Predicting the potential distribution of geographically-limited species, Apsylla cistellata Buckton (Psyllidae: Hemiptera) on mango (Mangifera indica) under different climate change scenarios

The aim of present study was to predict the potential distribution of mango shoot gall psylla, Apsylla cistellata (Psyllidae: Hemiptera) under current and future climate scenarios of 2050 and 2070. This study was conducted across six states in India where their infestation and occurrence noticed. The study provided a deep insight on surveys of shoot gall psylla infestation that occurred between 2012 and 2018. Current and future climate change scenarios acquired from the WorldClim database and Maxent modeling technique was used to fit with occurrence points and current climate data to model potential shoot gall psylla distributions. The model performance was tested using area under the curve (AUC) of the receiver operating characteristic (ROC) values. Response curves depicted the relationships between bioclimatic variables and predicted probability of A.cistellata presence. MaxEnt model used to develop spatial map and their distributions for selected climate change scenarios (RCP2.6, RCP 4.5. RCP 6.0 and RCP 8.5) and mapped the habitat for A.cistellata suitability under current and future scenarios. Present study results suggested that under current climate change scenarios, the potential distribution of shoot gall psylla was noticed in Western and Central part of Uttar Pradesh and Eastern part of Madhya Pradesh. In future climate change scenarios predicted suitable habitat areas for A.cistellata was found mostly from regions of Western and Central Uttar Pradesh, Southern parts Himachal Pradesh and Uttarakhand. The predicted suitability maps developed from present study will be useful in planning and designing of pest management strategies to control pest effectively from designated areas. The study provides clutches of clues for understanding potential changes in distribution and activity of pest in designated areas in response to current and future climate change scenarios.