| 青海巴滩草地小地老虎虫害发生的气象预测模型建立 |
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| 引用本文： | 郭连云,丁生祥,吴让.青海巴滩草地小地老虎虫害发生的气象预测模型建立[J].草业科学,2015,32(6):994-1001. |
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| 作者姓名： | 郭连云 丁生祥 吴让 |
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| 作者单位： | 1.青海省海南州气象局，青海 共和 813099； 2.青海省同德县气象局，青海 同德 813201 |
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| 摘 要： | 为了预防小地老虎(Agrotis ypsilon)的危害,采用相关分析、多元线性回归方法,利用2000-2013年青海省同德县巴滩放牧草地取得的小地老虎虫口密度数据和同时期气象观测资料,研究了气候因子对草原小地老虎虫害发生的影响。结果表明,近14年同德巴滩草原小地老虎虫害以每年6.81头·m-2的速率上升,虫口密度的平均绝对变率为66.07头·m-2,最多年虫口密度比最少年多93.95%。小地老虎虫口密度与气温、降水、地温、光照和平均风速之间的相关性较好。多元回归分析显示,影响小地老虎虫口密度的主导气候因子有上一年9月降水量、12月平均气温、上年年日照时数和12月10 cm平均地温,共同决定了小地老虎虫口密度的95.02%。回代检验表明,模型预测的准确率达96.3%,模拟效果较好。
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| 关 键 词： | 小地老虎 虫口密度 影响因子 预报模型 同德县 |
| 收稿时间： | 2014-10-11 |
The establishment of meteorological forecasting models for black cutworm on Batan area grassland in Qinghai |
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| GUO Lian-yun,DING Sheng-xiang,WU Rang.The establishment of meteorological forecasting models for black cutworm on Batan area grassland in Qinghai[J].Pratacultural Science,2015,32(6):994-1001. |
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| Authors: | GUO Lian-yun DING Sheng-xiang WU Rang |
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| Institution: | 1.Meteorological Bureau in Hainan State of Qinghai Province, Gonghe 813099, China; 2.Tongde Meteorological Bureau in Qinghai, Tongde 813201, China |
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| Abstract: | In order to prevent black cutworm damage, the influences of meteorological factors on the population of grassland black cutworm were analyzed by correlation analysis and regression analysis based on the population density of grassland black cutworm on Batan meadows in Tongde County and the ground meteorological observation data of Tongde County Meteorological Bureau in Qinghai Province during 2000-2013. During these studied 14 years, black cutworm increased with 6.81 head·m-2 per year with the average absolute rate of population density of 66.07 head·m-2 and the highest population density was 93.95% more than the lowest population density. There were good correlation between black cutworm population density and air temperature, precipitation, ground temperature, illumination and average wind speed. Multiple regression analysis indicated that the dominant climatic factors that affected population density of grassland black cutworm were the September precipitation last year, December average temperature, annual illumination duration and 10 cm average temperature in December, which had determined 95.02% of population density. Model test indicated that the model predictive accuracy was 96.3% which had good simulation. |
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| Keywords: | black cutworm population density impact factor forecast models Tongde County |
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