Species spatial distribution analysis using nearest neighbor methods: aggregation and self-similarity
Gao, Meng1; Wang, Xinxiu1,2; Wang, De1; Gao, M (reprint author), Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Shandong, Peoples R China. gaomeng03@hotmail.com
发表期刊ECOLOGICAL RESEARCH
ISSN0912-3814
2014-03-01
卷号29期号:2页码:341-349
关键词Spatial Aggregation Scaling Occurrence Map Fractal Dimension Barro Colorado Island Panama
DOI10.1007/s11284-014-1131-8
产权排序[Gao, Meng; Wang, Xinxiu; Wang, De] Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Shandong, Peoples R China; [Wang, Xinxiu] Chinese Acad Sci, Grad Univ, Beijing 100049, Peoples R China
作者部门海岸带信息集成与综合管理实验室
英文摘要Spatial aggregation and self-similarity are two important properties in species spatial distribution analysis and modeling. The aggregation parameter k in the negative binomial distribution model and fractal dimension are two widely used measures of spatial aggregation and self-similarity, respectively. In this paper, we attempt to describe spatial aggregation and self-similarity using nearest neighbor methods. Specifically, nearest neighbor methods are used to calculate k and box-counting fractal dimension of species spatial distribution. First, five scaling patterns of k are identified for tree species in a tropical rainforest on Barro Colorado Island (BCI), Panama. Based on the scaling patterns and the means of the nth nearest neighbor distance (NND), the mean NND of higher ranks can be accurately predicted. Second, we describe how to use the theoretical probability distribution model of the nth NND for a homogeneous Poisson process on regular fractals to estimate the fractal dimension. The results indicate that the fractal dimensions estimated using the nearest neighbor method are consistent with those estimated using the scale-area method for 85 tree species on BCI (abundance a parts per thousand yen 100 individuals and a parts per thousand currency sign 5000 individuals). For other tree species, the breakdown of self-similarity in estimates of fractal dimension causes these two methods to be inconsistent. The applicability of the nearest neighbor method is also discussed.
文章类型Article
资助机构National Natural Science Foundation of China 31000197 41001360 ; Knowledge Innovation Project of the China Academy of Sciences KZCX2-EW-QN209
收录类别SCI
语种英语
关键词[WOS]POINT PATTERN-ANALYSIS ; STATISTICAL-ANALYSIS ; SCALING PATTERNS ; ABUNDANCE ; OCCUPANCY ; ECOLOGY ; POPULATIONS ; MODEL ; SIZE
研究领域[WOS]Environmental Sciences & Ecology
WOS记录号WOS:000333157400022
引用统计
被引频次:3[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.yic.ac.cn/handle/133337/8602
专题中国科学院海岸带环境过程与生态修复重点实验室_海岸带信息集成与战略规划研究中心
通讯作者Gao, M (reprint author), Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Shandong, Peoples R China. gaomeng03@hotmail.com
作者单位1.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Shandong, Peoples R China
2.Chinese Acad Sci, Grad Univ, Beijing 100049, Peoples R China
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GB/T 7714
Gao, Meng,Wang, Xinxiu,Wang, De,et al. Species spatial distribution analysis using nearest neighbor methods: aggregation and self-similarity[J]. ECOLOGICAL RESEARCH,2014,29(2):341-349.
APA Gao, Meng,Wang, Xinxiu,Wang, De,&Gao, M .(2014).Species spatial distribution analysis using nearest neighbor methods: aggregation and self-similarity.ECOLOGICAL RESEARCH,29(2),341-349.
MLA Gao, Meng,et al."Species spatial distribution analysis using nearest neighbor methods: aggregation and self-similarity".ECOLOGICAL RESEARCH 29.2(2014):341-349.
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