Volume 36 Issue 1
Jan.  2019
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XU Qihu, LIN Liping, XUE Chunquan, LUO Yong, LEI Yuancai. Component specific carbon content and storage of Cinnamomum camphora in Guangdong Province[J]. Journal of Zhejiang A&F University, 2019, 36(1): 70-79. doi: 10.11833/j.issn.2095-0756.2019.01.010
Citation: XU Qihu, LIN Liping, XUE Chunquan, LUO Yong, LEI Yuancai. Component specific carbon content and storage of Cinnamomum camphora in Guangdong Province[J]. Journal of Zhejiang A&F University, 2019, 36(1): 70-79. doi: 10.11833/j.issn.2095-0756.2019.01.010

Component specific carbon content and storage of Cinnamomum camphora in Guangdong Province

doi: 10.11833/j.issn.2095-0756.2019.01.010
  • Received Date: 2018-01-10
  • Rev Recd Date: 2018-03-21
  • Publish Date: 2019-02-20
  • To quickly and accurately measure the car on sink in forest carbon sequestration projects and to monitor carbon storage changes in forest vegetation of Guangdong Province, Cinnamomum camphora trees were selected as the object to establish a carbon storage model. Based on the 8th continuous forest inventory data for C. camphora distribution in Guangdong Province in 2012, all 90 sample trees were classified in 10 diameter classes according to 2, 4, 6, 8, 12, 16, 20, 26, 32, and 38 cm. The weighted mean and total carbon storage were calculated for individual trees of C. camphora including components of stem wood, bark, leaves, branches, and roots among different diameter levels by using the analysis of variance (ANOVA) method. Results showed that:(1) The average carbon rate of C. camphora in Guangdong was 0.509 6. There were no significant differences among stems, leaves, branches, and roots (P>0.05) for the average carbon content in DBH levels, but the carbon content of bark was significantly lower than other components (P < 0.05). (2) Carbon content increased with age in period of mature and near-mature forests, but declined in period of over-mature forests. (3) The carbon content of the artificial forest was higher than the natural forest and increased with increasing latitude, but decreased with the increasing of altitude. (4) The proportion of carbon storage in each component was stem > branch > root > bark > leaf. (5) With an increase in DBH, the ratio of stem carbon storage increased first and then decreased, the proportion of bark carbon reserves was stable at an early age but decreased in later stages, the proportion of leaves and roots changed little, and the carbon storage of branches was stable first and increased in a later period at a significant level of 0.05. (6) The optimal carbon storage(Ct) model of C. camphora and R2 for age (A) was Ct=0.019 4A2.652 0, R2=0.602 9; for DBH was Ct=0.011 8D2.937 6, R2=0.943 2; and for D2H was Ct=0.001 6(D2H)1.268 6, R2=0.910 5. Through cross validation, the model fitting effect was significant (P < 0.01). The fitting carbon storage model of C. camphora with D and D2H was better than the age vatiable. In the model application, the model with D and D2H should be selected to estimate the carbon storage. When the diameter (D) and D2H were not easy to be measured but the age was easy to know, the age could be used to estimate the carbon storage.
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    [15] SUN Chong, LIU Qijing.  Carbon storage changes for major forest types in Beijing . Journal of Zhejiang A&F University, 2013, 30(1): 69-75. doi: 10.11833/j.issn.2095-0756.2013.01.010
    [16] CUI Rui-rui, DU Hua-qiang, ZHOU Guo-mo, XU Xiao-jun, DONG De-jin, Lü Yu-long.  Remote sensing-based dynamic monitoring of moso bamboo forest and its carbon stock change in Anji County . Journal of Zhejiang A&F University, 2011, 28(3): 422-431. doi: 10.11833/j.issn.2095-0756.2011.03.012
    [17] LIU Hai-xing, ZHANG De-shun, SHANG Kan-kan, CHEN Xiang-bo, DA Liang-jun.  Chlorophyll differences in chlorotic Cinnamomum camphora leaves . Journal of Zhejiang A&F University, 2009, 26(4): 479-484.
    [18] CAI Li-sha, CHEN Xian-gang, GUO Yin, YIN Yao.  Carbon sequestration potential with the Grain for Green Program in Guizhou Province . Journal of Zhejiang A&F University, 2009, 26(5): 722-728.
    [19] LI Zheng-cai, FU Mao-yi, XIE Jin-zhong, ZHOU Ben-zhi, XIAO Ti-quan, WU Ming.  Carbon sequestration of 5 ecological reestablishment vegetation types in Muchuan County of Sichuan . Journal of Zhejiang A&F University, 2004, 21(4): 382-387.
    [20] Fan Houbao, Zang Runguo.  Effects of Simulated Acid Rain on Seed Germination and Seeding Growth of Cinnamomum camphora. . Journal of Zhejiang A&F University, 1996, 13(4): 412-417.
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Component specific carbon content and storage of Cinnamomum camphora in Guangdong Province

doi: 10.11833/j.issn.2095-0756.2019.01.010

Abstract: To quickly and accurately measure the car on sink in forest carbon sequestration projects and to monitor carbon storage changes in forest vegetation of Guangdong Province, Cinnamomum camphora trees were selected as the object to establish a carbon storage model. Based on the 8th continuous forest inventory data for C. camphora distribution in Guangdong Province in 2012, all 90 sample trees were classified in 10 diameter classes according to 2, 4, 6, 8, 12, 16, 20, 26, 32, and 38 cm. The weighted mean and total carbon storage were calculated for individual trees of C. camphora including components of stem wood, bark, leaves, branches, and roots among different diameter levels by using the analysis of variance (ANOVA) method. Results showed that:(1) The average carbon rate of C. camphora in Guangdong was 0.509 6. There were no significant differences among stems, leaves, branches, and roots (P>0.05) for the average carbon content in DBH levels, but the carbon content of bark was significantly lower than other components (P < 0.05). (2) Carbon content increased with age in period of mature and near-mature forests, but declined in period of over-mature forests. (3) The carbon content of the artificial forest was higher than the natural forest and increased with increasing latitude, but decreased with the increasing of altitude. (4) The proportion of carbon storage in each component was stem > branch > root > bark > leaf. (5) With an increase in DBH, the ratio of stem carbon storage increased first and then decreased, the proportion of bark carbon reserves was stable at an early age but decreased in later stages, the proportion of leaves and roots changed little, and the carbon storage of branches was stable first and increased in a later period at a significant level of 0.05. (6) The optimal carbon storage(Ct) model of C. camphora and R2 for age (A) was Ct=0.019 4A2.652 0, R2=0.602 9; for DBH was Ct=0.011 8D2.937 6, R2=0.943 2; and for D2H was Ct=0.001 6(D2H)1.268 6, R2=0.910 5. Through cross validation, the model fitting effect was significant (P < 0.01). The fitting carbon storage model of C. camphora with D and D2H was better than the age vatiable. In the model application, the model with D and D2H should be selected to estimate the carbon storage. When the diameter (D) and D2H were not easy to be measured but the age was easy to know, the age could be used to estimate the carbon storage.

XU Qihu, LIN Liping, XUE Chunquan, LUO Yong, LEI Yuancai. Component specific carbon content and storage of Cinnamomum camphora in Guangdong Province[J]. Journal of Zhejiang A&F University, 2019, 36(1): 70-79. doi: 10.11833/j.issn.2095-0756.2019.01.010
Citation: XU Qihu, LIN Liping, XUE Chunquan, LUO Yong, LEI Yuancai. Component specific carbon content and storage of Cinnamomum camphora in Guangdong Province[J]. Journal of Zhejiang A&F University, 2019, 36(1): 70-79. doi: 10.11833/j.issn.2095-0756.2019.01.010
  • 森林生态系统是地球上仅次于海洋生态系统的第二大碳库,约占全球陆地总碳库的46%[1],森林植被碳库占全球植被碳库的77.1%[2],森林土壤碳库储存了全球土壤碳储量的40%左右[3]。森林生态系统不仅在维护区域生态环境上起重要作用,而且在维持全球碳平衡中有巨大贡献[4]。森林具有“碳源”和“碳汇”的双重功能,森林在增加碳汇、减缓大气“温室气体”浓度增加中发挥的作用越来越突出[5-7],准确估算森林生态系统的碳储量是全球气候变化研究的关键[8-9]。近年来,中国有关不同森林类型的碳储量、碳密度等研究取得了重大进展[10-13],但不同学者采用的估算方法不同、数据的时间及空间不同以及森林生态系统在时间和空间上的复杂性,导致森林生态系统碳储量的估算在学术界仍存在很大的不确定性[14-17]。目前,无论是在国家或是区域尺度上,还是在森林群落或生态系统的尺度上,对森林碳储量的估算普遍通过直接或间接测定森林植被的生物量再乘以含碳率推算而来。因此,森林群落中各组成树种的含碳率是研究森林碳储量的关键参数之一,对含碳率的测定是估算森林生态系统碳储量的基础[18]。在过去几十年中,有关森林碳储量的研究大多采用固定的数值0.500 0或0.450 0作为森林的平均含碳率[6, 19-23]。然而,许多研究表明:不同的森林类型,其植被及同一种植物不同器官的含碳率也明显不同[24-25],如果在估算森林植被碳储量时不考虑树种间及各器官含碳率的差异,将会引起约10%的偏差[26-27]。因此,为减少森林植被碳储量估算的不确定性,基于调查样本的试验材料准确测定、估计不同区域或同一区域不同环境和不同年龄的树种以及不同器官的含碳率是非常必要的。樟树Cinnamomum camphora是广东典型地带性树种,在广东省植被中大量分布,主要集中分布于粤北的韶关、清远、梅州、河源、惠州、肇庆等地区,粤东及粤西沿海分布较少,雷州半岛分布极少。樟树是优良的珍贵用材树种,是新一轮绿化广东大行动开展碳汇造林工程的主要树种之一。2012年以来,广东营造了大量的樟树人工林,但目前针对樟树含碳率及单株碳储量的研究报道较少,研究探索不同龄组、不同起源、不同纬度、不同海拔等条件下樟树含碳率及碳储量变化规律更是少见。本研究以伐倒的90株樟树单木为研究对象,对其树干、树皮、树叶、树枝、树根各器官含碳率以及碳储量进行测定和分析,建立适合广东的樟树碳储量模型,旨在为广东省森林植被碳储量动态的估算提供基础数据,为精准计量森林碳汇工程的碳汇量提供基础参数。

  • 研究区位于广东全省境内,地理坐标为20°09′~25°31′N,109°45′~117°20′E,面积17.97万km2,北回归线横贯而过,东南濒临南海,西北有南岭,地势北高南低,水热条件优越。广东从北向南形成3个不同的纬度带,分别为中亚热带、南亚热带和热带北缘。广东气候特征为热量丰富,夏长冬暖,降雨量充沛,干湿季分明,夏秋多台风,热带气旋频繁。年平均日照时数为1 745.8 h,年平均气温为22.3 ℃,最冷1月平均气温为13.3 ℃,最热7月平均气温为28.5 ℃,年太阳总辐射量为4 200~5 400 MJ·m-2,年平均降水量为1 300~2 500 mm。广东省地带性森林植被的主要类型为中亚热带常绿阔叶林、南亚热带常绿阔叶林和少量热带季雨林。地带性土壤类型有赤红壤、红壤等。

  • 试验材料取样方法依据LY/T 2259-2014《立木生物量建模样本采集技术规程》,以2012年广东省森林资源连续清查样地中樟树分布情况为基础,采用单株伐倒法按10个径阶区间选取90株样木进行伐倒木测定,10个径阶区间的胸径分别为2径阶(1.5~2.5 cm),4径阶(3.5~4.5 cm),6径阶(5.5~6.5 cm),8径阶(7.5~8.5 cm),12径阶(11~13 cm),16径阶(15~17 cm),20径阶(19~21 cm),26径阶(25~27 cm),32径阶(31~33 cm),38径阶(38 cm及以上),其中40株进行树根采集。测定因子包括所处的立地条件(海拔、坡位、坡向、坡度)以及树种的起源、胸径、树高、枝下高、冠幅和坐标等。样木年龄的调查主要包括2个方面:40株进行树干解析的样木,以树干年轮分析0号盘(0.3 m)处的年轮数为该样木的年龄;未进行树干解析的50株样木,观测伐桩(0.1 m)上的年轮数,并结合调查种植年限推测样木年龄。各样木调查情况见表 1,各采集样木径阶分布情况如表 2所示。

    变量 年龄/a 胸径/cm 树高/m
    平均值 16.4 14.5 9.2
    最小值 2.0 1.9 1.7
    最大值 60.0 41.0 17.6
    标准差 11.6 10.5 3.9

    Table 1.  90 sampling camphor trees data statistics

    统计类别 合计/株 樟树数量/株
    2径阶 4径阶 6径阶 8径阶 12径阶 16径阶 20径阶 26径阶 32径阶 38径阶
    伐倒木 90 6 6 12 16 14 10 8 6 6 6
    树干解析木 40 4 10 8 6 6 6
    树根采集 40 3 3 5 7 6 4 4 3 3 2

    Table 2.  Sampling camphor trees in different diameter classes data statistics

  • 采用重铬酸钾-硫酸氧化法(湿烧法)对样品含碳率进行测定。对已经进行烘干后的木材上部、木材中部、木材下部、树皮中部、树枝中部、树叶、根茎、粗根、细根等9类样品,选取有代表性的样品约1/5(不少于20.0 g),粗粉碎后按四分法取约1/4样品研磨并均匀混合,称取约30.0 mg试样(精确到0.01 mg),进行有机碳含量测定。重复3次,取其平均值作为样品的含碳率;若平均相对误差超出了±2%,则加做1次重复,取相差最小的3次测定结果的平均值作为样品的含碳率。

  • 由于不同器官的含碳率存在着一定的差异,单木各器官的生物量在总生物量中所占的权重又不尽相同,因此,以各器官含碳率的算术平均值作为该树种的平均含碳率并不能真实地反映实际情况。只有根据各器官的生物量权重计算的平均含碳率,才能真实地反映其实际平均水平及每一器官在平均值中的贡献[28]。因此,本研究在估算全树含碳率时,按照下列公式计算:

    式(1)中:P为全树加权平均含碳率;Pi为某树种i器官的含碳率,Wi为某树种i器官的生物量(i =1,2,3,4,5,分别代表树干、树皮、树叶、树枝、树根)。植物含碳率是植物碳储量的一种度量,反映绿色植物在光合作用中固定贮存碳的能力,李江等[29]研究表明:不同树木年龄、胸径和器官等因素都对树木含碳率有影响,在分析某一因素是否对含碳率有影响之前,首先应该考虑各个因素之间是否有交互作用。鉴于此,本研究主要针对年龄、起源、纬度带、海拔等因子对樟树不同器官含碳率的影响进行分析。

  • 碳储量计算公式如下:

    式(2)中:Ct为全树碳储量;Pi为某树种器官的含碳率,Wi为某树种i器官的生物量(i=1,2,3,4,5,分别代表树干、树皮、树叶、树枝、树根)。

  • 表 3可以看出:广东樟树全树加权平均含碳率为0.509 6;不同器官的含碳率不同,为0.483 8~0.516 6;树干的含碳率最高,其次是树叶、树枝、树根,最低的是树皮。树皮与其他各器官之间差异显著(P<0.05),但树干、树叶、树枝、树根之间差异不显著(P>0.05)。全树含碳率算术平均值与加权平均值相比较,2种方法得出的全树含碳率差异很小,差异值仅为-0.004 3。

    统计项目 含碳率 变异系数/%
    树干 树皮 树叶 树枝 树根 全树
    加权平均 0.516 6 0.483 8 0.510 8 0.510 7 0.502 3 0.509 6 5.98
    含碳率 (±0.033 8) (±0.042 7) (±0.046 1) (±0.039 1) (±0.049 6) (±0.030 5)
    算术平均 0.516 8 0.483 8 0.510 8 0.510 7 0.504 2 0.505 3 6.26
    含碳率 (±0.033 2) (±0.042 7) (±0.046 1) (±0.039 1) (±0.042 3) (±0.031 9)
    差异值 0.000 2 0.000 0 0.000 0 0.000 0 0.001 9 -0.004 3
    说明:括号中数值为标准差

    Table 3.  Carbon content in different organs of Cinnamomum camphora

    表 4可知:全树含碳率广东最高,其次为湖南,最低为贵州,广东和湖南樟树含碳率比较接近,贵州樟树含碳率与其他两省存在明显差异。从各器官的含碳率来看,各省区树皮含碳率比其他器官均低,除树干、树叶含碳率湖南比广东高以外,树皮、树枝、树根均比湖南高,全树各个器官含碳率广东、湖南均高于贵州。

    省区 含碳率 参考文献
    树干 树皮 树叶 树枝 树根 全树
    广东 0.516 6 0.483 8 0.510 8 0.510 7 0.502 3 0.509 6 本研究
    湖南 0.539 0 0.442 0 0.535 0 0.501 0 0.496 0 0.502 0 [24]
    贵州 0.469 8 0.442 5 0.456 8 0.440 5 0.453 5 [30]

    Table 4.  Carbon content in organs of Cinnamomum camphora from different provinces

  • ① 树干(去皮)平均含碳率空间分布。从树干上部、中部、下部圆盘含碳率测定结果(表 5)可知:树干含碳率为0.304 6~0.656 7,变异系数为7%~8%,含碳率各层次变动较小,平均值差异显著性分析表明,差异未达到显著水平(P>0.05)。②树根加权平均含碳率空间分布。从树根的根茎、粗根、细根各部位含碳率测定结果(表 6)可知:树根含碳率为0.294 0~0.639 5,变动范围较大,变异系数为10%~12%,含碳率各层次变动较小,平均值差异显著性分析表明,差异未达到显著水平(P>0.05)。粗根含碳率大于细根,但根茎含碳率和细根比较接近。

    统计项目 含碳率
    上层干 中层干 下层干
    加权平均含碳率 0.516 6 0.515 6 0.518 3
    标准差 0.037 4 0.038 1 0.038 1
    变化范围 0.400 6~0.656 7 0.304 6~0.620 6 0.319 1~0.632 3
    变异系数/% 7.23 7.39 7.35

    Table 5.  Carbon content of stem in different layers of Cinnamomum camphora

    统计项目 含碳率
    根茎 粗根 细根
    加权平均含碳率 0.496 3 0.511 2 0.504 9
    标准差 0.058 7 0.054 0 0.057 1
    变化范围 0.307 5~0.583 6 0.323 4~0.639 5 0.294 0~0.603 6
    变异系数/% 11.83 10.55 11.30

    Table 6.  Carbon content of roots in different layers of Cinnamomum camphora

  • 以实际测定的样木年龄为基础,按年龄的大小以用材林进行龄组分配,樟树90株样木按年龄分为5个龄组:幼龄林(10年生以下)、中龄林(11~20年生)、近熟林(21~25年生)、成熟林(26~35年生)、过熟林(36年生以上)。从表 7可知:各龄组(年龄)各器官的含碳率变化范围都不大,变异系数都在4%以下,全树不同龄组的含碳率之间差异不显著(P>0.05)。全树各龄组的含碳率从大到小依次为近熟林、成熟林、过熟林、中龄林、幼龄林,含碳率随年龄增加有增加趋势,到近熟林达到最高,到过熟林再下降。

    龄组 样木数/株 含碳率 变异系数/%
    树干 树皮 树叶 树枝 树根 全树
    幼龄林 35 0.519 1 0.482 7 0.510 4 0.503 5 0.499 1 0.508 1 2.45
    中龄林 24 0.511 1 0.483 5 0.515 4 0.522 1 0.503 7 0.508 6 2.62
    近熟林 11 0.525 9 0.476 9 0.504 2 0.521 4 0.525 5 0.520 2 3.72
    成熟林 11 0.522 2 0.492 5 0.509 0 0.497 9 0.498 3 0.510 4 2.15
    过熟林 9 0.503 4 0.486 4 0.510 2 0.510 4 0.501 8 0.509 6 1.83
    变异系数/% 1.75 1.18 0.79 2.09 2.23 0.98

    Table 7.  Carbon content of organs in different age groups of Cinnamomum camphora

  • 不同起源的含碳率分析表明(表 8):樟树人工林和天然林的含碳率差距不大,人工林与天然林的差值仅为0.018 0,全树人工林含碳率要高于天然林。从各器官来看,不同起源各器官的含碳率变化范围都不大,变异系数都在3%以下,人工林的树干、树皮、树根含碳率比天然林要高,但树叶、树枝比天然林的要低。

    起源 样木数/株 含碳率 变异系数/%
    树干 树皮 树叶 树枝 树根 全树
    人工 35 0.526 9 0.489 4 0.510 2 0.505 1 0.513 9 0.521 3 2.58
    (±0.032 4) (±0.044 4) (±0.043 1) (±0.037 9) (±0.022 8) (±0.024 8)
    天然 55 0.511 2 0.480 8 0.511 1 0.513 6 0.497 3 0.503 3 2.47
    (±0.033 6) (±0.041 9) (±0.047 9) (±0.039 7) (±0.057 1) (±0.036 5)
    差异值 -0.015 7 -0.008 6 0.000 9 0.008 5 -0.016 6 -0.018 0
    说明:括号中数值为标准差

    Table 8.  Carbon content of organs in different origins of Cinnamomum camphora

  • 表 9可以看出:不同纬度带的樟树含碳率差距较小,差异不显著(P>0.05),全树含碳率中亚热带最高,其次是南亚热带,最后是热带。各器官不同纬度带的含碳率变化差异均不大,变异系数均在5%以内。

    纬度带 样木数/株 含碳率 变异系数/%
    树干 树皮 树叶 树枝 树根 全树
    中亚热带 35 0.521 5 0.491 8 0.517 2 0.506 8 0.503 6 0.512 3 2.09
    南亚热带 52 0.516 0 0.487 7 0.530 5 0.506 1 0.502 2 0.508 6 2.81
    热带 3 0.505 1 0.498 4 0.513 1 0.471 0 0.485 6 0.494 5 3.01
    变异系数/% 1.62 1.10 1.75 4.15 2.02 1.86

    Table 9.  Carbon content of organs in different latitudes of Cinnamomum camphora

  • 以样木所处地点的海拔高度为基础,并结合采样点地形,按平原、丘陵、低山进行分组,分为平原(海拔0~100 m),丘陵(海拔101~500 m),低山(海拔501~1 000 m)。从表 10可以看出:不同海拔高度樟树含碳率差距较小,差异不显著(P>0.05),全树含碳率低山最高,其次丘陵,最后是平原。各器官不同海拔高度的含碳率变化差异均不大,变异系数均在3%以内。

    海拔 样木数/株 含碳率 变异系数/%
    树干 树皮 树叶 树枝 树根 全树
    平原 16 0.513 3 0.472 9 0.525 9 0.500 3 0.501 1 0.506 4 3.51
    丘陵 58 0.518 8 0.484 2 0.508 1 0.513 6 0.499 1 0.509 6 2.44
    低山 16 0.511 6 0.493 0 0.505 6 0.510 6 0.521 3 0.515 4 1.90
    变异系数/% 0.73 2.09 2.16 1.37 2.43 0.69

    Table 10.  Carbon content of organs in different altitudes of Cinnamomum camphora

  • 根据40株有树根采集的单株碳储量,计算出各径阶及平均单株碳储量。如表 11所示:对各器官平均碳储量分布进行分析,碳储量最高的是树干,占全树的33.78%,其次是树枝和树根,最后是树皮和树叶。树干、树枝、树根所占比例达到90.29%,表明碳储量主要集中在树干、树枝和树根上。从全树及各器官的碳储量来看,基本上是随着胸径增长,全树及各器官碳储量均有不同程度的增加,但增加幅度并不一样,在胸径2~8 cm时碳储量增加幅度较小,从胸径12 cm开始,碳储量增加幅度变大,表明碳储量增加主要在生长的中后期。各器官占全树碳储量的比例变化趋势也不相同,随着胸径增加,树干碳储量的比例变化呈先增加后下降趋势,到胸径20 cm时达到最大;树皮碳储量比例在胸径20 cm以前较稳定,20 cm以后下降;树叶、树根碳储量比例随胸径增加变化不大;树枝碳储量比例变化趋势是初期稳定、后期增加,在32 cm及以前,树枝碳储量比例变化较小,32 cm以后大幅增加。

    径阶 树干 树皮 树叶 树枝 树根 全树碳储量/(kg·株-1
    碳储量/(kg·株-1 比例/% 碳储量/(kg·株-1 比例/% 碳储量/(kg·株-1 比例/% 碳储量/(kg·株-1 比例/% 碳储量/(kg·株-1 比例/%
    平均 41.92 33.78 7.41 5.97 4.64 3.74 36.57 29.47 33.56 27.04 124.10
    2径阶 0.18 36.73 0.04 8.16 0.03 6.12 0.07 14.29 0.17 34.69 0.49
    4径阶 1.02 46.15 0.24 10.86 0.11 4.98 0.28 12.67 0.56 25.34 2.21
    6径阶 2.31 43.50 0.48 9.04 0.36 6.78 1.04 19.59 1.12 21.09 5.31
    8径阶 5.12 44.91 0.90 7.89 0.86 7.54 1.78 15.61 2.74 24.04 11.40
    12径阶 8.29 40.22 1.29 6.26 1.39 6.74 3.80 18.44 5.84 28.34 20.61
    16径阶 23.86 37.71 5.59 8.83 1.41 2.23 11.58 18.30 20.84 32.93 63.28
    20径阶 43.45 52.67 8.29 10.05 2.20 2.67 11.47 13.90 17.09 20.72 82.50
    26径阶 67.06 50.38 12.01 9.02 2.72 2.04 21.87 16.43 29.46 22.13 133.12
    32径阶 116.44 37.63 14.84 4.80 8.72 2.82 60.25 19.47 109.20 35.29 309.45
    38径阶 151.45 24.72 30.39 4.96 28.63 4.67 253.53 41.39 148.58 24.25 612.58

    Table 11.  Carbon storage and allocation of organs in different diameters of Cinnamomum camphora

  • 分别用y = axby = aebxy = ax + by = alnx + by= a1xb1+a2xb2+a3xb3+… + c等5种模型建立樟树各器官碳储量与年龄、胸径及D2H之间的回归方程,比较并选出拟合效果最好的模型作为预测樟树各器官及全树的碳储量方程(表 12)。结果表明:模型拟合效果较好的均为y = axb方程,年龄、胸径、D2H与碳储量均有显著相关性,各器官碳储量方程R2除树枝碳储量与年龄方程在0.5以下外,其他R2均在0.5以上,F均在50以上,P均小于0.01,经交叉检验,各模型拟合效果显著。

    回归因子 器官 样木数/株 回归方程 R2 F P
    年龄 全树 40 Ct= 0.019 4A2.652 0 0.602 9 57.693 6 0.000 2
    年龄 树干 90 Cs= 0.064 2A2.034 7 0.640 3 156.649 2 0.000 0
    年龄 树皮 90 Cba=0.027 9A1.749 3 0.648 8 162.575 9 0.000 0
    年龄 树枝 90 Cbr=0.025 4A2.225 1 0.408 8 60.850 4 0.000 2
    年龄 树叶 90 Cl= 0.000 5A2.755 5 0.511 4 92.107 2 0.000 0
    年龄 树根 40 Cr= 0.002 9A2.818 4 0.591 6 55.052 1 0.000 0
    胸径 全树 40 Ct= 0.011 8D2.937 6 0.943 2 631.255 7 0.000 0
    胸径 树干 90 Cs= 0.053 8D2.193 2 0.844 5 477.973 1 0.000 0
    胸径 树皮 90 Cba= 0.010 6D2.119 5 0.834 2 442.779 6 0.000 0
    胸径 树枝 90 Cbr= 1.17× 10-5D4.528 1 0.868 4 580.613 9 0.000 0
    胸径 树叶 90 Cl= 4.73× 10-5D3.522 7 0.636 5 157.096 3 0.000 0
    胸径 树根 40 Cr= 0.011 0D2.588 5 0.844 9 206.952 5 0.000 0
    D2H 全树 40 Ct= 0.001 6(D2H1.268 6 0.910 5 386.460 4 0.000 0
    D2H 树干 90 Cs= 0.005 8(D2H1.030 1 0.911 3 904.239 3 0.000 0
    D2H 树皮 90 Cba= 0.002 1(D2H0.939 0 0.871 5 596.904 5 0.000 0
    D2H 树枝 90 Cbr= 5.93× 10-5D2H)1.485 9 0.769 2 293.301 4 0.000 0
    D2H 树叶 90 Cl=0.000 4(D2H1.063 3 0.519 7 95.235 3 0.000 0
    D2H 树根 40 Cr=0.001 2(D2H1.161 7 0.819 9 173.028 7 0.000 0

    Table 12.  Carbon storage regression equation of Cinnamomum camphora

  • 广东樟树全树加权平均含碳率为0.509 6,各器官含碳率除树皮外,树干、树叶、树枝、树根差异不显著,树干含碳率高于其他各器官,而树皮含碳率要显著低于其他器官。由于树干木材有较多的木质素,木质素碳含量高,所以干、枝含碳率较高,而树皮作为植物营养运输器官,纤维素多,木质素少,因此含碳率低,显然这是由植物本身的构造特点所决定的,这与大多数研究结论一致[31-32]。由于树皮的单株碳储量占全树碳储量比例很少,平均不到6%,多数径阶不到10%,所以,从实用角度,可以忽略,可采用其他器官含碳率进行估算。算术平均计算与加权平均计算2种方法计算的含碳率差异不大,结论与部分研究学者相同[33]。树干上部、中部、下部含碳率无明显变化,粗根含碳率大于细根,这与李春平等[34]研究结果相一致。

    樟树不同龄组含碳率从大到小顺序为近熟林(0.520 2),成熟林(0.510 4),过熟林(0.509 6),中龄林(0.508 6),幼龄林(0.508 1)。含碳率的变化过程与林木成熟过程基本一致,含碳率随年龄增加而增加,到近熟林、成熟林达到最高,过熟林后再微小下降,主要是由于随着年龄增加,林木的木质化程度越来越高,到近熟林、成熟林木质化达到最大,过熟林后木质素分解所引起的。人工林的含碳率要高于天然林,可能是施肥、抚育等人工经营措施提高了植物光合作用的效率,从而导致人工林木质素多于天然林,提高了植物含碳率。

    各纬度带樟树含碳率从大到小顺序为中亚热带(0.512 3),南亚热带(0.508 6),热带(0.494 5),含碳率随着纬度降低而减少,主要是由于纬度降低,温度升高、降水增加,植物生长速度快,导致其木质化程度低,因此低纬度带含碳率总体要低于高纬度带的。广东纬度总体上要低于湖南和贵州,但本研究所述含碳率却高于湖南、贵州,可能是植物的生长环境如土壤、坡位、坡向、郁闭度等对含碳率影响更大,需要对此作更进一步的研究,才能得出更精确的结论。不同海拔高度樟树含碳率从大到小顺序为低山(0.515 4),丘陵(0.509 6),平原(0.506 4),随着海拔增加,植物含碳率降低,主要原因是海拔增加,温度降低,植物生长速度变慢,从而使木质化程度增加,提高其含碳率。这与罗艳等[35]研究结果相一致。

    含碳率是森林碳储量估算中的重要参数。大多数研究者估算不同区域尺度的森林碳储量时,多采用0.500 0或0.450 0作为通用平均含碳率,但不同气候带、不同海拔、不同年龄、不同起源的树种含碳率是不同的,在全国或大区域范围内采用0.500 0或0.450 0作为含碳率的固定参数进行森林植被碳储量的估测是可行的,但对省级区域以及地方区域森林植被碳储量的估算会有一定的误差。本研究中,广东樟树平均含碳率为0.509 6,略高于0.500 0,明显高于0.450 0的通用平均含碳率,当采用通用平均含碳率0.450 0计算广东森林植被碳储量时,可能会导致森林植被碳储量10%以上的误差,采用0.500 0估算会较接近真实结果。因此,为准确估算省级区域以及地方区域的森林植被碳储量,应根据不同气候带、不同海拔、不同年龄、不同起源的含碳率作为转换参数,以减少碳储量估算中的不确定性。

    樟树各器官碳储量在全树中的比例排列从大到小顺序为树干(33.78%),树枝(29.47%),树根(27.04%),树皮(7.41%),树叶(3.74%),表明樟树碳主要储存分布在树干、树枝和树根上。随着胸径增大,全树及各器官碳储量增加幅度并不一样,在胸径2~8 cm时碳储量增加幅度较小,从胸径12 cm开始,碳储量增加幅度较大,樟树碳储量增加主要在生长的中后期。随着胸径增加各器官碳储量占全树比例变化趋势并不相同,树干碳储量的比例先增加后下降,胸径20 cm时达到最大;树皮碳储量比例在胸径20 cm以前较稳定,20 cm以后下降;树叶、树根碳储量比例较稳定;树枝碳储量比例是初期稳定,后期增加。

    通过对样木年龄、胸径、D2H与碳储量进行回归分析,获得樟树全树碳储量最优回归方程,年龄回归方程为Ct= 0.019 4A2.652 0,胸径回归方程为Ct=0.011 8D2.937 6D2H回归方程为Ct=0.001 6(D2H1.268 6,全树最优碳储量方程的R2均达到了0.6以上。以胸径和D2H为自变量的全树及各器官碳储量方程R2为0.51~0.95,而以年龄为自变量的全树及各器官碳储量方程R2仅为0.40~0.65,相较于以常用的胸径和树高等易测因子建立的碳储量模型,以年龄为自变量的碳储量模型的拟合效果相对差一些,这可能与植物本身生长特性有关。各器官碳储量方程的R2绝大多数都在0.5以上,模型总体上相关性显著。相对而言,年龄、胸径、D2H与树枝、树叶碳储量相关性相对差一些,可能是树枝、树叶受生长环境影响较大,碳储量变动较大,影响了模型效果。此外,由于大径级样本少等建模局限性,本研究建立的樟树碳储量模型用于估算实验样本年龄、胸径、树高范围外的单木碳储量可能会存在误差,在使用过程中要注意模型的外延问题。

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