Optimizing Forest Spatial Structure with Neighborhood-Based Indices: Four Case Studies from Northeast China

Lingbo Dong,Hongyang Wei,Zhaogang Liu

doi:10.3390/f11040413

Abstract

The fine-scale spatial patterns of trees and their interactions are of paramount importance for controlling the structure and function of forest ecosystems; however, few management techniques can be employed to adjust the structural characteristics of uneven-aged mixed forests. This research provides an accurate, efficient, and impersonal comprehensive thinning index (P-index) for selecting candidate harvesting trees; the index was proposed by weighting the commonly used quantitative indices with respect to stand fine-scale structures, competition status, tree vigor, and tree stability. The applications of the proposed P-index in evaluating and simulating the process of thinning operations were examined using four 1-ha mapped plots with different forest types, namely, natural secondary forest, natural pine-broadleaved mixed forest, natural larch-birch mixed forest, and natural oak forest, which were widely distributed across the Heilongjiang Province in Northeast China. The results indicated that the proposed P-index could effectively affect the structural differentiations between different forest types and alternative thinning intensities. The marginal benefits of alternative thinning intensities on the integrated forest structure indicated that removing 10% of the trees from the plots might be the optimal thinning intensity from the perspective of optimizing stand structure, in which the P-index values could be increased by approximately 5%–11% for the four tested plots. The main conclusion from this paper was that the proposed P-index could be used as a quantitative tool to manage uneven-aged mixed forests.

Highlights

Forest structure, including spatial and nonspatial characteristics, is one attribute contributing to the sustainable management of mixed uneven-aged forests
The nonspatial forest structure usually describes the average states of forest attributes, such as the mean diameter at breast height (DBH), mean tree height (HT), and stand density, which have been widely used in forest resource surveys, management, and monitoring [1]
Spatial forest structures exist at a variety of spatial scales and are of paramount importance for determining habitat and species diversity, which can be roughly divided into four levels: alpha, beta, gamma, and delta [2,3]

Summary

Introduction

Forest structure, including spatial and nonspatial characteristics, is one attribute contributing to the sustainable management of mixed uneven-aged forests. Spatial forest structures exist at a variety of spatial scales and are of paramount importance for determining habitat and species diversity, which can be roughly divided into four levels: alpha, beta, gamma, and delta [2,3]. In forest ecosystems, the gamma and delta levels usually operate on landscape scales or at large forest areas, reflecting the fragmentation degrees of habitat and landscape; in contrast, the beta level refers to the variation between forest stands, reflecting the substitutability degree of different species under habitat gradients (e.g., elevation and succession stage), and the alpha level usually operates within forest stands, mainly reflecting the species richness, relative abundance, and uniformity. There is an increasing demand for information on the alpha scale, regarding the fine-scale spatial distribution of trees and their attributes [3,6,7], as societal values have changed from focusing on traditional timber to the diversified benefits and multiple functions of forest ecosystems in recent decades

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