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Agriculture, Ecosystems and Environment 105 (2005) 1–16

A novel indicator of environmental risks due to nitrogen

management on grasslands

Frank Pervanchona,*, Christian Bockstallera, Bernard Amiauda,Josephine Peigneb, Pierre-Yves Bernardc, Francoise Vertesd,

Jean-Louis Fiorellic, Sylvain Plantureuxa

aUMR INPL(ENSAIA)-INRA Agronomie et Environnement, BP 172, 54505 Vandoeuvre-les-Nancy cedex, FrancebISARA, 31 place Bellecour, 69288 Lyon cedex 02, France

cINRA SAD, Domaine du Joly, BP 29, 88501 Mirecourt cedex, FrancedUMR INRA-ENSAR Sol-Agronomie-Spatialisation, 4 rue Stang Vihan, 29000 Quimper, France

Received 13 May 2002; received in revised form 21 June 2004; accepted 28 June 2004

Abstract

An agro-ecological indicator IN losses was introduced in order to estimate the risks of air and water pollution through nitrogen

management on grasslands. The IN losses score in this study corresponded to the lowest score of four sub-indicators (INH3, IN2O,

INO and INO3) which, respectively, provide information on volatilisation, nitrous and nitric oxide emissions in the air and nitrate

leaching in groundwater. The score of each sub-indicator was obtained by comparing nitrogen losses to a threshold which

corresponded to the maximal level acceptable for the environment (e.g. 50 mg NO3 L�1 for the leaching sub-indicator INO3). The

losses in air of NH3, N2O, NO were calculated by means of emission coefficients. Nitrate leaching was estimated from the

residual mineral nitrogen in grassland soil found at the beginning of the drainage period. A validation of the indicator by

comparing calculated data with measurements of nitrate leaching by ceramic cups was carried out on grazed and hay grasslands.

A discrepancy between observed and calculated data was observed when using data from ceramic cups to validate the indicator.

Nevertheless, the indicator gave realistic results and is valid for use in order to indicate the degree of pollution risk in agricultural

management.

# 2004 Elsevier B.V. All rights reserved.

Keywords: Nitrogen balance; Soil residual nitrogen; Agro-ecological indicators; Permanent grasslands; Nitrogen management; Pollution

* Corresponding author. Present adress: TRAME, 9 rue de la

Baume, 75008 Paris, France. Tel.: +33 144 950 826;

fax: +33 140 740 302.

E-mail address: f.pervanchon@trame.org (F. Pervanchon).

0167-8809/$ – see front matter # 2004 Elsevier B.V. All rights reserved

doi:10.1016/j.agee.2004.06.001

1. Introduction

The study of the effect of agricultural management

practices on nitrogen losses have primarily focused on

arable fields and have shown that the management of

grassland systems impacts the environment (Ryden

.

F. Pervanchon et al. / Agriculture, Ecosystems and Environment 105 (2005) 1–162

et al., 1984; Watson and Foy, 2001). Nitrogen losses in

air (Freibauer and Kaltschmitt, 2000) and to ground-

water by leaching are higher in intensively-managed

grasslands than in arable crops (Hack-ten Broeke

et al., 1999). Therefore, in order to improve the

sustainability of grassland husbandry it is necessary to

take into account the environmental risk through

nitrogen losses associated with nitrogen management.

Because of high financial costs and time, direct

nitrogen loss measurements in fields cannot be carried

out. In the last decades, in order to improve

agricultural management many simulation models

have been developed for use in providing information

on such variables as nitrate leaching (Addiscott and

Wagenet, 1985). Several models, looking at mixed

farming systems have taken into account nitrogen

losses in both air and water (Ledgard et al., 1999), in

pastures (Scholefield et al., 1991), or specifically in

grasslands (Bhogal et al., 2001). Other models have

considered only one aspect of nitrogen losses (e.g.

nitrate leaching in Tuck et al., 2000) or one part of the

system (e.g. losses due to the spreading of manure in

Chambers et al., 1999). Despite the effort made to

reduce the number of input variables in functional

models (Addiscott and Wagenet, 1985), for the most

part models are still too complex for most rural

managers and advisors working with farmers.

Indicators have been proposed by many researchers

as operational tools for a global diagnostic assessment

of the effects of agricultural management on

environment (Lenz et al., 2000; van der Werf and

Petit, 2001). These indicators are tools that simplify

the ability to describe quantitatively or qualitatively

complex phenomena or complex systems (Girardin

et al., 2000; Merkle and Kaupenjohann, 2000).

In looking at nitrogen management in farming

systems, most authors have proposed indicators

calculated from the difference between nitrogen

outputs and inputs at various scales in order to

calculate nitrogen balance or budget (Benoıt, 1992;

Hanegraaf, 1998; Simon et al., 2000; van Eerdt and

Fong, 1998). These indicators are helpful for

analysing farming systems, but do not provide

accurate information about the fate of the nitrogen

surplus lost to the environment (Simon et al., 2000).

Furthermore, contradictory results have emerged from

validation studies done in grasslands (Laurent et al.,

2000; ten Berge, 2002). In determining nitrogen

leaching losses in grazed pastures, the best indicator

has been found to be the stocking rate expressed in

number of livestock units by grazing days (Simon

et al., 2000), but some variability has still been

observed, due mainly to management practices that

interact with climate and different soil types.

The IN losses indicator introduced in this article is an

attempt to go beyond the simple calculation of a field

nitrogen balance. This indicator’s intent is to provide

complete and detailed information concerning the

impact of grassland management decisions on water

and air quality and not only a nitrogen surplus to the

environment. With this approach, the IN losses indicator

could help potential users, especially farmers and rural

managers, to improve their grassland husbandry in

order to achieve the target of sustainable forage

production (hay and/or pasture), and environment

preservation (air and water).

In order to describe the development of the IN losses

indicator, this article has been divided into three

sections. The first identifies the environmental risks

which have to be estimated by the IN losses indicator.

The second lists in three steps the methodology of

IN losses development: (i) calculation of the emissions

in air and water; (ii) development of a sub-indicator

for each emission; and (iii) aggregation of the sub-

indicators to obtain the final IN losses indicator. The

third section of this article describes simulations and

tests carried out on IN losses. All variables used to

develop the indicator are included in Appendix A.

2. Identification of the objectives of the IN losses

indicator

The development of an agro-ecological indicator,

such as IN losses is feasible but it has to be based on

present available scientific knowledge (Girardin et al.,

1999). This statement implies that the indicator is to be

calculated from easily attainable on-farm data. In the

development of the IN losses attention must be paid to

the comprehensibility and to the pertinence for users

(farmers or rural managers), and take into account the

sensitivity to differences in agricultural practices.

Water quality is threatened mainly by nitrate (NO3)

leaching which occurs under grazed grasslands

(Jarvis, 2000). Losses by NO3 leaching can be high

when hay is produced on over-fertilised grasslands

F. Pervanchon et al. / Agriculture, Ecosystems and Environment 105 (2005) 1–16 3

(ten Berge et al., 2002b). It has been assumed that

nitrogen loss through surface runoff is negligible for

grassland systems due to vegetative cover of the soil

(Scholefield and Stone, 1995). For simplicities sake,

the differentiation of NO3 leaching loads was not

considered. The total amount of nitrogen loss below

rooting depth is here in considered as leached, even

though it may flow to surface water by subsurface

lateral flow, which is especially true in for clay soils

with an impermeable layer.

The main forms of nitrogen known to pollute air are:

ammonia (NH3), nitrous oxide (N2O) and nitric oxide

(NO) (Olivier et al., 1998). Emissions of NH3 occur

mainly during soil eutrophication or acidification, and

in modification of flora diversity and during the

development of plant diseases (Marshall et al., 1998;

Misselbrook et al., 2000). Agriculture is the major

source of the addition of NH3 to the environment as it is

volatilised from excreta of domestic animals and from

synthetic fertilisers (Olivier et al., 1998). A major

greenhouse gas, N2O in agriculture plays a significant

role in its global emissions (Freibauer, 2003). The

losses of N2O due to both nitrification and denitrifica-

tion are higher in grasslands than in arable soils

(Bouwman, 1996; Henault and Germon, 1995).

Increased production of ozone in the troposphere is

due to NO, which can also endanger human health and

cause soil acidification (Olivier et al., 1998). The NO

emissions due to agriculture appear much lower than

the emissions caused by industry (Freibauer and

Kaltschmitt, 2000), but there is a paucity of data from

field experiments (Harrison and Webb, 2001).

Consequently, the objective of IN losses indicator

was to estimate the four main environmental impacts

of nitrogen: NH3, N2O and NO emissions, and NO3

leaching.

3. Calculation of the nitrogen losses to the

environment for the development of IN losses

indicator

3.1. Time scale and spatial scale

The gaseous losses of nitrogen were calculated

from the nitrogen inputs for a one-year management

period (between the 1st of January and 31st of

December). Emissions of NH3 were first considered

because they are observed within immediately

following the spreading of fertiliser, or in the case

of manure, during the week following spreading

(Sommer and Hutchings, 2001). N2O and NO was

assessed globally for the year because emissions are

observed periodically, and the mechanisms influen-

cing N2O and NO emissions are not well-known

(Rudaz et al., 1999). For NO3 leaching, the calculation

method was more complex, because it occurs mainly

during the winter drainage period. During periods of

high vegetation development, it is assumed that the

soil mineral nitrogen available is low due to high

microbial immobilisation process (Recous et al.,

1997) and vegetation uptake. Leaching of NO3 was

due mostly to the accumulation of mineral N in the soil

during the management period of the current

measurement year.

The spatial scale considered for the application of

the IN losses indicator was a grassland plot that had

received uniform management treatment, and which

had the same soil and climatic influences.

3.2. Determination of the nitrogen inputs

Nitrogen in this study was restricted to the mineral

form of nitrogen which can be directly assimilated by

grassland vegetation during the year of its application.

Nitrogen inputs were therefore the sum of nitrogen

from spreading of mineral chemical fertilisers and

organic fertilisers plus nitrogen excreted by animals.

The amounts of organic or mineral fertilisers spread

by the farmer were obtained by on-farm interviews.

The amount of nitrogen excreted by the animals was

determined from simple models (Farruggia et al.,

2000; Scholefield et al., 1991; Delaby et al., 1997). For

organic fertilisers or for faeces and urine, it was

necessary to use data from tables or from expert

knowledge in order to determine the mineral nitrogen

(ammonium) available to vegetation grassland during

the production year studied.

3.3. Determination of the nitrogen losses in air

3.3.1. Losses of ammonia through agricultural

practices (LNH3)

The updated coefficients of Freibauer and Kaltsch-

mitt (2000) were chosen for mineral fertilisers N loss

to the air. For organic fertilisers, technical data

F. Pervanchon et al. / Agriculture, Ecosystems and Environment 105 (2005) 1–164

corresponding to output of empirical models was

available and these models outputs allow the rather

precise determination of volatilisation coefficients for

slurry and manure (Chambers et al., 1997; Menzi

et al., 1997). The incorporation of liquid manure in

soil according to the farming practices was considered

only because liquid manure was incorporated into

grasslands. Concerning faeces and urine, a respective

coefficient of 3% and 12% of volatilised nitrogen was

chosen (average from bibliographical synthesis by

Decau, 1997; Barre, 2001). The total amount of NH3

emitted in air from agricultural management practices

is calculated in Eq. (1).

LNH3¼ SðQ fertkCNH3 kÞ (1)

where LNH3is the total amount of NH3 emitted to air

due to agricultural practices (in kg NH3-N ha�1 yr�1),

Q fertk (in kg N ha�1 yr�1) is the amount of mineral

nitrogen (mostly ammonium ions) directly supplied by

the farmer in the form k (the form k can be mineral

fertilisers, organic fertilisers, faeces or urine), and

CNH3 k is the volatilisation coefficient for a given

fertiliser in the form k (examples in Table 1).

3.3.2. Losses of nitrous oxide due to agricultural

practices (LN2O)

Data determing the assessment of coefficients are

less available for N2O emission than for NH3

volatilisation, and as well, there is a high coefficient

of variation according to statistical analyses in the

bibliographic data (Henault and Germon, 1995).

Therefore, for the sake of consistency the N2O

emission coefficient 0.0125 given by Freibauer and

Table 1

Example of some emission factors CNH3for ammonia emissions which corr

nitrogen content of the fertilisers (the organic nitrogen mineralised over

Input types (k) Not injected into soil

Spreading period (month)

November–

January

April–May or

September–October

Jun

Au

Manure

Cattle 0.60

Pig 0.60

Poultry 0.40

Slurry

Cattle 0.65 0.70 0.8

Pig 0.30 0.40 0.4

Kaltschmitt (2000) was chosen, integrated through

CN2O k in Eq. (2).

LN2O ¼ FX

ðCN2O kðQ Nk � ðQ fertkCNH3 kÞÞÞ (2)

where LN2O is the total amount of N2O emitted to air

due to agricultural practices (in kg N2O-N ha�1 yr�1),

Q Nk is the total amount of nitrogen spread on grass-

land in the form k, CN2O k is the N2O emission

coefficient due to nitrogen inputs in the form k, and

F is a factor that determines N2O emissions according

to soil type or agricultural practices (irrigation or

cutting). For F, suggested values are: (i) if the grass-

land is cut more than two times, F = 0.70 (adapted

from Kammann et al., 1998); (ii) if the grassland is

irrigated, or in the case of clay soil or hydromorphic

soil, F = 1.5 (adapted from Barton, 1999; Muller et al.,

2002); (iii) in the case of organic soils, F = 2 (adapted

from Velthof and Oenema, 1997). The nitrogen vola-

tilised factor (Q fertkCNH3 k) is removed, because it is

no longer available for nitrification and denitrification

(Bouwman, 1996).

3.3.3. Losses of nitric oxide due to agricultural

practices (LNO)

There is insufficient information in the literature to

establish emission coefficients for nitric oxide (NO)

emissions. Therefore in this study, a conservative

estimate of 1% of fertiliser and manure equivalent

nitrogen has been chosen (Freibauer and Kaltschmitt,

2000). The amount of NH3 and N2O previously

calculated have been removed because they are no

longer available for NO emissions. It was also

espond to the fraction of nitrogen emitted in the air versus the mineral

one year is not taken into account)

Injected into soil

Spreading period (month)

e–

gust

November–

January

April–May or

September–October

June–

August

Unrealistic

Unrealistic

Unrealistic

0 0.35 0.40 0.50

5 0.20 0.20 0.25

F. Pervanchon et al. / Agriculture, Ecosystems and Environment 105 (2005) 1–16 5

necessary to remove N2 emitted when the process of

nitrate reduction has been completed. It is difficult to

calculate the N2 emissions as the ratio N2/N2O is

highly variable and no generalisation is possible

(Rudaz et al., 1999). Nevertheless, because of the 1%

coefficient, the score of INO will always be lower

compared to NH3 or N2O, even if N2 emissions are not

subtracted as these emission are negligible (Eq. (3)).

LNO ¼ 0:01ðNinput � ðLNH3þ LN2OÞÞ (3)

3.4. Equation for leaching in groundwater (LNO3)

3.4.1. Determination of the part of nitrogen leaching

(Nleachable)

The amount of nitrogen leaching in groundwater

was estimated from the residual nitrogen measured in

the grassland soil at the beginning of the drainage

period (ten Berge et al., 2002b). Residual N will be

low and constant as long as there has been no nitrogen

over-fertilisation (Fig. 1). If over-fertilisation has

occured, meaning that a critical input has been

exceeded, then, the amount of mineral residual

nitrogen increased rapidly (ten Berge et al., 2002b).

For hay grasslands, ten Berge (2002) derived by

regression means (from numerous mineral and organic

fertilisation trials) the mineral residual nitrogen in

soils (Eq. (4)).

Nleachable ¼ Nmin H0 þ mðNinput � Ninput critÞ2;

withm ¼ 0:000924(4)

Fig. 1. Illustration of the residual mineral nitrogen determination

(Nleachable) in grassland soils (from ten Berge et al., 2002a).

and if

Ninput � Ninput crit; Nleachable ¼ Nmin H0

where Nleachable is the amount of mineral residual

nitrogen in soil (in kg NO3-N ha�1 yr�1). NminH0 is

the mineral residual nitrogen observed in soils when

the N fertilisation rate was limiting (in kg NO3-N

ha�1 yr�1), equal to 10 (Hoving and van Riel, 2002).

Ninput is the amount of mineral nitrogen inputs (in kg N

ha�1 yr�1) managed by the farmer. In the case of

organic fertilisers, ammonia volatilisation is sub-

tracted to obtain Ninput (ten Berge et al., 2002a).

Ninput crit is the nitrogen required (in kg N ha�1 yr�1)

�1) to meet the forage production required for

animal breeding. Ninput crit can be determined by

model from dataset (ten Berge et al., 2002b). Alter-

natively, a simplified equation can be used to deter-

mine the recommended nitrogen input (Farruggia

et al., 2000). The mathematical function m(Ninput �Ninput crit)

2 provides the increase of residual nitrogen

due to over-fertilisation. The parameter m takes into

account the various nitrogen losses in the air, except

the volatilisation from organic fertilisers subtracted

from the total amount of Ninput (ten Berge et al.,

2002).

To adapt Eq. (4) for grazing conditions, it is

necessary that the available nitrogen coming from

grazing animals is added to the other nitrogen inputs

(organic and mineral fertilisers), and that volatilisation

is subtracted, as for organic fertilisers.

3.4.2. Determination of the amount of nitrogen

leaching (LNO3)

Amount of nitrogen leaching (in kg N ha�1 yr�1) is

calculated from the product of the amount of nitrogen

leaching by a leaching factor (Eq. (5)).

LNO3¼ 100ððNleachable �%NleachedÞ=WdÞ4:42 (5)

where LNO3is the amount of losses of nitrogen to the

environment through NO3 leaching due to agricultural

practices (in mg NO3 L�1), Wd is the average drainage

(in mm) over 30 years, %Nleached is the part of nitrogen

leached to water, and Nleachable is calculated in Eq. (4).

The constant 100 is for the conversion of kg N ha�1 in

mg L�1, and 4.42 is to convert kg N into kg NO3.

To estimate %Nleached, we propose to use a

simplified equation of the Burns’ model (Burns,

1976). Eq. (6) is adapted for French conditions with

F. Pervanchon et al. / Agriculture, Ecosystems and Environment 105 (2005) 1–166

the assumption that nitrogen is uniformly allocated in

the soil (Party et al., 1999).

%Nleached ¼ ðWd=ðWd þ ðWsr=10ÞÞÞD=2 (6)

where Wd is the average drainage (in mm) over 30

years during the drainage period, Wsr is the volumetric

soil water retention (in %) and D is the rooting depth

(in cm).

4. Transformation of the nitrogen losses quantities

into a final score for the IN losses indicator

4.1. Calculation of the sub-indicators INH3, IN2O,

INO and INO3

4.1.1. Determination of a scale

In order to calculate the score of an indicator, the N

losses in environment need to be compared to a

reference because it makes the interpretation easier for

decision-making (Riley, 2001). The reference used

will correspond to a threshold of acceptable losses for

the environment and the transformation of the losses

into a score has to be based on two points: (i) the best

value of the indicator corresponds to an ideal situation

of zero N losses; (ii) the reference corresponds to the

maximum N level acceptable for the environment

(Girardin et al., 1999).

In order to make the comparison legible for users,

Girardin et al. (1999) suggested to express the score of

an indicator between 0 for high risks and 10 for no risk

to the environment, with a reference at 7. This scale

was used for the score of each sub-indicator of IN losses

(Eq. (7)).

Ii ¼ 10 � ð3Li=Nmax iÞ (7)

and if

Ii < 0 then Ii ¼ 0

where Ii is the sub-indicator of the IN losses indicator; it

estimates the pollution risk due to nitrogen losses in

the form i (NH3, N2O, NO and NO3) for environment.

Li is the losses of nitrogen to the environment in the

form i (NH3, N2O, NO and NO3) through agricultural

practices. The determination of Nmax i value is based

on the European norm fixed at a maximum of

Nmax NO3¼ 50 mg NO3 L�1. For volatilisation, the

norm is based on benchmark values of atmospheric

deposition of NH3 below which effects on flora and

soil quality is noticeable. A median value of the

different thresholds given by Bobbink et al. (1996):

Nmax NH3¼ 20 kg NH3-N ha�1 yr�1 was used. Unfor-

tunately, for N2O and NO there are no fixed bench-

marks in the literature. For N2O emissions from

temperate and boreal grasslands, the maximum is

18 kg N2O-N ha�1 yr�1 and the minimum is 0 kg

N2O-N ha�1 yr�1 (Freibauer and Kaltschmitt,

2000). For NO emissions, only preliminary results

were at our disposal: in Europe, the maximum is

4.3 kg NO-N ha�1 yr�1 for an Austrian extensive

grassland and 0 kg NO-N ha�1 yr�1 for an untreated

pasture in UK (Freibauer and Kaltschmitt, 2000).

Thus, by linear interpolation, a benchmark value for

the indicator corresponding to Nmax N2O ¼ 5:4 kg

N2O-N ha�1 yr�1 for N2O emissions and Nmax NO =

1.3 kg NO-N ha�1 yr�1 for NO emissions on grass-

lands was used.

4.2. Equation of the IN losses indicator

The indicator IN losses score corresponds to the

minimal score of the four sub-indicators in order to

take the lowest case between the different pathways of

nitrogen losses in air or in water (Eq. (8)). This

corresponds to the precautionary principle, as it is not

possible at present to know which impact is the most

harmful for environment or human health.

IN losses ¼ MinðINH3; IN2O; INO; INO3

Þ (8)

where IN losses is the indicator of nitrogen losses for

grassland management, INH3, IN2O; INO and INO3

are

four sub-indicators which determine the environmen-

tal effect of, respectively NH3, N2O, NO on air, and

NO3 on groundwater.

5. The three levels of information given by the

calculation of IN losses

The IN losses indicator offers a way to identify the

causes of pollution, and to compare the pollution

sources in order to find management solutions through

the use of three complementary levels of information

on pollution risks due to nitrogen management in

grasslands. Table 3 illustrates the three levels of

information according to four different management

F. Pervanchon et al. / Agriculture, Ecosystems and Environment 105 (2005) 1–16 7

Table 2

Description of the four scenarios used to test the sensitivity of the IN losses indicator and the sub-indicators INH3, IN2O, INO and INO3

Scenarios Organic fertilisationa Mineral fertilisationb Grazing days Ninputc Ninput crit

d

Extensive hay grasslands 20 60 – 100 80

Intensive hay grasslands 70 200 – 340 200

Extensive grazed grasslands 0 80 100 110 80

Intensive grazed grasslands 20 200 500 420 200

a Amount of manure expressed in t ha�1 yr�1.b Amount of chemical fertiliser expressed in kg N ha�1 yr�1.c In kg N ha�1 yr�1.d In kg N ha�1 yr�1. It is the nitrogen necessary for forage production.

scenarios and two types of soil, as detailed in Table 2.

The type of soil is taken into account through the

factor F which determines the N2O emissions (F = 1.5

for clay soils and F = 1.0 for sandy loam soil in Table

3) (adapted from Barton, 1999; Muller et al., 2002).

The first level gives general information on

pollution risk due to agricultural practices given by

the score of the IN losses indicator. The second level of

information is for sources of air and water pollution

risk according to environmental norms given by the

score of each sub-indicator. At this second level, it is

possible to compare the impact of each sub-indicator

according to the acceptable reference (e.g., 50 mg

NO3 L�1). The third level of information is the amount

of nitrogen (in kg N ha�1 yr�1) lost in water or to air,

given by the equations on which the sub-indicators are

Table 3

Illustration of the three levels of information allowed by indicator methodo

of soil (clay soil, corresponding to F = 1.5, and sandy loam soil correspo

Levels of information Extensive hay grassland Intensive hay grass

Clay soil Sandy soil Clay soil Sandy

Losses (in kg ha�1 yr�1)

NH3 6.0 6.0 20.5 20.5

N2O 2.9 1.9 9.9 6.6

NO 0.9 0.9 3.1 3.1

NO3 14.3 14.3 20.9 20.9

Sub indicator value

INH39.1 9.1 6.9 6.9

IN2O 8.4 8.9 4.5 6.3

INO 9.4 9.4 7.8 7.8

INO38.7 8.7 8.2 8.2

Final indicator value

IN losses 8.4 8.7 4.5 6.3

based (Eqs. (1)–(3) for gaseous emissions, and

adaptation of Eq. (5) for leaching). These three levels

allow managers to make decisions in order to limit the

pollution risk of nitrogen through agricultural prac-

tices. For instance, if at the first level, the score is good

(between 7 and 10 in the case of the indicator scale

proposed by Girardin et al., 1999), current practices

can be maintained. If the score is lower than 7, the

second level of information helps to identify the

source of pollution. The third level improves the

precision of the diagnosis: for instance, a low score of

INO3is due to high NO3 concentration in water, but

this high NO3 concentration can be due to a high

amount of nitrate lost per hectare (anthropogenic

factor), or a small quantity of drained water (climatic

factor). In the first case, management practices should

logy from four management scenarios given in Table 2 and two types

nding to F=1.0)

land Extensive grazed grassland Intensive grazed grassland

soil Clay soil Sandy soil Clay soil Sandy soil

6.4 6.4 28.2 28.2

2.0 1.4 9.4 6.2

1.0 1.0 3.8 3.9

13.2 13.2 41.3 41.3

9.0 9.0 5.8 5.8

8.9 9.2 4.8 6.5

9.3 9.3 7.3 7.3

8.8 8.8 6.4 6.4

8.8 8.8 4.8 5.8

F. Pervanchon et al. / Agriculture, Ecosystems and Environment 105 (2005) 1–168

be changed and in the second case, the farmer can do

little because the source of the problem is climatic.

Fig. 2. Illustration of a sensitivity test on the indicator IN losses for

intensive management of hay grasslands. The four sub-indicators of

the indicator (INH3(&), IN2O (~), INO (*) and INO3

(*), were tested

according to the variation of chemical fertilisers (Q fertchem), and

mineral nitrogen inputs in the form of organic fertilisers (Q fertorg).

6. Evaluation of the indicator IN losses

6.1. Sensitivity tests on the indicator IN losses

Once an indicator has been developed, it is

necessary to test its sensitivity (Girardin et al.,

1999) to input variables and to determine the

respective effect of each variable. Thus, in our study,

tests were carried out for four different scenarios of

nitrogen management described in Table 2. For each

test, one variable’s values was changed with range of

French agricultural practices, whereas the other

variables were fixed for each of the four scenarios

(Pervanchon et al., 2002).

For extensive management, the indicator sensitivity

to the variables variation was very low (graphs not

shown). The decrease was small for extensive hay

grasslands: within a range of 1 point for INH3for a

variation of the fertiliser amount; and less than 0.5

point for IN2O and INO, whereas for INO3, the score

remains constant at 9.3. For extensive grazed grass-

lands, the range of variations of the sub-indicators

value due to grazing days and mineral fertilisers, were

close to those of hay grasslands. The sub-indicators

score for gaseous emissions did not vary at all with

rooting depth, drainage or soil water retention.

For intensive management, the sub-indicator scores

varied considerably according to variation in inputs.

For the hay grassland scenario (Fig. 2 for the influence

of the variation of organic and mineral fertilisers), the

INO3and INH3

sub-indicators were less sensitive than

in the case of grazing, but the range of variation

remained high. The range of variation of INO and IN2O

was of the same order as that for grazed grasslands:

within a range of two points. For grazed grasslands

(Fig. 3 for the influence of the variation of grazing

days and chemical fertiliser amount), the highest

sensitivity was observed for INO3and concerns for

both the fertiliser amount and the grazing days. The

sub-indicator INH3was more sensitive to variations in

grazing days than to fertiliser amounts. The NO sub-

indicator did not vary much, whereas the range of

variations of IN2O was within two points. The INO3was

also very sensitive to rooting depth, drainage and soil

water retention in the case of intensive grazed

grasslands, but indicated little variation in the case

of hay grasslands because leaching was too low.

These results demonstrate that the indicator was

sensitive to management decisions. The indicator

underlined that the risk of leaching was close to zero

for grasslands managed extensively; the risk of

ammonia emissions was higher, but the emissions

remained in an environmentally acceptable range. In

the case of intensive management, above all for grazed

grasslands, the indicator underlined a high risk of

pollution.

6.2. Test on the calculation of the leaching for the

indicator development

In the case of a composite indicator as IN losses, the

validation of each sub-indicator was made by

comparison with measured data or from another data

source (data obtained by modelling or by experts)

F. Pervanchon et al. / Agriculture, Ecosystems and Environment 105 (2005) 1–16 9

0

2

4

6

8

10

70 100 130 160 190 220 250

0

2

4

6

8

10

180 280 380 480 580 680 780

Indi

cato

r va

lue

Indi

cato

r va

lue

Input of mineral fertiliserQ fertchem (kg N ha-1yr-1)

Numb of grazing daysd graz (d LU ha-1)

Fig. 3. Illustration of a sensitivity test on the indicator IN losses for

intensive management of grazed grasslands. The four sub-indicators

of the indicator (INH3(&), IN2O (~), INO (*) and INO3

(*) are tested

according to the variation of chemical fertilisers (Q fertchem), and the

number of grazing days (d graz).

when observed data are not available (Bockstaller and

Girardin, 2003). If the indicator has been based on a

quantitative model, the validation should first focus

on this model. This was the case for the leaching sub-

indicator of IN losses, where measured data for INO3

were available. These measurements were carried out

on permanent hay grasslands and perennial hay

grasslands from both Eastern and Western France

(Table 4), in semi-continental and oceanic climate,

respectively, where the drainage period begins in

October and finishes in April.

For a validation of a model, Mayer and Butler

(1993) insist on the necessity to use several measure-

ments to determine ‘‘the whole picture’’ of the model.

Three independent statistical variables (Yang et al.,

2000) were calculated (Table 5). For the entire dataset

(hay and grazed grasslands), the mean error (ME)

close to zero confirmed an apparent lack of systematic

bias. The root mean square error (RMSE) showed a

low accuracy considering the norm fixed at 50 mg L�1

(the ratio between the norm and RMSE should be

lower than 0.5). The forecasting efficiency (EF) which

was considered preferable to the classical coefficient

of determination R2 by several authors (Mayer and

Butler, 1993; Mitchell, 1997; Yang et al., 2000),

showed an average quality of prediction.

For the grazed grasslands, bias for the lowest values

of leaching were observed between calculated and

observed data. This was confirmed by the positive ME

which indicated an underestimation of the nitrate

concentration. The EF was lower than for the whole set

of data but still positive, whereas the accuracy of

prediction was the lowest as shown by the higher value

of RMSE. Concerning the hay grasslands, the accuracy

of prediction was acceptable with a RMSE equal to

11 mg NO3� L�1 whereas the ME indicated a slight

underestimation. The negative value of EF demon-

strated that the quality of prediction was not satisfactory

at all.

These results were not surprising for the leaching

sub-indicator of IN losses, INO3as they were based on a

simple model using many data set and coefficients

from different bibliographic sources and from a large

range of management conditions (Vertes et al., 2002).

Nevertheless, the aim of an indicator was not to

forecast but to give information on a risk level under

the given conditions. According to Bockstaller and

Girardin (2003), the validation procedure should show

at least realistic results by means of a probability test

based on the comparison between classes: e.g. if INO3

does not show a risk of leaching in water above the EU

standard of 50 mg NO3 L�1. For the entire data set the

test gave acceptable results for the two levels of

accuracy: 79% (91 grasslands over 117) of realistic

results under 25 mg NO3 L�1 range classes, and 92%

(108 grasslands over 117) of realistic results under

50 mg NO3 L�1 range classes (Fig. 4). The results for

hay grasslands were very satisfactory (98% of realistic

results under 25 mg NO3 L�1 and 100% under 50 mg

NO3 L�1 corresponding to 51 hay grasslands over 52

and 52 plots over 52, respectively). The results were

least realistic for grazed grassland (66% and 86%

corresponding to 43 grazed grasslands over 65 and 56

over 65, respectively). Thus, despite a lack of

F.

Perva

nch

on

eta

l./Ag

ricultu

re,E

cosystem

sa

nd

Enviro

nm

ent

10

5(2

00

5)

1–

16

10

Table 4

Description of the data set used to test the leaching calculation (total = 117; n = 65 for grazed grasslands, and n = 52 for hay grasslands)

Location Type of

grassland

Number of

grazing days

Type of management Number

of data

Leachinga

Mirecourt Permanent 0 Manure (19–36 t, nitrogen rate of 6 kg N t�1 on average) 8 2.3–13.7 (138)b

Eastern France Permanent 0 Diluted slurry (30–160 t, nitrogen rate of 2.5 kg N t�1

on average)

8 1.4–21.2 (144)b

Permanent 0 Chemical fertiliser (90–170 kg N ha�1) 7 0.8–9.0 (108)b

Permanent 0 No fertilisation 9 0.4–27.8 (158)b

Permanent 217–557 Manure (0–72 t, nitrogen rate of 6 kg N t�1 on average);

chemical fertiliser (100–200 kg N ha�1)

6 2.2–37.3 (85)b

Temporary 0 Chemical fertiliser (130–150 kg N ha�1) 18 1.8–8.2 (196)b

Permanent 194–427 Chemical fertiliser (42–112 kg N ha�1) 12 4.4–37.3 (67)b

Temporary 0–18 Chemical fertiliser (116–160 kg N ha�1) 4 0.5–5.9 (152)b

Temporary 0–60 Chemical fertiliser (122–140 kg N ha�1) 4 4.2–16.4 (115)b

Permanent 179–496 Manure (0–11 t, nitrogen rate of 6 kg N t�1 on average);

mineral fertiliser (95–210 kg N ha�1)

11 0.9–67.4 (97.2)b

La Jailliere Temporary 216–909 Chemical fertiliser (100–250 kg N ha�1 yr�1) 9 23.7–119 (60)b

Pin-au-Haras Temporary 425–709 Chemical fertiliser (0–331 kg N ha�1 yr�1) 9 0.1–332 (60)b

Kerbenez Temporary (grass-clover) 420–510 No fertilisation 6 9.6–40 (129)c

Western France Temporary (ray-grass) 467–500 Chemical fertiliser (250 kg N ha�1 yr�1) 6 10.6–61.6 (133)c

a In milligrams of NO3 L�1; average coefficient of variation in parentheses.b From ceramic cups.c From lysimeters.

F. Pervanchon et al. / Agriculture, Ecosystems and Environment 105 (2005) 1–16 11

Table 5

Results from the comparison of calculated and measured data for

nitrate leaching

Data RMSEa MEb EFc

Total 27.18 0.54 0.47

Grazed grasslands 37.80 12.37 0.35

Hay grasslands 11.23 �8.07 �3.15

a Root mean square error.b Mean error.c Forecasting efficiency.

Fig. 4. Probability test for the leaching sub-indicator INO3. Each cell

gives the number of points (in bold for grazed grassland). The test

consists in verifying whether the observed–calculated points are

within an acceptance area. The area of acceptance are the shaded

cells for a range within 25 mg NO3 L�1 and the bold framed cell for

a range within 50 mg NO3 L�1.

prediction quality, results of INO3for hay grassland

remained realistic if classes were within a range of

25 mg NO3 L�1 and within a range of 50 mg NO3 L�1

for grazed grasslands (based on the EU standards).

7. Discussion

7.1. Methodological choices for the calculation of

IN losses

In order to have a tool to aid decisions which is

feasible, legible and convenient for farmers and rural

managers, methodological choices were necessary in

order to determine IN losses. It is important first, that the

calculation of IN losses be independent of variations in

climate and water fluxes. Climatic data used for the

development of IN losses came from 30-year average

data in order to avoid yearly variations which could

mask the environmental effect of agricultural prac-

tices. If nitrogen management by farmers is envir-

onmentally sound, the IN losses score would be

satisfactory, even if the climatic conditions for the

year of study should favour leaching or gaseous

emissions, as it would ultimately correspond to a

‘‘mean potential’’ nitrogen loss.

Second, in models for NH3 emissions (Sommer and

Hutchings, 2001) or for N2O emissions (Conen et al.,

2000; Pedersen, 2000) precise or complex atmo-

spheric and pedological conditions data (e.g. wind

speed, temperature, soil moisture content, etc.) are

necessary to work. Furthermore, models of N2O

emissions only give information on denitrification and

do not calculate a net N2O emission (Golterman, 2000;

Henault and Germon, 2000; Liang and Xu, 2000). For

NO emissions on the other hand, there is no available

model (Freibauer and Kaltschmitt, 2000). Therefore,

models are not structured with the aim to determine

IN losses with easily available data. The NH3 volatilisa-

tion coefficients chosen in our indicator were sensitive

to management practices such as the fertiliser type and

the spreading period. For N2O, we were able to add to

the emission coefficient a correction factor (F) in order

to take into account not only the fertiliser rate but the

management conditions and the soil type. Thus, in the

case of organic, hydromorphic or clay soils, IN losses

points out that the risk of N2O emissions is higher than

the risk of leaching, which is consistent with available

data on denitrification (Barton, 1999). The NO

changes are only kept in the study for pedagogic

purposes (Freibauer and Kaltschmitt, 2000) because

the NO emission and the score of the sub-indicator INO

are always the least compared to the other sub-

indicators. Concerning N2, it has no direct environ-

mental impact, thus, it is not necessary to determine a

specific sub-indicator for N2.

A simple model was chosen to calculate the nitrate

leaching that avoided the calculation of N2 emissions

which may be a greater source of N losses than

leaching in the case of clay or organic soils

(Krysanova and Haberlandt, 2002; Muller et al.,

F. Pervanchon et al. / Agriculture, Ecosystems and Environment 105 (2005) 1–1612

2002). The N2 emissions are considered in empirical

parameter (m) obtained through multiple regression

calculation (ten Berge, 2002). This empirical para-

meter also integrates the emissions of N2O and

NO, and under certain conditions, those of NH3.

Additionally this chosen parameter relies on the

separate calculation between gaseous emissions and

nitrate leaching, which avoids common errors in the

approximation of a balance. Therefore, this model has

the additional advantage that it only needs necessary

data concerning the level of grass production related to

the potential production of the area concerned, and

the soil nitrogen supply, for a complete nitrogen

balance (Schroder et al., 1996). These data are needed

to determine the required level of input (Farruggia

et al., 2000; ten Berge, 2002). Lastly, the model is

based on the assessment of the available N reserves

before winter, which was recommended as a relevant

indicator by several authors (ten Berge, 2002; Van Bol

and Peeters, 1997).

The simple model herein developed for leaching is

limited in that it is applicable only for hay grasslands.

In order to adapt it for grazing conditions, it is

assumed that animal excrements (faeces and urine) are

the same N amounts as organic fertilisers. This

assumption needs to be confirmed with field trials (ten

Berge, 2002). Another criticism is that the Burns’

equation, used to obtain the amount of N leaching, is

not adapted to clay soils (Scotter et al., 1993). In fact,

leaching is calculated for the drainage period when the

soil is wet, when there is no crack pattern in the clay,

and preferential flow from soil cracks is assumed to be

negligible.

7.2. Validation of IN losses

IN losses was tested and validated for various soil

and climate conditions in Eastern and Western

France and proved to be sensitive to soil type. The

adapted equations used for leaching were initially

developed for The Netherlands (ten Berge, 2002)

and IN losses is adapted to areas characterised from

a temperate oceanic climate to semi-continental

climate. The discrepancy between observed and

calculated data, may be due to the statistical

coefficients used from the bibliography (especially

for the assessment of N from animal excrements),

and difficulties to estimate key variables such as

produced biomass and net N mineralisation in

grassland soils (Vertes et al., 2002). Thus, the trend

to underestimate nitrate concentration by INO3may

be explained by enhanced soil nitrogen mineralisa-

tion through long-term manuring. Nevertheless, low

values shown by the validation procedure of the

model to determine INO3have to be adjusted. The

discrepancy between observed and calculated data

may also be due to methodological problems when

using data from ceramic cups which have a high

variability (the variation coefficient can sometimes

reach more than 150% on average in ceramic cups).

It may be profitable to use other methods to measure

the nitrogen available in soil before winter, such as

soil analyses (Vertes et al., 2002). To validate the

indicator, long-term experiments are necessary to

gather data on gaseous emissions, water pollution by

nitrates, and nitrogen mineralised by grassland soils.

These observations should be obtained according to

agricultural practices in various conditions but at

present no such data exist.

Despite choices which were necessary to develop

IN losses, the probability tests show realistic results in

comparison with the EU standard of water quality,

meaning that the indicator is able to alert farmers to

whether they should improve their nitrogen manage-

ment strategies in regards to the risk of nitrate

leaching.

8. Conclusion

The IN losses indicator is a novel tool, that can be

placed between simple (e.g., balance models) and

complex model. This indicator provides a way to

identify the causes of pollution due to nitrogen

management in grasslands. The IN losses indicator can

be used as an alarm in conjunction with a set of other

indicators in order to evaluate the sustainability of

agriculture by giving information on socially accep-

table levels of potential polluting effects of agricul-

ture. For instance, nitrogen management has potential

effects on water and air, but it also influences the

floristic diversity and the agronomic value of grass-

lands, which should be quantified (work in process).

As agro-ecological indicators are tools to assess the

ecological sustainability of agroecosystems, they

could also be made more fully operational with

F. Pervanchon et al. / Agriculture, Ecosystems and Environment 105 (2005) 1–16 13

addition of economic and social indicators, at various

levels (field, farm, landscape, region).

Acknowledgements

Many thanks to Damien Foissy and Claude

Bazard (INRA SAD, Mirecourt), and Marie-Laure

Appendix A. List of the variables used for the calculat

Variable Description

%Nleached Part of the nitrogen leaching which is leached

CN2O k Coefficient for the determination of the N2O emissi

for a given fertiliser in the form k

(k is mineral fertiliser, organic fertiliser,

dung or urine)

CNH3 k Coefficient for the determination of the volatilisatio

for a given fertiliser in the form k

(k is mineral fertiliser, organic fertiliser, dung or uri

D Rooting depth

d graz Total number of grazing days

F Factor weighting the N2O emission according to soi

type (hydromorphic, clay or organic) or

agricultural practices (irrigation or cutting)

IN losses Nitrogen losses agro-ecological indicator for nitroge

management on cut or grazed grasslands

Ii Sub-indicator of the IN losses indicator to determine t

pollution risk due to the emissions of nitrogen

in the form i (i being NH3, N2O, NO or NO3): IN2O

to determine the pollution risk due to N2O on air, IN

to determine the pollution risk due to NH3 on air,

INO to determine the pollution

risk due to NO on air, and INO3to determine the

pollution risk due to NO3 on groundwater

Li Losses of nitrogen in the form i, due to agricultural

practices, to the environment (LNH3for ammonia, L

for nitrous oxide, LNO for nitric oxide and LNO3

for nitrate)

Ninput Total amount of mineral nitrogen inputs (sum of

mineral inputs in the form of organic and mineral

fertilisers, urine and dung)

Ninput crit Input which is necessary to cover the requirement

for forage production

Nleaching Total amount of mineral residual nitrogen in soil

Nmax I Factor corresponding to a emission reference of

nitrogen in the form i, for the environment (i being

NH3, N2O, NO or NO3)

Nmin H0 Constant mineral residual nitrogen observed

in soils

Q fertk Mineral nitrogen directly supplied by the nitrogen

inputs in the form k (Q fertdung for dung deposition,

Q ferturine for urine deposition, Q fertchem for

mineral fertiliser and Q fertorg for

organic fertiliser)

Decau (UMR INRA UCBN, Caen) for their

help in collecting data for validation of the

indicator. We also thank Marc Benoıt for his

hospitality at the INRA Centre of Mirecourt, Anne

Farruggia (Institut de l’Elevage) for her advice on

the indicator and Dan Lucero for his review of the

English.

ion of the IN losses indicator.

Unit

%

ons /

n

ne)

/

cm

d LU ha�1

l /

n Dimensionless

he

H3

Dimensionless

N2O

kg N ha�1 yr�1

kg N ha�1 yr�1

kg N ha�1 yr�1

kg N ha�1 yr�1

20 kg NH3-N ha�1 yr�1; 5.4 kg N2O-N ha�1 yr�1;

1.3 kg NO-N ha�1 yr�1’; 50 mg NO3 L�1

10 kg NO3-N ha�1 yr�1

kg N ha�1 yr�1

F. Pervanchon et al. / Agriculture, Ecosystems and Environment 105 (2005) 1–1614

Appendix A. (Continued )

Variable Description Unit

Q Nk Mineral nitrogen supplied by fertiliser in the form k

(Q Ndung for dung deposition, Q Nurine for urine

deposition, Q Nchem for mineral fertiliser and Q Norg

for organic fertiliser)

kg N ha�1 yr�1

Wd Water drainage in grassland soil (30 years average) mm

Wsr Soil water retention (30 years average) %

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