Spatial heterogeneity within the plough layer: high variability of N2O emission rates

Röver, Manuela; Heinemeyer, Otto; Munch, Jean Charles; Kaiser, Ernst‐August

doi:10.1016/s0038-0717(97)00271-x

Cited by 69 publications

(47 citation statements)

References 15 publications

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“…Our findings for a fertilized tea field were similar to those of Konda et al (2010) for a tropical forest. However, these results contrasted with those of many previous investigations for agricultural fields, including winter wheat (Ball et al, 1997;Clemens et al, 1999;Röver et al, 1999;Mathieu et al, 2006), summer maize (Clements et al, 1999), onion (Yanai et al, 2003) and grassland (Ambus and Christensen, 1994;Velthof et al, 1996;van den Pol-van Dasselaar et al, 1998;Turner et al, 2008) fields, in which the N 2 O flux presented no, weak or moderate spatial dependence. This discrepancy primarily occurred because of the unique geographical characterization and land management of the tea plantation.…”

Section: Spatial Structure Of N 2 O Emissions From Red Soils Planted contrasting

confidence: 93%

“…Several geostatistical methods are used to examine the spatial variability in N 2 O fluxes, including simple kriging (SK), ordinary kriging (OK), regression kriging (RK) and cokriging (CK). The most commonly used method is OK (Clemens et al, 1999;Röver et al, 1999;Mathieu et al, 2006;Konda et al, 2008Konda et al, , 2010, which uses the derived theoretical semivariogram models to interpolate the spatial distribution of N 2 O fluxes. However, research has demonstrated that RK and CK approaches, which use related auxiliary variables, improve the prediction accuracy (Goovaerts, 1997;Webster and Oliver, 2001;Hengl et al, 2004).…”

Section: Fu Et Al: Wet-season Spatial Variability In N 2 O Emissionsmentioning

confidence: 99%

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Wet-season spatial variability in N2O emissions from a tea field in subtropical central China

Liu

et al. 2015

Biogeosciences

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Abstract. Tea fields emit large amounts of nitrous oxide (N 2 O) to the atmosphere. Obtaining accurate estimations of N 2 O emissions from tea-planted soils is challenging due to strong spatial variability. We examined the spatial variability in N 2 O 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 N 2 O 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 N 2 O flux data were transformed to a normal distribution by using a logit function. The geostatistical analyses of our data indicated that the logit-transformed N 2 O 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 N 2 O 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 N 2 O 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 N 2 O 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 N 2 O emissions from tea-planted soils.

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Section: Spatial Structure Of N 2 O Emissions From Red Soils Planted contrasting

confidence: 93%

Section: Fu Et Al: Wet-season Spatial Variability In N 2 O Emissionsmentioning

confidence: 99%

Wet-season spatial variability in N2O emissions from a tea field in subtropical central China

Liu

et al. 2015

Biogeosciences

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“…Most chambers showed the same trend of CO 2 flux, while in the case of N 2 O, each chamber had a different time course of emissions. High temporal and spatial variability of N 2 O emissions was often observed in earlier field studies (e.g., Velthof and Oenema 1995, Velthof et al 1996, Röver et al 1999 and is a typical feature of N 2 O fluxes. Together with known general features of N 2 O fluxes, our results also suggest that obtaining reasonable estimates of N 2 O flux requires that period(s) of high fluxes be identified and that detailed measurements be made during that period on the spatial distribution and temporal variability of emissions.…”

Section: Discussionsupporting

confidence: 53%

Diurnal fluxes of CO2 and N2O from cattle-impacted soil and implications for emission estimates

Šimek¹,

Brůček²,

Hynšt³

2010

PLANT SOIL ENVIRON

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Short-term diurnal changes in emissions of CO 2 and N 2 O were determined in a cattle overwintering area during three specific periods of the year. Production of both N 2 O and CO 2 , as determined with gas chambers buried in soil and spatially distributed changed rapidly, and the general course of fluxes of the two gases was different. CO 2 emissions were basically controlled by temperature, and most gas chambers showed the same trends in CO 2 flux, indicating low spatial heterogeneity. In contrast, N 2 O emissions were much more spatially heterogeneous and each chamber had its own time course of emission; therefore, the relationship between flux and temperature was more complicated for N 2 O than CO 2 . For estimating gas emissions over long periods, we strongly recommend the use of frequent emission measurements during periods of high gas fluxes.

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“…The highest emission rates of more than 1000 µg "hotspots" (e.g. Christensen et al 1990;Röver et al 1999;Wanga et al 2006), were detected at the fertilised sites only. Besides the highly emitting N 2 O hot spots with maxima above 1000 µg N 2 O/m 2 /h in 2001, 2002, and 2006, one or two less emitting N 2 O hot spots with maxima above 100 µg N 2 O/m 2 /h were also observed in all other years of this study, except in 1999.…”

Section: Resultsmentioning

confidence: 95%

Nitrogen conversion and nitrous oxide hot spots in energy crop cultivation

Hellebrand¹,

Scholz²,

Kern³

2008

Res. Agric. Eng.

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Since 1999, nitrous oxide (N 2 O) soil emissions from sites cultivated with energy plants have been measured by gas chromatography and gas flux chambers in experimental fields. The main aim of this study was the nitrogen conversion factor and its variability for sandy soils under climatic conditions of Central Europe. Annual plants (hemp, rape, rye, sorghum, triticale) and perennial plants (grass, perennial rye, poplar, willow) were fertilised with three different levels of nitrogen (150 kg N/ha/year, 75 kg N/ha/year, and none). The annual nitrogen conversion factors were derived from the annual mean differences between the fertilised sites and non-fertilised control sites. The mean nitrogen conversion factor for the non-cultivated soils was lower (perennial crops: 0.4%) than that for the regularly cultivated soils (annual crops: 0.9%). Few times, enhanced N 2 O emission spots with maxima above 1000 µg N 2 O/m 2 /h, lasting for several weeks, were observed in the course of measurements. The influence of these local peak emissions on the nitrogen conversion factor is discussed.

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Spatial heterogeneity within the plough layer: high variability of N2O emission rates

Cited by 69 publications

References 15 publications

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

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

Diurnal fluxes of CO<sub>2</sub> and N<sub>2</sub>O from cattle-impacted soil and implications for emission estimates

Nitrogen conversion and nitrous oxide hot spots in energy crop cultivation

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Spatial heterogeneity within the plough layer: high variability of N2O emission rates

Cited by 69 publications

References 15 publications

Wet-season spatial variability in N&lt;sub&gt;2&lt;/sub&gt;O emissions from a tea field in subtropical central China

Wet-season spatial variability in N&lt;sub&gt;2&lt;/sub&gt;O emissions from a tea field in subtropical central China

Diurnal fluxes of CO<sub>2</sub> and N<sub>2</sub>O from cattle-impacted soil and implications for emission estimates

Nitrogen conversion and nitrous oxide hot spots in energy crop cultivation

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

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