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国家标本资源共享平台蔷薇科植物标本记录采集地理偏差分析 被引量:3

Analysis of Geographical Deviation of Record Collection of Rosaceae Plant Specimens in National Specimen Resource Sharing Platform
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摘要 植物标本记录提供了植物空间分布的基础信息,为了评估标本采集记录数据的可信度以及是否具有利用价值,对蔷薇科植物标本的记录数据进行了一系列处理,以此分析标本记录的采集完整程度以及在地理上的采集偏差情况。本研究选取国家标本资源共享平台收录的蔷薇科植物标本采集记录,以县级行政单位为分类单元,结合Chao1模型(物种丰富度估计模型)和物种累积曲线对蔷薇科植物标本采集质量进行评估,相关参数包括:标本记录数量,物种丰富度,物种丰富度估计,标本采集完整性评估。结果显示:蔷薇科植物标本数据处理得到的1164个县中只有53个县级名录是采集完整的,采集极其不完整的县有13个。采集略微不完整的县(874)和相对不完整的县数量(185)远大于极其不完整的县,表明标本记录可信度较好,具有一定的利用价值。蔷薇科植物的标本采集地主要集中在西南地区(四川、重庆、云南)和华南地区(广东、广西)以及华中地区(湖南,湖北),而偏远地区的采集强度较低,如西北地区的新疆维吾尔自治区、青海省、甘肃省、西藏、内蒙古和东北地区。 The records of plant specimens provide basic information on the spatial distribution of plants. In order to evaluate the credibility and usefulness of the collection and recording data of specimens, a series of processing was performed on the recorded data of Rosaceae specimens to analyzethecollection integrity and geographical deviation of the specimen records.In this study, the collection records ofRosaceae plant specimens were selected from the national specimen resource sharing platform,Taking the countylevel administrative unit as the classification unit, combined with the Chao1 model(species richness estimation model) and the species accumulation curveto evaluatethe quality of the specimen collection of Rosaceae plants. Related parameters include: number of specimen records, species richness, species richness estimates, and specimen collection integrity assessment. The results showed that only 53 countyleveldirectoriesof the 1164 counties obtained from the processing of Rosaceae plantspecimen data were completed,and 13 county-leveldirectorieswere extremely incompleted. The number of slightly incomplete counties(874) and relatively incomplete counties(185) was far greater than the extremely incomplete counties, indicating that the specimen records was reliable and had a certain use value. The collection sites of Rosaceae plants are mainly concentrated in the southwest China(Sichuan, Chongqing, Yunnan) and South China(Guangdong, Guangxi) and Central China(Hunan, Hubei), The collection intensity of remote regions was relatively low, such as Xinjiang Uygur Autonomous Region, Qinghai Province, Gansu Province, Tibet, Inner Mongolia of the northwest regionand Northeast China.
作者 王凯莉 陈佳欣 范雪 Wang Kaili;Chen Jiaxin;Fan Xue(College of Resources and Environment,AnhuiAgrieultural University,Hefei,Anhui 230036,China;Institute of Botany,Chinese Academy of Sciences,Beijing 100093,China)
出处 《科研信息化技术与应用》 2018年第5期54-63,共10页 E-science Technology & Application
基金 国家标本资源共享平台(2005DKA21400) 中国植物主题数据库(DKA2017–12–02–11)
关键词 Chao1(物种丰富度估计值) 物种丰富度 物种累积曲线 数据质量评估 Chao 1(estimated species richness) species richness species accumulation curve data quality assessment
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