Background: The Asian citrus psyllid (ACP) Diaphorina citri Kuwayama (Hemiptera: Liviidae) is a destructive, invasive species that poses a serious threat to the citrus industry wherever it occurs. The psyllid vectors the phloem-limited bacteria 'Candidatus Liberibacter americanus' and 'Ca. L. asiaticus', causal agents of the incurable citrus greening disease or huanglongbing (HLB). It is essential to understand which regions and areas are suitable for colonization by ACP to formulate appropriate policy and preventive measures. Considering its biology and ecology, we used a machine learning algorithm based on the MaxEnt (Maximum Entropy) principle, to predict the potential global distribution of ACP using bioclimatic variables and elevation.
Results: The model predictions are consistent with the known distribution of ACP and also highlight the potential occurrence outside its current ecological range, that is, primarily in Africa, Asia and the Americas. The most important abiotic variables driving the global distribution of ACP were annual mean temperature, seasonality of temperature and annual precipitation.
Conclusion: Our findings highlight the need for international collaboration in slowing the spread of invasive pests like D. citri. © 2022 Society of Chemical Industry.
Keywords: Asian citrus psyllid; Diaphorina citri; MaxEnt; climate change; invasive species.
© 2022 Society of Chemical Industry.