Cover cropping has become a key management measure to reduce nitrate leaching and soil erosion in intensive crop production (e.g., Wyland et al., 1996; Dabney, 1998; Meyer et al., 1999; Shepherd and Webb, 1999; Hartwig and Ammon, 2002; Logsodon et al., 2002; van Dam, 2006). A new agro-environmental target in the current period of common European agricultural politics is climate change mitigation and adaptation (EU 2013). Estimates by IPCC (2007) and Smith et al. (2008) attribute around 10–12% of global greenhouse gas emissions to agriculture, with a dominant role for N2O (60—84%) and CH4 (50%) emissions. Soil borne N2O emissions are mainly related to N-fertilization, with estimates of about 1.25% ± 1% of total fertilizer N lost via N2O emission (Moisier et al., 1998). Cover crop uptake of excessive soil N is therefore expected to contribute to agricultural climate change mitigation (McSwiney et al., 2010). Parkin et al. (2006) evaluated the effect of a rye cover crop on the overall N balance after pig slurry application and showed that the rye cover crop lowered the cumulative N2O emission in case of high manure application. However, other studies reported different outcome. Liebig et al. (2010) and Jarecki et al. (2009) did not find differences in cumulative fluxes of CO2, CH4, and N2O between bare and green-manure (rye) amended soil, while Bavin et al. (2009) showed an increase in CO2 only and N2O emissions was not affected by the rye cover crop. Kallenbach et al. (2010) found that both CO2 as well as N2O losses from fields with a winter legume cover crop (hairy vetch) increased compared to fallow.
Rosecrance et al. (2000) compared the overall field N-balance including denitrification for rye, rye-vetch and vetch cover crops with fallow. They showed greater potential N losses from vetch than rye or rye-vetch mixtures due to rapid N-mineralization in conjunction with denitrification and potential leaching, prior to significant N-assimilation by the subsequent main crop. Under tropical conditions in Brazil, Gomes et al. (2009) measured N2O emissions in a no-tillage maize system after a grass (
Velthof et al. (2002) compared N2O emissions from different crop residues and the influence of NO3 addition in an incubation study. Emissions from residues of wheat, maize and barley were neglegible, while total N2O emission from white cabbage, Brussels sprouts, mustard, sugar beet residues and broccoli ranged from 0.13 to 14.6% of the amount of N added as residue and were higher with additional NO3 than without. The C/N ratio of the residue accounted for only 22—34% and the mineralizable N content of the residue for 18—74% of the variance in N2O emission. An incubation study with hairy vetch by Aulakh et al. (1991) showed that the losses occurred mainly during the first 10 days after residue addition and were mostly influenced by the additional C from the incorporated legume crop residues. Thus, the type of cover crop species seems to be decisive to either mitigate or even increase the greenhouse gas losses.
There are only a few field studies focusing on the over-winter emissions between the frost killing of cover crops in late autumn and start of the main crop in subsequent spring. In this period, freezing-thawing and snow melting could lead to critical moments with high nitrous oxide emissions (Hagedorn et al., 2011). A study conducted in Denmark by Petersen et al. (2011) reported slightly higher N2O emissions from a cover cropped soil (oilseed radish) after freezing events. Still, emissions during autumn, winter and early spring were generally low. A peak in emissions occurred in spring after tillage and organic fertilizer application. Pattey et al. (2008) investigated N2O emissions in a pea-cover crop sequence in Canada with particular regard to spring thawing. Thawing induced emissions were 15% of the total annual emissions. Also, Wagner-Riddle and Thurtell (1998) studied the effect of thawing on N2O emissions in a Canadian field experiment with different management practices. Nitrous oxide emissions between January and April over four years ranged between 0 and 4.8 kg N ha-1. The study indicated that denitrification losses from cover cropped soils strongly depended on hot moments (wetting-drying, freezing-thawing) following residue incorporating.
For Central European conditions, it is therefore suggested that greenhouse gas losses from cover cropped fields are determined by plant species and critical high emission moments after cover crop residue addition to the soil. The objectives of this study were (i) to compare the greenhouse gas emissions from field soil among commonly used cover crops and cover crop mixtures, and (ii) to evaluate the key drivers for gaseous losses between cover crop frost killing in late autumn and start of main crop vegetation period in early spring. The main hypothesis is that cover crops increase soil CO2 emissions due to an enhanced input of organic residues, while they reduce N2O emissions compared to fallow because of reduced nitrate content in surface soil.
Field experiments were established at two sites with different climatic and pedological conditions. A first experiment was located near Lichtenwörth, Lower Austria (47° 49′ N, 16° 16′ O, 254 mAA). Lichtenwörth is situated in the Southern Viennese Plain and belongs to the sub-humid climate zone with long-term averages (1971–2000) of rainfall being 599 mm and mean annual temperature 9.4°C. The soil is a calcareous chernozem with sandy loam texture and a depth of the A horizon of 60 cm, overlaying a D horizon of coarse fluvial sediments. The soil is characterized by high water permeability and air capacity. The second experimental site was located near Pötting, Upper Austria (48° 17′ N, 13° 46′ O, 381 mAA). Pötting belongs to the humid climate zone influenced by north-eastern Atlantic currents. Geographically, Pötting forms part of the hilly pre-alpine region. Long term average (1971 —2000) rainfall is 817 mm, mean annual temperature is 7.9°C. The soil is a typical stagnosol of silty loam texture and a moderately acidic pH value. Depth of the A horizon is 25 cm, followed by a P horizon of 40 cm, which is periodically water saturated, particularly in spring, due to low permeability of the underlying S1 and S2 horizons.
Experimental factors included (i) cover cropping vs. bare soil, and (ii) addition of organic fertilizer (30 kg ha-1 N) vs. no fertilization. Four cover crop treatments were established, being (a) mustard (Pötting:
Figure 1 shows the monthly averages of precipitation and temperature for the experimental time as well as the previous cover crop growing period.
At Pötting, the sum of rainfall between July 2012 to April 2013 was slightly lower (623 mm) compared to the long-term average (648 mm). At Lichtenwörth, on the contrary, there was substantially higher total precipitation (577 mm) compared to the long-term average (447 mm) which was mainly due to very high rainfall in July 2012. July rainfall is crucial for cover crop establishment, particularly in subhumid regions with higher probability of summer drought that might delay cover crop emergence.
For greenhouse gas emissions, both soil temperature and soil water content are crucial environmental parameters. These parameters were measured in the topsoil (0—5 cm depth) simultaneously with gas sampling (cf. green arrows in Figure 1). As expected, the soil temperature was generally lower, while the water content was higher at the humid compared to the sub-humid site. At Pötting, the soil temperatures ranged from a minimum of 6.1 ± 0.4°C in February 2013 to a maximum of 14.6 ± 0.3°C in March 2013. In November 2012, the soil temperature was 7.0 ± 0.4°C. Soil water content ranged from a minimum of 31.4 ± 3.0% in November 2012 to a maximum of 41.7 ± 2.3% in March 2013. In February 2013, the soil water content was 39.4 ± 3.0%. This corresponded to average water filled porosities between 62.9% and 83.3%. At Lichtenwörth, the minimum of soil temperature was also registered in February 2013 (7.1 ± 0.4°C) and the maximum in March 2013 (16.7 ± 1.6°C). Soil temperature in November was 9.7± 0.2°C. The range of soil water content at Lichtenwörth was between 24.5 ± 2.9% in November 2012 and 28.7± 3.1% in February 2013. In March 2013, the soil water content was 26.3 ± 3.1%. The corresponding average water filled porosities were 46.1%, 55.3% and 50.6% respectively.
Measured parameters comprised cover crop dry matter and C/N ratio, greenhouse gas emissions (CO2, N2O), soil mineral N (NO3- and NH4+), dissolved organic carbon, soil moisture and soil temperature (Table 1).
Overview of measured parameters, methods and sampling dates Tabelle 1. Überblick über die gemessenen Parameter, die Methoden und Beprobungstermine Sampling dates at the two sites were ± 2 days. DOC was measured from a mixed soil sample of three replicates.
Parameter Method Sampling date Aboveground biomass Dry matter at 105°C 14 November 2012 CN ratio CNS analyzer - CO2, N2O Closed chamber method 22 November 2012, 1 February 2013, 6 March 2013 Soil mineral N Photometric 22 November 2012, 1 February 2013, 6 March 2013 DOC Photometric 22 November 2012, 1 February 2013, 6 March 2013 Soil water content Capacitance 22 November 2012, 1 February 2013, 6 March 2013 Soil temperature Thermistor 22 November 2012, 1 February 2013, 6 March 2013
Overview of measured parameters, methods and sampling dates
Tabelle 1. Überblick über die gemessenen Parameter, die Methoden und Beprobungstermine
Sampling dates at the two sites were ± 2 days.
DOC was measured from a mixed soil sample of three replicates.
Aboveground biomass samples were taken on 16th November 2012 from one square meter, pre-dried at 50°C and thereafter dried for 24 hours at 105°C to constant dry weight. After weighing, the samples were milled and analyzed for carbon and nitrogen content using a Carlo Elba CNS Elemental analyzer.
Soil greenhouse gas emissions were measured on three dates. The first sampling was done in late autumn after a short frost period (16—18th November 2012) terminating most plants in order to capture immediate effects from dead leaf and stem addition to soil before winter. The second sampling was done during a period of temporary soil thawing over winter, while the third sampling date coincided with snow melting in March 2013. These sampling periods were considered hot moments (fresh residue addition, freezing-thawing, snow melt with high soil water content) for potential gas emissions. In a sub-set (mustard, legume mixture, fallow; fertilized plots), at the humid (high emission) site, the Pötting measurements were continued until the end of June to obtain comparative values of main crop related emissions (tillage, sowing, N-fertilization). All measurements were done using the closed chamber method (e.g., Rochette et al., 1992) with soil inserted PVC cylinders (10 cm height, 20 cm diameter, insertion depth 3 cm). Cylinders were closed airtight with a lid containing a rubber septum for gas sampling via a syringe (30 ml sampling volume). Gas samples were taken immediately after closing the chamber (initial concentration), after 15 and 45 minutes and injected in evacuated cups. Analysis of trace gas concentration (CO2, N2O and CH4) was done by gas chromatography with a 6890 N GCSystem (Agilent, Santa Clara, CA, USA) connected to an automatic headspace-sample injection system (Dani HSS 86.50 Dani, Cologno Monzese, Italy). Gas flux (µg resp. mg m-2 h-1) was then calculated from the change in gas concentration over time.
Soil parameters related to the greenhouse gas formation were measured in the upper soil layer (0—5 cm) at the time of gas sampling. Soil physical variables comprised water content and temperature (Vitel Hydra Probe). Soil chemical parameters were mineral N (NO3, NH4; ÖNORM L1091) and dissolved organic carbon (DOC). DOC was determined for selected sampling points only due to the limited analytical capacity. A mixed sample (mixture of three replicate samples; 10 samples per site) of each treatment was taken immediately after the cover crop vegetation period first gas sampling date) expecting most evident differentiation in DOC. A second set of DOC analysis was made for the measurement dates with the highest N2O emissions at each site, that is, 1st February 2013 at Lichtenwörth and 7th March 2013 at Pötting. Again, a mixed sample for each treatment was analyzed. Analysis was done by infrared spectroscopy after the extraction of the samples by deionized water (Brandstätter et al., 1996).
Samples were taken along a line transect with three replicate sampling points in each plot equally spaced at a 2-meter distance. All parameters were sampled at the same position with only small shifts in the longitudinal direction in case of destructive sampling. We first tested spatial correlation (trends) between the data points via autocorrelation analysis. If no spatial correlation was identified, the three samples per plot were considered random replicates and analysis of variance was performed to test for significant treatment effects. In case of spatial trends, further geo-statistical methods would be applied for data analysis.
Generally, the auto-correlograms did not reveal any spatial trend in the measured parameters as exemplified by Figure 2 for N2O. In case of greenhouse gas emissions, it is well known that emissions are frequently related to soil micro-sites (e.g., Parkin, 1987) with small scale variability. Thus, all data could be treated as spatially independent and tested for treatment effects by analysis of variance. Analysis of variance was performed using a mixed model with measurement dates as repeated measure and an unstructured covariance model for the repeated factor (Piepho et al., 2004).
Another analytical method we applied was joint regression. This technique originates from plant breeding to reveal the distinct response of varieties in different environments (e.g., Annicchiarico, 1997). Environments are characterized via the overall mean of all treatments and are plotted against the single treatments. For this purpose, the two sites were used together thereby defining six “environments” (2 sites × 3 measurement dates) from low to high emission potential. Regression analysis was applied to single soil cover emissions versus the average environmental emission potential.
Finally, regression analysis was performed to reveal any causal relations of greenhouse gas emissions versus soil (water content, temperature, N content, DOC) and plant (C/N ratio, N concentration) parameters.
All statistical analyses were done using SAS 9.1 with PROC MIXED for analysis of variance and PROC REG for regression analysis. For autocorrelations, the SAS time series viewer was used.
Figure 3 shows the cover crop dry matter and C/N ratio at the two sites. There was a significant interaction between site and cover crop species for dry matter, while C/N ratio showed only significant site and species main effects.
Cover crops achieved a relatively high dry matter yield at both sites compared to literature values (e.g., Lütke Entrup, 2000). Mustard and cress-mungo-radish mixture had higher dry matter yield at Lichtenwörth compared to the mixtures of mustard-phacelia and Alexandrian clover-Mungo-phacelia. At Pötting, on the contrary, mustard had the lowest dry matter yield, while all the other cover crops were at a similar level. This was obviously related to the later sowing date of mustard. Dry matter yield of both mustard and cress-mungo-radish mixture differed significantly between sites.
C/N ratio was lowest for mustard and highest for the mustard-phacelia mixture. The legume containing mixture (Alexandrian clover-Mungo-phacelia) was between these two variants. In average, the sub-humid site showed a significantly higher C/N ratio of biomass compared to the humid site.
Figure 4 shows the boxplots of the measured N2O and CO2 emissions. It reveals the average emission potential for each date and site as well as the high variability of soil emissions that has been described in several studies (e.g., Partkin, 1987; Rochette et al., 1991).
N2O emissions were generally low. The median of values was near zero in all cases. The highest N2O flux at Pötting was registered in March 2013 with a mean value of 6.3 μg m-2 h-1 and a peak of 31.4 μg m-2 h-1. At Lichtenwörth, the highest emissions were measured in February 2013 with a mean of 5.4 μg m-2 h-1 and a maximum of 46.6 μg m-2 h-1. Average CO2 emissions were higher at Pötting (15.1 mg m-2 h-1) compared to Lichtenwörth (7.9 mg m-2 h-1). At Pötting, the measurement date showed stronger influence on the average CO2 flux with a clear depression in February 2012. At Lichtenwörth, on the contrary, the variation between the measurement dates was low (± 1.3 mg m-2 h-1). Table 2 shows the ANOVA results for the influence of main and interaction effects on the measured greenhouse gas emissions.
Results of mixed model analysis of variance (F-statistics and p-value of main effects and interactions) for greenhouse gas emissions. Significant effects (in case of significant interactions, highest order interaction) are marked in bold. Tabelle 2. Ergebnis der Varianzanalyse (gemischtes Model; F-Werte und p-Werte der Haupteffekte und ihrer Wechselwirkungen) für Treibhausgasemissionen. Signifikante Effekte (bei signifikanten Interaktionen, die Interaktion höchster Ordnung) sind fett gekennzeichnet. Site refers to experimental location, date to measurement date, N is N fertilization treatment, CC is soil cover treatment, Rep is replication.
Effect N2O CO2 F-statistic p>F F-statistic p>F Site 0.00 0.9866 6.18 0.0180 Date 6.46 1.58 0.2197 Site × Date 1.53 0.2290 9.68 N 0.51 0.4785 0.00 0.9503 Site × N 2.98 0.0922 1.21 0.2782 Date × N 0.00 0.9966 3.16 0.0553 Site × Date × N 0.05 0.9541 1.51 0.2345 CC 3.33 9.17 <.0001 Site × CC 0.31 0.8716 0.25 0.9090 Date × CC 1.81 0.0967 2.84 Site × Date × CC 0.4 0.9137 0.78 0.6188 N × CC 1.14 0.3506 1.19 0.3325 Site × N × CC 0.68 0.6070 0.19 0.9397 Date × N × CC 1.50 0.1825 1.79 0.1018 Site × Date × N × CC 0.66 0.7226 0.16 0.9954 Rep 0.29 0.7510 0.73 0.4877 Date × Rep 1.18 0.3311 0.88 0.4856
Results of mixed model analysis of variance (F-statistics and p-value of main effects and interactions) for greenhouse gas emissions. Significant effects (in case of significant interactions, highest order interaction) are marked in bold.
Tabelle 2. Ergebnis der Varianzanalyse (gemischtes Model; F-Werte und p-Werte der Haupteffekte und ihrer Wechselwirkungen) für Treibhausgasemissionen. Signifikante Effekte (bei signifikanten Interaktionen, die Interaktion höchster Ordnung) sind fett gekennzeichnet.
Site refers to experimental location, date to measurement date, N is N fertilization treatment, CC is soil cover treatment, Rep is replication.
N2O emissions differed significantly between measurement dates and cover crop species. Interestingly, there was no significant difference between the average N2O emissions at the two sites. CO2 emissions showed significant interactions of date with site and cover crop species. Species effects (N2O main effect, CO2 date × species interaction) are shown in Figure 5.
The species effect for N2O emissions clearly indicated that monocropping a
Species effects for CO2 (Figure 5b) revealed the highest emissions for the cover cropped plots at the first measurement date. Mixtures of mustard-phacelia and cress-mungo-radish showed a significant increase of CO2 losses in March, following the lowest emissions in February. Fallow had no significant differences between dates, while mustard and clover-mungo-phacelia were at a similar level in February and March. On average, all the cover cropped plots had significantly higher CO2 emissions compared to the fallow in November and February. In March, the CO2 flux was similar for all treatments except the mustard-phacelia mixture that had a significantly higher value.
The date × site interaction for CO2 emissions can be inferred from Figure 4. Sites differed significantly in November (Pötting 20.8 mg m-2 h-1, Lichtenwörth 7.0 mg m-2h-1), while being similar in February (7.6 and 9.2 mg m-2 h-1) and March (16.9 and 7.4 mg m-2 h-1). At Pötting, the emissions in February were significantly lower compared to November and March; while at Lichtenwörth, the CO2emissions were at a similar level at all measurement dates. In March, the variability of CO2 values in Pötting was particularly high.
It can be hypothesized that the treatment differences become more evident when the average emission potential is high. Figure 6 compares the increase of single treatment emissions with increasing environmental emission potential (joint regression). For N2O, the application of organic N-fertilizer resulted in higher emission over the whole range of emission levels. For CO2 emissions, no differences in average level and trend could be found between the N-treatments. Comparing the soil cover treatments, there was a clear difference of mustard that leads to substantially higher emissions compared to the other treatments in high emission environments. For the other treatments, confidence bands were overlapping over the whole range of emission levels.
In case of CO2 emissions, joint regression did not reveal a clear distinction among the treatments. Still, it is evident that fallow has the lowest CO2 emission and differentiation to the cover cropped soil tends to increase with increasing emission potential.
In order to understand the role of causal factors for greenhouse gases formation, we determined regression relations of CO2 and N2O with soil chemical (mineral N, DOC; Figure 7) and soil physical (water content, temperature; Figure 8) parameters. For significant relations, regression equations, R2 and significance levels are given in Table 3. Among the soil chemical factors, a slight significant relation was found between CO2 and soil mineral N at Lichtenwörth. At both sites, the N2O emissions were not influenced by soil mineral N. DOC and soil water content were found as a significant causal factor for N2O emissions at both sites. At the semi-arid site Lichtenwörth, increasing soil water content also resulted in higher CO2 emissions.
Regression relations between soil chemical and physical parameters and greenhouse gas emissions Tabelle 3. Regressionsbeziehungen bodenchemischer und bodenphysikalischer Parameter mit Treibhausgasemissionen
Site Factors Equation R2 p-value Pötting Soil mineral N vs CO2 y = -4.36 + 0.57x 0.32 0.028 DOC vs N2O y = -8.82 + 0.37x 0.41 0.046 Soil water content vs. N2O y = -16.56 + 0.52x 0.39 0.013 Lichtenwörth DOC vs. N2O y = -5.21 + 0.26x 0.58 0.011 Soil water content vs. CO2 y = -14.11 + 0.83x 0.41 0.011 Soil water content vs. N2O y = -24.63 + 1.04x 0.56 0.001
Regression relations between soil chemical and physical parameters and greenhouse gas emissions
Tabelle 3. Regressionsbeziehungen bodenchemischer und bodenphysikalischer Parameter mit Treibhausgasemissionen
Soil temperature influenced neither CO2 nor N2O emissions under the given temperature ranges during the cover crop period.
Finally, we tested if either cover crop biomass or quality of residues (C/N, N) were directly related to any of the two greenhouse gasses. For this purpose, we pooled together the cover crop data from both sites resulting in 8 data pairs (4 cover crops × 2 sites). A significant relation was found between the N content of biomass and N2O emissions in February (Figure 9; R2 = 0.50, p = 0.05). Although significant, the regression has to be interpreted with care due to the clustering of observations at two extremes with the high C/N ratio mustard variants at the upper end and the other species with similar C/N values at the lower end.
This study reports greenhouse gas emissions (CO2, N2O) from cover cropped compared to fallow soil. Cover cropping is considered a potential measure to mitigate N2O emissions from agricultural soils mainly due to the reduction of soil NO3 content (McSwiney et al., 2010). Furthermore, it is suggested as a measure for carbon sequestration in agricultural soil (Lal, 2011). On the other hand, addition of easily mineralizable carbon from cover crop residues might also stimulate greenhouse gas formation (Mitchell et al., 2013). Under Central European climatic conditions, hot moments for N2O emissions can be expected between the period of cover crop termination by frost in late autumn (residue addition to the soil) and the start of the subsequent main crop in spring, for example, the periods of snow melting, freezing-thawing and high levels of water filled porosity (Hagedorn et al., 2011).
Our results demonstrated that even during hot moments of N2O emissions between late autumn and early spring, average fluxes were low. For better comparison, Figure 10 provides a time series of the subsequent emissions between March and end of June 2013 at the humid (high emission) site for three soil cover treatments (fallow, mustard, non-
Comparing Figure 4a and 10a, it is obvious that the main N2O losses are related to operations during the main crop, particularly tillage and N-fertilization. Here, an N2O peak as high as 2316 μg m-2 h-1 (N-application + tillage, 87.6% water filled porosity, 23.0°C soil temperature) occurred. A second peak of 874.4 g m-2 h-1 was measured on 2nd June following an intense rainfall with soil at 80.4% of water filled porosity, soil temperature of 11.5°C and mineral N in the topsoil (0—5 cm) of 36.7 kg ha-1. On the contrary, the highest emission to be considered an immediate spillover effect of cover cropping at this site was 31.5 μg m-2 h-1in a mustard plot in March 2013. This is in agreement with Petersen et al. (2011) who also reported N2O values near zero during the cover crop period, while values increased to 900 μg m-2 h-1 until May in the subsequent vegetation period. Several studies reported high N2O fluxes following N-fertilization (e.g., Arcara et al., 1999) and rainfall events saturating the topsoil (e.g., Jacinthe and Dick, 1997). Dobbie and Smith (2001) showed that a temperature increase between 5 and 12°C strongly stimulated N2O emissions, while the temperature effect became lower when further increasing soil temperature from 12 to 18°C. Thus, soil temperatures at soil thawing (February) and snow melting (March) were probably still suboptimum for microbial activity catalyzing denitrification. Furthermore, soil mineral N levels in the top soil in February (Pötting: 26.7 kg ha-1; Lichtenwörth: 26.1 kg ha-1) and March (Pötting: 34.4 kg ha-1; Lichtenwörth: 37.8 kg ha-1) were substantially lower compared to the values registered during the main cropping period (up to 179 kg N ha-1). From this comparison, it can be concluded that N2O emissions following cover crops are negligible compared to emissions during the main cropping period mainly due to environmental constraints (low soil temperature and N-content). We also notice here that N2O emissions from April onwards (cf. Figure 10a) did not show a distinctive trend between the cover cropped and fallowed plots, which is in agreement with other studies (e.g., Parkin and Kaspar, 2006).
Differences in the height of CO2 flux between the period from late autumn to early spring and the subsequent period until early summer were less pronounced compared to N2O. This shows the substantially stronger response of N2O to hot spots and hot moments compared to CO2 leading to higher spatial and temporal variability (Parkin, 1987; Yao et al., 2010). Following frost termination of cover crops, the highest average CO2 emissions were measured in November upon fresh residue addition to the soil (21.3 mg m-2 h-1), while the highest average value during the main crop time series was 52.7 mg m-2 h-1 on 16th June 2013. A first peak of CO2 was coincident with the N2O peak (5th May 2013) following tillage and N-fertilization. In this case, the emissions from fallow were significantly lower, which indicates an N-fertilizer induced mineralization push of cover crop residues. The second emission peak for CO2 on 16th June was registered two weeks later compared to N2 O, coincident with very high soil temperature (26.9°C) and lower water content (18.4%). Generally, the main driver of CO2 emissions (R2 = 0.63; p < 0.001) was soil temperature.
Cover cropping is expected to reduce nitrous oxide emissions via plant uptake of soil mineral N as well as microbial N-immobilization during residue decomposition. Most studies comparing different cover crop treatments focused on legumes versus non-legumes assuming that the latter contribute more to mitigation of greenhouse gas emissions due to higher depletion of soil NO3- and lower residue C/N ratio (e.g., Rosecrance et al., 2000; Baggs et al., 2000; Flessa et al., 2002; Basche and Miguez, 2012; Sanz-Cobena et al., 2014). However, availability of easily decomposable C from cover crop residues can also cause higher emissions (Mitchell et al., 2013). Concerning CO2, Lal (2011) attributes cover crops a potential to sequester C in agricultural soil. Still most cover crop residues are allocated to the easily degradable soil C pool and are readily mineralized (Puget and Drinkwater, 2001).
Cover crop treatments in our experiment were mainly species mixtures except for mustard as a predominant species in Central Europe. Mixtures combine single species environmental benefits and increase biodiversity within the main crop monocultures (e.g., Creamer et al., 1997; Snapp et al., 2005). Our results clearly showed a distinctive behavior of mustard with a significant increase of N2O emissions during the high emission moments between late autumn and early spring. In the subsequent main crop vegetation period, there was no evidence of enhanced emissions from mustard plots (cf.Figure 10). In a study of Baggs et al. (2000) in Scotland, on the contrary, no enhanced emissions from mustard were registered. In this study, the N2O measurements were performed after cover crop incorporation in April. The authors reported comparatively dry soil conditions and attributed N2O formation to nitrification. Furthermore, mustard residues in their experiment had larger C/N ratio (30.3:1) compared to our study (15.5:1). Petersen et al. (2011) found slightly higher emissions after freezing-thawing events from plots with fodder radish compared to fallow, which they attributed to residue mineralization and higher soil NO3 contents during warmer periods over winter. Similar to our study, the general emission level before the main crop vegetation period was low.Velthof et al. (2002) also reported peak N2O losses for
CO2 emissions were readily increased by cover crops upon frost killing in late autumn and thereafter decreased until spring. Also, Magid et al. (2004) demonstrated quick release of N and C from the cover crop residues after incorporation even at low temperatures (3°C). Taking the bare soil treatment as reference for CO2 respiration, CO2 release from the cover cropped plots was 313.7%, 103.1% and 28.7% above fallow in November, February and March respectively. Mixtures of mustard-phacelia and cress-mungo-radish had a significant depression of CO2 fluxes in February before the onset of spring mineralization. Their wider C/N-ratio probably slowed down the decomposition process to a larger extent under lower soil temperatures and microbial activity in February. We notice here that CO2 emissions from cover cropped plots do not allow inferring on potential soil carbon storage from the added plant material. Lal et al. (1998) estimated carbon sequestration from cover crops between 100–300 kg C ha-1 yr-1 depending on residue quality (Puget and Drinkwater, 2001) and interaction with soil aggregation (Kong et al., 2005). Concerning fallow, the measured CO2 emissions in any case are losses from the soil organic carbon pool, which are not counterbalanced by any previous inputs.
The conflicting results on cover crop induced N2O emissions are explained by their different impact on either of the causal factors for nitrous oxide formation: in case of dominant reduction of soil NO3-(uptake, immobilization) and/or drying of the top soil by plant water extraction, a reduction of N2O fluxes compared to fallow can be expected. On the contrary, whenever the dominant cover crop effects are addition of easily decomposable carbon, quick N release from fresh residues and/or higher top soil moisture under surface mulch residues, a temporal increase of losses can be caused. In this context, the inter-annual variability in weather conditions adds complexity to the cover crop effect. The overall effect will be reduced in years with adverse autumn conditions, leading to lower cover crop biomass compared to this study. Warmer spring temperatures than in this experiment may enhance an early cover crop turnover. In sub-humid Eastern Austria, the influence of spring-drought with subsequent wetting of the soil can constitute a special case for residue turnover to be studied.
As expected, our results showed a positive effect of soil water content on N2O emissions. A strong increase of losses, exceeding the background emissions of 5 μg m2 h-1, was observed at > 60%water filled porosity. Soil mineral N did not show a significant relation to N2O fluxes. At the time of highest N2O emissions (Lichtenwörth February; Pötting March), the soil N content was significantly lower in bare soil (11.4 kg N ha-1; 22.3 kg N ha-1) compared to the cover cropped plots (24.9 kg N ha-1; 37.4 kg N ha-1). Still, this does not explain the distinctive behavior of mustard, which did not differ from other cover crops in soil mineral N. The highest R2 among the tested causal factors for N2O was found for DOC. Also, Mitchell et al. (2013) showed that mineralizable C input from cover crop residue can control N2O emissions in case of sufficient availability of NO3-. Foi the distinctive behavior of mustard, furthermore, the higher biomass N-content of residues (cf. Figure 9) and their chemical composition has to be taken into account.
CO2 emissions were significantly related to soil mineral N at Pötting and soil water content at Lichtenwörth. CO2 and N release occur within the same process of organic matter mineralization. Therefore, it is difficult to prove if the relation between soil mineral N and CO2 is causal (enhanced microbial activity via otherwise limiting soil N), or coincidental (two parameters expressing the same process). The relation to soil water content at Lichtenwörth indicates that the average saturation level at this site was still favorable for aerobic processes. The equally positive relation to N2O points to the role of anaerobic microsites in a soil with otherwise sufficient air-filled porosity at larger representative elementary volume.
Soil greenhouse gas emissions (N2O, CO2) were compared between different cover crops and fallow at two climatically different sites in Austria. The focus was on hot moments of high denitrification potential in the period between late autumn cover crop residue addition and early spring snow melting. The main conclusions of this study are:
Overall N2O emissions between late autumn and early spring are low compared to the management impacts (tillage, N fertilization) during the main crop vegetation period in spite of temporally high soil water content and freezing-thawing. N2O emissions are increased by a mustard cover crop in pure stand, particularly for situations with high emission potential. It is suggested that high biomass N content and the specific biochemistry of mustard residues (glucosinolate decomposition) are the main reason for the enhanced N2O emissions. Cover crops increase CO2 flux reflecting an enhanced soil biological activity after addition of easily decomposable organic carbon. These gaseous C losses follow the previous C addition, which is not the case for CO2 emissions from fallow soil. Soil water content (N2O), soil temperature (CO2) and dissolved organic carbon (N2O and CO2) were the dominant causal factors for greenhouse gas emissions. Particularly DOC is suggested as an appropriate indicator for cover crop induced ecosystem dynamics related to the carbon and nitrogen cycle.
Overall N2O emissions between late autumn and early spring are low compared to the management impacts (tillage, N fertilization) during the main crop vegetation period in spite of temporally high soil water content and freezing-thawing.
N2O emissions are increased by a mustard cover crop in pure stand, particularly for situations with high emission potential. It is suggested that high biomass N content and the specific biochemistry of mustard residues (glucosinolate decomposition) are the main reason for the enhanced N2O emissions. Cover crops increase CO2 flux reflecting an enhanced soil biological activity after addition of easily decomposable organic carbon. These gaseous C losses follow the previous C addition, which is not the case for CO2 emissions from fallow soil.
Soil water content (N2O), soil temperature (CO2) and dissolved organic carbon (N2O and CO2) were the dominant causal factors for greenhouse gas emissions. Particularly DOC is suggested as an appropriate indicator for cover crop induced ecosystem dynamics related to the carbon and nitrogen cycle.
From these findings, it is suggested that cover cropping as an agro-environmental measure does not compromise climate change mitigation in agriculture. However,
Results of mixed model analysis of variance (F-statistics and p-value of main effects and interactions) for greenhouse gas emissions. Significant effects (in case of significant interactions, highest order interaction) are marked in bold.Tabelle 2. Ergebnis der Varianzanalyse (gemischtes Model; F-Werte und p-Werte der Haupteffekte und ihrer Wechselwirkungen) für Treibhausgasemissionen. Signifikante Effekte (bei signifikanten Interaktionen, die Interaktion höchster Ordnung) sind fett gekennzeichnet.
Site refers to experimental location, date to measurement date, N is N fertilization treatment, CC is soil cover treatment, Rep is replication.
|Site × Date||1.53||0.2290||9.68|
|Site × N||2.98||0.0922||1.21||0.2782|
|Date × N||0.00||0.9966||3.16||0.0553|
|Site × Date × N||0.05||0.9541||1.51||0.2345|
|Site × CC||0.31||0.8716||0.25||0.9090|
|Date × CC||1.81||0.0967||2.84|
|Site × Date × CC||0.4||0.9137||0.78||0.6188|
|N × CC||1.14||0.3506||1.19||0.3325|
|Site × N × CC||0.68||0.6070||0.19||0.9397|
|Date × N × CC||1.50||0.1825||1.79||0.1018|
|Site × Date × N × CC||0.66||0.7226||0.16||0.9954|
|Date × Rep||1.18||0.3311||0.88||0.4856|
Regression relations between soil chemical and physical parameters and greenhouse gas emissionsTabelle 3. Regressionsbeziehungen bodenchemischer und bodenphysikalischer Parameter mit Treibhausgasemissionen
|Pötting||Soil mineral N vs CO2||y = -4.36 + 0.57x||0.32||0.028|
|DOC vs N2O||y = -8.82 + 0.37x||0.41||0.046|
|Soil water content vs. N2O||y = -16.56 + 0.52x||0.39||0.013|
|Lichtenwörth||DOC vs. N2O||y = -5.21 + 0.26x||0.58||0.011|
|Soil water content vs. CO2||y = -14.11 + 0.83x||0.41||0.011|
|Soil water content vs. N2O||y = -24.63 + 1.04x||0.56||0.001|
Overview of measured parameters, methods and sampling datesTabelle 1. Überblick über die gemessenen Parameter, die Methoden und Beprobungstermine
Sampling dates at the two sites were ± 2 days.
|Aboveground biomass||Dry matter at 105°C||14 November 2012|
|CN ratio||CNS analyzer||-|
|CO2, N2O||Closed chamber method||22 November 2012, 1 February 2013, 6 March 2013|
|Soil mineral N||Photometric||22 November 2012, 1 February 2013, 6 March 2013|
DOC was measured from a mixed soil sample of three replicates.
|Photometric||22 November 2012, 1 February 2013, 6 March 2013|
|Soil water content||Capacitance||22 November 2012, 1 February 2013, 6 March 2013|
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