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Original article

Soil microbiological and biochemical propertiesfor assessing the effect of agricultural managementpractices in Estonian cultivated soils

Marika Truua,*, Jaak Truua, Mari Ivaskb

aFaculty of Biology and Geography, University of Tartu, 23 Riia Street, 51010 Tartu, EstoniabTartu College of Tallinn University of Technology, 78 Puiestee Street, 51008 Tartu, Estonia

a r t i c l e i n f o

Article history:

Received 3 September 2007

Accepted 19 December 2007

Published online 18 June 2008

Keywords:

Agricultural management practice

Microbial activity

Microbial biomass

Soil type

* Corresponding author. Tel.: þ372 7375 014;E-mail address: marika.truu@ut.ee (M. Tr

1164-5563/$ – see front matter ª 2008 Elsevidoi:10.1016/j.ejsobi.2007.12.003

a b s t r a c t

A set of soil microbiological and biochemical properties was used to assess the influence of

agricultural practices such as rotation, usage of pesticides, and fertilizers on the three most

widespread soil types (Calcaric Regosols, Calcaric Cambisols and Stagnic Luvisols) in the

fields of horticultural farms throughout Estonia. Microbial biomass, dehydrogenase and

alkaline phosphatase activity were significantly higher in Calcaric Regosols, whereas mea-

sured soil chemical parameters showed practically no difference among soil types. Multi-

variate exploratory analysis of soil biochemical and microbiological parameters clearly

distinguished soils with different management practices when the effect of soil type was

taken into account in data analysis. Activity of dehydrogenase, potential nitrification, N-

mineralisation, and microbial biomass contributed most strongly to the differentiation of

soils from differently managed fields. Soils managed according to organic farming princi-

ples were generally characterized by elevated microbiological parameter values, but at

the same time the variation of those parameters among soils from these fields was also

highest. The application of organic manure positively affected microbial biomass, N-

mineralisation, potential nitrification, dehydrogenase and acidic phosphatase activity.

Data analysis indicated that the amount of mineral nitrogen fertilizers added over time

has a stronger effect on microbial biomass than the amount added in a given year.

Legume-based crop rotation increased soil respiration and microbial biomass.

ª 2008 Elsevier Masson SAS. All rights reserved.

1. Introduction fertilizers and agrochemicals followed. At the beginning of

There have been two major changes in Estonian agricultural

management practice during the last century. At the begin-

ning of the 1940s land was taken from private owners and

large collective farms were established. Fifty years of very

intensive agricultural practice with high inputs of mineral

fax: þ372 7420 286.uu).er Masson SAS. All rights

the 1990s, the land was returned to private owners, but during

the last decade the economic situation and agricultural policy

have been unfavorable for agricultural land users. Since 1989

cropping area has steadily decreased by about half (from

975,000 ha in 1989 to 461,000 ha in 2003). The first organically

managed farms were established at the very end of the

reserved.

e u r o p e a n j o u r n a l o f s o i l b i o l o g y 4 4 ( 2 0 0 8 ) 2 3 1 – 2 3 7232

1990s. Nowadays ecologically managed land comprises about

5% of all agricultural land and only 14% of this land is used for

field crops. However, there are also still a number of farmers

who do not strictly follow any particular (organic or conven-

tional) management practice.

Soil is a complex environment, where microorganisms

play a crucial role in nutrient cycling and the degradation of

different pollutants (herbicides, pesticides, PAH-s, phenols,

etc.) contributing in this way to the maintenance of soil qual-

ity [8,14,39]. On the other hand, microbial activities are

strongly dependent on nutritional and other chemical and

physical conditions of the soil and respond rapidly to changes

in soil properties. Microorganisms are considered sensible

indicators when monitoring changes in soil status affected

by agricultural management, but the meaningful set of micro-

biological indicators still remains an object of debate

[3,11,31,35].

Microbial biomass is considered to be an integrative, bio-

logically meaningful, management sensitive, and measurable

signal in the soil [30]. Its turnover rate is much faster than that

of total soil organic matter, and based on the dynamics of soil

microbial biomass content, longer-term trends in soil total

organic matter content can be predicted [34]. The influence

of soil management on the organic matter C and N turnover

capacity of microbial biomass has been pointed out in many

studies focussing on microbial biomass and activity measure-

ments in arable soils [4,10,28]. Soil respiration is considered to

be one of the well-established parameters for monitoring

decomposition, but it is highly variable and can fluctuate

Table 1 – Soil and site characteristics of studied fields

Site no. Location Soil typea Mineral nitrogsum of thre

years (kg ha�

1 58�1600800N 22�0300200E CR

2 58�1900800N 22�0004500E CR

3 58�3701300N 26�3101500E CR 60

4 58�5804500N 24�4300100E CR 70

5 58�5804700N 24�4202500E CR 100

6 58�5805400N 24�4204200E CR 50

7 58�3902700N 26�3704000E CC 70

8 58�4300300N 26�3902800E CC 315

9 59�0902700N 25�4501900E CC 248

10 59�1005100N 25�4602100E CC 249

11 59�1004200N 25�4600900E CC 175

12 58�5805800N 24�4205300E CC 70

13 58�5805700N 24�4300000E CC 140

14 58�5805200N 24�4301000E CC 146

15 58�4103500N 26�3400300E SL

16 58�4104800N 26�3304900E SL

17 58�3700300N 26�3005900E SL

18 58�3301000N 25�3304400E SL 285

19 58�3300300N 25�3400200E SL 309

20 58�3304300N 25�3302300E SL 245

21 58�4200300N 26�3503800E SL 100

22 58�2602500N 22�0100800E CR

23 58�4203000N 26�3902200E SL 182

a CR – Calcaric Regosols, CC – Calcaric Cambisols, SL – Stagnic Luvisols.

b GM – green manure, numbers are shown for brown manure.

c H – Herbicides, I – Insecticidas, F – Fungicides.

widely depending on substrate availability, moisture content

and temperature [34]. N-mineralisation reflects the quality

and quantity of soil organic nitrogen and links the substrate

with the functioning and activity of a range of soil organisms.

In order to estimate the effects of soil management, land use

and specific conditions on soil microbial activity, short-term

laboratory measurements, including enzymatic activities are

used [3,12]. The advantage of standardizing environmental

factors is that it allows the comparison of soils of different or-

igins, but the results obtained represent the potential activity

only and must be interpreted with reservations [31].

The objective of this work was to use a set of soil microbi-

ological and biochemical indicators to evaluate the effect of

different management practices in three Estonian soil types.

2. Materials and methods

2.1. Soil type and management description

Twenty-three study areas with three most widespread soil

types (Calcaric Regosols, Calcaric Cambisols and Stagnic Luvi-

sols) throughout Estonia were selected (Table 1). On Calcaric

Cambisols and Stagnic Luvisols eight fields, and on Calcaric

Regosols seven fields with different management practices

were selected. Three years history of agricultural practices

(cover crops, amounts of mineral and organic fertilizers and

different kinds of pesticides used) was recorded. Mineral

nitrogen was applied on 17 fields and the amounts ranged

en,e1)

Organic fertilizers,sum of threeyearsb (t ha�1)

Pesticidesc Legumes/rape

No/no

120 Yes/no

65 H Yes/no

GM H Yes/no

H, F No/yes

H Yes/no

GM Yes/no

H, I Yes/no

H, I, F No/yes

H, I, F No/yes

40 H No/no

GM H, F Yes/no

H Yes/no

H Yes/no

GM Yes/no

GM Yes/no

25 Yes/no

H, I, F No/yes

H, I, F No/yes

H, I No/no

40 H, I No/yes

80 No/yes

H No/yes

e u r o p e a n j o u r n a l o f s o i l b i o l o g y 4 4 ( 2 0 0 8 ) 2 3 1 – 2 3 7 233

from 15 kg ha�1 per year (in three cases) to 142.5 kg ha�1 per

year (in one case during the last three years). Animal manure

was applied on seven fields and six fields have received green

manure. The amount of brown manure applied per year

ranged from 25 t ha�1 to 40 t ha�1. Three of the studied fields

had received both organic and mineral fertilizers simulta-

neously. Seven fields had oilseed rape in rotation (one or

two years during the last three years) and were also treated

with different pesticides – herbicides on all seven fields, insec-

ticides and fungicides on six fields. All together 16 fields were

treated with herbicides during the last three years. In 11 fields

at least once during the three years leguminous crops (mainly

clover) were grown. One field had not been treated with any

fertilizers or pesticides during the last three years, nor did it

have any leguminous crops in rotation.

2.2. Soil sampling

The samples were taken from the fields with a soil corer

(B2 cm) from 0 to 20 cm layer at the end of October 2003 and

composite samples were made for each field. For the compos-

ite samples (one to three composite samples depending on the

size of the field, one composite sample per 2 ha) 25 subsam-

ples were randomly collected from each field. The fresh soil

samples were sieved (<2 mm) and stored at 4 �C until the anal-

yses were carried out. From the sieved samples, soil organic

matter content (the loss on ignition method), dry matter

content, pHKCl, total nitrogen, total potassium, and available

phosphorus content were determined and microbiological

analyses were performed.

2.3. Microbiological biomass and activities

Substrate-induced respiration (SIR) by Isermeyer technique

was applied to measure metabolically active microbial

biomass carbon. Glucose (0.4 g 100 g�1 soil) was added to 20 g

of field moist soil and then incubated in a closed vessel for

4 h at 22 �C in the dark. The CO2 produced was absorbed in

0.1 M sodium hydroxide and quantified by titration. The mi-

crobial biomass C was calculated according to Beck et al. [2].

Soil microbial respiration rate (basal respiration) was mea-

sured by titration according to Ohrlinger [41]. Twenty gram

of soil was incubated in a closed vessel for 24 h at 25 �C. The

CO2 produced was absorbed in 0.05 M sodium hydroxide,

quantified by titration, and the respiration rate was calcu-

lated. The microbial metabolic quotient qCO2 was calculated

as the ratio between basal respiration and SIR-derived micro-

bial carbon. Dehydrogenase activity was measured using

triphenyltetrazolium chloride as a substrate. Samples were

incubated for 16 h at 25 �C and the triphenyl formazan pro-

duced was extracted with acetone and measured photometri-

cally at 546 nm [40]. N-mineralisation was determined under

waterlogged conditions according to Kandeler [16]. Water-

logged soils were incubated for seven days at 40 �C. The

ammonium released from organic nitrogen compounds was

extracted with 2 M potassium chloride solution, determined

by a modified Berthelot reaction, and measured with a spectro-

photometer at 660 nm [17]. In order to evaluate the nitrifica-

tion capacity of the microbial communities, the potential

nitrification method was used [18]. Soil samples with

ammonium sulfate as a substrate and sodium chlorate as an

inhibitor preventing nitrite oxidation were incubated for 5 h

at 25 �C and the released nitrite was extracted with 2 M potas-

sium chloride solution and determined colorimetrically at

520 nm. Acid and alkaline phosphomonoesterase activities

were measured using p-nitrophenyl phosphate as a substrate

according to Margesin [24]. Samples were incubated for 1 h at

37 �C and the released p-nitrophenol was extracted with 0.5 M

sodium hydroxide in the presence of calcium chloride. The

amounts of extracted products derived from all activity mea-

surements were determined photometrically at 400 nm. All

measured microbiological parameters were calculated on

dry matter bases.

2.4. Statistical analyses

Spearman rank correlation coefficient was used to relate soil

microbiological variables to soil chemical parameters, and to

the amount of mineral fertilizers applied annually and cumu-

latively during the last three years. The Kruskal–Wallis one-

way analysis of variance by ranks’ test was used to assess

the impact of soil type on soil microbiological and chemical

parameters. The data set of soil microbiological variables

was analyzed using principal component analysis (PCA) based

on a correlation matrix, and the effect of binary coded charac-

teristics on the grouping of samples was assessed using

a multivariate randomization test [23] with the computer

program ADE-4 [37]. Prior PCA values of microbiological

variables were log-transformed. The following management

options were binary (presence/absence) coded: use of organic

fertilizers, and pesticides (herbicides, fungicides, and insecti-

cides). The Mann–Whitney test was used to verify the impact

of coded factors on individual soil microbiological variables.

The results of PCA are interpreted using scatters of the sample

scores and a correlation plot showing the relationship of vari-

ables with PCA axes. Grouping of samples due to binary coded

variables is visualised using scatters of the sample scores

connected with group centroids (star plot). Group centroid

coordinates are calculated as the average of the coordinates

of all the group members.

3. Results

Comparison of soil microbiological parameters based on coef-

ficient of variation (CV) showed that the highest variation

among all samples appeared in values of dehydrogenase

activity and potential nitrification (CV 148.2% and 143.0%, re-

spectively), followed by alkaline phosphatase (CV 92.4%), mi-

crobial biomass (CV 89.3%), basal respiration rate (CV 68.8%).

The least variable was acid phosphatase activity (CV 57.9%).

The multivariate randomization test showed that soil type

has a strong effect on soil microbiological variables (P< 0.01,

10,000 permutations). According to the Kruskal–Wallis test,

microbial biomass, activities of dehydrogenase, and alkaline

phosphatase had significantly higher values in Calcaric

Regosols (Table 2). The measured chemical parameters did

not differ between soil types, except for pH (Kruskal–Wallis

test, P< 0.05) the values of which were lowest in Stagnic Luvi-

sols (6.03� 0.75), and did not differ between Calcaric Regosols

Table 2 – Mean values and standard deviations of soil microbiological parameters in different soil types

Soil type (WRB) SIR (mgC g�1 dw) Dehydrogenase activity(mgTFP g�1 dw 16 h�1)

Alkaline phospatase(mgNP g�1 dw h�1)

Calcaric Regosols 0.779� 0.219** 6.397� 4.022* 406.7� 185.1*

Calcaric Cambisols 0.559� 0.121 4.104� 0.975 297.5� 123.3

Stagnic Luvisols 0.439� 0.139 2.988� 0.705 167.4� 157.4

Only parameters that were different among soil types according to Kruskal–Wallis one-way analysis of variance by Ranks are shown. Asterisks

designate group means that are statistically different according to multiple comparisons of mean ranks. *P< 0.05, **P< 0.01.

e u r o p e a n j o u r n a l o f s o i l b i o l o g y 4 4 ( 2 0 0 8 ) 2 3 1 – 2 3 7234

and Calcaric Cambisols (6.82� 0.27 and 6.38� 0.35, respec-

tively). Total nitrogen content showed highest variation (CV

106.69%) among samples and was related to soil microbial bio-

mass, dehydrogenase activity, potential nitrification, N-min-

eralisation, and alkaline phosphatase activity (Table 3). Soil

organic matter content correlated significantly with all mea-

sured microbiological parameters, but the relationship was

strongest in the case of potential nitrification, dehydrogenase

activity, N-mineralisation, alkaline and acid phosphatase

activities. The soil pH was related to microbial biomass, basal

respiration, and alkaline phosphatase, but was only slightly

correlated with potential nitrification.

A partial form of principal component analysis was used to

estimate the importance of microbiological variables in the

grouping of the studied fields. In the case of partial PCA, the

analysis was performed on the residual matrix of microbiolog-

ical variables after regression on soil type, i.e. the effect of soil

type was removed from the analysis. The first two principal

components accounted for 78.9% of the total variation in the

microbiological data set. The first principal component was

positively related to dehydrogenase, potential nitrification

and N-mineralisation activity, and microbial biomass, while

the second principal component was negatively correlated

with metabolic quotient and soil respiration (Fig. 1a). Accord-

ing to PCA ordination, the fields of organic farms are located to

the right of the origin and are characterized by higher micro-

bial activity values and biomass (Fig. 1b, Table 4). The second

group of fields is scattered around the origin and consists

mainly of fields that have received both organic and inorganic

fertilizers. The third group of fields, which is situated to the

left of the origin, comprises mostly of fields that in most cases

have received higher amounts of mineral nitrogen as well as

other agrochemicals (herbicides, pesticides and fungicides).

The multivariate randomization test indicated that

Table 3 – Relationships between soil microbiological andchemical parameters based on Spearman rankcorrelation coefficient

Variable Ntot TC pH

SIR 0.51** 0.45* 0.69***

Dehydrogenase activity 0.82*** 0.75***

Potential nitrification 0.83*** 0.76*** 0.48**

N-mineralisation 0.62*** 0.60***

Alkaline phosphatase 0.88*** 0.82*** 0.83***

Acid phosphatase 0.50**

Respiration 0.45* 0.39* 0.80***

*P< 0.05, **P< 0.01, ***P< 0.001.

application of organic fertilizers had a significant impact on

the grouping of fields (P< 0.01, 10,000 permutations) (Fig. 1c).

According to the Mann–Whitney test, fields treated with

organic fertilizer are characterized by two times higher micro-

bial biomass (P< 0.01) and N-mineralisation values (P< 0.001).

Data analysis indicated a tendency for increased respiration

and microbial biomass in the case of fields with legume-based

crop rotation (Mann–Whitney test, P< 0.01 and P< 0.05,

respectively). At the same time, these two parameters were

negatively affected by the use of pesticides; respiration

activity (mean values 0.21 and 0.10 mg CO2 24 h�1 g�1 dw, re-

spectively) was repressed in particular.

Values of studied microbiological variables were regressed

on the amount of mineral fertilizers applied annually and

cumulatively during the last three years. From the set of mea-

sured microbiological parameters, only microbial biomass

was correlated negatively with the amount of mineral nitro-

gen applied annually (R¼�0.53, . �0.57, P< 0.01), but the

strongest relationship (R¼�0.68, P< 0.001) was found with

the cumulative amount of mineral nitrogen applied during

the last three years.

4. Discussion

Soil type is one of the primary determinants of soil microbial

structure, as demonstrated by polyphasic studies of soil bacte-

rial community composition [13,32]. We found that microbial

biomass, and activities of dehydrogenase and alkaline phos-

phatase are dependent on soil type, whereas measured soil

chemical parameters showed practically no variation among

the three studied soil types. These differences in soil microbial

parameters due to soil type may be related to the qualitative

structure of soil organic carbon as well as to soil texture [33].

In the study of conventional and organic farms Van Diepenin-

gen with co-workers [38] found that soil type in general has

a much stronger effect on the soil characteristics than man-

agement type. Our results support such a conclusion and

stress the importance of considering soil type in data analysis

of soil microbiological variables. In our study we took into

account the effect of soil type in the further statistical analysis

of microbiological variables. The partial form of PCA based on

soil biochemical and microbiological parameters separated

soils with different management practices, especially soils

from organically managed fields. From measured soil bio-

chemical and microbiological parameters, dehydrogenase,

potential nitrification, N-mineralisation activity, and micro-

bial biomass contributed most strongly to the separation of

soils in PCA. These microbiological variables are considered

Fig. 1 – Partial principal component analysis based on the correlation matrix of soil microbiological parameters. (a)

Ordination of soil samples along first two PCA axes (F1 3 F2). (b) Correlation of soil microbiological parameters with PCA

axes. Abbreviations: AcP – acidic phosphatase, AlP – alkaline phosphatase, D – dehydrogenase, N – N-mineralisation,

PN – potential nitrification, Q – metabolic quantient, R – respiration, SIR – microbial biomass. (c) Star plot showing

impact of manure application on grouping of soil samples. The results of PCA are interpreted using a scatter of the

sample scores connected with group centroids. Group centroids are designated by letters a (no manure used) and

b (fields with manure use).

e u r o p e a n j o u r n a l o f s o i l b i o l o g y 4 4 ( 2 0 0 8 ) 2 3 1 – 2 3 7 235

as potential indicators of soil quality and management impact

in many papers [3,11,12,27,35]. In our case the soils originating

from organically managed farms were generally characterized

by elevated microbiological parameter values, but at the same

time the within-group variation of soil microbiological param-

eters was also highest. The reasons for such large deviations

among organically managed soils may be the different dura-

tions of organic management practice as well as differences

in management history among fields, such as different

amounts and types of organic fertilizers (green or brown

manure) applied and differences in crop rotation.

The application of manure affected the functioning of

the microbial community and two groups were clearly

Table 4 – Minimum and maximum values of soil microbiologicfertilizer use

Variable Only organicfertilizers (n¼

SIR (mgC g�1 dw) 0.46–1.23

Dehydrogenase activity (mgTFP g�1 dw 16 h�1) 3.32–14.6

Potential nitrification (mgN g�1 dw 24 h�1) 0.85–6.64

N-mineralisation (mgN g�1 dw d�1) 0.94–2.28

Alkaline phosphatase (mgNP g�1 dw h�1) 92.5–774

Acid phosphatase (mgNP g�1 dw h�1) 120–336

Respiration (mgCO2 24 h�1 g�1 dw) 0.07–0.24

distinguished: soils which received manure in one or two years

or all the three last years, and those that have not received ma-

nure duringthe threeyear period.This treatmenthad a positive

effect on microbial biomass and N-mineralisation, potential

nitrification, dehydrogenase activity and acidic phosphatase

activity. Surprisingly, there was no significant positive impact

of manure on soil microbial biomass, which has been shown

by several authors [19,21,25]. The consecutive application of

manure over three years enhanced respiration rate, probably

due to the addition of easily degradable organic fractions in

the last year, when soil samples were taken. According to

Sparling [34] and Dilly [9] the quality of organic matter greatly

determines the amount of CO2 efflux from the soil. The

al parameters in soils of studied fields with different

5)Mineral and organic

fertilizers (n¼ 6)Only mineral

fertilizers (n¼ 11)

0.54–0.85 0.26–0.80

2.96–4.49 2.00–5.41

0.51–2.91 0.56–4.2

0.81–1.80 0.40–2.23

90.0–419 20.7–565

90–419 118–259

0.07–0.15 0.05–0.09

e u r o p e a n j o u r n a l o f s o i l b i o l o g y 4 4 ( 2 0 0 8 ) 2 3 1 – 2 3 7236

increase of qCO2 due to organic amendments was reported

also by Leita and co-workers [21]. Higher microbial biomass

and activities in the case of organic farming and manure

amendment have been described by many authors

[1,5,6,15,29]. Bittman et al. [4] have found significantly greater

bacterial abundance in the soils where manure has been

used compared to minerally fertilized and untreated soils,

but fungal biomass responded negatively to both types of fertil-

ization. Long-term organic and mineral fertilizer application is

reflected also in altered soil bacterial community structure

[36]. Another management option frequently used for the in-

put of organic matter, legume-based crop rotation, has been

reported to having a positive effect on the microbial commu-

nity [22]. Legume-based crop rotation was also proved to

increase soil respiration and microbial biomass, although the

use of manure had a much stronger overall effect on soil micro-

bial activity.

Strong cumulative negative effect of mineral nitrogen ap-

plication on microbial biomass was revealed in data analysis.

This means that the amount of nitrogen fertilizers added over

time has a stronger effect on microbial biomass than the

amount added in a given year. Such a relationship between

microbial biomass and mineral nitrogen application could be

partly explained by reduced input of readily available organic

matter for soil microbes. Chantigny et al. [7] found that water-

soluble organic carbon contents decreased with increasing

mineral nitrogen fertilizer application due to elevated C-min-

eralisation. Same authors also suggest that increased mineral

nitrogen application may indirectly affect soil respiration by

promoting plant growth and water uptake, which leads to re-

duced soil water content. In our case, simultaneous applica-

tion of manure and mineral fertilizers had the same

negative effect on soil microbial biomass as the use of mineral

fertilizers alone. The amount of mineral nitrogen added over

time was also negatively related to soil acidity, which was

on average 0.4 units lower in soils of minerally fertilized fields.

There was no relationship between the amount of mineral ni-

trogen added and soil organic matter content among the stud-

ied fields. This may be due to the fact that we do not have any

baseline data for the studied fields and, in such a situation,

comparison between fields may not reveal a decrease of soil

organic matter as a result of synthetic N fertilization [20].

Our data did not reveal a negative relationship between the

amount of mineral fertilizer used and dehydrogenase activity,

although Masciandaro et al. [26] have found that mineral and

organic fertilizers affect the kinetic parameters of dehydroge-

nase, substrate affinity and the maximal rate of the enzyme

activity. It could be suggested that the effect on the kinetic

parameters of dehydrogenase might be mediated through

microbial biomass, which decreases with the amendment of

mineral fertilizers; meanwhile the change in substrate affinity

reflects an alteration in soil microbial community structure.

Our results show that changes in Estonian agricultural

management practice during the last decade have already

been reflected in soil microbiological properties. In most

cases, organic farming practice has led to increased microbial

biomass and activities in the soil, but high variation of

microbiological parameters in those soils may, at the same

time, indicate the ongoing transitions caused by changes in

agricultural management practice.

Acknowledgements

This study was part of the research project ‘‘Impact of agricul-

tural management practices to the diversity of soil biota in

Estonian arable soils’’ funded by Estonian Science Foundation

grant No. 5571. The authors are grateful to the head of the

Laboratory of Soil Biology at Hohenheim University, Prof. Ellen

Kandeler, for the opportunity provided for M. Truu to study

soil biochemical methods in their laboratory. We also thank

Dr. Dagmar Tscherco and Dr. Kerstin Molter for their help

and advice.

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