文献类型：期刊文献

中文题名：广东省针叶树种蓄积量和生物量生长模型研究

英文题名：Growth Models of Stand Volume and Biomass of Coniferous Species in Guangdong Province

作者：黄金金[1,2] 刘晓彤[1,2] 张逸如[1,2] 李海奎[1,2]

第一作者：黄金金

机构：[1]中国林业科学研究院资源信息研究所,北京100091;[2]国家林业和草原局森林经营与生长模拟重点实验室,北京100091

年份：2022

卷号：35

期号：3

起止页码：93-102

中文期刊名：林业科学研究

外文期刊名：Forest Research

收录：CSTPCD;;Scopus;北大核心:【北大核心2020】；CSCD:【CSCD2021_2022】；

基金：中央级公益性科研院所基本科研业务费专项资金(CAFYBB2018ZB006);国家自然科学基金项目(31770676、31872704)。

语种：中文

中文关键词：生长模型;蓄积量;生物量;竞争;分级;广东省

外文关键词：growth model;volume;biomass;competition;classification;Guangdong

分类号：S718.55

摘要：[目的]定量化表征森林蓄积量和生物量与年龄的关系,为预测森林蓄积量和生物量提供依据。[方法]基于广东省3个针叶树种5期连清数据,通过保留木林分平均胸径和林龄之间的关系,分别以生长潜力和生长速度分级、是否考虑竞争、分步和联合建模共8种组合,构建林分蓄积量和生物量生长模型,并评价模型拟合优度;以独立的4期连清数据为验证样本,评价模型的适用性。[结果](1)不同种模型系确定系数皆在0.980以上,平均预估误差在±1%以内,总体相对误差在±0.5%以内。综合模型拟合和预测效果,以生长速度分级、不考虑竞争的分步模型最优,竞争对模型的适用性影响不大。(2)最优模型蓄积量和生物量的估计误差最大分别为10.36%和10.22%,模型适用性较好,4期估计误差表现为中期高于首末两期。(3)马尾松生长潜力最大,杉木最小,对杉木的估计效果优于马尾松和湿地松。(4)立地质量等级越高,生长量的极值越大,达到最高峰所需年限也更短;同一立地质量下马尾松生长量最大,其次为湿地松,杉木最小。[结论]含参数分级和林分特征的蓄积量和生物量模型,可以反映立地质量对广东省针叶树种蓄积量和生物量预测的影响,为精确估测森林储量提供方法学支持,也为其他地区林分水平生长模型的构建提供借鉴。
[Objective]To quantitatively characterize the relationship between forest volume as well as biomass and stand age for predicting forest volume and biomass in the future.[Methods]Based on the forest inventory data with five times of Pinus massoniana,Pinus elliottii and Cunninghamia lanceolata in Guangdong,the stand volume and biomass growth models were established by constructing the relationship between the average DBH and stand age,which was developed with 8 forms,respectively,including growth potential and grow rate classifications,developing models with competition or not,and developing models separately or simultaneously.[Result](1)The determination coefficients of the eight model systems were more than 0.980.The mean prediction errors(MPE)were within±1%.The total relative errors were within±0.5%.Comprehensively considering the goodness of fit and prediction accuracy of each model,the separate model based on the classification of parameter related to growth rate without considering competition was the best.Moreover,model with competition did not significantly improve the model performance.(2)The gap of MPE values of the best stand volume model and worst model was 10.36%,and the gap of biomass model was 10.22%,which indicated that the models were suitable.Besides,the MPE values from the second and third period data were larger than the first and the last period data.(3)The growth potential of Pinus massoniana was the largest,by contrast that of Cunninghamia lanceolata was the smallest.The growth models of Cunninghamia lanceolata were better than those of Pinus massoniana and Pinus elliottii.(4)The higher the site quality was,the greater the maximum growth was,and the time of trees growing to the maximum growth in the higher site quality stands was shorter.In addition,in the same quality site,the growth of Pinus massoniana was the largest,followed by Pinus elliottii,Cunninghamia lanceolata.[Conclusion]The volume and biomass models including parameters with growth classification and stand characteristics depicts the effects of site quality on forest growth in Guangdong,which provides methodological support for accurately estimating carbon storage,and also provides a reference for the construction of stand growth models in other regions.