鼠密度与气象因素的响应面分析研究

目的在相关回归分析的基础上，运用响应面模型分析对影响鼠密度的复合气象因素进行研究。方法连续监测鼠密度与7种气象因子资料，进行相关和线性回归分析，建立气象因子对鼠密度影响的响应面模型。结果线性回归分析表明月平均最低气温、日照时间、降雨量对回归方程的贡献最大，线性回归方程有统计学意义（P〈0．030），复相关系数为0．716。响应面分析表明月平均最低气温（P=0．003）、降雨量的二次方（P=O．059）、月平均最低气温与日照的交互作用（P=0．027）是影响鼠密度的气象因素，响应面模型有统计学意义（P〈0．013），复相关系数为0．761。结论响应面分析法能够较好地应用于气象因子对鼠密度的影响，建立的响应面模型优于多元线性回归，气象因素对鼠密度的影响是多因素及交互作用的结果。

Study on the relationship of meteorological factors and rats density by Response surface methodology

Objective To study the effect of meteorological factors on rats density by Response surface methodology （RSM） based on correlation and regression analysis. Methods The meteorological factors and rats density were monitored continuously. A response surface model was made by the correlation and regression analysis of them. Results Linear regression analysis （P〈0.030）indicated that monthly average minimum temperature, sunshine time and precipitation were the main influence factors, and the multiple correlation coefficient was 0.716. However, RSM suggested that monthly average minimum temperature （P=0.003）, precipitation square （P=0.059）, interaction of monthly minimum temperature and sunshine （P=0.027） affected mostly the density of rats, and its multiple correlation coefficient was 0.761. Conclusion The effect of meteorological factors on the rats density could be evaluated by RSM model. This model was superior to linear regression model. The effect of meteorological factors on rats density was resulted from multiple factors and their interaction.