Ecological Research

, Volume 28, Issue 2, pp 271–282 | Cite as

Seasonal variation of vegetation productivity over an alpine meadow in the Qinghai–Tibet Plateau in China: modeling the interactions of vegetation productivity, phenology, and the soil freeze–thaw process

  • Haibo Wang
  • Mingguo Ma
  • Xufeng Wang
  • Wenping Yuan
  • Yi Song
  • Junlei Tan
  • Guanghui Huang
Original Article


Phenology controls the seasonal activities of vegetation on land surfaces and thus plays a fundamental role in regulating photosynthesis and other ecosystem processes. Therefore, accurately simulating phenology and soil processes is critical to ecosystem and climate modeling. In this study, we present an integrated ecosystem model of plant productivity, plant phenology, and the soil freeze–thaw process to (1) improve the quality of simulations of soil thermal regimes and (2) estimate the seasonal variability of plant phenology and its effects on plant productivity in high-altitude seasonal frozen regions. We tested different model configurations and parameterizations, including a refined soil stratification scheme that included unfrozen water in frozen soil, a remotely sensed diagnostic phenology scheme, and a modified prognostic phenology scheme, to describe the seasonal variation in vegetation. After refined soil layering resolution and the inclusion of unfrozen water in frozen soil, the results show that the model adequately reproduced the soil thermal regimes and their interactions observed at the site. The inclusion of unfrozen water in frozen soil was found to have a significant effect on soil moisture simulation during the spring but only a small effect on soil temperature simulation at this site. Moreover, the performance of improved phenology schemes was good. The phenology model accurately predicted the start and end of phenology, and its precise prediction of phenology variation allows an improved simulation of vegetation production.


Alpine meadow Qinghai–Tibet Plateau (QTP) Unfrozen water Primary production Phenology Freezing–thawing process 



This work is funded by the Chinese State Key Basic Research Project (grant number: 2009CB421305), the Knowledge Innovation Program of the Chinese Academy of Sciences (grant number: KZCX2-EW-312), and the national high-tech program (863) of China (grant number: 2009AA122104). We would like to thank Dr. David T. Price for his kind help in IBIS modeling, Xujun Han for his help of soil parameters survey, and Yanlin Zhang, Qiuan Zhu, Qingxi Guo for their useful discussions about this work. We also thank two anonymous reviewers and editors for helpful comments on earlier versions of this manuscript.


  1. Arora VK, Boer GJ (2005) A parameterization of leaf phenology for the terrestrial ecosystem component of climate models. Glob Change Biol 11:39–59CrossRefGoogle Scholar
  2. Beer C, Lucht W, Gerten D, Thonicke K, Schmullius C (2007) Effects of soil freezing and thawing on vegetation carbon density in Siberia: a modelling analysis with the Lund–Potsdam–Jena dynamic global vegetation model (LPJ-DGVM). Global Biogeochem Cycles 21:GB1012. doi: 10.1029/2006GB002760
  3. Cheng GD (1998) Glaciology and geocryology of China during the past 40 years: progress and prospects. J Glaciol Geocryol 20(3):213–226Google Scholar
  4. Cramer W, Bondeau A, Woodward FI, Prentice IC, Betts RA, Brovkin V, Cox PM, Fisher V, Foley JA, Friend AD, Kucharik C, Lomas MR, Ramankutty N, Sitch S, Smith B, White A, Young-Molling C (2001) Global response of terrestrial ecosystem structure and function to CO2 and climate change: results from six dynamic global vegetation models. Glob Change Biol 7:357–373CrossRefGoogle Scholar
  5. Foley JA, Prentice IC, Ramankutty N, Levis S, Pollard D, Sitch S, Haxeltine A (1996) An integrated biosphere model of land surface processes, terrestrial carbon balance, and vegetation dynamics. Global Biogeochem Cycles 10(4):603–628CrossRefGoogle Scholar
  6. Jolly WM, Nemani R, Running SW (2005) A generalized, bioclimatic index to predict foliar phenology in response to climate. Global Change Biol 11:619–632CrossRefGoogle Scholar
  7. Kim Y, Wang G (2005) Modeling seasonal vegetation variation and its validation against moderate resolution imaging spectroradiometer (MODIS) observations over North America. J Geophys Res 110:D04106. doi: 10.1029/2004JD005436
  8. Kucharik CJ, Foley JA, Delire C, Fisher VA, Coe MT, Gower ST, Lenters J, Molling C, Norman JM, Ramankutty N (2000) Testing the performance of a dynamic global ecosystem model: water balance, carbon balance, and vegetation structure. Global Biogeochem Cycles 14(3):795–825CrossRefGoogle Scholar
  9. Kucharik CJ, Barford CC, El Maayar M, Wofsy SC, Monson RK, Baldocchi DD (2006) A multiyear evaluation of a dynamic global vegetation model at three AmeriFlux forest sites: vegetation structure, phenology, soil temperature, and CO2 and H2O vapour exchange. Ecol Model 196:1–31CrossRefGoogle Scholar
  10. Letts MG, Roulet NT, Comer NT, Skarupa MR, Verseghy DL (2000) Parametrization of peatland hydraulic properties for the Canadian Land Surface Scheme. Atmos Ocean 38:141–160CrossRefGoogle Scholar
  11. Li X, Koike T (2003) Frozen soil parameterization in SiB2 and its validation with GAMETibet observations. Cold Reg Sci Technol 36:165–182CrossRefGoogle Scholar
  12. Li X, Li XW, Li ZY, Ma MG, Wang J, Xiao Q, Liu Q, Che T, Chen EX, Yan GJ, Hu ZY, Zhang LX, Chu RZ, Su PX, Liu QH, Liu SM, Wang JD, Niu Z, Chen Y, Jin R, Wang WZ, Ran YH, Xin XZ, Ren HZ (2009) Watershed allied telemetry experimental research. J Geophys Res 114(D22103). doi: 10.1029/2008JD011590
  13. Ling F, Zhang T (2004) A numerical model for surface energy balance and thermal regime of the active layer and permafrost containing unfrozen water. Cold Reg Sci Technol 38:1–15CrossRefGoogle Scholar
  14. Luo S, Lü S, Zhang Y (2009) Development and validation of the frozen soil parameterization scheme in Common Land Model. Cold Reg Sci Technol 55:130–140CrossRefGoogle Scholar
  15. Niu G-Y, Yang Z-L (2006) Effects of frozen soil on snowmelt runoff and soil water storage at a continental scale. J Hydrometeor 7(5):937–952CrossRefGoogle Scholar
  16. Peñuelas J, Rutishauser T, Filella I (2009) Phenology feedbacks on climate change. Science 324:887–888PubMedCrossRefGoogle Scholar
  17. Pollard D, Thompson SL (1995) Use of a land-surface-transfer scheme (LSX) in a global climate model: the response to doubling stomatal resistance. Global Planet Change 10:129–161CrossRefGoogle Scholar
  18. Reed BC, Brown JF, Vanderzee D, Loveland TR, Merchant JW, Ohlen DO (1994) Measuring phenological variability from satellite imagery. J Veg Sci 5:703–714CrossRefGoogle Scholar
  19. Richardson AD, Anderson RS, Arain MA, Barr AG, Bohrer G, Chen G, Chen JM, Ciais P, Davis KJ, Desai AR, Dietze MC, Dragoni D, Garrity SR, Gough CM, Grant R, Hollinger DY, Margolis HA, McCaughey H, Migliavacca M, Monson RK, Munger JW, Poulter B, Raczka BM, Ricciuto DM, Sahoo AK, Schaefer K, Tian H, Vargas R, Verbeeck H, Xiao J, Xue Y (2012) Terrestrial biosphere models need better representation of vegetation phenology: results from the North American Carbon Program Site Synthesis. Glob Change Biol 18:566–584. doi: 10.1111/j.1365-2486.2011.02562.x CrossRefGoogle Scholar
  20. Stöckli R, Rutishauser T, Dragoni D, O’Keefe J, Thornton PE, Jolly M, Lu L, Denning AS (2008) Remote sensing data assimilation for a prognostic phenology model. J Geophys Res 113:G04021. doi: 10.1029/2008JG000781 CrossRefGoogle Scholar
  21. Thompson SL, Pollard D (1995) A global climate model (GENESIS) with a land-surface transfer scheme (LSX), part I: present climate simulation. J Climate 8:732–761CrossRefGoogle Scholar
  22. van Wijk MT, Williams M, Laundre JA, Shaver GR (2003) Interannual variability of plant phenology in tussock tundra: modelling interactions of plant productivity, plant phenology, snowmelt and soil thaw. Glob Change Biol 9(5):743–758CrossRefGoogle Scholar
  23. Wang G, Li Y, Wang Y (2008) Synergistic effect of vegetation and air temperature changes on soil water content in alpine frost meadow soil in the permafrost region of Qinghai–Tibet. Hydrol Process 22:3310–3320CrossRefGoogle Scholar
  24. Wang GX, Liu LA, Liu GS, Hu HC, Li TB (2010) Impacts of grassland vegetation cover on the active-layer thermal regime, northeast Qinghai–Tibet Plateau, China. Permafr Periglac Process 21(4):335–344CrossRefGoogle Scholar
  25. Wang XF, Ma MG, Huang GH, Veroustraete F, Zhang ZH, Song Y, Tan JL (2011) Vegetation primary production estimation at maize and alpine meadow over the Heihe River Basin, China. Int J Appl Earth Obs Geoinf. doi: 10.1016/j.jag.2011.09.009
  26. Wania R, Ross I, Prentice IC (2009) Integrating peatlands and permafrost into a dynamic global vegetation model: 1. Evaluation and sensitivity of physical land surface processes. Global Biogeochem Cycles 23:GB3014. doi: 10.1029/2008GB003412
  27. Wolf A, Callaghan TV, Larson K (2008) Future changes in vegetation and ecosystem function of the Barents Region. Clim Change 87:51–73CrossRefGoogle Scholar
  28. Yang K, Koike T, Ye B, Bastidas L (2005) Inverse analysis of the role of soil vertical heterogeneity in controlling surface soil state and energy partition. J Geophys Res 110:D08101. doi: 10.1029/2004JD005500 CrossRefGoogle Scholar
  29. Yi S, McGuire AD, Harden J, Kasischke E, Manies K, Hinzman L, Liljedahl A, Randerson J, Liu H, Romanovsky V, Marchenko S, Kim Y (2009) Interactions between soil thermal and hydrological dynamics in the response of Alaska ecosystems to fire disturbance. J Geophys Res Biogeosci 114:G02015. doi: 10.1029/2008JG000841 CrossRefGoogle Scholar
  30. Zhang Y, Wang S, Barr AG, Black TA (2008a) Impact of snow cover on soil temperature and its simulation in a boreal aspen forest. Cold Reg Sci Technol. doi: 10.1016/j.coldregions.2007.07.001 Google Scholar
  31. Zhang Y, Carey SK, Quinton WL (2008b) Evaluation of the algorithms and parameterizations for ground thawing and freezing simulation in permafrost regions. J Geophys Res 113:D17116. doi: 10.1029/2007JD009343 CrossRefGoogle Scholar
  32. Zhang ZH, Wang WZ, Ma MG, Wu YR, Xu ZW (2010) The processing methods of eddy covariance flux data and products in “WATER” test. Remote Sens Technol Appl 25(6):788–796 (Chinese with English abstract)Google Scholar
  33. Zhuang Q, Romanovsky VE, McGuire AD (2001) Incorporation of a permafrost model into a large-scale ecosystem model: evaluation of temporal and spatial scaling issues in simulating soil thermal dynamics. J Geophys Res 106(D24):33,649–33,670Google Scholar

Copyright information

© The Ecological Society of Japan 2012

Authors and Affiliations

  • Haibo Wang
    • 1
    • 2
  • Mingguo Ma
    • 1
  • Xufeng Wang
    • 1
    • 2
  • Wenping Yuan
    • 3
  • Yi Song
    • 4
  • Junlei Tan
    • 1
  • Guanghui Huang
    • 1
  1. 1.Cold and Arid Regions Environmental and Engineering Research Institute (CAREERI)Chinese Academy of SciencesLanzhouChina
  2. 2.Graduate University of Chinese Academy of SciencesBeijingChina
  3. 3.College of Global Change and Earth System ScienceBeijing Normal UniversityBeijingChina
  4. 4.Institute of Earth EnvironmentChinese Academy of SciencesXi’anChina

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