scholarly journals Wet-season spatial variability of N<sub>2</sub>O emissions from a tea field in subtropical central China

2015 ◽  
Vol 12 (2) ◽  
pp. 1475-1508
Author(s):  
X. Fu ◽  
X. Liu ◽  
Y. Li ◽  
J. Shen ◽  
Y. Wang ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Ordinary Kriging ◽  
Spatial Interpolation ◽  
Central China ◽  
N2o Emissions ◽  
Regression Kriging ◽  
Wet Season ◽  
Interpolation Methods ◽  
N2o Fluxes ◽  
Tea Field

Abstract. Tea fields emit large amounts of nitrous oxide (N2O) to the atmosphere. Obtaining accurate estimations of N2O emissions from tea-planted soils is challenging due to strong spatial variability. We examined the spatial variability of N2O emissions from a red-soil tea field in Hunan province, China, on 22 April 2012 (in a wet season) using 147 static mini chambers approximately regular gridded in a 4.0 ha tea field. The N2O fluxes for a 30 min snapshot (10–10.30 a.m.) ranged from −1.73 to 1659.11 g N ha−1 d−1 and were positively skewed with an average flux of 102.24 g N ha−1 d−1. The N2O flux data were transformed to a normal distribution by using a logit function. The geostatistical analyses of our data indicated that the logit-transformed N2O fluxes (FLUX30t) exhibited strong spatial autocorrelation, which was characterized by an exponential semivariogram model with an effective range of 25.2 m. As observed in the wet season, the logit-transformed soil ammonium-N (NH4Nt), soil nitrate-N (NO3Nt), soil organic carbon (SOCt), total soil nitrogen (TSNt) were all found to be significantly correlated with FLUX30t (r=0.57–0.71, p<0.001). Three spatial interpolation methods (ordinary kriging, regression kriging and cokriging) were applied to estimate the spatial distribution of N2O emissions over the study area. Cokriging with NH4Nt and NO3Nt as covariables (r= 0.74 and RMSE =1.18) outperformed ordinary kriging (r= 0.18 and RMSE =1.74), regression kriging with the sample position as a predictor (r= 0.49 and RMSE =1.55) and cokriging with SOCt as a covariable (r= 0.58 and RMSE =1.44). The predictions of the three kriging interpolation methods for the total N2O emissions of the 4.0 ha tea field ranged from 148.2 to 208.1 g N d−1, based on the 30 min snapshots obtained during the wet season. Our findings suggested that to accurately estimate the total N2O emissions over a region, the environmental variables (e.g., soil properties) and the current land use pattern (e.g., tea row transects in the present study) must be included in spatial interpolation. Additionally, compared with other kriging approaches, the cokriging prediction approach showed great advantages in being easily deployed, and more importantly providing accurate regional estimation of N2O emissions from tea-planted soils.

scholarly journals Wet-season spatial variability in N<sub>2</sub>O emissions from a tea field in subtropical central China

2015 ◽  
Vol 12 (12) ◽  
pp. 3899-3911 ◽  
Author(s):  
X. Fu ◽  
X. Liu ◽  
Y. Li ◽  
J. Shen ◽  
Y. Wang ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Ordinary Kriging ◽  
Spatial Interpolation ◽  
Central China ◽  
N2o Emissions ◽  
Regression Kriging ◽  
Wet Season ◽  
Interpolation Methods ◽  
N2o Fluxes ◽  
Tea Field

Abstract. Tea fields emit large amounts of nitrous oxide (N2O) to the atmosphere. Obtaining accurate estimations of N2O emissions from tea-planted soils is challenging due to strong spatial variability. We examined the spatial variability in N2O emissions from a red-soil tea field in Hunan Province, China, on 22 April 2012 (in a wet season) using 147 static mini chambers approximately regular gridded in a 4.0 ha tea field. The N2O fluxes for a 30 min snapshot (10:00–10:30 a.m.) ranged from −1.73 to 1659.11 g N ha−1 d−1 and were positively skewed with an average flux of 102.24 g N ha−1 d−1. The N2O flux data were transformed to a normal distribution by using a logit function. The geostatistical analyses of our data indicated that the logit-transformed N2O fluxes (FLUX30t) exhibited strong spatial autocorrelation, which was characterized by an exponential semivariogram model with an effective range of 25.2 m. As observed in the wet season, the logit-transformed soil ammonium-N (NH4Nt), soil nitrate-N (NO3Nt), soil organic carbon (SOCt) and total soil nitrogen (TSNt) were all found to be significantly correlated with FLUX30t (r = 0.57–0.71, p < 0.001). Three spatial interpolation methods (ordinary kriging, regression kriging and cokriging) were applied to estimate the spatial distribution of N2O emissions over the study area. Cokriging with NH4Nt and NO3Nt as covariables (r = 0.74 and RMSE = 1.18) outperformed ordinary kriging (r = 0.18 and RMSE = 1.74), regression kriging with the sample position as a predictor (r = 0.49 and RMSE = 1.55) and cokriging with SOCt as a covariable (r = 0.58 and RMSE = 1.44). The predictions of the three kriging interpolation methods for the total N2O emissions of 4.0 ha tea field ranged from 148.2 to 208.1 g N d−1, based on the 30 min snapshots obtained during the wet season. Our findings suggested that to accurately estimate the total N2O emissions over a region, the environmental variables (e.g., soil properties) and the current land use pattern (e.g., tea row transects in the present study) must be included in spatial interpolation. Additionally, compared with other kriging approaches, the cokriging prediction approach showed great advantages in being easily deployed and, more importantly, providing accurate regional estimation of N2O emissions from tea-planted soils.

scholarly journals Ordinary kriging vs inverse distance weighting: spatial interpolation of the sessile community of Madagascar reef, Gulf of Mexico

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e4078 ◽  
Author(s):  
Salvador Zarco-Perello ◽  
Nuno Simões
Keyword(s):  
Remote Sensing ◽  
Gulf Of Mexico ◽  
Spatial Variability ◽  
Ordinary Kriging ◽  
Spatial Interpolation ◽  
Prediction Errors ◽  
Interpolation Methods ◽  
Distance Weighting ◽  
Inverse Distance

Information about the distribution and abundance of the habitat-forming sessile organisms in marine ecosystems is of great importance for conservation and natural resource managers. Spatial interpolation methodologies can be useful to generate this information from in situ sampling points, especially in circumstances where remote sensing methodologies cannot be applied due to small-scale spatial variability of the natural communities and low light penetration in the water column. Interpolation methods are widely used in environmental sciences; however, published studies using these methodologies in coral reef science are scarce. We compared the accuracy of the two most commonly used interpolation methods in all disciplines, inverse distance weighting (IDW) and ordinary kriging (OK), to predict the distribution and abundance of hard corals, octocorals, macroalgae, sponges and zoantharians and identify hotspots of these habitat-forming organisms using data sampled at three different spatial scales (5, 10 and 20 m) in Madagascar reef, Gulf of Mexico. The deeper sandy environments of the leeward and windward regions of Madagascar reef were dominated by macroalgae and seconded by octocorals. However, the shallow rocky environments of the reef crest had the highest richness of habitat-forming groups of organisms; here, we registered high abundances of octocorals and macroalgae, with sponges, Millepora alcicornis and zoantharians dominating in some patches, creating high levels of habitat heterogeneity. IDW and OK generated similar maps of distribution for all the taxa; however, cross-validation tests showed that IDW outperformed OK in the prediction of their abundances. When the sampling distance was at 20 m, both interpolation techniques performed poorly, but as the sampling was done at shorter distances prediction accuracies increased, especially for IDW. OK had higher mean prediction errors and failed to correctly interpolate the highest abundance values measured in situ, except for macroalgae, whereas IDW had lower mean prediction errors and high correlations between predicted and measured values in all cases when sampling was every 5 m. The accurate spatial interpolations created using IDW allowed us to see the spatial variability of each taxa at a biological and spatial resolution that remote sensing would not have been able to produce. Our study sets the basis for further research projects and conservation management in Madagascar reef and encourages similar studies in the region and other parts of the world where remote sensing technologies are not suitable for use.

Spatial variability and distribution of N2O emissions from a tea field during the dry season in subtropical central China

Geoderma ◽  
2013 ◽  
Vol 193-194 ◽  
pp. 1-12 ◽  
Author(s):  
Yong Li ◽  
Xiaoqing Fu ◽  
Xinliang Liu ◽  
Jianlin Shen ◽  
Qiao Luo ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Dry Season ◽  
Central China ◽  
N2o Emissions ◽  
Tea Field

scholarly journals Spatio-temporal variability in N<sub>2</sub>O emissions from a tea-planted soil in subtropical central China

2016 ◽  
Author(s):  
X. L. Liu ◽  
X. Q. Fu ◽  
Y. Li ◽  
J. L. Shen ◽  
Y. Wang ◽  
...  
Keyword(s):  
Temporal Variability ◽  
Cross Validation ◽  
Central China ◽  
N2o Emissions ◽  
N2o Fluxes ◽  
The Cross ◽  
Spatio Temporal ◽  
Tea Field ◽  
Metric Model

Abstract. To explore the intrinsic spatial patterns of N2O emissions in agricultural systems, not only should the spatial and temporal variability in N2O emissions be analyzed separately, but the joint spatio-temporal variability should also be explored by applying spatio-temporal semivariogram models and interpolation methods. In this study, we examined the spatio-temporal variability in N2O emissions from a tea-planted soil from 28 April 2014 to 27 May 2014 using 96 static mini chambers in an approximately regular grid on a 40 m2 tea field (sampling 30 times), and the results were compared with long-term observations of the N2O emissions recorded using large static chambers (sampling 5 times). The N2O fluxes observed by the mini chambers during a 30 min snapshot (10:00–10:30 a.m. China Standard Time) ranged from −2.99 to 487.0 mg N m−2 d−1 and were positively skewed with a median of 13.6 mg N m−2 d−1. The N2O flux data were then log-transformed for normality. After detrending the influences from the chamber placement positions (Position) and the precipitation accumulated over two days (Rain2), the log-transformed N2O fluxes (FLUX30t) exhibited strong spatial, temporal and joint spatio-temporal autocorrelations, which were used as three components of spatio-temporal semivariogram models and were characterized by models based on Stein's parameterized Matérn (Ste) function, exponential function and again the Ste function, respectively. The spatio-temporal experimental semivariogram of the N2O fluxes was fitted using four spatio-temporal semivariogram models (separable, product-sum, metric and sum-metric). The sum-metric model performed the best and provided meaningful effective ranges of spatial and temporal dependence, i.e., 0.41 m and 5.4 days, respectively. Four spatio-temporal regression-kriging interpolations were applied to estimate the spatio-temporal distribution of N2O emissions over the study area. The cross-validation results indicated that the four interpolations exhibited similar performances (r = 0.817–0.824, RMSE = 0.456–0.486, p < 0.001), and outperformed the multiple linear regression prediction (r = 0.735, RMSE = 0.560, p < 0.001). The predictions of the four kriging interpolations for the total N2O emissions from the 40 m2 tea field ranged from 18.3 to 18.5 g N; these values were approximately 25 % higher than the results predicted using the observations of large static chambers. Furthermore, compared with the other three models, the metric model exhibited weak sensitivity for peak prediction, although the cross-validation results indicated that they had same prediction capabilities. Our findings suggested: (i) that the size of large static chambers used for long-term observations of N2O fluxes should be no less than 0.4 m and the time interval for gas sampling should be constrained to approximately 5 days; and (ii) that more efficient testing methods should be adopted to replace the conventional cross-validation methods for evaluating the performance of spatio-temporal kriging.

Response of N2O emissions to biochar amendment on a tea field soil in subtropical central China: A three-year field experiment

2021 ◽  
Vol 318 ◽  
pp. 107473
Author(s):  
Yanzheng Wu ◽  
Yong Li ◽  
Honghao Wang ◽  
Zijun Wang ◽  
Xiaoqing Fu ◽  
...  
Keyword(s):  
Field Experiment ◽  
Central China ◽  
N2o Emissions ◽  
Field Soil ◽  
Tea Field ◽  
Biochar Amendment

scholarly journals Methane and nitrous oxide fluxes from the tropical Andes

2013 ◽  
Vol 10 (11) ◽  
pp. 17397-17438 ◽  
Author(s):  
Y. A. Teh ◽  
T. Diem ◽  
S. Jones ◽  
L. P. Huaraca Quispe ◽  
E. Baggs ◽  
...  
Keyword(s):  
Elevation Gradient ◽  
Laboratory Data ◽  
Montane Forest ◽  
N2o Emissions ◽  
Wet Season ◽  
Ch4 Flux ◽  
Modelling Studies ◽  
N2o Fluxes ◽  
Ch4 And N2o ◽  
Montane Grasslands

Abstract. Remote sensing and inverse modelling studies indicate that the tropics emit more CH4 and N2O than predicted by bottom-up emissions inventories, suggesting that terrestrial sources are stronger or more numerous than previously thought. Tropical uplands are a potentially large and important source of CH4 and N2O often overlooked by past empirical and modelling studies. To address this knowledge gap, we investigated spatial, temporal and environmental trends in CH4 and N2O fluxes across a~long elevation gradient (600–3700 m a.s.l.) in the Kosñipata Valley, in the southern Peruvian Andes that experiences seasonal fluctuations in rainfall. The aim of this work was to produce preliminary estimates of CH4 and N2O fluxes from representative habitats within this region, and to identify the proximate controls on soil CH4 and N2O dynamics. Ecosystems across this altitudinal gradient were both atmospheric sources and sinks of CH4 on an annual basis. Montane grasslands (or, puna; 3200–3700 m a.s.l.) were strong atmospheric sources, emitting 56.94 ± 7.81kg CH4-C ha−1 yr−1. Upper montane forest (2200–3200 m a.s.l.) and lower montane forest (1200–2200 m a.s.l.) were net atmospheric sinks (−2.99 ± 0.29 kg CH4-C ha−1 yr−1 and −2.34 ± 0.29 kg CH4-C ha−1 yr−1, respectively); while premontane forests (600–1200 m a.s.l.) fluctuated between source or sink depending on the season (wet season: 1.86 ± 1.50 CH4-C ha−1 yr−1; dry season: −1.17 ± 0.40 CH4-C ha−1 yr−1). Analysis of spatial, temporal and environmental trends in CH4 flux across the study site suggest that soil redox was a dominant control on net CH4 flux. CH4 emissions were greatest from elevations, landforms and during times of year when soils were sub-oxic, and CH4 efflux was inversely correlated with soil O2 concentration (r2 = 0.82, F1, 125 = 588.41, P < 0.0001). Ecosystems across the region were net atmospheric N2O sources. N2O fluxes declined with increasing elevation; N2O emissions from premontane forest, lower montane forest, upper montane forest and montane grasslands averaged 2.23 ± 1.31 kg N2O-N ha−1 yr−1, 1.68 ± 0.44 kg N2O-N ha−1 yr−1, 0.44 ± 0.47 kg N2O-N ha−1 yr−1 and 0.15 ± 1.10 kg N2O-N ha−1 yr−1, respectively. N2O fluxes from premontane and lower montane forests exceeded prior model predictions for the region. Comprehensive investigation of field and laboratory data collected in this study suggest that N2O fluxes from this region were primarily driven by denitrification; that nitrate (NO3−) availability was the principal constraint on N2O fluxes; and that soil moisture and water-filled porosity played a secondary role in modulating N2O emissions. Any current and future changes in N management or anthropogenic N deposition may cause shifts in net N2O fluxes from these tropical montane ecosystems, further enhancing this emission source.

scholarly journals Nitrous oxide emissions from a beech forest floor measured by eddy covariance and soil enclosure techniques

2005 ◽  
Vol 2 (4) ◽  
pp. 377-387 ◽  
Author(s):  
M. Pihlatie ◽  
J. Rinne ◽  
P. Ambus ◽  
K. Pilegaard ◽  
J. R. Dorsey ◽  
...  
Keyword(s):  
Nitrous Oxide ◽  
Spatial Variability ◽  
Eddy Covariance ◽  
Temporal Variability ◽  
Nitrous Oxide Emissions ◽  
Small Scale ◽  
N2o Emissions ◽  
Ecosystem Level ◽  
N2o Fluxes ◽  
Trunk Space

Abstract. Spring time nitrous oxide (N2O) emissions from an old beech (Fagus sylvatica L.) forest were measured with eddy covariance (EC) and chamber techniques. The aim was to obtain information on the spatial and temporal variability in N2O emissions and link the emissions to soil environmental parameters. Mean N2O fluxes over the five week measurement period were 5.6±1.1, 10±1 and 16±11 μg N m−2 h−1 from EC, automatic chamber and manual chambers, respectively. High temporal variability characterized the EC fluxes in the trunk-space. To reduce this variability, resulting mostly from random uncertainty due to measuring fluxes close to the detection limit, we averaged the fluxes over one day periods. The variability in the chamber measurements was much smaller and dominated by high small scale spatial variability. The highest emissions measured by the EC method occurred during the first week of May when the trees were leafing and the soil moisture content was at its highest. If chamber techniques are used to estimate ecosystem level N2O emissions from forest soils, placement of the chambers should be considered carefully to cover the spatial variability in the soil N2O emissions. The EC technique, applied in this study, is a promising alternative tool to measure ecosystem level N2O fluxes in forest ecosystems. To our knowledge, this is the first study to demonstrate that the EC technique can be used to measure N2O fluxes in the trunk-space of a forest.

Effect of controlled-release fertilizer on N2O emissions and tea yield from a tea field in subtropical central China

2018 ◽  
Vol 25 (25) ◽  
pp. 25580-25590 ◽  
Author(s):  
Yanzheng Wu ◽  
Yong Li ◽  
Xiaoqing Fu ◽  
Jianlin Shen ◽  
Dan Chen ◽  
...  
Keyword(s):  
Controlled Release ◽  
Central China ◽  
N2o Emissions ◽  
Controlled Release Fertilizer ◽  
Tea Field
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