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Effect of Climate Change/global Warming on Yellow Stem Borer (ysb) and Brown Planthopper (bph)

Md. Panna Ali
Scientific Officer, Entomology Division, BRRI, Gazipur-1701

Mohammad Fazle Rabbi
CSO and Head
Entomology Division, BRRI, Gazipur-1701

Abstract/ Executive Summary:

Growth rate of BPH is expected to increase with temperature and probably also with rain, but not in a straightforward way. Temperature may affect YSB abundance negatively at high precipitation level, but positively at intermediate to low precipitation level. Precipitation may affect YSB abundance positively when monthly precipitation was <400 mm at high temperature level, and when monthly precipitation was <300 mm at intermediate temperature level. The impact of precipitation on YSB abundance might be negative when monthly precipitation was >400 mm at high temperature level, and when monthly precipitation was >300 mm at intermediate temperature level. These results suggested climate variability (e.g. temperature and/or precipitation rising) may not result in the increase of YSB outbreak frequency. Instead, the YSB outbreak frequency may unexpectedly be reduced that might decrease the risk of outbreaks frequency in rice field.

Keywords: Stemborer, BPH, Climate, Global warming

Location: BRRI, Gazipur

Start Date: 01-07-2011

End Date: 30-06-2012

Program Area: Pest Management

Commodity: Rice

Objectives:

To know the impact of climate change on yellow stemborer (YSB) and brown planthopper (BPH)

Methodology:

Monthly YSB and BPH catches from January 2000 to December 2009 were taken from light traps recorded data and then used in this study. The data were analyzed using different mathematical models. The optimal correlation structure of the autoregressive integrated moving average (ARIMA) model was chosen by minimizing Akaike information criterion (AIC), first selecting autoregressive (AR) and moving average (MA) orders and then removing non-significant AR and MA parameters. The residual series of models presented in this study accounted properly for auto correlation and non-stationarity (tested by Lagrange Multiplier Test and Augmented Dickey-Fuller Unit Root Test, respectively). The average per capita growth rate (r) from time t to time t+Δt was calculated as r, where N is the population size (monthly abundance). The average population size during the time interval from time t to time t+Δt was calculated as N = (Nt +Nt+Δt)/2. The average population size during the time interval from time t to time t+Δt was calculated as N = (Nt +Nt+Δt )/2. The average temperature and amount of rainfall during the time interval is denoted T and H respectively. We investigated whether r depends on temperature and rainfall by means of a general linear model, r = ß0 + ß1T + ß2T2 +ß3H + ß4H2 + ß5TH + ß6T2H + ß7TH2 + ß8T2H2 + ε.

Source of Information: Internal review workshop, 2011-12

Article Link (Online Journal):

Funding Source:

1. Government

Budget:

Total Budget (Tk.) :

Achievement/Findings:

The effect of temperature and rainfall showed that the growth rate of BPH was expected to increase with temperature and probably also with rain, but not in a straightforward way. It appears that there are two seasons where the population could grow. Both seasons were hot, but one was dry and the other wet. Monthly abundance and variation of YSB showed the seasonality of YSB population dynamics. April-June and August-November were considered the high-abundance and December–March low-abundance. The monthly YSB log abundance confirmed the seasonality with the strongest periodicity of 6 months, followed by a weaker periodicity of 12 months. This pattern was incompatible with previous field observations that show three peaks of YSB population (1st in April, 2nd in June-July and 3rd in October-mid November) annually in Bangladesh. The two-peak temporal pattern could be attributed to monthly climate variance. The number of YSBs captured in July was low, probably because the borers were in larval and pupal stages. As the life cycle of YSB is 5–9 weeks, the following generation of YSB moths emerged in August. Also, the newly emerged moths laid eggs, the prevailing favorable climatic factors induced rapid development of new frequent generations. These likely resulted in a seasonal abundance peak at August-November in each year. From December to February, months are very cold and dry season that induced low abundance. Variance partitioning showed that the two climate parameters explained a total of 30.2% of the variance in YSB abundance, of which temperature explained 22.7%, precipitation 7.5%. These indicated that effects of temperature and precipitation and their joint effects were significant and that temperature had a higher explanatory capacity of the variance in YSB abundance than precipitation. After adjusting for serial residual correlation by using a subset ARIMA (12,0,2) (1,0,1) 12 model, it was that the monthly YSB abundance depended on its own previous demographic history as well as temperature and precipitation (Y t = 0.458 Y t-1 - 0.518 Y t-2+ 0.306 Y t-3 + 0.002T 2t-1 -1.553R 2t - 0.225T t R t +7.462R t; R2=0.652, AIC=1.153). The subset ARIMA model included AR parameter for lag12, SAR parameter for lag 1, MA parameter for lag 2, and SMA parameter for lag 1, with the other AR and MA parameters coefficients set to zero. Results of simple linear regressions lent further support that climate variability had a quadratic effect on YSB population.

Knowledge Management: Report/Proceedings