Incorporating competition factors in a mixed-effect model with random effects of site quality for individual tree above-ground biomass growth of Pinus kesiya var. langbianensis

IF 1.5 4区农林科学 Q2 FORESTRY

New Zealand Journal of Forestry Science Pub Date : 2019-12-11 DOI:10.33494/nzjfs492019x27x

Mingchuan Nong, Yanbing Leng, Hui Xu, Chao Li, Guanglong Ou

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引用次数: 7

Abstract

Background: Accurate biomass estimation has critical effects on quantifying carbon stocks and sequestration rates, and above-ground biomass (AGB) growth models are a key component of tree biomass estimation. The study objective was to develop a growth model for AGB of an individual tree by combining competition factors and site quality using a mixed-effect model. Methods: The AGB of 128 sampling trees was investigated for Simao pine (Pinus kesiya var. langbianensis) at three typical sites near Pu’er City of Yunnan Province, China. Richards’ Equation was used for the basic growth model (BM) of the AGB, and a mixed-effect model with random effect of site quality (MEM) based on BM and a mixed-effect model with fixed effect of competition factors (MEMC) based on MEM were built using S-plus. Results: Both mixed-effect models are significantly better than the basic model in fitting and predicting the individual tree AGB growth for Simao pine, but the MEM is better than the MEMC. Moreover, the mixed-effect model with competition factors and site quality is the optimal estimation model due to its highest prediction precision (P=86.08%) as well as the lowest absolute average relative error (RMA=54.34%) and average relative error (EE =6.45%). Conclusion: A model including site quality and competition factors can be used to improve the tree AGB growth estimation for the individual tree AGB growth of Simao pine.

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基于竞争因子和立地质量随机效应的朗边松单株地上生物量生长混合效应模型

背景：准确的生物量估计对量化碳储量和固存率具有关键作用，而地上生物量（AGB）生长模型是树木生物量估计的关键组成部分。本研究的目的是通过使用混合效应模型将竞争因素和场地质量相结合，开发一个单株AGB的生长模型。方法：在云南省普洱市三个典型点对思茅松128株取样树的AGB进行调查。AGB的基本增长模型（BM）采用Richards方程，基于BM建立了具有场地质量随机效应的混合效应模型（MEM），基于MEM建立了具有竞争因素固定效应的混合效果模型（MEMC）。结果：两种混合效应模型在拟合和预测思茅松单株AGB生长方面均明显优于基本模型，但MEM模型优于MEMC模型。此外考虑竞争因素和场地质量的混合效应模型预测精度最高（P=86.08%），绝对平均相对误差最低（RMA=54.34%），平均相对误差最小（EE=6.45%），是最优的估计模型思茅松树AGB生长。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

New Zealand Journal of Forestry Science FORESTRY-

CiteScore

2.20

自引率

13.30%

发文量

审稿时长

39 weeks

期刊介绍： The New Zealand Journal of Forestry Science is an international journal covering the breadth of forestry science. Planted forests are a particular focus but manuscripts on a wide range of forestry topics will also be considered. The journal''s scope covers forestry species, which are those capable of reaching at least five metres in height at maturity in the place they are located, but not grown or managed primarily for fruit or nut production.