A simple and effective approach to quantitatively characterize structural complexity

Sci Rep. 2021 Jan 14;11(1):1326. doi: 10.1038/s41598-020-79334-7.

Abstract

This study brings insight into interpreting forest structural diversity and explore the classification of individuals according to the distribution of the neighbours in natural forests. Natural forest communities with different latitudes and distribution patterns in China were used. Each tree and its nearest neighbours form a structural unit. Random structural units (or random trees) in natural forests were divided into different sub-types based on the uniform angle index (W). The proportions of different random structural units were analysed. (1) There are only two types of random structural units: type R1 looks similar to a dumbbell, and type R2 looks similar to a torch. These two random structural units coexist in natural forests simultaneously. (2) The proportion of type R1 is far less than that of R2, is only approximately 1/3 of all random structural units or random trees; R2 accounts for approximately 2/3. Furthermore, the proportion of basal area presents the same trend for both random structural units and random trees. R2 has approximately twice the basal area of R1. Random trees (structural units) occupy the largest part of natural forest communities in terms of quantity and basal area. Meanwhile, type R2 is the largest part of random trees (structural units). This study finds that the spatial formation mechanism of natural forest communities which is of great significance to the cultivation of planted forests.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China
  • Forests*
  • Models, Biological*
  • Trees / classification
  • Trees / growth & development*