文献类型：期刊文献

中文题名：广东南岭苦竹地上生物量分配特征与回归模型

英文题名：The distribution characteristics and regression model of aboveground biomass of Pleioblastus amarus in Nanling Mountain,Gangdong

作者：林大雪[1] 赵厚本[2,4] 李兆佳[2,4] 黄春华[1,3] 许伟华[1]

第一作者：林大雪

机构：[1]广东省天井山林场(广东天井山国家森林公园管理处),广东乳源512726;[2]中国林业科学研究院热带林业研究所,广州510520;[3]广东南岭国家级自然保护区管理局,广东乳源512727;[4]南岭北江源森林生态系统国家定位观测研究站,广州510520

年份：2024

卷号：43

期号：10

起止页码：3205-3210

中文期刊名：生态学杂志

外文期刊名：Chinese Journal of Ecology

收录：CSTPCD;;Scopus;北大核心:【北大核心2023】；CSCD:【CSCD2023_2024】；

基金：广东省林业科技创新项目(2019KJCX026);中央级公益性科研院所基本科研业务费专项资金(CAFYBB2021SY002)资助。

语种：中文

中文关键词：苦竹;生物量;分配特征;回归模型

外文关键词：Pleioblastus amarus;biomass;distribution characteristics;regression model

分类号：S795

摘要：苦竹(Pleioblastus amarus)在广东南岭地区分布广、数量多,其碳汇潜力不可忽视,构建苦竹地上生物量模型可以为区域森林碳储量计算和碳汇功能评估提供重要基础数据。本研究以广东南岭地区苦竹林为对象,采用随机取样法选取45株样竹测定各器官生物量,以胸径(DBH)为主要因子构建苦竹各器官及地上生物量模型,并探讨竹高作为第二参数加入模型对模型精度的影响,比较地上生物量不同算法间差异。结果表明:苦竹竹秆生物量占比为76.1%±0.8%,竹枝为14.5%±0.5%,竹叶为9.4%±0.4%。竹秆生物量占比与DBH呈显著正相关(P<0.05),竹枝和竹叶生物量占比与DBH呈负相关。以DBH为自变量的一元模型及以DBH和竹高为自变量的二元模型对竹秆和地上生物量均有很高的预估精度(R^(2)均超过0.95),对竹枝和竹叶生物量预估也有较好精度(R^(2)分别为0.888和0.684)。增加竹高作为第二参数加入模型能小幅度提高模型预估精度但存在较严重的多重共线性问题。在估算地上生物量时,采用单一模型计算与采用先估算出各器官生物量再累加计算的差异很小。以上结果说明,苦竹倾向于采取先分配较多生物量给枝叶以快速进行光合作用之后再分配较多生物量给竹秆以稳定群落地位的生物量分配策略,在估算苦竹地上生物量时,采用DBH为单一变量的一元模型具有较好的估算精度,同时能减少工作量。
Pleioblastus amarus is widely distributed in the Nanling Mountain of Guangdong,and has great potential in carbon sink.Constructing aboveground biomass allometry model of P.amarus is important for the calculation of forest carbon stock and the assessment of carbon sink function.In this study,45 individuals of P.amarus were randomly sampled,and the biomass of each organ was determined to construct allometry models for different organs and total aboveground biomass(AGB).Diameter at breast height(DBH)was involved in the models as the main predictor and tree height(H)as an additional predictor.The accuracies of different models with or without H were compared.The results showed that 76.1%±0.8%of AGB was allocated to culm,14.5%±0.5%to twig and 9.4%±0.4%was allocated to leaf.Culm biomass was positively related to DBH(P<0.05),while the biomass of twigs and leaves were negatively related to DBH.The univariate model involving DBH and the bivariate model involving DBH and H had very high accuracies for predicting both culm biomass and AGB,with R^(2) exceeding 0.95,and the accuracies for predicting twig biomass and leaf biomass were also high,with R^(2) being 0.888 and 0.684,respectively.Adding H as an additional predictor into the model improved the accuracy of the model prediction to a small extent but resulted in the problem of multicollinearity.There were small differences between AGB estimates using a single model and the sum of different organs.The results suggest that P.amarus tends to allocate biomass to twigs and leaves in the early stage to ensure rapid photosynthesis and lately to culms for stabilizing its status in community.Univariate models with DBH as a single variable are recommended in the estimation of P.amarus AGB in order to reduce workload while having a high accuracy in calculation.