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2. Materials & Methods We used a sandy soil (Braunschweig, Germany) with 80% water filled pore space and flushed the headspace with N2 to achieve denitrifying conditions. N2O produced by fungi or bacteria was quantified in incubation experiments using the same selective inhibitors for bacteria and fungi as used in SIRIN. The following four treatments were tested: a) control without growth inhibition, b) inhibition of bacterial growth, c) inhibition of fungal growth and d) inhibition of bacterial and fungal growth. In a full factorial design, this was combined in two variants with N supplied as 15Nlabelled or non-labelled NO3- fertilizer. In addition all treatments were analyzed with and without blocking the N2O reduction by acetylene. Production of N2O was determined in all treatments. The non-labelled treatments with selective inhibition were used to determine SP of fungal and bacterial N2O, respectively. Isotopic signatures of N2O in the non-labelled treatments were used to estimate isotope effects of N2O production by fungal and bacterial denitrifiers. In the treatments with acetylene addition N2O reduction was blocked to determine the isotope effect of the NO3- to -N2O step and thus avoiding isotope effects by N2O reduction to N2. For the treatments without acetylene addition, 15N2 analysis in the 15N-labelled variant was conducted to estimate the impact of N2O reduction on isotopic signatures of N2O in the non-labelled treatments.
3. Results & Discussion The respiratory fungal/bacterial ratio indicated domination of fungi. Net N2O production was highest in the treatment without any inhibitor (control) followed by the treatment with bacterial growth inhibition showing that fungal N2O fluxes were relevant. Treatments with both inhibitors (N2O production of uninhibited organisms) yielded lowest N2O production. Using acetylene in the non-labelled treatments yielded higher N2O production than without acetylene with highest effect in bacterial dominated treatments (70% increase in N2O production), whereas the other treatments exhibited lower and relatively similar effects (42 to 47% increase in N2O production).
Currently, isotope analysis of gas samples is conducted. Based on this, we will calculate isotopologue signatures of fungal and bacterial N2O. These results will be presented and discussed.
References Anderson, J.P.E. and Domsch K.H. 1975. Measurement of bacterial and fungal contributions to respiration of selected agricultural soils. Canadian Journal ofMicrobiology 21, 314-322.
Frame C-H. and Casciotti, L. 2010. Biogeochemical controls and isotopic signatures of nitrous oxide production by a marine ammonia-oxidizing bacterium. Biogeosciences 7, 2695-2709.
Shoun, H., Kim, D.-H., Uchiyama, H. and Sugiyama, J. 1992. Denitrification by fungi. FEMS Microbiology Letters 94, 277-282.
Sutka R.L., Ostrom, N.E., Ostrom, P.H., Breznak, J.A., Gandhi, H., Pitt, A.J. and Li, F. 2006. Distinguishing Nitrous Oxide Production from Nitrification and Denitrification on the Basis of Isotopomer Abundances. Applied And Environmental Microbiology, 638-644.
Sutka, R.L., Adams, G.C., Ostrom, N.E.and Ostrom, P.H. 2008. Isotopologue fractionation during N2O production by fungal denitrification. Rapid Communication in Mass Spectrometry 22, 3989-3996.
Well R., Kurganova, I., Lopes de Gerenyu, V. and Flessa, H. 2006. Isotopomer signatures of soil-emitted N2O under different moisture conditions—A microcosm study with arable loess soil. Soil Biology & Biochemistry 38, 2923-2933.
Nitrogen Workshop 2012
Do cover crops affect leaching and soil accumulation of salt and mineral N?
Gabriel, J.L.a, Almendros, P.b, Quemada, M.a a Dpto. Producción Vegetal: Fitotecnia, ETS Ingenieros Agrónomos, Universidad Politécnica de Madrid, Avda.
Complutense s/n, 28040 Madrid, Spain b Dpto. Química Agrícola, ETS Ingenieros Agrónomos, Universidad Politécnica de Madrid
1. Background & Objective Nitrate leaching beyond the root zone increases water contamination hazards and decreases crop available N. Using cover crops instead of leaving the land fallow is an alternative to reduce nitrate contamination in the vadose zone, as cover crops reduce soil mineral N acummulation and drainage.
Cover crops may also enhance soil aggregate stability, and water retention capacity, two important characteristics in irrigated land. However, reducing drainage below the root system, by increasing evapotranspiration, could lead to soil salt accumulation. Salinity has already affected more than 80 million ha of arable land in many areas of the world (FAOSTAT, http://www.fao.org/nr/water/aquastat/main/index.stm), and in the Mediterranean region is one of the principal causes for yield reduction and land degradation. Few studies address both related problems simultaneously; therefore, a long-term evaluation of the potential effect on soil salinity and nitrate leaching is necessary to ensure that advantages of cover cropping are not compensated by potential disadvantages that could originate from soil salt accumulation.
2. Materials & Methods The soil salinity and nitrate leaching evaluation is based on studies conducted over 4 years in a semiarid irrigated agricultural area of Central Spain. Three treatments were studied: barley (Hordeum vulgare L.); vetch (Vicia villosa L.), and; fallow during the intercropping period of maize (Zea mays L.). Cover crops were killed in late winter allowing seeding of maize of the entire trial in early spring, and all treatments were irrigated and fertilised following the same procedure. Soil salt and nitrate accumulation was determined along the soil profile before maize sowing. Soil analysis was conducted in samples from four 1.2 m deep holes per plot and at 6 depth intervals (every 0.20 m). The electrical conductivity of the saturated paste extract was measured in each soil sample with a conductimeter (Rhoades, 1996). Soil mineral nitrogen (Nmin) was determined from the sum of nitrate and ammonium concentrations in 1M KCl soil sample extracts, obtained by spectrophotometry (Gabriel and Quemada, 2011). During the whole experiment, daily soil water content measurements from calibrated capacitance probes (Gabriel et al., 2010) were used to calculate drainage at 1.2 m depth, and applying a numerical model based on the Richards water balance equation (Vanclooster et al., 1996).
3. Results & Discussion Our results showed that when irrigation water was adjusted to crop needs, drainage during the irrigated period was minimized (Figure 1) which led to an accumulation of soil salt and nitrate on the upper layers after maize harvest. Salt and nitrate leaching occurred mainly during the intercrop period. In cover crop treatments, the drainage period was shorter, and the amount of drainage water and nitrate and salt leached were lower than in the fallow. This effect led to a larger nitrate accumulation in the upper layers of the soil after cover crop treatments than after fallow. However, soil salt accumulation did not increase in treatments with cover crops, and even decreased in years with a large cover crop biomass production (Figure 2, April 2008 and 2010).
Figure 1. Drainage (NO3- + NH4+) and salt leaching for the various treatments from October 2006 to April 2010.
Figure 2. Distribution of soil Nmin (kg N ha-1) and saturated paste extract soil electrical conductivity (S m-1) by depth at the end of the cover crop growing season (maize sowing), as influenced by the cover crop treatment.
4. Conclusion Adoption of cover crops in this irrigated cropping system reduced water percolation beyond the root zone; as a consequence salt and nitrate leaching diminished but did not lead to salt accumulation in the upper soil layers.
Financial support by CICYT (AGL2008-00163/AGR) and CAM (AGRISOST, S2009/AGR1630).
References FAOSTAT. Aquastat, http://www.fao.org/nr/water/aquastat/main/index.stm (verified on March 26th 2012).
Gabriel, J.L., Lizaso, J.I. and Quemada, M. 2010. Laboratory versus field calibration of Capacitance Probes. Soil Science Society of America Journal 74, 593-601.
Gabriel, J.L. and Quemada, M. 2011. Replacing bare fallow with cover crops in a maize cropping system: Yield, N uptake and fertiliser fate. European Journal of Agronomy 34, 133-143.
Rhoades, J.D. 1996. Salinity: electrical conductivity and total dissolved solids. In D.L. Sparks (ed.) Methods of soil analysis. Part 3. Chemical methods. SSSA Book series no. 5. ASA and SSSA, Madison, WI, US. pp. 417-435.
Vanclooster, M., Viaene, P., Diels, J. and Christiaens, K. 1996. WAVE: a mathematical model for simulating water and agrochemicals in the soil and vadose environment. En: Reference and user’s manual (Release 2.0), Institute for Land and Water Management, Katholieke Universiteit Leuven, Belgium.
Nitrogen Workshop 2012
Does groundwater level determine GHGs emissions from fertilized soil?
Cocco E.a, Morari F.a, Bertora C.b, Grignani C.b, Delle Vedove G.c, Polese R.a, Berti A.a, a Department of Environmental Agronomy, University of Padova, Italy b Department of Agronomy, Forestry and Land management, University of Torino, Italy.
c Department of Agriculture and Environmental Sciences, University of Udine, Italy
1. Background & Objectives Agriculture generates approximately 10-12% of the total greenhouse gases (GHGs) with major contributions in terms of N2O emissions (Snyder et al, 2009). Fluxes of GHGs are affected by water content in soil. Rainfall, irrigation and groundwater level affect denitrification and the subsequent production of N2, NO, N2O. The lysimeter study here presented aims to evaluate the influence of groundwater level on GHG emissions (CO2, CH4 and N2O) from soil receiving organic and mineral fertilization.
2. Materials & Methods The experiment (26/6/2011- 2/11/2011) was conducted in the Veneto Region (NE Italy) in 12 loamy-soil drainage lysimeters (1 x 1 m2 width x 1.5 m depth) cropped with maize (Zea mays L.).
Overall precipitation and irrigation during the monitored period were 1100 mm y-1.The factorial combination of three shallow water table levels (free drainage, 60 cm and 120 cm depth) with two levels of N input (250 and 368 kg ha-1 y-1) was compared. The experimental layout was completely randomised with two replicates. Fertilisation consisted in a mix of beef manure and poultry litter (for M treatments) at two doses (170 and 250 kg N ha-1 y-1) incorporated before crop sowing, integrated with top-dressed urea (U) at 80 kg N ha-1 and 118 kg N ha-1, respectively. GHG flux rates from soil were measured using an automatic close dynamic chamber system (12 chambers) (Delle Vedove et al., 2007). Chambers closed for measuring CO2 concentration six times per day. During the sampling air was forced to circulate between the chamber and an infrared gas analyser (IRGA, SBA-4, P-Systems): 150 measures of CO2 concentration (one every second) were performed during every closure. A non-linear regression between CO2 and time was used to establish the increase of CO2 concentration in every chamber.
N2O and CH4 concentration were obtained, on a daily basis, the first five days after fertilization and every two weeks for the remaining test-time. Chambers, in this case, were connected with an autosampler and air from chamber was stored in vials for N2O and CH4 analysis by gas chromatography.
Three measures were taken for every closure (at the closure, 20 min and 50 min from the closure) :
a linear model was preferred in this case for calculating N2O and CH4 fluxes. GHG daily emissions were tested with Kruskal-Wallis ANOVA.
3. Results and Discussion Measured CO2 fluxes represented the sum of autotrophic and heterotrophic respiration. An increase in CO2 fluxes occurred a few days after fertilization and lasted 15 days. Values ranged from 2 to 10 µmol CO2 m-2 s-1 for low N input and from 2 to 14 µmol CO2 m-2 s-1 for high N input. Total emissions of CO2 during the monitored period are shown in Table 1. Nitrous oxide fluxes started to be detectable three days after fertilization, in occurrence of the first irrigation (Figure 1). The largest fluxes were observed after the second urea application when very high soil temperature (up to 36°C in those days) occurred. Methane fluxes were not detectable. CO2 fluxes were significantly affected by the presence of groundwater level while N2O emissions (kg ha-1 d-1) appear to be constant between treatments.
4. Conclusion Contrasting interactions of agronomic practices, soil and meteorological conditions affected results.
A longer monitoring period will be necessary to highlight the potential effects of groundwater regimes on GHG emissions.
References Synder C.S., Bruulsema T.W., Jensen T.L. and Fixen P.E. 2009. Review of greenhouse gas emissions from crop production systems and fertilizer management effects. Agricolture, Ecosystems and Environment 133, 247-266.
Delle Vedove G., Alberti G., Zuliani M., Peressotti A., Inglima I. and Zerbi G., 2007. Automated monitoring of soil respiration: an improved automatic chamber system. Italian journal of Agronomy 4, 377-382.
Nitrogen Workshop 2012
Dynamic of ammonia emission from urea spreading in Po Valley (Italy): relationship with nitrogen compounds in the soil Carozzi, M.a, Ferrara R.M.b,c, Acutis M.a, Rana G.b a University of Milan, Department of Plant Production, Milan, Italy b CRA - Research Unit for Agriculture in Dry Environments, Bari, Italy c CRA - Research Centre for Agrobiology and Pedology, Florence, Italy