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二化螟种群密度的克力格估值及其模拟抽样
引用本文:袁哲明,柏连阳,王奎武,胡湘粤.二化螟种群密度的克力格估值及其模拟抽样[J].应用生态学报,2004,15(7):1166-1170.
作者姓名:袁哲明  柏连阳  王奎武  胡湘粤
作者单位:湖南农业大学植物保护学院,长沙,410128
基金项目:国家自然科学基金项目 ( 3 0 10 0 12 2 ),湖南省自然科学基金资助项目 ( 0 0JJY2 0 18)
摘    要:为设计可靠合理的二化螟幼虫种群密度抽样方案,从二化螟幼虫空间分布原始总体出发,另构建了一个随机总体和一个顺序总体,采用无放回随机抽样、间隔变程以上无放回随机抽样和基于克力格估值且初始点随机的顺序抽样对3总体进行了模拟抽样比较.结果表明,间隔变程以上随机抽样对原始总体平均数的估计优于随机抽样,且随总体聚集程度增加,间隔变程以上随机抽样愈优;正确识别种群空间格局极为重要,对聚集分布总体采用随机抽样和对随机分布总体采用间隔变程以上随机抽样均将降低抽样估计精度.针对随机抽样在应用上的局限性,提出了一种基于地统计学克力格估值、初始点随机的顺序抽样方案:它以初始点随机保证随机性,以顺序抽样保证可操作性,以二化螟种群空间分布的区域变量属性保证克力格样本较调查样本对局域样本和总体的平均数估计为优;且聚集范围一定时,总体聚集强度愈大,克力格样本局域估计和全局估计愈优于调查样本;取样间隔(以变程为标准)极为重要,样方的空间布局要平衡考虑相互独立的样方对数和变程范围内的样方对数。

关 键 词:有机肥  生物有机肥  烤烟  土壤微生物  青枯病  
文章编号:1001-9332(2004)07-1166-05
修稿时间:2003年4月18日

Krigle estimation and its simulated sampling of Chilo suppressalis population density
YUAN Zheming,Bai Lianyang,Wang Kuiwu and Hu Xiangyue.Krigle estimation and its simulated sampling of Chilo suppressalis population density[J].Chinese Journal of Applied Ecology,2004,15(7):1166-1170.
Authors:YUAN Zheming  Bai Lianyang  Wang Kuiwu and Hu Xiangyue
Institution:College of Plant Protection, Hunan Agricultural University, Changsha 410128, China. zhmyuan@sina.com
Abstract:In order to draw up a rational sampling plan for the larvae population of Chilo suppressalis,an original population and its two derivative populations,random population and sequence population,were sampled and compared with random sampling,gap-range-random sampling,and a new systematic sampling integrated Krigle interpolation and random original position.As for the original population whose distribution was up to aggregative and dependence range in line direction was 115 cm (6 9 units),gap-range-random sampling in line direction was more precise than random sampling.Distinguishing the population pattern correctly is the key to get a better precision.Gap-range-random sampling and random sampling are fit for aggregated population and random population,respectively,but both of them are difficult to apply in practice.Therefore,a new systematic sampling named as Krigle sample (n=441) was developed to estimate the density of partial sample (partial estimation,n=441) and population (overall estimation,N=1500).As for original population,the estimated precision of Krigle sample to partial sample and population was better than that of investigation sample.With the increase of the aggregation intensity of population,Krigel sample was more effective than investigation sample in both partial estimation and overall estimation in the appropriate sampling gap according to the dependence range.
Keywords:Chilo suppressalis  Geostatistics  Partial estimation  Overall estimation  Sampling  
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