# Developing mixed-effects height-diameter model using stand and environmental factors for mixed forests in northern China

## TL;DR

Researchers developed a model to predict tree height based on diameter and environmental factors in mixed forests of northern China, improving biomass and carbon estimates.

## Contribution

A novel mixed-effects model incorporating stand and environmental variables for tree height-diameter relationships in mixed forests.

## Key findings

- Quadratic mean diameter, BAL, and soil organic carbon increase height growth.
- Higher species diversity and precipitation reduce tree height.
- The model improves biomass and carbon storage estimates for adaptive forest management.

## Abstract

Understanding tree height (H)-diameter at breast height (D) allometric relationship is crucial for estimating biomass, carbon storage, and productivity. Environmental factors and species diversity strongly influence this relationship, yet remain understudied. Using data from 99 plots in Hulunbuir mixed forests, inner Mongolia, we developed an environment-sensitive nonlinear mixed-effects model for five tree species. The model incorporates variables representing stand-level attributes, soil properties, climate factors, and species diversity. Variations at the sample plot and species levels were accounted for by introducing random components into the H-D model. Quadratic mean diameter, total basal area greater than the target D (BAL), Simpson’s diversity index (SIM), mean annual precipitation (MAP), and soil organic carbon significantly affected the H-D relationship. Height growth increased with BAL and MAP but declined with higher SIM. Species traits and environmental factors jointly shaped H-D scaling. The proposed model supports adaptive forest management under changing environments.

•Mixed-effects H-DBH model developed for mixed forests with environmental variables•Genetic traits and environment jointly shape H-DBH scaling, below theoretical 2/3•Competition (BAL) and site quality (SOC) increase height; rain and diversity reduce it•Findings improve biomass and carbon estimates and guide sustainable forest management

Mixed-effects H-DBH model developed for mixed forests with environmental variables

Genetic traits and environment jointly shape H-DBH scaling, below theoretical 2/3

Competition (BAL) and site quality (SOC) increase height; rain and diversity reduce it

Findings improve biomass and carbon estimates and guide sustainable forest management

Environmental science; Environmental monitoring; Applied sciences