Site-level model–data synthesis of terrestrial carbon fluxes in the CarboEastAsia eddy-covariance observation network: toward future modeling efforts
详细信息 查看全文
- 作者：Kazuhito Ichii (1)
Masayuki Kondo (1)
Young-Hee Lee (2)
Shao-Qiang Wang (3)
Joon Kim (4)
Masahito Ueyama (5)
Hee-Jeong Lim (2)
Hao Shi (3)
Takashi Suzuki (1)
Akihiko Ito (6)
Hyojung Kwon (4)
Weimin Ju (7)
Mei Huang (3)
Takahiro Sasai (8)
Jun Asanuma (9)
Shijie Han (10)
Takashi Hirano (11)
Ryuichi Hirata (11)
Tomomichi Kato (12)
Sheng-Gong Li (3)
Ying-Nian Li (13)
Takahisa Maeda (14)
Akira Miyata (15)
Yojiro Matsuura (16)
Shohei Murayama (14)
Yuichiro Nakai (16)
Takeshi Ohta (17)
Taku M. Saitoh (18)
Nobuko Saigusa (6)
Kentaro Takagi (19)
Yan-Hong Tang (6)
Hui-Min Wang (3)
Gui-Rui Yu (3)
Yi-Ping Zhang (20)
Feng-Hua Zhao (3) - 关键词：Carbon fluxes ; East Asia ; Eddy covariance measurement ; Model comparison ; Terrestrial biosphere model
- 刊名：Journal of Forest Research
- 出版年：2013
- 出版时间：February 2013
- 年：2013
- 卷：18
- 期：1
- 页码：13-20
- 全文大小：503KB
- 参考文献：1. Aber JD, Ollinger SV, Driscoll CT (1997) Modeling nitrogen saturation in forest ecosystems in response to land use and atmospheric deposition. Ecol Model 101:61-8 CrossRef
2. Adams B, White A, Lenton TM (2004) An analysis of some diverse approaches to modeling terrestrial net primary productivity. Ecol Model 177:353-91 CrossRef
3. Cox PM (2001) Description of the “TRIFFID-dynamic global vegetation model. Hadley Centre Technical Note 24, Met Office Hadley Centre Technical Notes
4. Cramer W, Kicklighter DW, Bondeau A, Moore B III, Churkina G, Nemry B, Ruimy A, Schloss AL, The participants of the Potsdam NPP model intercomparison (1999) Comparing global models of terrestrial net primary productivity (NPP): overview and key results. Glob Change Biol 5:1-5 CrossRef
5. Cramer W, Bondeau A, Woodward FI, Prentice C, Betts RA, Brovkin V, Cox PM, Fisher V, Foley JA, Friend AD, Kucharik C, Lomas MR, Ramankutty N, Sitch S, Smith B, White A, Yound-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 7:357-73 CrossRef
6. FAO/IIASA/ISRIC/ISSCAS/JRC (2012) Harmonized World Soil Database (version 1.2). FAO/IIASA, Rome/Austria
7. Field CB, Randerson JT, Malmstr?m CM (1995) Global net primary production: combining ecology and remote sensing. Remote Sens Environ 51:74-8 CrossRef
8. Gerten D, Schaphoff S, Haberlandt U, Lucht W, Sitch S (2004) Terrestrial vegetation and water balance: hydrological evaluation of a dynamic global vegetation model. J Hydrol 286:249-70 CrossRef
9. Hong J, Kim J (2011) Impact of the Asian monsoon climate on ecosystem carbon and water exchanges: a wavelet analysis and its ecosystem modeling implications. v Biol 17:1900-916 CrossRef
10. Huete A, Didan K, Miura T, Rodriguez E (2002) Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sens Environ 83:195-13 CrossRef
11. Ichii K, Hashimoto H, White MA, Potter CS, Hutyra LR, Huete AR, Myneni RB, Nemani RR (2007) Constraining rooting depths in tropical rainforests using satellite data and ecosystem modeling for accurate simulation of GPP seasonality. Glob Change Biol 13:67-7 CrossRef
12. Ichii K, Wang W, Hashimoto H, Yang F, Votava P, Michaelis AR, Nemani RR (2009) Refinement of rooting depths using satellite-based evapotranspiration seasonality for ecosystem modeling in California. Agric For Meteorol 149:1907-918 CrossRef
13. Ichii K, Suzuki T, Kato T, Ito A, Hajima T, Ueyama M, Sasai T, Hirata R, Saigusa N, Ohtani Y, Takagi K (2010) Multi-model analysis of terrestrial carbon cycles in Japan: limitations and implications of model calibration using eddy flux observations. Biogeosciences 7:2061-080 CrossRef
14. Ito A (2008) The regional carbon budget of East Asia simulated with a terrestrial ecosystem model and validated using AsiaFlux data. Agric For Meteorol 148:738-47 CrossRef
15. Ito A (2010) Evaluation of defoliation impacts of tropical cyclones on the forest carbon budget using flux data and a process-based model. J Geophys Res 115:G04013. doi:10.1029/2010JG001314 CrossRef
16. Jorgensen SE, Faith BD, Bastianoni S, Marques JC, Muller F, Nielsen SN, Patten BC, Tiezzi E, Ulanowicz RE (2007) A new ecology: systems perspective. Elsevier, Oxford
17. Ju W, Wang S, Yu G, Zhou Y, Wang H (2010) Modeling the impact of drought on canopy carbon and water fluxes for a subtropical evergreen coniferous plantation in southern China through parameter optimization using an ensemble Kalman filter. Biogeosciences 7:845-57 CrossRef
18. Jung M, Le Maire G, Zaehle S, Luyssaert S, Vetter M, Churkina G, Ciais P, Viovy N, Reichstein M (2007) Assessing the ability of three land ecosystem models to simulate gross carbon uptake of forests from boreal to Mediterranean climate in Europe. Biogeosciences 4:647-56 CrossRef
19. Kalnay E, Kanamitsu M, Kistler R, Collins W, Daeven D, Gandin L, Iredell M, Saha S, White G, Woollen J, Zhu Y, Leetmaa A, Reynolds R, Chelliah M, Ebisuzaki W, Higgins W, Janowiak J, Mo KC, Ropelewski C, Wang J, Jenne R, Joseph D (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77:437-71 CrossRef
20. Kwon H, Kim J, Hong J, Lim JH (2010) Influence of the Asian monsoon on net ecosystem carbon exchange in two major ecosystems in Korea. Biogeosciences 7:1493-504 CrossRef
21. Li C, Mosier A, Wassmann R, Cai Z, Zheng X, Huang Y, Tsuruta H, Boonjawat J, Lantin R (2004) Modeling greenhouse gas emissions from rice-based production systems: sensitivity and upscaling. Glob Biogeochem Cycles 18:GB1043. doi:10.1029/2003GB002045
22. Liang N, Hirano T, Zheng ZM, Tang J, Fujinuma Y (2010) Soil CO2 efflux of a larch forest in northern Japan. Biogeosciences 7:3447-457 CrossRef
23. Mahecha MD, Reichstein M, Jung M, Seneviratne SI, Zaehle S, Beer C, Mraakhekke MC, Carvalhais N, Lange H, Maire GL, Moors E (2010) Comparing observations and process-based simulations of biosphere-atmosphere exchanges on multiple timescales. J Geophys Res 115:G02003. doi:10.1029/2009JG001016 CrossRef
24. Mitchell TD, Jones PD (2005) An improved method of constructing a database of monthly climate observations and associated high-resolution grids. Int J Climatol 25:693-12 CrossRef
25. Mu Q, Zhao M, Running SW, Liu M, Tian H (2008) Contribution of increasing CO2 and climate change to the carbon cycle in China’s ecosystems. J Geophys Res 113:G010118. doi:10.1029/2006JG000316
26. Myneni RB, Hoffman S, Knyazikhim Y, Privette JL, Glassy J, Tian Y, Wang Y, Song X, Zhang Y, Smith Y, Lotsch A, Friedl M, Morisette JT, Votava P, Nemani RR, Running SW (2002) Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data. Remote Sens Environ 83:214-31 CrossRef
27. NOAA National Climatic Data Center (2010) State of the climate: global analysis for annual 2010. http://www.ncdc.noaa.gov/sotc/global/2010/13
28. Oikawa T, Ito A (2001) Modeling carbon dynamics of terrestrial ecosystems in monsoon Asia. In: Matsuno T, Kida H (eds) Present and future modeling global environmental change: toward integrated modeling. TERRAPUB, Tokyo, pp 207-19
29. Oleson KW, Niu GY, Yang ZL, Lawrence DM, Thornton PE, Lawrence PJ, St?ckli R, Dickinson RE, Bonan GB, Levis S, Dai A, Qian T (2008) Improvements to the community land model and their impact on the hydrological cycle. J Geophys Res 113:G01021. doi:10.1029/2007JG000563 CrossRef
30. Patra PK, Ishizawa M, Maksyutov S, Nakazawa T, Inoue G (2005) Role of biomass burning and climate anomalies for land-atmosphere carbon fluxes based on inverse modeling of atmospheric CO2. Glob Biogeochem Cycles 19:GB3005. doi:10.1029/2004GB002258
31. Piao SL, Fang JY, Ciais P, Peylin P, Huang Y, Sitch S, Wang T (2009) The carbon balance of terrestrial ecosystems in China. Nature 458:1009-013 CrossRef
32. Piao SL, Ciais P, Lomas M, Beer C, Liu HY, Fang JY, Friedlingstein F, Huang Y, Muraoka H, Son Y, Woodward I (2011) Contribution of climate change and rising CO2 to terrestrial carbon balance in East Asia: a multimodel analysis. Glob Planet Change 75:133-42 CrossRef
33. Richardson AD, Williams M, Hollinger DY, Moore DJP, Dail DB, Davidson EA, Scott NA, Evans RS, Hughes H, Lee JT, Rodrigues C, Savage K (2010) Estimating parameters of a forest ecosystem C model with measurement of stocks and fluxes as joint constraints. Oecologia 164:25-0 CrossRef
34. Ruddel BL, Kumar P (2009) Ecohydrologic process networks: 1. Identification. Water Resour Res 45:W03419. doi:10.1029/2008WR007229 CrossRef
35. Saigusa N, Ichii K, Murakami H, Hirata R, Asanuma J, Den H, Han S-J, Ide R, Li SG, Ohta T, Sasai T, Wang SQ, Yu GR (2010) Impact of meteorological anomalies in the 2003 summer on gross primary productivity in East Asia. Biogeosciences 7:641-55 CrossRef
36. Saigusa N, Li SG, Kwon H, Takagi K, Zhang LM, Ide R, Ueyama M, Asanuma J, Choi YJ, Chun JH, Han SJ, Hirano T, Hirata R, Kang M, Kato T, Kim J, Li YN, Maeda T, Miyata A, Mizoguchi Y, Murayama S, Nakai Y, Ohta T, Saitoh TM, Wang HM, Yu GR, Zhang YP, Zhao FH (2012) CO2 flux measurement and the dataset in CarboEastAsia. J For Res (submitted)
37. Sasai T, Ichii K, Yamaguchi Y, Nemani RR (2005) Simulating terrestrial carbon fluxes using the new biosphere model BEAMS: biosphere model integrating eco-physiological and mechanistic approaches using satellite data. J Geophys Res 110:G02014. doi:10.1029/2005JG000045 CrossRef
38. Sasai T, Saigusa N, Nasahara NK, Ito A, Hashimoto H, Nemani R, Hirata R, Ichii K, Takagi K, Saitoh TM, Ohta T, Murakami K, Yamaguchi Y, Oikawa T (2011) Satellite-driven estimation of terrestrial carbon flux over Far East Asia with 1-km grid resolution. Remote Sens Environ 115:1758-771 CrossRef
39. Schwalm, CR, Williams CA, Schaefer K, Anderson R, Arain MA, Baker I, Barr A, Black TA, Chen G, Chen JM, Ciais P, Davis KJ, Desai A, Dietze M, Dragoni D, Fischer ML, Lawrence B. Flanagan LB, Grant R, Gu L, Hollinger D, Izaurralde RC, Kucharik C, Lafleur P, Law BE, Li L, Li Z, Liu S, Lokupitiya E, Luo Y, Ma S, Margolis H, Matamala R, McCaughey H, Monson RK, Oechel WC, Peng C, Poulter B, Price DT, Riciutto DM, Riley W, Sahoo AK, Sprintsin M, Sun J, Tian H, Tonitto C, Verbeeck H, Verma SB (2010) A model–data intercomparison of CO2 exchange across North America: results from the North American Carbon Program site synthesis. J Geophys Res 115:G00H05. doi:10.1029/2009JG001229
40. Sitch S, Smith B, Prentice IC, Arneth A, Bondeau A, Cramer W, Kaplan J, Levis S, Lucht W, Sykes M, Thonicke K, Venevsky S (2003) Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic vegetation model. Glob Change Biol 9:161-85 CrossRef
41. Tamai K (2010) Effects of environmental factors and soil properties on topographic variations of soil respiration. Biogeosciences 7:1133-142 CrossRef
42. Taylor KE (2001) Summarizing multiple aspects of model performance in single diagram. J Geophys Res 106:7183-192 CrossRef
43. Thornton PE, Law BE, Gholz HL, Clark KL, Falge E, Ellsworth DS, Goldstein AH, Monson RK, Hallinger D, Falk M, Chen J, Sparks JP (2002) Modeling and measuring the effects of disturbance history and climate on carbon and water budgets in evergreen needleleaf forests. Agric For Meteorol 113:185-22 CrossRef
44. Tian H, Melillo JM, Kicklighter DW, Pan S, Liu J, McGuire AD, Moore B III (2003) Regional carbon dynamics in monsoon Asia and its implications for the global carbon cycle. Glob Planet Change 37:201-17
45. Ueyama M, Ichii K, Hirata R, Takagi K, Asanuma J, Machimura T, Nakai Y, Saigusa N, Takahashi Y, Hirano T (2010) Simulating carbon and water cycles of larch forests in East Asia by the Biome-BGC model with AsiaFlux data. Biogeosciences 7:959-77 CrossRef
46. Ueyama M, Kai A, Ichii K, Hamotani K, Kosugi Y, Monji N (2011) The sensitivity of carbon sequestration to harvesting and climate conditions in a temperate cypress forest. Ecol Model 222:3216-225 CrossRef
47. Verbeeck H, Peylin P, Bacour C, Bonal D, Steppe K, Ciais P (2011) Seasonal patterns of CO2 fluxes in Amazon forests: fusion of eddy covariance data and the ORCHIDEE model. J Geophys Res 116:G02018. doi:10.1029/2010JG001544 CrossRef
48. Zhang Y, Rossow WB, Lacis AA, Oinas V, Mishchenko MI (2004) Calculation of radiative fluxes from the surface to top of atmosphere based on ISCCP and other global data sets: refinements of the radiative transfer model and the input data. J Geophys Res 109:D19105. doi:10.1029/2003JD004457 CrossRef
49. Zhou B, Gu L, Ding Y, Shao L, We Z, Yang X, Li C, Li Z, Wang X, Cao Y, Zeng B, Yu M, Wang S, Sun H, Duan A, An Y, Wang X, Kong W (2011) The great 2008 Chinese ice storm: its socioeconomic-ecological impact and sustainability lessons learned. Bull Am Meteorol Soc 92:47-0 CrossRef - 作者单位：Kazuhito Ichii (1)
Masayuki Kondo (1)
Young-Hee Lee (2)
Shao-Qiang Wang (3)
Joon Kim (4)
Masahito Ueyama (5)
Hee-Jeong Lim (2)
Hao Shi (3)
Takashi Suzuki (1)
Akihiko Ito (6)
Hyojung Kwon (4)
Weimin Ju (7)
Mei Huang (3)
Takahiro Sasai (8)
Jun Asanuma (9)
Shijie Han (10)
Takashi Hirano (11)
Ryuichi Hirata (11)
Tomomichi Kato (12)
Sheng-Gong Li (3)
Ying-Nian Li (13)
Takahisa Maeda (14)
Akira Miyata (15)
Yojiro Matsuura (16)
Shohei Murayama (14)
Yuichiro Nakai (16)
Takeshi Ohta (17)
Taku M. Saitoh (18)
Nobuko Saigusa (6)
Kentaro Takagi (19)
Yan-Hong Tang (6)
Hui-Min Wang (3)
Gui-Rui Yu (3)
Yi-Ping Zhang (20)
Feng-Hua Zhao (3)
1. Faculty of Symbiotic Systems Science, Fukushima University, 1 Kanayagawa, Fukushima, 960-1296, Japan
2. Department of Astronomy and Atmospheric Sciences, Kyungpook National University, Daegu, Korea
3. Key Lab of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Science, Beijing, China
4. Department of Landscape Architecture and Rural Systems Engineering, Seoul National University, Seoul, Korea
5. Graduate School of Life and Environmental Sciences, Osaka Prefecture University, Sakai, Japan
6. National Institute for Environmental Studies, Tsukuba, Japan
7. Nanjing University, Nanjing, China
8. Graduate School of Environmental Studies, Nagoya University, Nagoya, Japan
9. Graduate School of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Japan
10. Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, China
11. Graduate School of Agriculture, Hokkaido University, Sapporo, Japan
12. Laboratoire des Sciences du Climat et de l’Environnement, CEA-CNRS-UVSQ, 91191, Gif sur Yvette, France
13. Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, Qinghai, China
14. National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan
15. National Institute for Agro-Environmental Sciences, Tsukuba, Japan
16. Forestry and Forest Products Research Institute, Tsukuba, Japan
17. Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya, Japan
18. River Basin Research Center, Gifu University, Gifu, Japan
19. Field Science Center for Northern Biosphere, Hokkaido University, Toikanbetsu, Japan
20. Xishuangbanna Tropical Botanical Garden, Chinese Academy of Science, Yunnan, China - ISSN：1610-7403
文摘
Based on the model–data comparison at the eddy-covariance observation sites from CarboEastAsia datasets, we report the current status of the terrestrial carbon cycle modeling in monsoon Asia. In order to assess the modeling performance and discuss future requirements for both modeling and observation efforts in Asia, we ran eight terrestrial biosphere models at 24 sites from 1901 to 2010. By analyzing the modeled carbon fluxes against the CarboEastAsia datasets, the strengths and weaknesses of terrestrial biosphere modeling over Asia were evaluated. In terms of pattern and magnitude, the carbon fluxes (i.e., gross primary productivity, ecosystem respiration, and net ecosystem exchange) at the temperate and boreal forest sites were simulated best, whereas the simulation results from the tropical forest, cropland, and disturbed sites were poor. The multi-model ensemble mean values showed lower root mean square errors and higher correlations, suggesting that composition of multiple terrestrial biosphere models would be preferable for terrestrial carbon budget assessments in Asia. These results indicate that the current model-based estimation of terrestrial carbon budget has large uncertainties, and future research should further refine the models to permit re-evaluation of the terrestrial carbon budget.