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571
Chapter 18. DAYCENT Simulated Effects of Land Use
and Climate on County Level N Loss Vectors
in the USA
S.J. Del Grosso
a
,b
, W.J. Parton
b
, D.S. Ojima
b
, C.A. Keough
b
,
T.H. Riley
b
, and A.R. Mosier
c
a
USDA-ARS, Soil-Plant-Nutrient Research Unit, Fort Collins,
CO, USA
b
Natural Resource Ecology Laboratory, Colorado State University,
Fort Collins, CO, USA
c
1494 Oakhurst Dr., Mount Pleasant, SC 29466, USA
We describe the nitrogen (N) gas (NH
3
, NO
x
, N
2
O, N
2
) emission and NO
3
leaching submodels used in the DAYCENT ecosystem model and demonstrate
the ability of DAYCENT to simulate observed N
2
O emission and NO
3
leaching
rates for various sites representing different climate regimes, soil types, and land
uses. DAYCENT simulated seven major crops, grazing lands, and potential native
vegetation at the county level for the United States. At the national scale, NO
3
leaching was the major loss vector, accounting for 86%, 66%, and 56% of total
N losses for cropped soils, grazed lands, and native vegetation, respectively. NH
3
volatilization NO
x
emissions made up the majority of national N gas losses,
accounting for 58%, 89%, and 86% of N gas losses from cropped soils, grazed
lands, and native vegetation, respectively. However, there was considerable spa-
tial variability in the N loss vectors, with leaching accounting for less than 20%
of total N losses and NO
x
NH
3
emissions accounting for less than 50% of N gas
losses in some counties. Land use area weighted mean annual N losses were 43.9
(SD 26.8) and 12.3 (SD 22.2) kg N/ha for cropped/grazed and native sys-
tems, respectively. Area weighted mean annual N gas losses were 11.8 (SD 4.8)
and 5.4 (SD 2.1) kg N/ha for cropped/grazed and native systems, respectively.
Total N losses and NO
3
leaching tended to increase as N inputs and precipitation
increased, and as soils became coarser textured. Total N gas losses also increased
with N inputs and as soils became coarser textured, but N
2
O and N
2
made up a
larger portion of N gas losses as soils became finer textured and as precipitation
increased.
Nitrogen in the Environment: Sources, Problems, and Management
J.L. Hatfield and R.F. Follett (Eds)
© 2008 Elsevier Inc. All rights reserved
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1 . INTRODUCTION
Flows of N between the atmosphere, soil, and biota strongly influence the car-
bon (C) cycle and atmospheric chemistry. Net primary productivity (NPP) is lim-
ited by N availability in most terrestrial ecosystems ( Vitousek and Howarth, 1991 ;
Vitousek et al., 2002 ) and N transformations in soils are a major source of N gas
emissions to the atmosphere ( Davidson and Kingerlee, 1997 ; Kroeze et al., 1999 ).
Nitrous oxide (N
2
O) is a long lived, important greenhouse gas ( Prather et al., 1995 ).
Nitric oxide (NO) and its oxidized counterpart, nitrite (NO
2
), (together referred
to as NO
x
) are major ozone regulators and limit the overall oxidizing capacity of
the troposphere ( Williams et al., 1992 ). Nitrate (NO
3
) leaching is a major N loss
vector for agroecosystems which contributes to aquatic eutrophication and can
pose a risk to human health. Human activity has profoundly altered fixation rates
of atmospheric N
2
, emission rates of N
2
O and NO
x
to the atmosphere, and losses
of NO
3
to waterways. The amount of reactive N induced into the biosphere from
fertilizer production, N-fixation in crops and fossil fuel combustion exceeds the
N fixed annually in natural systems ( Vitousek et al., 1997 ; Smil, 1999 ; Galloway
et al., 2003 ). Anthropogenic activities, mainly fossil fuel burning and agriculture,
are major sources of atmospheric NO
x
( Prather et al., 1995 ) while biogenic proc-
esses are the major source of N
2
O ( Kroeze et al., 1999 ). Agriculture is a primary
source of NO
3
leaching into waterways ( Howarth et al., 1996 ; Goolsby et al., 1999 ;
Boesch et al., 2001 ).
The atmospheric concentration of N
2
O has been well documented for current
and historical time periods ( Prather et al., 1995 ). In contrast, the amount of N in
soils and the biota, as well as the flows of N that contribute to the observed changes
in atmospheric N
2
O, cannot be measured directly on the global scale. Ecosystem
models are necessary to scale up results of plot sized experiments and calculate the
contributions of natural and managed systems to global N budgets. Simple empir-
ical models correlate N fluxes with N additions ( IPCC, 1997 ) or with soil water
content ( Davidson and Verchot, 2000 ). At the opposite extreme, highly mechanistic
models explicitly simulate the biological, physical, and chemical processes involved
in N transformations and flows ( Grant and Pattey, 2003 ; Grant, 2004 ). Simple
models tend to be over-generalized and cannot represent the heterogeneity of real
world systems while mechanistic models require detailed parameterization and
intensive computation. DAYCENT is an ecosystem model of intermediate com-
plexity; some processes are represented mechanistically but the model requires a
relatively small number of site specific parameters. In this chapter we begin with a
brief overview of the DAYCENT model and describe the N gas submodel of
DAYCENT in detail. Then we present comparisons of simulated and observed val-
ues of N gas emissions and NO
3
leaching to demonstrate the validity of DAYCENT.
Lastly, we use DAYCENT to compare annual N gas (NH
3
, NO
x
, N
2
O, and N
2
) and
NO
3
leaching losses associated with different land uses, soil textures, and water
inputs.
572 Nitrogen in the Environment
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2 . DAYCENT MODEL DESCRIPTION
DAYCENT ( Parton et al., 1998 ; Kelly et al., 2000 ; Del Grosso et al., 2001 )
is the daily time step version of the CENTURY model. CENTURY ( Parton et al.,
1994 ) operates on a monthly time step and was developed to simulate changes
in soil organic matter (SOM), plant productivity, nutrient availability, and other
ecosystem parameters in response to changes in land management and climate.
However, finer time scale resolution is required to simulate N gas emissions from
soils because the processes that result in N gas fluxes respond nonlinearly to impor-
tant controls such as soil water content. DAYCENT simulates exchanges of carbon,
nutrients, and trace gases among the atmosphere, soil, and plants as well as events
and management practices such as fire, grazing, cultivation, and organic matter or
fertilizer additions. To run DAYCENT for a particular site, soil texture, current and
historical land use, and daily maximum/minimum temperature and precipitation
data are required. Soil water content, temperature, mineral N concentration, trace
gas flux, and SOM decomposition are simulated on a daily time step while plant
growth is updated weekly.
DAYCENT ( Figure 1 ) includes submodels for plant productivity, decomposi-
tion of dead plant material and SOM, soil water and temperature dynamics, and
N gas fluxes. Flows of C and nutrients are controlled by the amount of C in the
various pools, the N concentrations of the pools, abiotic temperature/soil water fac-
tors, and soil physical properties related to texture. NPP is a function of nutrient
availability, soil water and temperature, shading, and vegetation type ( Metherell
et al., 1993 ). NPP is divided among leafy, woody, and root compartments based
on plant type. The root to shoot ratio of NPP allocation is a function of soil water
content and mineral N availability. The death rate of plant compartments is control-
led by soil water, temperature, season, and plant specific senescence parameters.
Structural detritus has a higher C:N ratio and is more difficult to decompose than
metabolic detritus. Recent improvements in the plant submodel include the ability
to make seed germination a function of soil temperature and plant harvest/senes-
cence a function of accumulated growing degree days. SOM is divided into three
pools based on decomposition rates ( Parton et al., 1993 ; 1994). Decomposed detri-
tal material that has a low C:N ratio flows to the active SOM pool, which includes
microbial biomass and the highly labile byproducts of decomposition that turnover
in approximately 1 year or less. The products of detrital decomposition that have
a wider C:N ratio flow to the slow SOM pool, which includes the relatively resist-
ant (10–50 year turnover rate) byproducts of decomposition. The passive SOM
pool consists of humus that is extremely resistant to further decomposition. As soils
become finer textured a lower portion of SOM is respired as CO
2
and more SOM
is retained in stable form due to physical and chemical protection. Decomposition
of SOM and external nutrient additions supply the nutrient pool, which is available
for plant growth and microbial processes that result in trace gas fluxes. Ammonium
(NH
4
) is modeled for the top 15 cm while nitrate (NO
3
) is distributed throughout the
DAYCENT Simulated Effects of Land Use and Climate on N Loss Vectors 573
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soil profile. Nutrients and SOM are concentrated near the soil surface and decrease
exponentially with depth. The land surface submodel of DAYCENT simulates water
flow through the plant canopy, litter and soil profile, as well as soil temperature
throughout the profile ( Parton et al., 1998 ; Eitzinger et al., 2000 ). Saturated water
flow is simulated down the soil profile on days that it rains, snow melts, or a field
is irrigated. Unsaturated flow is simulated on all days that do not have water inputs
sufficient to saturate the profile and can be up or down the profile depending on
Dead plant
material
Metabolic
Structural
PLANT
COMPONENTS
Leaves
Fine roots
Branches
Large wood
Large
roots
NO
3
NH
4
0–1cm
1–4cm
4–15cm
15–30cm
etc.
0–15 cm
SOM
Active
0.5 –1 year
Slow
10 – 50 year
Passive
1,000 – 5,000 year
H
2
O
soil
T
soil
0–1cm
1–4 cm
4–15 cm
15–30cm
etc.
N GAS
0–1 cm
1–4 cm
4–15 cm
15–30 cm
etc.
C:N
CO
2
S, R
h
PPT, V, L
N inputs
Death
Den
Nil
C:N
V
N uptake
S
C:N
CO
2
CO
2
NPP
S
S
S
H
2
O
soil
Soil water content
T
soil
Soil temperature
S Soil texture
C:N Carbon: Nitrogen ratio of material
V Vegetation type
SOM Soil organic matter
L Land use
R
h
Heterotrophic respiration
C, N flows
Feedbacks, information flows
Control on process
N GAS N
2
O, NO
X
, N
2
Processes designated by italics
Stom Stomatal conductance
Death Plant component death
Decomp Decomposition
N inputs N Fixation, N deposition, N fertilization
Nit Nitrification
Den Denitrification
N min N mineralization
ET Evapotranspiration
Decomp
Decomp
R
h
R
h
Stom
ET
N min
Figure 1 . Conceptual diagram of the DAYCENT ecosystem model. Modified from
Del Grosso et al. (2001) .
574 Nitrogen in the Environment
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DAYCENT Simulated Effects of Land Use and Climate on N Loss Vectors 575
matric and gravitational potentials. If water inputs are sufficient, given a soil texture
specific saturated hydraulic conductivity, excess water will not enter the profile and
is assumed to be runoff. Coarse textured soils are assumed to have higher saturated
conductivity than finer textured soils. As saturated conductivity increases, surface
runoff decreases and water and NO
3
flow down the profile increase. Soil water and
dissolved NO
3
that exit the deepest soil layer simulated are assumed to be leached
into ground water or the subsoil but the model does not simulate lateral transfer of
water or nutrients. DAYCENT has been shown to reliably model soil water con-
tent, N mineralization, and NPP for a shortgrass steppe in Colorado ( Kelly et al.,
2000 ). The SOM and N cycling submodels used in DAYCENT have been vali-
dated for various systems including grasslands and forests ( Kelly et al., 1997 ), as
well as agricultural soils in Sweden ( Paustian et al., 1992 ) and Oregon ( Parton and
Rasmussen, 1994 ).
The N gas submodel of DAYCENT ( Figure 2 ) simulates soil N
2
O and NO
x
gas emissions from nitrification and denitrification as well as N
2
emissions from
denitrification. Nitrifying microbes oxidize NH
4
to NO
3
, with some N
2
O and
NO
x
released during the intermediate steps. N gas flux from nitrification is assumed
to be a function of soil NH
4
concentration, water content, temperature, and
pH ( Parton et al., 1996, 2001 ). Nitrification rates increase linearly with soil NH
4
NH
4
NO
3
N gas
nit
N gas
denit
N
2
O
NO
x
N
2
H
2
O
soil
, T
soil
Texture, pH
D/D
0
PPT
H
2
O
soil
, C
Texture
D/D
0
NO
3
:C
Control
Italics Process
N gas
nit
N gas from nitrification
N gas
denit
N gas from denitrification
D/D
0
Index of gas diffusivity in soil
PPT Precipitation
C Labile carbon
Nitrification
Mineralization
N inputs
Denitrification
Figure 2 . The N gas flux submodel of DAYCENT. Modified from Del Grosso et al.
(2001) .
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576 Nitrogen in the Environment
concentration. Nitrification is limited by moisture stress on biological activity when
soil water-filled pore space (WFPS % relative saturation) is too low and by O
2
availability when WFPS is too high. Nitrification increases exponentially with tem-
perature and stabilizes when soil temperature exceeds the site specific average high
temperature for the warmest month of the year. Nitrification is not limited when pH
is greater than neutral but decreases exponentially as soils become acidic.
Denitrification is an anaerobic process in which heterotrophic microbes reduce
NO
3
to NO
x
, N
2
O, and N
2
. Denitrification is a function of soil NO
3
(e
accep-
tor) concentration, labile C (e
donor) availability, WFPS, and soil physical proper-
ties related to texture that influence gas diffusivity ( Parton et al., 1996 ; Del Grosso
et al., 2000 ). Denitrification increases exponentially with increasing soil NO
3
concentration when NO
3
concentration is low ( 50 ppm) and approximately lin-
early at higher NO
3
levels. Denitrification increases approximately linearly with
soil heterotrophic respiration, a proxy for labile C availability. No denitrification is
assumed to occur until WFPS values exceed 50–60%, then denitrification increases
exponentially until WFPS reaches 70–80% and it stabilizes as soil water content
approaches saturation. The model calculates N
2
N
2
O emissions from denitrifi-
cation by assuming that the process is controlled by the input (NO
3
, respiration,
WFPS) that is most limiting. N
2
O emissions are calculated from N
2
N
2
O gas
emissions and an N
2
:N
2
O ratio function. The ratio of N
2
:N
2
O gases emitted due
to denitrification is assumed to increase as the ratio of e
acceptor (NO
3
) to e
donor (labile C) decreases and as soil gas diffusivity and O
2
availability decrease.
N
2
O can act as an alternative e
acceptor and be reduced to N
2
when labile C is in
excess compared to NO
3
. D/D
0
, a relative index of gas diffusivity in soils, is cal-
culated as a function of WFPS and soil physical properties (bulk density and field
capacity) that influence gas diffusion rates using equations presented by Potter et al.
(1996) . As D/D
0
decreases, the residence time of N
2
O in soil increases, thus
increasing the probability that N
2
O will be further reduced to N
2
before diffusing
from the soil.
NO
x
emissions from soil are a function of total N
2
O emissions, a NO
x
/N
2
O
ratio equation, and a precipitation initiated pulse multiplier ( Parton et al., 2001 ).
Simulated N
2
O gas emissions from nitrification and denitrification are summed to
obtain total N
2
O flux. The NO
x
/N
2
O ratio is high (maximum of ⬃ 20) when D/D
0
is high and decreases to a minimum of ⬃ 1 as D/D
0
decreases. This is based on the
following observations. The majority of NO
x
emissions from soils are from nitri-
fication because NO
x
is highly reactive under the reducing conditions that facili-
tate denitrification ( Conrad, 1996 ). Total N gas flux is due primarily to nitrification
when soils are well aerated (high D/D
0
) and mainly to denitrification under anaero-
bic conditions ( Linn and Doran, 1984 ; Davidson, 1993 ). Thus, the model assumes
that NO
x
becomes a larger proportion of total N gas emissions as soil gas diffusiv-
ity increases. The modeled total N
2
O emission rate is multiplied by the ratio func-
tion to obtain a base NO
x
emission rate. The current version of DAYCENT includes
canopy absorption of soil NO
x
emissions as a function of leaf area index. The model
CH18-P374347.indd 576CH18-P374347.indd 576 5/31/2008 6:22:58 PM5/31/2008 6:22:58 PM