文献类型：期刊文献

英文题名：A classification of woody communities based on biological dissimilarity

作者：Hao, Minhui[1] Gadow, Klaus[2,3] Alavi, Seyed Jalil[4] Alvarez-Gonzalez, Juan Gabriel[5] Rommel Baluarte-Vasquez, Juan[6] Corral-Rivas, Javier[7] Hui, Gangying[8] Korol, Mykola[9] Kumar, Rajesh[10] Liang, Jingjing[11] Meyer, Peter[12] Remadevi, Othumbam Kat[13] Kakkar, Ritu[13] Liu, Wenzhen[14] Zhao, Xiuhai[1] Zhang, Chunyu[1]

第一作者：Hao, Minhui

通信作者：Zhang, CY[1]

机构：[1]Beijing Forestry Univ, Res Ctr Forest Management Engn, State Forestry & Grassland Adm, Beijing 100083, Peoples R China;[2]Georg August Univ, Fac Forestry & Forest Ecol, Gottingen, Germany;[3]Stellenbosch Univ, Fac AgriSci, Dept Forestry & Wood Sci, Matieland, South Africa;[4]Tarbiat Modares Univ, Fac Nat Resources, Dept Forestry, Nour, Iran;[5]Univ Santiago de Compostela, Lugo Campus, Lugo, Spain;[6]SERFOR, Natl Forest Serv, Lima, Peru;[7]Univ Juarez Estado Durango, Inst Silviculture & Wood Ind, Durango, Mexico;[8]Chinese Acad Forestry, Res Inst Forestry, Beijing, Peoples R China;[9]Ukrainian Natl Forestry Univ, Fac Forestry, Lvov, Ukraine;[10]Forest Survey India, Dehra Dun, Uttarakhand, India;[11]Purdue Univ, Dept Forestry & Nat Resources, W Lafayette, IN 47907 USA;[12]Northwest German Forest Res Inst, Dept Forest Nat Conservat, Hannover Munden, Germany;[13]Environm Management & Policy Res Inst EMPRI, Bangalore, Karnataka, India;[14]Xiaolongshan Forest Expt Bur Gansu Prov, Tianshui, Peoples R China

年份：2021

卷号：24

期号：1

外文期刊名：APPLIED VEGETATION SCIENCE

收录：;Scopus(收录号：2-s2.0-85103251469);WOS:【SSCI(收录号:WOS:000636291500012)，SCI-EXPANDED(收录号:WOS:000636291500012)】；

基金：This research was supported by the Program of National Natural Science Foundation of China (31971650), the Key Project of National Key Research and Development Plan (2017YFC0504104), Beijing Forestry University Outstanding Young Talent Cultivation Project (2019JQ03001), and the Short‐term International Student Program for Postgraduates of Forestry First‐Class Discipline (2019XKJS0501)

语种：英文

外文关键词：biological heterogeneity; cluster analyses; community dissimilarity; Discriminating Avalanche; forest vegetation; taxonomic distance; vegetation classification

摘要：Aims Traditional quantitative approaches to forest classification are based on differences in species abundance or incidence among communities. In these approaches, all species are regarded as biologically equidistant regardless of the biological heterogeneity. The objective of the study is to evaluate the potential of the "Discriminating Avalanche" approach, which integrates species abundance and biological heterogeneity, as a new basis for forest classification. Location China, India, Iran, Ukraine, Germany, Italy, Mexico, Peru, and South Africa. Method We illustrate our approach using a set of 35 large tree-mapped forest plots from various regions of the world. Our dissimilarity matrices, which integrate species abundance with biological heterogeneity, are compared with the standard Bray-Curtis and Whittaker dissimilarity indices, and provide the quantitative basis for a hierarchical cluster analysis. Results Four distinct groups of forests were identified using the proposed forest dissimilarity matrix. Afro-montane forests from South Africa constitute a first group. A second group includes temperate deciduous broad-leaved forests dominated by oak (Quercus) and beech (Fagus) from Europe and China. Conifer-dominated forests constitute a third group. The remaining forests constitute the fourth group. Conclusion Biological heterogeneity provides a practical basis for vegetation classification. The results of this study, based on a variety of temperate and tropical forests, suggest that a measure of biological dissimilarity based on evolutionary and morphological differences among species is more effective than the traditional species abundance-based approaches to classify an arbitrary set of plant communities. This approach promises greater refinement and consistency in ecological classification. In particular, it has advantage in classifying forests along large geographic scales in situations of high beta diversity and species turnover.