Article(id=1207692035058929800, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1207692033305714759, articleNumber=null, orderNo=20, doi=10.3981/j.issn.1000-7857.2024.06.00655, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1716998400000, receivedDateStr=2024-05-30, revisedDate=1733760000000, revisedDateStr=2024-12-10, acceptedDate=null, acceptedDateStr=null, onlineDate=1765865818990, onlineDateStr=2025-12-16, pubDate=1752336000000, pubDateStr=2025-07-13, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1754064000000, onlineIssueDateStr=2025-08-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1765865818990, creator=13701087609, updateTime=1774079786393, updator=sys-migrate, issue=Issue{id=1207692033305714759, tenantId=1146029695717560320, journalId=1146031591421210625, year='2025', volume='43', issue='13', pageStart='1', pageEnd='108', issueExtLink='null', onlineDate='null', pubDate='1752336000000', pubDateStr='2025-07-13', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1765865818573, creator='13701087609', updateTime=1774330918339, updator='13041195026', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1243197235173900530, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1207692033305714759, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1243197235173900531, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1207692033305714759, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=63, endPage=68, ext={EN=ArticleExt(id=1207692035780350103, articleId=1207692035058929800, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Ecological security assessment based on landscape analysis method, columnId=1150494642224591153, journalTitle=Science & Technology Review, columnName=Exclusive, runingTitle=null, highlight=null, articleAbstract=

Basin ecological security is a major issue for human survival and development and has become an important branch in the field of social security research. This paper applies the principles and analytical methods of landscape ecology to evaluate the ecological security of the Chahannaoer Basin. Starting from the perspective of landscape structure, the ecological security status of the basin in 2010 and 2024 was evaluated using metrics such as Patch Density (PD), Landscape Shape Index (LSI), Landscape Division Index (DIVISION), and Landscape Aggregation Index (AI). Furthermore, a dynamic change analysis is conducted. Meanwhile, the study calculated the intensity of mutual transitions between ecosystem types and the overall dynamic degree of the watershed within the specified time period. The results indicate that between 2010 and 2024, the forest area and construction land in the basin showed an upward trend, while the grassland area showed a downward trend, and the saline-alkali land area increased significantly. A comprehensive analysis of the spatial distribution patterns of the indices PD, LSI, DIVISION, and AI reveals that the fragmentation of most landscapes decreased. Notably, the fragmentation of croplands and forests showed a significant decline, whereas the fragmentation of wetlands increased sharply. During this period, the land cover transition index and the comprehensive land cover change rate in the Chahannaoer Basin were 47.36% and 20.54%, respectively, indicating that land cover types are still transitioning towards a more favorable state.

, authors=null, authorsList=Guijie YUE, Gang ZHANG, Tao WANG, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=All rights reserved. Unauthorized reproduction is prohibited., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1207692037525180612, articleId=1207692035058929800, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=基于景观分析法的生态安全状况评估, columnId=1150494642375586098, journalTitle=科技导报, columnName=特色专题, runingTitle=null, highlight=null, articleAbstract=

将景观生态学原理与分析方法运用到察汗淖尔流域的生态安全评价中,从景观结构出发,通过斑块密度(patch density,PD)、景观形状指数(landscape shape index,LSI)、景观分离度指数(landscape division index,DIVISION)和景观聚集度指数(landscape aggregation index,AI),对察汗淖尔流域2010年和2024年2期的生态安全状况进行了评价,并开展了动态变化分析。与此同时,计算了该时间范围内流域生态系统的相互转换强度和综合动态度。结果表明,2010—2024年,流域和建设用地森林面积呈现上涨的趋势,草地面积呈现下降趋势,而盐碱地面积显著上升。综合分析格局指数值PD、LSI、DIVISION、AI的空间分布规律表明,大部分景观破碎度呈下降趋势,其中,耕地和森林的景观破碎度的下降较为显著,湿地的景观破碎度的增加较为急剧。在该时间段内,察汗淖尔土地覆被转类指数和土地覆被综合变化率分别为47.36% 和20.54%,表明土地覆被类型仍然在向较好的方向转变。

, authors=

岳贵杰,副教授,研究方向为遥感信息获取及应用,电子信箱:

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岳贵杰,副教授,研究方向为遥感信息获取及应用,电子信箱:

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土地覆盖类型 生态系统级别 土地覆盖类型 生态系统级别
湿地 1 耕地 5
森林 2 盐碱地 7
其他林地 3 建设用地 8
草地 4 其他林地 9
), ArticleFig(id=1242143936609853494, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1207692035058929800, language=CN, label=表1, caption=

土地覆被类型及其对应生态级别

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土地覆盖类型 生态系统级别 土地覆盖类型 生态系统级别
湿地 1 耕地 5
森林 2 盐碱地 7
其他林地 3 建设用地 8
草地 4 其他林地 9
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基于景观分析法的生态安全状况评估
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岳贵杰 1, 2 , 张刚 3 , 王涛 4
科技导报 | 特色专题 2025,43(13): 63-68
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科技导报 |特色专题 2025 , 43 (13) : 63 -68
基于景观分析法的生态安全状况评估
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岳贵杰1, 2 , 张刚3, 王涛4
作者信息
  • 1. 北京工业职业技术学院, 北京 100042
  • 2. 北京市电气安全技术研究所, 北京 100042
  • 3. 中国测绘科学研究院, 北京 100830
  • 4. 北京四维远见信息技术有限公司, 北京 100039
Ecological security assessment based on landscape analysis method
Guijie YUE1, 2 , Gang ZHANG3, Tao WANG4
Affiliations
  • 1. Beijing Polytechnic College, Beijing 100042, China
  • 2. Beijing Institute of Electrical Safety, Beijing 100042, China
  • 3. Chinese Academy of Surveying and Mapping, Beijing 100830, China
  • 4. Beijing Geo-Vision Technology Company Limited, Beijing 100039, China
出版时间: 2025-07-13 doi: 10.3981/j.issn.1000-7857.2024.06.00655
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将景观生态学原理与分析方法运用到察汗淖尔流域的生态安全评价中,从景观结构出发,通过斑块密度(patch density,PD)、景观形状指数(landscape shape index,LSI)、景观分离度指数(landscape division index,DIVISION)和景观聚集度指数(landscape aggregation index,AI),对察汗淖尔流域2010年和2024年2期的生态安全状况进行了评价,并开展了动态变化分析。与此同时,计算了该时间范围内流域生态系统的相互转换强度和综合动态度。结果表明,2010—2024年,流域和建设用地森林面积呈现上涨的趋势,草地面积呈现下降趋势,而盐碱地面积显著上升。综合分析格局指数值PD、LSI、DIVISION、AI的空间分布规律表明,大部分景观破碎度呈下降趋势,其中,耕地和森林的景观破碎度的下降较为显著,湿地的景观破碎度的增加较为急剧。在该时间段内,察汗淖尔土地覆被转类指数和土地覆被综合变化率分别为47.36% 和20.54%,表明土地覆被类型仍然在向较好的方向转变。

土地利用  /  景观格局  /  生态安全  /  综合动态度

Basin ecological security is a major issue for human survival and development and has become an important branch in the field of social security research. This paper applies the principles and analytical methods of landscape ecology to evaluate the ecological security of the Chahannaoer Basin. Starting from the perspective of landscape structure, the ecological security status of the basin in 2010 and 2024 was evaluated using metrics such as Patch Density (PD), Landscape Shape Index (LSI), Landscape Division Index (DIVISION), and Landscape Aggregation Index (AI). Furthermore, a dynamic change analysis is conducted. Meanwhile, the study calculated the intensity of mutual transitions between ecosystem types and the overall dynamic degree of the watershed within the specified time period. The results indicate that between 2010 and 2024, the forest area and construction land in the basin showed an upward trend, while the grassland area showed a downward trend, and the saline-alkali land area increased significantly. A comprehensive analysis of the spatial distribution patterns of the indices PD, LSI, DIVISION, and AI reveals that the fragmentation of most landscapes decreased. Notably, the fragmentation of croplands and forests showed a significant decline, whereas the fragmentation of wetlands increased sharply. During this period, the land cover transition index and the comprehensive land cover change rate in the Chahannaoer Basin were 47.36% and 20.54%, respectively, indicating that land cover types are still transitioning towards a more favorable state.

landuse  /  landscape pattern  /  ecological safety  /  comprehensive dynamic degree
岳贵杰, 张刚, 王涛. 基于景观分析法的生态安全状况评估. 科技导报, 2025 , 43 (13) : 63 -68 . DOI: 10.3981/j.issn.1000-7857.2024.06.00655
Guijie YUE, Gang ZHANG, Tao WANG. Ecological security assessment based on landscape analysis method[J]. Science & Technology Review, 2025 , 43 (13) : 63 -68 . DOI: 10.3981/j.issn.1000-7857.2024.06.00655
察汗淖尔流域位于京津风沙源头区域,是建设中国北方生态安全屏障、阻挡风沙入侵的重要组成部分。生态安全是指人们赖以生存发展的生态环境系统处于一种不受污染和不受危害或破坏的良好状态,是人类生态安全的核心,同时也是国家可持续发展的基础[12]。察汗淖尔流域位于内蒙古自治区中西部,是典型的内陆干旱和半干旱地区,生态系统脆弱,生态安全状况长期以来备受关注。由于气候变化和人类活动(如农业灌溉、工业用水和城市化扩展),流域内的水资源短缺问题加剧,导致湖泊萎缩甚至干涸。水资源过度开发直接影响了区域生态系统的稳定性。因此,对察汗淖尔流域生态安全进行有效的评估具有重要意义。
模糊综合评价法、综合指数法、生态足迹法等方法常被用于生态安全的评估[35]。模糊综合评价法的优势在于能够考虑到生态安全系统内部关系的错综复杂及模糊性,但模糊隶属函数的确定及指标参数的模糊化会掺杂人为因素从而丢失有用信息;综合指数法能够体现生态安全的综合性、整体性和层次性,但它容易将问题简单化,难以反映系统本质;生态足迹法近年来应用较为广泛,但由于其过于简单和静态化,很难对生态安全进行定量评估。
景观是生态环境管理的基础单元,对景观水平结构与过程特征的生态安全研究与评价,有利于实现生态安全现状与动态的相结合[6]。通过景观动态干扰分析,可以明确人类活动对流域生态安全的影响性质与过程,从而有针对性地提出生态安全修复和保护措施。现有研究中较多通过景观指数构建评价模型对研究区进行生态安全评价,都取得了较为不错的效果[79]。本研究将景观生态学原理与分析方法引入察汗淖尔流域的生态安全评价中,通过遥感数据的解析获取研究区土地利用和景观指数,并在此基础上计算生态系统类型转换强度和生态系统综合动态度,从而实现对该流域生态安全状况的全面评估。
察汗淖尔流域位于内蒙古自治区乌兰察布市商都县和河北省张家口市尚义县交界处,总面积为7359 km2。流域海拔为1272~1800 m,为典型的波状高原地形,地处半干旱的农牧交错带地区,属中温带半干旱大陆性季风气候。年平均降水量为300~400 mm,且降水量由南向北递减,由山区向平原地区递减。流域内冬季严寒、夏季凉爽,四季分明,年均日照时数2981 h,无霜期103 d。该流域位于商都盆地中央,呈不规则的长椭圆形,湖盆西南至东北向较长,约为17 km,西北至东南向较短,约为5.5 km,东南与河北省尚义县接壤。目前,该流域内的湖泊已成为季节性湖泊,根据第二次全国土地调查统计的水体面积为24.59 km2,2/3在商都县、1/3在尚义县(图 1)。
景观指数的计算是以土地利用数据为基础的,本研究采用2010年和2024年的Landsat 8遥感影像,采用最大似然监督分类法获取土地利用数据,并参照对应时期的全国林地一张图数据和全国第二次土地利用调查数据构建分类体系。土地利用信息提取的主要流程如下。
1) 遥感影像预处理。以1∶10000地形图为参考,采用二次多项式和最近邻域插值法对两期影像分别进行几何精纠正并保证配准误差在1个像元以内。在ERDAS软件中,将纠正好的影像采用察汗淖尔流域的边界进行掩膜处理,最终得到察汗淖尔的2期Landsat 8影像。
2) 土地利用分类。结合监督分类的方法将土地利用分为耕地、林地、草地、水域、建设用地(城乡、工矿、居民用地)和未利用土地6个一级类型以及25个二级类型。精度利用地面调查样地及收集到的参考图来验证。
3) 为了更详细分析察汗淖尔流域各子生态系统类型面积及其变化情况,根据分类结果,结合《国家森林资源连续清查技术规定(2014)》以及察汗淖尔流域实际的生态状况特征进行了调整和界定。最终将土地利用类型分为耕地、森林、草地、湿地、建设用地、盐碱地、未成林造林地、苗圃、无立木林地和其他等10类。
主要从生态系统格局和生态系统类型转换特征2个角度评估流域生态安全状况。
景观稳定性强调的是景观抵抗干扰、保持原状的能力,能够反映系统在受到人类的干扰和破坏以后的景观生态安全状态[10]。通过斑块密度(patch density,PD)、景观形状指数(landscape shape index,LSI)、景观分离度指数(landscape division index,DIVISION),以及景观聚集度指数(landscape aggregation index,AI)来评估[11]。各指数的计算方法如下。
1) 斑块密度。指某一类型在景观上的斑块密度(亦称孔隙度),揭示出景观基质被类型斑块分割的程度,对生物保护、物质和能量分布具有重要影响。PD值愈大,破碎化程度愈高,计算公式为
$P D=\frac{n_i}{A}$
式中,ni为第i类景观要素的总面积,A为所有景观的总面积,PD通常可计算斑块个数与整个研究区面积的比例,也可计算各景观类型斑块个数与其面积之比。
2) 景观形状指数。景观形状指数反映景观类型内部斑块的组合状况以及与外部其他景观类型组合分布的复杂程度,计算公式为
$L S I=\frac{e_i}{\text { mine }_i}$
式中,ei为第i类景观类型的边界长度;minei为由相同数量和形状的斑块组成的第i类景观类型的最小边界长度。
3) 景观分离度指数。景观分离度指数用于度量某类型景观不同斑块个体分布的离散程度,侧重景观内部,计算公式为
$D I V I S O N=1-\sum\limits_{j=1}^N\left(\frac{a_j}{T A}\right)^2 P D=\frac{n_i}{A}$
式中,aj为第j个斑块,TA为景观中斑块总面积。
4) 景观聚集度指数。景观聚集度指数基于同类型斑块像元间公共边界长度来计算。当某类型中所有像元间不存在公共边界时,该类型的聚合程度最低;当类型中所有像元间存在的公共边界达到最大值时,具有最大的聚合指数。计算公式为
$A I=\left[\frac{g_{i i}}{\max \rightarrow g_{i i}}\right] P D=\frac{n_i}{A}$
式中,gii为相应景观类型的相似邻接斑块数量。
生态系统类型相互转化强度反映研究区生态系统类型在一定时段内变化的总体趋势,通过土地覆被转类指数来衡量[12]。本研究按照该流域生态服务功能强度对土地利用类型进行生态系统级别的划分,具体如表 1所示。生态系统级别为1的地覆被类型具有最高的生态系统服务功能,如水源涵养、生物多样性保护、气候调节、土壤保持等。数字越大则生态系统服务功能越弱。在对生态系统类型定级后,将生态系统类型变化前后的生态级别相减,结果为正值表示研究区生态系统类型构成状况及宏观生态状况总体上转好,值越大,说明转好程度越高;反之表示转差,且绝对值越大,说明转差程度越大。
在完成了多期土地利用分类之后,土地覆被转类指数为
$L C C I=\frac{\sum\limits_k^n\left[A_k \times\left(D_{\mathrm{a}}-D_{\mathrm{b}}\right)\right]}{A} \times 100 \%$
式中,LCCI为土地覆被转类指数;Ak为由某种土地利用类型转化为另一种土地利用类型的面积;k为土地利用类型两两转化的类别;n为土地利用类型两两转化的总数;Da为转化前的生态系统级别;Db为转化后的生态系统级别;A为区域所有变化类型的变化面积总和。
生态系统综合动态度是定量描述研究时段内生态系统变化速度的指标,主要着眼于变化的过程而非变化结果,反映了研究区生态系统类型变化的剧烈程度,便于在不同空间尺度上找出生态系统类型变化的热点区域[13]。生态系统综合变化率为
$E C=\frac{\sum\limits_{i=1}^n \Delta E C O_{i-j}}{\sum\limits_{i=1}^n E C O_i} \times 100 \%$
式中,ECOi为监测起始时间第i类生态系统类型面积,ECOi根据全国生态系统类型图矢量数据在ARCGIS平台下进行统计获取。△ECOij为监测时段内第i类生态系统类型转为其他(j类,ij)生态系统类型的面积总和;△ECOij根据生态系统转移矩阵模型获取。
利用监督分类得到的两期土地利用结果如图 2所示。基于野外实测样点与人为影像判读获取验证数据,对每种土地利用类型获取高于50个点的参考数据。同时,利用参考数据计算分类的总体精度,结果表明土地利用分类精度均在90% 以上,可以满足本研究的精度需求。从土地利用分布图可以看出,察汗淖尔流域的耕地所占面积最大,其次为森林和草地,然后依次为无立木林地、未成林造林地、建设用地、盐碱地、湿地,苗圃所占面积最小。
图 3显示了各土地利用类型的变化趋势,耕地面积呈现下降趋势,从2010年的3001.78 km2下降到2024年的2876. 35 km2;森林面积呈现上涨的趋势,从2010年的1324.73 km2增加到2024年的1576.37 km2。草地面积呈现下降趋势;盐碱地面积上升。此外,建设用地面积有所增加。
图 4显示了基于2期土地利用数据对察汗淖尔流域各景观指数的计算结果。2010—2024年,湿地和其他土地的PD值呈波动上升趋势,表明湿地和其他土地的景观破碎化程度增加,其中湿地的破碎化进程较为明显。耕地、森林、草地、建设用地、其他林地的PD值呈下降趋势。盐碱地的PD值变化不大。在此期间,耕地、森林和草地的LSI值一直较高,说明这3个类型的土地形状较为复杂,边界分散性强,内部团聚性差;森林、湿地、盐碱地、其他土地的LSI值整体呈上升趋势,说明其形状由规则向复杂转变。从DIVISION值看,耕地、盐碱地和湿地呈下降趋势,表明景观由复杂、异质和不连续的斑块镶嵌体向单一、均质和连续的整体过渡,景观破碎度降低;其他林地的DIVISION值呈波动上升趋势,表明景观由单一、均质和连续的整体趋向于复杂、异质和不连续的斑块镶嵌体过渡,景观破碎度升高;其他景观类型的变化趋势不大,较为稳定。
与此同时,2010—2024年,除耕地的AI值呈波动上升外,其余类型的AI值都呈下降趋势。可以看出耕地的分布逐步集中,景观破碎化程度较低;而其他景观类型的分布由集中向分散转变,破碎化程度增加。
综合分析格局指数PDLSIDIVISIONAI的空间分布规律表明,耕地、森林、草地、建设用地、其他林地的景观破碎度呈下降趋势,其中耕地和森林的景观破碎度的下降较为显著;其他林地和盐碱地在该时间内景观破碎度相差不大;其他土地和湿地的景观破碎度呈上升趋势,其中湿地的景观破碎度的增加较为急剧。总体而言,流域景观破碎化程度降低,生态环境有所改善。
计算生态系统类型相互转换强度和综合动态度结果表明,2010—2024年,察汗淖尔土地覆被转类指数为47.36%。当土地覆被转类指数结果为正值时,表示区域土地覆被类型转好;结果为负值时,表明区域土地覆被类型转差。总的来说,2010—2024年,土地覆被类型仍然在向较好的方向转变。
本文通过Landsat 8遥感影像获取了察汗淖尔流域2010年和2024年的土地利用数据,并分析了各土地利用类型在该时间段内的变化。在此基础上,计算了2期的斑块密度、景观形状指数、景观分离度指数、景观聚集度指数,从景观格局角度分析评价了察汗淖尔流域的生态安全状况。结果表明,2010—2024年,流域内的盐碱地面积显著上升。从景观格局的角度分析,耕地和森林的景观破碎度下降较为显著,而湿地的景观破碎度急剧增加。总体来说,察汗淖尔土地覆被转类指数和土地覆被综合变化率分别为47.36%和20.54%,表明土地覆被类型仍然在向较好的方向转变。本文的方法通过对遥感影像的多尺度解译与景观格局指数的量化分析,能够全面、动态地揭示土地利用变化及生态斑块破碎化程度等关键生态特征,从而为生态安全格局的识别与风险评估提供科学依据。随着遥感技术与景观生态学的不断融合,该方法具备良好的通用性与适应性,可在数据条件满足的前提下推广应用于不同生态区类型(如城市群、农业区、生态敏感区等)的生态安全评价与空间优化[1415]。未来,结合高分辨率遥感数据、地理大数据与人工智能算法,有望进一步提高景观格局识别的精度与自动化水平,推动遥感景观分析法在国家生态安全格局构建、生态保护红线划定,以及区域国土空间规划等方面发挥更大作用。
  • 北京工业职业技术学院项目(BGY2022KY-06QT)
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doi: 10.3981/j.issn.1000-7857.2024.06.00655
  • 接收时间:2024-05-30
  • 首发时间:2025-12-16
  • 出版时间:2025-07-13
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  • 收稿日期:2024-05-30
  • 修回日期:2024-12-10
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北京工业职业技术学院项目(BGY2022KY-06QT)
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    1. 北京工业职业技术学院, 北京 100042
    2. 北京市电气安全技术研究所, 北京 100042
    3. 中国测绘科学研究院, 北京 100830
    4. 北京四维远见信息技术有限公司, 北京 100039
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
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Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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