文献类型：期刊文献

英文题名：Methods of Forest Structure Research: a Review

作者：Hui, Gangying[1,2] Zhang, Ganggang[2] Zhao, Zhonghua[2] Yang, Aiming[2]

第一作者：Hui, Gangying;惠刚盈

通信作者：Hui, GY[1];Hui, GY[2]

机构：[1]Beijing Forestry Univ, State Forestry & Grassland Adm, Res Ctr Forest Management Engn, Beijing 100083, Peoples R China;[2]Chinese Acad Forestry, Res Inst Forestry, Beijing 100091, Peoples R China

年份：2019

卷号：5

期号：3

起止页码：142-154

外文期刊名：CURRENT FORESTRY REPORTS

收录：;Scopus(收录号：2-s2.0-85068317773);WOS:【SCI-EXPANDED(收录号:WOS:000482391700004)】；

基金：This study was funded by the "Plantation Structure Regulation and Stability Maintenance mechanism and its productivity effect" of the National Key Research and Development Program of China (2016YFD0600203) and the "Research and Demonstration of Regional Forest Ecosystem Multi-objective Balanced Recovery and Reestablishment" of the National Key Research and Development Program of China (2017YFC050400501).

语种：英文

外文关键词：Forest structure; Quantitative expression; Structural parameters; Structure-based forest management

摘要：Purpose of Review The forest structure generally refers to the configuration and distribution of different plant species and sizes. Investigation and analysis of forest structures help us to understand the history, current status, and future development of forest ecological systems. This paper aims at a systematic summary of the quantitative analysis methods of forest structure. Recent Findings The marked second-order characteristic method has obvious advantages in explaining the relationships among tree species and the dynamic relationship between tree size differentiation and scale. The quantitative analysis method of spatial structure based on the relationships of nearest neighbor trees, compared with traditional non-spatial indices or functions, does not only analyze four important aspects of the forest structure (spatial distribution pattern diversity, species diversity, size diversity, crowding degree diversity), but also demonstrates its strength in elaborating fine-scale spatial stand structure. This nearest-neighbor analytical method also bridges the gap between stand structure parameters and tree competition indices, especially through the multivariate distribution of structural parameters. This nearest-neighbor analytical method provides an in-depth, multi-faceted interpretation of forest structure at different levels. Structure-based forest management has been proposed based on this analytical method of spatial structure, and is a proven way to effectively improve forest quality.