Potential distribution of Rice Thrip (S.biformis) in India under climate change

Abstract

Abstract India’s economy is agro-based economy and in which rice is the major crop grown in the country. India is also one among the global leaders in the production of rice and is accounted for approximately 10% of nation’s economy. Present and future changes in the climate may challenge the crop production as the pest pressure in agriculture varies significantly with the elevated temperatures. The rice thrip (S.biformis) is the most challenging pest of rice and often causes yield reduction and significant economic loss. The climate change leads to variations in meteorological parameters, and it apparently affects the developmental rates and population dynamics of rice thrip. Monitoring its geographical distribution based on the climatic conditions can minimize crop yield losses. Therefore, the present study focused to quantify the temperature changes and eventually the population dynamics of rice thrip in India using projections from Hadgem3-GC31 and MPI-ESMI-2 under three emission scenarios (SSP126, SSP245 and SSP585) for the year 2050. The probability distribution from the MaxEnt species distribution model indicates the southern and north-eastern regions of India will be highly affected by rice thrip in 2050, and a total of 391 districts will be highly affected (locations where the predicted probability by the model is greater than 0.8) for the SSP126. The number of districts which will be highly affected by rice thrip for SSP245 and SSP585 are 418 and 435 respectively. The analysis shows that the most influencing climatic parameter for the geographical distribution of rice thrip is Tmax (quadratic relation) followed by bioclimatic variable and Tmin (positive relation). This suggests the regions with possibility to increase the maximum temperature will be highly suitable for its growth and distribution. Quantifying the dynamic population of rice thrip under climate change can facilitate and strategize integrated pest management practices to a sustainable food production by minimizing the risks.