Inferring multispecies distributional aggregation level from limited line transect-derived biodiversity data

doi:10.1111/2041-210X.13197

CORC > 成都生物研究所 > 中国科学院成都生物研究所 > 生物多样性与生态系统服务领域 > 中国科学院山地生态恢复与生物资源利用重点实验室

	Inferring multispecies distributional aggregation level from limited line transect-derived biodiversity data
	Chen, Youhua 6; Shen, Tsung-Jen 2; Chung, Hoang Van 6; Shi, Shengchao 6; Jiang, Jianping 6; Condit, Richard 3,4; Hubbell, Stephen P.1,5
刊名	METHODS IN ECOLOGY AND EVOLUTION
	2019
卷号	10 期号:7 页码:1015-1023
关键词	biodiversity distributional aggregation distributional interspersion landscape ecology Markov chain negative binomial model neighbouring effect sampling theory
ISSN号	2041-210X
DOI	10.1111/2041-210X.13197
产权排序	1
文献子类	Article
英文摘要	Ecologists have generally concluded that species distributions are not random (e.g. aggregate), based on single-species studies that applied single-species-based statistical methods, like the negative binomial model. Although it is common knowledge that some specific species in an ecological community present aggregate distributions, this does not necessarily imply that the entire community presents an aggregate distribution. Studying community-level distributional aggregation patterns requires different statistical methods. Herein, by utilizing a novel conspecific-encounter index derived from a multiple species Markov transition model that accounts for the non-independent sampling of consecutive individuals along line transects, we were able to show that tree assemblages in tropical forest ecosystems can present a strong signal of extensive distributional interspersion. This interesting result is not unexpected, given the fact that neighbouring tree individuals in highly diverse tropical forests are usually of different species, resulting in strong niche packing or interspersed patterns. In contrast, for the amphibian assemblages surveyed from southwestern China and central-south Vietnam, the conspecific-encounter index was found to be consistently high, implying that amphibian communities tend to be highly aggregate in space. Conclusively, using the conspecific-encounter index derived from the Markov non-independent sampling model, we provide a legible definition of community-level distributional aggregation as an interspersed or cluster-like distribution of different species. This definition is not idiosyncratic, as it is coincident with the definition of the contagion index used in landscape ecology. To this end, the model used in this paper establishes a framework explicitly linking community ecology and landscape ecology from a multi-object perspective.
学科主题	Environment/ecology
URL标识	查看原文
WOS关键词	TREE SPECIES ABUNDANCE ; SPATIAL AGGREGATION ; DENSITY-DEPENDENCE ; DIVERSITY ; FOREST ; POPULATIONS ; DISPERSAL ; NUMBER ; INDEX
WOS研究方向	Environmental Sciences & Ecology
语种	英语
出版者	WILEY
WOS记录号	WOS:000473662700009
内容类型	期刊论文
源URL	[http://210.75.237.14/handle/351003/31125]
专题	生物多样性与生态系统服务领域_中国科学院山地生态恢复与生物资源利用重点实验室
通讯作者	Shen, Tsung-Jen
作者单位	1.Univ Calif Los Angeles, Dept Ecol & Evolutionary Biol, Los Angeles, CA USA 2.Natl Chung Hsing Univ, Inst Stat & Dept Appl Math, Taichung, Taiwan; 3.Field Museum Nat Hist, Chicago, IL 60605 USA; 4.Morton Arboretum, Lisle, IL USA; 5.Smithsonian Trop Res Inst, Balboa, Panama; 6.Chinese Acad Sci, Chengdu Inst Biol, CAS Key Lab Mt Ecol Restorat & Bioresource Utiliz, Ecol Restorat & Biodivers Conservat Key Lab Sichu, Chengdu, Sichuan, Peoples R China;
推荐引用方式 GB/T 7714	Chen, Youhua,Shen, Tsung-Jen,Chung, Hoang Van,et al. Inferring multispecies distributional aggregation level from limited line transect-derived biodiversity data[J]. METHODS IN ECOLOGY AND EVOLUTION,2019,10(7):1015-1023.
APA	Chen, Youhua.,Shen, Tsung-Jen.,Chung, Hoang Van.,Shi, Shengchao.,Jiang, Jianping.,...&Hubbell, Stephen P..(2019).Inferring multispecies distributional aggregation level from limited line transect-derived biodiversity data.METHODS IN ECOLOGY AND EVOLUTION,10(7),1015-1023.
MLA	Chen, Youhua,et al."Inferring multispecies distributional aggregation level from limited line transect-derived biodiversity data".METHODS IN ECOLOGY AND EVOLUTION 10.7(2019):1015-1023.