Wang Chunzhi, Huo Zhiguo, Guo Anhong, et al. Climatic risk assessment of winter wheat aphids in northern China. J Appl Meteor Sci, 2021, 32(2): 160-174. DOI:  10.11898/1001-7313.20210203.
Citation: Wang Chunzhi, Huo Zhiguo, Guo Anhong, et al. Climatic risk assessment of winter wheat aphids in northern China. J Appl Meteor Sci, 2021, 32(2): 160-174. DOI:  10.11898/1001-7313.20210203.

Climatic Risk Assessment of Winter Wheat Aphids in Northern China

DOI: 10.11898/1001-7313.20210203
  • Received Date: 2020-11-02
  • Rev Recd Date: 2020-12-30
  • Publish Date: 2021-03-31
  • Northern China is a main winter wheat production area and plays an important role in ensuring food security. Wheat aphids, as one kind of main agricultural pest, threaten wheat production. Based on wheat aphids disaster and prevention data, planting area and yield loss of wheat, growth period of winter wheat, and daily meteorological data at 561 observation stations from 1958 to 2018 in 8 main wheat production provinces of northern China, relationships between surface meteorological factors and the occurrence area of wheat aphids for every province in North China and Huanghuai area are fully analyzed using methods of correlation analysis, principal component analysis and stepwise regression analysis in various time-periods from last December to 10 June. Eight key meteorological factors which affect the occurrence area of wheat aphids in North China and 6 key meteorological factors for Huanghuai area are determined. The climate disaster indices of wheat aphids are established based on the normalized key meteorological factors and validated in 8 provinces. Furthermore, climatic risk aspects are assessed to explore the occurrence tendency of winter wheat aphids in northern China. The frequencies of different-level decadal climate disasters are taken as hazard index, the ratio of occurrence area of wheat aphids to the wheat-sown area is defined as vulnerability index, and the ratio of controlled area to occurrence area is calculated to measure the disaster prevention and mitigation capability.Comprehensive risk index is built by integrating hazard, vulnerability, disaster prevention and mitigation capability indexes to assess risk development trend in decades. The results show that the climatic hazard for wheat aphids tends to increase gradually and there are significant differences in different decades. The vulnerability for wheat aphids tends to be severe over time.The disaster prevention and mitigation capability for wheat aphids tends to improve gradually especially in the 1990s, and the trend slows down since 2001. The comprehensive climatic risk has been more severe and their scopes of the highest risk have been larger since the 1990s. The climatic risk is highest in Beijing, Tianjin, central-south Hebei, part of north Shandong. And it's the second highest in most of Shandong, north Henan, eastern and southern Shanxi, and north Jiangsu area, where effective measures should be taken to reduce the detriment of wheat aphids.
  • Fig. 1  Average occurrence area of wheat aphids

    Fig. 2  Study area of winter wheat

    Fig. 3  Climatic hazard of wheat aphids during different decades

    Fig. 4  Vulnerability of wheat aphids occurrence in different decades

    Fig. 5  Disaster prevention capability of wheat aphids in different decades

    Fig. 6  Climatic risk of wheat aphids in different decades

    Fig. 7  Tendency of wheat aphids ocurrence in 8 main winter wheat production provinces of northern China

    Table  1  Grade criterion of factors for assessing risk of wheat aphids

    因子 中等 较高
    危险性 [0.5,0.65] (0.65,0.70] (0.70,0.75] (0.75,1]
    脆弱性 [0.5,0.64] (0.64,0.77] (0.77,0.90] (0.90,1]
    防灾减灾能力 [0.5,0.68] (0.68,0.74] (0.74,0.80] (0.80,1]
    气候风险 [0.0,0.46] (0.46,0.53] (0.53,0.61] (0.61,1]
    DownLoad: Download CSV

    Table  2  Occurrence area, the ratio of occurrence area of wheat aphids in different decades in representative provinces of northern China

    时段 河南 山东 河北
    年平均发生面积/万公顷次 年平均发生面积率/% 年平均发生面积/万公顷次 年平均发生面积率/% 年平均发生面积/万公顷次 年平均发生面积率/%
    1961—1970年 84.9 22.4 14.1 4.0 46.3 21.8
    1971—1980年 69.7 18.5 110.5 29.6 104.5 39.4
    1981—1990年 143.4 31.6 190.8 49.1 179.2 74.9
    1991—2000年 306.7 63.1 332.9 82.6 255.0 98.0
    2001—2010年 355.5 70.0 334.1 97.6 220.5 92.0
    2011—2018年 376.4 67.4 350.9 89.4 228.9 95.3
    DownLoad: Download CSV
  • [1]
    Wang X M, Mu S M, Shi A J, et al. Research and application of local support vector regression in prediction of wheat aphid. Journal of Shandong Agricultural University (Nat Sci Ed), 2016, 47(1): 52-56. https://www.cnki.com.cn/Article/CJFDTOTAL-SCHO201601011.htm
    [2]
    Yang Y Z, Lin G L, Hu C F. Effects on wheat quality and yield by aphid infestation, index with discussions on control. Acta Phytophylacica Sinica, 1992, 19(2): 152;158. https://www.cnki.com.cn/Article/CJFDTOTAL-ZWBF199202012.htm
    [3]
    Cheng F F, Wang Y G, Li H W. Analysis of meteorological conditions and the forecast study on the wheat aphid in Zhengzhou. Meteorological and Environmental Sciences, 2012, 35(3): 81-84. https://www.cnki.com.cn/Article/CJFDTOTAL-HNQX201203013.htm
    [4]
    Liu S Y. Agricultural Entomology. Yangling: Tianze Press, 1990: 96-98.
    [5]
    Mu J Y. Agricultural Entomology. Beijing: China Agricultural Science and Technology Press, 1995: 225-237.
    [6]
    Yang X W. Preliminary study on the ear-type aphid of English grain aphid Sitobion avenae F. Acta Agriculturae Boreali-Sinica, 1991, 6(2): 103-107. https://www.cnki.com.cn/Article/CJFDTOTAL-HBNB199102016.htm
    [7]
    Dai P.Responses of Sitobion avenae (Fabricius) to Water-deficit Stress and the Underlying Genetic Basis.Yangling: Northwest A&F University, 2016.
    [8]
    Li S H.The Influence of Greenhouse Effect on Agricultural Diseases and Pests in China//Deng G Y.The Influence of Greenhouse Effect on Agriculture in China.Beijing: Beijing Science and Technology Press, 1993: 223-234.
    [9]
    Guo J P. Advances in impacts of climate change on agricultural production in China. J Appl Meteor Sci, 2015, 26(1): 1-11. doi:  10.11898/1001-7313.20150101
    [10]
    Huo Z G, Li M S, Li N, et al. Impacts of seasonal climate warming on crop diseases and pests in China. Scientia Agricultura Sinica, 2012, 45(11): 2168-2179. https://www.cnki.com.cn/Article/CJFDTOTAL-ZNYK201211006.htm
    [11]
    Huo Z G, Li M S, Wang L, et al. Impacts of climate warming on crop diseases and pests in China. Scientia Agricultura Sinica, 2012, 45(10): 1926-1934. https://www.cnki.com.cn/Article/CJFDTOTAL-ZNYK201210006.htm
    [12]
    Ye C L, Huo Z G, Ding S L, et al. Advance in study on formation of meteorological environment causing crop's diseases and insect pests. Journal of Natural Disasters, 2005, 14(1): 90-97. https://www.cnki.com.cn/Article/CJFDTOTAL-ZRZH20050100D.htm
    [13]
    Wang C Z, Huo Z G, Zhang L, et al. Construction of forecasting model of meteorological suitability for wheat aphids in northern China. J Appl Meteor Sci, 2020, 31(3): 280-289. doi:  10.11898/1001-7313.20200303
    [14]
    Hou Y Y, Zhang L, Wu M X, et al. Advances of modern agrometeorological service and technology in China. J Appl Meteor Sci, 2018, 29(6): 641-656. doi:  10.11898/1001-7313.20180601
    [15]
    Zhang K, Pan X, Yu D, et al. Systemically modeling the relationship between climate change and wheat aphid abundance. Science of The Total Environment, 2019(674): 392-400. http://www.zhangqiaokeyan.com/academic-journal-foreign_other_thesis/0204113064054.html
    [16]
    Drake V A. The influence of weather and climate on agriculturally important insects: An Australian perspective. Australian Journal of Agricultural Research, 1994, 45(3): 487-509. doi:  10.1071/AR9940487
    [17]
    Li W F, Yin B, Cao Z W, et al. Variation of wheat aphid population in Xuchang and prediction models with meteorological data. Journal of Henan Agricultural Sciences, 2011, 40(3): 81-84. https://www.cnki.com.cn/Article/CJFDTOTAL-HNNY201103025.htm
    [18]
    Mattson W J, Haack R A. The role of drought in outbreaks of Plant eating insects. Bioscience, 1987, 37(2): 110-118. doi:  10.2307/1310365
    [19]
    Zhang X X, Zhai B P, Mu J Y, et al. Insect Ecology and Forecast. Beijing: China Agriculture Press, 1985: 205-207.
    [20]
    Jin R, Li S C. Forecasting model for the occurrence degree of wheat aphids based on wavelet neural network. Acta Entomologica Sinica, 2015, 58(8): 893-903. https://www.cnki.com.cn/Article/CJFDTOTAL-KCXB201508010.htm
    [21]
    Wang H J, Wang G S, Zhang L S, et al. Ecological Regionalization of aphids in cotton seeding stage in Hebei Province. Chinese Journal of Agrometeorology, 1989, 10(3): 43-46. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGNY198903009.htm
    [22]
    Guo A H, Wang C Z, Li X, et al. Preliminary study on meteorological risk zoning of pine moth infestation in northeast China. Journal of Catastrophology, 2012, 27(2): 24-28. https://www.cnki.com.cn/Article/CJFDTOTAL-ZHXU201202006.htm
    [23]
    Zhang L, Guo A H, Wang C Z. Climatic risk assessment of wheat powdery mildew in China. Chinese Journal of Ecology, 2016, 35(5): 1330-1337. https://www.cnki.com.cn/Article/CJFDTOTAL-STXZ201605029.htm
    [24]
    Wu C J. Land Use Map of China. Beijing: SinoMaps Press, 2001.
    [25]
    Cleveland W S, Devlin S J. Locally weighted regression: An approach to regression analysis by local fitting. Journal of American Statistical Association, 1988, 83: 596-610. doi:  10.1080/01621459.1988.10478639
    [26]
    Xu Y.The Research on Risk Evaluation Technology of Meteorological Disaster Based on GIS.Nanning: Guangxi Teachers Education University, 2014.
    [27]
    Mao L X, Wei L. Meteorological Service Manual of Staple Crops. Beijing: China Meteorological Press, 2015.
    [28]
    Li S K, Huo Z G, Wang S Y, et al. Risk evaluation system and models of agrometeorological disasters. Journal of Natural Disasters, 2004, 13(1): 77-87. https://www.cnki.com.cn/Article/CJFDTOTAL-ZRZH200401013.htm
    [29]
    Shi P J. Theory and practice on disaster system research in a fifth time. Journal of Natural Disasters, 2009, 18(5): 1-9. https://www.cnki.com.cn/Article/CJFDTOTAL-ZRZH200905000.htm
    [30]
    Jia H C, Wang J A, Pan D H, et al. Maize drought disaster risk assessment based on EPIC model: A case study of maize region in northern China. Acta Geographica Sinica, 2011, 66(5): 643-652. https://www.cnki.com.cn/Article/CJFDTOTAL-DLXB201105010.htm
    [31]
    Chen J J, Li L C, Lin J, et al. Integrated risk evaluation on meteorological disasters of loquat in Fujian Province. J Appl Meteor Sci, 2014, 25(2): 232-241. http://qikan.camscma.cn/article/id/20140213
    [32]
    Zhang F S.Study on the impact of plant protection on grain production security in China.Fuzhou: Fujian Agriculture and Forestry University, 2007.
    [33]
    Zhou S T, Wang J Z. Development and trend of diseases and pests of wheat in Henan Province. Journal of Forecast of Disease and Pest, 1991(2): 49-51. https://www.cnki.com.cn/Article/CJFDTOTAL-ZBJS199102020.htm
    [34]
    National Agro-Technical Extension and Service Center. Annual Report on Monitoring and Early Warning of Major Crop Diseases and Pests(2014). Beijing: China Agriculture Press, 2015.
    [35]
    National Agro-Technical Extension and Service Center. Annual Report on Monitoring and Early Warning of Major Crop Diseases and Pests(2015). Beijing: China Agriculture Press, 2016.
    [36]
    Zhang L, Yang B Y. Risk assessment of drought damage during growing stages for winter wheat in North China. Agricultural Research in the Arid Areas, 2016, 34(4): 274-280;286. https://www.cnki.com.cn/Article/CJFDTOTAL-GHDQ201604042.htm
    [37]
    Wang L X, Wang T, Li Q, et al. Study on spatial and temporal characteristics of drought of winter wheat in Henan Province based on crop water deficit index. Jiangsu Agricultural Sciences, 2019, 47(12): 83-88. https://www.cnki.com.cn/Article/CJFDTOTAL-JSNY201912017.htm
    [38]
    China Meteorological Administration. China Meteorological Disaster Yearbook(2014). Beijing: China Meteorological Press, 2015.
    [39]
    Wang Y J, Zhou B T, Ren Y Y, et al. Impacts of global climate change on China's climate security. J Appl Meteor Sci, 2016, 27(6): 750-758. doi:  10.11898/1001-7313.20160612
    [40]
    Ren S X, Zhao H R, Qi Y, et al. The outbreak and damage of the Pleonomus Canaliculatus in wheat field under the background of climate change. J Appl Meteor Sci, 2020, 31(5): 620-630. doi:  10.11898/1001-7313.20200509
    [41]
    Wang C Z, Zhang L, Guo A H, et al. Long-term meteorological prediction model on the occurrence and development of rice leaf roller based on atmospheric circulation. J Appl Meteor Sci, 2019, 30(5): 565-576. doi:  10.11898/1001-7313.20190505
    [42]
    Ding Y H, Li X, Li Q P. Advances of surface wind speed changes over China under global warming. J Appl Meteor Sci, 2020, 31(1): 1-12. doi:  10.11898/1001-7313.20200101
    [43]
    Hartmann D L, Tank A M G K, Rusticucci M. Working Group Ⅰ Contribution to the IPCC Fifth Assessment Report, Climate Change 2013: The Physical Science Basic. Cambridge: Cambridge University Press, 2013: 1535.
    [44]
    Zhou G S, He Q J, Ji Y H. Advances in the international action and agricultural measurements of adaptation to climate change. J Appl Meteor Sci, 2016, 27(5): 527-533. doi:  10.11898/1001-7313.20160502
    [45]
    Li J J.Effects of Elevated Nocturnal Temperature on Experimental Population of Cereal Aphids.Yangling: Northwest A&F University, 2011.
    [46]
    Awmack C S, Harrington R, Leather S R. Host plant effects on the performance of the aphid 91 Aulacorthum solani (Homoptera: Aphididae) at ambient and elevated CO2. Global Change Biology, 1997(3): 545-549. doi:  10.1046/j.1365-2486.1997.t01-1-00087.x
  • 加载中
  • -->

Catalog

    Figures(7)  / Tables(2)

    Article views (2246) PDF downloads(151) Cited by()
    • Received : 2020-11-02
    • Accepted : 2020-12-30
    • Published : 2021-03-31

    /

    DownLoad:  Full-Size Img  PowerPoint