Size and structure of bacterial, fungal and nematode communities along an Antarctic environmental gradient
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
Size and structure of bacterial, fungal and nematode communities
along an Antarctic environmental gradient
Etienne Yergeau1, Stef Bokhorst2, Ad H.L. Huiskes2, Henricus T.S. Boschker2, Rien Aerts3 &
George A. Kowalchuk1,3
1
Netherlands Institute of Ecology, Centre for Terrestrial Ecology (NIOO-KNAW), Heteren, The Netherlands; 2Netherlands Institute of Ecology, Centre for
Marine and Estuarine Ecology (NIOO-KNAW), Yerseke, The Netherlands; and 3Institute of Ecological Science, Vrije Universiteit, Amsterdam, The
Netherlands
Correspondence: George A. Kowalchuk, Abstract
Netherlands Institute of Ecology, Centre for
Terrestrial Ecology (NIOO-KNAW), P.O. Box
The unusually harsh environmental conditions of terrestrial Antarctic habitats
40, 6666 ZG, Heteren, The Netherlands. Tel.: result in ecosystems with simplified trophic structures, where microbial processes
131 026 479 1314; fax: 131 026 472 3227; are especially dominant as drivers of soil-borne nutrient cycling. We examined
e-mail: g.kowalchuk@nioo.knaw.nl soil-borne Antarctic communities (bacteria, fungi and nematodes) at five locations
along a southern latitudinal gradient from the Falkland Islands (511S) to the base
Received 2 June 2006; revised 19 July 2006; of the Antarctic Peninsula (721S), and compared principally vegetated vs. fell-field
accepted 21 July 2006. locations at three of these sites. Results of molecular (denaturing gradient gel
First published online 18 September 2006.
electrophoresis, real-time PCR), biochemical (ergosterol, phospholipid fatty acids)
and traditional microbiological (temperature- and medium-related CFU) analyses
DOI:10.1111/j.1574-6941.2006.00200.x
were related to key soil and environmental properties. Microbial abundance
Editor: Max Häggblom
generally showed a significant positive relationship with vegetation and vegeta-
tion-associated soil factors (e.g. water content, organic C, total N). Microbial
Keywords community structure was mainly related to latitude or location and latitude-
Antarctica; PCR-DGGE; real-time PCR; bacterial dependent factors (e.g. mean temperature, NO3, pH). Furthermore, strong
communities; fungal communities; nematodes interactions between vegetation cover and location were observed, with the effects
communities. of vegetation cover being most pronounced in more extreme sites. These results
provide insight into the main drivers of microbial community size and structure
across a range of terrestrial Antarctic and sub-Antarctic habitats, potentially
serving as a useful baseline to study the impact of predicted global warming on
these unique and pristine ecosystems.
Although some complex trophic interactions have been
Introduction identified in terrestrial Antarctic environments (Newsham
Many factors are unfavorable to the majority of terrestrial et al., 2004), their less complex food-web structure provides
life-forms in Antarctic regions, such as low thermal capacity a relatively simplified system in which to disentangle the
of the substratum, frequent freeze–thaw and wet–dry cycles, drivers and consequences of soil microbial activities.
low and transient precipitation, low humidity, rapid drai- The Antarctic Peninsula is the most rapidly warming
nage, and limited organic nutrients (Wynn-Williams, 1990). region in the world (Houghton et al., 2001). Predicted
These generally adverse conditions support relatively simple global warming will lead to longer growing seasons across
ecosystems with a noted reduction in the complexity of food this region, and extended plant distributions are anticipated
webs, with highly simplified food web structures in the most (Frenot et al., 2005; Convey & Smith, 2006). Climate
extreme Antarctic habitats (Wall & Virginia, 1999). Anne- warming will not only affect Antarctic ecosystems directly,
lids, mollusks, winged insects and mammals are effectively but associated changes in precipitation patterns and in-
absent from these systems, and only two vascular plant creased water availability due to melting are thought to be of
species have been found to inhabit Antarctic terrestrial perhaps even greater significance. Consequently, it has been
environments (Davis, 1981). Consequently, most of these hypothesized that direct temperature effects on soil-borne
soil environments are devoid of the root systems of vascular microorganisms will be less important than indirect effects,
plants and larger animals which cause bioturbation. such as changes in vegetation density and other associated
c 2006 Federation of European Microbiological Societies FEMS Microbiol Ecol 59 (2007) 436–451
Published by Blackwell Publishing Ltd. All rights reservedMicrobial ecology in Antarctic soils 437
soil biophysical properties (Vishniac, 1993). Indeed, studies of terrestrial invertebrates suggest distinct biogeo-
although decreases in bacterial abundances have been ob- graphical regions within the Antarctic, although debate
served with increased latitude in terrestrial Antarctic sys- exists as to whether these adhere to the sub-Antarctic,
tems, this is thought to be related to a concomitant decrease maritime Antarctic and continental Antarctic regions deli-
in vegetation density (thus carbon and inorganic nutrients) neated for vegetation patterns (Smith, 1984) or follow a
rather than to climate per se or latitude (Vishniac, 1993). discontinuity between the Antarctic Peninsula and conti-
Although little is known about the structure and function nental Antarctica, along the newly coined ‘Gressitt Line’
of terrestrial microbial communities in southern polar (Chown & Convey, 2006). Despite the interest in soil
regions, a number of important preliminary investigations microfauna, the relative importance of this group with
have begun to shed some light on the ecology of these respect to heterotrophic respiration appears relatively low.
systems. For instance, it has been observed that culturable One study of relative respiration rates of soil organisms on
fungal communities are more diverse and more abundant in Signy Island revealed that 81–89% of heterotrophic respira-
sub-Antarctic islands, where the climate is more humid and tion could be attributed to bacteria and fungi, with a
temperate, as compared to Antarctica proper (Smith, 1994; remaining 10–19% due to protozoan activity. Rotifers,
Azmi & Seppelt, 1998). Organic matter, soil water content, tardigrades, nematodes, acari and collembola only ac-
pH and total nitrogen have also been shown to be correlated counted for 0.42–0.48% of total respiration (Davis, 1981).
with fungal abundance on the sub-Antarctic Signy Island Nevertheless, soil microfauna may provide important clues
(Bailey & Wynn-Williams, 1982). Also, several studies have into trophic interactions in Antarctic systems (Newsham
reported that Antarctic fungal communities are dominated et al., 2004) and may represent key indicators of change
by cold-tolerant, as opposed to cold-adapted, fungi, suggest- within such habitats.
ing that the superior tolerance of some fungal populations to The low number of recent studies about Antarctic soil
the harsh habitats results in distinct Antarctic fungal assem- ecosystems has hampered any attempts to predict or observe
blages (Kerry, 1990; Melick et al., 1994; Zucconi et al., 1996; the possible effects of the rapid and ongoing warming of this
Robinson, 2001). Interestingly, a recent molecular survey region. The main goal of this study is to provide an in-depth
targeting all eukaryotes reported no decrease in diversity assessment of soil-borne microbial communities across a
along a southern latitudinal gradient, but did discriminate range of Antarctic and sub-Antarctic terrestrial habitats. We
between continental vs. maritime sites, with the former further attempt to examine data on microbial abundance
harboring lower eukaryotic diversity (Lawley et al., 2004). and community structure in relation to key various envir-
Few detailed studies exist to date that provide in depth onmental factors to gain insight into the factors driving
descriptions of bacterial communities in Antarctic soils. Never- microbial communities in these unique environments.
theless, it has been observed that bacterial counts, activity and
community structure are related to soil type, nitrogen content,
water abundance and type of plant cover (Christie, 1987;
Materials and methods
Tearle, 1987; Bölter, 1995; Bölter et al., 1997; Harris & Tibbles,
Sampling sites
1997). Similarly, microbial activity was found to be controlled
by not only short-term patterns of temperature and moisture, During the austral summer of 2003–2004, 2 2 m plots
but also by the availability of organic matter and the supply of were established at the following sites (see Fig. 1 for a map):
soluble carbohydrates and amino acids, but not N and P Falklands Islands (cool temperate zone; 511S 591W), Signy
(Christie, 1987; Bölter, 1992). In contrast, another study found Island (South Orkney Islands, maritime Antarctic; 60143 0 S
no relationship between moisture, soil particle size, salinity, pH 45138 0 W) and Anchorage Island (near Rothera research
and number of bacteria (Line, 1988). In one of the few station, Antarctic Peninsula; 67134 0 S 68108 0 W). At each
molecular surveys of bacterial diversity in Antarctic terrestrial location, two types of vegetation selected for sampling: (1)
environments, it was recently reported that the extremely harsh ‘vegetated’, where dense vegetation cover was present with
environments of three different Antarctic cold desert mineral retention of underlying soil; and (2) ‘fell-field’, represented
soils contained bacterial communities of relatively low diver- as rocky or gravel terrain with scarce vegetation or crypto-
sity, with a high proportion of novel, potentially psychro- gam coverage. For the Falkland Islands, vegetated sites
trophic taxa (Smith et al., 2006). exhibited a dwarf shrub vegetation (Empetrum rubrum Vahl
A number of studies have examined microfaunal diversity ex Willd.), and the fell-field site was rocky with sporadic
and distribution in Antarctic soils, revealing a patchy grasses (Festuca magellanica Lam. and Poa annua L.). For
distribution of nematodes, collembola, acari, rotifers and the locations in the (maritime) Antarctic, vegetated sites
tardigrades, hypothesized to follow patterns of vegetation, were dominated by mosses (Chorisodontium aciphyllum
moisture retention or bird activity (Tilbrook, 1967; Spaull, Hook. F. & Wils on Signy Island and Sanionia uncinata
1973; Bölter et al., 1997; Sohlenius & Boström, 2005). Such Hedw. on Anchorage Island), and fell-field sites contained
FEMS Microbiol Ecol 59 (2007) 436–451
c2006 Federation of European Microbiological Societies
Published by Blackwell Publishing Ltd. All rights reserved438 E. Yergeau et al.
Fig. 1. Map of Antarctic Peninsula region highlighting the locations of study sites.
lichen cover (principally Usnea antarctica Du Rietz). Twelve serted in the plots 5 cm above the ground, at the soil surface
plots were delineated per location with half of the plots and 5 cm below the soil surface. Soil moisture content was
positioned over each vegetation type. The Falkland Islands measured with a Water Content Reflectometer (CS616,
fell-field vegetation was not large enough to allow for such a Campbell Scientific, Shepshed, UK) to a depth of 30 cm.
design and nine of the 12 plots were therefore placed in the Each of these sensors recorded every hour for the duration of
dwarf shrub vegetation. Two additional sites were chosen for the study, with data being stored using a data logger (CR10X
sampling, but without delineation of permanent plots. Six frost with a storage module of 16 Mb from Campbell Scientific).
polygons at two different sites were sampled near the Fossil Soil microclimatic data retrieved from the automated weath-
Bluff (711190 S 68118 0 W) fuel depot, and five frost polygons er stations were averaged over the whole year.
were sampled from Coal Nunatak (72103 0 S 68131 0 W).
Soil samples
Environmental data collection
For molecular and cultivation analyses, five 1-cm diameter
Automated weather stations and precipitation gauges (from 2 to 3 cm to up to 15 cm deep) cores were sampled
(PLUVIO, OTT Hydrometrie, Hoofddrop, The Netherlands) from each plot or polygon. They were frozen to 20 1C as
were installed at the first three study locations. Temperature soon as possible (within 24 h) and maintained at that
probes (copper/constantan thermocouple wires) were in- temperature until use. For soil analyses, one 10-cm diameter
c 2006 Federation of European Microbiological Societies FEMS Microbiol Ecol 59 (2007) 436–451
Published by Blackwell Publishing Ltd. All rights reservedMicrobial ecology in Antarctic soils 439
core was taken directly adjacent to the plots in order to and 20 1C). Colonies were counted after 9 or 17s day of
minimize destructive sampling in the long term plots. incubation, depending on the type of medium and the
Sampling took place on October 26–28, 2004 for the Falk- incubation temperature.
land Islands, on January 2–3, 2005 for the Signy Island, on
January 18–19, 2005 for Anchorage Island and on February
Nucleic acid extractions
22–23, 2005 for Coal Nunatak and Fossil Bluff.
Soil DNA was extracted using the following protocol. Five
hundred milligrams of soil was mixed with 250 mg of 0.1
Soil biochemical and physical analyses
and 0.5 mm (1 : 1) zirconia–silica beads, 500 mL of phenol–
Soil analyses were carried out using standard protocols chloroform–isoamyl alcohol (25 : 24 : 1; Tris saturated, pH
(Carter, 1993). Because this study represents the first char- 8.0) and 500 mL of extraction buffer (12.2 mM KH2PO4,
acterization of these habitats, we assessed a wide range of soil 112.8 mM K2HPO4, 5% w/v CTAB, 0.35 M NaCl; pH 8.0).
parameters to allow full correlative comparison with measures Soils were then bead-beaten for 30 s at 50 m s1, and
of soil-borne community size and structure. phospholipid centrifuged at 10 000 g for 5 min at 4 1C. The supernatant
fatty acids (PLFA) analyses were carried out as outlined in was mixed with 500 mL of chloroform–isoamyl alcohol
Boschker (2004), using 1 g (Falkland, Signy, and Anchorage (24 : 1) and centrifuged again at 10 000 g for 5 min at 4 1C.
Islands) or 8 g (Fossil Bluff and Coal Nunatak) of soil (wet The supernatant was then precipitated at room temperature
weight). i14:0, i15:0, a15:0, i16:0, C16:1o7t, i17:1o7, for 2 h with two volumes of a 30% w/v PEG 6000 and 1.6 M
10Me16:0, br17:0, a17:1o7, i17:0, a17:0, C17:1o8c, C17:1o6/7, NaCl solution. The precipitated nucleic acids were then
cy17:0, 10Me17:0, C18:1o7c, 10Me18:0, cy19:0 PLFAs were pelleted by centrifugation at 10 000 g for 10 min at 4 1C.
used for determining bacterial biomass while C18:2o6c was The nucleic acids pellets were then washed with 70%
used to estimate fungal biomass. The whole peaks data set alcohol, dried, resuspended in 50 mL of deionized water and
(except control peaks) was used for microbial community stored at 20 1C until use.
structure analyses (Table S1).
PCR-denaturing gradient gel electrophoresis
CFU counts analyses
Soil subsamples originating from the same plot were pooled Table 1 summarizes the primers, thermocycling regimes and
together and diluted in a basic salt solution (1% KH2PO4 electrophoresis conditions used to analyze the different
and 5% NaCl). Two fungal and two bacterial media were target communities examined in this study. All PCRs were
chosen: 1/10 strength potato dextrose agar (PDA) with carried out in 25-mL volumes containing 2.5 mL of 10x PCR
100 mg L1 of filter sterile streptomycin sulphate (for general buffer, 2.5 mL of bovine serum albumin (BSA; 4 mg mL1),
fungi), water agar (WA) with 100 mg L1 of filter sterile 0.75 mL of each primer (30 mM), 2.5 mL of dNTPs mix
streptomycin sulphate (for oligotrophic fungi), 1/10 (8 mM), and 1.4 U of Expand high fidelity polymerase
strength tryptic soy agar (TSA) with 50 mg L1 of filter (Roche, Mannheim, Germany). All amplifications were
sterile cycloheximide (for general bacteria), and water yeast carried out on a PTC-200 thermal cycler (MJ-Research,
agar (WYA) with 50 mg L1 of filter sterile cycloheximide Waltham, MA). All thermocylcing programs were preceded
(for oligotrophic bacteria). Following preliminary tests, by an initial denaturation step (95 1C for 5 min) and
fungal media were inoculated with 102 soil dilution and followed by a final elongation step phase (72 1C for
bacterial media with 103 soil dilution (101 is 1 g soil plus 10 min). For each cycle of PCR, denaturation was at 95 1C
9 mL basic salt solution). Inoculated agar plates were for 1 min, annealing at the specified temperature (Table 1)
incubated in the dark at three different temperatures (4, 12 for 1 min and elongation at 72 1C for 1 min. Touchdown
Table 1. Primers, PCR and denaturing gradient gel electrophoresis (DGGE) conditions used in this paper
Community Primers PCR protocol DGGE gradientsw Reference
Bacteria 968-gc/1378 Touchdown 65–55 1C; 35 cycles 45–65% denaturant Heuer et al. (1997)
Cyanobacteria pA/1492r followed by 1st: 55 1C; 25 cycles; 2nd: 20–60% denaturant Edwards et al. (1989);
CYA359F-gc/CYA781R 60 1C; 35 cycles Nübel et al. (1997)
Fungi FR1-gc/FF390 Touchdown 55–47 1C; 37 cycles 40–55% denaturant Vainio & Hantula (2000)
Nematodes NEMF1-gc/ NEM896r 53 1C; 40 cycles 25–50% denaturant Waite et al. (2003)
PCR protocols are given as: annealing temperature; number of cycles. The remaining parts of the procedure are given in the text.
w
100% denaturant is defined as 40% (v/v) formamide and 7 M urea.
FEMS Microbiol Ecol 59 (2007) 436–451
c2006 Federation of European Microbiological Societies
Published by Blackwell Publishing Ltd. All rights reserved440 E. Yergeau et al.
protocols started with the highest annealing temperature, ciences, Roosendaal, the Netherlands). The resulting binary
which was subsequently lowered by 2 1C for each two cycles matrices were exported and used in statistical analyses as
until the target annealing temperature was reached. Denatur- ‘species’ presence–absence matrices. To test and have a
ing gradient gel electrophoreses (DGGEs) were carried using graphical representation of the influences of environmental
a D-Code Universal Mutation Detection System (Bio-Rad, and soil variables on the microbial population structure,
Hercules, CA). All gradient gels were topped with 10 mL of canonical correspondence analyses (CCAs) were carried in
acrylamide containing no denaturant and electrophoresis Canoco 4.5 for windows (ter Braak & Šmilauer, 2002).
was carried at 60 1C and 200 V for 10 min followed by an Location and vegetation cover were treated as ‘supplemen-
additional 16 h at 70 V. Gels were stained in ethidium tary’ variables while soil and environmental data were
bromide and digital images captured using an Imago appa- included in the analysis as ‘environmental’ variables. Rare
ratus (Gentaur, Brussels, Belgium) subsequent to UV tran- species were taken out of the analyses following an empirical
sillumination. Banding patterns were normalized with method described by D. Borcard (http://biol10.biol.umon-
respect to standards of known composition as well as treal.ca/BIO6077/outliers.html). Variables to be included in
samples loaded across multiple gels. The validity of intergel the model were chosen by forward selection at a 0.05 base-
comparisons was tested by examining the grouping of like line. Using only the chosen variables, the significance of each
samples run across multiple gels, which revealed tight group- whole canonical model was tested with 999 permutations.
ing of replicates and grouping according to gel (not shown). The effects of location, presence of vegetation and the
interaction of these two factors on the community structure
Real-time PCR as analyzed by PCR-DGGE and PLFA were tested by
distance-based redundancy analyses (db-RDA, Legendre &
Real-time PCR was performed using the ABsolute QPCR
Anderson, 1999). Jaccard’s coefficient of similarity (DGGE)
SYBR green mix (AbGene, Epsom, UK) on a Rotor-Gene
or Bray–Curtis distance (PLFA) were first calculated be-
3000 (Corbett Research, Sydney, Australia). All mixes were
tween samples. The use of Jaccard’s coefficient is recom-
made using a CAS-1200 pipetting robot (Corbett Research,
mended for binary species data, such as DGGE patterns
Sydney, Australia) to reduce variation caused by pipetting
scored for presence vs. absence, whereas Bray–Curtis is the
errors. Quantification of fungal and bacterial ribosomal
distance of choice for species abundance data, such as PLFA
genes in soil were carried as described elsewhere (Lueders
patterns (Legendre & Legendre, 1998). The resulting simi-
et al., 2004a, b). For nematodes, the exact same amplification
larity/distance matrices were then used for the computing
protocol was used as for PCR-DGGE analyses except that the
of principal coordinates in the R package (Casgrain &
ABsolute QPCR SYBR green mix was substituted for the
Legendre, 2001). When necessary, eigenvectors were cor-
normal PCR mix. Standards were made from full-length
rected for negative eigenvalues using the procedure of
PCR-amplified 18S rRNA or 16S rRNA genes from pure
Lingoes (1971) and were then exported to Canoco as
fungal and bacterial isolates. To make the nematode stan-
‘species data’ for redundancy analyses (RDA). To test the
dard, extracted soil DNA was PCR-amplified and cloned.
effects of each of the two variables (vegetation and location),
One resulting clone that contained a proper insert of
each was recoded using dummy binary-variables and one
nematode origin was randomly chosen and used in a colony
was used in Canoco as the only environmental variable in
PCR procedure using plasmidic primers. PCR-amplified
the model while the other variable was entered as a covari-
partial or full-length ribosomal genes of bacteria, fungi and
able. To test the interaction, the only variable entered in the
nematodes were purified, quantified on a ND-1000 spectro-
model was the interaction between location and plant cover,
photometer (Nanodrop Technologies, Wilmington, DE) and
while both individual factors were included (without inter-
the number of gene copies mL1 was calculated using the
action) as covariables. The significances of such models were
molecular weight of ribosomal sequences as calculated from
tested with 999 permutations.
sequences deposited in GenBank. Using 10-fold increments,
All ANOVAs and correlation analyses were carried in
the standard concentrations were adjusted from 106 to 101
Statistica 7.0 (StatSoft Inc., Tulsa, OK). For ANOVA, data
SSU rRNA gene copies mL1 for bacteria and nematodes
normality was tested with a Shapiro–Wilks test and variance
and from 105 to 101 SSU rRNA gene copies mL1 for fungi.
homogeneity by Levene’s test. When data failed to satisfy
Most of the samples and all standards were assessed in at least
one of the tests, an appropriate transformation was applied
two different runs to confirm the reproducibility of the
(log or square root transformation). Tukey’s honestly sig-
quantification.
nificant difference (HSD) method modified for unequal
sample size (Unequal N HSD in Statistica) was used for
Statistical analyses
post-hoc comparison with a 0.05 grouping baseline. For
The banding patterns of DGGE gels (Fig. S1) were analyzed correlation analyses, CFU counts were averaged over all
using the Image Master 1D program (Amersham Bios- incubation temperatures to provide a simpler result table.
c 2006 Federation of European Microbiological Societies FEMS Microbiol Ecol 59 (2007) 436–451
Published by Blackwell Publishing Ltd. All rights reservedMicrobial ecology in Antarctic soils 441
Ergosterol
(mg kg1)
18.80 ab
Correlations were carried on the untransformed data using
71.98 d
38.05 b
20.79 a
21.99 a
5.80 c
0.004
0.014
nonparametric Spearman rank–order correlations.
Conduct
Results
Table 3. Mean soil characteristics for surface soil cores (0–5 cm depth) collected at the Falkland Islands (FI), Signy Island (SI), Anchorage Island (AI), Fossil Bluff (FB) and Coal Nunatak (CN)
230 a
812 c
235 a
66 b
162 ab
160 ab
85
573
(mS)
Soil and micro-climatic data
(mg kg1)
As expected, mean soil temperature (5 cm below surface)
1031 d
29 ab
73 ab
23 a
138 bc
504 cd
4
5
decreased with increasing latitude, while the vegetation
Cl
cover did not have any significant effect (Table 2). Free-
ze–thaw cycles occurred more frequently at the Signy Island
(mg kg1)
741 a
738 a
1163 a
351 c
88 b
124 b
sites, whereas they hardly occurred at the Falkland Islands
153
42
Mg
site (Table 2). Anchorage Island had a lower frequency of
freeze–thaw cycles than Signy Island, but this difference was
(mg kg1)
5.44 ab
7.41 ab
31.80 ac
0.00 b
9.32 a
not significant. Average soil data and associated statistical
60.70 c
1.50
0.30
tests are presented in Table 3. Some soil variables were
Fe
clearly influenced by the vegetation cover, being generally
(mg kg1)
higher in vegetated plots (Water content, Organic C, total N,
1.22 ab
2.75 bc
31.10 d
0.27 a
0.37 a
6.02 c
0.35
7.65
K, Mg, Cl, conductivity and ergosterol). Some others soil
Mn
variables were mostly influenced by location, decreasing
Different letters within a column refer to significantly (P o 0.05) different averages based upon an unequal N Tukey–HSD test.
(C : N ratio, pH, Mn) or increasing (NO3, P) with increasing
(mg kg1)
latitude. The other variables measured showed a more
225 ab
534 c
100 a
112 a
335 bc
344 bc
37
60
complex pattern (Fe, NH4).
K
(mg kg1)
1.50 ab
12.77 cd
6.21 bc
18.31 d
Effects of location and vegetation cover on
0.68 a
0.68 a
0.04
0.03
microbial population structure
P
Preliminary microbial community analyses via the various
pH-H2O
4.4 ab
PCR-DGGE strategies revealed from little to no detectable
4.8 b
4.7 b
4.3 a
4.1 a
6.1 c
7.7
6.9
intraplot variation when five separate samples per plot were
compared (data not shown). We therefore pooled five 12.0 ab
12.3 ab
23.1 cd
16.6 bc
29.3 d
10.4 a
replicate individual nucleic acids extractions from each plot
8.79
C:N
39.4
to produce one representative DNA template source for each
experimental plot. PLFA analyses were also made on pooled
0.81 abc
0.84 ab
1.15 bc
soil samples. Coal Nunatak and Fossil Bluff samples were left
2.98 d
0.43 a
1.55 c
N (%)
Total
0.02
0.02
out of the DGGE analyses because of insufficient PCR
amplification for most of the samples. For cyanobacteria,
(mg kg1)
0.08 a
only 14 samples provided sufficient amplification to be
58.3 b
114.5 b
81.5 b
0.2 a
2.7 a
0.07
0.07
NO3
Table 2. Mean annual (2004–2005) micro-climatic characteristics at
5 cm depth at the Falkland Islands (FI), Signy Island (SI) and Anchorage
(mg kg1)
12.0 ab
2.2 ab
4.5 ab
10.3 ab
Island (AI)
73.1 b
2.8 a
0.18
0.06
NH4
Soil temperature ( 1C) Freeze–thaw cycles (per day)
FI
Organic
4.11 d
11.4 ab
16.6 b
9.8 a
36.4 c
31.4 c
Vegetated 5.89 a 0.00 a
0.16
0.88
C (%)
Fell-field 7.43 a 0.04 ac
SI
content
Vegetated 1.68 b 0.37 b
Water
74 a
68 a
400 b
22 c
296 b
48 a
6
7
Fell-field 2.22 b 0.35 b
(%)
AI
Vegetated 3.67 c 0.22 abc
Vegetated
Vegetated
Vegetated
Fell-field
Fell-field
Fell-field
Fell-field
Fell-field
Fell-field 3.33 c 0.27 bc
Different letters within a column refer to significantly (P o 0.05) different
CN
FB
AI
SI
FI
averages based upon an unequal N Tukey–HSD test.
FEMS Microbiol Ecol 59 (2007) 436–451
c 2006 Federation of European Microbiological Societies
Published by Blackwell Publishing Ltd. All rights reserved442 E. Yergeau et al.
Table 4. Distance-based redundancy analyses results for location assessed by DGGE even with the use of a nested-PCR
and plant cover effects on different population structure assessed by amplification approach. Location, plant cover and the inter-
PCR-DGGE and PLFA analyses at the Falkland Islands, Signy Island and action between these factors were tested by db-RDA for their
Anchorage Island
influence on community structure assessed by DGGE and
PCR-DGGE PLFA analyses (Table 4). These results taken together point
PLFA
Bacteria Cyanobacteria Fungi Nematodes – out that the microbial communities have strongly dissimilar
structures depending on the vegetation cover and sampling
Location
Plant cover NS location.
Location
plant cover Influence of environmental and soil factors on
P 0.01; P 0.001. microbial community structure
NS, not significant. Canonical correspondence analyses were used to determine
the environmental factors that appeared to have the stron-
gest influence on microbial community structure as assessed
by the various PCR-DGGE strategies employed (Fig. 2). All
Fig. 2. Canonical correspondence analysis (CCA) representation of the relationships between the soil-borne community structure and the
environmental and soil variables assessed at the Falkland Islands (FI), Signy Island (SI) and Anchorage Island (AI). (a) Bacteria; (b) Fungi; (c) Cyanobacteria;
(d) Nematodes. Individual data points for samples and DGGE bands were omitted from the graphs for clarity purposes (Fig. S1 for additional data).
c 2006 Federation of European Microbiological Societies FEMS Microbiol Ecol 59 (2007) 436–451
Published by Blackwell Publishing Ltd. All rights reservedMicrobial ecology in Antarctic soils 443
the models produced when using the respective parameters (P o 0.000001) and the interaction between plant cover
represented in Fig. 2 were highly significant (test of sig- and location (P o 0.000001), but not from location by itself.
nificance of all canonical axes: P = 0.0010). Latitude was the No significant differences were found between vegetation
only factor that was chosen for all communities, indicating types on the Falkland Islands, but at the two other locations,
that community structure was at least partly dependent on the amount of ergosterol was significantly higher in vege-
latitude across a diverse range of soil-borne organisms. tated plots (Table 3).
Fungal/bacterial ratios were calculated using real-time
PCR and PLFA data as a means of evaluating the relative
Microbial abundance in soil
dominance of these two main soil organisms in the different
Although the different methods used to estimate microbial environment sampled. All the tested factors and their
abundance in soil (real-time PCR, ergosterol, PLFA and interaction terms were significant for both methods (Table
CFU counts) were not always in complete agreement with 5). The main difference between the different ratios was that
each other, all showed a clear break in the data, with the two most of the ratios calculated using Real-time PCR results
most southerly sites (Fossil Bluff and Coal Nunatak) as were approximately 10 times lower than the PLFA ratios
outliers. Due to this clear discontinuity in the data, and their (Fig. 3). However, the general trend was the same for both
lack of balanced sampling regime, these last two sites were ratios: in the Falkland Island plots, the fungal/bacterial ratio
excluded from ANOVAs and associated post-hoc tests in our was higher in the vegetated plots. The inverse was true for
examination of trends from the Falkland Islands through the Signy and Anchorage Island plots, where fell-field plots
Anchorage Island. The numbers observed for these samples were significantly richer in fungi. The highest ratios (fungi
were also typically several orders of magnitude lower than all relatively more abundant) were recorded for the Falkland
the other samples, and that is concordant with the increased Islands vegetated plots, in fell-field plots of Signy and
difficulty encountered in the amplification of certain SSU Anchorage Islands, at Fossil Bluff and at Coal Nunatak,
rDNA targets from these samples for PCR-DGGE analyses. although the magnitude of the differences with other plots
Real-time PCR results for bacteria and fungi are presented did vary in some cases depending on the method of
in Fig. 3 and associated ANOVA tests in Table 5. Bacterial 16S abundance estimation used.
rRNA gene abundance was influenced by location, plant CFU counts for the different media and incubation
cover and the interaction between these two factors in ANOVA temperature used are presented in Fig. 4 and the associated
tests. Following post-hoc tests, fell-field sites at Signy Island ANOVA tests are presented in Table 5. For PDA (nutrient-rich
were found to have lower 16S rRNA gene abundance than all fungal media), on the Falkland Islands, all plots had
other sites, except the fell-field Anchorage sites, while all approximately the same number of CFU, for all incubation
other sites were similar (Fig. 3). There was also a trend temperatures. In contrast, the number of CFU was consis-
toward decreasing bacterial 16S rRNA gene abundance with tently higher in vegetated plots on Signy Island. For CFU
increasing latitude in fell-field plots. This trend was not counts on WA (nutrient-poor fungal media), the only
evident in vegetated plots. Fungal 18S rRNA gene abundance interaction significant was the one between plant cover and
in soil was significantly influenced by location and the location. The effect of vegetation was not significant on the
interaction between location and plant cover, but plant cover Falkland Islands, but was significant most of the time on
by itself did not have any detectable effect in ANOVA tests. Signy Island, as well as on Anchorage Island at the incuba-
Following post-hoc tests, fungal 18S rRNA gene abundance tion temperature of 20 1C.
was found to be lower in the fell-field plots on Signy Island For bacterial CFU on both TSA (nutrient-rich bacterial
and, inversely, lower in the vegetated plots on Anchorage media) and WYA (nutrient-poor bacterial media), the
Island. Nematode 18S rRNA gene abundance was not pattern was somewhat more complex. The three second-
influenced by any of the factors tested (Table 5) and averaged order interaction terms were significant when analysed by
at 2.88 106 gene copies g1 soil DW for the Falkland, Signy ANOVA (Table 5), indicating that the effect of vegetation cover
and Anchorage sites and at 1.23 102 copies g1 soil DW for differed depending on the incubation temperature and
Fossil Bluff and Coal Nunatak. sampling location. Similarly, location effects depended on
For total bacterial PLFA, the only significant difference incubation temperature and were also different in fell-field
was between vegetated and fell-field plots on Signy Island vs. vegetated plots. Although not always significant, there
(Fig. 3). Signy Island also exhibited a relatively low amount was a consistent trend toward decreased bacterial CFU with
of bacterial PLFAs, especially for fell-field plots. On the increasing latitude in fell-field plots. Vegetated plots did not
other hand, total fungal PLFA amount was mainly influ- exhibit such a trend. Incubation temperature effects were
enced by location (Table 5), being significantly higher at always highly significant, both for bacterial and fungal
Anchorage Island for most cases (Fig. 3). Ergosterol analyses media, and there was a general trend toward increased CFU
revealed significant influences from plant cover with increasing incubation temperature.
FEMS Microbiol Ecol 59 (2007) 436–451
c2006 Federation of European Microbiological Societies
Published by Blackwell Publishing Ltd. All rights reserved444 E. Yergeau et al.
Fig. 3. Average soil bacterial and fungal abundance, and abundance ratios as determined by SSU rRNA gene real-time PCR and PLFA analyses at the
Falkland Islands, Signy Island, Anchorage Island, Fossil Bluff and Coal Nunatak. ’, vegetated plots; &, fell-field plots. Different letters within a graph
refer to significantly (P o 0.05) different averages based upon an unequal N Tukey-HSD test. Values for Fossil bluff and Coal Nunatak are too low to
appear on the scale represented on the graphs, and were also not included in statistical analyses. These values were for Fossil Bluff: bacterial rRNA
gene = 1.93 103 copies g1 soil DW; Fungal 18S rRNA gene = 6.75 103 copies g1 soil DW; Bacterial PLFA = 0.128 mg g1 soil DW; Fungal
PLFA = 0.0275 mg g1 soil DW; and for Coal Nunatak: bacterial 16S rRNA gene = 3.38 103 copies g1 soil DW; Fungal 18S rRNA gen-
e = 2.65 102 copies g1 soil DW; Bacterial PLFA = 0.195 mg g1 soil DW; Fungal PLFA = 0.0095 mg g1 soil DW.
Correlations between soil and environmental and included water content, organic matter, total N, Cl, K,
factors and microbial abundance Mg and conductivity (rs with water content ranging from
0.56 to 0.95, P o 0.05). The second was related to location
Following correlation analyses, two major groups of soil or latitude (see Tables 2 and 3) and included soil mean
variables emerged as presented grouped in Table 6. The first temperature, pH-H2O, C : N ratio, P, Mn and NO3 content
group of factors was related to vegetation cover (see Table 3) (rs with latitude in absolute value ranging from 0.62 to 0.95,
c 2006 Federation of European Microbiological Societies FEMS Microbiol Ecol 59 (2007) 436–451
Published by Blackwell Publishing Ltd. All rights reservedMicrobial ecology in Antarctic soils 445
Table 5. ANOVA tests results for soil bacterial, fungal and nematode SSU rRNA abundance, bacterial and fungal PLFA abundance and bacterial and
fungal CFU counts on PDA (nutrient-rich fungal media), water agar (WA; nutrient-poor fungal media), tryptic soy agar (TSA; nutrient-rich bacterial
media) and water yeast agar (WYA; nutrient-poor bacterial media) at the Falkland Islands, Signy Island and Anchorage Island
SSU rRNA gene PLFA CFU
w
Bacteria Fungi Nematode Ratio F/B Bacteria Fungi Ratio F/B PDA WA TSA WYA
Location NS NS
Plant cover NS NS NS NS
Incubation temperature – – – – – – – NS
Location plant cover NS NS
Location Inc. T – – – – – – – NS
Plant cover Inc. T – – – – – – – NS NS
Location plant cover Inc. T – – – – – – – NS NS NS NS
P o 0.05; P o 0.01; P o 0.001.
w
Ratio F/B: fungal 18S rRNA gene abundance /bacterial 16S rRNA gene abundance ratio or fungal PLFA/bacterial PLFA ratio.
, not applicable; NS, not significant.
P o 0.05). Most of the abundance measures were signifi- forward due to parallel variations in the severity of the
cantly correlated with plant-related parameters (Table 6). thermal and hydric environments, differences in precipita-
Furthermore, the main factors influencing the fungal/bac- tion balance and disparate geological histories across the
terial ratios were also related to vegetation type. The study range (Kennedy, 1993). Nevertheless, a number of
different bacterial abundance measures were also signifi- useful general trends can be elucidated from the dataset
cantly correlated most of the time: 16S rRNA gene abun- examined here. For instance, the structure of the various
dance, bacterial PLFA abundance, CFU counts on TSA subsets of the soil-borne communities examined assessed by
(nutrient-rich bacterial media) and on WYA (nutrient-poor several PCR-DGGE strategies was mostly coupled to factors
bacterial media) were all significantly correlated with each related to latitude (mean temperature, pH, C : N ratio, etc.),
other (rs all positive, ranging from 0.44 to 0.56, P o 0.05), whereas abundance data was mostly influenced by plant-
with the exception of the correlation between WYA counts related factors (organic C, soil humidity, total N, etc.). Thus,
and bacterial PLFA abundance. The picture was less coher- community structure appears to be determined to a large
ent for fungal abundance measures: soil ergosterol content extent by the location and/or the specific location-depen-
was positively correlated with CFU counts (rs = 0.69 (PDA) dent environmental conditions, whereas microbial abun-
and rs = 0.52 (WA), P o 0.05), with fungal PLFA abundance dance may be more associated with vegetation-related
and fungal 18S rRNA gene abundance being correlated effects of nutrient input and climatic buffering. Different
(rs = 0.43, P o 0.05). Fungal PLFA was also correlated to subsets of the total soil community also reacted differently
CFU counts on PDA (rs = 0.46, P o 0.05), but all other to the presence of different vegetation and the range of
combinations were insignificant. environmental conditions encountered across the study
area. Furthermore, conspicuous and complex interactions
were apparent between location, vegetation cover and other
Discussion variables, highlighting the fact that vegetation effects were
Global warming is expected to have mainly indirect effects highly dependent upon the environmental context in which
on microorganisms, especially via changes in macrophyte they occurred.
species composition, vegetation density, and litter quality
and quantity, as well as associated changes in soil biochem- Bacterial community size and structure
ical and biophysical characteristics (Panikov, 1999). This
study therefore sought to provide a baseline of understand- Antarctic environments are most well known for their severe
ing regarding the drivers of microbial community structure climates. Bacterial processes are particularly sensitive to
across a gradient of Antarctic and sub-Antarctic environ- environmental conditions (Eriksson et al., 2001), yet bacter-
ments with a special focus on the role of vegetation cover on ia are also highly adaptable to extreme and changing
the size and structure of associated soil-borne communities. environments (Cavicchioli et al., 2000; Georlette et al.,
Although spatial gradients have been used widely to predict 2004; Thomas, 2005). Previous studies on bacteria in
long-term effects of global warming on ecosystems (Dunne terrestrial Antarctic habitats have provided some general
et al., 2004), it should be recognized that the use of such a appreciation of such unique assemblages, but detailed com-
gradient along the Antarctic Peninsula region is not straight- munity analyses across a range of systems were still lacking
FEMS Microbiol Ecol 59 (2007) 436–451
c 2006 Federation of European Microbiological Societies
Published by Blackwell Publishing Ltd. All rights reserved446 E. Yergeau et al. Fig. 4. Average soil bacterial and fungal CFU at the Falkland Islands, Signy Island, Anchorage Island, Fossil Bluff and Coal Nunatak on PDA (nutrient-rich fungal media), water agar (WA; nutrient-poor fungal media), tryptic soy agar (TSA; nutrient-rich bacterial media) and water yeast agar (WYA; nutrient- poor bacterial media) and incubated at three different temperatures. ’, vegetated plots; &, fell-field plots. Different letters within a graph refer to significantly (P o 0.05) different averages based upon an unequal N Tukey-HSD test. Values for Fossil bluff and Coal Nunatak were not included in statistical analyses (see results for details). prior to this investigation. Previous reports have suggested interactions among these variables. Interestingly, bacterial that Antarctic bacteria are influenced by temperature pat- abundance did not simply decrease with the coldness of the terns, plant cover, soil humidity and other soil character- environment. For instance, the fell-field plots on Signy istics (Christie, 1987; Tearle, 1987; Bölter, 1992; Bölter, 1995; Island supported the lowest bacterial community densities Bölter et al., 1997; Harris & Tibbles, 1997). Our results (except for Fossil Bluff and Coal Nunatak). This Signy Island support these suggestions, as we found that bacterial abun- habitat is also subjected to a high frequency of freeze–thaw dance and community structure to be influenced both by cycles, which may actually impose a greater stress level than plant- and weather-related factors, with numerous complex conditions with a colder average temperature (Yanai et al., c 2006 Federation of European Microbiological Societies FEMS Microbiol Ecol 59 (2007) 436–451 Published by Blackwell Publishing Ltd. All rights reserved
Microbial ecology in Antarctic soils 447
Table 6. Spearman rank order correlations between soil and micro-climatic parameters and diverse microbial abundance parameters measured at the
Falkland Islands, Signy Island and Anchorage Island
16S B 18S F 18S N Ratio 18S/16S Ergosterol PLFA B PLFA F Ratio PLFA PDA WA TSA WYA
Location related
Latitude 0.14 0.07 0.003 0.09 0.15 0.53 0.53 0.05 0.35 0.27 0.05 0.35
Mean T 0.27 0.04 0.16 0.14 0.05 0.52 0.56 0.25 0.33 0.04 0.09 0.49
pH-H2O 0.06 0.16 0.27 0.03 0.34 0.45 0.47 0.03 0.49 0.08 0.10 0.18
C:N 0.30 0.05 0.53 0.11 0.40 0.27 0.41 0.39 0.02 0.60 0.24 0.40
NO3 0.02 0.15 0.10 0.41 0.02 0.50 0.47 0.03 0.35 0.50 0.13 0.15
P 0.18 0.06 0.11 0.02 0.40 0.31 0.27 0.01 0.33 0.03 0.03 0.15
Mn 0.04 0.11 0.32 0.15 0.20 0.30 0.26 0.004 0.27 0.64 0.02 0.15
Vegetation related
% water 0.56 0.06 0.97 0.64 0.85 0.51 0.30 0.57 0.64 0.61 0.78 0.56
% org C 0.44 0.07 0.93 0.55 0.89 0.46 0.27 0.51 0.57 0.63 0.71 0.49
Total N 0.41 0.13 0.76 0.60 0.81 0.76 0.61 0.38 0.68 0.34 0.63 0.37
K 0.42 0.10 0.68 0.42 0.65 0.01 0.14 0.42 0.33 0.69 0.48 0.66
Mg 0.38 0.09 0.67 0.40 0.64 0.01 0.21 0.50 0.18 0.62 0.50 0.67
Cl 0.51 0.09 0.64 0.42 0.53 0.02 0.25 0.58 0.34 0.52 0.57 0.75
Conduct 0.54 0.38 0.52 0.49 0.51 0.21 0.04 0.33 0.32 0.39 0.51 0.71
Others
F–T cycles 0.46 0.25 0.51 0.22 0.09 0.05 0.18 0.22 0.17 0.12 0.08 0.58
NH4 0.06 0.13 0.06 0.20 0.02 0.41 0.41 0.002 0.20 0.02 0.25 0.01
Fe 0.25 0.19 0.20 0.23 0.23 0.28 0.30 0.10 0.05 0.36 0.03 0.20
Significant correlation (P o 0.05) values are in bold. Mean temperature and the number of freeze–thaw cycles correlations were calculated using three
plots per site per treatment (N = 18) while the other correlations were calculated for all the plots (N = 36).
16S B, bacterial 16S rRNA gene abundance; 18S F, fungal 18S rRNA gene abundance; 18S N, nematode 18S rRNA gene abundance; ratio 16S/18S,
bacterial 16S rRNA gene abundance/fungal 18S rRNA gene abundance ratio; PLFA B, bacterial related PLFAs; PLFA F, fungal related PLFAs.
2004). Plants are known to produce soil microhabitats abundance measures were correlated to the soil water
(Kowalchuk et al., 2002), and even though the freeze–thaw content (Table 6). Soils with dense vegetation cover also
frequency was unchanged by vegetation cover (Table 2), our had a higher nutrient input than fell-field soils (Table 3),
results suggest that the dense vegetation in our experimental which might have helped to support a more abundant
plots was able to counter the effects of the extreme environ- bacterial community. Such a separation of soils with high
mental conditions to some extent. This influence of vegeta- organic matter content from mineral soils was previously
tion may explain the disparate effects of latitude on bacterial observed using cluster analysis of soil physical parameters
abundance in fell-field vs. vegetated sites. It is, however, not and diverse microbial population descriptors (Bölter, 1990).
clear whether these effects are mediated by vegetation- This could also explain the lack of significance of vegetation
induced protection of soil microhabitats, input of plant- cover at the Falkland Islands site for most data, as the
derived substrates, or other mechanisms. environment was rather mild and all plots relatively rich in
It is generally accepted that the harshness of Antarctic nutrients, which would decrease any buffering or nutrient
environments is not caused by the extreme climatic condi- effects conferred by increased vegetation cover.
tions per se, but perhaps more to the extreme range of Cyanobacterial community structure followed the same
conditions that are encountered. Previous reports have trends as seen for total bacterial communities, but showed a
demonstrated that polar soils with no vegetation generally lower level of significance, probably due to the lower
support fewer microorganisms than soils associated with number of samples in the final analysis. Cyanobacterial
mosses (Kaštovská et al., 2005), and it was suggested that, community structure might be dictated to some degree by
for Antarctic soil, this may be caused by the combined the presence of mosses, and a previous study demonstrated
effects of greater nutrient availability and more favorable an association of specific Cyanobacterial assemblages with
physical conditions (Harris & Tibbles, 1997). These data, mosses (Solheim et al., 2004). In barren arctic and alpine
however, are confounded by the fact that mosses tend to environments, a significant portion of the bacterial commu-
occur at sheltered sites that already exhibit relative thermal- nity was related to the photosynthetic bacterial division
and hydro-stability. Nevertheless, the buffering action of Cyanobacteria (Kaštovská et al., 2005; Nemergut et al.,
mosses is likely to maintain soils beneath them at relatively 2005). However, the difficulty we experienced in recovering
constant water content and temperature which might Cyanobacterial-specific PCR products suggests that this
strongly influence bacterial abundance. Indeed, all bacterial division did not represent a significant proportion of the
FEMS Microbiol Ecol 59 (2007) 436–451
c2006 Federation of European Microbiological Societies
Published by Blackwell Publishing Ltd. All rights reserved448 E. Yergeau et al.
bacterial communities in these soils. Sequence data from also thought to select fungal species that produce large
bacterial 16S rRNA gene clone libraries from these sites also numbers of small spores (Tosi et al., 2005), which could
suggests that Cyanobacteria only make up a small minority further bias fungal CFU counts. Additionally, it was re-
of these bacterial communities (E. Yergeau & G.A. Kowal- ported that ergosterol content should be used with caution
chuk, unpublished data). since it shows a high persistence in some soils (Mille-
Lindblom et al., 2004), especially in low-temperature soils
(Weinstein et al., 2000).
Fungal community size and structure
With these cautionary notes in mind, we still found some
Fungal community structure was not influenced by plant noteworthy trends in the culturable and ergosterol abun-
cover per se, but the interaction between location and dance data. At sites other than at the Falkland Islands, the
vegetation cover was highly significant, indicating that the fungal abundance was generally higher in vegetated plots,
type of vegetation cover was of importance in how latitude and correlation analyses indicated that the main factors
affected fungal communities. This supports the previous influencing fungal abundance were plant-related (soil or-
finding that fungal communities can respond very differ- ganic matter and water content; Table 6). These results are in
ently to changes in organic input levels and quality depend- line with previous culture-based studies carried out on Signy
ing on the environmental conditions (Tosi et al., 2005). Island (Bailey & Wynn-Williams, 1982). Despite the short-
Fungal quantification by real-time PCR showed a similar comings of ergosterol and CFU data for estimating fungal
trend. A previous study using culture-based methods re- biomass, these data do lend some support to the notion that
ported viable fungal propagules in a moss bank to be these fungal communities are shaped more by substrate
significantly influenced by the extent of the coverage of quality and quantity, as well as other site-specific character-
particular macrophyte species (Smith & Walton, 1985). This istics as opposed to pure weather-related parameters. CFU
suggests that the species composition of the vegetation counts also showed a trend toward increased numbers with
might also be of importance in influencing the response of increasing incubation temperature, suggesting that some
the fungal community to latitude. This is partly supported mesophilic strains that could not grow to the level of
in our dataset (DGGE and real-time PCR) by the fact that detection at low temperatures were present. This is in
vegetation by itself did not have a significant influence. agreement with other studies that reported a prevalence of
Instead, effects were more subtle, with fungal communities cold-tolerant fungal species rather than cold-adapted ones
responding differently to vegetation cover depending on the (Kerry, 1990; Melick et al., 1994; Zucconi et al., 1996;
environmental conditions present. This contrasted with data Robinson, 2001).
on bacterial community structure and abundance, where Fungal 18S rRNA gene/bacterial 16S rRNA gene and
vegetation cover was a highly significant determinant across fungal PLFA/bacterial PLFA ratios followed the same trend,
the range of latitudes examined. being the highest at sites with the harshest temperatures
In this study, we used several different approaches to (fell-field sites at Signy, Anchorage and Fossil Bluff) or in the
estimate fungal biomass. In contrast to bacteria abundance only plots having a dense cover of vascular plants (Falkland
measures, which all showed a similar picture, fungal abun- Islands vegetated plots). This could imply that fungi are less
dance measures did not agree in all cases. Fungal abundance influenced by weather conditions than bacteria and can
as estimated by 18S rRNA gene quantification via real-time dominate more easily in harsh ecosystems, probably because
PCR was correlated to values obtained using fungal PLFA of a better adaptation to lower temperatures or the presence
estimates. However, these estimates showed no coherent of a cell wall. Fungi are also known to be able to degrade
picture in regard to correlations with the soil and weather more complex organic matter than bacteria and that might
factors measured. Using direct counts, it was reported that explain their higher relative abundance in the Falkland
fungal abundance was similarly unaffected by environmen- Island vegetated plots. The only exception, where both
tal parameters (Bailey & Wynn-Williams, 1982). This con- methods did not completely agree, was in the case of the
trasted with the results we obtained via fungal CFU counts Coal Nunatak samples, probably because the biomarker
and ergosterol measurement. As already reported for other amounts present in these soil samples were approaching
environments (Widmer et al., 2001; Leckie et al., 2004), the detection limits of the methods. The 10-fold difference
different soil microbial abundance estimators can give between the two ratios is coherent with the differences in cell
different, sometimes complementary results. However, size and number of SSU rRNA gene copies per cell between
CFU are known to provide a biased view of the abundance fungi vs. bacteria. In support of other recent environmental
of microorganisms, as they only show the culturable part of studies (Malosso et al., 2004; Nemergut et al., 2005), it
the community (Staley & Konopka, 1985), and it is also appeared that real-time PCR and PLFA analyses were the
impossible to translate propagation units into biomass. The more consistent techniques for microbial biomass estima-
high stress and high disturbance conditions of Antarctica are tion in Antarctic soils.
c 2006 Federation of European Microbiological Societies FEMS Microbiol Ecol 59 (2007) 436–451
Published by Blackwell Publishing Ltd. All rights reservedMicrobial ecology in Antarctic soils 449
Nematode community size and structure abundance, and large changes in community structure,
including changes in the relative abundance of fungi and
Nematode community structure was strongly influenced by
bacteria, will only occur if climate change induces increases
plant cover, location and their interaction term in our study,
in nutrient inputs via increased vegetation density or
and although the abundance measured by real-time PCR
productivity. Both in situ and laboratory experimental
was statistically similar for all samples, excluding Fossil Bluff
investigations into such hypotheses are clearly necessary to
and Coal Nunatak, we found nematode abundance to be
determine the functional consequences of Antarctic micro-
highly correlated to soil organic matter and water content,
bial community responses to global warming.
both of which are vegetation-associated characteristics. In
agreement with our study, nematode community structure,
respiration and abundance were previously shown to be
linked to the overlying vegetation on Signy Island (Caldwell, Acknowledgements
1981). However, a slightly different pattern was observed for This study was supported by NWO grant 851.20.018 to
Mars Oasis, which is a coastal site close to Fossil Bluff, where R. Aerts and G.A. Kowalchuk. E. Yergeau was partly supported
nematode density, but not species richness, was considerably by a Fonds Québécois pour la Recherche sur la Nature et les
higher in naturally vegetated soil (Convey & Wynn-Wil- Technologies postgraduate scholarship. The British Antarctic
liams, 2002). Antarctica nematodes were also found to be Survey, and especially Pete Convey, is gratefully acknowledged
linked to organic matter, with higher numbers in the vicinity for supporting field operations. Merlijn Janssens and Kat Snel
of bird colonies and moss patches (Sohlenius & Boström, are acknowledged for sampling efforts. Wiecher Smant and
2005). In interpreting the differences between our results Wietse de Boer are thanked for help with soil analyses. This is
and those published previously, methodological differences NIOO-KNAW publication 3892.
also have to be considered. For instance, traditional nema-
tode counts using migration extraction were reported to be
difficult to adapt to some Antarctic soils (Freckman &
Virginia, 1993). On the other hand, primer incompatibil- References
ities, as well as uncertainties in extraction and amplification Azmi OR & Seppelt RD (1998) The broad-scale distribution of
efficiencies, are also potential sources of bias and error in the microfungi in the Windmill Islands region, continental
molecular estimators of nematode density. Nematode dis- Antarctica. Polar Biol 19: 92–100.
tribution in Antarctic habitats is also highly patchy (Sohle- Bailey AD & Wynn-Williams DD (1982) Soil microbiological
nius et al., 2004), making the use of small sample sizes for studies at Signy Island, South Orkney Islands. Br Antarct Surv
molecular analyses another potential source of error. Never- Bull 51: 167–191.
theless, it was recently reported that the abundance of Bölter M (1990) Evaluation – by cluster analysis – of descriptors
nematodes estimated by molecular methods could be related for the establishment of significant subunits in Antarctic soils.
to biovolume, but not to the number of individuals in soil Ecol Model 50: 79–94.
(Griffiths et al., 2006). The primers used here were also Bölter M (1992) Environmental conditions and microbiological
properties from soils and lichens from Antarctica (Casey
proven to be adapted to assess nematode communities in
Station, Wilkes Land). Polar Biol 11: 591–599.
soil directly (Waite et al., 2003).
Bölter M (1995) Distribution of bacterial numbers and biomass
in soils and on plants from King George Island (Arctowski
Concluding remarks Station, maritime Antarctica). Polar Biol 15: 115–124.
The analysis of soil-borne microbial communities described Bölter M, Blume HP, Schneider D & Beyer L (1997) Soil
here for the first time examines the factors shaping micro- properties and distributions of invertebrates and bacteria from
bial communities across a range of terrestrial Antarctic King George Island (Arctowski Station), maritime Antarctic.
Polar Biol 18: 295–304.
habitats. The latitudinal gradient examined was intended as
Boschker HTS (2004) Linking microbial community structure
a rough surrogate for long-term climate-change scenarios in
and functionning: stable isotope (13C) labeling in combination
soils, with our results forming an initial baseline to estimate
with PLFA analysis. Molecular Microbial Ecology Manual, Vol. 2
the direct and indirect consequences of global warming in (Kowalchuk GA, de Bruijn FJ, Head IM, Akkermans ADL &
these extreme, pristine and rapidly changing environments. van Elsas JD, eds), pp. 1673–1688. Kluwer Academic
Given the rate of climate change, natural seasonal fluctua- Publishers, Dordrecht, the Netherlands.
tions and microbial abilities to adapt to environmental Caldwell JR (1981) Biomass and respiration of nematode
changes, it is hypothesized that the direct effects of climate populations in two moss communities at Signy Island,
change on soil-borne communities will be minor (Panikov, maritime Antarctic. Oikos 37: 160–166.
1999). Accordingly, in light of the results presented here, we Carter MR (1993) Soil Sampling and Methods of Analysis. CRC
hypothesize that increases in bacterial, fungal and nematode Press, Boca Raton, FL.
FEMS Microbiol Ecol 59 (2007) 436–451
c 2006 Federation of European Microbiological Societies
Published by Blackwell Publishing Ltd. All rights reservedYou can also read
