方乐金, 李丰伯, 万志兵, 吴俊, 姚剑飞. 黄山松细纹新须螨发生与气象因素关系的分析[J]. 西南林业大学学报, 2014, 34(2): 104-107. DOI: 10.3969/j.issn.2095-1914.2014.02.020
引用本文: 方乐金, 李丰伯, 万志兵, 吴俊, 姚剑飞. 黄山松细纹新须螨发生与气象因素关系的分析[J]. 西南林业大学学报, 2014, 34(2): 104-107. DOI: 10.3969/j.issn.2095-1914.2014.02.020
FANG Lejin1, LI Fengbo1, WAN Zhibing1, WU Jun2, YAO Jianfei2. Study on Relationship Between Occurrence of Cenopalpus lineola in Pinus taiwanensis Plantation and Meteorological Factors[J]. Journal of Southwest Forestry University, 2014, 34(2): 104-107. DOI: 10.3969/j.issn.2095-1914.2014.02.020
Citation: FANG Lejin1, LI Fengbo1, WAN Zhibing1, WU Jun2, YAO Jianfei2. Study on Relationship Between Occurrence of Cenopalpus lineola in Pinus taiwanensis Plantation and Meteorological Factors[J]. Journal of Southwest Forestry University, 2014, 34(2): 104-107. DOI: 10.3969/j.issn.2095-1914.2014.02.020

黄山松细纹新须螨发生与气象因素关系的分析

Study on Relationship Between Occurrence of Cenopalpus lineola in Pinus taiwanensis Plantation and Meteorological Factors

  • 摘要: 在黄山风景区对黄山松细纹新须螨发生与气象因素的关系进行研究,结果表明:细纹新须螨发生与气温、降雨量、相对湿度等气候因子均有一定的关系。与细纹新须螨发生关系最为密切的气候因子为月均气温和旬均气温,曲线拟合结果与实际较吻合,细纹新须螨发生数量随温度升高而增加,当平均气温达到14℃以上,可用该曲线预测预报细纹新须螨发生的趋势;多个气候因子与细纹新须螨发生数量的回归分析表明,月均气温+月均降雨量+月均相对湿度、旬均气温+旬均降雨量、旬均降雨量+旬均相对湿度3个组合因子与细纹新须螨发生关系密切。采用旬均气温+旬均降雨量进行虫情预测预报,对指导防治具有实际应用意义。

     

    Abstract: The study on the relationship between meteorological factors and the occurrence of Cenopalpus lineola in Pinus taiwanensis plantation indicated that the occurrence of Cenopalpus lineola was related to the average temperature, rainfall, relative humidity and other meteorological factors. The monthly average temperature and the 10-day average temperature were most closely related to the occurrence of Cenopalpus lineola, and the simulated curves were well consistent with the actual results. The number of Cenopalpus lineola increased with temperature. When the average temperature was above 14℃, the occurence trend of Cenopalpus lineola could be forecast by the regression equation which had a high reference and application value. The regression analyses on the multiple meteorological factors and the occurrence of Cenopalpus lineola showed that the number of Cenopalpus lineola was closely related with three groups of meteorological factor combinations, i.e., the monthly average temperature + monthly average rainfall + monthly average relative humidity, 10-day average temperature + 10-day rainfall, and 10-day average rainfall + 10-day relative humidity. The regression equation of 10-day average temperature + 10-day average rainfall meteorological factor combinations with the occurrence of Cenopalpus lineola would be of practical significance for guiding the pest control.

     

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