Introduction
Nitrogen is an essential element and one of the main factors limiting the
functioning and productivity of various soil-plant systems. This is
particularly the case in cropping-dominant systems, where annual crop
productivity often depends on rotations with N2-fixing legumes or
the
continuous addition of chemical fertilizer or organic matter. External N
enters the soil (e.g. atmospheric N deposition and fertilizer N) and plants
(e.g. N2 fixation) and cycles through them in various chemical
forms or states, mostly mediated by soil microbes. Mineralization
(ammonification), microbial immobilization, nitrification, and denitrification
determine the availability of NH4+ or NO3- that can
be taken up by plants or lost to the environment, which in turn contributes
to the regulation of terrestrial C sequestration
. Biotic and
abiotic transformations of N from mineralized soil organic matter or those derived
from external soil inputs are spatially and temporally variable. In addition,
different mineral forms of N (e.g. NH4+ and NO3-)
often show different distribution patterns and their relative importance in terms
of the contribution to total N stocks across a broad range of land uses and
management practices due to different climatic and ecological conditions
.
Managed soil, especially that used for agricultural production and grazing,
is often characterized by N imbalances and reactive N losses to the
environment . One of the
consequences of continuous cropping on the N cycle is the increased emissions
of ammonia, N oxides (NOx), and nitrous oxide
(N2O), mainly through N fertilizer application. Nitrous oxide is a
potent greenhouse gas and ozone-depleting substance, while
NOx produces ozone in the troposphere
. Other concerns include the leaching of
NO3- to groundwater, which may contribute to terrestrial and
coastal eutrophication . Accordingly, there are increasing
demands to measure or simulate the fate of residual mineral N across
agricultural areas as well as in the soil under native vegetation, which can
be conceptually linked to the loss of N to air and water upon land-use
conversion. Indeed, there is a strong need for large-scale soil information
from which one can accurately define current baselines and determine the state
of soil mineral N and its response to soil conditions. However, such
large-scale soil information is generally not available.
Soil mineral N contents can be highly variable and uncertain because multiple
reaction pathways and oxidation states of N processes exist
. Nitrogen transformation processes in soil are
controlled by the complex interactions of soil variables, such as substrate
availability, pH, and temperature and water content, which are affected by
ecological factors (i.e. soil, climate, vegetation and topography) and past
management history. In particular, soil properties related to the storage and
quality of soil organic matter and its management could affect the levels and
variation in soil NH4+ and NO3-
. Soil N transformations also involve the biogeochemistry
of other nutrients, such as C and P, which are key constituents of organic
molecules. In particular, regular N input into the soil, including plant N
returning to the soil as residues or decomposing roots, is important for the
maintenance of soil organic C (SOC) (therefore the availability of soil N
to plants) and closely interacts with the terrestrial organic C sink
. showed that N fertilizer
addition alone resulted in an increase in both SOC and total N, but the
combined addition of N and P had the opposite effect. Conversely, there are
studies showing that SOC can be depleted by N fertilizer application
. Overall, N cycling is closely linked to soil C
sequestration and stabilization, but C–N cycle coupling can be complicated
through changes in soil P. found that, globally, SOC
and the C:N ratio of soil organic matter are important controls of total N in
soil, although large uncertainties remain. Therefore, the effects of soil N
and P and their elemental interactions on mineral N dynamics are important
, but they have not been widely explored across
large spatial scales.
Differences in inherent soil properties as well as land use cause a shift
in dominant forms of soil N and its distribution across sites. Land uses are
generally characterized by vegetation types, dominant sources of soil N
input, and the levels of soil disturbance and often coincide with climate and
ecological conditions. Therefore, it may be possible to specifically compare
the patterns of mineral N across broad regions by land use. The amount of N
stored in soil in organic and mineral forms is considered a limiting factor
for the primary productivity of many ecosystems. How primary productivity is
managed affects the rate at which soil N and other essential nutrients are
replenished. Yet, there is often a long-term tendency of ecological
properties, such as biodiversity, to decline with external additions of
reactive N through atmospheric deposition and fertilizer inputs
. It is therefore important to determine soil mineral
N patterns and their controlling factors, but there are limited soil N data
available for understanding plant and soil processes at different scales.
Since primary soil controls on mineral N are largely unknown on the
continental scale of Australia, it is relevant to measure and understand how
the state of soil N differs between regions, where diverse dominant land-use
conditions exist. Our aim here is to determine soil controls on the
continental variation in soil NH4+ and NO3-
contents between and within the agricultural and non-agricultural regions of
Australia. We focused on a set of soil attributes and assessed their
importance for determining the large-scale drivers of mineral N contents by
land use.
Materials and Methods
Data sets
We used two soil data sets for our analysis. First, the Biomes of Australian
Soil Environments (BASE) project provides soil and other
contextual data across the continent, originally developed for the assessment of
soil biodiversity (available at https://data.bioplatforms.com, last
access: 26 February 2018). The BASE
project performed soil sampling and analysis, as described in
. For this study, we obtained the contents of soil
NH4+ and NO3- (mg N kg-1), total organic C
(TOC) (%), exchangeable cations (Al3+, Ca2+,
Mg2+, K+, and Na+ in mequiv 100 g-1),
texture (%) and pH (in CaCl2) from BASE, which were measured at the
0–0.1 and 0.2–0.3 m depths from over 650 sites across Australia between
2011 and 2016 (Fig. ). Each sample was collected from a site that
represented a unique combination of soil, climate and management.
Specifically, between 9 and 30 soil cores were sampled in a
25 m × 25 m quadrat and split into two different depths, 0–0.1
and 0.2–0.3 m, respectively, and then combined into one composite sample
(approximately 1 kg of soil) for each depth. Site soil sampling was done in
a destructive manner and measured at a single time point. The contents of
mineral N were determined colourimetrically on dried soil samples <2 mm
after extraction with 1 M KCl. Spatial distribution of NH4+ and
NO3- content can be different and temporally unstable for each
site . So far, this is the most comprehensive data
describing soil mineral N pools across different soil and land-use types of
Australia at the continental scale, including a wide range of agricultural
soil conditions. At the scale of this study, we assumed that spatial patterns of
soil mineral N remained persistent with time. This assumption was based on
the number of sites across which the effect of confounding factors may be
minimized. The size of sampling area was fixed to match the smallest grid
size of legacy soil attribute maps in Australia. Although fine-resolution (<25 m) soil heterogeneity was not addressed, the BASE data of soil
NH4+ and NO3- contents could be extended with key
soil attributes previously produced from national mapping efforts but not
measured in BASE. The exchangeable cations were summed to estimate cation
exchange capacity (CEC).
Location of 469 sampling sites across Australia, indicated with open
circles for soils used for dryland and irrigated cropping and from improved
and native pastures used for animal grazing (160 sites), and closed circles
for soils from areas that are conserved and in natural environments outside
of the agricultural production zones (309 sites). The dark grey area
represents intensive agricultural and plantation production. The light grey
area represents agricultural production from relatively natural environments.
The white area indicates the non-agricultural region.
Second, to complement the BASE data set, we used Australian soil attribute
values extracted from recently produced soil maps with robust uncertainty
estimates at a pixel resolution of 90 × 90 m (or 3 arcsec)
. The maps that we used were the percentage of
total N (TN) and total P (TP) contents, bulk density (BD) (g cm-3), and
available water capacity (AWC). Each of the Australian soil attribute maps
were independently produced by 3-D spatial modelling that combined historical
soil data and estimates derived from visual and infrared soil spectra. The
approaches used to produce the maps were described in detail in
. When the soil maps were produced at the fine
spatial scale, auxiliary environmental data were already considered in the
spatial modelling. These variables represent proxies for the main
environmental factors of soil formation, which were related to parent
material, climate, biota and vegetation, and terrain and landscape position.
For this study, a weighted average over the 0–5, 5–15, and 15–30 cm
depths was calculated for each of the mentioned soil variables. The
depth-average values of each soil attribute were extracted using the
coordinates from the 469 sites at which both NH4+ and
NO3- contents were measured. The extraction of grid values to each
geographic location and the compiling of data was done in the Geographic Resources
Analysis Support System (GRASS) GIS 7.2 (http://grass.osgeo.org, last
access: 1 January 2018).
Data analyses
The data set was screened for any missing values of land uses and soil
properties. A total of 469 sites were retained for data analyses
(Fig. ), and we performed the analyses on (1) all samples, (2) the
samples from the sites that mainly originate from dryland and irrigated
cropping and from improved and native pastures used for animal grazing
(hereafter referred to as the “agricultural” region), and (3) the samples
from the protected sites and those in natural environments outside of the
agricultural production zones (referred as the “non-agricultural” region)
(Fig ). The agricultural region (160 sites) covers the main
grain-cropping zones of Australia, which differ by climate and soil regimes
and farming practices. Sites used for agricultural production from relatively
natural environment did not receive external N fertilization but some N
excretion by grazing animals or biomass inputs from commercial production.
There was no livestock grazing in the non-agricultural region. If the content
of soil mineral N in the data was reported as the value at or below the
detection limit of 1 ppm, it was replaced with 0.5 mg N kg-1 (a
median of the detection limit). The content of soil mineral N was averaged
over the two sampling depths and then log transformed to approximate
normality. Mean comparisons of the log-transformed data were performed
between the regions at the 0.05 significance level (p<0.05) using the
analysis of variance (ANOVA). Tukey's HSD test was used to compare the
measured mineral N contents among the multiple land uses. The data set
covered four general land uses: (1) conservation and natural environments,
(2) production from dryland agriculture and plantations, (3) production from
irrigated agriculture and plantations and (4) production from relatively
natural environments. The general land use classes included 28 detailed land
uses, according to the Australian Land Use and Management Classification
(Table S1 in the Supplement).
The contents of soil NH4+, NO3-, TOC, TN, TP, CEC,
and the fraction of sand, silt, clay, BD, and AWC, except for pH, were
log transformed for further modelling. For each of the soil NH4+ and
NO3- measurements, data analyses were performed on the whole
data, including 22 samples for NH4+ and 170 samples for
NO3-, which were measured under the detection limit. Only 3 and 42
of these samples for NH4+ and NO3- were located
within the agricultural region, respectively. Empirical models of soil
mineral N as a function of the selected soil properties were built using the
machine learning algorithm Cubist . Cubist is a form of a
rule-based decision tree with piecewise linear models. Models were developed
and evaluated by 10-fold, 50-repeated cross-validation. Model performance was
assessed using the coefficient of the determination (R2), the root mean
squared error (RMSE), the mean error (ME), and the standard deviation of the
error (SDE). In Cubist, the number of committees was fixed as one to avoid
producing complex models, but the number of nearest neighbours was optimized
using the RMSE of resampling results. The optimized models consisted of 1–8
different rule sets, with 3–9 neighbours. The importance of each soil
variable was assessed based on the usage of each individual variable in the
rule conditions and the model for Cubist. The cut-off was set at 80 % as
the probability to be essentially used in either the rule conditions or the
linear model. In addition, the sensitivity of important soil variables was
tested with 5, 10, and 20 committee models. The same data analysis and
regression approach were applied on the data sets for the agricultural and
non-agricultural regions separately, and then a Pearson correlation analysis
was performed, accordingly. All statistical analyses and Cubist modelling were
performed in the R version 3.4.3 (R Core Team, 2017). Functions from the
“Cubist” (version 0.0.21) and “caret” (version 6.0.76) packages were
used.
Results
Soil mineral N in relation to large-scale land use
The median contents of NH4+ and NO3- in the soil
were 3.5 and 1.5 mg N kg-1, respectively, across all sites
(Fig. ). The interquartile ranges of NH4+ and
NO3- contents were 1.75–6.0 and 0.5–4.5 mg N kg-1. The
corresponding coefficient of variation was 147 % for NH4+
and 215 % for NO3- across the sites, showing wide variation
in the measured soil mineral N. The median sum of NH4+ and
NO3- was 6.0 mg N kg-1, with the interquartile range of
3.5–12.0 and the maximum of up to 123 mg N kg-1. Compared to the
non-agricultural region, the soil in the agricultural region had similar
contents of NH4+ (4.0 vs. 3.5 mg N kg-1) but
significantly (p<0.05) larger contents of NO3- (3.0 vs.
1.0 mg N kg-1). There were a number of sites with relatively small
contents of mineral N, particularly NO3-. If we only considered
soil NO3- contents above the detection limit, the median
NO3- contents would then increase to 4.5 mg N kg-1 in the
agricultural region and to 2.5 mg N kg-1 in the non-agricultural
region. Nevertheless, the regional patterns of
NH4+ and NO3- remained consistent. The sum of soil
mineral N showed a regional difference similar to that of NO3-.
For all sites, the ratio of NH4+-N to NO3--N was
about 2.0 (interquartile range 0.75–6.0). Specifically, soil
NH4+ was identified as a dominant mineral form of N at
309 sites. The NH4+ and NO3- fractions of TN were
0.4 % and 0.2 %, respectively, and comprised together approximately
1 %–2 % of TN in the soil at the sites. The NO3-
fraction of TN ranged between 0.01 % and 10.0 % and appeared to be
more variable than that of NH4+, which had the range of
0.05 %–5.8 %. The NH4+-N : NO3--N ratio
was significantly lower in the agricultural region (median 1.4) than the
non-agricultural region (median 2.3). This also corresponded to a
significantly higher NO3- fraction of TN in the agricultural
region, compared to the non-agricultural region.
Mineral N contents (mg N kg-1) and fractions of total N in
soil. The bottom, middle, and top of each box represents the 25th, 50th
(median), and 75th percentiles, respectively. The points above the whiskers
are extreme values. Means between main agricultural and non-agricultural
regions of Australia are significantly different at P-value <0.001
(***), indicated by the ANOVA on the log of the values.
Summary of NH4+ and NO3-
contents (mg N kg-1) in Australian soil by land use across 469 sites.
Means with different letters are significantly different at p<0.05, based
on Tukey's HSD on the log of the values. Any categorical variables with a
sample size of <10 are considered in the multiple mean comparisons but not
presented in the table. See Table S1 for the definition of land uses.
NH4+
NO3-
n
Median
Mean
Max
Min
Median
Mean
Max
Min
Broad land use
Agricultural
Production from dryland agriculture and plantations
81
4.5
5.7
46.5
0.5
4.0
7.8a
59.0
0.5
Production from irrigated agriculture and plantations
11
6.0
6.1
14.0
0.9
4.5
8.8a
30.3
0.8
Production from relatively natural environments
68
3.0
3.7
13.5
0.5
1.5
3.4b
26.0
0.5
Non-agricultural
Conservation and natural environments
309
3.5
5.6
120.0
0.5
1.0
3.8b
121.0
0.5
Detailed land use
Agricultural
Cropping
16
2.5
3.4bc
13.0
0.5
4.5
6.2ab
18.5
0.5
Environmental forest plantation
12
4.8
4.8abc
8.0
1.5
0.5
0.6cd
1.3
0.5
Grazing modified pastures
45
5.5
7.3ac
46.5
0.5
5.0
11.0a
59.0
0.5
Grazing native vegetation
45
3.0
3.6bc
11.0
0.5
2.5
4.8ab
26.0
0.5
Production native forests
23
3.0
4.0abc
13.5
1.3
0.5
0.6d
1.5
0.5
Non-agricultural
Habitat/species management area
10
15.0
28.1a
120.0
2.0
1.0
1.3bcde
2.5
0.5
National park
171
3.5
4.9bc
39.0
0.5
0.5
3.3cde
80.0
0.5
Natural feature protection
21
5.0
5.7abc
12.0
0.8
2.0
9.0abe
121.0
0.5
Other conserved area
18
1.8
3.1b
15.0
0.5
0.8
2.9bcde
11.0
0.5
Residual native cover
60
3.8
5.3abc
25.5
0.5
2.1
3.7b
28.0
0.5
The contents of NH4+ and NO3- differed by both
broad and detailed land uses (Table ). Soil NH4+
contents showed no difference among the broad land uses, but there was more
variation for conservation and natural environments, compared to the other
land uses. Relatively low NH4+ contents were found in the soil
used for production from relatively natural environments. Overall, also
considering the limited data, no apparent differences were found between the
detailed land uses. Large soil NO3- contents generally resulted
from agricultural production, compared to the soil in conservation and
natural environments or those used mainly for production from relatively natural
environments. This pattern was generally found for detailed land uses as
well.
Soil controls on the contents of mineral N
The importance of each of the soil variables as the primary controlling
factor over soil mineral N are shown in Fig. . Across all sites,
TOC, TN, TP, the clay fraction, CEC and pH appeared to have effects on
NH4+ contents. Especially, the variation in soil
NH4+ contents was consistently related to pH (Fig. S1 in the
Supplement). The contents of NO3- were primarily
affected by CEC and to a lesser extent by similar soil controls as for
NH4+. In addition, BD was identified as a potential driver for
NO3- only. In the agricultural region, soil NH4+
was controlled by TN, CEC, and pH, while TN and CEC as well as TOC, sand
fraction, and AWC were important controlling factors of NO3-.
Among these soil properties, only the pH and CEC showed consistent large-scale
effects on mineral N (Figs. S1 and S2). There was no effect of TOC and TP on
NH4+, but their effects were important in more complex models.
In the non-agricultural region, soil NH4+ was affected by TOC,
TP, CEC, and pH. Soil NO3- was affected by all selected soil
variables in the same region, where BD, CEC and TOC were the most important
factors. There was some effect of TN, but TP and pH had relatively less
important contribution in contrast to its importance for the soil controls on
NH4+. In general, based on Pearson’s correlation coefficients,
the contents of NH4+ and NO3- significantly
correlated with the soil variables identified by Cubist (Table ).
The exception was CEC, which was not correlated with but was selected as
important for NH4+ in the agricultural region. A similar case
was found between NO3- and TN or BD when accounting for
all sites or regions.
Significant Pearson's correlation coefficients between
soil NH4+ or NO3- (mg N kg-1) and selected soil
variables at p-value <0.05 (n=469). The correlations indicated by
“ns” are not significant.
Variable
NH4+
NO3-
All
Agricultural
Non-agricultural
All
Agricultural
Non-agricultural
sites
region
region
sites
region
region
Total organic C (%)
0.67
0.49
0.73
0.21
ns
0.27
Total N (%)
0.65
0.47
0.70
ns
ns
ns
Total P (%)
0.46
0.26
0.52
0.14
0.26
0.08
Sand (%)
-0.31
-0.20
-0.43
-0.29
-0.23
-0.37
Silt (%)
0.41
0.17
0.53
0.24
0.16
0.3
Clay (%)
0.43
0.19
0.53
0.31
0.25
0.35
Bulk density (g cm-3)
-0.50
-0.24
-0.58
ns
ns
ns
Cation exchange capacity (mequiv 100 g-1)
0.27
ns
0.33
0.51
0.52
0.50
pH
-0.43
-0.23
-0.51
0.30
0.38
0.25
Available water capacity
0.12
ns
0.14
ns
0.35
ns
Importance of soil attributes as the predictors of NH4+
and NO3- contents (mg N kg-1). The importance of the
predictors is based on the usage of each variable in the rule conditions
(grey bars) and in the Cubist model (black bars). The abbreviations used are CEC
(effective cation exchange) and AWC (available water capacity).
After cross-validation, Cubist models were able to explain 60%±11% of the measured variation for NH4+ and 42%±13% for NO3- in the soil across all sites
(Table ). The models were evaluated by considering all sites
together as well as the sites in each of the regions separately.
Specifically, the RMSE and SDE of the region-specific models tended to
decrease, showing overall improvement in accuracy and precision. The Cubist
models appeared to reasonably cover a range of measured NH4+ and
NO3- contents for each selected region (Fig. ).
However, the model failed to reproduce a high range of measured mineral N
values when considering all sites or each of the regions. Therefore, the soil
factors identified by the model may have unstable effects on these high
values.
Soil NH4+ and NO3- contents on the
log-transformed scale estimated by optimized Cubist models. Points represent
model evaluation by 10-fold, 50-repeated cross-validation. The error bar is
the standard deviation of the estimated mineral N content. The 1 : 1 line
is indicated.
Cross-validation statistics (mean ± standard deviation) of Cubist
model on the estimation of NH4+ and NO3- contents (mg N kg-1)
in soils. The performance of the models was evaluated with 10-fold, 50-repeated cross-validation
with instance-based corrections. The coefficient of determination (R2), the root mean
squared error (RMSE), estimated bias (ME), and the standard error of estimated bias (SDE) are considered.
All sites
Agricultural
Non-agricultural
region
region
NH4+
R2
0.60±0.11
0.36±0.21
0.68±0.10
RMSE
0.60±0.09
0.65±0.16
0.58±0.09
ME
-0.01±0.07
-0.02±0.14
-0.01±0.09
SDE
0.60±0.09
0.66±0.16
0.58±0.09
NO3-
R2
0.42±0.13
0.47±0.19
0.47±0.16
RMSE
1.01±0.17
0.99±0.22
0.92±0.19
ME
0.00±0.13
0.05±0.23
0.05±0.16
SDE
1.01±0.18
1.00±0.23
0.92±0.19
For NH4+ and NO3- (mg N kg-1),
scatter plots of total organic C (TOC), total N (TN), total P (TP), and
element ratios on the log-transformed scale in the agricultural region. The
unit is expressed as percent C, N, or P by weight of soil. Pearson's
correlation coefficient is reported only when the trend is significant (p<0.05).
For NH4+ and NO3- (mg N kg-1),
scatter plots of total organic C (TOC), total N (TN), total P (TP), and
element ratios on the log-transformed scale in the non-agricultural region,
where soil is used for conservation and under natural vegetation. The unit is
expressed as percent C, N, or P by weight of soil. Pearson's correlation
coefficient is reported only when the trend is significant (p<0.05).
Relationships between mineral N and soil C, N, and P stoichiometry
Depending on the specific region, soil nutrients had distinct effects on the
level of each mineral form of N. In the agricultural region
(Fig. ), soil NH4+ was directly related to TN and TOC
to a lesser extent TP, with significant effects from the interaction of total
soil nutrients (p<0.05). Soil NO3- was significantly related
to TP only in the agricultural soil (p<0.05). However, no significant
relationships between NO3- and all soil elemental ratios and
the model suggest that the contents of NO3- were insensitive to
changes in the elemental TP but indirectly related to TOC or TN. In the
non-agricultural region (Fig. ), each of the total nutrient
contents was significantly related to the distribution of soil
NH4+ in a similar manner to the soil in the agricultural region.
This suggests that TOC was a main controlling factor, but the effects of
elemental interactions would be potentially important, also corresponding to
those from the modelling. Specifically, the levels of NH4+
increased in the P-depleted soil relative to the other nutrients in both
regions.
Discussion
Continental variation in soil NH4+ and NO3-
The distribution of NH4+ and NO3- in the soil and
the ratio of NH4+-N to NO3--N show that
NH4+ is a predominant source of N for plant uptake or other
biological processes across the sites, compared to NO3-. This
suggests that the risk of loss from leaching and denitrification may not be
large or evident at the scale of the study or from the sparse data set. The
sum of NH4+ and NO3- at the sites might be useful
to approximately set the potential limits of inherent soil N availability
and thus the relevant limits for mineral N management particularly in the
agricultural region of Australia. However, it was again based on limited soil
data across a vast area of the continent and should be interpreted with
caution. The distribution of NO3- was characterized by
relatively low values or values under the detection limit, which suggest that
those soils were depleted in NO3-. On the other hand,
large-scale variation in soil NO3- and total mineral N contents
should be considered when making implications for the regional effects of land
use patterns on soil N dynamics. The NO3- fraction, relative to
NH4+ of TN, substantially increased if the soil with small
NO3- contents was excluded (data not shown). There may also be extreme values for NH4+ and NO3-, usually higher
than 45–50 mg N kg-1 and approximately equivalent to
150–200 kg N ha-1, representing potential hot spots. Such a wide
range of NH4+ and NO3- contents on top of
spatially scarce soil data presents a challenge in determining the responses
of varying mineral N to soil factors in different regions defined by broad
land uses.
We found complex but consistent regional patterns of soil NH4+
and NO3- by broad land uses. The soil in the agricultural region
was characterized by relatively smaller NH4+ but significantly
larger NO3- contents than the soil in the non-agricultural
region, generally from conservation areas and natural environments
(Fig. ). However, each site in the agricultural region represents
more modified landscapes for production. This region accounts for most of the
soil conditions affected by land uses particularly related to agricultural
production and grazing. Overall, more NO3- appeared to be
accumulated in the soil under agricultural conditions because of the
significant mean difference in the sum of mineral N between the regions. The
relative accumulation of soil NO3- was also supported by the
ratio of NH4+ to NO3-, which was considerably lower
in the soil from the agricultural region, compared to that in the
non-agricultural region. The soil receiving high N inputs from external
sources and recycled N may have more NO3- in the balance of soil
NH4+ and NO3- pools . In the
agricultural region, historical soil N input is known to enhance potential N
nitrification over time, although it is further complicated by continuous
soil disturbance (e.g. intensive tillage) and various tillage intensities
. In addition, the soil's capacity to supply
NH4+ through N mineralization may have been decreased with soil
organic matter decline in response to continuous soil disturbance
. The regional balance of soil mineral N would in part
depend on preferential N uptake in main crops
. However, this effect has not been
shown for many crops grown in the region, and thus more data are needed to
further confirm this.
Land-use types play a role as the major sources of regional differences in
soil NH4+ and NO3- across the sites
(Table ). It is therefore promising to split the continental data
on mineral N into the region-specific variation in N based on land uses, if
the current land uses were maintained with minimal spatial and temporal
changes. Land uses and associated conditions can geographically constrain or
be constrained by each other, contributing to regional differences in soil
characteristics and N transformation rates . As shown above,
the amount of NO3- or the sum of NH4+ and
NO3- stored in the soil was distinctly characterized between the
regions, subject to different dominant land uses. The land-use types affected
by production activities have been driven by N inputs and eventually led to
enrichment of soil NO3-, as suggested also by the differences in
mineral N between the agricultural and other non-agricultural regions.
NH4+ was depleted in the soil within low-input or relatively
natural environments used for production, compared to the soil under
conservation and natural environments not used for agricultural purposes.
This has important implications because resource-based production systems
with little to no input (e.g. grazing of native vegetation) may not be
sustainable, compared to input-driven production systems. The effect of
agricultural land uses on the levels of NH4+ and
NO3- may depend on the interactive effect of soil management and
external N input from anthropogenic sources . Similarly,
soil NH4+ and NO3- contents under cropping were
about 2.5 and 4.5 mg N kg-1, respectively, showing the decline in
NH4+ and enrichment of NO3-. The levels of soil
mineral N were highly variable in the protected or natural environments,
particularly for NH4+, similar to the patterns between the
regions. Presumably, this was due to the differences in the amount and
quality of biomass input under natural vegetation and crop production,
leading to different soil organic matter decomposition (source) versus N
immobilization (sink) .
Among ecological factors, the climatic variables such as precipitation and
temperatures are known to strongly limit soil N storage across spatial
scales . In this study, however, we did not determine
how soil mineral N status would change under other climatic and ecological
conditions in Australia. This was because most of the sites were located in
arid or temperate ecological zones. Given the number of the sites, the extent
and support of measured soil data did not fully represent a possible range of
soil conditions. Therefore, further measurements are needed to account for
diverse agro-ecological settings.
Soil controls over the measured variation in NH4+ and NO3-
Interactions between soil variables and related processes operating on
multiple aspects of the N cycle are often difficult to understand at the
continental scale. Much less is known about the large-scale effect of
land-use patterns on soil mineral N dynamics. In this study, we used the
measured data as well as the high-resolution soil values from model
predictions that are reliable and accurate with small to moderate uncertainty
. Although potential
uncertainties exist in the data as a proxy for “real” soil conditions,
multiple soil variables were significantly related to NH4+ and
NO3- contents in the soil at all sites and between the regions
(Table ). In Cubist models, a comparable set of the soil variables
acted as the controlling drivers on the distribution of NH4+ and
NO3- across the sites (Table and Fig. ).
Rule-based models are practical in interpreting and extrapolating plant N
availability and N losses under various conditions. These common soil drivers
suggest that similar mechanisms drive NH4+ and NO3-
to some extent, linking them together. It is well known that CEC contributed
to the potential to retain both NH4+ and NO3-. In
addition, there were probably more complex interactions of soil controls on
NO3- contents, for example, including additional effects of soil
texture. Since the selected soil variables can potentially determine soil
mineral N availability and losses, the accurate measurement and mapping of
soil attributes are important for continental simulations of soil N dynamics.
Some of the soil variables, particularly CEC, may have indirect effects on
soil mineral N, presumably confounded by other predominant drivers, such as
soil texture and BD .
It is important to note that the importance of soil controlling factors was
different between the agricultural and non-agricultural regions. These
variables, which were previously identified as important across the sites could serve as
conditional controls between the regions, depending on dominant land-use and
vegetation types. Particularly for the soil in the agricultural region, the
contents of soil NH4+ and NO3- tended to be
controlled by only 3–5 primary drivers and the interactions of less
important variables. These included pH for NH4+ and CEC for
NO3- in the soil. Total organic C, TN, and TP had varying
degrees of importance that were specific for each mineral form of N between
regions. In the agricultural region, NH4+ positively depended on
TN and thus the distribution and sources of organic matter and potential N
availability in the soil. Instead, NH4+ retention capacity may
become important through pH and CEC effects. In the non-agricultural region,
soil NH4+ might depend on the mineralization of organic matter
sources but is less limited by TN or TP under near steady-state conditions.
Soil NO3- was positively affected by TOC and TN in the
agricultural region, where it could be more affected by the capacity of the
soil to immobilize residual NO3- if an ample N supply was assumed.
In contrast, NO3- was affected to a certain extent by TOC and TN
and the effect of TP remained relatively higher in the non-agricultural
region, receiving limited soil inputs. Thus, soil NO3- may
presumably be associated with organic matter and N mineralization rates. At
this stage, however, no clear mechanisms are evident from the different
drivers of mineral N contents between the regions. Nevertheless, land-use
conditions would provide constraints on what critical soil variables drive
the large-scale variation in NH4+ and NO3-
contents.
The Cubist models were able to account for 36 %–68 % of the measured
variation in both NH4+ and NO3- in the soil across
the sites and within each region (Table and Fig. ).
The contents of NH4+ and NO3- were reasonably
estimated by the model for each region. In contrast, the model performance of
soil mineral N was substantially limited by high prediction error,
particularly over a high range of contents at all sites and in the
non-agricultural region. In addition, the overall model performance was possibly
limited by the presence of samples with NO3- contents under the
detection limit so that any differences in the selected soil variables could
not be fully considered in the model, eventually leading to the
oversimplified controls in each of the regions. As a result, much of the
model error resulted from the lack of accuracy. In addition, the models may
not capture all the processes and resulting variation as they were based on
the limited data sets. Similar issues, such as the underestimation of
relatively high NO3- contents, have been found using model-based
approaches . The
evaluation of these models suggests that the region-specific simulation of
soil mineral N may not be sufficiently reliable at the continental scale, and
this issue has been reported . These studies recommended
further improvement in the mechanisms within the models, especially for
hydrological or N transformation processes responsible for NO3-
contents. Specifically, we need to focus more on mechanistic roles of
different soil drivers in N cycling between the regions, temporal controls
over N transformation, and biogeochemical hot spots and moments in N retention
and removal. As such, it is especially relevant to continue the development
of accurate models in order to predict general patterns when integrating
different land uses.
Soil stoichiometric controls on NH4+ and NO3-
Stoichiometric interactions of total soil C, N, and P can be geographically
related to the transformation processes between soil organic and inorganic N
over large spatial scales. The states of soil TOC, TN, and TP have been
reported at the continental scale for Australia
and across Australia's major agro-ecological regions . As far
as we know, little or no studies have addressed the fate of soil mineral N by
directly linking to soil stoichiometric interactions of C, N and P at the
continental scale in Australia because of practical difficulties in directly
measuring soil mineral N. We acknowledge this challenge and the need for more
measurements at additional sites. Despite this limitation, our results
suggest that soil organic matter and its C : N : P stoichiometry may
contribute to the potential to maintain or increase NH4+
contents in each region under different land uses. Specifically, there was a
trend of increasing soil NH4+ contents with increasing C : N
(median 15.9 and 15.1), C : P (72.8 and 73.1), and N : P (5.0 and 4.5)
ratios in the agricultural (Fig. ) and non-agricultural regions
(Fig. ). There is also an indication that final soil elemental
ratios are less affected by soil input stoichiometric ratios than previously
expected and depend mostly on soil mineralogy .
Similarly, found that the stable portion of organic matter
had relatively constant C : N : P ratios across a range of soil types.
This suggests that soil NH4+ dynamics may depend on the amount
of C and N stored in the soil as well as the relative P limitation in soil
nutrient quality. The effects of these elemental interactions on soil
NO3- seemed to be important in the non-agricultural region only
(Figs. and ), specifically through changes in the
amount of N and P retained in soil organic matter.
Different organic matter depletion and composition and N mineralization from
soil organic matter between the regions can limit the initial step for the
terrestrial N cycle and determine the fate of mineral N
. Recently,
reported global averages of the C : N and C : P stoichiometry, which
approximately corresponded to 8.3 and 62.5 for nutrient-rich soil organic
matter and 25.6 and 909.0 for nutrient-poor soil organic matter. The contents
of C, N and P and corresponding elemental ratios in the soil suggest that TN
was limited while TP was abundant in Australian soil, relative to organic C.
However, plant-available P is typically very low in Australian soil
. Soil C : P and N : P ratios are
known to increase in response to disturbance events, such as the level of
soil tillage and fire intensity . Our soil
stoichiometry results, although limited, generally support the general status
of nutrient-poor soil organic matter, as previously shown by
. More importantly, these regional patterns may not
be consistent over different spatial scales. For example,
reported significantly higher C : P ratios for four Australian agricultural
soils than international soils and thus a potential P reduction due to total C
loss at the field scale. Therefore, the importance of soil elemental
interactions in determining the variation of mineral N at different spatial
scales across and within various production and ecological conditions needs
to be estimated.
Conclusions
The distribution of soil NH4+ and NO3- contents was
significantly affected by regional differences of land use across Australia.
Despite a wide range of soil conditions, the nature of the main soil controls
and interactions over soil N storage and availability appeared to differ
across the sites and between the agricultural and non-agricultural regions,
constituting regionally explicit soil controls. Total organic C, TN, and TP
had varying degrees of importance as a controlling factor between
NH4+ and NO3- and between regions. Assuming that
total soil nutrients were related to the amount of soil N that can be
retained, the effects of total soil elements was probably due to differences
in the source type of mineral N and under declining or steady-state soil
organic N. In addition, more complex effects of soil properties on
NO3- than on NH4+ were found in both regions. Our
results also suggest that the stoichiometric interactions of C, N, and P may
provide potentially important constraints on the dynamics of mineral N at
the sites, specifically for NH4+ in each of the regions and
NO3- in the non-agricultural region. Overall, large-scale
NH4+ and NO3- tended to be sensitive to N or P
status relative to C in the soil nutrient budget, showing the biogeochemical
role of soil nutrients in the regulation of soil mineral N cycling. The
Cubist model was effective at explaining the region-specific heterogeneity of
Australian soils, empirically related to the contents of mineral N. However,
the mechanisms of mineral N cycling controlled by the soil properties were
not evident at the continental scale. In addition, the current data set and
models still under-represent the intensive production and other
agro-ecological zones of Australia. Therefore, more focus should be given
to a mechanistic understanding of the large-scale changes in soil mineral N
retention and losses at this scale.