The colonization by a large number of sea animals, including penguins and
seals, plays an important role in the nitrogen cycle of the tundra ecosystem
in coastal Antarctica. However, little is known about the effects of sea
animal colonization on ammonia-oxidizing archaea (AOA) and bacteria (AOB)
communities involved in nitrogen transformations. In this study, we chose
active seal colony tundra soils (SSs), penguin colony soils (PSs), adjacent
penguin-lacking tundra soils (PLs), tundra marsh soils (MSs), and background
tundra soils (BSs) to investigate the effects of sea animal colonization on
the abundance, activity, and diversity of AOA and AOB in maritime
Antarctica. Results indicated that AOB dominated over AOA in PS, SS, and PL, whereas AOB and AOA abundances were similar in MS and BS. Penguin or seal
activities increased the abundance of soil AOB amoA genes but reduced the
abundance of AOA amoA genes, leading to very large ratios (1.5×102 to 3.2×104) of AOB to AOA amoA copy numbers. Potential
ammonia oxidation rates (PAORs) were significantly higher (P=0.02) in SS
and PS than in PL, MS, and BS and were significantly positively correlated
(P<0.001) with AOB amoA gene abundance. The predominance of AOB over
AOA and their correlation with PAOR suggested that AOB play a more important
role in the nitrification in animal colony soils. Sequence analysis for gene
clones showed that AOA and AOB in tundra soils were from the
Nitrososphaera and Nitrosospira lineages, respectively. Penguin or seal activities led to a
predominance of AOA phylotypes related to Nitrososphaera cluster I and AOB phylotypes
related to Nitrosospira clusters I and II but very low relative abundances in AOA
phylotypes related to cluster II, and AOB phylotypes related to clusters III
and IV. The differences in AOB and AOA community structures were closely
related to soil biogeochemical processes under the disturbance of penguin or
seal activities: soil C : N alteration and sufficient input of
NH4+–N and phosphorus from animal excrements. The results
significantly enhanced the understanding of ammonia-oxidizing microbial
communities in the tundra environment of maritime Antarctica.
Introduction
Nitrification, the oxidation of ammonia to nitrate through nitrite, plays
a pivotal role in the global biogeochemical nitrogen cycle (Nunes-Alves,
2016). As the first and rate-limiting step of nitrification, ammonia
oxidation (the aerobic oxidation of ammonia to nitrite) is performed by
phylogenetically and physiologically distinct groups of ammonia-oxidizing
archaea (AOA) and ammonia-oxidizing bacteria (AOB) (Belser and Schmidt,
1978; Könneke et al., 2005). AOA and AOB have been investigated
using the amoA gene as a functional marker in a wide variety of environments,
including soils (Di et al., 2009; Gubry-Rangin et al., 2017; Leininger et
al., 2006; Ouyang et al., 2016; Shen et al., 2012), sediments (Li et al.,
2015; Zheng et al., 2013), estuaries (Dang et al., 2008; Mosier et al.,
2008; Santoro et al., 2011), the oxic and suboxic marine water column (Baker et
al., 2012; Bouskill et al., 2012), plateau permafrost (Zhang et al., 2009;
Zhao et al., 2017), and in subarctic and arctic soils (Alves et al., 2013;
Daebeler et al., 2017). Results indicated that the relative abundance and
functional importance of AOA vs. AOB vary greatly in natural ecosystems.
Environmental drivers, including substrate concentration, oxygen
availability, pH, and salinity, might be responsible for the different AOA
and AOB abundances and distribution (Alves et al., 2013; Bouskill et al.,
2012; Le Roux et al., 2008; Wang et al., 2015). The abundance, diversity,
and activity of ammonia oxidizers have been explored in tundra soils of the
Antarctic Peninsula (Jung et al., 2011; Yergeau et al., 2007) and the Antarctic
Dry Valleys (Ayton et al., 2010; Magalhães et al., 2014; Richter et al.,
2014) and in Antarctic coastal waters (Kalanetra et al., 2009; Tolar et
al., 2016). However, there is still a large gap in our understanding of
factors that control AOA vs. AOB prominence, and the relationships between
nitrification rates and ammonia-oxidizer dynamics need to be explored in
Antarctica.
In maritime Antarctica, a large number of sea animals, such as penguins or
seals, settle on coastal ice-free tundra patches. Tundra vegetation
including mosses, lichens, and algae, penguin colonies, and their
interactions form a special ornithogenic tundra ecosystem (Tatur et al.,
1997). The soil biogeochemistry of an ornithogenic tundra ecosystem has
become a research hotspot under penguin-activity disturbance (Otero et
al., 2018; Riddick et al., 2012; Simas et al., 2007; Zhu et al., 2013,
2014). Previous studies indicated that sea animals significantly affect the
tundra N and P cycles (Lindeboom et al., 1984; Simas et al., 2007; Zhu et
al., 2011), and the total N and P excreted by seabird breeders and chicks
are 470 Gg N yr-1 and 79 Gg P yr-1 in Antarctica and the Southern
Ocean, accounting for 80 % of the N and P from total global seabird
excreta (Otero et al., 2018). Uric acid is the dominant N compound in
penguin guano, and during its mineralization, different N forms, such as
NH3, NH4+, and NO3-, can be produced via
ammonification, nitrification, and deposition, following the changes in soil
pH and the C : N ratio (Blackall et al., 2007; Otero et al., 2018; Riddick et
al., 2012). The alteration of soil biogeochemistry under the sea-animal-activity disturbance might have an impact on the abundance and
diversity of the AOA and AOB involved in the nitrogen cycle. Increased
bacterial abundance, diversity, and activity have been detected in penguin
or seal colony soils (Ma et al., 2013; Zhu et al., 2015). Penguin or seal
colonies have been confirmed as strong sources for greenhouse gas N2O
(Zhu et al., 2008, 2013), a by-product of microbial ammonia oxidation
(Santoro et al., 2011). However, the effects of sea animal colonization on
AOA and AOB community structures have not been thoroughly investigated in
the maritime Antarctic tundra.
In the present study, we investigated the abundance, potential activity, and
diversity of soil AOA and AOB in five tundra patches, including a penguin
colony, a seal colony, the adjacent animal-lacking tundra, tundra marsh, and
background tundra, where soil biogeochemical properties were subjected to
the differentiating effects of sea animal activities. Our objectives were
(a) to examine the abundance, diversity, and community structure of soil AOA
and AOB using the amoA gene as a functional marker; (b) to investigate potential
links between amoA gene abundance, AOA and AOB community structures, potential
activity, and environmental variables; and (c) to assess the relative
contribution of these two distinct ammonia-oxidizing groups to
nitrification.
Materials and methodsStudy area
The study area is located on the Fildes Peninsula and Ardley Island in the
southwest of King George Island (Fig. 1), having oceanic climate
characteristics. The mean annual air temperature is about -2.5 ∘C,
with a range of daily mean temperature from -26.6 to 11.7 ∘C,
and mean annual precipitation is about 630 mm, mainly in the form of snow.
The Fildes Peninsula (about 30 km2 area) is a host to important sea
animal colonies. Based on annual statistical data, a total of over 10 700
sea animals colonize this peninsula in the austral summer. On the western
coast there are established seal colonies including elephant seal (Mirounga leonine), Weddell seal
(Leptonychotes weddellii), fur seal (Arctocephalus gazella), and leopard seal (Hydrurga leptonyx) (Sun et al., 2004). Ardley Island, with an area of 2.0 km in length and 1.5 km in width, is connected to the Fildes
Peninsula via a sand dam. This island belongs to an important ecological
reserve for penguin populations in western Antarctica. A great majority of
breeding penguins, including Adélie penguins (Pygoscelis adeliae), gentoo penguins
(Pygoscelis papua), and chinstrap penguins (Pygoscelis antarcticus), colonize the east of this island in the
austral summer. Seal excrements or penguin droppings rich in nitrogen and
phosphorus are transported into local tundra soils by ice and snow melting
water during the breeding period (Sun et al., 2000, 2004). Mosses and
lichens dominate local vegetation. However, the vegetation is almost absent
in penguin or seal colonies because of over-manuring and animal trampling.
A more detailed description of the study area can be found in Zhu et al. (2013).
Study area and soil sampling sites. Panel (a): the red dot
indicates the location of the investigation area in maritime Antarctica.
Panel (b): location of the sampling sites on the Fildes Peninsula. The
sampling soils from tundra patches included the active seal colony tundra
soils SS (SS1–5) in the western coast of the Fildes Peninsula and the
background tundra soils on the upland areas (BS1–3). Panel (c): the
location of the sampling sites on Ardley Island. The sampling soils from
tundra patches included the western tundra marsh soils (MS1–5), the eastern
active penguin colony tundra soils PS (PS1–5), and the adjacent
penguin-lacking tundra soils PL (PL1–4). Note: the map was drawn using
CorelDRAW X7 software (http://www.corel.com/cn/, last access: 20 September 2019).
Tundra soil collection
In the summer of 2014/2015, soil samples were collected from the following
tundra patches, as illustrated in Fig. 1.
Penguin colony and penguin-lacking tundra sites: the tundra on Ardley
Island was categorized into three areas from east to west according to
the distance to the penguin nesting sites (i.e., the intensity of penguin
activity) – the eastern active penguin colony with nesting sites, PS (i.e.,
high penguin-activity area), where penguins have the highest density and a high-frequency presence during the breeding period; the adjacent penguin-lacking
tundra areas, PLs (i.e., low penguin-activity areas) in the middle of Ardley
Island, where penguins occasionally wander and have a typically low density;
and the western tundra marsh, MS, moderately far from penguin nesting sites
(i.e., a slight penguin-activity area), where penguins rarely frequent the
sites. In total, 14 soil samples were collected from Ardley Island to
study the effects of penguin colonization on the abundance, activity, and
community structures of soil AOA and AOB. Specifically, samples PS1–PS5
were collected sequentially from the center of the colony in the PS. Samples
PL1–PL4 and MS1–MS5 were randomly collected in the PL and MS.
The
seal colony and its adjacent tundra sites, SSs: these sites are on the
western coast of the Fildes Peninsula. According to the distance to seal
wallows (i.e., the intensity of seal activity), samples SS1–SS5 were
collected in sequence to investigate the effects of seal colonization. Site
SS1 was closest to the seal colony (i.e., a high seal-activity site),
whereas SS5 was the farthest from the seal colony (i.e., a low seal-activity
site).
Background tundra sites, BSs: three soil samples were collected
from an upland tundra at about 40 m a.s.l. and with no sea
animals around. The tundra surface is covered with mosses or lichens with a
10–15 cm organic clay layer (Zhu et al., 2013).
At each sampling site, soil was collected aseptically using a clean scoop
from the top 5–10 cm at the four corners of a 1 m2 subarea, and
combined into one sample. Appropriate precautions were taken to avoid
cross-site or human-made contamination. Immediately after collection, each
sample was divided into two portions: one was stored in sterile plastic
containers at -80 ∘C for the analysis of the microbial
community structures, and the other portion was stored at close to the in situ
temperature to determine the geochemical characteristics and potential
ammonia oxidation rates. All of the analyses were conducted within 1 month.
General analysis of soil characteristics
Soil pH was determined by mixing the soil and 1 M KCl solution (1:3 ratio).
Soil moisture was measured by oven drying at 105 ∘C to a constant
weight. Total carbon (TC), total nitrogen (TN), and total sulfur (TS)
contents in the soils were determined through a CNS (carbon, nitrogen, sulfur) analyzer (vario MACRO,
Elementar, Germany). The samples were digested in Teflon tubes using
HNO3-HCl-HF-HClO4 digestion at 190 ∘C, and total
phosphorus (TP) was determined using ICP-OES (inductively coupled plasma optical emission spectrometer; Perkin Elmer 2100DV, Waltham,
MA, USA). The NO3--N, NO2--N, and NH4+-N
concentrations were determined through a continuous-flow analyzer (Skalar,
Netherlands) (Gao et al., 2018; Zhu et al., 2011).
Measurement of soil potential ammonia oxidation rate
The potential ammonia oxidation rate (PAOR) in tundra soil was determined using
the chlorate inhibition method (Kurola et al., 2005; Xia, 2007). Sodium
chlorate was used to inhibit NO2- from being oxidized
into NO3-. Briefly, 5 g fresh tundra soil was incubated in 20 mL
of 1 mM phosphate-buffered saline with 1 mM of (NH4)2SO4 and
NaClO3 in the dark at 15 ∘C. After moderately shaking for
24 h, the 5 mL of 2 M KCl was used to extract the nitrite. The optical
density for the supernatant after centrifugation was determined
spectrophotometrically at 540 nm. The standard curve obtained from
NaNO2 (0–2.5 µmol L-1) was used to calculate the PAOR in the
tundra soils.
DNA extraction and gene amplification (polymerase chain reaction, PCR)
Genomic DNA was extracted from 0.25 g of homogenized tundra soils using a PowerSoil™ DNA Isolation Kit (Mo Bio, Carlsbad, CA, USA) as
described in the manufacturer's protocol. The extracted DNA was eluted in 50 µL of elution buffer, quantified by a Nanodrop-2000 spectrophotometer
(Thermo Scientific, Waltham, MA, USA), and stored at -20 ∘C.
AOA amoA gene fragments (635 bp) were amplified using the primers Arch-amoAF
(5′-STAATGGTCTGGCTTAGACG-3′) and Arch-amoAR (5′-GCGGCCATCCATCTGTATGT-3′)
(Francis et al., 2005). The amoA gene fragment (491 bp) of β-proteobacterial AOB, which represents known AOB in soil, was amplified
using the primer set composed of amoA-1F (5′-GGGGTTTCTACTGGTGGT-3′) and
amoA-2R (5′-CCCCTCKGSAAAGCCTTCTTC-3′) (Rotthauwe et al., 1997). All PCRs were performed using Taq PCR Master Mix (Sangon Biotech, Shanghai,
China) in a total volume of 50 µL. PCRs were carried out with
a thermal profile of 5 min at 95 ∘C; 35 cycles of 94 ∘C for 30 s, 56 ∘C for AOA or 55 ∘C for AOB for 45 s,
72 ∘C for 1 min; and a final 5 min extension cycle at 72 ∘C (Y. L. Zheng et al., 2014). Subsequently, the amplification products
were visualized by electrophoresis on 1.0 % agarose gels.
Sequencing and phylogenetic analysis
The amplification products were sent to Sangon Company (Shanghai, China) for
purification, cloning, and sequencing (Y. L. Zheng et al., 2014). The sequences
were edited using DNAstar (DNASTAR, Madison, WI, USA) and then aligned by
MUSCLE (Edgar, 2004) using the UPGMB (unweighted pair group method with arithmetic mean) clustering method with the ClustalX program. The
sequences with 97 % identity were grouped into one OTU (operational
taxonomic unit) using the mothur program (version 1.23.0; Schloss et al.,
2009) by the furthest-neighbor approach (Y. L. Zheng et al., 2014). The closest
reference sequences were identified at NCBI
(http://www.ncbi.nlm.nih.gov/BLAST/, last access: 5 August 2018) using the BLASTn tool (Madden, 2002),
and phylogenetic trees were constructed by the neighbor-joining method using
the Molecular Evolutionary Genetics Analysis (MEGA) software (version 5.03,
https://www.megasoftware.net/, last access: 5 August 2018). The sequences reported in this study have
been deposited in GenBank under accession numbers MH318029 to MH318568 and
MH301331 to MH302505.
Quantitative real-time PCR
The AOB and AOA amo A gene copy numbers for tundra soils were determined in
triplicate using quantitative real-time PCR (qPCR) on an ABI 7500 Sequence
Detection System (Applied Biosystems). The specific details were given by
Y. L. Zheng et al. (2014). The strong linear inverse relationship confirmed the
consistency of the qPCR assay between the threshold cycle and the log value
of gene copy numbers (R2=0.997 for AOA; R2=0.999 for AOB).
The amplification efficiencies for AOA and AOB were 99.8 % and 90.4 %,
respectively. Melting curve analysis had only one observable peak at a
melting temperature (Tm) (84.9 ∘C for AOA and 89.6 ∘C
for AOB) (Fig. S1 in Supplement). Negative controls were
subjected to exclude any possible carryover or contamination in all
experiments.
Statistical analysis
The Shannon–Wiener index, Simpson index, and the richness estimator Chao 1
were calculated by the mothur program (version 1.23.0; Schloss et al., 2009).
The coverage was the percentage of the number of observed OTUs divided by
the Chao 1 (Table S1 in the Supplement). The Kruskal–Wallis test and Wilcoxon signed rank
test were conducted for the comparison between amoA gene abundance and PAOR from
five tundra patches using SPSS Statistics 17 (IBM Corp, Armonk, NY, USA).
Correlations between ammonia-oxidizer gene abundance, PAOR and environmental
variables were obtained by Spearman correlation analysis. The relationships
between the ammonia-oxidizer community structure and environmental variables
were explored using canonical correspondence analysis (CCA) in the software
Canoco for windows (version 4.5; Microcomputer Power, Ithaca, NY, USA) because the maximum gradient length of both AOA and β-AOB was longer
than four SD (AOA: 4.406; AOB: 18.326). All environmental parameter values
were transformed into ln(x+1) before statistical analyses. The OTU
richness (defined at 3 % distance) served as the species input, and several
simulations of manual forward selection were performed with 499 Monte Carlo
permutations to build the optimal models. The scaling in the final CCA
biplots was focused on inter-sample relations.
Soil properties, potential ammonia oxidation rates, and ammonia-oxidizer populations for the soil samples (n=22) that span a penguin
colony, a seal colony, and their adjacent animal-lacking tundra across
Ardley Island and the Fildes Peninsula in maritime Antarctica.
Note: ND indicated that the soil sample was not determined. The average value with different superscript letters (a, b or c) indicates a significant difference at P<0.05 between the different patches.
ResultsSoil chemistry and sea animal activities
Almost all the tundra soils were slightly acidic, and the mean pH ranged
from 5.3 to 6.6 at each tundra patch (Table 1). In PS and SS, soil properties including TC, TN, TS, TP,
NH4+-N, and NO3--N levels showed high heterogeneity due
to the deposition of penguin or seal excreta. In the seal colony tundra
soils, the highest TC, TN, TP, TS, and NH4+-N levels occurred at
the sites (SS1–2) close to the seal wallows. In the tundra soils on Ardley
Island, the highest TP, TS, and NH4+-N levels occurred in the
soils close to the eastern penguin nesting sites (PS1-5). PS and SS had
generally lower C : N ratios than PL,
MS, and BS. Soil mean TN, TS, and NH4+–N levels were higher in PS, SS, PL, and MS than in BS.
Soil NH4+–N contents were 1–2 orders of magnitude higher in PS
and SS than in PL, MS, and BS, with means of 176.9 and 137.6 mg
NH4+-N kg-1, respectively. The highest NO3--N
contents occurred in SS. Phosphorus levels were significantly greater (p<0.05) in PS (10.6–32.9 mg g-1) than in other types of tundra
soils (mean < 6.0 mg g-1). Overall, penguin or seal activities
altered the local soil biogeochemical properties through the deposition of
their excreta, leading to generally low C : N ratios in tundra soils.
Gene abundances under sea animal colonization
AOB amoA gene abundances were significantly higher (by approximately 2–4 orders
of magnitude) than AOA amoA gene abundances (Wilcoxon test, n=22, P=0.002) in the penguin and seal colony and the adjacent tundra soils, PS, SS,
and PL. However, amoA gene abundances were similar in the MS and BS soils (Fig. 2a). Overall, the abundances of AOB and AOA amoA genes were significantly
negatively correlated (r=-0.93, P=0.002) across all the tundra
patches (Fig. S2). The AOA amoA gene abundances showed a heterogeneous
distribution in the abundances among the different tundra patches, and they
were 2 orders of magnitude lower in PS and SS relative to those in BS and
MS. Maximum AOA amoA gene abundance appeared in BS, followed by MS and PL,
whereas the PS and SS soils had the lowest AOA amoA gene abundances. The log
values of soil AOA amoA gene abundances showed a significant positive
correlation (r=0.52, P<0.001) with C : N ratios (Fig. 3a), but
their abundances showed a significant negative correlation with
NH4+-N contents (r=-0.52, P=0.013) (Table 2).
Comparisons of soil AOA and AOB amoA gene copy numbers (a), log ratio
of AOB : AOA abundances (b), and potential ammonia oxidation rates (PAORs) (c)
between five tundra patches. The error bars indicate standard deviations of
the means.
Spearman correlations (n=22) among ammonia-oxidizer
populations, the ratios of AOA : AOB abundances, potential ammonia oxidation
rates (PAOR), and environmental variables in the soils of maritime Antarctic
tundra.
Note: significant correlations are indicated by * at the P=0.05 level and
** at the P=0.01 level.
Unlike AOA amoA gene abundances, AOB amoA genes showed the opposite distribution
pattern. AOB amoA gene abundances were significantly higher (by approximately
2–3 orders of magnitude) in PS and SS compared with those in MS and BS
(Fig. 2a). The log values of soil AOB amoA gene abundances showed a significant
negative correlation with C : N ratios (r=-0.71, P<0.001) (Fig. 3b), but their abundances showed a significant positive correlation with
NH4+-N (r=0.53, P<0.05) and TP (r=0.47, P<0.05) (Table 2). The ratios of AOB to AOA amoA copy numbers were
strongly affected by animal activities and were much higher in PS and SS
than in PL, MS, and BS (Fig. 2b; Kruskal–Wallis test, χ2=18.2, P=0.01). Their ratios showed a significant positive correlation with
NH4+-N contents (r=0.62; P<0.01) and TP (r=0.43, P<0.05) (Table 2) but a significant negative correlation with the C : N
ratios (r=-0.79; P<0.001) (Fig. 3c). Overall, penguin or seal
activities, which were indicated by soil C : N ratios, significantly increased
the abundance of soil AOB amoA genes but reduced the abundance of AOA amoA genes,
leading to very large ratios (1.5×102 to 3.2×104) of AOB to AOA amoA copy numbers in PS and SS. However, the ratios
varied only from 0.1 to 7.2 in BS and MS.
Effects of soil C : N alteration on AOA and AOB abundances and
potential ammonia oxidation rates (PAOR) at five tundra patches.
Potential ammonia oxidation rates under sea animal colonization
PAORs ranged from 8.9 to 138.8 µg N kg-1 h-1 in all the soil samples (Table 1). The PAOR was
slightly higher in SS (mean 76.1 µg N kg-1 h-1) than in PS
(mean 64.7 µg N kg-1 h-1) but significantly higher than in
PL, MS, and BS (mean 12.0–21.8 µg N kg-1 h-1). Overall the
PAOR was significantly higher in animal colony soils (mean 70.4 µg N kg-1 h-1 for SS and PS) than in non-animal colony soils (mean
15.7 µg N kg-1 h-1 for PL, MS, and BS; Kruskal–Wallis
test, χ2=11.6, P=0.02) (Fig. 2c). The greatest PAOR occurred at the sites PS1 nearest the penguin nests (88.8±2.7µg N kg-1 h-1) and SS1 close to seal wallows (138.8±0.8µg N kg-1 h-1). The PAOR followed the distribution changes
of AOB amoA gene abundances but showed the opposite trend to the AOA amoA gene
abundances. A significant positive correlation (r2=0.77, P<0.001) was observed between the PAOR and the AOB amoA gene abundance
when the data from all the tundra patches were combined, whereas no
correlation occurred between PAOR and AOA amoA gene abundance (Fig. 4). The
higher abundance of AOB compared to AOA in PS, SS, and PL and their
correlation with the PAOR suggested that AOB populations might contribute
more to the PAOR than the AOA populations in penguin or seal colonies. In
addition, PAOR significantly negatively correlated with soil C : N ratios
(r=-0.73, P<0.001) (Fig. 3d) but significantly positively
correlated with TS contents (r=0.47, P<0.05) and TP contents
(r=0.43, P<0.05) (Table 2).
Correlation between potential ammonia oxidation rates (PAORs) and
AOA and AOB amoA gene copy numbers in tundra soils of maritime Antarctica.
Community structure of AOA and AOB under sea animal colonization
The PCR products were insufficient to construct the clone libraries for the
AOA amoA gene from SS and PS because of the low AOA abundance in the soils, as
was the case with the AOB amoA gene from MS and BS. Overall, 10 AOA and 14 AOB
amoA gene clone libraries were successfully constructed. The 543 AOA sequences
and 1175 AOB quality sequences were generated from the respective sites.
Within each individual site, 1–6 AOA OTUs and 6–15 AOB OTUs were
identified, as defined by < 3 % divergence in nucleotides. The AOA
and AOB OTU numbers for each library are presented in Table S1. These
numbers might be higher if more clones were sequenced, based on the
rarefaction curves (Figs. S3 and S4). AOB amoA gene diversity was generally
higher compared to AOA, based on the indices of Shannon–Wiener and Simpson.
Specifically, AOA amoA gene diversity was higher in PL and MS than in BS,
whereas AOB amoA gene diversity was higher in SS and PS compared with that in
adjacent animal-lacking tundra soils (Table S1).
The 543 AOA amoA gene sequences had 76 %–100 % sequence similarity to each
other and 95 %–100 % identity with the corresponding top hit amoA sequences
deposited in GenBank. Phylogenetic analysis showed that the AOA amoA sequences
were grouped into 16 unique OTUs, representing 100 % of all the AOA amoA OTUs
identified, and these sequences were affiliated with two Nitrososphaera clusters (Fig. 5a): cluster I contained 11 OTUs and 264 clones, and 57.9 % of AOA amoA sequences
were from PL, 41.3 % from SS and only 0.8 % from MS. In cluster II,
there are five unique OTUs and 279 clones, and 58.8 % of them were from
BS, 38.3 % from MS, and only 2.9 % from PL. Almost all the AOA
phylotypes retrieved from PL and SS were related to Nitrososphaera cluster I, whereas the
AOA phylotypes retrieved from MS and BS were distributed in cluster II (Fig. S5a). Seal or penguin activities led to the predominant existence of AOA
phylotypes related to cluster I but very low relative abundances in AOA
phylotypes related to cluster II, which were almost completely excluded in
SS and PL. Almost all AOA phylotypes in BS and MS were related to
Nitrososphaera cluster II, whereas the relative abundances of AOA phylotypes related to
cluster I were very low or undetectable.
The 1175 AOB amoA gene sequences shared 87 %–100 % sequence identity to each
other and 93 %–100 % identity with the closest matched GenBank sequences.
Phylogenetic analysis showed that the AOB amoA sequences could be grouped into
38 unique OTUs, representing 58.5 % of all the AOB amoA OTUs identified, and
they were grouped into four Nitrosospira clusters according to the evolutionary distance
of the phylogenetic tree (Fig. 5b): cluster I contained 11 OTUs and 226
clones, and 67.7 % of AOB amoA sequences were from PS, 23.5 % from SS,
8.4 % from PL, and only 0.4 % from MS. Clusters II and III contained 17
unique OTUs and 521 clones. The sources of the OTUs in cluster II were
similar to those of cluster I, with 69.8 % from PS, 29.9 % from SS, and
0.3 % from PL. For cluster III, 79.2 % of the sequences were from PL,
19.8 % from SS, and 1.0 % from MS. Cluster IV contained nine unique OTUs
and 370 clones from PL (50.0 %), SS (36.8 %), and MS (13.2 %). All the AOB phylotypes retrieved from PS were related to
dominant Nitrosospira clusters I and II, whereas AOB phylotypes related to clusters III
and IV were completely excluded because of penguin colonization (Fig. S5b).
The AOB phylotypes retrieved from SS were distributed in clusters I, II,
III, and IV (16 %–38 % for each cluster). Almost all the AOB phylotypes
retrieved from PL and MS were related to Nitrosospira clusters III and IV.
Neighbor-joining phylogenetic tree of AOA amoA(a) and AOB amoA(b). The
phylogeny is based on nucleotide sequences. Bootstrap values ≥50 %
(of 1000 iterations) are shown near the nodes. GenBank accession numbers are
shown for sequences from other studies. OTUs were defined at 97 %
similarity. Numbers in parentheses following each OTU indicate the number of
sequences recovered from each sampling site.
Relationships of the ammonia-oxidizer community structure with
environmental variables
The relationships of the AOA and AOB communities with environmental
variables were analyzed using CCA. The environmental variables explained
62.1 % of the total variance in the AOA amoA genotype compositions and
71.5 % of the cumulative variance of the genotype-environment
relationships in the first two CCA dimensions (Fig. 6a). Overall, the AOA
community structures significantly correlated with C : N (F=2.59, P=0.022)
and TC (F=2.07, P=0.048) in tundra soils (Table 3), and the combination
of the two factors explained 39.6 % of the variation. High soil C : N and TC
concentrations increased the AOA richness in MS and BS. Although other
environmental parameters, including TP, pH, NH4+-N, and
NO3--N were not statistically significant (P>0.05),
these variables additionally explained 47.3 % of the variation. As
illustrated in Fig. 6b, the first two dimensions explained 26.6 % of the
total variance in the AOB compositions and 54.3 % of the cumulative
variance of the AOB genotype–environment relationships. The composition and
distribution of AOB communities correlated significantly with C : N ratios
(F=1.844, P=0.002) and NH4+-N (F=1.823, P=0.002), and the
two factors combined yielded 21.9 % of total CCA explanatory power. The
others including TP, NO3--N, and pH accounted for 27.1 % of the
variance. Penguin or seal activities significantly increased the AOB
richness in SS and PS through higher NH4+-N and P input from sea
animal excrement, whereas AOB richness was closely related to the soil C : N
in PL and MS.
Canonical correspondence analysis (CCA) ordination plots for the
relationship between the AOA and AOB community structures with environmental
variables. The circles with different colors represent the various sampling
sites. The size of the circles corresponds to the OTU richness in individual
samples. The black triangles represent amoA phylotypes. Environmental variables
are represented by red arrows. The percentage of species–environment
relation variance explained by the two principal canonical axes is
represented close to the axes.
Individual and combined contributions of soil
biogeochemical properties to the AOA and AOB community structures in tundra
patches.
SoilFPIndividualpropertiescontributionAOAC : N2.5930.02221.5 %TC2.0680.04818.0 %NO3--N1.8470.07816.5 %pH1.4580.14413.5 %TP1.0350.40610.5 %NH4+-N0.7310.6227.3 %Combined effect86.9 %of all factorsAOBC : N1.8440.00211.6 %NH4+-N1.8230.00211.5 %TP1.390.0789.1 %pH1.3830.0669.0 %NO3--N1.1610.2587.7 %Combined effect48.9 %of all factorsDiscussionEffects of sea animal colonization on AOA and AOB abundances
In this study, soil AOA amoA gene abundances were 2 orders of magnitude lower
in PS and SS relative to BS and MS; however, AOB amoA gene abundances were
approximately 2–3 orders of magnitude higher in PS and SS than in MS and
BS, indicating that sea animal activities increased the AOB population size but decreased AOA abundances in tundra soils (Figs. 2 and 3). Overall,
the AOA amoA gene abundances obtained here were similar to the abundance range
reported in the soils of the Antarctic Dry Valleys and arctic tundra soils;
however, the AOB amoA gene abundances were 2–3 orders of magnitude
higher in PS and SS than in Antarctic Dry Valleys (Alves et al., 2013;
Magalhães et al., 2014). In contrast to previous studies indicating that
AOA were more abundant than AOB in some terrestrial or marine ecosystems
(Beman et al., 2008; Lam et al., 2007; Wuchter et al., 2006; Yao et al.,
2011) and in soils from the Antarctic Peninsula (Jung et al., 2011), our qPCR
estimates showed that the AOB amoA copy numbers were much greater than those of
AOA amoA in PS, SS, and PL because of sea animal activities. However, their
abundances were very similar to each other in BS and MS. The ratios of AOB
to AOA abundance were strongly affected by sea animal activities, which were
indicated by soil C : N ratios (Fig. 2c). A shift in the relative abundance of
AOA and AOB was recorded previously for the Antarctic Dry Valleys, with a
greater abundance of AOB compared with that of AOA for Battleship Promontory
and Miers Valley and the reverse for upper Wright Valley and Beacon Valley
(Magalhães et al., 2014). The results for PS, SS, and PL are also in
agreement with those detected in subglacial soils (Boyd et al., 2011).
The ratios of AOB to AOA showed significant correlations with C : N,
NH4+-N, and TP when all the data were combined in the five tundra
patches (Table 2). This suggested that C : N, NH4+-N, and TP are key
factors in determining a predominance of AOB over AOA. In Antarctica, the
productivity of terrestrial ecosystems is strongly limited because of the
extremely low nitrogen levels (Park et al., 2007). However, the
physiochemical properties for tundra soils were strongly influenced by the
deposition of penguin or seal excreta under the effects of local microbes (Tatur
et al., 1997). Sea animals provide considerable external N inputs for their
colony soils and adjacent tundra soils through direct input of their excreta
and atmospheric deposition via ammonia volatilization (Lindeboom, 1984; Sun
et al., 2002; Blackall et al., 2007; Zhu et al., 2011; Riddick et al.,
2012). In addition to ammonium, phosphorus can typically be found in penguin
guano (Sun et al., 2000). Generally low C : N ratios and significantly
elevated NH4+–N and TP concentrations occurred in PS and PL due
to penguin or seal activities (Table 1). These conditions allow high
abundance of AOB amoA genes, which explains the strong correlations between AOB
abundances and C : N, NH4+-N, and TP in the sea animal colony soils
(Table 2). This agreed with the high bacterial abundance previously
documented in penguin or seal colony soils and ornithogenic sediments (Ma et
al., 2013; Zhu et al., 2015).
The AOA abundance showed a significant negative correlation with
NH4+-N levels in tundra patches (Table 2), indicating that AOA
might better adapt to low NH4+ and oligotrophic environments
(Martens-Habbena et al., 2009; Stieglmeier et al., 2014). High
NH4+-N concentrations might partially inhibit AOA populations
(Hatzenpichler et al., 2008). This result is similar to that reported for
some agricultural soils with increased fertilization and grassland soils
with increased grazing (Fan et al., 2011; Prosser and Nicol, 2012; Pan et
al., 2018), supporting the conclusion that AOA and AOB generally inhabit
different niches in soil, distinguished by the NH4+ concentration
and availability (Verhamme et al., 2011; Wessén et al., 2011).
Effects of sea animal colonization on soil potential ammonia oxidation
rates
The PAOR ranged from 9 to 139 µg N kg-1 h-1, lower than
nitrification rates measured in most agricultural soils (83–1875 µg N kg-1 h-1) (Fan et al., 2011; Ouyang et al., 2016; Daebeler et al.,
2017). One reason might be the selection of a 15 ∘C incubation
temperature, which was lower than the incubation temperatures used in other
studies. Generally, the gross nitrification rate and amoA abundance increased
significantly when the incubation temperature was higher than 15 ∘C (Daebeler et al., 2017; Zhao et al., 2014). Our measurements indicated
that there were significant differences (P=0.02) in the PAOR across
different tundra patches, and the PAORs in SS and PS were about 10 times
higher than those in BS and MS. A significant correlation was obtained
between the PAOR and C : N, TP, and TS (Table 2). Overall, ammonia oxidation
activity was modulated by soil biogeochemical processes under the
disturbance of penguin or seal activities: generally low C : N ratios and
sufficient input of the nutrients TP, TS, and NH4+–N from sea
animal excrements.
The higher AOB abundances (Fig. 2b) and significant negative correlation of
AOA abundance with NH4+–N levels (Table 2) indicated that AOB
might play a more important role in nitrification in tundra soils. In
agreement with these results, AOB dominated nitrification in the areas where
it was easy to achieve nitrogen input, whereas the relative contribution of
AOA to nitrification was higher in the areas where the ammonium
concentration remained low (Fan et al., 2011; Sterngren et al., 2015).
Moreover, the cell-specific activity for AOB was 10 times higher than that
for AOA due to the bigger cell size of AOB (Hatzenpichler, 2012;
Prosser and Nicol, 2012). Therefore, AOB might play a more important role in
nitrification in SS, PS, and PL with the input of NH4+–N from
penguin or seal excrements.
In addition, AOA might play a role that cannot be ignored in MS and BS, just
like the prevalence of AOA among ammonia oxidizers in arctic soils (Alves et
al., 2013; Daebeler et al., 2017). AOB groups were mostly undetectable in
the analysis of MS and BS. Although unknown γ-AOB groups might not
have been detected, the primer set used here covers the β-AOB groups
typically found in soils (Alves et al., 2013). The BS and MS were moderately
far away from penguin or seal colonies without the input of the nutrients
from sea animal excrements, and their substrates can be provided only
through the mineralization of organic matter from local tundra plants. The
simple organic substrates and barren soil environment might favor AOA
(Stopnišek et al., 2010; Habteselassie et al., 2013). Therefore, AOA
showed relatively high abundance in MS and BS compared with PS and SS.
Effects of sea animal colonization on genotypic diversity of soil AOA
and AOB
In this study, distinct AOA communities appear to inhabit different types of
tundra patches, depending on sea animal activities (Fig. 5a). It was
difficult to amplify the AOA amoA gene from SS and PS, whereas a high diversity
of AOA amoA genes was observed in PL, MS, and BS. Phylogenetic analysis indicated
that the AOA amoA sequences in cluster I were from PL and tundra soils close to
seal wallows, while the sequences in cluster II were from BS and MS (Fig. S5). AOA in most extreme environments have lower levels of microbial
diversity than in benign ecosystems because of the requirement for specific
physiological adaptations which allow organisms to exploit the combination
of physical and biochemical stressors (Cowan et al., 2015). Detected OTUs in
cluster I had their closest matches mainly in the hyper-arid soils of
Antarctic Dry Valleys (Magalhães et al., 2014), wetland soils (Y. K. Zheng et
al., 2014), alpine meadow soils (Zhao et al., 2017), and some agricultural
soils (Glaser et al., 2010). Cluster II was more prevalent in BS and MS,
probably because of their stronger adaptation to barren soil environments.
In cluster II, the sequences were affiliated with sequences recovered from
cold environments, including the soils of the Tibetan Plateau (Xie et al., 2014)
and Icelandic grassland soils (Daebeler et al., 2012). The compositions of
soil AOA populations are likely not to be explained by individual
physicochemical properties, and their community structures significantly
correlated with tundra soil C : N, and TC, which was consistent with previous
studies (Glaser et al., 2010; Wessén et al., 2011).
AOB amoA gene diversity was higher than that of AOA, similar to results in the
Antarctic Dry Valley soils (Magalhães et al., 2014). A high diversity of
AOB amoA genes occurred in SS, PS, and PL compared to BS, indicating that penguin
or seal activities had important effects on AOB genotypic diversity.
Phylogenetic analysis indicated that the sequences in clusters I and II were
mainly from PS and SS (Fig. 5b), and the detected OTUs in cluster I had
their closest matches in mixed community culture systems, a meadow-to-forest
transect in Oregon Cascade Mountains (Mintie et al., 2003), and Dutch
agricultural soils (M. C. Silva et al., 2012a) and reservoir sediments (A. F. Silva et
al., 2012b). For clusters III and IV, the sequences were predominantly from
PL and SS, and they were affiliated with sequences recovered from high-altitude wetland (Yang et al., 2014). Previous studies have shown that
multiple environmental factors affected the AOB communities (Dang et al.,
2008; Mosier and Francis, 2008). In this study, the C : N ratios and
NH4+-N concentrations seemed to be the most important factors
influencing the AOB community structure, which was in accordance with the
results from different environments (Bouskill et al., 2012; Jung et al.,
2011; Li et al., 2015). Moreover, the TP also affected the AOB amoA community
compositions (Zheng et al., 2013). Therefore, the AOB community compositions
were impacted by the biogeochemical factors related to sea animal
activities, such as low C : N ratios and a sufficient supply of the nutrients
NH4+–N and TP from sea animal excreta.
Conclusions
The findings of this study concerning the abundance, potential activity, and
diversity of tundra soil AOA and AOB provide insights into microbial
mechanisms driving nitrification in maritime Antarctica. We confirmed the
presence of AOA and AOB amoA genes in five different tundra patches and
demonstrated that the spatial distribution heterogeneities of the tundra
soil AOA and AOB communities were driven by penguin or seal activities. The
soil AOB amoA copy numbers were generally higher than the AOA amoA copy numbers,
following the higher PAOR in penguin or seal colonies and their adjacent
tundra, compared with that in the background tundra and marsh tundra.
Penguin or seal activities resulted in a significant shift in soil AOA and AOB
community compositions. AOB amoA gene diversity was higher in SS and PS than in
PL and MS, and the majority of the AOB sequences was closely related to
Nitrosospira-like sequences. The AOA amoA gene had higher diversity in PL and MS than in BS,
and it was associated with Nitrososphaera sequences recovered from barren soils. Soil
AOB and AOA abundances, and their community compositions, were related to
soil biogeochemical processes under the sea-animal-activity disturbance,
such as soil C : N alteration and a sufficient supply of the nutrients
NH4+–N, N and P from animal excreta. This study significantly
enhances the understanding of ammonia-oxidizing microbial communities in
the tundra environment of maritime Antarctica.
Data availability
The final derived data presented in this study are available at 10.5281/zenodo.1260292 (Wang, 2018).
The supplement related to this article is available online at: https://doi.org/10.5194/bg-16-4113-2019-supplement.
Author contributions
RBZ, LJH, and QW conceived of the study together. QW conducted the laboratory analyses and statistical analyses with support from LJH and YLZ. TB retrieved samples during field work. The paper was written by QW with support by RBZ.
Competing interests
The authors declare that they have no conflict of interest.
Acknowledgements
This work was supported by the NSFC (grant nos. 41576181, 41776190). We are
particularly grateful to the members of the Chinese Antarctic Research
Expedition and the Polar Office of the National Ocean Bureau of China for their
support and timely help.
Financial support
This research has been supported by the National Natural Science Foundation of China (grant nos. 41576181, 41776190).
Review statement
This paper was edited by Denise Akob and reviewed by Weidong Kong and Barbara Bayer.
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