缺失数据插补方法及其参数估计窗口大小对毛竹林CO2通量估算的影响

doi:10.11707/j.1001-7488.20150918

Abstract

Abstract:

[Objective] Due to high ratio of missing CO₂ flux data, a suitable interpolation method is necessary to collect continuous and reliable CO₂ flux data. The objective of this study is to analyze effect of interpolation (nighttime data-based method (NB) and daytime data-based method (DB)) with different window sizes for fitting parameters on CO₂ flux data estimation, which provides a basis for selecting suitable interpolation method. [Method] Based on the data of net ecosystem exchange (NEE), temperature and photosynthetically active radiation obtained from the carbon flux tower for moso bamboo forest ecosystem in 2011, interpolation (NB and DB) with different time window sizes for fitting parameters were used to estimate missing data through interpolation. Then, the estimated data from interpolation was compared with the observed data. [Results] Time window size for fitting parameter has an effect on the fluctuation of CO₂ flux. Fluctuation of CO₂ flux decreases as time window size increases. If the time window size is too large, the result can not reflect the local specific variation in CO₂ flux, and if the time window size is too small, it can get abnormal CO₂ flux. The optimal time window size is closely related to the amount of missing data. As to this case study, for NB method, the 15-day moving window size and 90-day window size for fitting parameters are suitable to interpolate ecosystem respiration (Re). The 2-day moving window size and 4-day window size for fitting parameters are suitable to interpolate gross primary production (GPP). For DB method, the 2-day moving window size and 60-day window size for fitting parameters are optimal. Annual GPP and Re from NB method are 13.8% and 26.8% greater than those from DB method, respectively. While NEE from NB method is 32.2% lower than that from DB method. Daytime NEE from NB and DB methods are very similar, but there is great difference in Re between NB and DB methods. [Conclusion] The proportion of missing data has important effect on determining time window sizes for fitting parameters. Taken the proportion of missing data and the feature of seasonal variation in CO₂ flux into account, selecting suitable interpolation method and window size for fitting parameters is helpful to increase the accuracy of CO₂ flux estimation.

Key words: missing data, gap-filling method, window size, flux tower, Phyllostachys edulis forest, CO₂ flux

CLC Number:

S718

Xu Xiaojun, Zhou Guomo, Du Huaqiang, Shi Yongjun, Zhou Yufeng. Effects of Interpolation and Window Sizes in Phyllostachys edulis forest for Parameter Estimation on Calculation of CO₂Flux[J]. Scientia Silvae Sinicae, 2015, 51(9): 141-149.

References

黄昆,王绍强,王辉民,等. 2013.中亚热带人工针叶林生态系统碳通量拆分差异分析. 生态学报, 33(17):5252-5265.
(Huang K, Wang S Q, Wang H M, et al. 2013. An analysis of carbon flux partition differences of a mid-subtropical planted coniferous forest in southeastern China. Acta Ecologica Sinica, 33(17):
5252-5265.[in chinese])
刘敏, 何洪林, 于贵瑞, 等. 2010. 数据处理方法不确定性对 CO₂ 通量组分估算的影响. 应用生态学报, 21(9):2389-2396.
(Liu M, He H L, Yu G R, et al. 2010. Impacts of uncertainty in data processing on estimation of CO₂ flux components. Chinese Journal of Applied Ecology, 21(9):2389-2396.[in chinese])
孙成, 江洪, 周国模, 等. 2013. 我国亚热带毛竹林CO₂通量的变异特征. 应用生态学报,24(10):2717-2724.
(Sun C, Jiang H, Zhou G M, et al. 2013. Variation characteristics of CO₂ flux in Phyllostachys edulis forest ecosystem in subtropical region of China. Chinese Journal of Applied Ecology, 24(10):
2717-2724.[in chinese])
谢莉,陈三雄,彭庭国,等. 2012. 浙江安吉主要植被类型土壤水库库容特性研究.亚热带水土保持,24(3):14-18.
(Xie L, Chen S X, Peng T G, et al. 2012. Study on the properties of soil reservoir in the main vegetation types of Anji county of Zhejiang Province. Subtropical Soil and Water Conservation, 24(3):14-18.[in chinese])
于贵瑞, 伏玉玲, 孙晓敏, 等. 2006a.中国陆地生态系统通量观测研究网络 (ChinaFLUX) 的研究进展及其发展思路. 中国科学: D 辑, 36(A01): 1-21.
(Yu G R, Fu Y L, Sun X M, et al. 2006a. Progresses and prospects of Chinese terrestrial ecosystem flux observation and research network (ChinaFLUX). Science in China Ser:D Earth Sciences, 36(A01): 1-21.[in chinese])
于贵瑞, 孙晓敏. 2006b. 陆地生态系统通量观测的原理与方法. 北京:高等教育出版社.
(Yu G R, Sun X M, 2006b. Principles of flux measurement in terrestrial ecosystems. Beijing: Higher Education Press.[in chinese])
Beer C, Reichstein M, Tomelleri E, et al. 2010. Terrestrial gross carbon dioxide uptake: global distribution and covariation with climate. Science, 329(5993): 834-838.
Desai A R, Richardson A D, Moffat A M, et al. 2008. Cross-site evaluation of eddy covariance GPP and RE decomposition techniques. Agricultural and Forest Meteorology, 148(6): 821-838.
Falge E, Baldocchi D, Olson R, et al. 2001. Gap filling strategies for defensible annual sums of net ecosystem exchange. Agricultural and Forest Meteorology, 107(1): 43-69.
Hollinger D Y, Aber J, Dail B, et al. 2004. Spatial and temporal variability in forest-atmosphere CO₂ exchange. Global Change Biology, 10(10): 1689-1706.
Janssens I A, Freibauer A, Ciais P, et al. 2003. Europe’s terrestrial biosphere absorbs 7% to 12% of European anthropogenic CO₂ emissions. Science, 300(5625): 1538-1542.
Lasslop G, Reichstein M, Papale D, et al. 2010. Separation of net ecosystem exchange into assimilation and respiration using a light response curve approach: critical issues and global evaluation. Global Change Biology, 16(1):187-208.
Li Z Q, Yu G R, Wen X F, et al. 2005. Energy balance closure at ChinaFLUX sites. Science in China Ser. D Earth Sciences, 48(Supp II): 51-62.
Lloyd J, Taylor J A. 1994. On the temperature dependence of soil respiration. Functional Ecolgy, 8(3):315-323.
Moffat A M, Papale D, Reichstein M, et al. 2007. Comprehensive comparison of gap-filling techniques for eddy covariance net carbon fluxes. Agricultural and Forest Meteorology, 147(3): 209-232.
Noormets A, Chen J, Crow T R. 2007. Age-dependent changes in ecosystem carbon fluxes in managed forests in northern Wisconsin, USA. Ecosystems, 10(2): 187-203.
Reichstein M, Falge E, Baldocchi D, et al. 2005. On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm. Global Change Biology, 11(9): 1424-1439.
Richardson A D, Braswell B H, Hollinger D Y, et al. 2006. Comparing simple respiration models for eddy flux and dynamic chamber data. Agricultural and Forest Meteorology, 141(2): 219-234.
Running S W. 2008. Ecosystem disturbance, carbon, and climate. Science, 321(5889): 652-653.
Zhao M, Running S W. 2011. Response to comments on “Drought-induced reduction in global terrestrial net primary production from 2000 through 2009”. Science, 333(6046): 1093-1093.

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Effects of Interpolation and Window Sizes in Phyllostachys edulis forest for Parameter Estimation on Calculation of CO₂Flux

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Effects of Interpolation and Window Sizes in Phyllostachys edulis forest for Parameter Estimation on Calculation of CO2 Flux

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Effects of Interpolation and Window Sizes in Phyllostachys edulis forest for Parameter Estimation on Calculation of CO₂Flux