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2006-2011 Mission Kearney Foundation of Soil Science: Understanding and Managing Soil-Ecosystem

Functions Across Spatial and Temporal Scales Progress Report: 2007009, 1/1/2008-12/31/2008

*Principal Investigator University of California, Berkeley

The Production and Isotope Composition of Soil N2O Along Gradients of Climate and Time Ronald Amundson* and Chloë Lewis

Project Objectives (1) Development of analytical and numerical models of soil N2O production, consumption and transport; (2) compilation of the few measurements of N2O in situ or in unmodified soil cores in California (see fig. 6 and table 1); (3) compilation of N2O measurements elsewhere that can be compared to California soils.

Approach We have developed an analytical model to simulate N2O and δ15N–N2O profiles in the soil with diffusive transport and depth-dependent consumption and production:

(1)

where N(z,t) is the concentration of 44(N2O) or 45(N2O) [mol cm-3], and for either molecule Ds is its diffusivity in a particular soil [cm2 s-1], φ(z) the consumption rate [0%-100% s-1] and ρ(z) the production rate [mol cm-3 s-1]. To describe isotope ratios of N and O in soil N2O, the profiles of 44(N2O) and 45(N2O) are calculated independently and then combined to derive the ratios. Fractionation factors for 44(N2O) and 45(N2O) during production and consumption are taken from laboratory incubations, e.g., Yoshida (1988); Toyoda et al. (2005). Equation (1) can be directly solved for N(z,t) for a limited range of functions φ and ρ. Additionally, for the condition of steady state, there are still more φ, ρ for which N(z) is known (e.g., Farlow, 1993). While these solutions are useful for certain questions, they are not sufficient to describe all the N2O-reaction hypotheses we would like to test, so we wrote a numerical model of Equation (1) that allows a wider range of Ds, φ, and ρ. With the numerical model, we can examine time-dependent processes and spatial and temporal variations in N2O production and consumption, diffusivity, etc. The numerical model is programmed in Python, using the NumPy library for numerical computing, and complete code files will be made available at the conclusion of the project.

At this stage, we are focusing on model descriptions of total soil N2O and N isotopes. Oxygen isotopes are not presently being modeled because δ18O effects of N2O production and consumption are likely to be obscured by exchanges with H2O (Kool et al. 2005). Understanding δ18O-N2O therefore requires knowing δ18O-H2O, which in turn is affected by rainfall and evaporation. Thus, we will delay the exploration of the more complex O signal until a later time, first extending our efforts to the application of the model to existing and proposed new field data.

!

"N(z ,t)"t

= Ds

" 2 N(z ,t)"z 2

# $(z )N(z ,t)+ %(z )

The Production and Isotope Composition of Soil N2O Along Gradients of Climate and Time—Amundson

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N2O fluxes measured in surface chambers represent a highly integrated snapshot of soil N processes. Some key questions which we wished to explore are: 1. how rapidly does soil N2O flux approach a steady state after disturbance? 2. how do depth variations in φ or ρ change net flux at the soil surface? 3. do depth variations in φ and ρ impact the δ15N–N2O values within the soil profile? Can δ15N–

N2O profiles suggest or rule out some depth variations in biological processes?

Results The attached figures 1-5 show the results of five numerical experiments. In each figure, plot (a) is the [N2O] profile and plot (b) the δ15N –N2O profile. Plotted lines get darker as the profile relaxes to steady state. Boundary conditions and details of φ, ρ are in table 2.

Figure 1 answers question 1 for an extremely simple situation: a sterile soil with an elevated level of [N2O] degasses and equilibrates with the atmosphere. Given the soil permeability in table 2, the soil takes about two days to equilibrate, giving us some perspective on relaxation rates after N2O perturbations, such as fertilizations or rain events. At every depth, [N2O] decreases smoothly to the atmospheric value. However, the isotopic profile has an initial, near-surface diffusive enrichment of about 0.4 ‰ that is translated to greater depths with time, before decreasing back to atmospheric δ15N –N2O. This simulation was also addressed analytically, allowing us to verify the time and concentration solutions of the numerical model.

Figures 2 and 3 address the response of soil N2O profiles to variations in consumption profiles. In these two figures, ρ is the same, and the total potential consumption (φ integrated through the soil profile) is the same. However, in figure 2, φ declines exponentially with depth, while in figure 3, it is greatest in mid-profile (see table 2). Because actual consumption φN is a function of concentration at each depth, we see feedback functions: high [N2O] is consumed at a greater rate, so regions of higher [N2O] lose N2O more rapidly and experience stronger consumption-discrimination effects. In figure 2, φ and ρ are in nearly the same ratio through the profile, so this effect is weak: most consumption is a direct response to local production. However, with the same total potential consumption in figure 3, the soil is near the transition to a net sink, with consumption deep in the profile creating a concentration gradient that draws N2O downward. The steady-state surface flux of N2O is 1.32e-14 mol N2O cm-2 s-1 for figure 2 and 1.18e-12 mol N2O cm-2 s-1 for figure 3, a difference caused entirely by the shape of the N2O consumption function, not its magnitude.

Figures 4 and 5 vary only in the depth of the soil. The same total potential φ and total production ρ, with the same distributions, are spread through 100cm in figure 4 and 600cm in figure 5. The thicker soil ‘insulates’ the interior processes from diffusion to the atmosphere, so that more N2O is consumed and the lower boundary of figure 5 has lower [N2O] than the lower boundary of figure 4. At the base of the deep profile, where there is almost no production, most N2O has passed the ‘filter’ of maximum consumption in mid-soil. 44N2O is consumed slightly faster than 45N2O, so the N2O at the base of the profile is enriched by 2‰. Near the surface, where diffusion from the atmosphere is dominant, N2O is depleted by 0.02‰.


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Discussion Previous research has assumed that the depth profiles of N2O and its isotopes provide insight into the balance between production and consumption (Perez et al. 2000; van Groenigen et al. 2005), but there has not been a convenient mathematical means to decipher these relations. Our numerical models now allow us to design experiments to explore how changes in processes impact measurable soil gas values. In the tests of the model shown here, we sampled a subset of the possible field scenarios. We are currently comparing existing profile measurements of N2O and δ15N-N2O with numerical experiments . Where model results (using reported parameters in the papers) cannot agree with observations, we can then test the role of other likely factors: for instance, if Ds is not constant with depth, or production or consumption change with both depth and time. N2O concentrations combined with isotopes provide constraints on the value of important processes, and the models allow us to disentangle these processes based on field measurements.

Our ultimate goal is to explain and predict N2O in California soils, by adding observations along well-designed environmental or management gradients. This model-driven sampling and interpretation approach may allow a more general understanding of environmental controls on N2O and a more accurate global projection using available soil and climatic variables.

References Balser, T. C. and M.K. Firestone. 2005. Linking microbial community composition and soil

processes in a California annual grassland and mixed-conifer forest. Biogeochemistry, 73:395–415.

Burger, M., L.E. Jackson, E.J. Lundquist, D.T. Louie, R.L. Miller, D.E. Rolston, and K.M. Scow. 2005. Microbial responses and nitrous oxide emissions during wetting and drying of organically and conventionally managed soil under tomatoes. Biology and Fertility of Soils, 42: 109–118.

Delwiche, C.C., S. Bissell, and R. Virginia. 1978. Soil and other sources of nitrous oxide. In: Nitrogen in the environment, Volume I, Nitrogen behaviour in the field soil, pp: 459–476.

Fenn, M.E., M.A. Poth, and D.W. Johnson. 1996. Evidence for nitrogen saturation in the San Bernardino Mountains in Southern California. Forest Ecology and Management, 82: 211–230.

Hungate, B., C. Lund, H. Pearson, and F. Chapin. 1997. Elevated CO and nutrient addition after soil N cycling and N trace gas fluxes with early season wet-up in a California annual grassland. Biogeochemistry, 37:89–109.

Hungate, B.A., C.P. Lund, H.L. Pearson, and F. Chapin. 1996. CO-2 alters soil N cycling and trace gas fluxes with early-season rains in a California grassland. Bulletin of the Ecological Society of America, 77:207.

Jackson, L.E., F.J. Calderon, K.L. Steenwerth, K.M. Scow, and D.E. Rolston. 2003. Responses of soil microbial processes and community structure to tillage events and implications for soil quality. Geoderma, 114:305–317.


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Jackson, R.D., B. Allen-Diaz, L.G. Oates, and K.W. Tate. 2006. Spring-water nitrate increased with removal of livestock grazing in a California oak savanna. Ecosystems, 9:254–267.

Kong, A.Y.Y., S.J. Fonte, C. van Kessel, and J. Six. 2007. Soil aggregates control n cycling efficiency in long-term conventional and alternative cropping systems. Nutrient Cycling In Agroecosystems, 79: 45–58.

Kool, D.M., N. Wrage, O. Oenema, J. Dolfing, and J.W.V. Groenigen. 2007. Oxygen exchange between (de)nitrification intermediates and H2O and its implications for source determination of NO 3 and N2O: a review. Rapid Communications in Mass Spectrometry, 21: 3569–3578.

Maggi, F., C. Gu, W.J. Riley, G.M. Hornberger, R.T. Venterea, T. Xu, N. Spycher, C. Steefel, N.L. Miller, and C.M. Oldenburg. 2008. A mechanistic treatment of the dominant soil nitrogen cycling processes: Model development, testing, and application. Journal of Geophysical Research-Biogeosciences, 113 (G2).

Perez, T., S.E. Trumbore, S.C. Tyler, E.A. Davidson, M. Keller, and P.B. de Camargo. 2000. Isotopic variability of NO emissions from tropical forest soils. Global Biogeochemical Cycles, 14: 525–535.

Poth , M.A. and I.C. Anderson. 1989. Semiannual losses of nitrogen as nitric oxide and nitrous oxide from unburned and burned chaparral. Global Biogeochemical Cycles, 3: 121–136.

Rolston, D.E., M. Fried, and D.A. Goldhamer. 1976. Denitrification Measured Directly from Nitrogen and Nitrous Oxide Gas Fluxes. Soil Science Society of America Journal, 40:259–266.

Rolston, D.E., D.L. Hoffman, and D.W. Toy. 1978. Field Measurement of Denitrification: I. Flux of N2 and N2O. Soil Science Society of America Journal, 42:863–869.

Rolston, D.E., A.N. Sharpley, D.W. Toy, and F.E. Broadbent. 1982. Field Measurement of Denitrification: III. Rates During Irrigation Cycles. Soil Science Society of America Journal, 46:289–296.

Rudaz, A.O., E.A. Davidson, and M.K. Firestone. 1991. Sources of nitrous-oxide production following wetting of dry soil. FEMS Microbiology Letters, 85:117–124.

Ryden, J. and L. Lund. 1980. Nitrous Oxide Evolution from Irrigated Land. Journal of Environmental Quality, 9(3): 387.

Ryden, J.C., L.J. Lund, and D.D. Focht. 1978. Direct In-field Measurement of Nitrous Oxide Flux from Soils. Soil Science Society of America Journal, 42:731–737.

Toyoda, S. , H. Mutobe, H. Yamagishi, N. Yoshida, and Y. Tanji. 2005. Fractionation of NO isotopomers during production by denitrifiers. Soil Biology and Biochemistry, 37: 1535–1545.

Van Groenigen, J.W., K.B. Zwart, D. Harris, and C. van Kessel. 2005. Vertical gradients of N and O in soil atmospheric NO–temporal dynamics in a sandy soil. Rapid Communications in Mass Spectrometry, 19:1289–1295.

Venterea, R. and D. Rolston. 2000. Nitric and nitrous oxide emissions following fertilizer application to agricultural soil: Biotic and abiotic mechanisms and kinetics. Journal of Geophysical Research-Atmospheres, 105 (D12):15117–15129.

Yoshida, N. 1988. N-depleted NO as a product of nitrification. Nature, 335:528–529.


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Table 1: California soils with N2O data sets. The next phase of the work will be to determine the sites’ total N, MAT, MAP, and other relevant geological constraints.

Reference Location Lat Long Soil type Details

Fenn et al, 1996

San Bernardino Mts 34.17 -116.87

coarse-loamy, mixed, frigid, Xerumbrepts and Xerochrepts

Fenn et al, 1996

San Bernardino Mts 34.236 -117.32

coarse-loamy, mixed, mesic Ultic Haploxerolls

Balser and Firestone, 2005 Fallbrook 33.37 -117.25 Mollic Haploxeralfs,

Oak-grass savannah

Balser and Firestone, 2005 Musick 38.07 -120.78 Ultic Haploxeralfs Conifer forest Burger et al., 2005 LTRAS 38.541 -121.88 Yolo silt loam

Irrigated; organic and conventional

Hungate et al., 1997

Jasper Ridge 37.4 -122.22

sandstone-derived grassland

Increased and ambient CO2 treatments

Jackson et al., 2006 SFREC 39.3 -121.4

Ruptic-Lithic Xerochrepts or Mollic Haploxeralfs Wetland

Rolston et al., 1982 Davis 38.5 -121.7

fine-silty, mixed, nonacid, thermic, typic Xerorthents

Rudaz et al., 1991

UC Sierra Foothills Range Station 39.3 -121.4 Argonaut silt loams, Mollic Haploxeralfs

Ryden et al., 1978 Simas 34.96 -120.64 Haploxeroll Celery crop Venterea and Rolston, 2000

Sacramento County 38.4 -121

moderately acidic loam soil Tomato crop

Kong et al., 2007 CIFS 38.54 -121.87

Yolo silt loam and Rincon silty clay loam


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Table 2: Parameters used in all models Constant Value Units Comments Air-filled pore space 0.3

Between 0 and 1 Same in all models

Permeability 0.012 cm2 Same in all models

Surface value of [N2O] 1.31� 10-9 mol cm-3

Standard atmospheric value; same in all models

Flux at lower boundary 0 mol cm-2 s-1 Same in all models

RP: ratio of rare/heavy N2O produced 3.5� 10-3 Ratio

Derived from ε in Yoshida et al. (1998) and assumption of 60% from nitrification, 40% from denitrification

Rc: ratio of rare/heavy N2O consumed 3.4� 10-3 Ratio

Derived from ε in Barford et al. (1999)

ρ , 44N2O 1.12� 10-15(exp(-z/37)) mol cm-3 s-1 Figures 2,3

ρ , 45N2O 3.91� 10-18(exp(-z/37)) mol cm-3 s-1 Figures 2,3

φ, 44N2O 4.06� 10-5(exp(-z/ 57)) Between 0 and 1

Figure 2, with consumption decreasing exponentially

φ, 45N2O 4.04� 10-5(exp(-z/ 57)) Between 0 and 1 As above

φ, 44N2O 3� 10-5 - 1.2� 10-8� (z - 50 ) 2 Between 0 and 1

Figure 3, consumption maximum at 50 cm; a parabola

φ, 45N2O 2.98� 10-5 - 1.2� 10-8� (z - 50 ) 2 Between 0 and 1 As above

ρ , 44N2O 1.86� 10-16(exp(-z/222)) mol cm-3 s-1 Figure 4

ρ , 45N2O 6.51� 10-19(exp(-z/222)) mol cm-3 s-1 As above

φ, 44N2O 5� 10-6 - 5.6� 10-11 � (z - 300 ) 2 Between 0 and 1

Figure 4, consumption maximum at 300 cm; a parabola

φ, 45N2O 4.98� 10-6- 5.6� 10-11 � (z - 300 ) 2 Between 0 and 1 As above


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Figure 1: Model simulation of a soil with an initially high concentration of [N2O] at time 0. There is no production or consumption, and the soil relaxes to steady state with the atmosphere for both total N2O (a) and its δ15N value (b).


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Figure 2: Model simulation of a soil which is filled with atmospheric N2O at time 0. ρ and φ both decrease exponentially with depth, φ more slowly than ρ (see table 2). The soil relaxes to a steady state profile in which [N2O] increases with depth and δ15N-N2O decreases with depth. It is a net source of N2O to the atmosphere at 1.32e-14 mol N2O cm-2 s-1.


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Figure 3: Model simulation of a soil which is filled with atmospheric N2O at time 0. ρ is the same as in figure 2. The total potential consumption in the soil (φ integrated through the profile) has the same value as total potential consumption in figure 2, but in this case φ(0) = 0 and φ(100)=0; the maximum potential consumption is at 50 cm. The soil relaxes to a steady state profile with [N2O] higher than atmospheric values in the upper soil and lower than atmospheric values in the lower soil. δ15N –N2O decreases slightly with depth. Although this soil produces exactly as much N2O as the soil in figure 2, the steady state flux to atmosphere is two orders of magnitude greater, 1.18e-12 mol N2O cm-2 s-1.


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Figure 4: Model simulation of a soil which is filled with atmospheric N2O at time 0. ρ is the same as in figure 2. The total potential consumption in the soil (φ integrated through the profile) is greater than total potential consumption in figure 2, and φ(0) = 0 and φ(100)=0; the maximum potential consumption is at 50 cm. The soil relaxes to a steady state profile with [N2O] lower than atmospheric values and negative surface flux, -1.97e-12 mol cm-2 s-1; it is a net sink for N2O. δ15N –N2O decreases measurably with depth.


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Figure 5: Model simulation of a soil which is filled with atmospheric N2O at time 0. This soil is 600cm deep; all other soils modeled are 100cm deep. Total ρ is the same as in figure 4, and as in figure 4 ρ decreases exponentially with depth. The total potential consumption in the soil (φ integrated through the profile) is equal to the total potential consumption in figure 4, and φ(0) = 0 and φ(100)=0; the maximum potential consumption is at 300 cm. The soil relaxes towards a steady state profile with [N2O] lower than atmospheric values and negative surface flux; it is a net sink for N2O. δ15N –N2O decreases in the upper 80cm of the soil and increases to a 2 ‰ enrichment at the lower boundary.

Figure 6: Locations of published N2O fluxes for California.


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This research was funded by the Kearney Foundation of Soil Science: Understanding and Managing Soil-Ecosystem Functions Across Spatial and Temporal Scales, 2006-2011 Mission (http://kearney.ucdavis.edu). The Kearney Foundation is an endowed research program created to encourage and support research in the fields of soil, plant nutrition, and water science within the Division of Agriculture and Natural Resources of the University of California.

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