Rao Mathukumalli Srinivasa, Swathi Pettem, Rao Chitiprolu Anantha Rama, Rao K V, Raju B M K, Srinivas Karlapudi, Manimanjari Dammu, Maheswari Mandapaka
Central Research Institute for Dryland Agriculture (CRIDA), Hyderabad, India.
PLoS One. 2015 Feb 11;10(2):e0116762. doi: 10.1371/journal.pone.0116762. eCollection 2015.
The present study features the estimation of number of generations of tobacco caterpillar, Spodoptera litura. Fab. on peanut crop at six locations in India using MarkSim, which provides General Circulation Model (GCM) of future data on daily maximum (T.max), minimum (T.min) air temperatures from six models viz., BCCR-BCM2.0, CNRM-CM3, CSIRO-Mk3.5, ECHams5, INCM-CM3.0 and MIROC3.2 along with an ensemble of the six from three emission scenarios (A2, A1B and B1). This data was used to predict the future pest scenarios following the growing degree days approach in four different climate periods viz., Baseline-1975, Near future (NF) -2020, Distant future (DF)-2050 and Very Distant future (VDF)-2080. It is predicted that more generations would occur during the three future climate periods with significant variation among scenarios and models. Among the seven models, 1-2 additional generations were predicted during DF and VDF due to higher future temperatures in CNRM-CM3, ECHams5 & CSIRO-Mk3.5 models. The temperature projections of these models indicated that the generation time would decrease by 18-22% over baseline. Analysis of variance (ANOVA) was used to partition the variation in the predicted number of generations and generation time of S. litura on peanut during crop season. Geographical location explained 34% of the total variation in number of generations, followed by time period (26%), model (1.74%) and scenario (0.74%). The remaining 14% of the variation was explained by interactions. Increased number of generations and reduction of generation time across the six peanut growing locations of India suggest that the incidence of S. litura may increase due to projected increase in temperatures in future climate change periods.
本研究的特点是使用MarkSim估算印度六个地点花生作物上烟草夜蛾(斜纹夜蛾)的代数。MarkSim提供了来自六个模型(即BCCR - BCM2.0、CNRM - CM3、CSIRO - Mk3.5、ECHams5、INCM - CM3.0和MIROC3.2)以及来自三种排放情景(A2、A1B和B1)的六个模型集合的未来日最高气温(T.max)和最低气温(T.min)的通用循环模型(GCM)数据。这些数据被用于按照生长度日法预测四个不同气候时期(即基准期 - 1975年、近期(NF) - 2020年、远期(DF) - 2050年和极远期(VDF) - 2080年)的未来害虫情况。预计在未来三个气候时期会出现更多世代,不同情景和模型之间存在显著差异。在这七个模型中,由于CNRM - CM3、ECHams5和CSIRO - Mk3.5模型未来温度较高,预计在远期和极远期会多出现1 - 2代。这些模型的温度预测表明,与基准期相比,世代时间将减少18 - 22%。方差分析(ANOVA)用于划分花生作物季节斜纹夜蛾预测代数和世代时间的变化。地理位置解释了世代数总变化的34%,其次是时间段(26%)、模型(1.74%)和情景(0.74%)。其余14%的变化由相互作用解释。印度六个花生种植地点世代数增加和世代时间缩短表明,由于未来气候变化时期预计气温升高,斜纹夜蛾的发生率可能会增加。