气象因素变化与虫害发生的灰色关联分析
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摘要
为探究气象因素变化对虫害发生的影响规律,以21 a落叶松毛虫幼虫发生面积为主系列,相应时间节点气象数据为映射量进行灰色关联分析,得出其灰色关联度排序为:全年极端最低气温(γ_(09)=0. 87)> 3月份降水量(γ_(03)=0. 86)=8月份降水量(γ_(08)=0. 86)> 4月份连续无降水日数(γ_(06)=0. 83)> 3月份连续无降水日数(γ_(04)=0. 81)> 4月份降水量(γ_(05)=0. 78)> 7月份降水量(γ_(07)=0. 72)> 4月份一候平均气温(γ_(02)=0. 66)>繁殖期平均风速(γ_(010)=0. 64)> 3月份六候平均气温(γ_(01)=0. 60)。通过绝对关联度概念的引入分析验证计算结果:全年极端最低气温对虫害发生影响最大,3月六候平均气温与虫害发生的关联度较小。因此可从上年8月降水量、全年极端气温、3月降水量为切入点预测气象相似年落叶松毛虫是否大发生,为森防部门提供参考。
In order to explore the rule of the influence of meteorological factors on the occurrence of insect pests,the Dendrolimus superans occurrence area was used as main sequence and the time node meteorological data were used as the gray correlation analysis.The gray correlation degree was sorted as: extreme minimum temperature throughout the year( γ_(09)= 0. 87) > precipitation in March( γ_(03)= 0. 86) = precipitation in August( γ_(08)= 0. 86) > consecutive arid days in April( γ_(06)= 0. 83) > consecutive arid days in March( γ_(04)= 0. 81) > precipitation in April( γ_(05)= 0. 78) > precipitation in July( γ_(07)= 0. 72) > average temperature in first five days of April( γ_(02)= 0. 66) > average wind speed during breeding season( γ_(010)= 0. 64) > average temperature in last five days of March( γ_(01)=0. 60). Analyze and verify the calculation results by the introduction of absolute relation degree,which is: extreme minimum temperature throughout the year influence the pests most,while the average temperature in last five days of March influence the pests lest.Therefore,the occurrence of Dendrolimus superans in meteorological similarity year can be predicted by analyzing the precipitation in August,extreme minimum temperature throughout the year and precipitation in March,which provides the reference for the forest defense department.
In order to explore the rule of the influence of meteorological factors on the occurrence of insect pests,the Dendrolimus superans occurrence area was used as main sequence and the time node meteorological data were used as the gray correlation analysis.The gray correlation degree was sorted as: extreme minimum temperature throughout the year( γ_(09)= 0. 87) > precipitation in March( γ_(03)= 0. 86) = precipitation in August( γ_(08)= 0. 86) > consecutive arid days in April( γ_(06)= 0. 83) > consecutive arid days in March( γ_(04)= 0. 81) > precipitation in April( γ_(05)= 0. 78) > precipitation in July( γ_(07)= 0. 72) > average temperature in first five days of April( γ_(02)= 0. 66) > average wind speed during breeding season( γ_(010)= 0. 64) > average temperature in last five days of March( γ_(01)=0. 60). Analyze and verify the calculation results by the introduction of absolute relation degree,which is: extreme minimum temperature throughout the year influence the pests most,while the average temperature in last five days of March influence the pests lest.Therefore,the occurrence of Dendrolimus superans in meteorological similarity year can be predicted by analyzing the precipitation in August,extreme minimum temperature throughout the year and precipitation in March,which provides the reference for the forest defense department.
引文
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[20]刘思峰,谢乃明,等.灰色系统理论及其应用[M].北京:科学出版社,2013.LIU S F,XIE N M,et al. Grey systems theory and the application[M]. Beijing:Science Press,2013.
[21] CHAN J W K. Application of grey relational analysis for ranking material options[J]. International Journal of Computer Applications in Technology,2006,26(4):210-217.
[22] WESTERHUIS J A,DERKS E,HOEFSLOOT H,et al. Grey Component Analysis[J]. Journal of Chemometrics,2007,21(10-11):474-485.
[23]李芝茹.基于灰色系统理论对大兴安岭白桦低质林改造模式的评析[D].哈尔滨:东北林业大学,2012.LI Z R. The evaluation analysis to the reconstruction mode of white birch low-quality forest based on the grey system theory[D].Harbin:Northeast Forestry University,2012.
[24]铁力市病防站积极指导乡镇开展松毛虫防治工作[N/OL].中国森防信息网http://www. forestpest. org/localinfo/heilongjiang/04/10. html The Dendrolimus superans prevention and control work of township was carry out under the guides of Tieli City Disease Prevention Station[N/OL]. China Forest Defense Information Network,http://www. forestpest. org/localinfo/heilongjiang/04/10. html
[2]徐艳梅.林木病虫害防治实用技术图解[M].北京:化学工业出版社,2015.XU Y M. The practical diagram of forest pest control techniques[M]. Beijing:Chemical Industry Press,2015.
[3] TOMIN F N,OSINA O V,KUZUBOV A A,et al. Stability of forest lepidopteran pheromones against environmental factors[J]. Biophysics,2011,56(4):695-701.
[4] KIRICHENKO N,BARANCHIKOV Y N,VIDAL S. Performance of the potentially invasive Siberian moth Dendrolimus superans sibiricus on coniferous species in Europe[J]. Agricultural and Forest Entomology,2009,11(3):247-254.
[5] CHEN Y T,VASSEUR L,YOU M S. Potential distribution of the invasive loblolly pine mealybug,Oracella acuta(Hemiptera:Pseudococcidae),in Asia under future climate change scenarios[J]. Climatic Change,2017,141(4):719-732.
[6]桂占吉,王凯华,陈兰荪.病虫害防治的数学理论与计算[M].北京:科学出版社,2014.GUI Z J,WANG K H,CHEN L S. Mathematical theory and calculation of pest control techniques[M]. Beijing:Science Press,2015.
[7]冯慧敏,闫巍,李雪非.基于Choquet积分的非线性虫害预测[J].湖北农业科学,2013,52(22):5485-5487.FENG H M,YAN W,LI X F. Non-linear prediction of insects based on Choquet integral[J]. Hubei Agricultural Science,2013,52(22):5485-5487.
[8]王娟,姬兰柱,Marina K.黑龙江大兴安岭地区森林害虫发生面积与气象因子的关系[J].生态学杂志,2007,26(5):673-677.WAND J,JI L Z,MARINA K. Relationships between forest insect pest occurrence area and meteorological factors in Great Xing’an Mountains of Heilongjiang Province,Northeast China[J]. Chinese Journal of Ecology,2007,26(5):673-677.
[9]王文龙.落叶松毛虫成虫种群数量监测技术研究[D].北京,北京林业大学,2014.WANG W L. Technology of population dynamics monitoring of Dendrolimus superans(Butler)adult[D]. Beijing:Beijing Forestry University,2014.
[10]陈素华,张晓磊.落叶松毛虫发生与气象因子的关系及其发生面积预报[J].东北林业大学学报,2011,39(11):135-136.CHEN S H,ZHANG X L. Meteorological conditions and area forecast for occurrence of Dendrolimus superans in Inner Mongolia[J].Journal of Northeast Forestry University,2011,39(11):135-136.
[11]杨淑香,赵慧颖,包兴华.基于人工神经网络的落叶松毛虫发生量预测模型的研究[J].中国农学通报,2014,30(28):72-75.YANG S X,ZHAO H Y,BAO X H. A study on the forecast model of Dendrolimus superans Burler occurrence based on artificial neural network[J]. Chinese Agricultural Science Bulletin,2014,30(28):72-75.
[12]冯玉元.白僵菌防治思茅松毛虫研究[J].林业科技,2018,43(4):26-29.FENG Y Y. Study on the control of Dendrolimus kikuchii by Beauveria bassiana[J]. Forestry Science&Technology,2018,43(4):26-29.
[13]于跃,方磊,方国飞,等.气象因子对落叶松毛虫种群数量的影响[J].应用生态学报,2016,27(9):2839-2847.YU Y,FANG L,FANG G F,et al. Influences of meteorological factors on larch caterpillar population[J]. Chinese Journal of Applied Ecology,2016,27(9):2839-2847.
[14] KUMAR S,NEVEN L G,ZHU H Y,et al. Assessing the global risk of establishment of Cydia pomonella(Lepidoptera:Tortricidae)using CLIMEX and Max Ent Niche Models[J]. Journal of Economic Entomology,2015,108(4):1708-1719.
[15]张文一,景天忠,严善春.基于机器学习的落叶松毛虫发生面积预测模型[J].北京林业大学学报,2017,39(1):85-93.ZHANG W Y,JING T Z,YAN S C. Studies on prediction models of Dendrolimus superans occurrence area based on machine learning[J]. Journal of Beijing Forestry University,2017,39(1):85-93.
[16] KARIM M R,COCHEZ M,BEYAN O D,et al. Mining maxing frequent patterns in transactional databases and dynamic data streams:a spark-based approach[J]. Information Sciences,2018,432(3):278-300.
[17]张子恺,齐航,王上,等.基于Apriori算法的森林虫害预测方法[J].东北林业大学学报,2017,45(8):93-96.ZHANG Z K,QI H,WANG S,et al. Forest pest prediction method with apriori algorithm[J]. Journal of Northeast Forestry University,2017,45(8):93-96.
[18] ATHEE S,KASHYAP A. Adaptive-miner:an efficient distributed association rule mining algorithm on spark[J]. Journal of Big Date,2018,5(1):6.
[19]孙广婷,李丹,周唯唯,等.云计算下Spark进行Apriori算法林业病虫害防治研究[J].森林工程,2018,34(4):45-51.SUN G T,LI D,ZHOU W W,et al. Study on forest pest control based on Spark Apriori algorithm in cloud computing[J]. Forest Engineering,2018,34(4):45-51.
[20]刘思峰,谢乃明,等.灰色系统理论及其应用[M].北京:科学出版社,2013.LIU S F,XIE N M,et al. Grey systems theory and the application[M]. Beijing:Science Press,2013.
[21] CHAN J W K. Application of grey relational analysis for ranking material options[J]. International Journal of Computer Applications in Technology,2006,26(4):210-217.
[22] WESTERHUIS J A,DERKS E,HOEFSLOOT H,et al. Grey Component Analysis[J]. Journal of Chemometrics,2007,21(10-11):474-485.
[23]李芝茹.基于灰色系统理论对大兴安岭白桦低质林改造模式的评析[D].哈尔滨:东北林业大学,2012.LI Z R. The evaluation analysis to the reconstruction mode of white birch low-quality forest based on the grey system theory[D].Harbin:Northeast Forestry University,2012.
[24]铁力市病防站积极指导乡镇开展松毛虫防治工作[N/OL].中国森防信息网http://www. forestpest. org/localinfo/heilongjiang/04/10. html The Dendrolimus superans prevention and control work of township was carry out under the guides of Tieli City Disease Prevention Station[N/OL]. China Forest Defense Information Network,http://www. forestpest. org/localinfo/heilongjiang/04/10. html