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Journal of Arid Land  2019, Vol. 11 Issue (4): 608-622    DOI: 10.1007/s40333-019-0023-8
    
Allometric biomass equations of Larix sibirica in the Altay Mountains, Northwest China
Yuanyuan LI1,2, Qijing LIU1,*(), Shengwang MENG3, Guang ZHOU1
1 Key Laboratory of Forest Cultivation, Department of Forest Sciences, Beijing Forestry University, Beijing 100083, China
2 Agricultural College, Shihezi University, Shihezi 832000, China
3 Qianyanzhou Ecological Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
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Abstract  

Boreal forests are important carbon sinks and have tremendous potential to mitigate climate change. Aboveground biomass of Siberian larch (Larix sibirica Ledeb.) stands in the Altay Mountains, Northwest China was studied and allometric equations that are related to the biomass of aboveground components using diameter at breast height (DBH) or both DBH and height (H) as independent variables for L. sibirica trees were derived in this paper. A linear simultaneous equation system by using either DBH or both DBH and H (DBH&H) indices, was used to ensure additivity of the biomass of individual tree components, and was fitted for L. sibirica. Model performance was validated using the jackknifing test. Results indicate that the goodness-of-fit for the regressions was lowest for the needles (R2 ranging from 0.696 to 0.756), and highest for the stem wood (R2 ranging from 0.984 to 0.997) and the aggregated biomass components (R2 ranging from 0.994 to 0.995). The coefficient of determination for each component was only marginally improved in terms of model fit and performance in the biomass equations that used DBH&H as the independent variables compared to that used DBH as the independent variable, and needles yielded an even worse fit. Stem biomass accounted for the largest proportion (87%) of the aboveground biomass. Based on the additive equations that used DBH as the single predicitor in this study, the mean aboveground carbon stock density and the carbon storage values of L. sibirica forests were 74.07 Mg C/hm2 and 30.69 Tg C, respectively, in the Altay Mountains. Empirical comparisons of published equations for the same species growing in the Altay Mountains of Mongolia were also presented. The mean aboveground carbon stock density estimated for L. sibirica forests was higher in the Chinese Altay Mountains than in the Mongolian Altay Mountains (66.00 Mg C/hm2).



Key wordsLarix sibirica      additive equation      allometric equation      nested regression method      carbon storage     
Received: 20 November 2017      Published: 10 August 2019
Fund:  This study was financially supported by the National High-Tech Research and Development Plan of China (2013AA122003).
Corresponding Authors:
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The first and second authors contributed equally to this work.

Cite this article:

Yuanyuan LI, Qijing LIU, Shengwang MENG, Guang ZHOU. Allometric biomass equations of Larix sibirica in the Altay Mountains, Northwest China. Journal of Arid Land, 2019, 11(4): 608-622.

URL:

http://jal.xjegi.com/10.1007/s40333-019-0023-8     OR     http://jal.xjegi.com/Y2019/V11/I4/608

[1] Alvarez E, Duque A, Saldarriaga J, et al.2012. Tree above-ground biomass allometries for carbon stocks estimation in the natural forests of Colombia. Forest Ecology and Management, 267(297): 297-308.
[2] Anitha K, Verchot L V, Joseph S, et al.2015. A review of forest and tree plantation biomass equations in Indonesia. Annals of Forest Science, 72(8): 981-997.
[3] Annighöfer P, Mölder I, Zerbe S, et al.2012. Biomass functions for the two alien tree species Prunus serotina Ehrh. and Robinia pseudoacacia L. in floodplain forests of Northern Italy. European Journal of Forest Research, 131(5): 1619-1635.
[4] Basuki T M, van Laake P E, Skidmore A K, et al.2009. Allometric equations for estimating the above-ground biomass in tropical lowland dipterocarp forests. Forest Ecology and Management, 257(8): 1684-1694.
[5] Battulga P, Tsogtbaatar J, Dulamsuren C, et al.2013. Equations for estimating the above-ground biomass of Larix sibirica in the forest-steppe of Mongolia. Journal of Forestry Research, 24(3): 431-437.
[6] Bi H, Turner J, Lambert M J.2004. Additive biomass equations for native eucalypt forest trees of temperate Australia. Trees, 18(4): 467-479.
[7] Blujdea V N B, Pilli R, Dutca I, et al.2012. Allometric biomass equations for young broadleaved trees in plantations in Romania. Forest Ecology and Management, 264(1): 172-184.
[8] Bonan G B.2008. Forests and climate change: forcings, feedbacks, and the climate benefits of forest. Science, 320(5882): 1444-1449.
[9] Bond-Lamberty B, Wang C, Gower S T.2002. Aboveground and belowground biomass and sapwood area allometric equations for six boreal tree species of northern Manitoba. Canadian Journal of Forest Research, 32(8): 1441-1450.
[10] Cairns M A, Haggerty P K, Alvarez R, et al.2000. Tropical Mexico's recent land-use change: A region's contribution to the global carbon cycle. Ecological Applications, 10(5): 1426-1441.
[11] Cairns M A, Olmsted I, Granados J, et al.2003. Composition and aboveground tree biomass of a dry semi-evergreen forest on Mexico's Yucatan Peninsula. Forest Ecology and Management, 186(1-3): 125-132.
[12] Carvalho J P, Parresol B R.2003. Additivity in tree biomass components of Pyrenean oak (Quercus pyrenaica Willd.). Forest Ecology and Management, 179(1-3): 269-276.
[13] Chauchard S, Beilhe F, Denis N, et al.2010. An increase in the upper tree-limit of silver fir (Abies alba Mill.) in the Alps since the mid-20th century: A land-use change phenomenon. Forest Ecology and Management, 259(8): 1406-1415.
[14] Chen F, Yuan Y J, Wei W S, et al.2012. Climatic response of ring width and maximum latewood density of Larix sibirica in the Altay Mountains, reveals recent warming trends. Annals of Forest Science, 69(6): 723-733.
[15] Chytrý M, Danihelka J, Kubešová S, et al.2008. Diversity of forest vegetation across a strong gradient of climatic continentality: Western Sayan Mountains, southern Siberia. Plant Ecology, 196(1): 61-83.
[16] Dong L, Zhang L, Li F.2014. A compatible system of biomass equations for three conifer species in Northeast, China. Forest Ecology and Management, 329: 306-317.
[17] Dong L, Zhang L, Li F.2015. Developing additive systems of biomass equations for nine hardwood species in Northeast China. Trees, 29(4): 1149-1163.
[18] Dulamsuren C, Hauck M, Khishigjargal M, et al.2010. Diverging climate trends in Mongolian taiga forests influence growth and regeneration of Larix sibirica. Oecologia, 163(4): 1091-1102.
[19] Dulamsuren C, Wommelsdorf T, Zhao F, et al.2013. Increased summer temperatures reduce the growth and regeneration of Larix sibirica in southern boreal forests of eastern Kazakhstan. Ecosystems, 16(8): 1536-1549.
[20] Dulamsuren C, Klinge M, Degener J, et al.2016. Carbon pool densities and a first estimate of the total carbon pool in the Mongolian forest-steppe. Global Change Biology, 22(2): 830-844.
[21] Fang J, Chen A, Peng C, et al.2001. Changes in forest biomass carbon storage in China between 1949 and 1998. Science, 292(5525): 2320-2322.
[22] Frank D, Ovchinnikov D, Kirdyanov A, et al.2007. The potential for long-term climatic reconstructions in the central Altay Mountains from living and relict larch. Trace, 5: 85-96.
[23] Gower S, Kucharik C, Norman J.2007. Direct and indirect estimation of leaf area index. International Journal of Remote Sensing, 5: 259-274.
[24] Goetz S J, Baccini A, Laporte N T, et al.2009. Mapping and monitoring carbon stocks with satellite observations: a comparison of methods. Carbon Balance and Management, 4(2): 1-7.
[25] Gower S T, Kucharik C J, Norman J M.1999. Direct and indirect estimation of leaf area index, fAPAR , and net primary production of terrestrial ecosystems. Remote Sensing of Environment, 70(1): 29-51.
[26] Hall R J, Case B S, Arsenault E, et al.2002. Modeling and mapping forest biomass using forest inventory and Landsat TM data: results from the foothills model forest, Alberta. Geoscience and Remote Sensing Symposium, 2002. IGARSS'02. 2002 IEEE International, 3: 24-28.
[27] Hall R J, Skakun R S, Arsenault E J, et al.2006. Modeling forest stand structure attributes using Landsat ETM+ data: Application to mapping of aboveground biomass and stand volume. Forest Ecology and Management, 225(1): 378-390.
[28] Hosoda K, Iehara T.2010. Aboveground biomass equations for individual trees of Cryptomeria japonica, Chamaecyparis obtusa and Larix kaempferi in Japan. Journal of Forest Research, 15(5): 299-306.
[29] Huang L, Gao Y, Li Y, et al.2015. Growth of siberia larch in the middle east of Altay Mountains and its reponse to climate change. Arid Land Geography, 38(6): 1169-1178. (in Chinese)
[30] Jarvis P, Linder S, Vaganov E A, et al.2000. Constraints to growth of boreal forests. Nature, 405(6789): 904-905.
[31] Jia Q, Liu Q, Li J.2015. Individual-based fine root biomass and its functional relationship with leaf for Pinus tabuliformis in northern China. European Journal of Forest Research, 134(4): 705-714.
[32] Jiao L, Jiang Y, Zhang W T, et al.2015. Divergent responses to climate factors in the radial growth of Larix sibirica in the eastern Tianshan Mountains, northwest China. Trees, 29(6): 1673-1686.
[33] Kajimoto T, Matsuura Y, Sofronov M A, et al.1999. Above- and below-ground biomass and net primary productivity of a Larix gmelinii stand near Tura, central Siberia. Tree Physiology, 19(12): 815-822.
[34] Kajimoto T, Matsuura Y, Osawa A, et al.2006. Size-mass allometry and biomass allocation of two larch species growing on the continuous permafrost region in Siberia. Forest Ecology and Management, 222(1-3): 314-325.
[35] Ketterings Q M, Coe R, Van Noordwijk M, et al.2001. Reducing uncertainty in the use of allometric biomass equations for predicting above-ground tree biomass in mixed secondary forests. Forest Ecology and Management, 146(1-3): 199-209.
[36] Koizumi A, Takata K, Yamashita K, et al.2003. Anatomical characteristics properties of Larix sibirica grown in south-central Siberia. IAWA Journal, 24(4): 355-370.
[37] Kuyah S, Sileshi G W, Rosenstock T S.2016. Allometric models based on Bayesian frameworks give better estimates of aboveground biomass in the miombo woodlands. Forests, 7(2): 1-13.
[38] Lambert M C, Ung C H, Raulier F.2005. Canadian national tree aboveground biomass equations. Canadian Journal of Forest Research, 35(8): 1996-2018.
[39] Li H, Zhao P.2013. Improving the accuracy of tree-level aboveground biomass equations with height classification at a large regional scale. Forest Ecology and Management, 289(289): 153-163.
[40] Li X, Liu Q, Hu L, et al.2006. Calculation of Pinus elliotii biomass: A comparison of different methods. Chinese Journal of Ecology, 25(12):1594-1598. (in Chinese)
[41] Liu Q.2009. Nested regression for establishing tree biomass equations. Chinese Journal of Plant Ecology, 33(2): 331-337. (in Chinese)
[42] Menéndezmiguélez M, Canga E, Barrio-Anta M, et al.2013. A three level system for estimating the biomass of Castanea sativa Mill. coppice stands in north-west Spain. Forest Ecology and Management, 291(2): 417-426.
[43] Meng S, Liu Q, Zhou G, et al.2017. Aboveground tree additive biomass equations for two dominant deciduous tree species in Daxing’anling, northernmost China. Journal of Forest Research, 1-8.
[44] Meng X.2006. Forest Mensuration (3rd ed.). Beijing:Chinese Forestry Publishing House, 25-26. (in Chinese)
[45] Ni J.2004. Forest productivity of the Altay and Tianshan Mountains in the dryland, northwestern China. Forest Ecology and Management, 202(1-3): 13-22.
[46] Pan Y, Birdsey R A, Fang J, et al.2011. A large and persistent carbon sink in the World's forests. Science, 333(6045): 988-993.
[47] Parresol B R.1999. Assessing tree and stand biomass: a review with examples and critical comparisons. Forest Science, 45(4): 573-593.
[48] Parresol B R.2001. Additivity of nonlinear biomass equations. Canadian Journal of Forest Research, 31(5): 865-878.
[49] Pérez-Cruzado C, Rodríguez-Soalleiro R.2011. Improvement in accuracy of aboveground biomass estimation in Eucalyptus nitens plantations: Effect of bole sampling intensity and explanatory variables. Forest Ecology and Management, 261(11): 2016-2028.
[50] Picard N, Henry M, Mortier F, et al.2012. Using Bayesian model averaging to predict tree aboveground biomass in tropical moist forests. Forest Science, 58(1): 15-23.
[51] Riofrío J, Herrero C, Grijalva J, et al.2015. Aboveground tree additive biomass models in Ecuadorian highland agroforestry systems. Biomass and Bioenergy, 80: 252-259.
[52] Shuman J K, Shugart H H, O'Halloran T L.2011. Sensitivity of Siberian larch forests to climate change. Global Change Biology, 17(7): 2370-2384.
[53] Son Y, Hwang J W, Kim Z S, et al.2001. Allometry and biomass of Korean pine (Pinus koraiensis) in central Korea. Bioresource Technology, 78(3): 251-255.
[54] Sprugel D G.1983. Correcting for bias in log-transformed Allometric Equations. Ecology, 64(1): 209-210.
[55] Tei S, Sugimoto A, Yonenobu H, et al.2014. Growth and physiological responses of larch trees to climate changes deduced from tree-ring widths and δ13C at two forest sites in eastern Siberia. Polar Science, 8(2): 183-195.
[56] Thurner M, Beer C, Santoro M, et al.2014. Carbon stock and density of northern boreal and temperate forests. Global Ecology and Biogeography, 23(3): 297-310.
[57] Tsogt K, Lin C.2014. A flexible modeling of irregular diameter structure for the volume estimation of forest stands. Journal of Forest Research, 19(1): 1-11.
[58] Wang C, 2006. Biomass allometric equations for 10 co-occurring tree species in Chinese temperate forests. Forest Ecology and Management, 222(1): 9-16.
[59] Wang W, Zu Y, Wang H, et al.2005. Plant biomass and productivity of Larix gmelinii forest ecosystems in Northeast China: intra- and inter-species comparison. Eurasian Journal of Forest Research-Hokkaido University (Japan), 8(1): 21-41.
[60] Wirth C, Schumacher J, Schulze E D.2004. Generic biomass functions for Norway spruce in Central Europe-a meta-analysis approach toward prediction and uncertainty estimation. Tree Physiology, 24(2): 121-139.
[61] Xu Y, Zhang J, Franklin S B,et al.2016. Improving allometry models to estimate the above- and below-ground biomass of subtropical forest, China. Ecosphere, 6(12): 1-15.
[62] Youkhana A H, Idol T W.2011. Allometric models for predicting above- and below-ground biomass of Leucaena-KX2 in a shaded coffee agroecosystem in Hawaii. Agroforestry Systems, 83(3): 331-345.
[63] Zhang H, Tang S, Xu H.1998. Studies on the estimate method for average stem density. Forest Research, 11(1): 58-62. (in Chinese)
[64] Zhang H, Zhu Y, Dixiati B, et al.2017. Biomass allocation patterns of Picea obovata and Larix sibirica in the Altai Mountains forest area. Journal of Nanjing Forestry University: Natural Sciences Edition, 41(1): 203-208. (in Chinese)
[65] Zhang M, Wang G.2008. The forest biomass dynamics of Zhejiang Province. Acta Ecologica Sinica, 28(11): 5665-5674. (in Chinese)
[66] Zhang Y, Meyers P A, Liu X, et al.2016. Holocene climate changes in the central Asia mountain region inferred from a peat sequence from the Altai Mountains, Xinjiang, northwestern China. Quaternary Science Reviews, 152: 19-30.
[67] Zhou G, Wang Y, Jiang Y, et al.2002. Estimating biomass and net primary production from forest inventory data: a case study of China's Larix forests. Forest Ecology and Management, 169(1-2): 149-157.
[68] Zhou X, Brandle J R, Schoeneberger, et al.2007. Developing above-ground woody biomass equations for open-grown, multiple-stemmed tree species: Shelterbelt-grown Russian-olive. Ecological Modelling, 202(3-4): 311-323.
[69] Zianis D, Mencuccini M.2004. On simplifying allometric analyses of forest biomass. Forest Ecology and Management, 187(2-3): 311-332.
[70] Zianis D, Muukkonen P, Maekipaeae R, et al.2005. Biomass and stem volume equations for tree species in Europe. Silva Fennica Monographs, 4(4): 1-63.
[71] Zianis D, Xanthopoulos G, Kalabokidis K, et al.2011. Allometric equations for aboveground biomass estimation by size class for Pinus brutia Ten. trees growing in North and South Aegean Islands, Greece. European Journal of Forest Research, 130(2): 145-160.
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