Predicting the potential global distribution of an invasive alien pest Trioza erytreae (Del Guercio) (Hemiptera: Triozidae).

The impact of invasive alien pests on agriculture, food security, and biodiversity conservation has been worsened by climate change caused by the rising earth's atmospheric greenhouse gases. The African citrus triozid, Trioza erytreae (Del Guercio; Hemiptera: Triozidae), is an invasive pest of all citrus species. It vectors the phloem-limited bacterium "Candidatus Liberibacter africanus", a causal agent of citrus greening disease or African Huanglongbing (HLB). Understanding the global distribution of T. erytreae is critical for surveillance, monitoring, and eradication programs. Therefore, we combined geospatial and physiological data of T. erytreae to predict its global distribution using the CLIMEX model. The model's prediction matches T. erytreae present-day distribution and shows that parts of the Mediterranean region have moderate (0 < EI < 30) to high (EI > 30) suitability for the pest. The model predicts habitat suitability in the major citrus-producing countries, such as Mexico, Brazil, China, India, and the USA. In the Special Report on Emissions Scenarios (SRES) A1B and A2 scenarios, the model predicts a reduction in habitat suitability from the current time to 2070. The findings show that global citrus production will continue to be threatened by T. erytreae. However, our study provides relevant information for biosecurity and risk assessment.

Climate-based seasonal dynamics of the invasive red palm mite Raoiella indica.

BACKGROUND: Raoiella indica Hirst (Acari: Tenuipalpidae) is the most critical coconut and banana pest recently introduced in Brazil. Once the mite pests are introduced, it is essential to understand their dynamics in important crops under open-field climatic conditions to implement strategies for their management and determine the periods when species populations may increase in the field. Modelling tools have been used to determine the potential distribution of species and implications for the management of invasive species. Thus, our aim in this study was to determine the seasonal variation in R. indica and the influence of the monthly climate using CLIMEX modelling. We adjusted the CLIMEX model for R. indica based on distribution data, additional biological characteristics, and fluctuations in the R. indica population in a commercial coconut plantation. RESULTS: The model for the current climate shows a good match between the ecoclimatic index and the global distribution of R. indica. The model results demonstrate that most states of Brazil and several regions worldwide include areas with highly suitable climatic conditions for R. indica. We observed variations in the density of R. indica in commercial coconut crops, with the highest incidence occurring during the first months of the year. CONCLUSION: Our results showed different alterations in seasonal suitability for R. indica that may provide information for the implementation of methods for time management, such as strategies for sampling and control during periods with a high degree of suitability for R. indica. © 2020 Society of Chemical Industry.