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基于GIS的陕西蝗虫地理分布及区划分析 被引量:6

Distribution and Geographic Division of Grasshopper in Shaanxi Based on GIS Techniques
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摘要 运用GIS(地理信息系统)技术研究陕西蝗虫物种地理分布及区划。以593个(0.2°×0.2°)经纬网 格单元统计蝗虫物种数,并采用多元分析的分层聚类方法进行聚类分析。结果表明:陕南山地蝗虫物种丰富度 总体高于秦岭以北地区,陕西最北部的鄂尔多斯高原蝗虫丰富度高于陕北黄土高原。当相关性系数为0.538时, 593个蝗虫地理分布单元聚类为9个单元组,该聚类结果与陕西自然环境区划基本相似,但秦岭山地被聚为两 类,即秦岭南坡与秦岭北坡;商南丘陵从秦岭山地分出;安康地区与巴山山地聚为一类;巴山与米仓山被聚为 并列的两组。该聚类结果表明陕西蝗虫的地理分布与自然环境密切相关,其分布格局表现出明显的地带性,陕 西多样化的地貌特征和气候类型,是形成蝗虫物种多样化的主要原因。 This paper deals with the distribution and geographic division of grasshopper in Shaanxi province using GIS (geographic information system) techniques. 593 longitude and latitude grid cells (0.2°×0.2°) were used to count the species number of grasshopper and multi-analysis hierarchical cluster method was used in the cluster analysis. The resuits showed (1) the number of grasshopper species of southern Shaanxi are greater than that of the rest of Shaanxi, and the number of grasshopper species of Ordos Plateau are greater than that of Loess Plateau of northern Shaanxi. The 593 distributional units are clustered into 9 groups with proximity coefficients of 0. 538 which resembles the physical division of Shaanxi. However, there are some differences in the distributional units as follows: Qinling mountain is divided into a southern and northern slope; Shangnan Hill is separated from Qinling Mountain; Ankang Area and Bashan Mountain from a single cluster of one group ; Bashan Mountain and Micang Mountain are clustered into two paratactic groups. The cluster results also showed that there is a close relation between the geographic distribution of grasshopper in Shaanxi and its envi- ronment, and the distribution pattern of grasshopper has obvious zone differences. We conclude that the diversification of the geography and climate types of Shaanxi are the main reasons of the diversification of grasshopper species.
出处 《Zoological Research》 CAS CSCD 北大核心 2005年第5期473-478,共6页 动物学研究(英文)
基金 国家自然科学基金资助项目(30307170)) 陕西师范大学2005年研究生培养创新基金
关键词 陕西 蝗虫 GIS 聚类分析 分布格局 Shaanxi Grasshopper GIS Cluster analysis Distribution pattern
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