Ecosystems limited in phosphorous (P) are widespread, yet there is limited
understanding of how these ecosystems may respond to anthropogenic
deposition of nitrogen (N) and the interconnected effects on the
biogeochemical cycling of carbon (C), N, and P. Here, we investigate the
consequences of enhanced N addition for the C–N–P pools of two P-limited
grasslands, one acidic and one limestone, occurring on contrasting soils, and we
explore their responses to a long-term nutrient-manipulation experiment. We
do this by combining data with an integrated C–N–P cycling model (N
Grasslands represent up to a fifth of terrestrial net primary productivity (NPP) (Chapin et al., 2011) and potentially hold over 10 % of the total organic carbon stored within the biosphere (Jones and Donnelly, 2004). The ecosystem services provided by grasslands, such as carbon storage, are highly sensitive to perturbations in their nutrient cycling, including the perturbation of nitrogen (N) inputs from atmospheric deposition (Phoenix et al., 2012).
Since the onset of the industrial revolution, human activity has doubled the
global cycling of N, with anthropogenic sources contributing 210 Tg of fixed
N yr
Despite large anthropogenic fluxes of N, most terrestrial ecosystems on temperate post-glacial soils are thought to be N-limited (biomass production is most restricted by N availability) (Vitousek and Howarth, 1991; Du et al., 2020), as weatherable sources of phosphorus (P) remain sufficiently large to meet plant P demand (Vitousek and Farrington, 1997; Menge et al., 2012). Both empirical and modelling studies have shown that pollutant N, when deposited on N-limited ecosystems, can increase productivity (Tipping et al., 2019) and soil organic carbon (SOC) storage (Tipping et al., 2017), largely as a result of stimulated plant growth. This suggests that while there are negative consequences of N deposition, there may also be benefits from enhanced plant productivity and increases in carbon sequestration.
Whilst most research focuses on N-limited ecosystems (LeBauer and Treseder, 2008), a number of studies have highlighted that P limitation and N–P co-limitation are just as prevalent, if not more widespread, than N limitation (Fay et al., 2015; Du et al., 2020; Hou et al., 2020). In a meta-analysis of grassland nutrient addition experiments spanning five continents, Fay et al. (2015) found that aboveground annual net primary productivity was limited by nutrients in 31 out of 42 sites, most commonly through co-limitation of N and P (Fay et al., 2015). Similarly, P additions in 652 field experiments increased aboveground plant productivity by an average of 34.9 % (Hou et al., 2020), and it is estimated that P limitation, alone or through co-limitation with N, could constrain up to 82 % of the natural terrestrial surface's productivity (Du et al., 2020).
Furthermore, P limitation may be exacerbated by N deposition (Johnson et al., 1999;
Phoenix et al., 2004) or become increasingly prevalent as previously N-limited
ecosystems transition to N-sufficient states (Goll et al., 2012). For example, in
parts of the Peak District National Park, UK, N deposition has exceeded 3 g m
While N deposition may worsen P limitation in some instances, plant strategies for P acquisition may require substantial investments of N, suggesting that increased N supply may facilitate enhanced P uptake (Vance et al., 2003; Long et al., 2016; Chen et al., 2020). Indeed, previous work from long-term experimental grasslands has shown strong effects of N deposition on plant enzyme production (Johnson et al., 1999; Phoenix et al., 2004), whereby the production of additional extracellular phosphatase enzymes was stimulated. While it is not clear whether this response is driven by exacerbated P limitation resulting from N deposition or extra N availability making elevated enzyme production possible, such changes in plant physiology may promote cleaving of P from organic soil pools. Over time, the accumulation of plant-available P from organic sources may provide a mechanism by which plants exposed to high levels of N deposition may overcome P limitation (Chen et al., 2020).
By using the integrated C–N–P cycle model N
Process-based models have a role to play in addressing this, as they allow us to test our mechanistic understanding and decouple the effects of multiple drivers. There has been increasing interest in linking C with N and P cycles in terrestrial ecosystem models (Wang et al., 2010; Achat et al., 2016; Jiang et al., 2019) as the magnitude of the effects that anthropogenic nutrient change can have on biogeochemical cycling are realised (Yuan et al., 2018). Yet, few modelling studies have explicitly examined the effects of P limitation or the role of organic P access in determining nutrient limitation, likely mirroring the relatively fewer empirical studies of these systems.
By combining process-based models with empirical data from long-term
nutrient-manipulation experiments, we may simultaneously improve our
understanding of empirical nutrient limitation, the role(s) of organic P
acquisition, and their interactions with anthropogenic nutrient pollution.
In particular, this approach offers a valuable opportunity for understanding
ecosystem responses to environmental changes that may only manifest after
extended periods of time, such as with changes in soil organic C, N, and P
pools, which typically occur on decadal timescales (Davies et al., 2016a;
Janes-Bassett et al., 2020). Here, we combine new data from a long-term nutrient
manipulation experiment on two P-limited upland grasslands (acidic and
limestone) occurring on contrasting soils, with the mechanistic C–N–P
plant–soil biogeochemical model N
We use these experimental data to explore the role of organic P access in determining ecosystem nutrient limitation and grassland responses to long-term nutrient manipulations. Specifically, we aim to explore how variation in P acquisition parameters, which control access to organic and inorganic sources of P in the model, may help account for differing responses of empirical grassland C, N, and P pools to N and P additions. Second, we explore the effects of long-term anthropogenic N deposition and experimental N and P additions on plant and soil variables of the simulated acidic and limestone grasslands. This will help improve our understanding of organic P process attribution within the model and may suggest how similarly nutrient-limited grasslands could respond to similar conditions.
We hypothesise that (1) access to organic P will be an important determinant of ecosystem nutrient limitation, (2) increased organic P availability may alleviate P limitation resulting from N deposition, and (3) grasslands capable of accessing sufficient P from organic forms may overcome P limitation resulting from N deposition and nutrient treatments, whereas grasslands lacking such accessibility will not.
The empirical data are from Wardlow Hay Cop (henceforth referred to as Wardlow), a long-term experimental grassland site in the Peak District National Park (UK) (Morecroft et al., 1994). Details of empirical data collection are available in Supplement Sect. S1. There are two distinct grassland communities occurring in close proximity: acidic (National vegetation classification U4e) and limestone (NVC CG2d) semi-natural grasslands (Table S2). Both grasslands share a carboniferous limestone hill, but the limestone grassland sits atop a thin humic ranker (Horswill et al., 2008) and occurs predominantly on the hill brow. In contrast, the acidic grassland occurs in the trough of the hill, allowing the accumulation of windblown loess and the formation of a deeper soil profile of a palaeo-argillic brown earth (Horswill et al., 2008).
Despite contrasting soil types, both the acidic and limestone grasslands are largely P-limited (Morecroft et al., 1994; Carroll et al., 2003), though occasional N and P co-limitation can occur (Phoenix et al., 2003), and more recently, positive growth responses in solely N-treated plots have been observed, in line with the latest understanding that long-term N loading may increase P supply by increasing phosphatase enzyme activity (Johnson et al. 1999; Phoenix et al.2004; Chen et al. 2020).
Nutrients (N and P) have been experimentally added to investigate the
effects of elevated N deposition and the influence of P limitation
(Morecroft et al., 1994). Nitrogen treatments simulate additional N deposition to
the background level, and the P treatment acts to alleviate P limitation.
Nutrients are added as solutions of distilled water and applied as fine
spray by backpack sprayer and have been applied monthly since 1995, and
since 2017 bi-monthly. Nutrient additions are in the form of
NH
Data collected from the Wardlow grasslands for the purpose of this work are aboveground biomass C, SOC, and total N, which is assumed to be equivalent to modelled SON. These new data are combined with total P data that were collected by Horswill et al. (2008) at the site (Horswill et al., 2008). Summaries of these data are available within the Supplement (Table S1), and details of their collection and conversion to model-compatible units are in Supplement Sect. S1.
The N
However, N
Here, we modify N
Plant biomass is simulated in the model as two sets of pools of coarse and
fine tissues representing both above and belowground plant C, N, and P, with
belowground biomass for each plant functional type represented by a root
fraction. NPP adds to these on a quarterly basis with growth occurring in
quarters 2 and 3 (spring and summer). In N
First, the potential maximum NPP limited by climate is calculated using regression techniques, as in Tipping et al. (2014). The corresponding plant demand for N and P to achieve this potential NPP is then calculated (Davies et al., 2016b; Tipping et al., 2017). This demand is defined by plant functional type stoichiometry, which changes through time in accordance with ecosystem succession (see Sect. 2.3.2). Stoichiometry of coarse tissue is constant, but the fine tissue of each plant functional type has two stoichiometric end members. This allows the model to represent transitions from N-poor to N-rich plant communities or an enrichment of the fine tissues within plants (or a combination of both) (Davies et al., 2016b), dependent on available N. This allows a degree of flexibility in plant C : N ratios in response to environmental changes such as N deposition. If the available nutrients cannot meet the calculated plant nutrient demand, the minimum calculated NPP based on either N or P availability is used, giving an estimation of the most limiting nutrient to plant growth.
Nutrient co-limiting behaviour can occur in the model through increased
access to organic P sources in the presence of sufficient N (see Sect. 2.2.3) and
by having the rate of N fixation dependent on plant- and microbial-available
P (Davies et al., 2016b). The initial rate of N fixation is based on literature
values for a given plant functional type and is downregulated by
anthropogenic N deposition but not soil N content more generally, as it is
assumed that atmospherically deposited N is readily available to N fixers.
Nitrogen fixation in the model is also related to P availability. The degree
to which P availability limits this maximum rate of fixation is determined by
a constant, K
A simplified summary of key pools and processes regarding plant–soil nutrient cycling is detailed in Fig. 1. Details such as initial base cation pools, their effects on soil pH, and most parameter names have been omitted for clarity but are available from the original model development study (Davies et al., 2016b). Key changes for the purpose of this work are highlighted in red.
A simplified schematic of the key flows and pools of C, N, and P within N
Plant-available N is derived from biological fixation, the decomposition of coarse litter and soil organic matter (SOM), atmospheric deposition, and direct N application. Fine plant litter enters the SOM pool directly due to its rapid rate of turnover whereas coarse litter contributes N and P through decomposition and does not join the SOM pool. Plant-available P also comes from SOM and coarse litter decomposition, direct treatment, desorption of inorganic P from soil surfaces, and sometimes cleaving of organic P (Davies et al., 2016b). The sorbed inorganic P pool builds over time with inputs of weathered P and sorption of any excess plant-available inorganic P, and desorption occurs as a first-order process.
Phosphorus enters the plant-soil system by weathering of parent material,
the initial value of which (P
The size of the available P pool is determined by summing: P retained within plant biomass prior to litterfall, inorganic P from decomposition, dissolved organic P, and P cleaved from SOP by plants. Accessibility of each P form is determined by a hierarchal relationship in the order mentioned above, whereby plants and microbes access the most readily available P sources first and only move on to the next once it has been exhausted.
When N is in sufficient supply and more bioavailable P forms have been
exhausted from the total available pool, simulated plants can access P from
SOM via an implicit representation of extracellular P-cleaving enzymes with
a parameter termed P
The functioning of the P
A fraction of plant biomass is converted to litter in each quarterly time step and contributes a proportion of its C, N, and P content to SOM, which is sectioned intro three pools (fast, slow, and passive) depending on turnover rate (Davies et al., 2016b). Soil organic P (SOP) is simulated alongside SOC and SON using C : N : P stoichiometries of coarse and fine plant biomass. Decomposition of SOP, and its contribution to the available P pool, is subject to the same turnover rate constants as for SOC and SON.
Carbon is lost as CO
We use data from the Wardlow limestone and acidic grasslands to explore the potential role organic P access may have in determining grassland nutrient limitation when exposed to long-term N deposition and more recently experimental nutrient manipulation. We use environmental input data collated from Wardlow to drive model processes. Empirical data regarding contemporary soil C, N, and P for the contrasting grasslands are used to calibrate the initial size of the weatherable P pool within the model and to allow access to organic cleaved P to vary to account for patterns in the data. We do not aim to perfectly replicate the Wardlow grasslands but rather use the unique opportunity that Wardlow provides to test our understanding of such P-limited ecosystems and how our conceptualisation of P-access mechanisms within the model may affect them. In addition, we can use the model-simulated grasslands to investigate the potential effects of long-term N deposition and nutrient manipulation on ecosystems which may differ in their relative availability of different P forms.
Nutrient treatments are treated in N
N
To use this spin-up phase and simulate contemporary soil C, N, and P stocks, we use a variety of input driver data. Inputs closer to the present are more accurately defined based on site-scale measurements, and assumptions are made regarding past conditions. This approach of spinning up to present-day observations avoids the assumption that ecosystems are in a state of equilibrium, which is likely inaccurate for ecosystems exposed to long-term anthropogenic changes in C, N, and P availability. Input driver data include plant functional type history, climatic data, and N deposition data. A summary of the data used for model input is provided in Supplement Table S3. To simulate the sites' plant functional type history, we used data on Holocene pollen stratigraphy of the White Peak region of Derbyshire (Taylor et al., 1994), which captures important information regarding Wardlow's land-use history for the entire duration of the model spin-up phase.
Input drivers are provided as annual time series to drive the model, and as
the acidic and limestone sites are co-located, these input time series are
shared for both grasslands. It is assumed in the model that anthropogenic N
deposition was negligible prior to 1800 and the onset of the industrial
revolution. After 1800, N deposition is assumed to have increased similarly
across Europe (Schöpp et al., 2003). In N
To provide climate forcing data, daily minimum, mean, and maximum temperature and mean precipitation records beginning in 1960 were extracted from the UKPC09 Met office CEDA database (Table S3). The data closest to Wardlow were calculated by triangulating latitude and longitude data and using Pythagoras' theorem to determine the shortest distance. These data were converted into mean quarterly temperature and precipitation. Prior to this, temperature was assumed to follow trends described in Davies et al. (2016b), and mean quarterly precipitation was derived from Met Office rainfall data between 1960 and 2016 and held constant.
The N
As this is the first time that N
We ran a series of simulations systematically varying P
The model outputs were compared to measured, SOC, SON, and total P (Table S4)
for each grassland. We tested how these parameter sets performed by
calculating the error between the observations and model outputs of the same
variables for each combination of P
Plant biomass C data were excluded from the cost function to allow for blind testing of the model's performance against empirical observations. As the variable most responsive to nutrient additions, in terms of both rapidity and magnitude of the response, we deemed these the most rigorous data to use for separate testing. We included soil C, N, and P data from all nutrient treatments rather than just the control to ensure that the selected parameter combination could better account for patterns in empirical data. For instance, we know that empirical N treatments can increase plant and soil enzyme activity in both Wardlow grasslands (Johnson et al., 1999; Phoenix et al., 2004; Keane et al., 2020), which a calibration to control-only data may not have captured.
While the cost function is a useful tool in allowing the model to simulate
the magnitude of contemporary C, N, and P pools, it does not allow us to
capture all necessary information to accurately simulate grassland responses
to long-term nutrient manipulation. The pattern of grassland response, i.e.
how a variable responds to nutrient treatment, is an important consideration
and is determined in the model by the most limiting nutrient. Consequently,
the parameter combination with the lowest
Below, we first present data regarding the results of the calibration of
P
A comparison of the observed values of
The model calibration selected parameter values for P
The selected parameter combinations resulted in the model simulating the acidic grassland as N-limited and the limestone as P-limited, with reasonable congruence between observed and modelled data. The outputs for the calibrated model are shown in Fig. 2 against the observations for above-ground biomass C, soil organic C, N, and total phosphorous (TP) for both the acidic and limestone grasslands (Fig. 2). Raw data used for Fig. 2 are provided in Supplement Tables S4 and S5.
Plots showing the nutrient most limiting productivity for all nutrient treatments in both simulated grasslands. The vertical dashed line is the year of the first nutrient addition within the model (1995). The value of the lines represents the maximum amount of productivity attainable given the availability of N and P separately. Due to Liebig's law of the minimum approach to plant growth, it is the lowest of the two lines that dictates the limiting nutrient of the grassland and represents actual modelled productivity. Where lines share a value, it can be considered in a state of N–P co-limitation.
Overall, N
Soil organic C on average was slightly overestimated (7.1 % with SE
Time series plots of aboveground biomass C and soil organic C, N, and P for the acidic (panels
Simulated magnitudes of SON are well-aligned with observations for the
acidic grassland, with an average error of 2.3 % (SE
Finally, the model overestimated TP (defined in the model as
organic P plus sorbed P) by an average of 6.0 % (SE
Modelled C, N, and P budgets for the acidic (panels
Modelled acid grassland NPP remained N-limited from 1800 through to 2020 under most nutrient treatments (Fig. 3). Nitrogen deposition increased the potential NPP through time, and the grassland moved toward co-limitation in the LN treatment (i.e. the N and P lines were closer) but remained N-limited (Fig. 3b). In the HN treatment, the acidic grassland shifted to P limitation as N-limited NPP surpasses P-limited NPP (Fig. 3c).
The simulated limestone grassland was also initially N-limited but was driven through a prolonged (ca. 100 years) state of apparent co-limitation until clearly reaching P limitation in 1950, solely as a result of N deposition (Fig. 3). In the 0N treatment, the grassland remained P-limited, but the potential NPP values for N and P are similar, suggesting the grassland is close to co-limitation (Fig. 3e). The LN and HN treatment amplified pre-existing P limitation, lowering the potential NPP of the grasslands (Fig. 3f, g). With the addition of P in 1995, P limitation is alleviated, and the ecosystem transitions to a more productive N-limited grassland (Fig. 3h).
Another way to interpret the extent of nutrient limitation within N
Conversely, while cleaved P is used in the 0N treatment in the acidic grassland, it occurs at approximately one-third of the total rate; hence the grassland is not entirely P-limited (Fig. S1, Table S9). The LN treatment increases the rate of access to cleaved P, and HN causes it to reach its maximum value, confirming the shift to P limitation suggested by the NPP data (Fig. S1, Table S9). Soil organic P cleaving does not occur in the P-treated plots of either grassland.
The model allows the temporal trends and responses to nutrient additions to be further explored. Figure 4 provides the temporal responses for the treatments and Fig. 5 a full nutrient budget for the year 2020. Full data for changes in soil C, N, and P and plant biomass C pools since the onset of large-scale N deposition (1800 within the model) for both grasslands are included in Supplement Table S14. All data used for determining responses of biomass C and soil organic C, N, and P pools to experimental nutrient additions are in Supplement Tables S15 (acidic) and S16 (limestone).
The modelled time series suggest that in the 0N (control) treatment for the acidic grassland, background levels of atmospheric N deposition between the period 1800–2020 resulted in an almost 4-fold increase in biomass C, a near-2-fold increase in SOC and SON, and an increase in the size of the SOP pool by almost a fifth (Fig. 4).
Since initiated in 1995, all C and N pools responded positively to N but not P treatments (Fig. 5a, c, Tables S7, S8). The LN and HN treatments further increased aboveground biomass C by 36.2 % and 61.7 % (Fig. 4a) and increased the size of the total SOC pool by 11.5 % and 20.6 % respectively (Fig. 4c). Similarly, the total SON pool in the acidic grassland increased by 9.7 % in the LN treatment and 36.6 % in the HN (Fig. 4e).
Responses of the SOP pool are in contrast to those of the SOC and SON pools, with LN and HN decreasing SOP by 4.4 % and 9.1 % respectively, while P addition substantially increased the size of the SOP pool by 76.7 % (Fig. 4g). Nitrogen treatments facilitated access to SOP from both subsoil and topsoil, increasing plant-available P and facilitating its uptake into biomass material (Fig. 5e, Table S8).
Model simulations for the limestone grassland also suggest N deposition between 1800 and 2020 considerably increased aboveground biomass C, SOC, and SON pools (Fig. 4) but to a lesser extent than in the acidic grassland. Soil organic C and SON increased by almost half, and biomass C more than doubled. Soil organic P accumulated at a faster rate than in the acidic grassland, increasing by about a third (Fig. 4, Table S14).
Responses of the aboveground biomass C and SOC pools in the limestone grassland differ greatly to those of the acidic grassland, declining with N addition and increasing with P addition (Fig. 4). This response was ubiquitous to all C pools, with declines in subsoil, topsoil, and biomass C (Fig. 5b, Table S10). Biomass C declined by 2.4 % and 7.3 % with LN and HN addition (Fig. 4b), and SOC declined by 0.5 % and 1.4 % with the same treatments (Fig. 4d). Phosphorus addition increased biomass C and SOC by 22.0 % and 6.1 % respectively (Fig. 4b, d).
Nitrogen treatments increased the size of subsoil, topsoil, and available N pools but led to small declines in biomass N (Fig. 5d, Table S11) The P treatment slightly reduced subsoil and topsoil SON compared to the control yet increased available N and biomass N, to the extent that biomass N is greater in the P than HN treatment (Fig. 5d, Table S11). Total SON increased by 6.4 % and 15.0 % with LN and HN respectively and declined by 0.2 % with P treatment (Fig. 4f).
The response of the limestone P pools mirrors that of carbon, with declines in subsoil SOP, topsoil SOP, available P, and biomass P with LN and HN addition (Fig. 5f, Table S12). The limestone grassland SOP pool declined by 0.2 % with LN and 0.5 % with HN addition, with an increase of 20.0 % upon addition of P (Fig. 4h). The P treatment substantially increased total ecosystem P in the limestone grassland, particularly in the topsoil sorbed pool (Fig. 5f, Table S12).
This is the first instance in which N
The model suggests that the acidic grassland was characterised by high access to organic P, with comparatively low inorganic P availability, whereas the limestone grassland was the opposite, with low organic and high inorganic P availability. These simulated differences could reflect the relative availability of different P sources at Wardlow. As the acidic grassland formed in a hillside depression, loess has accumulated, thickening the soil profile and distancing the plant community from the limestone bedrock. The plant rooting zone of the acidic grassland is therefore not in contact with the bedrock, and roots almost exclusively occur in the presence of organic P sources which can be cleaved and utilised by plants (Caldwell, 2005; Margalef et al., 2017). Conversely, the limestone grassland soil rarely exceeds 10 cm depth, and the rooting zone extends to the limestone beneath, providing plants with greater access to weatherable calcium phosphate (Smits et al., 2012).
Such parameter combinations allowed for reasonable congruence between
empirical and simulated data, with an average discrepancy of only 6.6 %
(SE
The overestimation of acidic C pools and underestimation of total P suggest that the model is simulating that too much organic P is being accessed by plants in response to N addition and transferred into plant biomass pools (Fig. 2d). Few parameter sets were simultaneously able to simulate the magnitude of the empirical TP pool and the positive response of biomass to N addition in the acidic grassland. This may also be due to limitations in the empirical P data, as P data used for calibrating P cycling were available for only two nutrient treatments and represented total soil P, not organic P. While we acknowledge the technical and theoretical issues associated with distinguishing between organic and inorganic P pools (Lajtha et al., 1999; Barrow et al., 2020), such distinctions would help in understanding this discrepancy and likely improve the model's ability to simulate P-limited systems, particularly when organic P availability may be important.
Additionally, N
In addition to physico-chemical processes reducing P availability, in P-limited grassland soils, microbial processes may be dominant drivers of ecosystem P fluxes (Bünemann et al., 2012). For instance, while mineralisation of organic P may increase inorganic P in solution (Schneider et al., 2017), this can be rapidly and almost completely immobilised by microbes, particularly when soil P availability is low (Bünemann et al., 2012). As the model lacks a mechanism for increasing access to secondary mineral P forms comparable to organic P cleaving, and microbial P immobilisation is incompletely represented for P-limited conditions, it is possible that the uptake of organic P by the acidic grassland in the model is exaggerated.
The model's inability to simulate a positive response to both N and P
addition in the acidic grassland may be an unintended consequence of the
downregulation of N fixation by N deposition included within N
Ultimately, differences in modelled accessibility to organic forms of P
enabled N
While the model's estimation of P
Nitrogen addition increases plant demand for P and can shift ecosystems
toward a state of P limitation or increase the severity of limitation where
it already exists (Menge and Field, 2007; An et al., 2011; Goll et al., 2012). Consistent
with this, both simulated grasslands saw SOP decline with LN and HN
treatment, worsening P limitation in the limestone grassland and depleting
the SOP pool in the acidic grassland. As P cleaved from organic pools is the least
bioavailable within the model hierarchy (Sect. 2.2.3), this is indicative
of increasing P stress in both grasslands. While SOP declined in both
grasslands, the responses of available and biomass P to nutrient treatments
differed markedly between the grasslands. Due to the higher rate of
P
Such high access to organic P sources in the modelled acidic grassland
likely led it to respond to nutrient enrichment in an N-limited manner,
increasing productivity in response to N deposition and LN and HN treatments
as the model's limiting nutrient stimulated plant growth. Detrital C inputs
from plant biomass are the primary source of SOC accumulation within N
Similar increases in N-limited grassland SOC under N addition have been
shown, resulting from significant increases in below-ground carbon input
from litter, roots (He et al., 2013), and detrital inputs (Fornara et al., 2013),
mechanisms similar to those reported by the model. Similarly, Tipping et al. (2017) used N
Despite its P-limited condition under the HN treatment (Fig. 3c), the acidic grassland continued to accumulate biomass with N addition as the grassland's greater access to topsoil SOP (Table S8) allowed it to acquire sufficient P to stimulate additional growth but not necessarily to alleviate P limitation. This is consistent with the acidic grassland at Wardlow, where N treatment stimulated root surface phosphatases, likely supplying more SOP to plants (Johnson et al., 1999). Our simulated acidic grassland therefore supports the hypothesis that prolonged N deposition may increase SOP access to such an extent that P limitation is alleviated and growth can be stimulated (Chen et al., 2020). Organic P release from SOM and its potential immobilisation are poorly represented in models, and we encourage further study aimed at quantifying these processes (Chen et al., 2020; Janes-Bassett et al., 2020; Phoenix et al., 2020). However, such high rates of SOP access only occurred under experimental LN and HN treatments, and in reality, such rapid degradation of SOP may eventually degrade the pool to such an extent that P limitation soon returns.
Conversely, biomass C and SOC in the modelled limestone grassland responded positively to P addition, via similar mechanisms to the N response in the modelled acidic grassland. However, in contrast to the acidic grassland, N addition caused declines in limestone biomass and SOC, the former of which has been observed at the limestone grassland at Wardlow (Carroll et al., 2003). Reductions in limestone biomass C (and consequently SOC) in the model are a combined result of reductions in bioavailable P (Table S12), occurring via N-driven increases in stoichiometric P demand, in addition to an inability to access sufficient P from the SOP pool (Table S14). Plants therefore cannot meet P demand, and new biomass is insufficient to replace senesced plant material, decreasing net biomass C input to the SOC pool. This suggests that in P-limited limestone grasslands such as at Wardlow, where access to organic P forms may be comparatively limited, N deposition may worsen pre-existing P limitation and reduce ecosystem C stocks (Goll et al., 2012; Li et al., 2018).
While N
N
While we feel incorporating a suite of plant strategies for acquiring P
would represent over-parameterisation, we acknowledge that a modelled
equivalent to P
Currently, N
We have shown that by varying two P-acquisition parameters within N
Differences in organic P access was a key factor distinguishing the contrasting responses of the modelled grasslands to nutrient manipulation, with high plant access allowing the acidic grassland to acquire sufficient P to match available N from chronic deposition and prevent “anthropogenic P limitation”. In the acidic grassland, N treatment stimulated plant access of organic P, promoting growth and C sequestration. However, the model suggests that this is an unsustainable strategy, as the SOP pool rapidly degrades, and if N additions are sustained, P limitation may return. Conversely, in the limestone grassland, which was less able to access organic P, additional N provision exacerbated pre-existing P limitation by simultaneously increasing plant P demand and reducing P bioavailability. This reduced productivity, and consequently C input to soil pools declined, resulting in SOC degradation exceeding its replacement.
We further show that anthropogenic N deposition since the onset of the industrial revolution has had a substantial impact on the C, N, and P pools of both the modelled acidic and limestone grasslands, to the extent that almost half of contemporary soil C and N in the model could be from, or caused by, N deposition.
Our work therefore suggests that with sufficient access to organic P, long-term N addition may alleviate P limitation. Where organic P access is limited, N deposition could shift more ecosystems toward a state of P limitation or strengthen it where it already occurs (Goll et al., 2012), reducing productivity to the point where declines in grassland SOC stocks – one of our largest and most labile carbon pools – may occur.
Data presented in the manuscript have been deposited with NERC's Environmental Information Data Centre (EIDC) at the following DOI:
The supplement related to this article is available online at:
CRT contributed to conceptualisation of the study, data curation, formal analysis, investigation, methodology, project administration, validation, visualisation, and writing. VJB contributed to conceptualisation, formal analysis, investigation, methodology, supervision, and writing. GKP contributed to conceptualisation, methodology, funding acquisition, project administration, resources, supervision, and writing. BK contributed to the investigation, methodology, supervision, and writing. IPH contributed to funding acquisition, methodology, resources, supervision, and writing. JACD contributed to conceptualisation, formal analysis, investigation, resources, methodology, supervision, project administration, and writing.
The authors declare that they have no conflict of interest.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
We thank Jonathan Leake for his insightful interpretation of our findings and for constructive feedback on early versions of the work. In addition, we are grateful for technical assistance from Irene Johnson, Heather Walker, and Gemma Newsome, without whom there would be no carbon and nitrogen data for model input. We are grateful to the Met Office UK and the Centre for Ecology and Hydrology for use of their meteorological and deposition data respectively. We also wish to extend our thanks to James Fisher for his earlier work on Wardlow carbon data, which prompted additional investigation into the grassland's carbon stocks. Finally, we thank the anonymous reviewers for their valuable contributions to improving the paper. Site access was provided by Shaun Taylor at Natural England.
This work was funded by the Natural Environment Research Council award NE/N010132/1 to GKP and NERC award NE/N010086/1 to IPH of the “Phosphorus Limitation and Carbon dioxide Enrichment” (PLACE) project. This work was also funded through “Adapting to the Challenges of a Changing Environment” (ACCE), a NERC-funded doctoral training partnership to CRT: ACCE DTP NE/L002450/1.
This paper was edited by Michael Weintraub and reviewed by four anonymous referees.