摘要
本文用地统计学的方法研究了栗山天牛及其天敌花绒寄甲的空间分布规律,结果表明:栗山天牛与花绒寄甲均呈聚集性分布,而且栗山天牛分布较多的样地,花绒寄甲也较多,花绒寄甲与栗山天牛有较强的跟随效应。栗山天牛与花绒寄甲的空间分布模型为球状+指数套合模型。栗山天牛和花绒寄甲空间分布在四个方向的变程均在100 m左右,而且在四个方向均比较集中。栗山天牛在东西方向聚集度最高,超过了0.8,而花绒寄甲在南北方向聚集度最高,2008年达到0.8452,2009年达到0.7230。研究还表明,2008年人工释放花绒寄甲后,其成虫在林间逐渐扩散,聚集度下降。
In order to understand the spatial patterns of Massicus raddei and its parasitoid Dastarcus helophoroides,we investigated the number of M. raddei larvae in 2008 in Kuandian County Liaoning Province,and also the number of D. helophoroides adult in 2008 and 2009 in the same plots,and then analyzed the data by geostatistic. The results showed that both M. raddei and D. helophoroides were aggregation distribution, and more beetles distributed plots, also more the parasitoid, showed the parasitoid and the beetles had a strong following effect. The spatial distribution models of the longhorn beetle and its parasitoid were globular + index nested models. And the spatial variations of them were about 100 m away and relatively concentrated in four directions. The beetles were highest degree of aggregation in East-West direction, more than 0. 8, but the parasitoid aggregated in North-South direction,the degree of aggregation was 0. 8452 in 2008 and 0. 7230 in 2009. The results also showed that after released the parasitoid in 2008,its adults gradually spread in the forest,the degree of aggregation was decreased.
作者
唐艳龙
姜静
王小艺
魏可
杨忠岐
吕军
TANG Yan- Long;JIANG Jing;WANG Xiao- Yi;WEI be;YANG Zhong- Qi;LU Jun(School of Life Sciences, Zunyi Normal University, Zunyi 563002,Guizhou Province, China;Research Institute of Forest Ecology,Environment and Protection,Chinese Academy of FLaboratory of Forest Protection of State Forestry Administration, Beijing 100091, China;KuandianForest Pest & Disease Control Station,Kuandian 118200,Liaoning Province, China)
出处
《环境昆虫学报》
CSCD
北大核心
2018年第2期290-298,共9页
Journal of Environmental Entomology
基金
国家"十一五"科技支撑计划课题(2006BAD08A12)
林业科技成果国家级推广计划[2015]42号
关键词
栗山天牛
花绒寄甲
空间分布
地统计学
Massicus raddei ( Blessig )
Dastarcer helophoroides (Fairmaire)
spatial patterns
geostatistic