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Bacterial diversity in Greenlandic soils as affected by potato cropping and inorganicversus organic fertilization

Frydenlund Michelsen, Charlotte; Pedas, Pai; Glaring, Mikkel Andreas; Schjoerring, Jan Kofod;Stougaard, Peter

Published in:Polar Biology

Link to article, DOI:10.1007/s00300-013-1410-9

Publication date:2013

Document VersionPublisher's PDF, also known as Version of record

Link back to DTU Orbit

Citation (APA):Frydenlund Michelsen, C., Pedas, P., Glaring, M. A., Schjoerring, J. K., & Stougaard, P. (2013). Bacterialdiversity in Greenlandic soils as affected by potato cropping and inorganic versus organic fertilization. PolarBiology. https://doi.org/10.1007/s00300-013-1410-9

ORIGINAL PAPER

Bacterial diversity in Greenlandic soils as affected by potatocropping and inorganic versus organic fertilization

Charlotte Frydenlund Michelsen • Pai Pedas •

Mikkel Andreas Glaring • Jan Kofod Schjoerring •

Peter Stougaard

Received: 15 April 2013 / Revised: 27 August 2013 / Accepted: 26 September 2013

� Springer-Verlag Berlin Heidelberg 2013

Abstract Arctic and Subarctic ecosystems will in the

near future be exposed to severe environmental stresses

due to global warming. For example, the microbial com-

munity structure and function may change as a result of

increased temperatures. In Greenland, agriculture is carried

out in the Subarctic regions with only limited pest man-

agement, despite the presence of plant pathogenic fungi.

The microbial community composition in agricultural soils,

which plays an important role for soil and plant health and

for crop yield, may be affected by the use of different

fertilizer treatments. Currently, only limited research has

been performed on the effects of these treatments on bac-

terial communities in Arctic and Subarctic agricultural

soils. The major objective of this study was to investigate

the short-term impact of conventional (NPK) and organic

(sheep manure supplemented with nitrogen) fertilizer

treatments on bacterial diversity, nutrient composition and

crop yield in two Greenlandic agricultural soils. An effect

of fertilizer was found on soil and plant nutrient levels and

on crop yields. Pyrosequencing of 16S rRNA gene

sequences did not reveal any major changes in the overall

bacterial community composition as a result of different

fertilizer treatments, indicating a robust microbial com-

munity in these soils. In addition, differences in nutrient

levels, crop yields and bacterial abundances were found

between the two field sites and the two experimental

growth seasons, which likely reflect differences in physi-

cal–chemical soil parameters.

Keywords Soil bacterial diversity � Pyrosequencing �Nutrient composition � NPK-fertilizer � Sheep manure

Introduction

With the rising temperatures due to global warming, The

International Arctic Science Committee expects great

prospects for increasing the cultivation areas in the Arctic

and Subarctic regions. Until now, agriculture in Greenland

has been limited to areas very far southwest, located in the

inner fjords between the towns Narsaq and Nanortalik

(Fig. 1). The major crops are potato and forage grass, but

cabbage and turnips are cultivated as well although to a

minor degree. In Greenland, agriculture is carried out

without the use of pesticides and with limited crop rotation.

Despite this, there are no reports about severe plant dis-

eases, such as potato late blight. The low incidence of plant

diseases in Greenland in general may be ascribed to either

the relative low winter temperatures and/or to the presence

of beneficial biocontrol microorganisms in the Greenlandic

soils. We have shown that Greenlandic soils cultivated with

potato crops contain beneficial biocontrol bacteria

Electronic supplementary material The online version of thisarticle (doi:10.1007/s00300-013-1410-9) contains supplementarymaterial, which is available to authorized users.

C. F. Michelsen � P. Pedas � M. A. Glaring �J. K. Schjoerring � P. Stougaard (&)

Department of Plant and Environmental Sciences, University of

Copenhagen, Thorvaldsensvej 40, 1871 Frederiksberg C,

Denmark

e-mail: psg@life.ku.dk

C. F. Michelsen

e-mail: charl@life.ku.dk

P. Pedas

e-mail: pp@life.ku.dk

M. A. Glaring

e-mail: mig@life.ku.dk

J. K. Schjoerring

e-mail: jks@life.ku.dk

123

Polar Biol

DOI 10.1007/s00300-013-1410-9

(Michelsen and Stougaard 2011, 2012), but whether the

temperature conditions contribute to the low disease inci-

dences, still has to be documented. Beneficial biocontrol

microorganisms and potential plant pathogenic fungi only

constitute a minor fraction of the total soil microbial

community, which has been shown to be responsible for a

vast number of functions affecting, e.g., biogeochemical

cycles, release of trace gases (Lundquist et al. 1999),

mineralization of nitrogen, phosphorus and sulfur (Gray-

ston et al. 1998), and formation of soil aggregates (Haynes

and Naidu 1998; Six et al. 1998). Thus, the composition of

microbial communities in agricultural soils can

Fig. 1 Map of Greenland. The

black square denotes the study

area (60�4406000N; 45�5302200W)

at the inner Fjord system around

the towns Narsaq and

Nanortalik in southwest

Greenland, where the

experimental research farm at

Upernaviarssuk is located

Polar Biol

123

significantly affect plant health, yield and nutrient levels.

However, the microbial community composition in soils

can be influenced by a number of abiotic and biotic factors.

In agriculture, one of the most important factors, which

can significantly modify the structure of microbial com-

munities and thus plant health and yield, is amendment

with fertilizers (Haynes and Naidu 1998). In grassland

soils, different fertilizer treatments in addition to plant

species and soil pH were found to influence the bacterial

community structure (Nacke et al. 2011; Liliensiek et al.

2012), and in long-term field experiments with different

types of fertilizers, the structure of soil bacterial commu-

nities was dependent on whether conventional or organic

fertilizers were used (Esperschutz et al. 2007). Changes in

soil pH were also found to strongly affect the bacterial

community composition in Canadian, Alaskan and Euro-

pean Arctic soils (Chu et al. 2010).

However, despite that Arctic and Subarctic regions in

particular are exposed to severe environmental stresses due

to global warming, only limited research has been per-

formed on the effects of nutrient deposition on bacterial

communities in soils from these areas, and no research has

been conducted on Greenlandic soils.

In this study, we investigate the bacterial community

composition in two Greenlandic soils over two growth

seasons by using pyrosequencing of 16S rRNA gene

sequences. One soil was sampled in a field, which had been

cultivated for decades, while the other soil was from a

recently established field site. The effects of inorganic

fertilizer versus sheep manure supplemented with inor-

ganic N on the bacterial community composition were

analyzed along with parameters characterizing potato crop

yield and soil chemical fertility.

Materials and methods

Field site, soil sampling and soil chemical analysis

The experiment was conducted in an old, well-established

agricultural field (Field WE) and a newly established field

(Field NE) at the experimental research farm of Upernavi-

arssuk, southwest Greenland (60�4406000N; 45�5302200W)

(Fig. 1). In each of the two fields, an area of 40 m2 was divided

into two main blocks, each consisting of three plots applied

different treatments, viz. (1) commercial NPK-fertilizer

(Kemira, 14-3-15; approximately 850 kg per hectares (ha) per

year), (2) 2-year-old sheep manure supplemented with nitro-

gen (manure.N), (approximately 15 tons sheep manure and

90 kg N (N27-Mg2.5) per ha per year, see analysis of sheep

manure in Table S1) and (3) an untreated control. The fertil-

izer treatments were applied the 20th of May prior to seeding

of potatoes (variety Leoni) in three rows per plot.

Sampling of soil took place in May before fertilization

and again in September 2010 and August 2011 after har-

vest of the potato crops. A soil auger was used to take 10

random cores in 4 replicates from the top 20 cm in each

plot. The 10 cores per replicate were subsequently pooled

and stored in sealed plastic bags at 5 �C. Soil texture and

content of P, K, Mg and inorganic N were determined at a

certified commercial laboratory (Eurosteins, Sweden)

according to official Danish standards for soil analysis. The

pH level was measured in 0.01 M CaCl2 with a soil-to-

solution ratio of 1:2.5. Phosphorus was measured by

extraction with NaHCO3 (0.5 M for 30 min, soil-to-solu-

tion ratio of 1:20), and potassium and magnesium were

extracted with 0.5 M CH3COONH4 for 30 min in a soil-to-

solution ratio of 1:10. Inorganic N (NH4? and NO3

-) was

extracted in a soil-to-solution ratio of 1:5 with 1 M KCl for

45 min and analyzed on a flow injection analyzer system

using the gas diffusion and cadmium reduction method,

respectively (Sparks et al. 1996).

Soil and air temperature measurements

Soil and air temperatures were measured every hour during

the two experimental years using HOBO Pendant Tem-

perature/Light Data Loggers (T/L-logger). The data loggers

were placed in the soil and air at the beginning of field trial

in May 2009. Four data loggers were placed in each field at

approximately 10–15 cm below ground to measure soil

temperatures, while the data logger for air temperature

measurements was placed at two meters height above the

soil surface.

Sampling of plant material and plant analysis

Potato shoot samples were collected in July in each of the

two experimental years. The shoots of two potato plants

from the middle row of each plot were collected by cutting

the stems 5 cm above ground. The shoots were stored in

sealed plastic bags at -20 �C until analysis.

Potato tuber yield was measured at the end of the

growth season in each of the 2 years. The tubers were

collected in September from the middle row in each

treatment plot.

To assess the nutritional status of shoots and tubers, mul-

tielemental analyses were performed (Laursen et al. 2009;

Hansen et al. 2009). The plant samples were freeze-dried

(Christ Alpha 2–4; Martin Christ GmbH), digested and the

elemental concentrations determined using ICP-MS (Agilent

7500ce, Agilent Technologies, Manchester, UK). For every

40 samples, four blanks without plant material and four with

certified reference material (apple leaf, standard reference

material 1515; US Department of Commerce, National

Institute of Standards and Technology, Gaithersburg, MD,

Polar Biol

123

USA) were included. For total N determination, 4 mg of dried

plant material was weighed into tin capsules and analyzed in a

system consisting of an ANCA-SL Elemental Analyzer cou-

pled to a 20–20 Tracermass Mass Spectrometer (Europa

Scientific Ltd., Crewe, UK).

DNA isolation and amplification of 16S rRNA gene

sequences by pyrosequencing

DNA was isolated directly from 0.5 g of soil from each of the

samples, by using the UltraCleanTM Soil DNA Kit (MO BIO

Laboratories, Inc., Carlsbad, CA, USA) following the

manufactures instructions. The concentration of double-

stranded DNA in each sample was determined using Quant-

iT dsDNA HS Assay Kit (Invitrogen, Life Technologies

Europe, Naerum, DK) with the FLUOstar OPTIMA

Microplate fluorometer (BMG LABTECH GmbH, Orten-

berg, GE). The DNA concentration was adjusted to

5 ng ll-1 for all samples. A 466-bp fragment covering the

V3 and V4 hypervariable regions of the 16S rRNA gene from

bacteria and archaea was amplified using the primers 341F

(50-CCTAYGGGRBGCASCAG-30) and 806R (50-GGAC-

TACNNGGGTATCTAAT-30). The PCR (50 ll) was per-

formed using 5 ng of template DNA, 1 U of Phusion

HotStart DNA polymerase (Finnzymes, Vantaa, Finland), 1x

Phusion HF Buffer, 200 lM of each dNTP and 0.5 lM of

each primer with the following cycle conditions: 98 �C for

30 s, followed by 30 cycles of 98 �C for 5 s, 56 �C for 20 s

and 72 �C for 20 s and a final extension of 72 �C for 5 min.

PCR products were purified using an E.Z.N.A. Gel Extrac-

tion Kit (Omega Bio-Tek, Norcross, GA, USA).

Adapters and tags for pyrosequencing were added in a

second 15-cycle PCR on 5 ng of purified PCR product,

using the conditions described above with primers 341F

and 806R carrying sequencing adapters and tags for mul-

tiplexing. The amplified fragments were gel-purified using

the Montage DNA Gel Extraction Kit (Millipore, Hellerup,

Denmark), quantified using the Quant-iT dsDNA HS Assay

Kit (Invitrogen, Life Technologies Europe, Naerum, Den-

mark) and mixed in equal amounts before sequencing on a

Genome Sequencer FLX pyrosequencing system (454 Life

Sciences, Roche, Branford, CT, USA).

Sequence trimming and phylogenetic analysis

Trimming and quality-filtering were performed using

Biopieces (www.biopieces.org). Initially, tags and primer

sequences were removed, discarding any sequences that

did not show a match to both a tag and the forward primer.

Low-quality bases were trimmed from both ends and

sequences shorter than 250 bases, containing more than one

ambiguous nucleotide, or with an average Phred quality

score lower than 25 were discarded. The trimmed and

quality-filtered sequences used as an input for the QIIME

pipeline is available on the MG-RAST server (http://

metagenomics.anl.gov/,ID4520195.3).

Phylogenetic analysis was performed using the quanti-

tative insights into microbial ecology (QIIME) pipeline

version 1.5 (www.qiime.org) (Caporaso et al. 2010). OTU

clustering was performed using the USEARCH (Edgar

2010) quality filter pipeline in QIIME, which included: (1)

dereplication and subsequent error correction by outputting

the consensus sequences of an initial clustering step at 97 %

identity, (2) removing chimeric sequences using UCHIME

(Edgar et al. 2011) by comparison to the chimera-free

‘‘gold’’ database available from the Broad Institute Mi-

crobiome Utilities (microbiomeutil.sourceforge.net) and (3)

an OTU clustering step at 94 or 97 % roughly corre-

sponding to genus and species level, respectively. Taxon-

omy was assigned to the resulting OTUs using the RDP

classifier with a confidence threshold of 50 % (Cole et al.

2009) and a training set from the Greengenes database

(version 12_10) (DeSantis et al. 2006). Subsequently, all

OTUs containing only one sequence (singletons) that did

not show a phylogenetic match at the family level or lower

were deemed unreliable and discarded.

Alpha diversity (rarefaction and richness estimators) and

beta diversity (PCoA plots) analysis was performed using

the QIIME functions ‘‘alpha_rarefaction.py’’ and ‘‘beta_-

diversity_through_plots.py,’’ respectively, using default

options. All samples were subsampled to an even number

of sequences as part of the analysis.

Results

Soil fertility and crop responses

The content of sand (0.02–2.0 mm particle size), silt

(0.002–0.02 mm) and clay (\0.002 mm) was 79.5–81.7 %,

5.1–7.0 % and 2.4–4.6 %, respectively, in both soils. The

content of organic matter was 11.3 % in Field WE and

8.8 % in Field NE (Table S2). The soil pH in Field WE

(6.0) was significantly lower than that in Field NE (6.8),

whereas the P, K and inorganic N contents were much

higher in Field WE compared to Field NE, i.e., 14.7, 15.3

and 57.1 versus 11.5, 10.9 and 38.4 mg 100 g-1 soil for P,

K and N, respectively (Table 1). The magnesium content

was 11.6 and 12.8 mg 100 g-1 soil in Fields WE and NE,

respectively (Table 1).

In both of the experimental fields, pH was stable during

the two growth seasons, although with a tendency to

decrease in Field NE (Table 1). The potassium levels were

on the other hand markedly reduced, up to 50 % in Field

WE and up to 40 % in Field NE (Table 1). The reduction

was most pronounced in the unfertilized treatments. Soil

Polar Biol

123

Ta

ble

1S

oil

pH

and

nu

trie

nt

lev

els

ina

wel

l-es

tab

lish

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ield

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da

new

lyes

tab

lish

ed(F

ield

NE

)fi

eld

sup

ple

men

ted

wit

hd

iffe

ren

tfe

rtil

izer

trea

tmen

ts;

NP

K,

NP

K-f

erti

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un

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man

ure

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shee

pm

anu

resu

pp

lem

ente

dw

ith

nit

rog

en

NP

KU

nfe

rtil

ized

Man

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.N

Sp

rin

g

20

10

Au

tum

n

20

10

Sp

rin

g

20

11

Au

tum

n

20

11

Sp

rin

g

20

10

Au

tum

n

20

10

Sp

rin

g

20

11

Au

tum

n

20

11

Sp

rin

g

20

10

Au

tum

n

20

10

Sp

rin

g

20

11

Au

tum

n

20

11

Fie

ldW

E

pH

6.0

±0

.25

.3±

0.1

5.5

±0

.15

.8±

0.2

6.0

±0

.25

.5±

0.1

5.6

±0

.15

.7±

0.1

6.0

±0

.25

.5±

0.1

5.8

±0

.15

.9±

0.1

P(m

g1

00

g-

1

soil

)

14

.7±

0.6

15

.0±

0.4

14

.0±

0.4

13

.3±

0.5

14

.7±

0.6

14

.0±

01

3.0

±0

12

.8±

0.3

14

.7±

0.6

15

.5±

0.3

13

.3±

0.5

13

.0±

0.4

K(m

g1

00

g-

1

soil

)

15

.3±

1.0

9.0

±0

.38

.8±

0.8

6.8

±0

.31

5.3

±1

.06

.9±

0.4

4.9

±0

.26

.5±

0.1

15

.3±

1.0

8.9

±0

.56

.6±

0.3

7.2

±0

.2

Mg

(mg

10

0g

-1

soil

)

11

.6±

1.0

10

.7±

0.8

9.4

±1

.08

.0±

1.1

11

.6±

1.0

10

.7±

0.5

8.9

±1

.29

.2±

1.0

11

.6±

1.0

14

.0±

0.6

12

.0±

0.8

11

.5±

0.6

To

tal

Na

(mg

kg

-1

soil

)

57

.1±

18

.84

0.0

±1

0.9

46

.6±

8.4

75

.7±

15

.35

7.1

±1

8.8

50

.7±

21

.36

1.3

±1

4.3

76

.2±

14

.25

7.1

±1

8.8

72

.3±

27

.97

1.8

±8

.89

8.0

±1

5.3

Fie

ldN

E

pH

6.8

±0

.16

.7±

0.2

6.6

±0

.16

.7±

0.1

6.8

±0

.16

.8±

0.1

6.8

±0

.16

.8±

06

.8±

0.1

6.7

±0

.16

.7±

06

.8±

0

P(m

g1

00

g-

1

soil

)

11

.5±

1.0

11

.5±

0.3

11

.5±

0.5

11

.75

±0

.31

1.5

±1

.01

1.0

±0

.61

0.0

±0

.41

1.0

±0

.41

1.5

±1

.01

0.5

±0

.99

.8±

0.8

10

.4±

0.7

K(m

g1

00

g-

1

soil

)

10

.9±

0.9

10

.1±

0.3

11

.5±

0.3

8.4

±0

.31

0.9

±0

.97

.1±

0.5

5.8

±0

.46

.3±

0.4

10

.9±

0.9

7.8

±0

.58

.3±

0.7

6.3

±0

.3

Mg

(mg

10

0g

-1

soil

)

12

.8±

1.6

13

.3±

1.0

14

.5±

1.4

13

.3±

1.1

12

.8±

1.6

11

.8±

1.3

11

.6±

1.1

11

.6±

1.2

12

.8±

1.6

11

.2±

1.9

11

.6±

1.5

10

.3±

0.9

To

tal

Na

(mg

kg

-1

soil

)

38

.4±

11

.94

7.5

±1

9.2

48

.7±

7.0

61

.5±

8.1

38

.4±

11

.93

1.6

±9

.84

2.4

±7

.15

9.2

±5

.13

8.4

±1

1.9

31

.4±

8.4

51

.8±

5.9

54

.2±

5.7

So

ils

wer

esa

mp

led

inM

ayb

efo

rese

edin

go

fp

ota

toes

and

inS

epte

mb

eraf

ter

po

tato

tub

erh

arv

est

in2

01

0an

d2

01

1.

Dat

aar

em

ean

±S

E(n

=4

)a

To

tal

ino

rgan

icn

itro

gen

Polar Biol

123

phosphorus did not change over the experimental period in

Field WE but showed a small decrease (up to 14 %) in

Field NE. The content of inorganic N was at all sampling

occasions up to 100 % higher in Field WE compared to

Field NE (Table 1). This difference between fields was

most pronounced in the manure.N treatment (Table 1).

The nutritional status of the potato plant shoots was

within the optimum range for all analyzed elements [Table

S3; see also (Reuter et al. 1997)]. In both fields, the fer-

tilizer treatments resulted in increased N-concentration of

the shoots with the highest values attained in the NPK-

treatment (Table S3). The P-concentration in the shoots

was up to 100 % higher in Field NE compared to Field WE

and was not further affected by the fertilizer treatments

(Table S3). The K-concentration in tubers ranged between

1.2 and 2 % and was not consistently affected by the fer-

tilizer treatments (Table S3).

The tuber yield in the growth season of 2011 was much

lower than the yield in 2010 (Table S4). This was due to

episodes of Foehn winds in August 2011, which damaged

the shoots of the potato plants. The tuber yields were

generally lower in Field NE compared to Field WE, values

ranging between 11.6 and 17.0 and 5.9 and 11.4 ton ha-1

compared to 7.4–11.1 and 5.3–9.8 ton ha-1 in 2010 and

2011, respectively. Application of NPK- and manure.N-

fertilizer increased yields in both fields (Table S4).

The fields were fully covered with acryl the entire

growth seasons. Mean soil and air temperatures during the

growth seasons were measured to 13.6 and 9.8 �C for 2010

and 12.6 and 7.8 �C for 2011, respectively (data not

shown). Maximum (max.) and minimum (min.) soil and air

temperatures for 2010 were 22.3 and 22.4 �C and 5.2 and

-2.3 �C, respectively, whereas maximum and minimum

soil and air temperatures for 2011 were 22 and 21.5 �C and

2.4 and -1.7, respectively (data not shown).

Bacterial phylogenetic structure and diversity

The microbial diversity in 43 independent soil samples was

determined by pyrosequencing of a 466-bp DNA amplicon

covering the V3 and V4 hypervariable regions of the 16S

rRNA gene. A total of 425,809 reads with an average

length of 392 bp were obtained after trimming and quality-

filtering (Table S5). Phylogenetic analysis was performed

using the QIIME pipeline (www.qiime.org) (Caporaso

et al. 2010). Chimeras and singletons were filtered from the

dataset before analysis, and operational taxonomic units

(OTUs) were clustered at 94 and 97 % identity, roughly

corresponding to genus and species level, respectively. The

resulting OTUs were classified using the Greengenes

database and taxonomy (DeSantis et al. 2006).

Rarefaction curves of pooled sequences for each soil

treatment showed comparable levels of richness, with the

lowest number of OTUs (97 % identity) observed with the

NPK-fertilizer treatment (Fig. S1). Similarly, average val-

ues after even subsampling (N = 11,769) for the number of

observed OTUs and the Chao 1 and Shannon richness

estimators revealed only minor differences between fertil-

izer treatment, field and sampling time (Table 2). A sta-

tistically significant difference (p B 0.05), however, was

detected between the September 2010 (S10) and August

2011 (AU11) samples, with the latter showing both a lower

number of OTUs and Chao 1 estimate. Analysis of a

combined dataset of 241,170 sequences identified 83,629

OTUs and gave a Chao 1 estimate of 194,398, suggesting

that the Greenlandic soils harbor a very diverse microbial

community (Table S6).

An analysis of the distribution of the most abundant

OTUs (clustered at 94 % identity and represented by at

least 5 sequences in the combined dataset) between the

three treatments revealed that the majority of OTUs were

shared, with 69.1 % of the OTUs being present in all three

treatments. This corresponded to 90.8 % of all sequences

(Fig. S2), indicating that the unique OTUs are primarily

low-abundance OTUs. Indeed, the 500 OTUs (4.3 %)

present in only one treatment were represented by\1 % of

the sequences. The number of shared OTUs between the

two fields was slightly lower, with 56.2 % of the OTUs,

corresponding to 77.8 % of all sequences, present in both

fields (Fig. S2). A similar analysis using a minimum of 20

sequences for each OTU (2,198 OTUs) increased the per-

centage of shared OTUs to 98.7 and 80.0 % for the treat-

ments and fields, respectively (data not shown).

Table 2 Number of observed OTUs and Chao 1 and Shannon

diversity indices as richness estimators

Sample OTUs Chao 1 Shannon

N 11,769

Unfertilized 6,941 (±529) 23,981 (±2,907) 12.07 (±0.21)

NPK 6,431 (±773) 21,979 (±3,791) 11.78 (±0.40)

Manure.N 7,125 (±603) 25,846 (±3,150) 12.15 (±0.25)

Field WE 6,497 (±708) 22,581 (±3,931) 11.81 (±0.32)

Field NE 7,199 (±437) 25,303 (±2,499) 12.21 (±0.17)

May 2010 7,407 (±88) 25,803 (±1,715) 12.23 (±0.11)

Sept. 2010 7,211 (±497) 26,026 (±2,732) 12.15 (±0.25)

Aug. 2011 6,299 (±554) 21,238 (±2,895) 11.79 (±0.31)

Averaged values (±SD) based on treatment, unfertilized, NPK, sheep

manure supplemented with nitrogen (manure.N); location, well-

established field (Field WE) and newly established field (Field NE);

and sample date May 2010, September 2010 and August 2011. OTUs

were clustered at 97 % identity, and all samples were subsampled to

an even number of sequences (N) before each comparison

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The community structure of individual samples was

compared by principal coordinate analysis (PCoA) of beta

diversity calculated using the weighted UniFrac metric

after even subsampling. A plot of the most significant

coordinates revealed a clear separation between samples

based on the field and the time of sampling, with the largest

variation observed between the two fields (PC1, Fig. 2a).

The fertilizer treatments, on the other hand, did not appear

to have any major effect on the overall community struc-

ture (Fig. 2).

Microbial phylogeny

The taxonomy of the OTUs clustered at 94 % identity was

assigned using the RDP classifier and the latest release of

the Greengenes 16S rDNA database. The most abundant

phyla in all samples were Proteobacteria, Actinobacteria

and Acidobacteria, followed by varying occurrences of

Gemmatimonadetes, Bacteroides, Chloroflexi and Ver-

rucomicrobia (Fig. 3, Table S7). Compared to Field WE,

the relative abundances of bacterial phyla were more

Field WE

Field NEMay 2010

Sept. 2010

Aug. 2011

a b

Fig. 2 Principal coordinate analysis (PCoA) plots of beta diversity

calculated using the weighted UniFrac metric. Individual biological

replicates are plotted by three components, showing separation by

location; Field NE, newly established field and Field WE, well-

established field (PC1 and PC2, a) and time; May 2010, September

2010 and August 2011 (PC3 and PC2, b). The % variation explained

is given in parenthesis. Squares unfertilized, triangles NPK-fertilizer,

diamonds manure.N. All samples were subsampled to 3,052

sequences before analysis

Fig. 3 Distribution of the most

abundant bacterial phyla for

each sample point. Means of

biological replicates ± standard

error are given. Samples are

named by location, treatment

and time. NE newly established

field, WE well-established field,

U unfertilized, NPK NPK-

fertilizer; manure.N, sheep

manure supplemented with

nitrogen; M10, May 2010; S10,

September 2010; AU11, August

2011

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consistent between samples taken from Field NE (Fig. 3).

The abundance of Archaea was very low in all soil sam-

ples, showing an average occurrence of 0.13 % (data not

shown).

Among the most abundant classes were the Alpha-,

Beta-, Gamma- and Deltaproteobacteria, Actinobacteria,

Acidimicrobiia, Acidobacteria, Gemmatimonadetes and

Sphingobacteriia (Table S7). As suggested by the com-

munity structure analysis (see above), an examination of

the relative abundances of phyla, classes and orders pri-

marily revealed differences between the two fields. In

particular, the abundance of Alphaproteobacteria, order

Rhizobiales, was significantly (p B 0.05) higher in Field

NE, as were the Actinobacteria, order Actinomycetales, and

Acidimicrobiia, order Acidimicrobiales. The largest dif-

ferences were observed in the phylum Acidobacteria,

where the orders Acidobacteriales and Solibacterales were

approximately twelve- and fourfold more abundant,

respectively, in Field WE, and the class Acidobacteria-6

was decreased more than eightfold (Table S7). Significant

differences between the two fields were also detected for

several other less abundant phyla, classes and orders (Table

S7, data not shown). With respect to fertilizer treatment,

only minor differences were observed. Fertilization sig-

nificantly increased the abundance of Gammaproteobac-

teria, order Xanthomonadales, in Field WE from 3.9 % in

unfertilized soil to 7.5 and 7.8 % in NPK- and manure.N-

treated soils, respectively, whereas the Deltaproteobacte-

ria, order Myxococcales, was decreased twofold by NPK

treatment in the same field (p B 0.05, Table S7). The time

of sampling also had an overall effect on the microbial

community, with the major differences being a decrease in

the abundance of Proteobacteria (primarily the Alpha and

Delta classes) from 47.1 % in May 2010 (M10) to 33.4 %

in S10 and 28.9 % in AU11 and an associated increase in

the phyla Gemmatimonadetes, Verrucomicrobia, TM7 and

Planctomycetes from a total of 2.2 % in M10 to 11.0 % in

S10 and 12.1 % in AU11 (Fig. 3, data not shown). Other

significant changes included a decrease in the order Acti-

nomycetales from 15.2 % in S10 to 9.3 % in AU11 and a

decrease in the order Sphingobacteriales from 4.2 % in

M10 to 2.4 % in S10 followed by an increase to 7.4 % in

AU11 (data not shown).

Among the 20 most abundant OTUs in the combined

dataset were representatives from the phyla Proteobacte-

ria, Actinobacteria, Acidobacteria, Gemmatimonadetes

and Bacteroidetes, and these OTUs made up 7.5, 10, and

8.3 % of all sequences from the unfertilized-, NPK- and

manure.N-treated soils, respectively (Table S8). Since

taxonomy could not be reliably assigned to the genus level

for the majority of these OTUs, the sequences were man-

ually inspected using the SILVA Incremental Aligner

(SINA, www.arb-silva.de/aligner), and the best match to

the Greengenes or SILVA taxonomy was recorded. Inter-

estingly, one of the OTUs was 100 % identical to multiple

sequences from the genus Pseudomonas, which contains

known biocontrol agents (BCAs) (data not shown).

Further examination of the overall taxonomy of the

combined dataset identified several families and genera

known to be involved in disease suppressiveness of soils

(so-called BCAs) (Table 3). The abundances of known

BCA genera were generally low, though this is likely, at

least in part, to be a consequence of the difficulty in reli-

ably assigning taxonomy to the genus level. At the family

level, the Pseudomonadaceae, containing the Pseudomo-

nas OTU mentioned above, was the most abundant BCA

family in Field NE with 0.58 % of the sequences. The most

abundant BCA family in Field WE was the Microbacteri-

aceae (0.52 %), which was also frequently observed in

Field NE (data not shown). Other potential BCAs include

members of the genera Bacillus, Paenibacillus, Strepto-

myces and Burkholderia, all of which were detected in both

fields (Table 3).

Discussion

Soil amendment with fertilizers can improve plant growth

and health by, e.g., increasing soil nutrient status or by

modifying the structure and/or biological activity of soil

microbial communities (Haynes and Naidu 1998; Espers-

chutz et al. 2007). In addition, due to global warming,

Arctic and Subarctic ecosystems are expected in the nearest

future to be exposed to severe environmental stresses, such

as an increased deposition of reactive nitrogen, which may

Table 3 OTU counts and abundance of detected potential bacterial

biocontrol agents, given in % of all sequences from each field

Family/genus %

Pseudomonadaceae 3.342

Pseudomonas 0.070

Bacillaceae 0.156

Bacillus 0.014

Paenibacillaceae 0.391

Paenibacillus 0.221

Streptomycetaceae 2.713

Streptomyces 0.735

Burkholderiaceae 0.644

Burkholderia 0.111

Microbacteriaceae 5.333

Microbacterium 0.105

Micromonosporaceae 2.742

Actinoplanes 0.306

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123

cause rapid changes in microbial community structures and

functions (Campbell et al. 2010). In the present study, two

Greenlandic agricultural soils, a well-established field

(Field WE) and a newly established field (Field NE), were

investigated for the short-term effect of fertilization on

bacterial diversity, soil nutrient availability and crop per-

formance. The texture of the investigated soils was sandy

with a higher content of organic matter in Field WE

compared to Field NE. The pH and nutrient levels in the

two fields differed significantly, Field WE having lower

soil pH and much higher N, P and K levels than Field NE.

The differences in nutrient levels between the two fields

can be explained by the many years of cultivation and

fertilizer application in Field WE, resulting in an increased

return of organic material to the soil, i.e., via decaying

plant parts and causing accumulation of nutrients in the top

soil layer (Haynes and Naidu 1998). In contrast, Field NE

had for many years been a permanent grassland and was

cultivated just prior to these experiments. In general, the

sub- and low Arctic soils in Greenland are developed from

acidic rocks, i.e., granite, gneiss and sandstone from the

mountains, and characterized as acidic, and low in nutrient

levels and plant accessible nutrients (Rutherford 1995).

However, the nutrient levels in these soil samples indicated

well-fertilized soils. This relatively high content of nutri-

ents may be related to the fact that both fields were

localized at the bottom of a small slope and may have been

enriched by downwards transport of nutrient-rich small

particles.

The fertilizer treatments significantly affected the

nutrient status of the soil and the potato crop in both fields

and also increased tuber yield. Tuber yields were lower in

Field NE compared to Field WE, and in both fields, the

tuber yield increased significantly upon fertilization. The

yield response was roughly similar for the NPK- and

manure.N-treated soils, indicating that the use of manure.N

in these Greenlandic soils may maintain the same level of

yield as can be obtained with traditional NPK-fertilizer.

The N-concentration in shoots and tubers of plants

receiving NPK was higher compared to those in the

manure.N-treatment, reflecting the more immediate avail-

ability of the mineral N. There were no effects of fertil-

ization on the phosphorus concentration in the plants

indicating that the amount of phosphorus in the soil was

already sufficiently high. However, the potassium levels

were markedly affected by the fertilizer treatments, and the

response also differed between the fields. Amendment with

manure.N or NPK increased the plant potassium concen-

tration in both fields, but the concentration was lower in

Field NE receiving manure.N, suggesting that part of the

added potassium became bound in the soil and was not

available for plant uptake. The potato tubers did not show

any necrotic spots. However, the potassium concentration

in the tubers was relatively low, indicating risks for

development of blackspot disease if handling and storage is

not carried out properly (McGarry et al. 1996).

The different fertilizer treatments did not affect the

overall microbial community composition in the Green-

landic soils investigated in this study. Bacteria from the

phyla Proteobacteria, Actinobacteria and Acidobacteria

were the most abundant in all treatments, which is con-

sistent with other microbial community studies of Arctic

soils (Campbell et al. 2010; Chu et al. 2010), whereas the

Gemmatimonadetes, Bacteroides, Chloroflexi and Ver-

rucomicrobia varied in frequency among the samples.

However, small changes in the abundance of different

bacterial phyla were observed between the two fields,

between sampling times and to a minor extent between the

different fertilizer treatments. During the 2-year Green-

landic field trial, a significant decrease in the abundance of

Proteobacteria could be found in both fields between soil

sampled in May 2010 and soil sampled in September 2010

and August 2011. In addition, Field WE showed a higher

abundance of Acidobacteria and a lower abundance of

Actinobacteria compared to Field NE that prior to experi-

ments was a soil with non-disturbed grass cover. This result

is in accordance with a previous study, which showed that

Actinobacteria were more abundant in soils with non-dis-

turbed grass cover compared to agricultural soils (Acosta-

Martinez et al. 2008). The higher abundance of Actino-

bacteria in Field NE compared to Field WE could also be

due to differences in pH levels between the two soils. Soil

pH levels have in other studies showed to play an important

role in shaping bacterial community structures (Lauber

et al. 2009; Chu et al. 2010; Nacke et al. 2011; Li et al.

2012), and increased relative abundance of Actinobacteria

has been associated with elevated pH levels (Nacke et al.

2011).

Only minor differences could be observed between the

different fertilizer treatments, where the relative abundance

of Gammaproteobacteria increased significantly in Field

WE in soils treated with NPK and manure.N compared to

the unfertilized soil. Furthermore, a decrease in the abun-

dance of Deltaproteobacteria was found within the same

field in the NPK-treated soil. Similar to the results in this

study, no major changes in the microbial diversity between

different fertilizer treatments were found in a recent study

by Poulsen et al. (2013), in which soils were treated with

different urban fertilizers as well as NPK. However, minor

differences in the relative abundance on phylum level were

observed. For example, the abundance of Actinobacteria

was higher in soils treated with cattle manure than in soils

treated with NPK-fertilizer (Poulsen et al. 2013). Further-

more, inorganic N has previously been associated with

changes in soil bacterial communities where the abundance

of Actinobacteria increased in soils treated with N

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123

(Ramirez et al. 2010). In this study, no significant differ-

ences were observed in the relative abundance of Actino-

bacteria among the different fertilizer treatments; however,

further studies would reveal if this is also the case in the

long term.

The occurrence of bacterial taxa that previously have

been found associated with disease suppressiveness of soils

(so-called BCAs) was investigated in the two Greenlandic

soils, since no severe disease incidences of potatoes have

been detected. These bacterial groups include the genera

Pseudomonas, Bacillus, Burkholderia and from the acti-

nomycetes order (e.g., Streptomyces) (van Bruggen and

Semenov 2000; Mendes et al. 2011). Previous studies have

shown that BCAs belonging to the genera Burkholderia,

Stenotrophomonas and Pseudomonas genera were more

abundant in organic farming compared to conventional

farming systems and could be a response of differences in

organic carbon and nitrogen availability in the soils (van

Bruggen and Semenov 2000; Li et al. 2012). In the

Greenlandic potato soils investigated, bacteria from all the

above-mentioned genera were found, with Streptomyces

being the most abundant. We have previously isolated

BCAs affiliated to the genus Pseudomonas from a Green-

landic potato soil, which inhibits various plant pathogenic

fungi by producing several antifungal compounds (Mi-

chelsen and Stougaard 2011, 2012). Whether or not the

bacterial genera identified in this study contribute to the

low disease incidences in the Greenlandic fields remains to

be determined.

This is the first report describing the short-term impact

of conventional and organic fertilizer treatments on soil

and plant nutrient levels, crop yield and bacterial diversity

in Greenlandic agricultural soils. Changes in soil and plant

nutrient levels as well as crop yields were observed for the

different treatments and between the soils in the two fields,

a well-established field and a newly established field. No

major differences were observed on the overall bacterial

community compositions; however, changes in the relative

abundances of specific bacterial phyla were found

depending on fertilizer treatments, the field site and sam-

pling times. Bacterial genera comprising potential BCAs

were also found in the soils. Because Arctic soils in par-

ticular will be exposed to environmental stresses in the

future due to global warming, studies of the long-term

impact of fertilization on soil, plants and soil microbial

community composition would be important for future

agricultural efforts in the Arctic regions.

Acknowledgments We acknowledge the excellent assistance of the

former chief gardener Anders Iversen for support during sampling of

material and research at the experimental research farm in Upernav-

iarssuk, Greenland. We also acknowledge Ditte Elsborg MSc., for

help with collecting soil samples and preparation of pyrosequencing

samples. Referring to the convention on Biological Diversity, we

thank the Government of Greenland for permission to sample bacteria

in south Greenland. This work was funded in part by the Commission

for Scientific Research in Greenland.

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