『Abstract
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 0-30 min (10:00-10:30 am) ranged
from - 6.42 to 79.56 g N ha-1 d-1 with an
average value of 5.88 g N ha-1 d-1 and 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 Matern(eの頭に´)-type semivariogram
model and an effective range of 28.5 m. 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 26.8 g N d-1.
Keywords: N2O emissions; Tea field; Spatial variability; Dry season』
1. Introduction
2. Materials and methods
2.1. Site description
2.2. Digital elevation model and sampling positions
2.3. Gas measurement
2.4. Measurements of soil properties
2.5. Data analyses
3. Results and discussion
3.1. Exploratory data analyses
3.2. Spatial variability of nitrous oxide emissions and related
environmental factors
3.3. Spatial interpolations of nitrous oxide emissions by three
methods
3.4. Assessing the performance of three spatial interpolation
methods
3.5. Spatial distribution of nitrous oxide emissions over the
catchment
4. Conclusions
Acknowledgements
References