Skip to main content
Have a personal or library account? Click to login
Global simulations of carbon allocation coefficients for deciduous vegetation types Cover

Global simulations of carbon allocation coefficients for deciduous vegetation types

Tellus B: Chemical and Physical Meteorology
Volume 67 (2015): Issue 1
By: ,  ,  ,   and    
Open Access
|Jan 2015
References

References

  1. Anderson M. C. , Norman J. M. , Mecikalski J. R. , Otkin J. A. , Kustas W. P . A climatological study of evapotranspiration and moisture stress across the continental United States based on thermal remote sensing: 1. Model formulation . J. Geophys. Res . 2007 ; 112 : D10117 .
    Search in Google ScholarBack to article
  2. Arora V. K. , Boer G. J . A parameterization of leaf phenology for the terrestrial ecosystem component of climate models . Global Change Biol . 2005 ; 11 : 39 – 59 .
    Search in Google ScholarBack to article
  3. Barrett D. J. , Galbally I. E. , Graetz R. D . Quantifying uncertainty in estimates of C emissions from above-ground biomass due to historic land-use change to cropping in Austraila . Global Change Biol . 2001 ; 7 : 883 – 902 .
    Search in Google ScholarBack to article
  4. Bazzaz F. A. , Grace J . Plant Resource Allocation . 1997 ; Academic Press, San Diego, CA .
    Search in Google ScholarBack to article
  5. Bonan G. B . Ecological Climatology: Concepts and Applications . 2008 ; Cambridge University Press, Cambridge . 278 – 281 .
    Search in Google ScholarBack to article
  6. Bradley B. A. , Houghton R. A. , Mustard J. F. , Hamburg S. P . Invasive grass reduces aboveground carbon stocks in shrublands of the Western US . Global Change Biol . 2006 ; 12 ( 10 ): 1815 – 1822 .
    Search in Google ScholarBack to article
  7. Cannell M. G. R. , Dewar R . Carbon allocation in trees: a review of concepts for modelling . Adv. Ecol. Res . 1994 ; 25 : 59 – 104 .
    Search in Google ScholarBack to article
  8. Cerrillo R. M. N. , Oyonarte P. B . Estimation of above-ground biomass in shrubland ecosystems of southern Spain . Forest Syst . 2006 ; 15 ( 2 ): 197 – 207 .
    Search in Google ScholarBack to article
  9. Chapin F. S . Integrated responses of plants to stress . BioScience . 1991 ; 41 ( 1 ): 29 – 36 .
    Search in Google ScholarBack to article
  10. Chen Y. , Xia J. , Liang S. , Feng J. , Fisher J. B. , co-authors . Comparison of satellite-based evapotranspiration models over terrestrial ecosystems in China . Remote Sens. Environ . 2014 ; 140 : 279 – 293 .
    Search in Google ScholarBack to article
  11. De Kauwe M. G. , Medlyn B. E. , Zaehle S. , Walker A. P. , Dietze M. C. , co-authors . Where does the carbon go? A model–data intercomparison of vegetation carbon allocation and turnover processes at two temperate forest free air CO2 enrichment sites . New Phytol . 2014 ; 203 : 883 – 899 .
    Search in Google ScholarBack to article
  12. Doughty C. E. , Metcalfe D. B. , da Costa M. C. , de Oliveira A. A. R. , Neto G. F. C. , co-authors . The production, allocation and cycling of carbon in a forest on fertile terra preta soil in eastern Amazonia compared with a forest on adjacent infertile soil . Plant Ecol. Divers . 2013 ; 7 ( 1–2 ): 41 – 53 .
    Search in Google ScholarBack to article
  13. Foley J. A. , Prentice I. C. , Ramankutty N. , Levis S. , Pollard D. , co-authors . An integrated biosphere model of land surface processes, terrestrial carbon balance, and vegetation dynamics . Global Biogeochem. Cycles . 1996 ; 10 : 603 – 628 .
    Search in Google ScholarBack to article
  14. Franklin O. , Johansson J. , Dewar R. C. , Dieckmann U. , McMurtrie R. E. , co-authors . Modeling carbon allocation in trees: a search for principles . Tree Physiol . 2012 ; 32 ( 6 ): 648 – 666 .
    Search in Google ScholarBack to article
  15. Friedlingstein P. , Joel G. , Field C. , Fung I . Toward an allocation scheme for global terrestrial carbon models . Global Change Biol . 1999 ; 5 : 755 – 770 .
    Search in Google ScholarBack to article
  16. Friend A. , Stevens A. , Knox R. , Cannell M . A process-based, terrestrial biosphere model of ecosystem dynamics (Hybrid v3. 0) . Ecol. Model . 1997 ; 95 : 249 – 287 .
    Search in Google ScholarBack to article
  17. Fung I. Y. , Doney S. C. , Lindsay K. , John J . Evolution of carbon sinks in a changing climate . Proc. Natl. Acad. Sci. USA . 2005 ; 102 : 11201 – 11206 .
    Search in Google ScholarBack to article
  18. Global Modeling and Assimilation Office . File Specification for GEOSDAS Gridded Output Version 5.3, Report . 2004 ; Greenbelt, MD : NASA Goddard Space Flight Cent .
    Search in Google ScholarBack to article
  19. Gorissen A. , Tietema A. , Joosten N. N. , Estiarte M. , Penuelas J. , co-authors . Climate change affects carbon allocation to the soil in shrublands . Ecosystems . 2004 ; 7 : 650 – 661 .
    Search in Google ScholarBack to article
  20. Gower S. T. , Kucharik C. J. , Norman J. M . Direct and indirect estimation of leaf area index, f APAR, and net primary production of terrestrial ecosystems . Remote Sens. Environ . 1999 ; 70 : 29 – 51 .
    Search in Google ScholarBack to article
  21. Hastings W. K . Monte Carlo sampling methods using Markov chains and their applications . Biometrika . 1970 ; 57 : 97 – 109 .
    Search in Google ScholarBack to article
  22. Haverd V. , Smith B. , Raupach M. , Briggs P. , Nieradzik L. , co-authors . Coupling carbon allocation with leaf and root phenology predicts tree-grass partitioning along a savanna rainfall gradient . Biogeosci. Discuss . 2015 ; 12 : 16313 – 16357 .
    Search in Google ScholarBack to article
  23. Haxeltine A. , Prentice I. C . BIOME3: an equilibrium terrestrial biosphere model based on ecophysiological constraints, resource availability, and competition among plant functional types . Global Biogeochem. Cycles . 1996 ; 10 : 693 – 709 .
    Search in Google ScholarBack to article
  24. Holben B. N . Characteristics of maximum-value composite images from temporal AVHRR data . Int. J. Remote Sens . 1986 ; 7 : 1417 – 1434 .
    Search in Google ScholarBack to article
  25. Ise T. , Litton C. M. , Giardina C. P. , Ito A . Comparison of modeling approaches for carbon partitioning: impact on estimates of global net primary production and equilibrium biomass of woody vegetation from MODIS GPP . J. Geophys. Res . 2010 ; 115 ( G4 ): G04025 .
    Search in Google ScholarBack to article
  26. Jackson R. D. , Idso S. B. , Reginato R. J. , Pinter P. J . Canopy temperature as a crop water stress indicator . Water Resour. Res . 1981 ; 17 : 1133 – 1138 .
    Search in Google ScholarBack to article
  27. Janecek A. , Benderoth G. , Lüdeke M. , Kindermann J. , Kohlmaier G . Model of the seasonal and perennial carbon dynamics in deciduous-type forests controlled by climatic variables . Ecol. Model . 1989 ; 49 : 101 – 124 .
    Search in Google ScholarBack to article
  28. Kindermann J. , Lüdeke M. , Badeck F.-W. , Otto R. , Klaudius A. , co-authors . Structure of a global and seasonal carbon exchange model for the terrestrial biosphere the frankfurt biosphere model (FBM) . Water Air Soil Poll . 1993 ; 70 : 675 – 684 .
    Search in Google ScholarBack to article
  29. Krinner G. , Viovy N. , de Noblet Ducoudré N. , Ogée J. , Polcher J. , co-authors . A dynamic global vegetation model for studies of the coupled atmosphere biosphere system . Global Biogeochem. Cycles . 2005 ; 19 : 1015 .
    Search in Google ScholarBack to article
  30. Kucharik C. J. , Foley J. A. , Delire C. , Fisher V. A. , Coe M. T. , co-authors . Testing the performance of a dynamic global ecosystem model: water balance, carbon balance, and vegetation structure . Global Biogeochem. Cycles . 2000 ; 14 : 795 – 825 .
    Search in Google ScholarBack to article
  31. Levy P. , Cannell M. , Friend A . Modelling the impact of future changes in climate, CO2 concentration and land use on natural ecosystems and the terrestrial carbon sink . Global Environ. Change . 2004 ; 14 : 21 – 30 .
    Search in Google ScholarBack to article
  32. Liu D. , Chen Y. , Cai W. , Dong W. , Xiao J. , co-authors . The contribution of China's Grain to Green Program to carbon sequestration . Landscape Ecol . 2014 ; 29 : 1675 – 1688 .
    Search in Google ScholarBack to article
  33. Lüdeke M. K. , Badeck F.-W. , Otto R. D. , Hager C. , Donges S. , co-authors . The Frankfurt Biosphere Model: a global process-oriented model of seasonal and long-term CO2 exchange between terrestrial ecosystems and the atmosphere. I. Model description and illustrative results for cold deciduous and boreal forests . Clim. Res . 1994 ; 4 : 143 – 166 .
    Search in Google ScholarBack to article
  34. Luo T. X . The Spatial Pattern and Mathematical Model of Productions of China's Major Forest Types . 1996 ; Beijing, China : Science Academy of China . Unpublished Doctoral Dissertation .
    Search in Google ScholarBack to article
  35. Luo T. X. , Brown S. , Pan Y. , Shi P. , Ouyang H. , co-authors . Root biomass along subtropical to alpine gradients: global implication from Tibetan transect studies . Forest Ecol. Manag . 2005 ; 206 ( 1 ): 349 – 363 .
    Search in Google ScholarBack to article
  36. Luo T. X. , Li W. H. , Zhu H. Z . Estimated biomass and productivity of natural vegetation on the Tibetan Plateau . Ecol. Appl . 2002 ; 12 ( 4 ): 980 – 997 .
    Search in Google ScholarBack to article
  37. Malhi Y. , Doughty C. , Galbraith D . The allocation of ecosystem net primary productivity in tropical forests . Philos. Trans. R. Soc. Lond. B Biol. Sci . 2011 ; 366 : 3225 – 3245 .
    Search in Google ScholarBack to article
  38. McMurtrie R. E. , Dewar R. C . New insights into carbon allocation by trees from the hypothesis that annual wood production is maximized . New Phytol . 2013 ; 199 : 981 – 990 .
    Search in Google ScholarBack to article
  39. Metropolis N. , Rosenbluth A. W. , Rosenbluth M. N. , Teller A. H. , Teller E . Equation of state calculations by fast computing machines . J. Chem. Phys . 1953 ; 21 : 1087 – 1092 .
    Search in Google ScholarBack to article
  40. Monsi M. , Saeki T . Uber den Lichtfaktor in den Pflanzengesellschaften und seine Bedeutung fur die Stoffproduktion [The light factor in the plant communities and its importance for the fabric production] . Jpn. J. Bot . 1953 ; 14 : 22 – 52 .
    Search in Google ScholarBack to article
  41. Monteith J . Evaporation and environment . Symp. Soc. Exp. Biol . 1965 ; 19 : 205 – 234 .
    Search in Google ScholarBack to article
  42. Moorcroft P. , Hurtt G. , Pacala S. W . A method for scaling vegetation dynamics: the ecosystem demography model (ED) . Ecol. Monogr . 2001 ; 71 : 557 – 586 .
    Search in Google ScholarBack to article
  43. Morataya R. , Galloway G. , Berninger F. , Kanninen M . Foliage biomass-sapwood (area and volume) relationships of Tectona grandis LF and Gmelina arborea Roxb.: silvicultural implications . Forest Ecol. Manag . 1999 ; 113 : 231 – 239 .
    Search in Google ScholarBack to article
  44. Mu Q. , Zhao M. , Kimball J. S. , McDowell N. G. , Running S. W . A remotely sensed global terrestrial drought severity index . Bull. Am. Meteorol. Soc . 2013 ; 94 : 83 – 98 .
    Search in Google ScholarBack to article
  45. Myneni R. B. , Ramakrishna R. , Nemani R. , Running S. W . Estimation of global leaf area index and absorbed PAR using radiative transfer models . IEEE Trans. Geosci. Remote Sens . 1997 ; 35 : 1380 – 1393 .
    Search in Google ScholarBack to article
  46. Parton B. , Ojima D. , Del Grosso S. , Keough C . CENTURY Tutorial. Supplement to CENTURY User's Manual . 2001 . NREC Pub. Natural Resource Ecology Laboratory, Colorado State Univ., Fort Collins, Colorado, USA, pp. 13 .
    Search in Google ScholarBack to article
  47. Pinzon J. , Brown M. E. , Tucker C. J . Huang N . Satellite time series correction of orbital drift artifacts using empirical mode decomposition . Hilbert-Huang Transform: Introduction and Applications . 2005 ; Toh Tuck Lake, Singapore : World Scientific . 167 – 186 .
    Search in Google ScholarBack to article
  48. Poorter H. , Niklas K. J. , Reich P. B. , Oleksyn J. , Poot P. , co-authors . Biomass allocation to leaves, stems and roots: meta-analyses of interspecific variation and environmental control . New Phytol . 2012 ; 193 : 30 – 50 .
    Search in Google ScholarBack to article
  49. Post W. M. , King A. W. , Wullschleger S. D . Historical variations in terrestrial biospheric carbon storage . Global Biogeochem. Cycles . 1997 ; 11 : 99 – 109 .
    Search in Google ScholarBack to article
  50. Potter C. S. , Klooster S. A . Dynamic global vegetation modelling for prediction of plant functional types and biogenic trace gas fluxes . Global Ecol. Biogeogr . 1999 ; 8 : 473 – 488 .
    Search in Google ScholarBack to article
  51. Potter C. S. , Randerson J. T. , Field C. B. , Matson P. A. , Vitousek P. M. , co-authors . Terrestrial ecosystem production: a process model based on global satellite and surface data . Global Biogeochem. Cycles . 1993 ; 7 : 811 – 841 .
    Search in Google ScholarBack to article
  52. Reichle D. E . Dynamic Properties of Forest Ecosystems . 1981 ; Cambridge University Press, Cambridge .
    Search in Google ScholarBack to article
  53. Scheiter S. , Higgins S. I . Impacts of climate change on the vegetation of Africa: an adaptive dynamic vegetation modelling approach . Global Change Biol . 2009 ; 15 : 2224 – 2246 .
    Search in Google ScholarBack to article
  54. Schulze E.-D. , Wirth C. , Heimann M . Managing forests after Kyoto . Science . 2000 ; 289 : 2058 – 2059 .
    Search in Google ScholarBack to article
  55. Shang-guan T. L. , Zhang F . On synecological features and biomass of Ostryopsis davidiana bush-wood in Yunding Mountain, Shanxi province (in Chinese) . J. Shanxi Univ . 1989 ; 12 ( 3 ): 347 – 352 .
    Search in Google ScholarBack to article
  56. Sharpe P. J. , Rykiel E. J. Jr . Mooney H. A. , Winner W. E. , Pell E. J . Modelling integrated response of plants to multiple stresses . Response of Plants to Multiple Stresses . 1991 ; San Diego, CA : Academic Press . 205 – 224 .
    Search in Google ScholarBack to article
  57. Shinozaki K. , Yoda K. , Hozumi K. , Kira T . A quantitative analysis of plant form-the pipe model theory: I. Basic analyses . Jpn. J. Ecol . 1964a ; 14 : 97 – 105 .
    Search in Google ScholarBack to article
  58. Shinozaki K. , Yoda K. , Hozumi K. , Kira T . A quantitative analysis of plant form-the pipe model theory: II. Further evidence of the theory and its application in forest ecology . Jpn. J. Ecol . 1964b ; 14 : 133 – 139 .
    Search in Google ScholarBack to article
  59. Sitch S. , Smith B. , Prentice I. C. , Arneth A. , Bondeau A. , co-authors . Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model . Global Change Biol . 2003 ; 9 : 161 – 185 .
    Search in Google ScholarBack to article
  60. Tilman D . Plant Strategies and the Dynamics and Structure of Plant Communities . 1988 ; Princeton, NJ : Princeton University Press .
    Search in Google ScholarBack to article
  61. Tucker C. J. , Pinzon J. E. , Brown M. E. , Slayback D. A. , Pak E. W. , co-authors . An extended AVHRR 8 km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data . Int. J. Remote Sens . 2005 ; 26 : 4485 – 4498 .
    Search in Google ScholarBack to article
  62. Usoltsev V. A . Eurasian Forest Biomass and Primary Production Data (in Russian) . 2010 ; Yekaterinburg : Ural Branch of Russian Academy of Sciences . 18 – 41 .
    Search in Google ScholarBack to article
  63. Wang Y. P. , Law R. , Pak B . A global model of carbon, nitrogen and phosphorus cycles for the terrestrial biosphere . Biogeosciences . 2010 ; 7 : 2261 – 2282 .
    Search in Google ScholarBack to article
  64. Waring R. H. , Running S. W . Forest Ecosystems: Analysis at Multiple Scales . 2010 ; Academic Press, New York .
    Search in Google ScholarBack to article
  65. Watt M. S. , Clinton P. W. , Whitehead D. , Richardson B. , Mason E. G. , co-authors . Above-ground biomass accumulation and nitrogen fixation of broom (Cytisus scoparius L.) growing with juvenile Pinus radiata on a dryland site . Forest Ecol. Manag . 2003 ; 184 ( 1 ): 93 – 104 .
    Search in Google ScholarBack to article
  66. White M. A. , Thornton P. E. , Running S. W. , Nemani R. R . Parameterization and sensitivity analysis of the BIOME-BGC terrestrial ecosystem model: net primary production controls . Earth Interact . 2000 ; 4 : 1 – 85 .
    Search in Google ScholarBack to article
  67. Wilson J. B . A review of evidence on the control of shoot: root ratio, in relation to models . Ann. Bot . 1988 ; 61 ( 4 ): 433 – 449 .
    Search in Google ScholarBack to article
  68. Xu T. , White L. , Hui D. , Luo Y . Probabilistic inversion of a terrestrial ecosystem model: analysis of uncertainty in parameter estimation and model prediction . Global Biogeochem. Cycles . 2006 ; 20 ( 2 ): B2007 .
    Search in Google ScholarBack to article
  69. Yuan W. , Liang S. , Liu S. , Weng E. , Luo Y. , co-authors . Improving model parameter estimation using coupling relationships between vegetation production and ecosystem respiration . Ecol. Model . 2012a ; 240 : 29 – 40 .
    Search in Google ScholarBack to article
  70. Yuan W. , Liu S. , Liang S. , Tan Z. , Liu H. , co-authors . Estimations of evapotranspiration and water balance with uncertainty over the Yukon River Basin . Water Resour. Manag . 2012b ; 26 : 2147 – 2157 .
    Search in Google ScholarBack to article
  71. Yuan W. , Liu S. , Yu G. , Bonnefond J.-M. , Chen J. , co-authors . Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data . Remote Sens. Environ . 2010 ; 114 : 1416 – 1431 .
    Search in Google ScholarBack to article
  72. Yuan W. , Liu S. , Zhou G. , Zhou G. , Tieszen L. L. , co-authors . Deriving a light use efficiency model from eddy covariance flux data for predicting daily gross primary production across biomes . Agr. Forest Meteorol . 2007 ; 143 : 189 – 207 .
    Search in Google ScholarBack to article
  73. Zhou T. , Luo Y . Spatial patterns of ecosystem carbon residence time and NPP driven carbon uptake in the conterminous United States . Global Biogeochem. Cycles . 2008 ; 22 ( 3 ): GB3032 .
    Search in Google ScholarBack to article
DOI: https://doi.org/10.3402/tellusb.v67.28016 | Journal eISSN: 1600-0889
Journal RSS Feed
Language: English
Page range: 28016 - 28016
Submitted on: Mar 30, 2015
Accepted on: Nov 6, 2015
Published on: Jan 1, 2015
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services
Keywords:
carbon allocation,
resource availability,
leaf area index,
Bayesian inversion,
Integrated Biosphere Simulator

© 2015 Jiangzhou Xia, Yang Chen, Shunlin Liang, Dan Liu, Wenping Yuan, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 67 (2015): Issue 1
Previous article
Next article