北京地区美国白蛾时空分布变化及其影响因素

Spatiotemporal distribution of Hyphantria cunea(Drury)in Beijing and its influencing factors

美国白蛾是我国农林对外重大检疫对象之一,已经对我国的生态和经济造成了巨大损失,且十分难以防治。基于地统计学和地理信息系统原理,通过半变异函数分析,选取最优拟合模型,利用克里金插值法对2008—2016年北京地区美国白蛾的种群时空分布特征进行制图,并结合气象数据,运用冗余分析探究了美国白蛾种群动态变化与气候因子的关系。结果表明:(1)空间特征上,美国白蛾种群呈现聚集分布,分布趋势为东部、南部高,西部、北部少,主要集中在海拔400m以下的地区;(2)时间特征上,北京地区的美国白蛾种群一年3代,单年内越冬代数量远大于第一代和第二代,第一代和第二代种群数量相近,到次年越冬代种群数量回升,依此呈现周期性变化;(3)冗余分析结果显示影响北京地区美国白蛾种群变化与3月份平均相对湿度、7月份平均气温、上一年8月份最高温度呈正相关关系,与2月份日照时数、4月份最高温度、上一年9月份最低温度呈负相关关系;(4)插值结果表明在北京东部和南部边界与河北省交界处分布有一个较大的美国白蛾种群,能够影响该地区的美国白蛾种群数量。

Hyphantria cunea(H.cunea)is one of the major quarantine objects in China,which has caused great losses to the ecology and economy,and it is very difficult to control.Based on the principles of geostatistics and geographic information system,this study selected the best fitting model through semi variogram analysis,and mapped the spatial and temporal distribution characteristics of the population of American white moth in Beijing from 2008 to 2016 by Kriging interpolation method,exploring the relationship between the H.cunea population dynamics and climate factors by redundancy analysis(RDA).The results showed that:(1)in terms of spatial characteristics,the populations of the H.cunea presented a clustering distribution trend,which was higher in the east and south,less in the west and north,and mainly concentrated in the areas below 400 meters above sea level.(2)In terms of time characteristics,the populations of H.cunea in Beijing had three generations a year,showing periodic changes.The number of overwintering generations was much larger than that of the first and second generations,and the populations of the first and second generations were similar.(3)The results of RDA showed that the population of H.cunea in Beijing was positively correlated with the averagely relative humidity in March,the average temperature in July and the maximum temperature in August of the previous year,and negatively correlated with the sunshine hours in February,the maximum temperature in April and the minimum temperature in September of the previous year.(4)The interpolation results showed that there was a large population of H.cunea at the junction of the eastern and southern borders of Beijing and Hebei Province,which can affect the population of H.cunea in this area.