Abstract
Abundance of brown plant hopper (BPH) Nilaparvatalugens (Stål) (Delphacidae: Homoptera) is modulated by prevalent weather conditions of rice growing seasons and locations. Categorization of BPH adults caught in light traps (nos/week/trap) into low, moderate and high and formulation of criteria accounting weather variables [maximum/ minimum/ mean temperature (ÚC), morning/evening/mean relative humidity (%), rainfall (mm) and sunshine hours (h/day) and wind speed (km/h)] during kharif of2011-16 for four locations viz., Ludhiana (Punjab), Chinsurah (West Bengal), Raipur (Chhattisgarh) and Aduthurai (Tamil Nadu) with associated rules for weather based BPH prediction. Validation of BPH predictions for kharif 2017 indicated 96, 87, 73 and 61% accuracies in respect of Aduthurai (TN), Raipur (CG), Ludhiana (PB) and Chinsurah (WB). Future weather based predictions of BPH based on climatic projections of representative concentration pathway (RCP) 4.5 for 2020, 2050 and 2080 indicated absence of high population at Chinsurah (WB) during all time periods of 2020-2080. Progressively reducing BPH abundance from past (2011) to all future periods was noticed at Aduthurai (TN). ‘High’ BPH from 2020 and beyond over 2011 and 2016 at Raipur (CG) and reducing ‘high’ but increasing ‘moderate’ category between 2020-2050 but the reverse in 2080 at Ludhiana (PB) were predicted indicating requirement of continued monitoring strategies put in place at these locations. The observed spatial variability of climate change influence on BPH implied a need for zonation mapping of rice insects including BPH for India.
Highlights
Twentieth century documented an increasing trend of surface temperature with no significant trends for rainfall across India (Rupa Kumar et al, 2006)
The use of such developed weather based models in conjunction with the future projections of climate change by inter-governmental panel for climate change (IPCC) provides an opportunity to understand the future scenarios of insect pests (Vennila et al, 2019)
As insect development depends both on magnitude and distribution of weather variables, the weather-based prediction of brown plant hopper (BPH) based on iterative and exploratory analysis of data sets over many seasons was found to be an effective tool toknow the forthcoming insect abundance
Summary
Twentieth century documented an increasing trend of surface temperature with no significant trends for rainfall across India (Rupa Kumar et al, 2006). Weather based models using heuristic and empirical approaches for different agroeco regions based on datasets of light traps have been found useful to predictthe severity of rice insect pests (Vennila et al, 2016) that providesadvance information on timing and abundance of their population for use in pest management (Anon.2016). The use of such developed weather based models in conjunction with the future projections of climate change by IPCC provides an opportunity to understand the future scenarios of insect pests (Vennila et al, 2019)
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