Dynamic Top Height Growth Models for Eight Native Tree Species in a Cool-Temperate Region in Northeast China

Abstract

In this study, we developed dynamic top height growth models for the eight important Chinese tree species Larix gmelinii var. principis-rupprechtii, Pinus tabuliformis Carr., Pinus sylvestris var. mongolica Litv., Picea asperata Mast., Quercus mongolica Fisch. ex Ledeb, Betula platyphylla Suk., Betula dahurica Pall. and Populus davidiana Dode based on age-height relationships. For this purpose, commonly growth data from long-term observations of permanent experimental plots are used, which ideally cover all development stages from stand establishment to final harvest. As such data were not available in the research area of Hebei Province in Northeast China, we used stem analysis data as well as tree height and annual shoot length measurements. The dataset consisted of 72 stands, 233 dominant trees and 10,195 observations of stem discs and annual shoot length measurements. Five dynamic base-age invariant top height growth models were derived from four base models with the generalized algebraic difference approach and fitted to our age-height data using nested regression techniques. According to biological plausibility and model accuracy the Chapman–Richards model showed the best performance for Picea asperata. This selected model accounted for 99% of the total variance in age-height relationship with average absolute bias of 0.2322 m, root mean square error of 0.3337 m and Radj2 of 0.9979, respectively. The distribution of the residuals was scattered around 0 and without visible trends, indicating that the fitness of the models was good. All developed models are able to generate top height growth curves representing the analyzed height growth data and can be utilized for predicting height growth on the base of current height and age of dominant trees. Additionally, they are the base for calculating the development of other relevant stand attributes such as basal area and volume growth. The determination of potential site productivity by the use of top height growth curves is a practical and convenient method for a simplified presentation of complex growth processes in stands and helps to create growth models, which facilitate implementing sustainable forest management practices in Mulan Forest.