Spatial variability and distribution of N2O emissions from a tea field during the dry season in subtropical central China
Spatial variability and distribution of N2O emissions from a tea field during the dry season in subtropical central China
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中国亚热带中部地区旱季茶田N2O排放空间变异及分布
DOI：
10.1016/j.geoderma.2012.10.008
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发表时间：
2013-02
期刊：
影响因子：
6.1
通讯作者：
Wu, Jinshui
中科院分区：
文献类型：
--
作者：
Xiao, Runlin;Li, Yuyuan;Tong, Chengli;Wu, Jinshui
近年来，中国中部亚热带地区茶叶产业的蓬勃发展和集约化，以及大量的化肥投入，使我们能够观察到茶园的一氧化二氮（N2 O）排放，以研究其排放特征和减缓潜力。在这项研究中，我们研究了2010年10月30日观察到的N2 O排放量的空间变异性，使用147个静态的迷你室网格几乎定期在4.8公顷施肥茶园。0- 30 min（10：00-10：30 am）的N2 O通量变化范围为-6.42 ~79.56gNha −1d− 1，平均值为5.88gNha− 1d − 1，呈正偏态分布，接近对数正态分布。地统计学分析表明，归一化对数转换的N2 O排放量表现出较强的空间自相关性，其特征在于由Matérn型半变异函数模型和有效范围为28.5米。在旱季，只有海拔高度与N2 O排放量显著相关（r=-0.42，P<0.001）;其他土壤性质与N2 O排放量均无显著相关（r<0.10，P>0.05）。采用三种空间插值方法（普通克里格、回归克里格和协同克里格）估计研究区N2 O排放量的空间分布。回归克里格与海拔作为一个辅助预测和cokriging与逆的归一化海拔和归一化土壤有机碳作为两个协变量略优于cokriging与个人归一化的环境因素作为协变量和普通克里格。然而，所有方法预测的茶叶田N2 O排放总量相似，范围从25.6到26.8gNd−1。
The recent boom and intensification of the tea industry in subtropical central China, with its large fertiliser inputs, lead us to observe nitrous oxide (N2O) emissions from tea fields to investigate the emission characteristics and mitigation potential. In this study, we examined the spatial variability of N2O emissions observed on 30 October 2010 using 147 static mini chambers gridded almost regularly in a 4.8-ha fertilised tea field. The N2O fluxes for 0–30min (10:00–10:30am) ranged from −6.42 to 79.56gNha−1d−1with an average value of 5.88gNha−1d−1and were positively skewed, thus approximating a log-normal distribution. The geostatistical analysis indicated that the normalised log-transformed N2O emissions exhibited strong spatial autocorrelation, characterised by a Matérn-type semivariogram model and an effective range of 28.5m. As observed during the dry season, only the elevation was found to be significantly correlated with N2O emissions (r=−0.42, P<0.001); none of the other measured soil properties had a significant relationship with N2O emissions (r<0.10, P>0.05). Three spatial interpolation methods (ordinary kriging, regression kriging and cokriging) were applied to estimate the spatial distribution of N2O emissions over the study area. Regression kriging with the elevation as an auxiliary predictor and cokriging with the inverse of the normalised elevation and the normalised soil organic carbon as two co-variables slightly outperformed both cokriging with individual normalised environmental factors as the co-variable and ordinary kriging. However, all methods predicted similar total amounts of N2O emissions in the tea field, ranging from 25.6 to 26.8gNd−1.
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影响因子：
2.5
作者：
J. Wisnowski
通讯作者：
J. Wisnowski
DOI：
--
发表时间：
2000
期刊：
--
影响因子：
--
作者：
T. Musgrave;W. Musgrave
通讯作者：
T. Musgrave;W. Musgrave
影响因子：
2
作者：
Shin-ichi Tokuda;M. Hayatsu
通讯作者：
Shin-ichi Tokuda;M. Hayatsu
DOI：
10.2136/sssaj1983.03615995004700020001x
发表时间：
1983-03
影响因子：
2.9
作者：
M. Vauclin;S. R. Vieira;G. Vachaud;D. R. Nielsen
通讯作者：
M. Vauclin;S. R. Vieira;G. Vachaud;D. R. Nielsen
影响因子：
6.1
作者：
McBratney, AB;Odeh, IOA;Shatar, TM
通讯作者：
Shatar, TM