|
|
Biomass allometric model of main forest types in Shanxi Plateau |
HE Li1, YAN Junxia1, DUAN Lanlan1, LIU Ju2, WANG Yan1 |
1. Institute of Loess Plateau, Shanxi University, 030006, Taiyuan, China; 2. Shanxi Academy of Forestry and Grassland Science, 030012, Taiyuan, China |
|
|
Abstract [Background] The distribution pattern and estimation model of forest biomass differ greatly in different regions. It is necessary to establish a biomass growth model suitable for specific area and specific environmental conditions to accurately estimate regional forest biomass and reduce estimation errors. To establish biomass allometry models of different forest types in Shanxi Plateau is of scientific significance for forest productivity and carbon cycle research.[Methods] Based on the data of a total of 97 trees of 9 tree species, which was grouped into deciduous broad-leaved forest(DBF), temperate coniferous forest(TCF) and cold temperate coniferous forest(CCF), from 10 representative ecological stations in Shanxi province, as well as their biomass data of the each part of the species measured by harvest method, we established their biomass regression models by using diameter at breast height(D) and height(H) of a tree as the independent variables for the three forest types to compare the accuracy of the models. [Results] 1) The overall average proportion of total biomass in trunk, crown and root of the 9 tree species was 47.22%, 25.59% and 27.18%, respectively; except for Pinus sylvestris, the tree trunk biomass accounted for the largest proportion of the total biomass. The ratio of root to shoot of the all tree species ranged from 0.12-0.88, with a maximum and minimum ratio in both Platycladus orientalis and Pinus sylvestris. 2) Among trunk biomass models, the model including both D and H variables fitted well for all the species. The determination coefficient(R2) of the model for DBF, TCF and, CCF species, when both D and H was used as a combining variable(D2×H), reached 0.82, 0.97 and 0.96, respectively. The R2 of the model, when D and H were used as additive variable(D+H), were 0.84, 0.97 and 0.98, respectively, for DBF, TCF and CCF, respectively. For canopy and root biomass, the performance of the models was similar to those for the trunks, and both D and H could be well used to estimate their biomass. The R2 values of the fitted models for canopy biomass were 0.67, 0.75 and 0.88 for DBF, TCF, and CCF, respectively, and 0.61 and 0.70 for the roots biomass for both DBF and CF. 3) Comparing with the results from the Chinese Forest Model(CFM), the biomass prediction deviation from the current models was significantly less than those from the CFM. [Conclusions] The established allometric equations using both D and H as independent variables in our study are more suitable for biomass estimation of this area. In practical applications, a model that is applicable and meets the accuracy requirements should be selected for different sites.
|
Received: 25 August 2022
|
|
|
|
|
[1] |
WOODWELL G M,WHITTAKER R H,REINERS W A,et al.The biota and the world carbon budget[J].Science,1978,199(4325):141.
|
[2] |
ALTANZAGAS B,LUO Y,ALTANSUKH B,et al.Allometric equations for estimating the above-ground biomass of five forest tree species in Khangai,Mongolia[J].Forests,2019,10(8):661.
|
[3] |
赵厚本,周光益,李兆佳,等.南亚热带常绿阔叶林4个常见树种的生物量分配特征与异速生长模型[J].林业科学,2022,58(2):23.ZHAO Houben,ZHOU Guangyi,LI Zhaojia,et al.Biomass allocation and allometric growth models of four common tree species in southern subtropical evergreen broad-leaved forest[J].Scientia Silvae Sinicae,2022,58(2):23.
|
[4] |
CHAVE J,ANDALO C,BROWN S,et al.Tree allometry and improved estimation of carbon stocks and balance in tropical forests[J].Oecologia,2005,145(1):87.
|
[5] |
曾伟生.全国立木生物量方程建模方法研究[D].北京:中国林业科学研究院,2011:2.ZENG Weisheng.Methodology on modeling of single-tree biomass equations for national biomass estimation in China[D].Beijing:Chinese Academy of Forestry,2011:2.
|
[6] |
卢立华,李华伟,农友,等.南亚热带4种人工林生物量及其分配格局[J].中南林业科技大学学报,2020,40(8):91.LU Lihua,LI Huawei,NONG You,et al.Biomass and its distribution pattern in four subtropical plantation ecosystems[J].Journal of Central South University of Forestry & Technology,2020,40(8):91.
|
[7] |
李海奎,雷渊才.中国森林植被生物量和碳储量评估[M].北京:中国林业出版社,2010:13.LI Haikui,LEI Yuancai.Estimation and evaluation of forest biomass carbon storage in China[M].Beijing:China Forestry Publishing House,2010:13.
|
[8] |
朱江,韩海荣,康峰峰,等.山西太岳山华北落叶松生物量分配格局与异速生长模型[J].生态学杂志,2016,35(11):2918.ZHU Jiang,HAN Hairong,KANG Fengfeng,et al.Biomass allocation patterns and allometric models of Larix principis-rupprechtii in Mt.Taiyue,Shanxi[J].Chinese Journal of Ecology,2016,35(11):2918.
|
[9] |
陈天成,李新平,郝向春,等.山西省辽东栎单株木生长模型研究[J].林业建设,2022(2):36.CHEN Tiancheng,LI Xinping,HAO Xiangchun,et al.Growth model of individual Quercus wutaishansea Mary in Shanxi province[J].Foresty Construction,2022(2):36.
|
[10] |
邱丽氚,王尚义.山西植被空间分布及其变化[J].太原师范学院学报(自然科学版),2013,12(3):124.QIU Lichuan,WANG Shangyi.Spatial distributions and changes of vegetation in Shanxi province[J].Journal of Taiyuan Noramal University (Natural Science Edition),2013,12(3):124.
|
[11] |
孙拖焕,李振龙,孙向宁,等.山西省直国有林森林生态系统服务功能研究[M].北京:中国林业出版社,2019:8.SUN Tuohuan,LI Zhenlong,SUN Xiangning,et al.Study on forest ecosystem service function of directly state-owned forest in Shanxi province[M].Beijing:China Forestry Publishing House,2019:8.
|
[12] |
孙拖焕,梁守伦,樊兰英,等.山西省森林生态连清与生态系统服务功能研究[M].北京:中国林业出版社,2019:41.SUN Tuohuan,LIANG Shoulun,FAN Lanying,et al.Study on forest ecological continuous clearing and ecosystem service function in Shanxi province[M].Beijing:China Forestry Publishing House,2019:41.
|
[13] |
郭耆,赵厚本,周光益,等.南亚热带4个树种人工林生物量及其分配格局[J].林业科学研究,2022,35(1):182.GUO Shi,ZHAO Houben,ZHOU Guangyi,et al.Biomass and its distribution patterns of four species plantations in subtropical China[J].Forest Research,2022,35(1):182.
|
[14] |
余明,刘效东,薛立.温度和降水对森林生物量分配的影响研究进展[J].生态科学,2021,40(2):204.YU Ming,LIU Xiaodong,XUE Li.Progress on effects of temperature and precipitation on forest biomass allocation patterns[J].Ecological Science,2021,40(2):204.
|
[15] |
REICH P B,LUO Y,BRADFORD J B,et al.Temperature drives global patterns in forest biomass distribution in leaves,stems,and roots[J].PNAS,2014,111(38):13721.
|
[16] |
HOUGHTON R A,LAWRENCE,JHACKLER J L,et al.The spatial distribution of forest biomass in the Brazilian Amazon:A comparison of estimates[J].Global Change Biology,2001,7(7):731.
|
[17] |
罗云建,张小全,王效科,等.华北落叶松人工林生物量及其分配模式[J].北京林业大学学报,2009,31(1):13.LUO Yunjian,ZHANG Xiaoquan,WANG Xiaoke,et al.Biomass and its distribution patterns of Larix principis-rupprechtii plantations in northern China[J].Journal of Beijing Forestry University,2009,31(1):13.
|
[18] |
CHAVE J, RÉJOU-MÉCHAIN M, BÚRQUEZ A, et al. Improved allometric models to estimate the aboveground biomass of tropical trees[J]. Global Change Biology, 2014, 20(10): 3177.
|
[19] |
BASUKI T M,van LAAKE P E,SKIDMORE A K,et al.Allometric equations for estimating the above-ground biomass in tropical lowland Dipterocarp forests[J].Forest Ecology and Management,2009,257(8):1684.
|
[20] |
MCNICOL I M,BERRY N J,BRUUN T B,et al.Development of allometric models for above and belowground biomass in swidden cultivation fallows of northern Laos[J].Forest Ecology and Management,2015,357:104.
|
[21] |
汪珍川,杜虎,宋同清,等.广西主要树种(组)异速生长模型及森林生物量特征[J].生态学报,2015,35(13):4462.WANG Zhenchuan,DU Hu,SONG Tongqing,et al.Allometric models of major tree species and forest biomass in Guangxi[J].Acta Ecologica Sinica,2015,35(13):4462.
|
[22] |
BOND-LAMBERTY B,WANG C,GOWER S T.Aboveground and belowground biomass and sapwood area allometric equations for six boreal tree species of northern Manitoba[J].Canadian Journal of Forest Research,2002,32(8):1441.
|
[23] |
CLOUGH B F.Primary productivity and growth of mangrove forests[J].Coastal and Estuarine Studies,1992,41:225.
|
[24] |
NIIYAMA K,KAJIMOTO T,MATSUURA Y,et al.Estimation of root biomass based on excavation of individual root systems in a primary dipterocarp forest in Pasoh Forest Reserve,Peninsular Malaysia[J].Journal of Tropical Ecology,2010,26(3):271.
|
|
|
|