FEMS Microbiology Ecology, 92, 2016, fiw008
doi: 10.1093/femsec/fiw008
Advance Access Publication Date: 18 January 2016
Research Article
RESEARCH ARTICLE
Effect of altitude and season on microbial activity,
abundance and community structure in Alpine
forest soils
José A. Siles1 , Tomas Cajthaml2,3 , Stefano Minerbi4 and Rosa Margesin1,∗
1
Institute of Microbiology, University of Innsbruck, Technikerstrasse 25, A-6020 Innsbruck, Austria, 2 Institute
of Microbiology, Academy of Sciences of the Czech Republic, v.v.i., Vı́deňská 1083, CZ-142 20 Prague 4, Czech
Republic, 3 Institute for Environmental Studies, Faculty of Science, Charles University in Prague, Benatska 2,
CZ-128 01 Prague 2, Czech Republic and 4 Division Forestry, Autonomous Province of Bozen/Bolzano,
Brennerstrasse 6, I-39100 Bozen/Bolzano, Italy
∗
Corresponding author: Institute of Microbiology, University of Innsbruck, Technikerstrasse 25, A-6020 Innsbruck, Austria. Tel: +43512-507-51230;
Fax: +43512-507-51240; E-mail: [email protected]
One sentence summary: Soil organic matter increases with altitude and drives the differences in soil microbial activity, abundance and community
structure along an altitudinal gradient in Alpine forest soils, contrary to the assumption that low temperatures limit abundance and activity at high
altitudes.
Editor: Max Häggblom
ABSTRACT
In the current context of climate change, the study of microbial communities along altitudinal gradients is especially
useful. Only few studies considered altitude and season at the same time. We characterized four forest sites located in the
Italian Alps, along an altitude gradient (545–2000 m a.s.l.), to evaluate the effect of altitude in spring and autumn on soil
microbial properties. Each site in each season was characterized with regard to soil temperature, physicochemical
properties, microbial activities (respiration, enzymes), community level physiological profiles (CLPP), microbial abundance
and community structure (PLFA). Increased levels of soil organic matter (SOM) and nutrients were found at higher altitudes
and in autumn, resulting in a significant increase of (soil dry-mass related) microbial activities and abundance at higher
altitudes. Significant site- and season-specific effects were found for enzyme production. The significant interaction of the
factors site and incubation temperature for soil microbial activities indicated differences in microbial communities and
their responses to temperature among sites. CLPP revealed site-specific effects. Microbial community structure was
influenced by altitudinal, seasonal and/or site-specific effects. Correlations demonstrated that altitude, and not season,
was the main factor determining the changes in abiotic and biotic characteristics at the sites investigated.
Keywords: Alpine soils; forest; altitude; respiration; enzymes; PLFA
INTRODUCTION
The amount of soil organic C in forests typically accounts for
more than 50% of the total ecosystem carbon and in some cases
it exceeds the carbon stored in the aboveground biomass by
three times (Rodeghiero et al. 2010). In this way, it has been estimated that the current C-stock in the soil forests (to 1-m depth)
over the world is 383 ± 30 Pg C (Pan et al. 2011). The Fifth Assessment Report of the Intergovernmental Panel on Climate Change
(Edenhofer et al. 2014) estimated that by the end of the 21st
Received: 28 October 2015; Accepted: 13 January 2016
C FEMS 2016. All rights reserved. For permissions, please e-mail: [email protected]
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FEMS Microbiology Ecology, 2016, Vol. 92, No. 3
century, the global average surface temperature will increase in
the range of 2.6–4.8◦ C under RCP8.5 scenario. This temperature
increase will likely produce a decoupling between the amount of
C annually emitted by soil microbial respiration in forests, and
the amount of C sequestered by photosynthetic activities, resulting in a positive feedback to climate change (Bradford 2013).
However, there are significant uncertainties in the magnitude
and mechanisms of soil microbial respiration feedback to global
warming in Alpine zones (Gavazov 2010; Nazaries et al. 2015).
Litter and soil organic matter (SOM) decomposition depend
on three main interacting groups of factors: chemical (chemical composition and quality of litter and SOM), physical (climate, moisture and soil physical properties) and biotic factors
(abundance and composition of soil microorganisms and fauna
involved in the process) (Polyakova and Billor 2007). The importance of soil microorganisms in this process is clear since they
mediate 85–90% of SOM decomposition (Djukic et al. 2013). Their
activity is dependent on substrate quantity and quality as well
as on environmental conditions, such as temperature, moisture,
pH, soil type or soil depth (Zhang et al. 2013). Climate change will
produce an immediate rising of soil temperature; this increase
along with the other alterations related to climate change (e.g.
increasing CO2 levels or N-deposition) will rapidly affect soil microbial communities (Sierra et al. 2015), producing changes in
their structure and abundance due to their high susceptibility to
environmental conditions (Xu et al. 2014). These alterations will
have consequences on litter and SOM decomposition process
and turnover, which may in turn affect the stability and function of the ecosystems. In this context, the altitudinal gradients
of mountains have been regarded as especially interesting in
the study of the effects of global warming on terrestrial ecosystems. First, because high-mountain ecosystems, such as European Alps, are especially vulnerable to climate change (Schröter
et al. 2005) and second, because increasing altitude is associated
with a decline in temperature. In this way, elevational gradients
represent powerful natural experiments that may give us information about microbial community responses to variation in
temperature at the landscape scale (Sundqvist et al. 2014). Likewise, other factors such as vegetation composition and snow
cover regimes, which are predicted to shift with climate change,
also vary along elevational gradients and can therefore be investigated simultaneously under field conditions to know their
importance in the modelling of soil microbes (Djukic et al. 2010).
Previous studies have shown differences in soil microbial
diversity (Fierer et al. 2010; Singh et al. 2012; Singh, Shi and
Adams 2013), community structure (Margesin et al. 2009; Xu
et al. 2014), abundance (Djukic et al. 2010; Wang et al. 2015) and
enzyme activities (Schinner 1982) along several elevational gradients, which were significantly correlated with soil temperature, moisture, C/N ratio or soil pH. However, knowledge about
the seasonal effect on microbial communities along altitudinal
gradients is scarce (Margesin, Minerbi and Schinner 2014), and to
the best of our knowledge, there are no previous integrative surveys studying the changes in soil microbial activity, abundance
and community structure associated with altitude and season
at the same time. For studies on shifts of soil microbial communities or on mechanisms that determine microbial life in a specific forest ecosystem, it is important to take into account seasonal changes. Over the year, soil microorganisms have to face
large seasonal variations in environmental conditions such as
temperature and moisture (López-Mondéjar et al. 2015) as well
as in resource availability, driven by plants via belowground Cexudation during the growing season or via litterfall in autumn
(Koranda et al. 2013).
In this study, we evaluated the effects of altitude and season
(spring and autumn) on microbial properties in soils from four
forest sites along an altitudinal gradient, including submontane, montane, subalpine and alpine vegetation levels, from the
poorly investigated European Alps. The objectives of the present
work were as follows: (i) to characterize soil temperature and soil
physicochemical properties at the studied sites in spring and autumn; (ii) to assess the changes produced by altitude, season and
temperature on microbial activity by measuring soil respiration
and key enzyme activities involved in P, S, N and C cycles as well
as by determining community level physiological profiles (CLPP)
using Biolog Ecoplate System; (iii) to characterize the changes in
soil microbial abundance and community structure over the altitudinal gradient in spring and autumn by using phospholipid
fatty acid (PLFA) analysis; and (iv) finally, to determine to what
extent altitude and/or season govern changes in abiotic and biotic soil properties at the studied forest sites.
MATERIALS AND METHODS
Site description
The investigated four sampling sites represent widely distributed and forestally significant forest types in South Tyrol in the Italian Alps and were selected according to altitude
above sea level (a.s.l.) to cover the four typical vegetation zones
prevailing in the studied Alpine area: submontane, montane,
subalpine and alpine. The submontane site (Montiggl, M) is a
long-term monitoring site (IT02) installed in 1992 within the
framework of ICP IM (Kleemola and Forsius 2002) and is located 8 km south of Bozen/Bolzano on the small peak Kleiner
Priol above the Small Lake Montiggl at an altitude of 545–570
m a.s.l. The pedogenic substratum consists of rhyolite (quartzporphyry) and the soil was classified as dystric cambisol (FAO).
The site consists of mixed deciduous forest, dominated by Quercus pubescens, Q. robur, Fraxinus ornus, Pinus sylvestris and Ostrya
carpinifolia. The climate is mild continental with submediterranean influences, with a mean annual air temperature of 11.0◦ C
and an annual precipitation of 900 mm (Bonavita et al. 1998; Margesin, Minerbi and Schinner 2014).
The montane site (Klobenstein/Ritten, K) is located on a small
hill 300 m north of the village center of Klobenstein at an altitude of 1175–1200 m a.s.l. The pedogenic substratum consists
of rhyolite (quartz–porphyry), and the soil was classified as dystric cambisol (FAO). The site consists of mixed deciduous forest,
dominated by Fagus sylvatica, P. sylvestris, Picea abies and Larix decidua. The climate is montane-continental with a mean annual
air temperature of 7.4◦ C and an annual precipitation of 950 mm.
The subalpine site (Kleebach/Ritten, R) is a long-term monitoring site installed in 1992 within the framework of ICP IM
(Kleemola and Forsius 2002) and is located 7 km north of
Bozen/Bolzano below the Rittner Horn at an altitude of 1724–
1737 m a.s.l. The pedogenic substratum consists of rhyolite
(quartz–porphyry); the soil was classified as haplic podzol (FAO)
and contained a thick layer of raw humus. The site consists
of coniferous forest close to the timber line, dominated by Pi.
abies, P. cembra, L. decidua and Vaccinium myrtillus. The climate is
subalpine-continental with a mean annual air temperature of
4.0◦ C and an annual precipitation of 1000 mm (Bonavita et al.
1998; Margesin, Minerbi and Schinner 2014).
The alpine site (Schwarzseespitze/Ritten, S) is located below the mountain Schwarzseespitze at an altitude of 1965–2000
m a.s.l at the tree line. The pedogenic substratum consists of
rhyolite (quartz–porphyry), and the soil was classified as haplic
Siles et al.
podzol (FAO). The site consists of single trees in a P. mugo location
above the timberline, dominated by P. mugo, P. cembra, Pi. abies
and Rhododendron ferrugineum. The climate is alpine-continental
with a mean annual temperature of 2.4◦ C and an annual precipitation of 1050 mm. The sites K, R and S were located on a
transect along the same geographical area.
Soil sampling
Eight sampling spots distributed uniformly over each site (100 ×
100 m) were chosen to cover within-site variability. Soil samples
(ca. 5 kg) were collected from each of these sampling spots from
the Ah horizon (top 10 cm); the number of sampled cores depended on the thickness of the sampled Ah horizon at each site.
The distance between sampling spots in each sampling area was
site-dependent. To determine the effect of season and to take
into account the different vegetation periods at the investigated
sites, soil samples were collected both in late spring (sites M and
K: 24 April 2014; sites R and S: 3 June 2014) and autumn (sites M
and K: 15 November 2014; sites R and S: 15 October 2014). Immediately after sampling, soil samples were transported in cooled
boxes to the laboratory, sieved (2 mm mesh) and stored at 4◦ C
under aerobic conditions for microbial activity measurements,
or stored at −80◦ C prior to PLFA analysis.
Physicochemical soil properties and soil temperature
Analysis of soil samples included measurements of dry mass
(dm; 24 h at 105◦ C), pH (CaCl2 ), contents of humus (SOM; dry
combustion of carbon at 1250◦ C), total organic carbon (TOC;
dry combustion of carbon at 1250◦ C), total nitrogen (N; Kjeldahl
method: digestion with H2 SO4 ), plant-available P, K and Mg as
well as electrical conductivity (EC) (converted to electrolyte concentration) following standard methods (Schinner et al. 1996;
ÖNORM L1084 1999; ÖNORM L1080 2005; ÖNORM L1082 2005;
ÖNORM L1093 2010; ÖNORM EN15933 2012). C/N ratio was calculated as TOC/N. All the results were calculated on a soil dm
basis (105◦ C).
Soil temperature was measured in triplicate at each site at
4 h intervals during one year using DS1921G Thermochron iButton dataloggers buried at a depth of ca. 5 cm in the Ah horizon
(DS1921G-F5#, Maxim Semiconductor Inc.).
Soil microbial activities
Basal respiration and potential soil enzyme activities were determined at various incubation temperatures in each of the eight
soil samples collected per site in spring and autumn.
Soil respiration (basal respiration) was determined by using
R Control (WTW). For each site, 10 g of soil
the System OxiTop
fresh mass were weighed into each of 100-ml vessels and water
content was adjusted to 50% of the maximum water holding capacity. The vessels were provided with the corresponding measuring heads that were filled with NaOH platelets. Afterwards
the vessels were tightly closed and eight vessels per site (containing the eight soil samples collected per site) were incubated
at 0◦ C, 10◦ C, 20◦ C and 30◦ C after pre-incubation of 1 h to avoid interference with the initial CO2 flush. The consumption of oxygen
due to soil respiration resulted in a negative pressure that was
constantly monitored via the Oxi-Top Control measuring heads
over 6 days. NaOH platelets were regularly replaced. For calculation, we used data obtained during linear pressure decrease
(after ca. 2–4 days).
3
Soil phosphomonoesterase activity (acidic phosphatase; EC
3.1.3.2) was carried out as described Eivazi and Tabatabai (1977)
and Schinner et al. (1996) by using 0.115 M p-nitrophenyl phosphate as substrate and 0.5 M sodium acetate-acetic acid buffer,
pH 5.0. After 1 h of incubation at 10◦ C, 20◦ C and 40◦ C, the
p-nitrophenol (pNP) released during incubation was extracted
and colorimetrically determined at 400 nm.
Arylsulfatase activity (EC 3.1.6.1) was determined as described Schinner et al. (1996) according to a modification of
the method of Tabatabai and Bremner (1970) by using 0.025 M
p-nitrophenyl sulfate as substrate and 0.5 M sodium acetateacetic acid, pH 5.8, as buffer. After 1 h of incubation at 10◦ C, 20◦ C
and 40◦ C, the pNP released during incubation was colorimetrically determined at 400 nm.
Protease activity (EC 3.4.2.21-24) was determined as described Ladd and Butler (1972) and Schinner et al. (1996) using
2% (w/v) Na-casein as substrate and 0.05 M Tris-HCl, pH 8.1, as
buffer. After 2 h of incubation at 10◦ C, 20◦ C and 40◦ C, the reaction was stopped and the amino acids released during incubation were colorimetrically determined at 700 nm.
β-Glucosidase activity (EC 3.2.1.21) was assayed as described
Eivazi and Tabatabai (1988) by using 0.025 M p-nitrophenyl β-Dglucopyranoside as substrate and 0.5 M sodium acetate-acetic
acid buffer, pH 5.0. After 1 h of incubation at 10◦ C, 20◦ C and 40◦ C,
the pNP released was colorimetrically determined at 400 nm.
Xylosidase activity (EC 3.2.1.37) was assayed following the
procedure of Lama et al. (2004) using 0.025 M p-nitrophenyl βD-xylopyranoside as substrate and 0.5 M sodium acetate-acetic
acid buffer, pH 5.0. After 1 h of incubation at 10◦ C, 20◦ C and 40◦ C,
the pNP released was colorimetrically determined at 400 nm.
Cellobiohydrolase activity (EC 3.2.1.91) was assayed according to Deshpande, Eriksson and Göran Pettersson (1984) using
0.01 M p-nitrophenyl-ß-D-cellobioside as substrate and 0.5 M
sodium acetate-acetic acid, pH 5.0, as buffer. After 1 h of incubation at 20◦ C and 40◦ C, the pNP released during incubation was
colorimetrically determined at 400 nm.
Community level physiological profiles
CLPP for each site, in each season and at different incubation
temperatures were assessed using the Biolog EcoPlate system
(BIOLOG. Inc., CA, USA). Each Biolog EcoPlate contains 31 different kinds of carbon sources (ten types of carbohydrates, nine
carboxylic/acetic acids, six amino acids, four polymers and two
amines/amides) (Fra̧c, Oszust and Lipiec 2012). The analyses
were performed in triplicate. To determine the CLPP for each
sample, 1 g of soil fresh mass was shaken in 10 ml of sterile
saline solution (0.85% w/v NaCl) at 150 rpm for 1 h (Siles et al.
2014). Soil suspensions were then serially diluted to 10−4 based
on pre-testing. A total of 130 μl of soil solutions were used for
each well, and Ecoplates were incubated at 0◦ C, 10◦ C, 20◦ C and
30◦ C for 30 days. The C-source use rate was indicated by the reduction in tetrazolium salts, which changed from colourless to
purple. Colour development for each well was obtained in terms
of optical density (OD) at 590 nm every 24 h using an automated
plate reader. Microbial activity for each soil sample at each site
and at each incubation temperature was calculated as average
well colour development (AWCD) according to the equation:
AWCD =
ODi
,
31
where ODi is the OD value at 590 nm from each well corrected
by the blank. AWCD values reached 0.3 for each of the soil
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FEMS Microbiology Ecology, 2016, Vol. 92, No. 3
samples after 28 days (0◦ C), 10 days (10◦ C), 4 days (20◦ C) and 3
days (30◦ C), and these values were used to calculate the relative consumption rate of each C-source family, as well as substrate richness, Shannon’s functional diversity index and evenness. For Shannon’s functional diversity index and evenness, the
PAST program ver. 3.06 (Hammer, Harper and Ryan 2001) was
used.
Phospholipid fatty acid analysis
Phospholipid fatty acids (PLFA) of each of the eight soil samples collected per site in spring and autumn were analysed as described by Stella et al. (2015). Briefly, phospholipids
were extracted from 0.5 g of lyophilized soil sample using
a mixture of chloroform:methanol:phosphate buffer (1:2:0.8;
v/v/v) according to Bligh and Dyer (1959) and then separated by solid-phase extraction cartridges (LiChrolut Si 60,
Merck). Thereafter, samples underwent mild alkaline methanolysis and the free methyl esters of phospholipid fatty acids
were analysed by gas chromatography–mass spectrometry (GC–
MS; 450-GC, 240-MS ion trap detector, Varian, Walnut Creek,
CA).
The PLFA i14:0, i15:0, a15:0, 16:1ω9, 16:1ω7, 16:1ω5, 10Me16:0, i17:0, a17:0, cy17:0, 17:0, 10Me-17:0, 10Me-18:0 and cy19:0
were addressed as bacterial signature markers (B). The PLFA
10Me-16:0, 10Me-17:0 and 10Me-18:0 were used as actinobacterial signature markers (Act). The fatty acid 18:2ω6, 9 was selected as fungal signature marker (F). The fatty acids found both
in bacteria and fungi, such as 15:0, 16:0 and 18:1ω7, were excluded from the analysis (Tornberg, Bååth and Olsson 2003).
The total content of PLFA was used as a measurement of total microorganisms. Ratios between PLFA signature markers
derived from fungi and bacteria (F/B) as well as Actinobacteria and bacteria (Act/B) were calculated (Moore-Kucera and
Dick 2008).
Statistical analyses
All parameters determined in this study were analysed in each
of the eight soil samples collected per site in spring and in autumn. Multifactorial ANOVA (MANOVA) was applied to determine whether the sampling site, the sampling season and/or
the incubation temperature (for respiration, enzymatic activities and CLPP) had a significant (P ≤ 0.05) effect on the investigated soil parameters. Normal distribution and heteroscedasticity of data were tested by the Shapiro–Wilk and Breusch–Pagan
tests, respectively. Tukey’s honest significance difference (HSD)
post-hoc test was used for multiple comparisons of means at
a 95% confidence interval. For these analyses, the program Statgraphics Centurion XVI was used. Non-metric multidimensional
scaling (NMDS) analysis was used as an ordination method to
reduce the multiple dimensions in PLFA markers data and visualize patterns in soil samples over the altitudinal gradient in
both seasons using Statgraphics Centurion XVI software. Twoway Permutational Analysis of Variance (PERMANOVA) was used
to test the significance of altitude, season and their interaction
effect on soil microbial community structure using PLFA markers with Euclidean distances and 9999 permutations by means
of PAST program ver. 3.06 (Hammer, Harper and Ryan 2001). Linear regression analysis (Pearson method) was performed to determine if there were significant (P ≤ 0.05) correlations between
the parameters investigated in this study also using Statgraphics Centurion XVI.
Table 1. Mean (Tmean ), maximum (Tmax ) and minimum (Tmin ) annual
soil temperatures (◦ C) at the studied sites during the period of investigation (May 2014 to April 2015). For ANOVA analysis, P-values in
bold denote statistical significance (P ≤ 0.05); for Tukey’s HSD tests,
mean values followed by different letters are significantly different.
Factor
SITE (SI)
P-value
Post-hoc
M
K
R
S
Tmean
<0.0001
9.8b
9.3b
4.3a
3.9a
Tmax
0.0001
13.5b
12.7b
6.1a
6.2a
Tmin
<0.0001
6.5b
5.5b
1.9a
1.1a
RESULTS AND DISCUSSION
Soil temperature
Continuous monitoring of soil temperature over one year
demonstrated significantly (P < 0.0001) lower mean annual soil
temperatures at the subalpine and alpine sites (R and S; 4.3◦ C
and 3.9◦ C) than at the sites at lower altitude (submontane and
montane sites M and K; 9.8◦ C and 9.3◦ C) (Table 1). Minimum and
maximum soil temperatures decreased with altitude although
significant differences between M and K and between R and S
were not found (Table 1, Fig. S1, Supporting Information). For
mean, maximum and minimum soil temperature, differences
between the sites at the lowest and the highest altitude were
5.8◦ C, 7.3◦ C and 5.4◦ C, respectively. In comparison, the difference for the mean annual air temperature was 8.6◦ C (see data
site description).
Monthly minimum soil temperatures showed that the sites
R and S at the higher altitudes were exposed to temperatures
of or below 0◦ C between December and April (i.e. five months
per year), while the sites at the lower altitudes reached subzero
temperatures only between December and February or not at all
(Fig. S1, Supporting Information). The highest maximum temperatures were detected in summer between June/July and August and reached ca. 16–20◦ C at the lower (M, K) and ca. 12–13◦ C
at the higher altitude (R, S). Mean monthly soil temperatures
above 10◦ C were recorded at sites M and K almost half of the
year (six and five months, respectively), while sites R and S were
exposed to temperatures close to 10◦ C only two months of the
year.
Soil temperature has been recognized as one of the most
important factors determining soil dynamics and properties
at regional scale (Zhou et al. 2015). According to Salinas et al.
(2011), soil temperature explained 95% of the litter decomposition variation rate over an altitudinal gradient. On the other
hand, changes in soil temperature along altitudinal gradients
are a consequence of factors physically tied to meters above sea
level (e.g. atmospheric pressure, temperature and clear-sky turbidity) and of factors which are not generally altitude-specific,
such as precipitation, wind velocity or seasonality, site topography, soil water content and texture, and the area of surface
covered by litter and canopies of plants (Paul et al. 2004; Körner
2007). Thus, although generally an increase in altitude is related to a decrease in soil temperature, the soil temperature decrease rate over the gradient investigated in this study could not
be lineal due to the unequal variation of the aforementioned
factors.
Siles et al.
5
Table 2. Results of MANOVA and post-hoc analyses on the effect of site and season and their interactions on physicochemical soil properties
determined over the altitudinal gradient studied. For MANOVA analyses, P-values in bold denote statistical significance (P ≤ 0.05); for Tukey’s
HSD tests, mean values followed by different letters are significantly different (P ≤ 0.05).
Factor
SITE (SI)
P-value
Post-hoc
M
K
R
S
SEASON (SE)
P-value
Post-hoc
Spring
Autumn
SI × SE
P-value
pH
ECa
Humusb
TOCb
Nb
C/N
Pc
Kc
Mgc
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
0.0003
<0.0001
0.0001
4.6c
4.1b
3.4a
4.2b
159a
296a
487b
552b
19.4a
44.1b
50.4b
56.9b
12.0a
27.7b
32.6b
36.1b
0.6a
0.8a
1.3b
1.3b
19.8a
29.2c
22.9a,b
24.9b
24.8a
39.8a,b
51.4b
59.5b
119a
344b
394b
472b
219a
307a,b
238a
402b
0.8774
<0.0001
0.0409
0.0007
0.0071
0.9496
0.2166
0.4154
0.109
4.1a
4.1a
262a
486b
38.1a
47.3b
22.2a
32.1b
0.9a
1.1b
24.2a
24.2a
40.4a
47.3a
313a
351a
268a
315a
0.7202
0.9924
0.9335
0.6583
0.8793
0.9654
0.8294
0.5383
0.9921
EC, electrolyte concentration, expressed as mg KCl (kg soil dm)−1 .
For post-hoc tests, the values are expressed as %.
c
For post-hoc tests, the values are expressed as mg (kg soil dm)−1 .
a
b
Soil physicochemical properties
All four sites over the altitudinal gradient were SW exposed, contained the same bedrock (rhyolite) and were carbonate-free. Altitude had a significant (P < 0.001) effect on all soil physicochemical properties investigated (Table 2). The four sites presented a
low pH and significant differences were found between the sites
(P < 0.0001); the highest pH (4.6) was found at site M, while the
most acidic pH (3.4) was detected at site R. These differences are
most likely related to the different nature of litter in the different zones; previous studies have demonstrated that spruce litter
(highly present at site R) tends to increase soil acidity (Berger and
Berger 2012).
Significantly increased (P < 0.001) values with altitude were
found for EC (ca. 3.5-fold), SOM (humus; ca. 3-fold from 19% to
57%), TOC and other nutrient contents (Table 2). We explain the
increasing SOM content with altitude with the higher recalcitrance of coniferous litter, which results in the accumulation of
high amounts of organic matter in the Ah horizon (C sequestration). In this line, previous works have indicated that soil organic
carbon concentrations and/or stocks increased with decreasing
temperatures (Zehetner, Miller and West 2003; Kane et al. 2005).
Berger et al. (2015) also demonstrated in a litter incubation experiment over an elevational gradient that altitude retarded decay
of beech and pine litter after one and two years of incubation,
respectively.
With regard to season, there was at all sites a trend of increased nutrient contents in autumn compared to spring; a significant effect (P < 0.05) could be recognized for EC (ca. 2-fold),
humus, TOC and N (by ca. 20%), but not for P, K and Mg (Table 2).
The increase of EC (related to cation exchange capacity, which
increases with high levels of SOM; Smith, Halvorson and Bolton
2002), and nutrients in autumn was expected since this season is
characterized by the enrichment of soil with fresh litter, which is
rich in available nutrients and contains a high C/N ratio (Baldrian
et al. 2013). Values for soil pH and C/N ratio were almost identical
in spring and autumn; thus, the decrease of both N and C contents in spring compared to contents in autumn had no effect
on the C/N ratio.
Regarding the interaction of factors, there were no significant interactions between site (altitude) and season for any of
the properties studied (Table 2).
Soil respiration and potential enzyme activities
Soil respiration and all potential enzyme activities analysed in
this study (and expressed on a soil dm basis) significantly varied
with altitude (Table 3); specifically, microbial activities increased
with altitude. These increases were in the range of 1.7-fold (sulphatase) to 4.8-fold (ß-glucosidase). Highly significant correlations of soil respiration and most of the investigated potential
enzyme activities with SOM and other nutrients at each site, in
both seasons, and determined at the lowest and at the highest incubation temperatures, clearly demonstrated the impact
of SOM on soil microbial activities (Tables S1 and 2, Supporting Information). Except for xylanase activity, the highest levels
for respiration and enzymes were detected at the alpine site S
(Table 3). At a first glance, this finding seems to be contradictory
to other studies which reported a decrease of soil enzyme activities and respiration with increasing altitude (Schinner 1982;
Xu et al. 2014). However, this apparent contradiction can be explained by the SOM content (and the significant correlation between activities and SOM content; Tables S1 and 2, Supporting
information), which significantly increased with altitude (by a
factor of ca. 3) in our study, in contrast to some other studies.
Xu et al. (2014) detected no elevational trend in soil organic C
in forest soils up to the tree line and even above. Forest soils
investigated by Niklińska and Klimek (2007) along an altitudinal
gradient from 600 to 1200 m had SOM contents between 72% and
78% (i.e. the SOM content at the highest altitude was only higher
by ca. 10% than that at the lowest altitude) and respiration rates
on some mountain peaks did not decrease with altitude. Schinner (1982) reported higher SOM contents and xylanase activity
in Alpine soils at 1920 m compared to 1560 m in the period from
July to October, and the same was observed for respiration in autumn; only at higher elevation above the tree line (2550 m) both
SOM and activities decreased. The lower soil microbial activities
6
FEMS Microbiology Ecology, 2016, Vol. 92, No. 3
Table 3. Results of MANOVA and post-hoc analyses on the effects of site (altitude), season, assay incubation temperature and their interactions
on soil respiration (RES), acid phosphatase (PHO), sulphatase (SUL), protease (PRO), β-glucosidase (GLU), xylosidase (XYL) and cellobiohydrolase
(CBH) activities. For MANOVA analyses, P-values in bold denote statistical significance (P ≤ 0.05); for Tukey’s HSD tests, mean values followed
by different letters are significantly different (P ≤ 0.05).
Factor
SITE (SI)
P-value
Post-hoc
M
K
R
S
SEASON (SE)
P-value
Post-hoc
Spring
Autumn
TEMPERATURE (T)
P-value
Post-hoc
0◦ C
10◦ C
20◦ C
30◦ C
40◦ C
SI × SE
P-value
SI × T
P-value
SE × T
P-value
SI × SE × T
P-value
RESa
PHOb
SULc
PROd
GLUc
XYLc
CBHc
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
215a
489b
532b
718c
18a
37b
57c
65c
149a
129a
207b
253b
415a
576a
598a
975b
204a
522b
666b
996c
58a
132b
180b
166b
69a
176b
190b
268c
0.0013
0.1882
0.8033
0.0607
0.1302
0.0517
0.2995
416.19a
560.44b
42a
46a
186a
183a
570a
712a
542a
652a
121a
147a
184a
167a
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
62 a
216a
603b
1073b
n. d.e
n. d.
21a
35b
n. d.
77c
n. d.
56a
97b
n. d.
402c
n. d.
105a
316a
n. d.
1502b
n. d.
139a
270a
n. d.
1381b
n. d.
26a
53a
n. d.
323b
n. d.
n. d.
36a
n. d.
316b
0.6470
0.0475
0.1631
0.1894
0.5151
0.0571
0.8095
<0.0001
<0.0001
<0.0001
0.0001
<0.0001
<0.0001
<0.0001
0.0233
0.0063
0.1869
0.0181
0.0998
0.0347
0.2746
0.9997
0.0406
0.9612
0.1380
0.8154
0.5313
0.6482
For post-hoc tests, the values are expressed as O2 (g soil dm)−1 (24 h)−1 .
For post-hoc tests, the values are expressed as μMOL pNP (g soil dm)−1 (1 h)−1 .
c
For post-hoc tests, the values are expressed as μg pNP (g soil dm)−1 (1 h)−1 .
d
For post-hoc tests, the values are expressed as μg tyr (g soil dm)−1 (2 h)−1 .
e
n. d., not determined.
a
b
and abundance at site R compared to site M in a long-term study
over 17 yr (Margesin, Minerbi and Schinner 2014) were due to
the fact that in that study data were calculated on a SOM basis and not on a dm basis, as it was done in the present study.
As previously described, SOM content is the major determinant
of the level and activity of soil enzymes (Štursová and Baldrian
2011; Wallenius et al. 2011). Several reports associated with the
accumulation of high SOM contents at high altitudes with low
microbial activities and biomass (Gavazov 2010 and references
therein). We hypothesize that the high SOM content at high altitudes could be a consequence of an excess amount of recalcitrant (coniferous) litter (Rapp and Leonardi 1988), which accumulates in the Ah horizon mainly because of its recalcitrance
and not because of low microbial activity and/or abundance.
Regarding season, there was a trend of increased (soil dm
related) soil microbial activities (except sulphatase and cellobiohydrolase) in autumn compared to spring; however, a
significant seasonal effect (P < 0.05) was only detected for respiration (increase by 30%; Table 3). The high variability between
soil samples at each site, as a consequence of high diversity
of soil microsite conditions (Smith, Marin-Spiotta and Balser
2015), may have interfered with the detection of a significant
effect of season on soil enzyme activities. Higher microbial activities in autumn than in spring could be related to the enrichment of L and H horizons with fresh litter and the subse-
quent leaching of nutrients and compounds from these horizons to the Ah horizon (sampled in this study) and deeper horizons by the effect of rain. The significantly higher respiration
and the tendency in increased enzyme levels in autumn compared to spring is also seen as a consequence of the vegetation period of plants. The increase in plant photosynthesis during spring and summer is associated with the deposition of
easily decomposable compounds in the soil (Ekblad and Hogberg 2001). These compounds likely remain in soil after the end
of vegetation period during the first months of autumn and
can be used by microorganisms. This also explains the significantly higher EC values detected in autumn compared to spring
(Table 2).
Since soil enzyme production is linked to soil microbial
biomass, we expressed the activities measured in this study
not only on a soil dm basis (Table 3), but also on a biomass
proxy, using total PLFA contents as a measurement of total
microorganisms (for PLFA data, see below). PLFA-related data
(Table S7, Supporting information) showed a site-specific effect of enzyme production. While respiration as well as activities of sulphatase and protease produced per biomass proxy
unit were highest at the site M (in opposite to soil dm-related
data), ß-glucosidase production was highest at site S (in agreement with soil dm-related data). A significant seasonal effect was detected for all activities except ß-glucosidase and
Siles et al.
7
Table 4. Results of MANOVA and post-hoc analyses on the effects of site (altitude), season, assay incubation temperature and their interactions
on CLPP C-source families and functional diversity properties. For MANOVA analyses, P-values in bold denote statistical significance (P ≤ 0.05);
for Tukey’s HSD tests, mean values followed by different letters are significantly different (P ≤ 0.05).
Factor
SITE (SI)
P-value
Post-hoc
M
K
R
S
SEASON (SE)
P-value
Post-hoc
Spring
Autumn
TEMPERATURE (T)
P-value
Post-hoc
0◦ C
10◦ C
20◦ C
30◦ C
SI × SE
P-value
SI × T
P-value
SE × T
P-value
SI × SE × T
P-value
a
b
Amines/amidesa
Amino acidsa
Carbohydratesa
Car/ace acidsa , b
Polymersa
Richness
Shannon
Evenness
<0.0001
<0.0001
0.0020
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
0.68c
0.48b
0.26a
0.48b
2.40b
2.71b
1.53a
2.44b
2.72a
2.99a
3.93b
2.82a
2.67b
2.40b
1.17a
2.91b
1.54a
1.43a
3.11b
1.35a
22.58b
25.92c
18.13a
24.38b,c
2.63b
2.76b
2.22a
2.79b
0.85b
0.85b
0.79a
0.88b
0.5840
0.6930
0.6840
0.1660
0.0270
0.0363
0.5360
0.0221
0.49a
0.46a
2.24a
2.30a
3.07a
3.16a
2.16a
2.41a
2.05b
1.67a
23.56b
21.94a
2.58a
2.62a
0.83a
0.86b
0.8920
0.1320
0.0220
0.0480
<0.0001
<0.0001
0.0407
0.4142
0.46a
0.45a
0.51a
0.47a
2.50a
2.21a
1.98a
2.40a
2.70a
2.86a,b
3.22a,b
3.67b
1.90a
2.35a,b
2.30a,b
2.59b
2.44b
2.13b
1.98b
0.88a
20.04a
22.92b
25.79c
22.25a,b
2.51a
2.64a,b
2.74b
2.52a
0.85a
0.85a
0.84a
0.82a
0.0140
0.0570
0.9880
0.3860
0.0010
0.0270
0.1098
0.2152
0.4930
0.0590
0.9610
0.0290
0.0070
0.0156
0.0759
0.7119
0.4990
0.1710
0.9940
0.6070
0.3080
0.4103
0.9329
0.5017
0.2020
0.6540
0.3230
0.4120
0.4390
<0.0001
0.0006
0.1200
For post-hoc tests, the values are expressed as AWCD.
Carboxylic and acetics acids.
xylosidase, showing higher enzyme production per biomass
proxy unit in spring than in autumn. There was also a significant effect of the interaction between site and season.
These data show that differences in enzyme production are
partly responsible for the observed site- and season-specific
differences.
Soil microbial activity is, among others, governed by temperature and climate conditions (altitudinal and seasonal impacts). Therefore, we considered the effect of temperature on
microbial activities in this study by performing activity measurements at various incubation temperatures. Generally, temperature increases the rates of enzyme reactions as long as the
stability of a particular enzyme is not affected. The activity of
several forest soil hydrolytic and oxidative enzymes increased
with temperature (Baldrian et al. 2013). In our study, increased
incubation temperatures resulted in a significant effect on soil
microbial activities, independent whether expressed on soil dm
basis (Table 3) or on total PLFA basis (Table S7, Supporting information). The highest activities were generally detected at
the highest temperatures tested (30◦ C for respiration, 40◦ C for
enzymes).
The combination of site and incubation temperature for the
measurement of soil microbial activities produced a significant
(P < 0.0001) effect on (soil dm-related) soil respiration and all
measured potential enzyme activities (Table 3), and partly also
on activities related to total PLFA contents (Table S7, Supporting information). This interaction clearly indicates differences
in microbial communities and their responses to temperature
among sites.
Community level physiological profiles
The relative oxidation rate of the five C-source families
(amines/amides, amino acids, carbohydrates, carboxylic/acetic
acids and polymers), which comprised the 31 C-sources of Biolog EcoPlates, significantly varied over the altitudinal gradient
(Table 4). Amines and amides were preferably oxidized at site M
(the site at the lowest altitude), while site R (the subalpine site)
presented the lowest consumption rate of this group. In the case
of amino acids and carboxylic/acetic acids, the lowest oxidation
rate was detected at site R; the values obtained at the other three
sites were significantly higher than those at site R but did not
significantly differ from each other. In contrast, carbohydrates
and polymers were oxidized to a significantly higher extent at
site R than at the other three sites, which did not significantly
differ in their consumption rate. Season exerted a significant effect only on polymer utilization; C-sources of this group were oxidized to a higher extent in spring than in autumn (Table 4). We
explain this by the preference of microorganisms to use polymers in spring compared to autumn, since these compounds
are most likely more abundant in spring as a result of the predecomposition of litter in late autumn and winter. Clearly, the
site showing the most different CLPP compared to the other sites
was the subalpine site R, characterized by a higher consumption of polymers and carbohydrates and a lower consumption of
amines/amides, amino acids as well as carboxylic/acetic acids.
Previous studies have shown that amines/amides and amino
acids utilization was lowest in soils with high contents of organic nitrogen (Klimek et al. 2015). We did not detect a higher
8
FEMS Microbiology Ecology, 2016, Vol. 92, No. 3
Table 5. Results of statistical MANOVA and post-hoc analyses on the effect of site (altitude), season and their interactions on PLFA parameters.
For MANOVA analyses, P-values in bold denote statistical significance (P ≤ 0.05); for Tukey’s HSD tests, mean values followed by different letters
are significantly different (P ≤ 0.05). For post-hoc tests, the values are expressed as μg PLFA (g soil dm)−1 . F, fungi; B, bacteria; Act, Actinobacteria.
Factor
SITE (SI)
P-value
Post-hoc
M
K
R
S
SEASON (SE)
P-value
Post-hoc
Spring
Autumn
SI × SE
P-value
PLFA
PLFA ratio
total
F
B
Act
F/B
Act/B
0.0001
0.0034
<0.0001
<0.0001
0.0002
0.0010
5.51a
13.59b
16.97b
17.14b
0.44a
2.89b
2.76b
2.35b
2.44a
4.66a,b
7.09b
6.99b
0.30a
0.54a,b
0.99c
0.63b
0.19a
0.53b
0.35a,b
0.28a
0.14b
0.12a,b
0.14b
0.10a
0.0194
0.0469
0.0154
0.1037
0.2233
0.0539
11.08a
15.52b
1.60a
2.62b
4.47a
6.13b
0.55a
0.67a
0.31a
0.37a
0.13a
0.12a
0.2972
0.213
0.2747
0.1088
0.3723
0.9858
total N-content at site R than at the other sites; however, we did
not determine organic N in this study.
In accordance with soil respiration and enzyme activities, we
determined the effect of incubation temperature (0◦ C–30◦ C) on
CLPP. The incubation temperature did not have a significant effect on the oxidation rate of amines/amides and amino acids.
Conversely, oxidation of carbohydrates and carboxylic/acetic
acids increased with increasing temperatures. The highest
AWCD values for these two groups were obtained at 30◦ C. Polymer oxidation also was affected by temperature; in this case,
AWCD values were significantly lower at 30◦ C than at 0–20◦ C.
This pattern in the use of different C-sources could be a consequence of the quick growth rates of microorganisms at higher
temperatures and could also point to different communities
with different substrate specificities and growth rates.
Diversity parameters of substrate utilization (richness, Shannon diversity index, evenness) were also affected by altitude
(Table 4). All three parameters were significantly lowest at site
R, indicating the utilization of a lower number of substrates
and a non-homogeneous distribution of substrate oxidizers at
this site. The lower functional diversity at site R compared to
the other sites (where values for Shannon index and evenness
were not significantly different) indicates a higher specialization of soil microorganisms at site R in the use of C-sources
(as shown above, towards the use of complex C-sources such as
polymers). This coincides with results from a long-term study on
litter degradation (Margesin, Minerbi and Schinner 2016), where
a high decomposition potential of coniferous litter was detected
at site R. SOM resource (quality and quantity) plays an important
role in determining soil microbial functional diversity (Tian et al.
2015).
With regard to season, Shannon index did not change significantly between spring and autumn at the four sites; however, richness was higher in spring over the altitudinal gradient,
which indicates a higher catabolic capacity of the soil microbial
community in this season. Regarding incubation temperature,
the highest richness and Shannon index values were detected
after incubation at 20◦ C. On the other hand, no changes in evenness were detected between 0◦ C and 30◦ C. Several of the factor interactions (site and season; site and incubation temperature; site, season and temperature) were significant for richness
(Table 4).
Microbial abundance and community structure
Altitude had a significant effect on all the PLFA markers determined in this study (total soil microorganisms, fungi, bacteria
and actinobacteria; Table 5). The lowest amounts of microbial
PLFA were found at site M at the lowest altitude, and no significant differences were found between the other three sites, except for actinobacterial PLFA. In absolute values, the amounts of
total PLFA found at sites K, R and S were 2.4–3.1-times higher
than those found at site M. Furthermore, total and signature
PLFA were significantly positively correlated with SOM (2.3–2.9fold higher at sites K, R and S than at site M) and nutrient contents in spring and autumn (Tables S3 and 4, Supporting Information). The availability of organic resources is regarded as
one of the most important factors in influencing soil microbial
biomass. Many previous studies on soil forests have reported
positive correlations between bacterial and fungal PLFA markers
and C- and N-pools (e.g. Wagai et al. 2011; de Vries et al. 2012). In
contrast to the present results, Margesin et al. (2009) described a
decrease in microbial PLFA with increasing altitudes in another
Alpine gradient, but in that study soils above the tree line (2300–
2530 m) were included which contained a lower SOM content
that those at lower altitudes.
Bacterial and fungal PLFA markers were significantly higher
in autumn than in spring (Table 5), which is seen, as previously commented, as a result of the microbial stimulation by the
leaching of nutrients and compounds from the upper soil horizons after litterfall and/or the deposition of easily decomposable
compounds from roots in soil after the end of the vegetation period. This was evidenced by a higher SOM content in autumn
than in spring.
To determine whether soil microbial community structure
varied with altitude and/or season, we analysed the ratio between fungal and bacterial signatures (F/B), which did not
change significantly between seasons, and there was no significant effect of altitude. The large variation between samples may
have interfered with the detection of a significant effect of altitude. Interestingly, the ratio F/B was clearly highest at site K
(more than threefold higher than at site M), which matched perfectly with the C/N ratio at these sites, being also highest at
site K and lowest at site M and not being affected by season
(Table 2). Other surveys of elevational gradients reported an
Siles et al.
9
Figure 1. Non-metric multidimensional scaling (NMDS) ordination of soil microbial community structure based on PLFA datasets determined at site M (545–570 m), K
(1175–1200 m), R (1724–1737 m) and S (1965–2000 m) in spring and autumn.
increase in the F/B ratio with altitude (Margesin et al. 2009; Zhang
et al. 2013; Xu et al. 2015), which was attributed to the better
adaptation of fungi to cold conditions (Robinson 2001; Margesin
2009). According to our study, the C/N ratio had a higher impact
on the increase of the fungal community than other factors investigated in this study. This was also evidenced by a significantly positive correlation between the F/B ratio and soil C/N in
autumn (Table S4, Supporting Information). Likewise, it is known
that fungi are better adapted to environments containing high
C/N ratios (Xu et al. 2015). However, changes in litter and SOM
quality also may affect fungal communities. Within the bacterial community, actinobacterial PLFA markers (Act/B) increased
(more than threefold) with altitude, but were not affected by
season.
Two-way PERMANOVA analysis of PLFA markers confirmed
that both altitude (P = 0.0002) and season (P = 0.0262), but not
their interaction (altitude × site; P = 0.3079), exerted a significant
effect on soil microbial community structure. These results were
corroborated by NMDS analysis, which clustered the soil samples according to the site they belong to and evidenced a seasonal effect, especially on sites M and K (soil samples from sites
M and K in autumn, and spring were separated by NMDS coordinate 2 and 1, respectively) (Fig. 1). Xu et al. (2015) also detected,
using PLFA, significant differences in the structure of forest soil
microbial community over an altitudinal gradient in China. Unfortunately, there are no previous studies assessing the effect of
season on the forest soil microbial community structure along
altitudinal gradients for comparison. On the other hand, the seasonal effect detected in our study was expectable since there are
many season-dependent abiotic parameters (e.g. soil temperature and moisture), changing with season, as well as shifts in
vegetation cover that influence the input of organic matter and
N in soil, which altogether, could influence the microbial community structure (Corneo et al. 2013).
Correlations
Respiration, potential phosphatase and potential ß-glucosidase
activity at the different incubation temperatures correlated sig-
nificantly and positively with the signature PLFA of fungi, bacteria and actinobacteria (except for ß-glucosidase activity in autumn) in both seasons, indicating that soil microorganisms were
actively involved in the heterotrophic metabolism in both seasons. A trend for correlation with microbial abundance was also
visible for the other potential enzyme activities determined in
this study. Sulphatase activity correlated predominantly with
actinobacterial PLFA signatures in both seasons, which could
be an indication of the active involvement of Act in S-cycling.
Indeed, sulphatase-producing actinobacteria are widespread in
soils (Paul 2015). In comparison, actinobacterial PLFA markers
were correlated with ß-glucosidase activity only in spring and
not in autumn. Proteolytic fungi could be involved in N-cycling
in spring, as shown from significant correlations between fungal
PLFA and proteolytic activity (Table S3, Supporting information).
Correlations between soil temperature and soil physicochemical properties (including values obtained at all four sites
and in both seasons) revealed a significantly negative effect of
increasing mean, minimum and maximum soil temperatures on
EC and nitrogen contents; P-content was negatively correlated
with minimum soil temperature (Table S5, Supporting information). Interestingly, no significant correlations between soil
temperatures and microbial activities were found, except for
phosphatase activity which was inversely related to P-content
(Table S5, Supporting information). Also total microbial abundance and community structure (ratios between different microbial groups) were not significantly affected by soil temperature, whereas the PLFA of bacteria were inversely related to the
minimum soil temperature. As mentioned before, correlations
of soil nutrients with microbial activities and microbial PLFA
were significantly positive at all four sites and in both seasons
(Tables S1–4 and S6, Supporting information). Thus, the correlations demonstrated that the effect of nutrients was stronger
than the effect of soil temperature on microbial activities. Only
few studies considered the effect of soil temperature on soil microbial activities and abundance (Baldrian et al. 2013; Xu et al.
2015). While Baldrian et al. (2013) reported an increase in forest
soil microbial activity with increasing soil temperature, Xu et al.
(2015) found significant correlations of soil temperature with soil
10
FEMS Microbiology Ecology, 2016, Vol. 92, No. 3
nutrients but not with soil microbial activities, which was corroborated by this study.
CONCLUSIONS
The data from our study on abiotic and biotic soil properties
at four forest sites along an altitudinal gradient up to the tree
line, determined in two seasons (spring and autumn), demonstrated an increase in SOM and nutrient contents with altitude,
with a rise in these levels in autumn compared to spring. The increased amounts of nutrient resources resulted in significantly
increased microbial activities and (bacterial and fungal) abundance at higher altitudes. The correlations between soil nutrients and microbial activities and abundance were significantly
positive, and the effect of nutrients on activities was stronger
than the effect of soil temperature. Thus, the SOM increase
with altitude drives the differences in soil microbial activity,
abundance and community structure along the studied altitudinal gradient, contrary to the assumption that low-temperatures
limit abundance and activity at high altitudes. Nonetheless,
temperature is linked to altitude and affects the quantity and
quality of soil nutrients through differences in vegetation and
litter and has thus both direct and indirect effects on soil microbial communities. In addition, the observed site- and seasonspecific differences in soil microbial activities could be partly attributed to differences in enzyme production.
Microbial community structure was influenced by altitudinal, seasonal and/or site-specific effects. The significant interaction of the factors site and incubation temperature for soil microbial activities indicates differences in microbial communities
and their responses to temperature among sites.
Site-specific conditions played a major role. The CLPPderived microbial community at the subalpine site R was more
specialized compared to communities at the other three sites.
At site K, the soil C/N ratio was of higher importance for fungal
PLFA signatures than altitude or season.
Finally, we like to note that our study focused on forest soils
up to the tree line and not above. Care has to be taken when comparing results obtained from different altitude gradients; factors
such as soil SOM, nutrients, vegetation type and tree line should
always be taken into account.
SUPPLEMENTARY DATA
Supplementary data are available at FEMSEC online.
ACKNOWLEDGEMENTS
We thank J. Mair, F. Reischer and K. Weber (University of Innsbruck) for technical assistance and F. Schinner (University of
Innsbruck) for his help with soil sampling and useful discussions.
FUNDING
This work was supported by a grant of the Autonomous
Province of Bozen/Bolzano, South Tyrol, Promotion of Educational Policies, University and Research Department (Grant
number 15/40.3).
Conflict of interest statement. None declared.
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