Simulation of nitrogen uptake, fixation and leaching in a grass/white clover mixture

Simulation of nitrogen uptake, ®xation and leachingin a grass/white clover mixture

L. Wu* and M. B. McGechan

Soils Department, The Scottish Agricultural College (SAC), Edinburgh, UK

Abstract

To represent nitrogen cycling in a low input grass/

legume pasture system, a previously developed, weath-

er-driven grass/white clover growth model has been

adapted to become the crop growth component of the

soil nitrogen dynamics model SOILN. This provides a

means of simulating nitrogen uptake by a grass/white

clover crop, an important component of the overall

nitrogen balance in low-input grassland systems.

Crop growth is represented by a photosynthesis equa-

tion adapted to take account of competition between

the two crops for resources of light, water and nitrogen

in the soil. Water shortage is represented by linked

simulations with the soil water and heat model SOIL,

and nitrogen shortage by links with the SOILN model.

Nitrogen ®xation has been introduced according to an

equation for potential ®xation reduced by environmen-

tal factors, particularly temperature. Transfer of nitro-

gen-rich clover plant material to the soil nitrogen pools

of SOILN (from where it becomes available as a nutrient

for grass) is also represented. The model is tested by

comparing simulated cut crop yields and nitrogen

content of cut material with measured data from

perennial ryegrass/white clover at a test site. Soil

nitrogen processes in the model are tested by comparing

simulated and measured nitrate in drain¯ows. Apart

from some discrepancies between simulated and mea-

sured results attributable to the inherent instability of a

mixed crop system, agreement is reasonable by the

standards of biological system models, indicating that

the combined model gives a realistic representation of

carbon and nitrogen processes in grassland with a grass,

legume mixed crop.

Introduction

It has long been recognized that unfertilized pastures

that include a proportion of legume species can sustain

soil fertility and a high level of sward production despite

continual losses of nitrogen through cutting or leach-

ing, because of their capability for ®xing atmospheric

nitrogen. N2 ®xation in white clover/grass pastures has

been estimated to be as high as 680 kg N ha)1 year)1,

although 50±250 kg N ha)1 year)1 is a more commonly

estimated range (Ledgard and Steele, 1992). The most

dominant pasture legume in the temperate zone is

white clover. It is reported to contribute up to

342 kg N ha)1 year)1 in mixed swards world-wide

(Ledgard and Steele, 1992). In Britain, the quantity of

N2 ®xed by white clover in a mixed grass/clover sward

can vary from nil to about 400 kg N ha)1 year)1, and

productive swards often ®x between 100 and

200 kg N ha)1 year)1 (Whitehead, 1995).

The use of N2 ®xation in farming systems assists in

reducing the requirement for N fertilizers, which need

relatively large inputs of non-renewable resources for

their production. In contrast, the energy requirement

for N2 ®xation is obtained via photosynthesis. How-

ever, unfertilized pasture is not the preferred system of

herbage production in Europe. One reason for the

reluctance to rely on clover for maintaining soil

fertility is the perception of risk. Unlike industrially

produced chemical nitrogen fertilizer, which can be

administered at almost any time according to demand,

biological nitrogen ®xation is highly variable and

largely uncontrollable. Most variation in annual nitro-

gen ®xation can be related to the white clover content

of pastures and the availability of mineral nitrogen in

the soil (Crush et al., 1982). Ledgard and Steele (1992)

reviewed N2 ®xation in legume/grass pastures and

noted that the persistence of legume production and

N2 ®xation in various areas of the world is greatly

reduced by dry soil conditions, acid soils and the pest/

disease complex. Even where conditions are favour-

able for long-term persistence of legumes, legume

production and N2 ®xation can change markedly over

time.

*Present address: Department of Agrometeorology, China

Agricultural University, Beijing, China.

Correspondence to: Dr M. B. McGechan, Environmental

Division, The Scottish Agricultural College (SAC), West

Mains Road, Edinburgh EH9 3JG, UK

Received 11 February 1998; revised 14 July 1998

Ó 1999 Blackwell Science Ltd. Grass and Forage Science, 54, 30±41 30

When N fertilizer is applied to soil, it is either present

as nitrate or is quickly converted to nitrate, which is

immediately available for plant uptake but is also prone

to loss. Losses of N from the plant/soil system are of

increasing concern, particularly because of eutrophicat-

ion of water bodies caused by nutrient enrichment,

possible effects on public health of high nitrate levels in

drinking water, and emissions of the greenhouse gas

N2O causing global warming and depletion of the ozone

layer. Potentially, N2 ®xation may result in a greater

ef®ciency of N ¯ow and less likelihood of loss than

where N fertilizer is used because of the natural

feedback mechanism between N2 ®xation and soil N.

Mineralization of ®xed N from decomposing plant

material is a relatively slow process and is potentially

very ef®cient if the rate of N release meets the demand

of an associated non-N2-®xing sward.

There are few literature sources on which to base

representation of the N2 ®xation process in a dynamic

simulation model, either for a monoculture legume or

for a mixture of grass and legume. The purpose of the

present study is to demonstrate the effect of N2 ®xation

and quantify its contribution to the components of

nitrogen cycling in a clover/grass mixed system by

implementing the N2 ®xation process in a soil nitrogen

dynamics model. This study follows on from a previous

one in which an existing model representing monocul-

ture grass growth (Topp and Doyle, 1996) was devel-

oped for use as an interactive submodel (Wu and

McGechan, 1998a) for the Swedish soil nitrogen

dynamics model SOILN (Johnsson et al., 1987), which

in turn operates in conjunction with the soil water and

heat model SOIL (Jansson, 1996). The Topp and Doyle

(1996) model already included equations for photosyn-

thesis and water stress for a grass/white clover mixture

as well as for monoculture grass, but new equations

were required for the rate of nitrogen ®xation in

relation to soil nitrogen levels, temperature and water

contents. The actual rate of nitrogen ®xation was also

related to the potential ®xation rate, and this approach

differs from that in the study by Hutchings and

Kristensen (1995) where ®xation was constrained to

produce the same quantity of nitrogen as that applied in

mineral fertilizer to a comparable grass sward.

Brief description of model

Photosynthesis of mixed canopy

As in the previous study for monoculture grass (Wu and

McGechan, 1998a), equations for gross and net photo-

synthesis (in this case considered separately for grass

and white clover) were as presented by Topp and Doyle

(1996) based on the work of Johnson and Thornley

(1984). Unlike in the monoculture crop, they included

consideration of the vertical distribution of leaf area

between components throughout the depth of the

mixed canopy before calculating the photosynthesis

rate for individual components, which were then

summed. The method of estimating the vertical distri-

bution was adapted from Topp and Doyle (1996).

Separate equations for the effect of stress were

considered for each crop of the same form as in the Topp

and Doyle (1996) model, but with water stress for both

crops related to available soil water W in the root layer

derived from the SOIL model, and nitrogen stress for

grass only related to the nitrogen content of the leaves n1,

as described in detail by Wu and McGechan (1998a).

/g � b1

��W

Wmax

r� b2

��nl ÿ nlMin

nlMax ÿ nlMin

r� �2

�1�

/c � b3 � b4 �W

Wmax�2�

where /g and /c are functions representing the effect of

stress on net photosynthesis of grass and white clover,

respectively (expressed as a fraction in the range 0±1),

Wmax is available soil water at ®eld capacity, nlMin and

nlMax are, respectively, the leaf nitrogen concentrations

at which minimum and maximum growth occur, and

b1, b2, b3 and b4 are constants.

Nitrogen transformation processes

The SOILN model with a grassland crop option (rather

than a cereal crop or trees) selected (Wu et al., 1998;

Wu and McGechan, 1998a) was used as the basic model

in this study. The main soil nitrogen dynamic physical

and chemical processes ± surface application (as fertil-

izer, atmospheric deposition and deposition of dead

plant material), mineralization/immobilization (be-

tween organic and inorganic forms), nitri®cation (from

ammonium to nitrate), nitrate leaching, denitri®cation

(from nitrate to N2O and N2) and uptake by plants were

considered in the model. A nitrogen transformation or

¯ow between pools is represented in most instances as a

`®rst-order rate process', which means that the ¯ow out

of the ®rst pool to the second is proportional to the

quantity of material remaining in the ®rst pool. Details

about representation of these processes in the model

can be found in Johnsson et al. (1987), Wu et al. (1998)

and Wu and McGechan (1998a; b).

Nitrogen ®xation by clover

The nitrogen-®xing organism in clover is of the

Rhizobium legume association. N2 ®xation is a com-

plex process, and it is usually limited by factors such

as temperature, water or nutrient supply and by

competition from the grass in the mixture stand.

Simulation of nitrogen ¯ows in a grass/white clover mixture 31

Ó 1999 Blackwell Science Ltd, Grass and Forage Science, 54, 30±41

Nitrogen availability from soil is important for rapid

establishment of small-seeded legumes and it is

in¯uenced by soil N status as starter nitrogen as

well as rapid development of N2 ®xation activity

(Schomberg and Weaver, 1992). The initial stage of

N2 ®xation was ignored in this study to reduce the

complexity of the model. A description was assumed

for the processes of effective N2 ®xation and nodule

senescence. Factors affecting the N2 ®xation process,

soil moisture, temperature, soil acidity and nutrition-

al status in soil were assumed to be of the greatest

importance.

The potential capacity of white clover to ®x

nitrogen under optimal conditions can be considered

as potential nitrogen ®xation. Under ®eld conditions,

the capacity will be reduced under less favourable

conditions of growth. Similar to the estimation of

photosynthesis, the rate of nitrogen ®xation can be

written as:

NF � NFpotf�f1; f2; . . . fn� �3�where NFpot is the potential capacity of white clover,

and f(f1, f2, . . ., fn) is a response function to environ-

mental factors contributing to f1, f2, . . ., fn

Potential nitrogen ®xation capacity

The potential ®xation of a canopy is highly dependant

on root nodules being present as hosts for symbiosis as

well as the speci®c potential ®xation of root nodules.

Hence the potential capacity must be related to photo-

synthesis and its allocation to roots and subsequently to

nodules. Lie (1971) observed a linear relationship

between light intensity (the most important parameter

controlling photosynthesis), nodulation and nitrogen

®xation.

Macduff et al. (1996) observed that the ratio of root

dry weight and nodule dry weight remained nearly

constant at around 6:1 without NO3) treatment, but

increased exponentially over time after NO3) treatments.

Under what was considered to be the optimal environ-

ment for white clover, they found an average speci®c

N2 ®xation rate of 7á9 mmol N d)1 g)1 nodule dry

weight (d.w.), equivalent to 110á6 mg N d)1 g)1 nodule

d.w. The progressive decline in the partitioning of plant

biomass to nodules after NO3) applications has also been

shown in time-course studies on this ratio, such as

Svenning et al. (1996). Harris and Clark (1996) in

northern New Zealand observed that the ratio increased

from 7á5 to 15á0 with fertilizer application levels rising

from zero to 400 kg N ha)1 year)1, a trend that was

incorporated into the model for this study, although for

simplicity the continuing increase over time after

application was ignored.

Effect of mineral nitrogen

Many reported experiments suggest that high concen-

trations of mineral N in soil can inhibit the processes of

root-hair infection, nodule growth and development,

and N2 ®xation, although its exact mechanism remains

unde®ned. When legumes are nodulated, changes in

inorganic N concentration in soil interact inversely with

N2 ®xation.

Some experiments have indicated that ammonia and

nitrate concentrations in the soil will affect the ®xation

rate. Macduff et al. (1996) observed a rapid decrease in

N2 ®xation rate with increase in NO3) concentration at

low NO3) concentrations, with a more gentle decrease at

high concentrations. For this study, a relationship

between N2 ®xation and mineral nitrogen concentra-

tion ®tted to the data presented by Macduff et al. (1996)

was assumed, as shown in Figure 1.

Effect of temperature

Temperature is a major factor affecting the rate of N2

®xation. Frame and Newbould (1986) and Leconte

(1987) observed that active N2 ®xation requires a

minimum soil temperature of about 9°C, although

there are slight differences in this threshold value

among other literature sources where experimental

conditions varied. Halliday and Pate (1976) observed in

experiments that nitrogenase activity appeared to have

a broad optimum range of 13±26°C with a sharp decline

below 13 and above 26°C. Lie (1971) tested the nitrogen

®xation capacity of a number of Rhizobium strains from

Western Europe, Scandinavia and the Middle East on

pea cv. Rondo grown at different temperatures, and

found nitrogen ®xation to cease completely at 30°C; this

can be compared with a fast rate of ®xation for the same

species at 20°C (a common maximum soil temperature

in Western Europe). This is in agreement with evidence

presented by Halliday and Pate (1976) that ®xation

activity declines sharply above 26°C.

In a similar manner to the response function for

temperature on other processes, the effect of temper-

ature on N2 ®xation may be expressed as a single rate

adjustment factor Ft. For simplicity, the effect of

temperature based on the above observations is repre-

sented by a number of linear relationships (Figure 2).

Ft �

0 �T < Ta� or �T > Td�T ÿ 9

4�Ta � T � Tb�

1 �Tb � T � Tc�30ÿ T

4�Tc < T < Td�

8>>>>>>><>>>>>>>:�4�

where T is soil temperature (°C), Ta is the minimum

temperature below which ®xation ceases, Tb and Tc

32 L. Wu and M. B. McGechan

Ó 1999 Blackwell Sience Ltd, Grass and Forage Science, 54, 30±41

de®ne the optimum temperature range, and Td is the

maximum temperature at which ®xation occurs. It

should be emphasized that all the values in this set of

equations are highly dependent on clover species, with

some further ¯uctuations within a particular species.

Effect of soil water content

Water de®cits and waterlogging can also be expected to

affect N2 ®xation. Unfortunately, little research has

been carried out to indicate the mechanisms by which

water stress affects nitrogen ®xation, or to supply

suf®cient data to suggest a quantitative expression for

the relationship. It was therefore assumed here that the

effect of water stress on nitrogen ®xation would be

similar to that on the rate of photosynthesis of white

clover as given by Equation 2, with coef®cients b5 and

b6 in place of b3 and b4. Coef®cient values were

adjusted during validation of the model (see below),

keeping the ratio b5:b6 the same as the ratio b3:b4, to

give an annual nitrogen ®xation at roughly the

expected level.

Transformation of ®xed nitrogen

McNeil and Wood (1990) estimated that annual N2

®xation by white clover in the United Kingdom was

155 kg N ha)1, about 28% of this subsequently trans-

ferring to ryegrass, and accounting for 29% of the total

nitrogen content of ryegrass.

Although there are a number of mechanisms by

which ®xed N can become available to associated grass,

mineralization of ®xed N from organic sources is the

most important mechanism of N transfer. Direct trans-

formation is so minimal that it can be ignored in the

model.

The fact that little transfer occurs during the ®rst few

months after sowing a grass-clover sward (Haystead and

Marriott, 1979; Broadbent et al., 1982; Boller and

NoÈ sberger, 1987), and that most transfer appears during

the spring (Evans et al., 1990), suggests that the main

route for transfer of nitrogen from white clover to grass

is decomposition of dead materials from white clover.

The same conclusion can also be drawn from the results

obtained by Jensen (1996), in an experiment with

mixed intercropping of ®eld pea (Pisum sativum L.) and

spring barley (Hordeum vulgare L.), where there was no

evidence for pea N being transferred directly to barley.

The bene®t of intercropping in this case was mainly due

to the complimentary use of soil inorganic and atmo-

spheric N sources by the intercrop components, result-

ing in reduced competition for inorganic N, rather than

a facilitative effect in which symbiotically ®xed N2

would be made available to barley.

Decomposition of root nodules of white clover is a

potentially signi®cant route for transfer, as their con-

centration of N is high, with reported values in theFigure 2 Response function of temperature on N2 ®xation rate.

Figure 1 Comparison of N2 ®xation rate with nitrogen concentration in soil. (±±±, Simulated; m, measured.) Data source: Macduff et al. (1996).



range 4á8±9á0% of root dry matter (Butler and Bathurst,

1956; Chu and Robertson, 1974; Wardle and Green-

®eld, 1991). For this study, nitrogen in senescent

above-ground material was added to the above-ground

litter pool, and nitrogen in senescent root material was

added to the soil litter pool in the appropriate layer in

the SOILN model.

Simulation procedure and experimentalsite

Management of experimental site

The test site was located on the Acrehead Experimental

Dairy Unit at the Crichton Royal Farm, Dumfries, in

south-west Scotland, a dairy farming area with a

relatively high annual rainfall. The soil type was a silty

clay loam of Stirling/Duffus/Pow/Carbrook Association,

as classi®ed by Bown and Shipley (1982). Two isolated

plots, each 0á5 ha in area, were ®tted with equipment to

record the volume of drain¯ow and the concentrations

of solute. The grass-white clover mixture system in this

study had been established by ploughing and reseeding

with perennial ryegrass (Lolium perenne cv. Merlinda

and cv. Morgana) and white clover (Trifolium repens cv.

Milkanova and cv. Menna). The crop on the plots was

managed for silage-making with two or three cuts for a

`low input' dairy system, receiving applications of slurry

(Table 1) but no mineral nitrogen fertilizer. Two adja-

cent similar plots in a `conventional' system with a

monoculture grass crop receiving both slurry and

mineral nitrogen were the subject of a previous study

(Wu and McGechan, 1998a). The available nitrogen

content of slurry in®ltrating the soil was estimated by

adjusting the measured composition at the time of

application to allow for ammonia volatilization occur-

ring before in®ltration according to guidelines reported

by Dyson (1992). The third silage cut was not taken in

some drier years because of demands for grazing grass

on the farm. In simulations, three cuts were assumed

on the same dates as the real cuts, with the third cut

(where it had not been taken in practice) at an

estimated probable time to represent grass offtake by

grazing.

Driving variables derived from associatedsimulations using the SOIL model

Most of the input or `driving' variables required for

simulations with SOILN must be prepared by carrying

out a simulation with the soil water and heat model

SOIL before a simulation with SOILN. These variables

include temperature and water content of each soil

layer, water ¯ow between each pair of adjacent hori-

zontal layers, water ¯ow into the surface layer, surface

run-off, water ¯ow out of each layer to ®eld drain

back®ll and deep percolation ¯ow from the lowest layer

in the pro®le. Air temperature and solar radiation are

input weather parameters required both by SOIL and

SOILN. Parameter selection, testing and results of

simulations with SOIL for the site used in this study

have been reported by McGechan et al. (1997). Soil

water contents given by the SOIL model are used both

in the growth stress functions (Equations 1 and 2) and

the similar equation for the effect of water stress on

nitrogen ®xation.

Required parameters, initial valuesand simulation details

Selection of parameters for SOILN, concerning both

grass growth and soil processes at the site, have been

reported by Wu and McGechan (1998a) and Wu et al.

(1998). Parameters for the grass component of the

mixed crop remained unchanged from the monoculture

grass crop (Wu and McGechan, 1998a), and parameters

with differing values for white clover and grass are

listed in Table 2.

The initial values of grass tissue biomass in leaf,

stem and root at the beginning of each simulation

were based on those suggested by Topp and Doyle

(1996) and were divided into two equal parts,

allocated to grass and white clover respectively.

Simulations with a 1-day timestep to represent soil

water, nitrogen cycling, nitrogen ®xation and crop

growth were carried out for the period from January

1992 to August 1995, starting 2 years ahead of the

collection of experimental data (with estimated

cutting dates for those 2 years) to reduce the effect

of errors in the assumed initial soil nitrogen and

Table 1 Nitrogen applications (g N m)2) in slurry to experimental plots.

1994 1995 1996

14 February 25 May 21 November 31 May 07 July 31 January

Organic nitrogen 2á95 3á07 2á35 4á93 1á43 17á7

NH4-N 5á05 3á03 3á36 4á33 2á18 10á5



water contents. All roots (apart from the proportion

undergoing senescence on a daily basis) were

assumed to remain alive after each of the ®rst two

cuts, but after the third cut a proportion became dead

plant material, transferring to the litter pool.

Validation

Nitrogen ®xation

Nitrogen ®xation by white clover appears to make a

substantial contribution to nitrogen cycling in a mixed

crop system, as shown in Table 3. Initial simulations

with the coef®cients b5 and b6 in the nitrogen ®xation

water stress equation equal to b3 and b4 in the

photosynthesis water stress equation, gave annual

nitrogen ®xation of about three times the expected

value of 150 kg N ha)1. As there was no direct exper-

imental evidence about the values of these coef®cients,

each was adjusted downwards by multiplying by a

factor of 0á35, to give an annual nitrogen ®xation of

about 160 kg N ha)1, near to the expected value. b5

and b6 were the only model parameters to be adjusted

at the validation stage.

Harvested biomass and nitrogen offtake

A comparison between simulated and measured results

was made for cut biomass dry-matter and nitrogen

contents in the dry matter, as shown in Table 4.

Simulated biomass dry matter is in close agreement

with the measured values only for the ®rst two cuts in

1994. Thereafter, alternate overestimation and under-

estimation occurs. It is very clearly indicated from these

values that only an approximation to the composition

of the sward can be represented in the model. Taking

the ®rst two cuts in 1995 as an example, it is clear that

there is a higher proportion of grass in the measured cut

biomass in the ®rst cut than that in the second cut, but

the reverse situation occurs in the simulations. Simu-

lations of biomass show that the proportion of white

clover in the system varies over time (Figure 3).

As well as the alternately positive and negative

discrepancy in cut biomass, the model tends to under-

estimate nitrogen offtake.

Nitrate leaching

Simulated and measured cumulative nitrate N leached

is shown in Figure 4 for 1994±95 and 1995±96. There

Table 2 Parameter values which differ between grass and white clover crops.

Value

Symbol Grass White clover Unit Description

± Biomass accumulation

b1 0á366 ± Coef®cient in stress equation (water stress term, grass)

b2 0á664 ± Coef®cient in stress equation (nitrogen stress term, grass)

b3 0á216 ± Coef®cient in stress equation (constant term, white clover)

b4 0á789 ± Coef®cient in stress equation (water stress term, white clover)

kg 0á5 0á8 ± Light extinction coef®cient

Y 0á83 0á63 ± Respiration growth conversion ef®ciency

Biomass allocation and senescence

A 0á0258 0á0368 m2 g)1 Speci®c leaf area

bi0 0á06 0á045 Coef®cients for leaf area development as a function of above

ground biomass

bi1 0á008 0á0063 ±

cL Varies 0á023 d)1 Fraction of leaf biomass senescing (lost to litter)

0á03 0á03 d)1 Fraction of daily root growth senescing (lost to litter)

0á03 0á03 d)1 Fraction of root biomass senescing (lost to litter)

cS 0á0259 0á0259 d)1 Fraction of stem biomass senescing (lost to litter)

Nitrogen ®xation

Ta 9 °C Threshold temperatures in nitrogen ®xation temperature

Tb 13 °C response function (Equation 4)

Tc 26 °CTd 30 °Cb5 0á0756 ± Coef®cient in stress equation (constant term)

b6 0á276 ± Coef®cient in stress equation (water stress term)



was generally good agreement between simulated and

measured values. As leached nitrate is strongly in¯u-

enced by drainage ¯ow, differences between measured

and simulated nitrate leached could arise because of

errors in simulated drainage ¯ows indicated by the SOIL

model.

There was a distinct difference in annual nitrogen

leached between the 2 years, both in measurements

and simulations. This is probably a re¯ection of the

conclusion that nitrate leached is strongly in¯uenced by

previous weather conditions (Jordan and Smith, 1985),

which in turn determines the mineralization, nitri®cat-

ion and denitri®cation processes in nitrogen cycling

(Schole®eld et al., 1993). This is supported in Figure 5,

which shows simulated mineralization and nitri®cation

rates in the soil during the two years.

Table 3 Comparison of simulated and measured harvested biomass and nitrogen.

Cut biomass (t ha)1) Nitrogen in cut biomass (kg ha)1)

Harvest date Simulated Measured Relative error (%) Simulated Measured Relative error (%)

19 May 1994* 3á41 3á08 10á71 64á2 69á9 )8á15

05 July 1994 2á82 2á95 )4á41 64á3 74á6 )13á81

27 August 1994 2á81 2á15 30á70 37á1 66á7 )44á38

Subtotal 9á04 8á18 10á51 165á6 211á2 )21á59

20 May 1995 2á54 4á03 )36á97 47á5 64á5 )26á36

01 July 1995 3á61 2á79 29á39 70á1 73á7 )4á88

27 August 1995*** 2á33 Not cut Not cut 29á6 Not cut Not cut

Subtotal (excluding

third cut)

6á15 6á82 )9á82 117á6 138á2 )14á91

23 May 1996 3á44 3á70 )7á03 88á7 82á9 7á00

15 July 1996 3á47 3á02 14á90 53á8 N/A

Subtotal 6á91 6á72 2á83 142á5

*The start date of the growth period was estimated from the following year.

**Estimated from crude protein contents.

***The cut date was estimated from the previous year.

Table 4 Annual and seasonal nitrogen inputs and outputs (g N m±2) in simulations for experimental site.

Input Output Change

Interval

Slurry Depo

-sition Subtotal Fixation

Harvest Leaching Denitri

-®cation Subtotal

in humus

pool

28 August 1993±31 March 1994 13á71 1á43 15á14 5á80 0á00 0á96 0á93 1á89 7á76

01 April 1994±19 May 1994 0á00 0á25 0á25 2á61 6á42 0á12 0á22 6á76 2á65

20 May 1994±05 July 1994 6á10 0á22 6á32 2á75 6á43 0á01 0á73 7á17 5á21

06 July 1994±27 August 1994 0á00 0á33 0á33 4á79 3á71 0á19 1á11 5á01 4á75


01 April 1994±31 March 1995 11á81 2á28 14á09 16á02 16á56 1á56 3á09 21á21 21á44





01 April 1995±31 March 1996 41á07 2á15 43á22 16á04 14á72 2á51 5á10 22á33 28á15




01 April 1996±26 August 1996 0á00 0á74 0á74 11á96 20á06 0á27 3á12 23á46 16á87

Rows in bold print are period totals.



Nitrogen balance in grass/clover and grassmonoculture systems

Although the mixed crop system has lower external

nitrogen input than monoculture grass, it still has

higher offtakes, and contains higher nitrogen content in

the soil pools, because of white clover recycled into soil

as litter. During the course of a year, high ®xation rates

occur in summer (Figure 6), and somewhat lower

®xation rates during autumn and winter because of

low temperatures and small root biomass. A comparison

of inputs and outputs of nitrogen between the mono-

culture (as reported by Wu and McGechan, 1998a) and

the mixture systems during the same periods is shown

in Figure 7. In both systems, the largest ¯ows are inputs

in the form of slurry and either mineral fertilizer or

nitrogen ®xation, and outputs to crop biomass (in the

leaf and stem components removed by cutting) and to

soil humus. Other ¯ows, atmospheric deposition,

leaching and denitri®cation, are small by comparison,

so losses are also small in relation to the large ¯ows.

Discrepancies between simulated and measured leach-

ing are, therefore, also very small in relation to the large

nitrogen ¯ows.

Discussion

The current model can simulate approximately the

processes of nitrogen cycling in a grass/white clover

mixture system, even though some processes relating to

grass growth and nitrogen ®xation are simpli®ed. Small

discrepancies arise between prediction and measure-

ment in biomass harvest, nitrogen offtake and leached

nitrate, partly because the mixture system is more

complicated than a monoculture.

There are a number of possible explanations for the

overestimation or underestimation of both harvested

grass biomass and nitrogen offtakes during a year.

Errors in both could be caused by lack of precision in

representing the interacting processes between white

clover and grass due to a lack of detailed knowledge

Figure 4 Dynamic annual concentrations of simulated and experimental nitrate leaching. ( , Simulated; m, measured.)

Figure 3 Simulated proportion of white clover in grass/clover mixture systems.



about these interactions. Above ground, the two crops

compete for light for photosynthesis through the

vertical distribution of interception throughout the

canopy. It has been reported that white clover tends

to predominate in the upper layers of the canopy in cut

swards (Woledge, 1988; Woledge et al., 1992). Long-

term records (Steele and Shannon, 1982; Tyson et al.,

1990) have indicated persistent and substantial varia-

tion of annual white clover content in harvested

biomass, despite consistent management practices.

Schwinning and Parsons (1996) pointed out that there

is an intrinsic, oscillatory component of variation in

grass-legume systems, with a period of 3±4 years, and

there are external stimulants to legume variation, or

`stresses', interacting with these oscillations and intro-

ducing a random element to variations. In this study,

interactions are excluded by assuming that once the

initial allocation of accumulated biomass has been

made to give a total for each crop, grass and white

clover each have an independent function to allocate

this total to leaf, stem and root. This assumption could

contribute to similar errors in simulated harvested

biomass and nitrogen offtake. In particular, the simu-

lated white clover proportion was very high during the

winter of 1995±96, which could have been caused by

the biomass of grass dropping to a low level. Alterna-

tively, in the soil, although the model has included a

stress function to represent the effect of water and

Figure 6 Simulated N ®xation rate by white clover.

Figure 5 Simulated dynamic mineralization and nitri®cation rates. (- - -, Mineralization; nitri®cation.)



nitrogen on photosynthesis, there is also competition

between the species for absorption of soil water. These

interaction processes are too complex to model in detail

in the current study.

Errors in predictions of leached nitrogen in simula-

tions could be caused by a combination of factors such

as inaccuracy of soil water simulations derived from the

SOIL model, the nitrogen ®xation function, and other

nitrogen transformation processes represented in the

SOILN model. In a similar manner to ®ndings of related

studies (Wu and McGechan, 1998a; Wu et al., 1998) in

which the differences between measured and simulated

quantities of nitrate leached appeared to be caused by

errors in simulated drainage ¯ow in the SOIL model,

the same cause of discrepancies still appears to exist in

the current study. It is probable that the dynamic

simulation of nitrate leaching could be improved if

drainage ¯ow could be simulated more precisely. The

effect of mineral nitrogen applications on N2 ®xation is

a lagged process. Svenning and Macduff (1996) found

that the speci®c rate of N2 ®xation after supplying

NH4NO3 declined at an almost constant rate to zero by

day 10 at 17°C. Nitrogen ®xation in the current

simulation is likely to be oversimpli®ed. In addition,

the inaccuracy of white clover growth estimation

discussed above will also lead to some discrepancies.

Despite some simpli®cation and slight discrepancies

between simulated results and measured values, the

model provides a realistic representation of the relevant

processes in broad terms. For nitrogen cycling studies, it

gives a good indication of the relative quantities of

nutrients following each route through the system. It

indicates how a crop system based on nitrogen ®xation

rather than mineral fertilizer for its main nutrient

source can be sustainable, giving adequate yields of a

forage crop. Nitrogen transformation into soil humus

can be regarded as a useful recycling ¯ow, because

increases in soil organic matter improve soil structure

and the nitrogen can be released slowly in the future by

mineralization to become available again as a plant

nutrient. The comparison of ¯ows between grass

monoculture and the mixed crop leads to the conclu-

sion that pastures with some legumes receiving appro-

priate slurry applications can sustain soil fertility and

high levels of sward production.

Acknowledgments

This research was supported by funds from the Scottish

Of®ce Agriculture, Environment and Fisheries Depart-

ment, and also from the European Union under the

project `Optimal use of animal slurry for input reduc-

tion and protection of the environment in sustainable

agricultural systems'. The authors express sincere

thanks to: Professor P-E Jansson and Dr H. Eckersten

of the Department of Soil Sciences, The Swedish

University of Agricultural Sciences, Uppsala, for per-

mission to use and adapt the source code of the SOILN

model; Dr C. F. E. Topp of SAC, Auchincruive for access

to her source code in BASIC for the photosynthesis

equations; John Bax of SAC Crichton Royal Farm for

providing measured crop data and information about

fertilizer and slurry applications; Dr P. S. Hooda of SAC

Auchincruive for supplying the drain ¯ow and nitrate

leaching data.

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Monoculture grass; n, 1994±95 grass/clover mixture; , 1995±96 monoculture grass; ,1995±96 grass/clover mixture.



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Simulation of nitrogen uptake, fixation and leaching in a grass/white clover mixture