Predicting carbon storage of mixed broadleaf forests based on the finite mixture model incorporating stand factors, site quality, and aridity index

IF 3.8 1区 农林科学 Q1 FORESTRY
Yanlin Wang , Dongzhi Wang , Dongyan Zhang , Qiang Liu , Yongning Li
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引用次数: 0

Abstract

The diameter distribution function (DDF) is a crucial tool for accurately predicting stand carbon storage (CS). The current key issue, however, is how to construct a high-precision DDF based on stand factors, site quality, and aridity index to predict stand CS in multi-species mixed forests with complex structures. This study used data from 70 survey plots for mixed broadleaf Populus davidiana and Betula platyphylla forests in the Mulan Rangeland State Forest, Hebei Province, China, to construct the DDF based on maximum likelihood estimation and finite mixture model (FMM). Ordinary least squares (OLS), linear seemingly unrelated regression (LSUR), and back propagation neural network (BPNN) were used to investigate the influences of stand factors, site quality, and aridity index on the shape and scale parameters of DDF and predicted stand CS of mixed broadleaf forests. The results showed that FMM accurately described the stand-level diameter distribution of the mixed P. davidiana and B. platyphylla forests; whereas the Weibull function constructed by MLE was more accurate in describing species-level diameter distribution. The combined variable of quadratic mean diameter (Dq), stand basal area (BA), and site quality improved the accuracy of the shape parameter models of FMM; the combined variable of Dq, BA, and De Martonne aridity index improved the accuracy of the scale parameter models. Compared to OLS and LSUR, the BPNN had higher accuracy in the re-parameterization process of FMM. OLS, LSUR, and BPNN overestimated the CS of P. davidiana but underestimated the CS of B. platyphylla in the large diameter classes (DBH ≥18 ​cm). BPNN accurately estimated stand- and species-level CS, but it was more suitable for estimating stand-level CS compared to species-level CS, thereby providing a scientific basis for the optimization of stand structure and assessment of carbon sequestration capacity in mixed broadleaf forests.

基于包含林分因子、林地质量和干旱指数的有限混合物模型预测阔叶混交林的碳储量
直径分布函数(DDF)是准确预测林分碳储量(CS)的重要工具。然而,目前的关键问题是如何根据林分因子、立地质量和干旱指数构建高精度的直径分布函数,以预测结构复杂的多树种混交林的林分碳储量。本研究利用中国河北省木兰围场国有林场70个调查点的杨树和桦树混交阔叶林数据,基于最大似然估计和有限混合模型(FMM)构建了DDF。利用普通最小二乘法(OLS)、线性似非相关回归(LSUR)和反向传播神经网络(BPNN)研究了林分因子、立地质量和干旱指数对DDF形状和尺度参数的影响,并预测了阔叶混交林的林分CS。结果表明,FMM 能准确地描述 P. davidiana 和 B. platyphylla 混交林的林分级直径分布;而用 MLE 构建的 Weibull 函数能更准确地描述树种级直径分布。二次平均直径(Dq)、林分基部面积(BA)和林地质量的组合变量提高了 FMM 形状参数模型的准确性;Dq、BA 和 De Martonne 干旱度指数的组合变量提高了尺度参数模型的准确性。与 OLS 和 LSUR 相比,BPNN 在 FMM 重参数化过程中具有更高的精度。OLS、LSUR 和 BPNN 高估了 P. davidiana 的 CS,但低估了大直径等级(DBH ≥18 cm)中 B. platyphylla 的 CS。BPNN准确估计了林分和树种水平的CS,但与树种水平的CS相比,BPNN更适合估计林分水平的CS,从而为阔叶混交林的林分结构优化和固碳能力评估提供了科学依据。
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来源期刊
Forest Ecosystems
Forest Ecosystems Environmental Science-Nature and Landscape Conservation
CiteScore
7.10
自引率
4.90%
发文量
1115
审稿时长
22 days
期刊介绍: Forest Ecosystems is an open access, peer-reviewed journal publishing scientific communications from any discipline that can provide interesting contributions about the structure and dynamics of "natural" and "domesticated" forest ecosystems, and their services to people. The journal welcomes innovative science as well as application oriented work that will enhance understanding of woody plant communities. Very specific studies are welcome if they are part of a thematic series that provides some holistic perspective that is of general interest.
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