, Volume 33, Issue 1, pp 153–169 | Cite as

Biotic and abiotic influences on monthly variation in carbon fluxes in on-year and off-year Moso bamboo forest

  • Yufeng Zhou
  • Guomo Zhou
  • Huaqiang Du
  • Yongjun Shi
  • Fangjie Mao
  • Yuli Liu
  • Lin Xu
  • Xuejian Li
  • Xiaojun XuEmail author
Original Article


Key message

Monthly variation in gross primary productivity (GPP) between on-years and off-years were different. Main drivers of GPP in on-years were abiotic. In off-years drivers were biotic and abiotic.


Understanding biotic (living or once-living organisms) and abiotic (non-living physical and chemical elements) influences on seasonal variation in carbon fluxes in Moso bamboo forest is important for predicting future carbon sequestration under climate change. Although differing physiological and ecological characteristics of Moso bamboo forest between on-years and off-years have been observed, the drivers of annual differences in carbon fluxes remain unknown. In this study, drivers of variation in carbon fluxes were analyzed based on gross primary productivity (GPP) and biotic factors (leaf area and chlorophyll content here, represented by vegetation indices—VIs) and abiotic factors. Results showed that average monthly GPP between on-years and off-years was significantly different from January to June, mainly due to natural variation in biotic factors. The monthly variation in GPP during on-years was mainly influenced by abiotic factors, whereas that in off-years was determined by the combination of biotic and abiotic factors. Monthly variation and differences in GPP between on-years and off-years were well represented by VIs. The GPP was more strongly correlated with VIs in off-years than in on-years, owing to large seasonal variation in canopy chlorophyll content. Hence, GPP estimated from both air temperature and simple ratio was more accurate than that estimated from air temperature alone. Overall, the difference in GPP between on-years and off-years and its underlying mechanisms can be used to accurately estimate carbon fluxes in Moso forest and predict carbon fluxes under future climate warming.


Moso bamboo Gross primary productivity Biotic Abiotic MODIS 



This research was supported by the National Natural Science Foundation of China (Grant nos. 31500520, 31870619, 31670644).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


  1. Aubinet M, Chermanne B, Vandenhaute M, Longdoz B, Yernaux M, Laitat E (2001) Long term carbon dioxide exchange above a mixed forest in the Belgian Ardennes. Agric For Meteorol 108:293–315CrossRefGoogle Scholar
  2. Baldocchi D, Chu H, Reichstein M (2018) Inter-annual variability of net and gross ecosystem carbon fluxes: a review. Agric For Meteorol 249:520–533CrossRefGoogle Scholar
  3. Barford CC, Wofsy SC, Goulden ML, Munger JW, Pyle EH, Urbanski SP, Hutyra L, Saleska SR, Fitzjarrald D, Moore K (2001) Factors controlling long- and short-term sequestration of atmospheric CO2 in a mid-latitude forest. Science 294:1688–1691CrossRefGoogle Scholar
  4. Barr AG, Black TA, Hogg EH, Griffis TJ, Morgenstern K, Kljun N, Theede A, Nesic Z (2007) Climatic controls on the carbon and water balances of a boreal aspen forest, 1994–2003. Glob Chang Biol 13:561–576CrossRefGoogle Scholar
  5. Blanken PD, Black TA, Neumann HH, Den Hartog G, Yang PC, Nesic Z, Staebler R, Chen W, Novak MD (1998) Turbulence flux measurements above and below the overstory of a boreal aspen forest. Bound Layer Meteorol 89:109–140CrossRefGoogle Scholar
  6. Botta A, Viovy N, Ciais P, Friedlingstein P, Monfray P (2000) A global prognostic scheme of leaf onset using satellite data. Glob Chang Biol 6:709–725CrossRefGoogle Scholar
  7. Chen JM, Cihlar J (1996) Retrieving leaf area index of boreal conifer forests using Landsat TM images. Remote Sens Environ 55:153–162CrossRefGoogle Scholar
  8. Chen W, Chen J, Liu J, Cihlar J (2000) Approaches for reducing uncertainties in regional forest carbon balance. Global Biogeochem Cycles 14:827–838CrossRefGoogle Scholar
  9. Chen XG, Zhang XQ, Zhang YP, Booth T, He XH (2009) Changes of carbon stocks in bamboo stands in China during 100 years. For Ecol Manag 258:1489–1496CrossRefGoogle Scholar
  10. Chen S, Jiang H, Cai Z, Zhou X, Peng C (2018) The response of the net primary production of moso bamboo forest to the on and off-year management: a case study in Anji county, Zhejiang, China. For Ecol Manag 409:1–7CrossRefGoogle Scholar
  11. Doughty CE, Goulden ML (2008) Seasonal patterns of tropical forest leaf area index and CO2 exchange. J Geophys Res 113:G00B06. Google Scholar
  12. Dragoni D, Schmid HP, Wayson CA, Potter H, Grimmond CSB, Randolph JC (2011) Evidence of increased net ecosystem productivity associated with a longer vegetated season in a deciduous forest in south-central Indiana. USA Glob Chang Biol 17:886–897CrossRefGoogle Scholar
  13. FAO (2010) Global forest resources assessment 2010: main report. Food and Agriculture Organization of the United Nations, Rome. Google Scholar
  14. Gitelson AA, Viña A, Ciganda V, Rundquist DC, Arkebauer TJ (2005) Remote estimation of canopy chlorophyll content in crops. Geophys Res Lett 32:L08403. CrossRefGoogle Scholar
  15. Gitelson AA, Viña A, Verma SB, Rundquist DC, Arkebauer TJ, Keydan G, Leavitt B, Ciganda V, Burba GG, Suyker AE (2006) Relationship between gross primary production and chlorophyll content in crops: implications for the synoptic monitoring of vegetation productivity. J Geophys Res 111:D08S11. CrossRefGoogle Scholar
  16. Gitelson AA, Wardlow BD, Keydan GP, Leavitt B (2007) Evaluation of MODIS 250-m data for green LAI estimation in crops. Geophys Res Lett 34:L20403. CrossRefGoogle Scholar
  17. Gitelson AA, Peng Y, Arkebauer TJ, Schepers J (2014) Relationships between gross primary production, green lai, and canopy chlorophyll content in maize: implications for remote sensing of primary production. Remote Sens Environ 144:65–72CrossRefGoogle Scholar
  18. Gitelson AA, Peng Y, Arkebauer TJ, Suyker AE (2015) Productivity, absorbed photosynthetically active radiation, and light use efficiency in crops: implications for remote sensing of crop primary production. J Plant Physiol 177:100–109CrossRefGoogle Scholar
  19. Gratani L, Crescente MF, Varone L, Fabrini ED (2008) Growth pattern and photosynthetic activity of different bamboo species growing in the Botanical Garden of Rome. Flora 203:77–84CrossRefGoogle Scholar
  20. Griffis TJ, Rouse WR, Waddington JM (2000) Interannual variability of net ecosystem CO2 exchange at a subarctic fen. Global Biogeochem Cycles 14:1109–1121CrossRefGoogle Scholar
  21. Gu CY (2013) Satellite-based retrieval of canopy parameters of Moso bamboo forest with PROSAIL radiative transfer model. Zhejiang A&F University, Hangzhou (in Chinese) Google Scholar
  22. Hilker T, Galvão LS, Aragão LEOC, de Moura YM, do Amaral CH, Lyapustin AI, Wu J, Albert LP, Ferreira MJ, Anderson LO, dos Santos VAHF, Prohaska N, Tribuzy E, Ceron JVB, Saleska SR, Wang Y, de Carvalho Goncalves JF, de Oliveira Junior RC, Rodrigues JVFC, Garcia MN (2017) Vegetation chlorophyll estimates in the Amazon from multi-angle MODIS observations and canopy reflectance model. Int J Appl Earth Obs 5:8278–8287Google Scholar
  23. Hmimina G, Dufrêne E, Pontailler J-Y, Delpierre N, Aubinet M, Caquet B, de Grandcourt A, Burban B, Flechard C, Granier A, Gross P, Heinesch B, Longdoz B, Moureaux C, Ourcival J-M, Rambal S, Saint André L, Soudani K (2013) Evaluation of the potential of MODIS satellite data to predict vegetation phenology in different biomes: An investigation using ground-based NDVI measurements. Remote Sens Environ 132:145–158CrossRefGoogle Scholar
  24. Hörtensteiner S (2006) Chlorophyll degradation during senescence. Annu Rev Plant Biol 57:55–77CrossRefGoogle Scholar
  25. Hu YB (2011) Effects of fertilizations on leaf characteristics and photosynthesis character during the shoot period to deciduous period of Phyllostarchys pubescens. Zhejiang A&F University, Hangzhou (in Chinese) Google Scholar
  26. Huang Q, Yang D, Gao A, Shen Y, Qiu G, Long S, Beadle C, Hall D, Scurlock J (1989) Research on photosynthesis of bamboo. Bamboo Res 8:8–18 (in Chinese) Google Scholar
  27. Huete A, Didan K, Miura T, Rodriguez EP, Gao X, Ferreira LG (2002) Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sens Environ 83:195–213CrossRefGoogle Scholar
  28. Hui D, Luo Y, Katul G (2003) Partitioning interannual variability in net ecosystem exchange between climatic variability and functional change. Tree Physiol 23(7):433–442CrossRefGoogle Scholar
  29. Hwayne P, Frank AB, Sanabria J, Phillips RL (2008) Interannual variability in carbon dioxide fluxes and flux-climate relationships on grazed and ungrazed northern mixed-grass prairie. Glob Chang Biol 14:1620–1632CrossRefGoogle Scholar
  30. Kleinhenz V, Midmore DJ (2001) Aspects of bamboo agronomy. Adv Agron 74:99–153CrossRefGoogle Scholar
  31. Kleinhenz V, Milne J, Walsh KB, Midmore DJ (2003) A case study on the effects of irrigation and fertilization on soil water and soil nutrient status, and on growth and yield of bamboo (Phyllostachys pubescens) shoots. J Bamboo Rattan 2:281–293CrossRefGoogle Scholar
  32. Komatsu H, Onozawa Y, Kume T, Tsuruta K, Shinohara Y, Otsuki K (2012) Canopy conductance for a moso bamboo (Phyllostachys pubescens) forest in western japan. Agric For Meteorol 156:111–120CrossRefGoogle Scholar
  33. Law B, Falge E, Gu L, Baldocchi DD, Bakwin P, Berbigier P, Davis K, Dolman AJ, Falk M, Fuentes JD, Goldstein A, Granier A, Grelle A, Hollinger D, Janssens IA, Jarvis P, Jensen NO, Katul G, Mahli Y, Matteucci G, Meyers T, Monson R, Munger W, Oechel W, Olson R, Pilegaard K, Paw U, Thorgeirsson KT, Valentini H, Verma R, Vesalaa S, Wilson T, Wofsy KS (2002) Environmental controls over carbon dioxide and water vapor exchange of terrestrial vegetation. Agric For Meteorol 113:97–120CrossRefGoogle Scholar
  34. Li R, Werger MJA, During HJ, Zhong ZC (1998) Biennial variation in production of new shoots in groves of the giant bamboo Phyllostachys pubescens in Sichuan, China. Plant Ecol 135:103–112CrossRefGoogle Scholar
  35. Li R, Werger MJA, During HJ, Zhong ZC (1999) Biomass distribution in a grove of the giant bamboo Phyllostachys pubescens in Chongqing. China Flora 149:86–96Google Scholar
  36. Li P, Zhou G, Du H, Lu D, Mo L, Xu X, Shi Y, Zhou Y (2015) Current and potential carbon stocks in Moso bamboo forests in China. J Environ Manage 156:89–96CrossRefGoogle Scholar
  37. Liu Z, Wu C, Peng D, Wang S, Gonsamo A, Fang B, Yuan W (2017) Improved modeling of gross primary production from a better representation of photosynthetic components in vegetation canopy. Agric For Meteorol 233:222–234CrossRefGoogle Scholar
  38. Lou YP, Li YX, Buckingham K, Henley G, Zhou GM (2010) Bamboo and climate change mitigation. Technical report—International Network for Bamboo and Rattan (INBAR)Google Scholar
  39. Ma X, Huete A, Yu Q, Coupe NR, Davies K, Mark B, Ratana P, Beringer J, Hutley LB, Cleverly J, Boulain N, Eamus D (2013) Spatial patterns and temporal dynamics in savanna vegetationphenology across the north Australian tropical transect. Remote Sens Environ 139:97–115CrossRefGoogle Scholar
  40. Mao F, Li P, Zhou G, Du H, Xu X, Shi Y, Mo L, Zhou Y, Tu G (2016) Development of the BIOME-BGC model for the simulation of managed moso bamboo forest ecosystems. J Environ Manage 172:29–39CrossRefGoogle Scholar
  41. Mao F, Du H, Zhou G, Li X, Xu X, Li P, Sun S (2017) Coupled LAI assimilation and BEPS model for analyzing the spatiotemporal pattern and heterogeneity of carbon fluxes of the bamboo forest in Zhejiang province, China. Agric For Meteorol 242:96–108CrossRefGoogle Scholar
  42. Melaas EK, Richardson AD, Friedl MA, Dragoni D, Gough CM, Herbst M, Montagnani L, Moors E (2013) Using FLUXNET data to improve models of springtime vegetation activity onset in forest ecosystems. Agric For Meteorol 171:46–56CrossRefGoogle Scholar
  43. Nakaji T, Kosugi Y, Takanashi S, Niiyama K, Noguchi S, Tani M, Oguma H, Nik AR, Kassim AR (2014) Estimation of light-use efficiency through a combinational use of the photochemical reflectance index and vapor pressure deficit in an evergreen tropical rainforest at pasoh, peninsular malaysia. Remote Sens Environ 150(7):82–92CrossRefGoogle Scholar
  44. Papale D, Reichstein M, Aubinet M, Canfora E, Bernhofer C, Kutsch W, Longdoz B, Rambal S, Valentini R, Vesala T, Yakir D (2006) Towards a standardized processing of Net Ecosystem Exchange measured with eddy covariance technique: algorithms and uncertainty estimation. Biogeosciences 3:571–583CrossRefGoogle Scholar
  45. Qiu F (1984) The on-year and off-year of Phyllostachys pubescens forests and their control. J Bamboo Res 3:62–69 (in Chinese) Google Scholar
  46. Qiu GX, Shen KS, Li DY, Wang ZW, Huang QM, Yang DD, Gao AX (1992) Bamboo in subtropical eastern China. In: Long SP, Jones MB, Roberts MJ (eds) Primary production of grass ecosystems of the tropics and subtropics. Chapman and Hall, London, pp 159–188Google Scholar
  47. Rahman AF, Sims DA, Cordova VD, El-Masri BZ (2005) Potential of MODIS EVI and surface temperature for directly estimating per-pixel ecosystem C fluxes. Geophys Res Lett 32:L19404. CrossRefGoogle Scholar
  48. Richardson AD, Hollinger DY, Aber JD, Ollinger SV, Braswell BH (2007) Environmental variation is directly responsible for short- but not long-term variation in forest-atmosphere carbon exchange. Glob Chang Biol 13:788–803CrossRefGoogle Scholar
  49. Richardson AD, Hollinger DY, Dail DB, Lee JT, Munger W, O’Keefe J (2009) Influence of spring phenology on seasonal and annual carbon balance in two contrasting New England forest. Tree Physiol 29:321–331CrossRefGoogle Scholar
  50. Running SW, Hunt ER (1993) Generalization of a forest ecosystem processmodel for other biomes, BIOME-BGC, and an application for global-scalemodels. In: Scaling physiological processes: leaf to globe. Academic, New York, pp 141–158CrossRefGoogle Scholar
  51. Shanmughavel P, Anburaj A, Hemalatha S, Francis K (1997) Biochemical characteristics of plantation bamboo (bambusa bambos) leaf with reference to organic productivity. J Trop For Sci 9(4):558–560Google Scholar
  52. Shao J, Zhou X, He H, Yu G, Wang H, Luo Y, Chen J, Gu L, Li B (2014) Partitioning climatic and biotic effects on interannual variability of ecosystem carbon exchange in three ecosystems. Ecosystems 17(7):1186–1201CrossRefGoogle Scholar
  53. Shi H, Li L, Eamus D, Huete A, Cleverly J, Tian X, Yu Q, Wang S, Montagnani L, Magliulo V, Rotenberg E, Pavelka M, Carrara A (2017) Assessing the ability of MODIS EVI to estimate terrestrial ecosystem gross primary production of multiple land cover types. Ecol Indic 72:153–164CrossRefGoogle Scholar
  54. Sims DA, Rahman AF, Cordova VD, El-Masri BZ, Baldocchi DD, Flanagan LB, Goldstein AH, Hollinger DY, Misson L, Monson RK, Oechel WC, Schmid HP, Wofsy SC, Xu L (2006) On the use of modis EVI to assess gross primary productivity of north American ecosystems. J Geophys Res Biogeosci 111(G4):695–702CrossRefGoogle Scholar
  55. Sims DA, Rahman AF, Cordova VD, El-Masri BZ, Baldocchi DD, Flanagan LB, Goldstein AH, Hollinger DY, Misson L, Monson RK, Oechel WC, Schmid HP, Wofsy SC, Xu L (2008) A new model of gross primary productivity for North American ecosystems based solely on the enhanced vegetation index and land surface temperature from MODIS. Remote Sens Environ 112:1633–1646CrossRefGoogle Scholar
  56. Song X, Zhou G, Jiang H, Yu S, Fu J, Li W, Wang W, Ma Z, Peng C (2011) Carbon sequestration by Chinese bamboo forests and their ecological benefits: assessment of potential, problems, and future challenges. Environ Rev 19(1):418–428CrossRefGoogle Scholar
  57. Song X, Peng C, Zhou G, Gu H, Li Q, Zhang C (2016) Dynamic allocation and transfer of non-structural carbohydrates, a possible mechanism for the explosive growth of moso bamboo (phyllostachys heterocycla). Sci Rep 6:25908CrossRefGoogle Scholar
  58. Song X, Chen X, Zhou G, Jiang H, Peng C (2017) Observed high and persistent carbon uptake by Moso bamboo forests and its response to environmental drivers. Agric For Meteorol 247:467–475CrossRefGoogle Scholar
  59. Tang X, Li H, Xu X, Luo J, Li X, Ding Z, Xie J (2016) Potential of MODIS data to track the variability in ecosystem water-use efficiency of temperate deciduous forests. Ecol Eng 91:381–391CrossRefGoogle Scholar
  60. Teklemariam TA, Lafleur PM, Moore TR, Roulet NT, Humphreys ER (2010) The direct and indirect effects of inter-annual meteorological variability on ecosystem carbon dioxide exchange at a temperate ombrotrophic bog. Agric For Meteorol 150:1402–1411CrossRefGoogle Scholar
  61. Tucker CJ (1979) Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens Environ 8:127–150CrossRefGoogle Scholar
  62. Ueyama M, Iwata H, Harazono Y (2014) Autumn warming reduces the CO2 sink of a black spruce forest in interior Alaska based on a nine-year eddy covariance measurement. Glob Change Biol 20:1161–1173CrossRefGoogle Scholar
  63. Verma M, Friedl MA, Richardson AD, Kiely G, Cescattim A, Law BE, Wohlfahrt G, Gielen B, Roupsard O, Moors EJ, Toscano P, Vaccari FP, Gianelle D, Bohrer G, Varlagin A, Buchmann N, van Gorsel E, Montagnani L, Propastin P (2014) Remote sensing of annual terrestrial gross primary productivity from MODIS: an assessment using the FLUXNET La Thuile dataset. Biogeosciences 11(8):2185–2200CrossRefGoogle Scholar
  64. Viña A, Gitelson AA, Rundquist DC, Keydan G, Leavitt B, Schepers J (2004) Monitoring maize (Zea mays L.) phenology with remote sensing. Agron J 96:1139–1147CrossRefGoogle Scholar
  65. Wagle P, Xiao X, Scott RL, Kolb TE, Cook DR, Brunsell N, Baldocchi DD, Basara J, Matamala R, Zhou Y, Bajgain R (2015) Biophysical controls on carbon and water vapor fluxes across a grassland climatic gradient in the united states. Agric For Meteorol S215–S215(2):293–305Google Scholar
  66. Webb EK, Pearman GI, Leuning R (1980) Correction of flux measurements for density effects due to heat and water vapour transfer. Q J R Meteorolog Soc 106:85–100CrossRefGoogle Scholar
  67. Wilczak JM, Oncley SP, Stage SA (2001) Sonic anemometer tilt correction algorithms. Bound-Lay Meteorol 99:127–150CrossRefGoogle Scholar
  68. Wu C, Chen JM, Huang N (2011) Predicting gross primary production from the enhanced vegetation index and photosynthetically active radiation: evaluation and calibration. Remote Sens Environ 115(12):3424–3435CrossRefGoogle Scholar
  69. Wu C, Chen JM, Black TA, Price DT, Kurz WA, Desai AR, Gonsamo A, Jassal RS, Gough CM, Bohrer G, Dragoni D, Herbst M, Gielen B, Berninger F, Vesala T, Mammarella I, Pilegaard K, Blanken PD (2013) Interannual variability of net ecosystem productivity in forests is explained by carbon flux phenology in autumn. Glob Ecol Biogeogr 22:994–1006CrossRefGoogle Scholar
  70. Wu C, Gonsamo A, Gough CM, Chen JM, Xu S (2014) Modeling growing season phenology in north american forests using seasonal mean vegetation indices from modis. Remote Sens Environ 147(18):79–88CrossRefGoogle Scholar
  71. Wu J, Albert LP, Lopes AP, Restrepo-Coupe N, Hayek M, Wiedemann KT, Guan K, Stark SC, Christoffersen B, Prohaska N, Tavares JV, Marostica S, Kobayashi H, Ferreira ML, Campos KS, Da Silva R, Brando PM, Saleska SR (2016) Leaf development and demography explain photosynthetic seasonality in Amazon evergreen forests. Science 351(6276):972–977CrossRefGoogle Scholar
  72. Xiao X, Zhang Q, Braswell B, Urbanski S, Boles S, Wofsy S, Moore III, Ojima B, D (2004) Modeling gross primary production of temperate deciduous broadleaf forest using satellite images and climate data. Remote Sens Environ 91:256–270CrossRefGoogle Scholar
  73. Xiao X, Zhang Q, Hollinger D, Aber J, Moore III, B (2005) Modeling gross primary production of an evergreen needleleaf forest using MODIS and climate data. Ecol Appl 15(3):954–969CrossRefGoogle Scholar
  74. Xiao J, Zhuang Q, Baldocchi DD, Law BE, Richardson AD, Chen J, Oren R, Starr G, Noormets A, Ma S, Verma SB, Wharton S, Wofsy SC, Bolstad PV, Burns SP, Cook DR, Curtis PS, Drake BG, Falk M, Fischer ML, Foster DR, Gu L, Hadley JL, Hollinger DY, Katul GG, Litvak M, Martin TA, Matamala R, McNulty S, Meyers TP, Monson RK, Munger JW, Oechel WC, Paw U, Schmid KT, Scott HP, Sun R, Suyker G, Torn AE (2008) Estimation of net ecosystem carbon exchange for theconterminous United States by combining MODIS and AmeriFlux data. Agric For Meteorol 148(11):1827–1847CrossRefGoogle Scholar
  75. Xu X, Zhou G, Liu S, Du HQ, Mo LF, Shi YJ, Jiang H, Zhou YF, Liu EB (2013) Implications of ice storm damages on the water and carbon cycle of bamboo forests in southeastern China. Agric For Meteorol 177:35–45CrossRefGoogle Scholar
  76. Xu L, Shi Y, Zhou G, Xu X, Liu E, Zhou Y, Zhang F, Li C, Fang H, Chen L (2018a) Structural development and carbon dynamics of moso bamboo forests in Zhejiang province, China. For Ecol Manag 409:479–488CrossRefGoogle Scholar
  77. Xu X, Du H, Zhou G, Mao F, Li X, Zhu D, Li Y, Cui L (2018b) Remote estimation of canopy leaf area index and chlorophyll content in moso bamboo (Phyllostachys edulis, (carrière) j. houz.) forest using MODIS reflectance data. Ann For Sci 75(1):33CrossRefGoogle Scholar
  78. Yang DD, Huang QM, Gao AX (1988) Changes of bamboo leaf Pn at different positions in the canopy. For Res 1:217–223Google Scholar
  79. Yen TM (2016) Culm height development, biomass accumulation and carbon storage in an initial growth stage for a fast-growing moso bamboo (Phyllostachy pubescens). Bot Stud 57:1–9CrossRefGoogle Scholar
  80. Yen TM, Lee. J-S (2011) Comparing aboveground carbon sequestration between moso bamboo (Phyllostachys heterocycla) and China fir (Cunninghamia lanceolata) forests based on the allometric model. For Ecol Manag 261:995–1002CrossRefGoogle Scholar
  81. Yuan W, Luo Y, Richardson AD, Oren R, Luyssaert S, Janssens IA, Ceuleman R, Zhou X, Grünwald T, Aubinet M, Berhofer C, Baldocchi DD, Chen J, Dunn AL, Deforest JL, Dragoni D, Goldstein AH, Moors E, Munger JW, Monson RK, Suyker AE, Star G, Scott RL, Tenhunen J, Verma SB, Vesala T, Wofsy SC (2009) Latitudinal patterns of magnitude and interannual variability in net ecosystem exchange regulated by biological and environmental variables. Glob Chang Biol 15:2905–2920CrossRefGoogle Scholar
  82. Zhang X, Friedl MA, Schaaf CB, Strahler AH, Hodges JCF, Gao F, Reed BC, Huete A (2003) Monitoring vegetation phenology using MODIS. Remote Sens Environ 84(3):471–475CrossRefGoogle Scholar
  83. Zhao M, Running SW (2010) Drought-induced reduction in global terrestrial net primary production from 2000 through 2009. Science 329(5994):940–943CrossRefGoogle Scholar
  84. Zhou BZ, Fu MY, Xie JZ, Yang XS, Li ZC (2005) Ecological functions of bamboo forest: research and application. J Forestry Res 16(2):143–147CrossRefGoogle Scholar
  85. Zhou G, Jiang P, Mo L (2009) Bamboo: a possible approach to the control of global warming. Int J Nonlinear Sci Num 10:547–555Google Scholar
  86. Zhou B, Li Z, Wang X, Cao Y, An Y, Deng Z, Letu G, Wang G, Gu L (2011a) Impact of the 2008 ice storm on moso bamboo plantations in southeast China. J Geophys Res Biogeosci. Google Scholar
  87. Zhou GM, Xu XJ, Du HQ, Ge HL, Shi YJ, Zhou YF (2011b) Estimating aboveground carbon of Moso bamboo forests using the k nearest neighbors technique and satellite imagery. Photogramm Eng Rem S 77(11):1123–1131CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Yufeng Zhou
    • 1
    • 2
    • 3
  • Guomo Zhou
    • 1
    • 2
    • 3
  • Huaqiang Du
    • 1
    • 2
    • 3
  • Yongjun Shi
    • 1
    • 2
    • 3
  • Fangjie Mao
    • 1
    • 2
    • 3
  • Yuli Liu
    • 1
    • 2
    • 3
  • Lin Xu
    • 1
    • 2
    • 3
  • Xuejian Li
    • 1
    • 2
    • 3
  • Xiaojun Xu
    • 1
    • 2
    • 3
    Email author
  1. 1.State Key Laboratory of Subtropical SilvicultureZhejiang A & F UniversityLin’anChina
  2. 2.Zhejiang Provincial Collaborative Innovation Center for Bamboo Resources and High-efficiency UtilizationZhejiang A&F UniversityLin’anChina
  3. 3.Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang ProvinceZhejiang A & F UniversityLin’anChina

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