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Influence of Temperature on the Northern Distribution Limits Of Journal of Thermal Biology 37 (2012) 130–137 Contents lists available at SciVerse ScienceDirect Journal of Thermal Biology journal homepage: www.elsevier.com/locate/jtherbio Influence of temperature on the northern distribution limits of Scirpophaga incertulas Walker (Lepidoptera: Pyralidae) in China Peijian Shi a,1, Bo Wang a, Matthew P. Ayres b,1, Feng Ge a,n, Ling Zhong c, Bai-Lian Li d a State Key Laboratory of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing, China b Department of Biological Sciences, Dartmouth College, Hanover, NH, USA c Plant Protection and Quarantine Bureau of Jiangxi Province, Nanchang, China d Ecological Complexity and Modeling Laboratory, University of California, Riverside, CA, USA article info abstract Article history: We explored the influence of temperature on the northern distribution limits of Scirpophaga incertulas Received 28 September 2011 Walker, an important agricultural pest of rice in Asia. We analyzed Z48 years of records from 186 Accepted 5 December 2011 climate stations of Mainland China to estimate the annual probabilities of reaching the lower lethal Available online 9 December 2011 temperature for S. incertulas. The relevant climatic metric, minimum annual temperature, approxi- Keywords: mated a normal distribution. Consequently, the probability density function for any site could be Local regression method characterized with the mean and standard deviation of minimum annual temperatures. We used the Rice local regression method to map the mean and standard deviation of minimum annual temperatures Lower lethal temperature throughout Mainland China and then calculated isolines representing annual probabilities for reaching Sharpe-Schoolfield-Ikemoto model or exceeding the lower lethal temperature of S. incertulas. In addition, we calculated and mapped the Sum of effective temperatures number of generations per year based on the annual accumulative degree days and the sum of effective temperatures required to complete one generation. The empirical northern distribution limits of S. incertulas were generally congruent with the theoretical limits based on winter survival, with exceptions within the Shandong and Sichuan provinces, which are apparently thermally suitable but where the host plant is not cultivated. The expected number of generations per year was 3–5 within most of the range of S. incertulas in China. In central China, the expected number of generations per year was about 3. A climate warming scenario of 4 1C in minimum and maximum daily temperatures predicted an increase in the expected number of generations per year in central China from about 3to4. & 2011 Elsevier Ltd. All rights reserved. 1. Introduction least of a closely related species in the family Pyralidae. It is always one of the main rice pest insects in southern China. For example, in Rice is the most important human food crop in the world, with 2005, the area infested by this pest insect in China reached 5 million China and India being the leading producers (Maclean et al., 2002). ha, causing a loss of 240 thousand tons of rice (Guo and Zhao, 2006). The history of rice cultivation in China dates from 8000 B.C.E. to Cai (1959) studied the northern distribution limits of the pest insect 6000 B.C.E. (Lawler, 2009). In 2009, the rice output of China was in China, but he only used the 14 1C annual isotherm of China as the about 195 million tons (National Bureau of Statistics of China, http:// possible theoretical northern distribution limits of the pest without www.stats.gov.cn/). Scirpophaga incertulas is an important pest of any clear explanations. Cai (1959) also reported that its real north- rice in Southern China. The distribution areas of S. incertulas includes ern distribution limits lie in 36 1N. Zhang and Zhao (1996) specu- China, Japan, the Philippines, Vietnam, Laos, Kampuchea, Burma, lated that the northern distribution limits in eastern China might be India, Thailand, Bangladesh, Pakistan, Sri Lanka, Malaysia, Indonesia, around 37 1N according to the previous reports. However, they did Afghanistan, Egypt, Papua New Guinea, Northern Australia, and not provide an explanation for the existing northern distribution some islands in the Pacific Ocean (Zhang and Zhao, 1996). In China, limits. the pest insect is autochthonous and monophagous on rice. Terrestrial poikilotherms are largely affected by temperature ‘‘The Book of Songs’’ (Big field), edited by Confucius (from 551 (Makarieva et al., 2005a, 2005b). S. incertulas is highly responsive B.C.E. to 479 B.C.E.), might be the earliest record of this pest or, at to environmental temperature (Zhang, 1992; Rahman and Khalequzzaman, 2004; Stevenson et al., 2005). The minimum annual temperature (MAT) has been considered to be a determin- n ing factor of northern distribution limits for many insects Corresponding author. Tel.: þ86 10 6880 7123; fax: þ86 10 6480 7099. E-mail address: [email protected] (F. Ge). (Uvarov, 1931; Ungerer et al., 1999). When minimum annual 1 These two authors contributed equally to this work. temperatures approximate a normal distribution, and the lower 0306-4565/$ - see front matter & 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.jtherbio.2011.12.001 P. Shi et al. / Journal of Thermal Biology 37 (2012) 130–137 131 Table 1 Summary of abbreviations used. Abbreviation Meaning MAT Minimum annual temperature, i.e., the coldest temperature of the coldest night in winter AMAT Average minimum annual temperature SDMAT Standard deviation of minimum annual temperatures SCP Supercooling point; temperature at which sudden crystallization occurs (frequently the lower lethal temperature for insects, as in S. incertulas) LLT Lower lethal temperature, i.e., temperature below which insects cannot survive (even with brief exposure when LLT¼SCP, as in S. incertulas) PLLT Probability of reaching the lower lethal temperature during one winter NGEN Average number of generations per year LOESS Local regression (a non-parametric fitting method) lethal temperature (LLT) for an insect species is known, the probability of reaching or exceeding the lower lethal temperature (PLLT) can be regarded as the definite integral of the probability density function of MAT from minus infinity to LLT (Ungerer et al., Fig. 1. Climate stations used in the study. The provinces in blue font represent the 1999). places where the northern distribution limits of S. incertulas were observed In the current study, we used the local regression models according to the previous report of Zhang and Zhao (1996). (LOESS) (Cleveland, 1979) to predict the average minimum annual temperature and the standard deviation of minimum annual temperature based on 186 climate stations in China. From this we could map the probabilities of reaching the lower lethal temperature for S. incertulas across China. The number of genera- tions per year of S. incertulas varies in different areas of China due to different climate conditions (e.g., Xu, 1991; Chen, 1996; Li, 2000; Zhong et al., 2000; Zhao and Xue, 2001; Zhang, 2002; Wang and Zhong, 2003; Song et al., 2005; Kong et al., 2006). The number of generations per year descends with latitude decreasing from seven generations in Hainan province (Xu, 1991) to three generations in the more northern Jiangsu province (Kong et al., 2006). There would be value in understanding the influence of climate change on the number of generations because more generations per year tend to yield greater damage to rice crops. Therefore, we used the local regression models to predict the average number of genera- tions based on the law of accumulative effective temperatures. We developed and evaluated the first process-based model of how geographically structured climatic variation influences the distri- bution limits and annual reproductive potential (generations per year) of this important rice pest species. This permitted defensible Fig. 2. Probability of reaching the lower lethal temperature (PLLT) at Deqin station predictions of future pestilence under a changing climate. (28.481N, 98.921E) of Yunnan province. The dark curve represents the empirical Table 1 lists the meanings of all abbreviations used in the accumulative distribution; the red curve represents the normal accumulative distribu- tion function; the gray point represents the probability of reaching the lower lethal present study. temperature (¼0.38) when minimum annual temperatures are less than À11 1C. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) 2. Methods the lower lethal temperature (LLT) for this species. Following 2.1. Site selection Zhang, we estimated the LLT for S. incertulas to be À11 1C based on Table 2. At any specified climate station, the annual probability We selected 186 climate stations in China (Fig. 1). All stations of reaching the lower lethal temperature (PLLT) is equal to the provided at least 48-year records of minimum annual tempera- proportion of years with MATtr À11 1C. PLLT approximates to a ture (MAT). Daily maximum and minimum temperature records definite integral of the probability density function with a mean of these sites were also available. The data came from China AMAT and a standard deviation SDMAT from minus infinity to Meteorological Data Sharing Service System (http://cdc.cma.gov. lower lethal temperature. That is, cn/). We used the Shapiro-Wilk W statistic (e.g., Xue and Chen, Z 2007) to test the normality of the MAT for each site. LLT PLLT ¼ f ðTÞdT, 1 2.2. Simulating the spatial patterns in PLLT of S. incertulas where "# 1 1 TÀAMAT 2 Zhang (1990) measured the supercooling points of larvae of f ðTÞ¼ pffiffiffiffiffiffi exp À ð1Þ 2 USDMAT 2 SDMAT S. incertulas (Table 2) and showed that the supercooling point is p 132 P. Shi et al. / Journal of Thermal Biology 37 (2012) 130–137 LOESS, short for local regression, is a non-parametric method Here, r represents development rate (daysÀ1), T represents absolute for estimating regression surfaces (Cleveland, 1979; Cleveland temperature (K), T^ represents the intrinsic optimum temperature and Grosse, 1991; Cleveland et al., 1992).
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