citrus-producing areas throughout Indonesia.
• The MaxEnt model achieved excellent predictive performance (ROC/AUC = 0.917).
• High suitability for ACP was predicted in Java, Bali, and Nusa Tenggara, with moderate to low suitability elsewhere, driven by temperature, rainfall, and altitude.

Conclusions:

• ACP exhibits a wide distribution across Indonesia.
• MaxEnt modeling is an effective tool for mapping current ACP distribution and predicting future potential ranges.
• The findings support the development of targeted surveillance and control strategies for ACP in Indonesia.