林业科学Issue(9)：141-149,9.DOI:10.11707/j.1001-7488.20150918
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
Effects of Interpolation and Window Sizes in Phyllostachys edulis forest for Parameter Estimation on Calculation of CO2 Flux
摘要
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.关键词
缺失数据/插补方法/窗口大小/通量塔/毛竹林/CO2 通量Key words
missing data/gap-filling method/window size/flux tower/Phyllostachys edulis forest/CO2 flux分类
农业科技引用本文复制引用
徐小军,周国模,杜华强,施拥军,周宇峰..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[J].林业科学,2015,(9):141-149,9.基金项目
国家自然科学基金项目(31370637)、国家林业局948(2013－4－71)、浙江省教育厅项目(Y201432350)、浙江省基金杰出青年科学基金项目(LR14C160001)、浙江农林大学科研发展基金人才启动项目(2014FR025)、浙江省本科院校中青年学科带头人学术攀登项目(pd2013239)资助。 （31370637）
