基于国家森林资源清查数据的不同生物量和碳储量估计方法的对比分析
|
摘要
[目的]通过对不同生物量和碳储量的估计方法进行对比分析,为确定在国家森林资源清查中生物量和碳储量的具体估计方法提供依据。[方法]以广东省2012年森林资源清查的100个杉木林和80个马尾松林的实测样地资料为基础,利用近年来我国建立的主要树种立木生物量模型,对改进IPCC法、生物量模型法和转换因子连续函数法(即方精云法)3种方法按一元和二元模型共6种方案进行了对比;同时,基于改进IPCC法一元和二元模型的生物量估计值,用平均含碳系数法、组分含碳系数法和固定含碳系数(0.5或0.47)法分别对碳储量进行估计。[结果]用二元生物量模型法得到的杉木林和马尾松林样地的总生物量分别为320 Mg和331 Mg,一元生物量模型法的结果分别相差0.9%和6.2%;改进IPCC法的估计结果,采用二元和一元模型时杉木林分别相差-3.6%和-11.9%,马尾松林分别相差-8.5%和-19.6%;而方精云法的估计结果,采用二元和一元模型时杉木林分别相差6.65倍和6.60倍,马尾松林分别相差-14.3%和-18.0%。平均含碳系数法和组分含碳系数法的碳储量估计结果,杉木林仅相差0.2%,马尾松林相差约0.4%;固定含碳系数法的估计结果因树种而异,对杉木林要低估0.6%5.4%,对马尾松林要低估3.3%9.1%。[结论]对生物量的估计,采用生物量模型法准确性最高,而林木水平的生物量模型其预估精度要高于林分水平的模型;IPCC法是基于材积源的通用方法,将其中的缺省参数改进为可变参数模型,可大大提高方法的适应性;方精云法只是基于IPCC法所建立的林分水平模型在大尺度上的一种具体应用方法,其精度要低于林木水平的生物量模型法,不适于中小尺度应用。对碳储量的估计,采用平均含碳系数法与组分含碳系数法差异很小,但采用固定含碳系数法则误差较大。
[Objective] To provide the basis for determining the specific estimation methods of biomass and carbon storage in national forest inventory,by comparing and analyzing different methods for estimating forest biomass and carbon storage. [Method]Based on the mensuration data of 100 Chinese fir( Cunninghamia lanceolata) plots and 80 Masson pine( Pinus massoniana) plots of national forest inventory in Guangdong Province in 2012,a total of 6 schemes,combined from 2 kinds of models( one-and two-variable models) and 3 methods( improved IPCC method,biomass model method and biomass conversion factor continuous function method or Fang'method),were compared applying the individual tree biomass models of main tree species in China developed in recent years. In addi-tion,based on the biomass estimates of one-and two-variable models from improved IPCC method,3 approaches,i.e. the mean carbon content method,the component carbon content method and the constant carbon content( 0. 5 or 0. 47) method,were used for estimating carbon storage respectively. [Result] Total biomass of Chinese fir and Masson pine plots estimated from two-variable biomass models were 320 Mg and 331 Mg respectively,and the differences of estimates from one-variable models were 0. 9% and 6. 2% respectively. As for the improved IPCC method,the differences of estimates from two-and one-variable models were-3. 6% and -11. 9% respectively for Chinese fir,and -8. 5% and -19. 6% respectively for Masson pine. As for Fang's method,the differences of estimates from two-and one-variable models were 6. 65 and 6. 60 times respectively for Chinese fir,and -14. 3% and -18. 0% respectively for Masson pine. For comparison of mean carbon content and component carbon content methods,the differences of carbon storage estimates were about 0. 2% and 0. 4% for Chinese fir and Masson pine respectively; and the estimation results from constant carbon content method depended upon tree species,the carbon storages were underestimated by 0. 6% ~ 5. 4% for Chinese fir and 3. 3% ~ 9. 1% for Masson pine. [Conclusion]For biomass estimation,the biomass model method is the most accurate,and the tree level biomass models have lower prediction errors than stand level models. IPCC method is a volume-based general approach,which can be greatly improved when default parameters are changed to variable parameter models. Fang's method is just an approach for application on large-scale of stand level models developed on the basis of IPCC method,not suitable for middle-and small-scale applications because of its higher prediction errors than tree level biomass model method.For carbon storage estimation,the mean carbon content method and component carbon content method are little different,but constant carbon content method is less accurate.
[Objective] To provide the basis for determining the specific estimation methods of biomass and carbon storage in national forest inventory,by comparing and analyzing different methods for estimating forest biomass and carbon storage. [Method]Based on the mensuration data of 100 Chinese fir( Cunninghamia lanceolata) plots and 80 Masson pine( Pinus massoniana) plots of national forest inventory in Guangdong Province in 2012,a total of 6 schemes,combined from 2 kinds of models( one-and two-variable models) and 3 methods( improved IPCC method,biomass model method and biomass conversion factor continuous function method or Fang'method),were compared applying the individual tree biomass models of main tree species in China developed in recent years. In addi-tion,based on the biomass estimates of one-and two-variable models from improved IPCC method,3 approaches,i.e. the mean carbon content method,the component carbon content method and the constant carbon content( 0. 5 or 0. 47) method,were used for estimating carbon storage respectively. [Result] Total biomass of Chinese fir and Masson pine plots estimated from two-variable biomass models were 320 Mg and 331 Mg respectively,and the differences of estimates from one-variable models were 0. 9% and 6. 2% respectively. As for the improved IPCC method,the differences of estimates from two-and one-variable models were-3. 6% and -11. 9% respectively for Chinese fir,and -8. 5% and -19. 6% respectively for Masson pine. As for Fang's method,the differences of estimates from two-and one-variable models were 6. 65 and 6. 60 times respectively for Chinese fir,and -14. 3% and -18. 0% respectively for Masson pine. For comparison of mean carbon content and component carbon content methods,the differences of carbon storage estimates were about 0. 2% and 0. 4% for Chinese fir and Masson pine respectively; and the estimation results from constant carbon content method depended upon tree species,the carbon storages were underestimated by 0. 6% ~ 5. 4% for Chinese fir and 3. 3% ~ 9. 1% for Masson pine. [Conclusion]For biomass estimation,the biomass model method is the most accurate,and the tree level biomass models have lower prediction errors than stand level models. IPCC method is a volume-based general approach,which can be greatly improved when default parameters are changed to variable parameter models. Fang's method is just an approach for application on large-scale of stand level models developed on the basis of IPCC method,not suitable for middle-and small-scale applications because of its higher prediction errors than tree level biomass model method.For carbon storage estimation,the mean carbon content method and component carbon content method are little different,but constant carbon content method is less accurate.
引文
[1]Ter-Mikaelian M T,Korzukhin M D.Biomass equations for sixtyfive north American tree species[J].Forest Ecology and Management,1997,97:1-24.
[2]Zianis D,Muukkonen P,MakipaaR,et al.Biomass and stem volume equations for tree species in Europe[J].Silva Fennica,2005,Monographs 4.
[3]Zeng W S.Developing tree biomass models for eight major tree species in China[M].Biomass Volume Estimation and Valorization for Energy.In Tech,2017,1-21,doi:10.5772/65664.
[4]Zeng W S.Development of monitoring and assessment of forest biomass and carbon storage in China[J].Forest Ecosystems,2014,1:20,doi:10.1186/s40663-014-0020-5.
[5]刘国华,傅伯杰,方精云.中国森林碳动态及其对全球碳平衡的贡献[J].生态学报,2000,20(5):733-740.
[6]周玉荣,于振良,赵士洞.我国主要森林生态系统碳贮量和碳平衡[J].植物生态学报,2000,24(5):518-522.
[7]王效科,冯宗炜,欧阳志云.中国森林生态系统的植物碳储量和碳密度研究[J].应用生态学报,2001,12(1):13-16.
[8]Fang J Y,Chen A P,Peng C H,et al.Changes in forest biomass carbon storage in China between 1949 and 1998[J].Science,2001,292:2320-2322.
[9]IPCC.Good practice guidance for land use,land use change and forestry.The Institute for Global Environmental Strategies for the IPCC,Japan[EB/OL].2003.http://www.ipcc-nggip.iges.or.jp/public/gpglulucf/gpglulucf_contents.html.
[10]IPCC.Guidelines for national greenhouse gas inventories-agriculture,forestry and other land use.Vol.4:Agriculture,Forestry and Other Land Use.Institute for Global Environmental Strategies for the IPCC,Japan.2006[EB/OL].http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html.
[11]Zhou X P,Hemstrom M A.Estimating aboveground tree biomass on forest land in the Pacific northwest:a comparison of approaches[J].Research Paper PNW-RP-584,US.2009.
[12]李海奎,赵鹏祥,雷渊才,等.基于森林清查资料的乔木林生物量估算方法的比较[J].林业科学,2012,48(5):44-52.
[13]Gao H L,Dong L H,Li F R,et al.Evaluation of four methods for predicting carbon stocks of Korean pine plantations in Heilongjiang province,China[J].PLo S ONE,2015,10(12):e0145017.doi:10.1371/journal.pone.0145017
[14]Tang X,Fehrmann L,Guan F,et al.Inventory-based estimation of forest biomass in Shitai County,China:A comparison of five methods[J].Ann For Res.2016,59(1):269-280.doi:10.15287/afr.2016.574
[15]曾伟生,唐守正.利用度量误差模型方法建立相容性立木生物量方程系统[J].林业科学研究,2010,23(6):797-803.
[16]曾伟生,唐守正,夏忠胜,等.利用线性混合模型和哑变量模型方法建立贵州省通用性生物量方程[J].林业科学研究,2011,24(3):285-291.
[17]国家林业局.立木生物量模型及碳计量参数—杉木(LY/T2264-2014)[S].北京:中国标准出版社.2015.
[18]国家林业局.立木生物量模型及碳计量参数—马尾松(LY/T2263-2014)[S].北京:中国标准出版社.2015.
[19]国家林业局.立木生物量模型及碳计量参数—湿地松(LY/T2261-2014)[S].北京:中国标准出版社.2015.
[20]国家林业局.立木生物量模型及碳计量参数—栎树(LY/T2658-2016)[S].北京:中国标准出版社.2017.
[21]国家林业局.立木生物量模型及碳计量参数—木荷(LY/T2660-2016)[S].北京:中国标准出版社.2017.
[22]国家林业局.立木生物量模型及碳计量参数—枫香(LY/T2661-2016)[S].北京:中国标准出版社.2017.
[23]叶金盛.广东省主要树种相对树高曲线模型的研建[J].广东林业科技,2006,22(1):26-31.
[24]Fang J Y,Liu G H,Xu S L.Biomass and net production of forest vegetation in China[J].Acta Ecol Sin,1996,16(4):497-508.
[25]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.
[26]曾伟生.二元立木材积方程的检验与更新方法探讨[J].中南林业调查规划,2010,29(3):1-5.
[2]Zianis D,Muukkonen P,MakipaaR,et al.Biomass and stem volume equations for tree species in Europe[J].Silva Fennica,2005,Monographs 4.
[3]Zeng W S.Developing tree biomass models for eight major tree species in China[M].Biomass Volume Estimation and Valorization for Energy.In Tech,2017,1-21,doi:10.5772/65664.
[4]Zeng W S.Development of monitoring and assessment of forest biomass and carbon storage in China[J].Forest Ecosystems,2014,1:20,doi:10.1186/s40663-014-0020-5.
[5]刘国华,傅伯杰,方精云.中国森林碳动态及其对全球碳平衡的贡献[J].生态学报,2000,20(5):733-740.
[6]周玉荣,于振良,赵士洞.我国主要森林生态系统碳贮量和碳平衡[J].植物生态学报,2000,24(5):518-522.
[7]王效科,冯宗炜,欧阳志云.中国森林生态系统的植物碳储量和碳密度研究[J].应用生态学报,2001,12(1):13-16.
[8]Fang J Y,Chen A P,Peng C H,et al.Changes in forest biomass carbon storage in China between 1949 and 1998[J].Science,2001,292:2320-2322.
[9]IPCC.Good practice guidance for land use,land use change and forestry.The Institute for Global Environmental Strategies for the IPCC,Japan[EB/OL].2003.http://www.ipcc-nggip.iges.or.jp/public/gpglulucf/gpglulucf_contents.html.
[10]IPCC.Guidelines for national greenhouse gas inventories-agriculture,forestry and other land use.Vol.4:Agriculture,Forestry and Other Land Use.Institute for Global Environmental Strategies for the IPCC,Japan.2006[EB/OL].http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html.
[11]Zhou X P,Hemstrom M A.Estimating aboveground tree biomass on forest land in the Pacific northwest:a comparison of approaches[J].Research Paper PNW-RP-584,US.2009.
[12]李海奎,赵鹏祥,雷渊才,等.基于森林清查资料的乔木林生物量估算方法的比较[J].林业科学,2012,48(5):44-52.
[13]Gao H L,Dong L H,Li F R,et al.Evaluation of four methods for predicting carbon stocks of Korean pine plantations in Heilongjiang province,China[J].PLo S ONE,2015,10(12):e0145017.doi:10.1371/journal.pone.0145017
[14]Tang X,Fehrmann L,Guan F,et al.Inventory-based estimation of forest biomass in Shitai County,China:A comparison of five methods[J].Ann For Res.2016,59(1):269-280.doi:10.15287/afr.2016.574
[15]曾伟生,唐守正.利用度量误差模型方法建立相容性立木生物量方程系统[J].林业科学研究,2010,23(6):797-803.
[16]曾伟生,唐守正,夏忠胜,等.利用线性混合模型和哑变量模型方法建立贵州省通用性生物量方程[J].林业科学研究,2011,24(3):285-291.
[17]国家林业局.立木生物量模型及碳计量参数—杉木(LY/T2264-2014)[S].北京:中国标准出版社.2015.
[18]国家林业局.立木生物量模型及碳计量参数—马尾松(LY/T2263-2014)[S].北京:中国标准出版社.2015.
[19]国家林业局.立木生物量模型及碳计量参数—湿地松(LY/T2261-2014)[S].北京:中国标准出版社.2015.
[20]国家林业局.立木生物量模型及碳计量参数—栎树(LY/T2658-2016)[S].北京:中国标准出版社.2017.
[21]国家林业局.立木生物量模型及碳计量参数—木荷(LY/T2660-2016)[S].北京:中国标准出版社.2017.
[22]国家林业局.立木生物量模型及碳计量参数—枫香(LY/T2661-2016)[S].北京:中国标准出版社.2017.
[23]叶金盛.广东省主要树种相对树高曲线模型的研建[J].广东林业科技,2006,22(1):26-31.
[24]Fang J Y,Liu G H,Xu S L.Biomass and net production of forest vegetation in China[J].Acta Ecol Sin,1996,16(4):497-508.
[25]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.
[26]曾伟生.二元立木材积方程的检验与更新方法探讨[J].中南林业调查规划,2010,29(3):1-5.