Modelling biomass, water and nitrogen in grass ley: Estimation of N uptake parameters

Europ. J. Agronomy 27 (2007) 89–101

Modelling biomass, water and nitrogen in grass ley: Estimation of N uptake parameters H. Eckersten a,∗ , B. Torssell a , A. Kornher b , U. Bostr¨om a,1 a

b

Department of Crop Production Ecology, SLU, Uppsala, Sweden Institute of Crop Science and Plant Breeding, Department of Grass and Forage Science/Organic Farming, CAU University of Kiel, Germany Received 2 November 2006; received in revised form 25 January 2007; accepted 7 February 2007

Abstract The N concentration over the 2-year life cycle of grass swards was modelled assuming plant total N uptake to be the lowest value of the plant N demand and the availability of soil mineral N. The variability in the N demand and N availability parameters was estimated for seven site conditions in Central and Southern Sweden, at three N addition levels (0, 14 and 20 g N m−2 year−1 , respectively) by calibration to measured above ground N concentration. The N demand was a function of plant growth, plant current N concentration and day length. Plant growth and biomass were taken from growth model predictions calibrated to measured aboveground biomass. The N availability was assumed to be a fraction of the soil mineral N within the root zone, which was simulated with soil water and nitrogen models calibrated against previous soil model applications. The plant N maximum concentration (nMax ) was successfully modelled as a decreasing function of increasing biomass and decreasing day length in combination. The fraction of available soil mineral N taken up per day under N limiting conditions (cUptake ) decreased after cutting. The parameters varied between sites, cuts and N treatment levels. The effects of these variations on predicted seasonal N uptake was most pronounced for cUptake and sites, and least for nMax and cuts. It is concluded that cUptake needs to be calibrated for new site conditions in order to accurately predict plant N uptake. © 2007 Elsevier B.V. All rights reserved. Keywords: Grass nitrogen uptake; Parameterization; Nitrogen effects; Plant N demand; Soil mineral N availability; Plant N concentration; Radiation use efficiency

1. Introduction Plant N is of central importance for the yield and protein content of grass leys and for forage quality. By appropriate timing of fertilization and cutting, yield and quality can be optimized. However, planning the optimal timing is not easy, as effects of fertilization interact with site conditions. The weather varies over time and the soil conditions are site-specific, and fertilizers must be applied in relation to these factors (Engel, 1997; Vold et al., 1999; Jamieson and Semenov, 2000; Evans et al., 2001; Jeuffroy et al., 2002; Gastal and Lemaire, 2002; Brown et al., 2005). The problem for the farmer is to match the type of fertilizer and fertilization regime to the site conditions in order to achieve the desired yield and plant N concentration in the harvested product (Torssell and Fagerberg, 1990; Bonesmo and Belanger, 2002; Barrett et al., 2004, 2005). In addition, fertilization should be ∗ 1

Corresponding author. Tel.: +46 18673259. E-mail address: [email protected] (H. Eckersten). Tel.: Tel.: +46 18671449; fax: +46 18672890.

1161-0301/$ – see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.eja.2007.02.003

minimized to lower the costs and adjusted to get the least N immediate leaching (Jensen et al., 1994; Wu and McGechan, 1998; Wu et al., 1998; Kowalenko and Bittman, 2000; Trott et al., 2004; del Prado et al., 2006). It is also important to forecast the effects on accumulated leaching throughout the growth period and the period after harvest, when nitrogen release may increase (Trebada-Crende and Vinten, 1998; Aronsson and Torstensson, 1998; Singh and Sondhi, 2001; Korsaeth et al., 2003; Wolf et al., 2005). At the present state of the art, the task is not to permanently solve the problem of prediction, but rather to improve prediction and to examine its precision on the basis of current process knowledge (Wu and McGechan, 1998; Jamieson and Semenov, 2000; Gastal and Lemaire, 2002). 1.1. N demand There are many papers describing models for nitrogen dynamics and their underlying concepts, ranging from single model descriptions and applications (e.g. O’Leary and Connor,

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1996; Riedo et al., 1998; Thornley, 2001; Vold et al., 1999; Thornley and Cannell, 2000; Evans et al., 2001; Bonesmo and Belanger, 2002; Kage et al., 2003; Nkoa et al., 2003; del Prado et al., 2006; Jouven et al., 2006a) to more general reviews (e.g. Bachelet et al., 1989; Wu and McGechan, 1998; Jamieson and Semenov, 2000; Gastal and Lemaire, 2002; Jeuffroy et al., 2002). The processes for plant N uptake, allocation within plant and loss by litter fall, basically determine the changes in plant N, of which plant uptake is possibly the most crucial process for the prediction of plant N dynamics. Models for simulating the N uptake range from simple concepts based e.g. mainly on the N supply by fertilization (Korsaeth et al., 2003) to more processbased approaches (Yang et al., 2002). A commonly used concept for estimating the N uptake is based on two different processes of plant N uptake (Eckersten and Jansson, 1991; Jamieson and Semenov, 2000; Gastal and Lemaire, 2002). When there is a large amount of available N, the uptake is regulated by the maximum plant N uptake related to the plant needs for growth. This is regulated by the availability of carbon and energy in the plant (Novoa and Loomis, 1981; Sinclair and Shiraiwa, 1993), which in turn could be related to the N concentration of the plant, and solar radiation absorbed by the canopy. This process has been described previously in several models (e.g. Wu and McGechan, 1998), most often based on a maximum N concentration that decreases over time. However, time is an indirect factor affecting this concentration. Other more mechanistically based approaches relate the N concentration to plant biomass (Gregory et al., 1979; Lemaire and Salette, 1984; Greenwood et al., 1986, 1991) and/or phenological development (Bange et al., 1997; Sinclair and Amir, 1992). In the present study, we investigated how well we could predict the plant N uptake, setting the maximum N concentration as dependent on a combination of canopy development (biomass) and incoming radiation (day length). 1.2. N availability The second process is the plant ability to take up N when there is less N available in the soil than the plant demands for optimal growth. The uptake is then regulated by the N availability, which is basically determined by soil conditions and root activity. Several very detailed models have been used to mimic these processes (cf. Hansen et al., 1991, 1993; Devienne-Barret et al., 2000), but it has proven very difficult to predict N uptake under N limiting conditions in the field (Feller and Flink, 2002). It is therefore difficult to decide the model approach to be used. The model should mimic the processes in a realistic way, and at the same time be applicable to an extensive data set. In this study, we simulated the soil mineral N content using a partly mechanistic approach based on decomposition and mineralization of N from soil organic material (cf. Blomb¨ack et al., 2003). The uptake by roots was assumed to be proportional to soil mineral N in the root zone. This concept has been used in several previous model applications, usually having the uptake efficiency of soil mineral N as an input, sometime taken from an independent source (cf. Eckersten and Jansson, 1991), sometime estimated without explicitly considering whether the N availability or plant N demand regulates the uptake (cf. Bergstr¨om

and Jarvis, 1991; Johnsson et al., 2002). In the present study, we aimed at identifying situations when uptake was regulated by the N uptake efficiency of the plant and to estimate the variability of this parameter over time and site conditions. 1.3. N limitation The plant N demand was assumed to determine uptake at fertilization rates of 200 kg N m−2 year−1 and a mineralization of approximately 100 kg N m−2 year−1 (Persson, 2003). The other situation, when N availability is limiting N uptake, is found in non-fertilized stands in Sweden almost throughout the whole growing period (Eriksson et al., 1997). Intermediate fertilization levels were used to test the model for combined situations, when both N demand and N uptake regulate uptake. To replicate all these situations, we used field data from a grass ley at three levels of nitrogen application, sampled at seven site × year combinations in Central and Southern Sweden (Fagerberg and Torssell, 1995; Eckersten et al., 2004; Torssell et al., 1997). The main objective of this study was to test how well the N concentration of a grass sward could be predicted from the demand–availability concept. A secondary objective was to estimate the variability in the parameters of N demand and N availability in relation to site conditions and cutting regime, and to evaluate the consequences of variations in these parameters on N uptake. 2. Materials and methods 2.1. Experimental data The field data used comprised aboveground dry matter content and N concentration of a mixture of timothy (Phleum pratense L.) and meadow fescue (Festuca pratensis Huds.) in two seasonal growth cycles during two consecutive years at three levels of nitrogen application, sampled at five sites in Central and Southern Sweden. Seven 2-year experiments were carried out at: Kungs¨angen (59.8◦ N, 17.7◦ E, close to Uppsala) 1985–1986 and 1987–1988, Klevarp (57.7◦ N, 14.3◦ E close to J¨onk¨oping) 1985–1986 and 1987–1988, Lanna (58.5◦ N, 13.3◦ E close to Skara) 1985–1986, Karlslund (59.4◦ N, 17.3◦ E close ¨ to Orebro) 1987–1988, and T¨onnersa (56.5◦ N, 13.0◦ E close to Halmstad) 1987–1988. Soil types differed between sites and were clay, clay loam, sandy loam and loamy sand, respectively, see further Table 1. The three levels of N addition investigated were 0 g N m−2 year−1 (N0), 14 g N m−2 year−1 (N1) and 20 g N m−2 year−1 (N2), respectively. The fertilization was split between two applications. The first application (10 and 12 g N m−2 for N1 and N2, respectively) was made at the onset of spring growth, around 1 May. The second application (4 and 8 g N m−2 , respectively) was made the day after the first harvest, around 10 June, the exact date depending on site and year. The experiment was designed to allow measurements in two consecutive years of the ley (Eckersten et al., 2004; Torssell et al., 1997). It was therefore duplicated in two identical sections, of which the first was used for sampling in the first year, and

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Table 1 Soil characteristics and model soil type for the experimental sites Site

USDA soil type Clay fraction (%) Organic matter (%) Model soil type

Kungs¨angen

Lanna

Karlslund

Klevarp

T¨onnersa

Clay >40

Clay loam 33 3.5 Clay loam

Clay loam 29 4.5 Clay loam

Sandy loam 2.1 3.0 Sandy loam

Loamy sand 7.2 2.6 Sandy loam

Clay

Parameter values related to model soil type are presented in Appendix A.

the second for sampling in the second year. To avoid sampling effects from the first to the second year, the whole second section was harvested at the third sampling time of the first growth period in the first section. In that way the experiment represented a 2-year life cycle of the ley by using the three first samples (day numbers around 154, 161 and 168) in the first growth periods, and all five samples (day numbers around 196, 210, 224, 239 and 252) in the second growth periods each year (cf. Fig. 2). Altogether this gave 16 (3 + 5 + 3 + 5) samples in 7 soil–weather conditions, and 112 (16 × 7) samples for calibration per N treatment. Each harvested sample represented a 2 m × 10 m plot in two replicates, from which subsamples were taken for dry matter and nitrogen concentration determinations. The phenology development changed from leaf stage at first sampling to heading at harvest. 2.2. Model description The model consists of four main modules simulating plant biomass, plant nitrogen, water availability and nitrogen availability, respectively. The models are theoretically similar to the SOIL/SOILN models (Johnsson et al., 1987; Eckersten and Jansson, 1991; Eckersten et al., 2001; Blomb¨ack et al., 2003) but reprogrammed into the Matlab/Simulink (version 5.3/3.0) software environment (MathWorks Ltd.) allowing a transparent representation and flexible linkage and use of modules (Eckersten et al., 2006). The plant biomass and N models are linked to a soil plant water model in terms of the ratio between actual and potential transpiration influencing growth when below unity. In turn the plant biomass model, influences the water model by means of the root depth and leaf area. The soil N model simulates the evolution of the soil mineral N content, as influenced by the plant N uptake simulated by the plant N model. 2.3. Biomass model Daily growth is proportional to the intercepted solar radiation. Growth is further limited by low temperature or low actual to potential transpiration ratio. Assimilates are allocated to leaf, stem and root growth, respectively. Leaf area development is determined by leaf growth being proportional to the specific leaf area, and leaf fall being dependent on leaf age. Stem and roots continuously lose a proportion of their biomass by mortality, and roots also as a fraction of growth. After cutting, a fraction

of the standing biomass is reallocated to growth (for details, see Eckersten et al., 2004; Torssell et al., 1997). 2.4. Water model The water model is based on processes for throughfall, evaporation of intercepted water, soil evaporation, infiltration, soil water storage, root water uptake, transpiration, capillary rise and run-off. The model simulates water dynamics on a daily basis in the vertical dimension, disregarding horizontal water flows into the soil column. Soil heat storage is not considered. The model is basically similar to the water part of the models SOIL (Jansson and Halldin, 1979; Jansson, 1991) and COUP (Jansson and Karlberg, 2004), except that the soil profile is represented by only three layers (Eckersten, 1995). Infiltration and soil evaporation are the dominant processes in the surface layer. In the root zone, root water uptake (transpiration) is most important, and in the zone below the root zone capillary rise and run-off are the most significant processes (for details, see Eckersten et al., 2004; Torssell et al., 1997). 2.5. Soil nitrogen model The soil nitrogen model is based on processes for litter input, N deposition, microbial decomposition, N mineralization, plant N uptake, nitrification, denitrification, nitrate transport and N leaching. The model simulates N dynamics on a daily basis and is linked to the water model. Water flows drive the nitrate transport, and water content influences the microbial activity. Capillary rise of N is neglected. The soil layer representation is the same as for the water model, and otherwise basically similar to the SOILN model (Johnsson et al., 1987; Eckersten et al., 1998, 2001) and the COUP model (Jansson and Karlberg, 2004). All processes are active in all three layers except for root N uptake and litter fall, which do not occur in the layer below the root zone. The model has been described in more detail in an application to short rotation forests by Noronha-Sannervik (2003) and Eckersten et al. (2006). 2.6. Plant nitrogen model The plant nitrogen model is linked to the biomass model (Fig. 1). The plant N uptake and allocation losses are related to the plant biomass dynamics. In total, there are three main flows determining daily changes in plant N (Eq. (1)): uptake from soil

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fnD =

D − DMin , DMax − DMin

0 ≤ fnD ≤ 1

nMaxShoot = nMax0 fnW fnD ,

Fig. 1. Approximate schematic description of N dynamics of the N uptake model. Shoot and root biomass, and soil mineral N are simulated with linked models programmed in Matlab/Simulink (MathWorks Ltd.). N losses are not represented in the figure.

(NSoil→Plant ), loss by litter (NPlant→Litter ) and loss by harvest (NPlant→Harvest ): NPlant = NSoil→Plant − NPlant→Litter − NPlant→Harvest t ×(g N m−2 d−1 )

(1)

When there is sufficient available N in soil to cover the plant demand for N, root uptake is driven by the demand. The plant is divided into two pools for nitrogen, shoot (leaves and stems) and roots, each with a specific maximum concentration (nMax0 and nMaxRoot , respectively). The demand (NDemand ; g N m−2 d−1 ) is determined by the maximum N concentration of the daily growth of shoots (WShoot /t) and roots (WRoot /t). However, the demand is also limited so as not to exceed the maximum N concentration of the standing biomass that decreases with plant biomass and decreasing day length. The plant N demand (NDemand ; g N m−2 d−1 ) is limited to the difference (NDeficit ; g N m−2 ) between the maximum plant N and its actual N content: NDemand =

nMax0 WShoot nMaxRoot WRoot + , t t

≤ NDeficit (2a)

NDeficit = (nMaxShoot − nShoot )WShoot +(nMaxRoot − nRoot )WRoot

(2b)

where nMaxShoot and nMaxRoot are maximum N concentration of the shoots and roots, respectively, and nShoot and nRoot are the corresponding actual concentrations. WShoot and WRoot are the biomass of shoot and root (g d.w. m−2 ), respectively, simulated by the biomass model. nMaxRoot is set constant. For the shoots the maximum concentration (nMaxShoot ) decreases with increased shoot biomass, and decreases with decreasing day length (D): fnW = 1 −

WShoot , WMax

0 ≤ fnW ≤ 1

(3a)

≥ nMinShoot

(3b) (3c)

where WMax , DMin and DMax are parameters determining the reduction of shoot N concentration from its maximum value (nMax0 ) due to changing shoot biomass and day length. Shoot N concentration is not lower than a minimum concentration (nMinShoot ). The equations of nMaxShoot are expected to reflect the influence of structural biomass and self-shading (Eq. (3a)), and the influence of average incoming solar radiation (Eq. (3b)). The day length function was introduced because the one and the same parameter set of the biomass function was not able to predict nMaxShoot in both the first and the second growth period, and during winter. We also tried a curve linear response to increasing biomass as proposed by Gastal and Lemaire (2002), however, as the same parameter set could not be applied for the whole season, we instead used two linear functions of biomass and day length. When N availability is lower than the N demand, N uptake is limited by the ability of roots to take up the soil mineral N (NSoilMineral ). This is expressed in terms of the N uptake efficiency (cUptake ), i.e. the fraction of NSoilMineral that can be taken up per day. The actual N uptake to the whole plant during a single day then equals the minimum value of the available amount and the plant N demand: NSoil→Plant = min(cUptake NSoilMineral , NDemand )

(4)

NSoilMineral and NDemand are updated daily and N uptake might shift between availability and demand limiting from one day to the other. The available soil mineral N is located in the root zone and the surface layer. The N in the root zone is utilized first to cover N demand. In the event of a deficit, N in the surface layer is also utilized. The uptake to the total plant is allocated between roots (NPlant→Root ) and shoots (NPlant→Shoot ). First all N is distributed to achieve equal concentrations in both roots and shoots. If there is excess N above the concentration of the roots (nRoot ), the rest is distributed to the shoots (NPlant→Shoot ). This approach result in an almost constant root N concentration (nRoot ; cf. Mulder et al., 2002): nMaxRoot WRoot , t nRoot WShoot < NSoil→Plant − t

NPlant→Root =

NPlant→Shoot = NSoil→Plant − NPlant→Root

(5a) (5b)

Plant lose N by litter fall in relation to N concentrations of the tissues. However, a certain fraction (a) of the N is redrawn to the plant before abscission: NPlant→Litter = (1 − a)nShoot WShoot→Litter +(1 − a)nRoot WRoot→Litter

(6)

where WShoot→Litter and WRoot→Litter are daily litter fall of shoot and roots taken from the biomass model simulations. For roots

H. Eckersten et al. / Europ. J. Agronomy 27 (2007) 89–101

there is an additional loss at harvest, when a fraction (30%) of the root biomass is assumed to be lost as litter. At harvest, the shoots lose N in relation to the N concentration of the harvested material: NPlant→Harvest = nShoot WShoot→Harvest

(7)

where WShoot→Harvest is the amount of shoot biomass taken away at harvest, as simulated by the biomass model. 3. Model inputs 3.1. Input variables Daily values of mean air temperature, mean relative air humidity, mean wind speed, precipitation sum and global radiation sum were taken from national meteorological network stations (SMHI) near the experimental locations. For Kungs¨angen, data from the SLU climate station in Uppsala (Lat. 59.8◦ N; Karlsson and Fagerberg, 1995) were used. For Lanna, Karlslund, Klevarp and T¨onnersa, data from Skara ¨ (58.3◦ N), Orebro (59.3◦ N), J¨onk¨oping (57.7◦ N) and Halmstad ◦ (56.6 N) national network weather stations were used, respectively. The average temperature during April to September ranged 9.6–13.6 ◦ C between sites and years. The corresponding ranges of precipitation sum was 268–586 mm, average daily solar radiation 12.1–15.6 MJ m−2 d−1 , average relative air humidity 71–81%, and for average wind speed 1.6–4.2 m s−1 . Biomass variables, which drive the N dynamics (WShoot , WRoot , WShoot→Litter , WRoot→Litter and WShoot→Harvest in Eqs. (2a), (2b), (3a) and (5)–(7)) were simulated using the biomass model, which had been calibrated to the aboveground biomass measurements of the current experiment for each single growth period by Eckersten et al. (2004). These simulations mimicked the aboveground biomass well (R2 was on average 0.97 and ranged between 0.91 and 0.99). The soil simulations ultimate role for this study was to provide a soil mineral N driving variable for the plant N uptake model. The humus decomposition rate was adjusted at each site to achieve a stable soil mineral N fluctuation over the 2-year period. 3.2. Parameterization The parameterization adopted a multi-parameter model to site conditions with a very limited amount of information. We reduced the number of parameters to be set at each site by introducing soil types with specified parameter values. Only the parameters for initial soil mineral nitrogen and decomposition of humus in the soil N model were calibrated for each site. Four soil types were used: clay, clay loam, sandy loam, and loamy sand. The parameters of the soil models were taken from previous applications (Eckersten et al., 2006; see also Johnsson et al., 2002). Values are given in Appendix A. For our applications we allocated a specific model soil type to each site in accordance to its USDA classification (Table 1).

93

Table 2 Parameterization of the plant nitrogen model for grass ley Parameter Initial maximum shoot N concentration Minimum shoot N concentration Maximum root N concentration Shoot biomass at no N demand Day length at maximum N concentration Day length at no N demand N uptake efficiency Fraction of N redrawn at abscission

Symbol

Value

Unit

Reference

nMax0

0.04

g N g d.w.−1

Calibrateda

nMin

0.015

g N g d.w.−1

b

nMaxRoot

0.015

g N g d.w.−1

b

WMax

Varies

g d.w. m−2

Calibrateda

DMax

20

h

Arbitrary

DMin

Varies

h

Calibrateda

cUptake a

Varies 0.3

d−1 –

Calibrateda Thornley (2001)

a

See Section 4. Salette et al. (1984), Talbourel-Tayot and Gastal (1998b) and Gastal and Nelson (1994). b

The parameters of the biomass model were all set independently of the nitrogen simulations, taken from an earlier calibration of the model to the biomass data of this experiment (Eckersten et al., 2004; Torssell et al., 1997, see Appendix A). For the plant N model (Table 2), parameters for maximum N concentration and specific N uptake rate were calibrated. In the calibration, the first step was to estimate the functions for maximum N concentration of shoots (nMaxShoot ) for the high fertilization trials (N2 ). The mineralization was initially set high to make simulated N uptake independent of availability. The parameters nMax0 , WMax and DMin (Eqs. (3a–3c)) were calibrated to fit simulated N concentration to observed values. nMax0 was set to a common value for all sites, and was mainly determined by the N concentration in the first growth period of the first year. The responses to biomass and day length (WMax and DMin ) were adjusted to site conditions (i.e. to every site and every 2year period) to estimate the variation in these parameters, and to get a best fit to optimal conditions to be used for the simulations of N limiting conditions at the sites. The second step was to calibrate the specific decomposition rate of humus (kh ), determining the mineralization of N to the soil mineral N pool, so as to fit observed plant N contents of the non-fertilized treatment (N0). The targets were accumulated seasonal uptake to simulate reasonable total N supplies to plant. The resulting simulated final soil mineral N of 31 December in the second year, was then used as the initial soil mineral N of 1 January in the first year for the next simulation with a new value of kh . This was repeated until a fairly stable NSoilMineral pattern was achieved from year to year. The third step was to calibrate the N uptake efficiency (cUptake ; Eq. (4)) to N concentration for each separate growth period. In this way the variation in cUptake between growth periods was estimated. The model was thereafter validated to the medium fertilization stand (N1), which had a growth rate closer to N2 than N0 (Lunnan and Nesheim, 2002) and an intermediate N concentration.

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3.3. Statistical analysis To evaluate statistically significant effects of growth periods on calibrated model parameters, a one-way ANOVA was performed with growth periods as treatment factor. The MIXEDprocedure of the SAS package (SAS, 1999) was applied. A mixed model approach was used (Littell et al., 1996), as the time series of samples were taken from the same plot in a replicate (Torssell et al., 1997). Two statistical measures for model fit were used: (i) linear regression with the simulated variable as independent and the observed variable as dependent variable. The regression line includes the slope (b) and the intercept (a) of the line, and the square of the correlation coefficient between observed and calculated data (R2 ). Model parameter values were chosen by maximising R2 and achieving a slope (b) as close to one as possible. For model evaluation, R2 wasused (Analla, 2 1998),  and model  efficiency2 as defined by ( (M − Mmv ) 2 − (S − M) )/ (M − Mmv ) (Smith et al., 1996), where M is the measured value, S the simulated value and Mmv is the mean of measured values. 4. Results 4.1. Simulated C, N and water budgets The simulations were made with closed soil–plant budgets for carbon, nitrogen and water. As an example, for the nonfertilized stand of the clay soil at Kungs¨angen 1985, 1986, the annual net exchange of carbon from the atmosphere to plant was 705 g C m−2 year−1 , harvest 450 g C m−2 year−1 , and soil respiration 180 g C m−2 year−1 . Hence there was a net increase of carbon in the soil–plant system of 74 g C m−2 year−1 . The annual input of N by deposition was 0.74 g N m−2 year−1 , and the loss by N leaching was 0.6 g N m−2 year−1 . At harvest, 6.73 g N m−2 year−1 was removed and the soil C/N ratio had increased. The N mineralization and total plant N uptake were similar, 9.84 and 9.75 g N m−2 year−1 , respectively. Annual input of water by precipitation was 644 mm year−1 . Almost equal parts were lost by evapotranspiration, 305 mm year−1 , and by run-off, 328 mm year−1 . All 21 site and N treatment simulations achieved their own balance as a consequence of different growth rates and inputs (data not shown). There were some general differences between N treatments. In the high fertilization stands, all the C and N flows were two to three times larger except soil respiration and N mineralization, which were only slightly changed, and N leaching sometimes even decreased, especially for the sandy loams, compared to the non-fertilized control. The C/N ratio of soil organic matter did not increase for the high fertilization stands. For the sandy loams, the evapotranspiration to run-off ratio was essentially lower than for the clay soils. It ranged from 0.5 for non-fertilized to 0.65 for fertilized stands. 4.2. Calibration The fit of the simulations to observed values of N concentration were best for the high fertilization stands (N2; see example

Fig. 2. Simulated (solid line) and measured shoot N concentration (points) (g N g−1 d.w.) for (a) the high fertilization stand (N2) at the Kungs¨angen site 1985–1986, (b) the non-fertilized stand (N0) at the Kungs¨angen site 1985–1986, and (c) the medium fertilization stand (N1) at the Kungs¨angen site 1985–1986.

in Fig. 2a). R2 for each site varied between 0.75 and 0.95 and was on average 0.90. The R2 for plant N amount was somewhat higher ranging from 0.82 to 0.98 (mean = 0.93). The corresponding values for model efficiency was 0.54–0.89 (mean = 0.74) and 0.62–0.94 (mean = 0.76), respectively. The maximum shoot N concentration (nMax ) parameter expressing the influence of biomass (WMax ; Eq. (3a)) varied between sites, whereas the parameter expressing the influence of day length (DMin ; Eq. (3b)) was almost constant (Table 3). Biomass was the main limiting factor for nMaxShoot in the first growth period, whereas in the second growth period, biomass and day length both limited nMaxShoot . During autumn and spring, day length was the dominant limiting factor. During winter, the minimum N concentration determined the N concentration.

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95

Table 3 Calibrated parameter values for the above ground biomass at no N demand (WMax , g d.w. m−2 ), the day length at no N demand (DMin , h), initial soil mineral N (NOrg (t0 ), g N m−2 ), the specific humus decomposition rate (kh , ×10−3 d−1 ), and the specific N uptake rate (cUptake , % d−1 ), for different site conditions and growth periods achieved by calibration to plant N concentration Site

WMax

DMin

NOrg (t0 )

kh

cUptake

Kungs¨angen 1985–1986 Kungs¨angen 1987–1988 Lanna 1985–1986 Karlslund 1987–1988 Klevarp 1985–1986 Klevarp 1987–1988 T¨onnersa 1987–1988

1500 1500 800 900 1200 900 900

4 4 5 4 4 4 4

5 5 5 10 20 25 25

0.120 0.075 0.050 0.070 0.350 0.200 0.150

Mean

1100

4.1

13.6

0.150

1

2

3

4

10 (1) 3 (1) 8 (1) 9 (1) 7.5 (1) 5 (1) 3.5 (1)

4.0 (0.40) 1.0 (0.33) 3.5 (0.43) 3.2 (0.36) 4.8 (0.64) 1.8 (0.36) 0.4 (0.11)

3.5 (0.35) 5 (1.67) 2 (0.25) 10 (1.11) 1.3 (0.17) 5 (1.0) 3.4 (0.97)

0.95 (0.01) 1.7 (0.08) 0.6 (0.08) 2.6 (0.28) 0.44 (0.05) 3.5 (0.70) 1.3 (0.37)

2.67 (0.41)

4.31 (0.65)

1.58 (0.24)

6.57 (1)

cUptake (i) means cUptake of period i (i = 1–4). Values in brackets are cUptake (i) normalised to cUptake (1) for each site.

The calibrated fit to the non-fertilized stands (N0) was essentially lower than for N2 (see example in Fig. 2b). R2 for nitrogen concentration ranged 0.31–0.96 (mean = 0.66), and R2 for plant N amount was higher ranging from 0.92 to 0.99 (mean = 0.96). The corresponding values for model efficiency was −0.98 to 0.91 (mean = −0.11) and 0.77–0.94 (mean = 0.97), respectively. The fraction of soil mineral N (NSoilMineral ) taken up per day (cUptake ) under N limiting conditions varied with growth period, age and site (Table 3). There was a statistically significant reduction in the uptake efficiency between growth periods within years, but the reduction between years was not significant (Fig. 3). 4.3. Soil mineral N Initial soil organic N (NOrg (t0 )) and specific humus decomposition rate (kh ) were calibrated for each soil in the unfertilized treatment (Table 3), so that simulated soil mineral N (NSoilMineral ), that varied over time (Fig. 4), remained at essen-

Fig. 3. Fraction (%) of available N taken up per day (mean over sites) for first and second growth period in the first year (1, 2) and in the second year (3, 4). Bars indicated by the same letters (A–C) are not significantly different (LSD, P > 0.05).

tially the same level at the start and at the end of the 2-year period. This target was satisfactorily met for all sites (except for Klevarp 1985, 1986), confirmed by an almost zero correlation (R2 = 0.03) between the mean NSoilMineral for each period and site, on one hand, and mean day of the period on the other hand. 4.4. Model test The model with parameterization derived from the N2 and N0 treatments was validated for the medium fertilization stand (N1; Fig. 2c). R2 for nitrogen concentration ranged 0.35–0.76 (mean = 0.50), and R2 for plant N amount ranged from 0.37 to 0.95 (mean = 0.77). The corresponding values for model efficiency were −1.06 to 0.50 (mean = −0.30) and −2.81 to 0.74 (mean = −0.15). In most parts of the first growth period of each year, the uptake (NSoil→Plant ) was determined by the plant N demand (parameters WMax and DMin ), whereas in the second growth period it was mainly determined by the N availability for root uptake (parameter cUptake ). The N concentration was overestimated, especially in the second growth period. The discrepancy might be explained by too high values of cUptake . To evaluate the degree to which cUptake was overestimated, it was

Fig. 4. Simulated soil mineral N (g N m−2 ) of root zone (solid line), surface layer (lower dashed line), and below root zone (upper dashed line). Note that the time period (x-axis) of two full years is plotted.

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Table 4 Relative deviation in simulated annual total N uptake due to using parameter values of cUptake , WMax and DMin derived from another N treatment or site (Table 3) Site

Kungs¨angen 1985–1986 Kungs¨angen 1987–1988 Lanna 1985–1986 Karlslund 1987–1988 Klevarp 1985–1986 Klevarp 1987–1988 T¨onnersa 1987–1988 Average a b c

NUptake (%) cUptake a from N0

cUptake b from another site

WMax , DMin c from another site

11 −7 −8 4 10 0 −20

– −34 −3 −4 3 −18 −50

– 0 −24 −18 −6 −18 −18

−1

−17

−14

Deviation in N1 simulation of the site concerned due to using the cUptake values calibrated for the N0 treatment. Deviation in Kungs¨angen 1985–1986 N0 simulation due to using cUptake as calibrated for the N0 treatment of the site concerned. Deviation in Kungs¨angen 1985–1986 N2 simulation due to using WMax and DMin as calibrated for the N2 treatment of the site concerned.

recalibrated to fit N concentration of N1. The average values for the seven sites of cUptake for the growth periods 1–4 changed from being 6.6, 3.0, 4.5 and 1.4% d−1 for the N0 treatments (Table 3), to 5.6, 2.3, 4.7 and 1.5% d−1 for the N1 treatments. The recalibration of cUptake increased the R2 value from 0.50 to 0.74. The errors in the predictability of N uptake of N1 treatments caused by using the cUptake values derived from calibration to N0 conditions varied considerably between sites (−20% to +11%; Table 4). Only 1 year was investigated in this case, since the change in N availability of the second year to a large extent compensated for the change in cUptake of the first year. Similarly, the consequence on simulated N flows at a certain site of using parameter values calibrated for another site was investigated. The Kungs¨angen 1985–1986 non-fertilized simulation was repeated using cUptake as calibrated for the other sites. The lowest values of cUptake were achieved for the loamy sand at T¨onnersa (Table 3). Using these values for Kungs¨angen 1985–1986 resulted in an underestimation of accumulated N uptake by 50% (Table 4), indicating that the influence of soil conditions is very important for predictions under N limiting conditions. Furthermore, the influence of years seems to be important, as shown by the simulations for Kungs¨angen and Klevarp. Using a calibration for the 1987–1988 period in 1985–1986 predictions caused an underestimation of N uptake of about 20–30% and an overestimation of leaching of up to 40% (data not shown). The importance of site-specific calibration of the parameters related to plant maximum N concentration (WMax , DMin ) for predicting N flows under high N availability situations was also evident, although considerably less than for cUptake . It seems that the influence of year is small, so that parameter values calibrated for one period might be used, with minor errors, for predictions for another period. However, as regards differences due to sites, Kungs¨angen had a considerably higher N demand function than the other sites (Table 4).

4.5. N uptake in relation to radiation use The radiation use efficiency (ε), defined as non-water- or temperature-limited total growth per unit intercepted global radiation, estimated for these stands (Eckersten et al., 2004), changed

Fig. 5. Relation between mean radiation use efficiency and mean fraction of available N taken up per day. Points represent means over sites for (from the right): first and second growth period in the first year and in the second year.

systematically in relation to the growth period, similarly to cUptake , and there was a relationship between the two for the N0 treatments (the coefficient of determination R2 = 0.49; one value rejected). The growth period mean values of cUptake and ε, respectively, were almost linearly related (Fig. 5). 5. Discussion The results indicated that the plant maximum N concentration could be described as a decreasing function of increasing biomass and decreasing day length in combination, and that these functions were approximately similar for different site conditions. Plant N uptake and its conversion into different N compounds in the plant is energy demanding (cf. Jamieson and Semenov, 2000; Gastal and Lemaire, 2002). Our results are in line with this theory, where we expressed the available solar energy to the canopy in terms of increasing day length, and per leaf area by decreasing shoot biomass. In addition, the N concentration is expected to decrease at high biomass due to a higher proportion of structural tissues with low N concentrations (Sheehy et al., 1996; Talbourel-Tayot and Gastal, 1998a,b; Wu and McGechan, 1998; Garnier et al., 1999). The maximum N concentration was higher for the Kungs¨angen site than for the other sites, indicating that 20 g N m−2

H. Eckersten et al. / Europ. J. Agronomy 27 (2007) 89–101

year−1 fertilization rates did not necessarily provide optimal N conditions for all the other sites. The Kungs¨angen site is known to be nutrient-rich. In addition, recent studies have shown a considerable contribution of non-exchangeable ammonium N from clay minerals and this contribution was highest for the Kungs¨angen clay soil among several Swedish soils studied (R¨oing, 2005). The present study also indicated that the fraction of soil mineral N taken up per day (cUptake ) under N limiting conditions decreased significantly after cutting (Table 3 and Fig. 3), which is in agreement with observed reductions in N uptake per plant after defoliation of ley grass species (Thornton and Millard, 1996; Mackie-Dawson, 1999; Jouven et al., 2006b). Our study shows a reduction in cUptake larger than 50% which might result in pronounced effects on other flows on the field, like N leaching. The cutting regime was fixed. A variation in cutting regimes would, though, have allowed a more general analysis of for instance the plant development stage effect on the cutting effect. The estimated value of cUptake depends on the value of NSoilMineral , which was simulated. There were no observations of the soil mineral N for the current data set. However, the simulations fulfilled two reasonable assumptions. NSoilMineral was stable between years, and the amounts of N taken up to aboveground biomass were similar to the observed values. It could be argued that NSoilMineral would decrease over years in the non-fertilized treatment, since the preceding barley crop had been fertilized by about 10 g N m−2 year−1 (see Eckersten et al., 2004). The absence of annual trends might then have resulted in an overestimation of NSoilMineral , and the decrease in cUptake after cutting might be explained by this assumption, although probably only to a minor extent as NSoilMineral levels were low in the second cut (Fig. 4). To evaluate this effect the correlation between cUptake and NSoilMineral was estimated. The test revealed a weak insignificant, negative relationship between the two factors (R2 = 0.09), apparently not large enough to explain the decrease in cUptake with growth period. In many model applications, cUptake has been assumed to be constant and is often set arbitrarily (cf. Johnsson et al., 1987; Sheehy et al., 1996; Talbourel-Tayot and Gastal, 1998a,b; Blomb¨ack et al., 2003). In these applications, the soil profile has been divided into several layers. This, together with a partial compensatory uptake between layers, has made it very difficult to estimate any variation in cUptake or address the importance of a realistic variation. There are, however, modelling approaches for the variations in cUptake . In detailed models (e.g. Hansen et al., 1991, 1993; Yang et al., 2002) cUptake is allowed to increase with transpiration to represent an increased bulk water flow to roots and in plants. In our study, cUptake had a tendency to decrease after cutting and with age (year). On average, we could expect drier conditions in the second growth period than in the first, and transpiration rates might have been lower and thus might explain a decrease in cUptake . However, for the second year this would not be the case, and instead a possible decreased vitality of the plant might have decreased transpiration (Stockle and Kiniry, 1990; Cavigilia and Sadras, 2001; Stone et al., 2001; Kemanian et al., 2004; Steduto and Albrizio, 2005).

97

In detailed models, cUptake can also increase due to high diffusion rates at large gradients in N concentration between the soil solution and the root surface (Hansen et al., 1993). This situation would appear upon an N deficit arising in plants, decreasing the concentration at the root surface. In our data we sometimes, within individual growth periods, found that observed shoot N concentration decreased less than predicted values when using a constant value for cUptake (cf. period 2 in Fig. 2b), but this pattern was not general. The variation of cUptake with growth period and age (Table 3 and Fig. 3) was similar to that found in an independent estimate of radiation use efficiency of the same fields by Eckersten et al. (2004) and Torssell et al. (1997) (Fig. 5). RUE was basically estimated from intercepted radiation and above ground biomass, without considering the N conditions explicitly. The N uptake efficiency (cUptake ) was estimated without any dependency on RUE, from the N concentration of shoots and the amount of soil mineral N, for the N limited (non-fertilized) conditions. So RUE is a measure of how solar radiation was utilized to achieve the observed above ground biomass, and cUptake is a measure of how soil mineral N was utilized to achieve the observed N concentration, and we found indications that the two measures were related for non-fertilized stands. Genotype specific characters are expected to influence root growth and would influence the value of cUptake . However, in the present study the similar plant material was used throughout, and the estimated variation in cUptake reflects the importance of site conditions. A deeper knowledge of the variation in plant N uptake efficiency would be of importance in planning crop rotations for improved N management and utilization. 6. Conclusions Decreasing maximum shoot N concentration was successfully modelled as a function of increasing shoot biomass and decreasing day length. The effects of variations in this function among sites on simulated N flows were small, except for one site with a considerable higher maximum N concentration. The fraction of soil mineral N taken up per day (N uptake efficiency; cUptake ) decreased after cutting. This variation with growth period correlated with variations in the plant ability to utilize the intercepted radiation. The parameter cUptake varied considerably between sites and fertilization levels and need to be calibrated for new site conditions or fertilization rates, to predict plant N uptake. Appendix A. Parameterization of models Parameter values for the soil and the biomass models were taken from previous applications described by Eckersten et al. (2004). The values are given in Table A1. A.1. Soil N model See Table A1.

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Table A1 Parameterization of the nitrogen model for grass ley, Kungs¨angen 1985–1986 Parameter Initial states Initial root depth Plant initial d.w.: leaf, stem, root Initial soil organic N Initial C/N ratio of soil Initial soil mineral N

Symbol

Value

Unit

Reference

zr (t0 )

1 0, 0 variesa Variesc Variesc Variesc

m g d.w. m−2 g N m−3 g C m−3 g N m−3

Assumed established root system (3) Calibrated vs. plant N at 1:1 harvest for N0 Kung1b From SOILN simulationd From SOILN simulationd From SOILN simulatione

1.0 5

m g d.w. m−2

zOrg zMin cUptake CNRatioMic Q10 θ0 , θ1

Variesc Variesc Variesf 10 2.75 θ Poro − 0.325, θ Poro − 0.025

m m d−1 g C gN−1 – m3 m−3

(1) From previous application (2) Set to achieve almost max root depth at start of simulation From SOILN simulationd From SOILN simulationd Calibrated against above ground N concentration Eckersten et al. (2001) Calibrated vs. temperature responseb Calibrated vs. moist responseb

fl fh kl kh kCorr

0.4 0.2 0.015 Variesa 1.3θ/θ Poro

– – d−1 d−1 –

Calibrated vs. C/N ratiog Calibrated vs. C/N ratiog Calibrated vs. soil C and Nb Calibrated in this study Calibrated vs. accumulated N leachingb

NOrg (t0 ) COrg /NOrg (t0 ) NMin (t0 )

Nitrogen model Max root depth Root coefficient Depth of soil organic matter Depth of soil mineral N Fractional uptake of soil mineral N C/N ratio of microbes Microbial temperature response Microbial moisture response. Lower and upper limits Microbial efficiency of litter Microbial efficiency of humus Litter specific decomposition rate Humus specific decomposition rate Correction of N flow a

Varies with site (calibrated, see main text). Calibrations linked to each other. c Varies with soil type, see Table A3.

b d

SOILN simulation of S¨ankan clay soil (Eckersten et al., 2001).

e

Profile distribution from S¨ankan simulation (see footnote d) but total profile from Modellskogen simulation (see footnote b). f Varies with growth period (calibrated, see main text). g SOILN simulation of S¨ankan clay soil and Mellby loamy sand.

A.2. Water model The water parameterization was taken from an earlier application to biomass measurements of the same experiments (Eckersten et al., 2004) and is given in Table A2. Table A2 Parameter values of the water model for a winter wheat stand on a clay soil (S¨ankan), and a loamy sand (Mellby) Parameter

Symbol

Value

Unit

Reference

Total soil depth Maximum root depth Surface layer thickness Coefficient1 for soil surface resistance Coefficient2 for soil surface resistance Saturated hydraulic conductivity Coefficient for soil hydraulic resistance Porosity Critical soil water potential for maximum root uptake Coefficient for reduction of water uptake as function of potential transpiration Maximum stomata conductance per leaf area in Lohammar equation Coefficient a in Lohammar equation Coefficient b in Lohammar equation Rain interception coefficient Experimental decrease rate related to radiation of stomata resistance per leaf area Height of canopy and wind speed measurements, respectively Run-off correction factor

zSoilDepth zRDmax zSurf crss1 crss2 kSat cSoil θ Porosity ψCrit ct

2 1 0.04 275 Variesc Variesc 2 Variesc Variesc Variesc

m m m s m−1 MPa−1 m d−1 – m3 m−3 MPa d mm−1

From SOIL simulationa (depth for zero accumulated vertical water flow) Assumed From SOIL simulationa Calibrated vs. accumulated soil evaporationb Calibrated vs. accumulated soil evaporationb Calibrated vs. accumulated run-offb Kowalik and Eckersten (1984) From Johnsson et al. (2002) Transpiration reduction occurs directly at water content below saturation Calibrated vs. accumulated transpiration and Et /Etp b

cMax

Variesc

m s−1

Calibrated vs. accumulated transpiration and Et /Etp b

aL bL kI

13 6 0.05d 0.05

MJ m−2 hPa – m2 W−1

Blomb¨ack and Eckersten (1997) Blomb¨ack and Eckersten (1997) Calibrated vs. accumulated evaporation of intercepted precipitationb Estimated

1, 1.5

m

Arbitrary

a

0

Calibrated vs. accumulated run-offb

Inputs used in SOIL model simulation for winter wheat (Eckersten et al., 2001). Simulated values of SOIL model simulation for 1980–1986 (Eckersten et al., 2001). Clay values are calibrated against the S¨ankan simulation and the sand values against the Mellby simulation. c Varies with soil type, see Table A3 below. d Only values that differ from the clay soil are given. b

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99

A.3. Soil parameters that differ between soil types See Table A3. Table A3 Soil model parameters that differ between the experimental sites Clay (Kung 1, Kung 2)

Clay loam (Lanna, Karlslund)

Sandy loam (Klevarp 1, Klevarp 2)

Loamy sand (T¨onnersa)

75 1 0.475 1 0 0.01 0.0068

75 1 0.475 1 0 0.01 0.0068

500 40 0.45 3 −0.0002 0.04c 0.0088c

500 100 0.435 4 −0.0001 0.04 0.0088

2100e 1500e 640e

2100f 1500f 838f , h

2300g 1500g 482g , h

2300 1500 943

Initial C/N ratio in layers: surface, root zone, below (g C g N−1 )

11.5e 10.5e 10.5e

11.5f 10.5f 10.5f

15.5g 15.5g 0g

15.5 15.5 0

Initial soil mineral N in layers: surface, root zone, below (g m−3 )d

See Table 3 2.4e 1.7e

See Table 3 2.8f 2.2i

See Table 3 7.9g 5.1g

See Table 3 9.5 7.8

zOrg (m) zMin (m) kl (d−1 ) kh (×10−5 d−1 )

1.2e 1.5e 0.006e 12e

1.2j 1.5f 0.006f 5f

0.8k 1.3g 0.015g 35g

0.7 1.2 0.015 15

Water model crss2 a (MPa−1 ) kSat a (m d−1 ) θ Poro a pF soil typeb ψCrit a (MPa) ct (d mm−1 ) cMax (m s−1 ) Nitrogen model Initial soil organic N in layers: surface, root zone, below (g m−3 )d

For explanation of water symbols see Table A1, and for nitrogen symbols see Table A2. a From application of the RUE-W model by Eckersten et al. (2006). b From Johnsson et al. (2002). c From calibration to a SOILN simulation for sandy loam (Uppsala 1980–1986 in Eckersten et al., 2001). d Initial root depth is 0.26 m. e From Modellskogen and S¨ankan clay soil. f The same as for Modellskogen clay soil. g The same as for Grimstad loamy sand. h Estimated in relation to z . Org i Estimated in relation to z Min . j Kirschman (1991), Kirschman and Eriksson (1993) and Kirschman et al. (1996, 1999, 2005). k Arbitrary.

A.4. Biomass model The biomass model parameterization was taken from an earlier application to biomass measurements of the same experiments (Eckersten et al., 2004) (Table A4). Table A4 Parameters and symbols in the plant module Parameter

Symbol

Value

Unit

Source

Initial leaf weight Fraction of total DM allocated for growth Radiation use efficiency Lower temperature limit of growth Lower temperature limit for maximum growth Specific leaf area Root/total plant ratio at start of growth Leaf/shoot ratio at start of growth Fraction of root growth lost as litter Fraction of stem and root biomass lost as litter Maximum age of leaves Fraction of root going to litter when plant is alive after harvest Fraction of leaf lost at harvest Fraction of stem lost at harvest Light extinction coefficient related to leaf area

Wl (t0 ) bRG ε TMin TMax cSLA br bl0 mr m d hr hl hs k

1–7 0.01–0.10 0.1–3.6 2 15 0.0265 0.15–0.52 0.7 0.5 0.0001 90 0.30 0.99 0.95 0.5

g m−2

Calibrated vs. Wta Calibrated vs. Wta Calibrated vs. Wta and Wr /Wt (at harvest) = 0.4 Eckersten and Jansson (1991) Blomb¨ack and Eckersten (1997) Adjusted to get maximum LAI equal to about 5 Calibrated vs. Wta , and Wr /Wt (at harvest) = 0.4 Arbitrary Eckersten and Slapokas (1990) Arbitrary Adjusted to get leaves surviving winter Adjusted to get stable root biomass over the 2-year period Estimated from experiment Estimated from experiment Eckersten and Jansson (1991)

g MJ−1 ◦ C ◦ C g m−2 – – – d−1 d – – – –

100

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