Predicting the invasion risk of rugose spiraling whitefly, <i>Aleurodicus rugioperculatus</i>, in India based on <scp>CMIP6</scp> projections by <scp>MaxEnt</scp>

Pest Management Science - Tập 79 Số 1 - Trang 295-305 - 2023
R. Maruthadurai1, Bappa Das2, R. Ramesh1
1Crop Science Section, Indian Council of Agricultural Research, Central Coastal Agricultural Research Institute, Goa, India
2Natural Resource Management Section, Indian Council of Agricultural Research, Central Coastal Agricultural Research Institute, Goa, India

Tóm tắt

AbstractBACKGROUNDRugose spiraling whitefly (RSW), Aleurodicus rugioperculatus Martin, is a highly polyphagous invasive pest native to Central America. The occurrence of A. rugioperculatus in the Oriental region was first reported from Pollachi, Tamil Nadu, India in 2017. This pest is widely distributed in India, causing severe economic damage to coconut and other horticultural crops. It is a recent invasion in India and information on its potential distribution is lacking. Thus, in the present study we used the latest Coupled Model Intercomparison Project phase 6 (CMIP6) dataset through Maximum Entropy species distribution modelling (version 3.4.1, MaxEnt) to determine the potential distribution of RSW in present and future climate change scenarios in 2050 and 2070 under Shared Socioeconomic Pathway (SSP) 126 and SSP585 emission scenarios. The performance of the model was evaluated using the area under the curve (AUC), true skill statistics (TSS) and the continuous Boyce index (CBI).RESULTSThe MaxEnt model performed well and predicted the potential distribution of A. rugioperculatus with high‐accuracy AUC values of 0.991 and 0.989, TSS values of 0.891 and 0.842, and CBI values of 0.972 and 0.934 for training and testing, respectively. Jackknife analysis revealed that A. rugioperculatus distribution was mostly influenced by temperature‐based bioclimatic variables contributing 62.1% of the suitability, with precipitation variables contributing the remainder. The most important bioclimatic variables for RSW distribution were annual mean temperature (Bio 1, 28.9%) followed by mean diurnal range (Bio 2, 19.5%) and annual precipitation (Bio 12, 19.1). Potential suitable areas for RSW establishment were mostly found in all coastal and southern states of India. A. rugioperculatus prefers a warm and humid climate, indicating that the tropics, subtropics and temperate regions are ideal for its spread and invasion. Our results highlighted that the suitable habitat area for A. rugioperculatus is predicted to increase and highest probability of invasion and spread in 2050 and 2070 under future climate change scenarios of SSP126 and SSP585 compared to present climatic conditions.CONCLUSIONSThis is the first study to use the latest CMIP6 models and it predicts the potential distribution of RSW in India under present and future climate change scenarios. The implementation of strict domestic quarantine measures may prevent the spread and damage of RSW to noncoastal regions of India. The results of the current study should help in timely monitoring and surveillance of RSW and to formulate integrated pest management strategies at the national level to restrict its spread, invasion and damage to new areas. © 2022 Society of Chemical Industry.

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Pest Management Science

Tập 79 Số 1

295-305

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