Nitrous oxide (N2O) is an important ozone-depleting
greenhouse gas produced and consumed by microbially mediated nitrification
and denitrification pathways. Estuaries are intensive N2O emission
regions in marine ecosystems. However, the potential contributions of
nitrifiers and denitrifiers to N2O sources and sinks in China's
estuarine and coastal areas are poorly understood. The abundance and
transcription of six key microbial functional genes involved in
nitrification and denitrification, as well as the clade II-type nosZ
gene-bearing community composition of N2O reducers, were investigated
in four estuaries spanning the Chinese coastline. The results showed that
the ammonia-oxidizing archaeal amoA genes and transcripts were more dominant in
the northern Bohai Sea (BS) and Yangtze River estuaries, which had low
nitrogen concentrations, while the denitrifier nirS genes and transcripts were
more dominant in the southern Jiulong River (JRE) and Pearl River estuaries,
which had high levels of terrestrial nitrogen input. Notably, the nosZ clade II
gene was more abundant than the clade I-type throughout the estuaries except
for in the JRE and a few sites of the BS, while the opposite transcript
distribution pattern was observed in these two estuaries. The gene and
transcript distributions were significantly constrained by nitrogen and
oxygen concentrations as well as by salinity, temperature, and pH. The nosZ clade
II gene-bearing community composition along China's coastline had a high level of
diversity and was distinctly different from that in the soil and in marine
oxygen-minimum-zone waters. By comparing the gene distribution patterns
across the estuaries with the distribution patterns of the N2O
concentration and flux, we found that denitrification may principally
control the N2O emissions pattern.
Introduction
Nitrous oxide (N2O) is a kind of ozone-depleting substance and an
important, long-lived greenhouse gas with a global warming potential 298 times that of carbon dioxide (CO2) (Solomon et al., 2007; Ravishankara et
al., 2009; Rowley et al., 2013). Prokaryotic microorganisms play an
important role in N2O production and consumption through the
nitrification and denitrification pathways
(Babbin
et al., 2015; Domeignoz-Horta et al., 2015; Ji et al., 2018b; Meinhardt et
al., 2018; Santoro et al., 2011; Silvennoinen et al., 2008). N2O is
produced as a byproduct in the first step (NH4+→NO2-) of nitrification, which is catalyzed by ammonia
monooxygenase in ammonia-oxidizing archaea (AOA) and ammonia-oxidizing
bacteria (AOB) (Codispoti and Christensen, 1985). The ammonia
monooxygenase subunit A gene (amoA) is frequently used as a functional gene
marker for AOA and AOB analysis. N2O is also produced as a kind of
intermediate product in the denitrification process, in which nitrite
(NO2-) is reduced to nitric oxide (NO) and then further reduced to
N2O. Usually, the nitrite reductase genes nirS and nirK are used to evaluate
the N2O production potential through denitrification
(Hallin
et al., 2018; Shaw et al., 2006; Wrage et al., 2001). Some bacterial
nitrifiers can also reduce NO2- to N2O through a nitrifier
denitrification pathway. The last step of denitrification is the only known
biological N2O consumption pathway, reducing N2O into nitrogen
(N2) under the catalysis of nitrous oxide reductase encoded by the
nosZ gene. This gene is divided into two clades according to the differences in
the signal peptides of nitrous oxide reductase
(Henry
et al., 2006; Jones et al., 2013). The microorganisms possessing clade
I-type nosZ genes are mainly affiliated with alpha-, beta-, and
gamma-proteobacteria, and the clade I gene has a higher frequency of
co-occurrence with nir and nor genes than the clade II gene. The nosZ clade II genes
are present in a much larger range of archaeal and bacterial phyla (Jones et
al., 2013), and intergenomic comparisons have revealed that more than half
of the microorganisms possessing clade II genes lack nitrite reductase or
nitric oxide reductase, do not produce N2O, and thus are expected to
drive potential N2O sinks
(Graf
et al., 2014; Jones et al., 2008; Marchant et al., 2017; Sanford et al.,
2012). The community composition of microorganisms with nosZ clade II genes is
considered important for the N2O : N2 end-product ratio of
denitrification, influencing the regional N2O source or sink
characteristics (Domeignoz-Horta1 et al., 2015; Philippot,
2013). However, there are few studies on nosZ clade II gene diversity and
community composition in Chinese estuarine and coastal areas.
Decades of research have revealed that the ocean, contributing
one-third of the N2O emission fluxes to the atmosphere, is the second most
important source of N2O emissions following arable soils
(Nevison et al., 2003). Estuaries, as
important bioreactors, are the most active N2O exchange areas in the
ocean, accounting for 33 % of oceanic N2O emissions with only
approximately 0.4 % of the area
(Bange
et al., 1996; Zhang et al., 2010). Denitrification is the major contributor
to N2O production in terrestrial ecosystems and stream and river
networks
(Beaulieu
et al., 2011; Marzadri et al., 2017). However, complete denitrification can
consume N2O (Jones et al., 2014). A recent study reports a fourfold
increase in global riverine N2O emissions influenced by human
activities (Yao et al., 2020). Marine
nitrification supported by ammonia-oxidizing archaea is largely responsible
for oceanic N2O emissions, especially in the open ocean
(Löscher
et al., 2012; Santoro et al., 2011), while nitrate reduction is the dominant
N2O source in oxygen-minimum zones (OMZs)
(Frey
et al., 2020; Ji et al., 2018a; Yamagishi et al., 2007). In estuaries, which are the
transition zones between the land and sea, both nitrification and
denitrification could be the dominant driving processes of active N2O
exchange. For example, nitrification was credited as the dominant N2O
production pathway in the Scheldt Estuary as well as in some other European
estuaries
(Barnes
and Upstill-Goddard, 2011; Brase et al., 2017; De Wilde and De Bie, 2000; Li et al., 2015),
while an inverse correlation between N2O concentrations and oxygen
indicates that denitrifiers might be the dominant N2O contributor in
the Potomac River estuary
(McElroy
et al., 1978). In addition, the incubation experiments with nitrogen-stable
isotope tracers reveal active N2O production by denitrification in the
Chesapeake Bay (Ji et al., 2018b). Another research project in the Chesapeake Bay
reveals that physical processes such as wind events and vertical mixing
affect the net balance between N2O production and consumption,
resulting in a variable source and sink for N2O
(Laperriere et al., 2019).
The four main estuaries along the Chinese coastline include the Bohai Sea
(BS) in the north, the Yangtze River estuary (YRE) and the adjacent East
China Sea (ECS) in the middle, as well as the Jiulong River estuary (JRE)
and Pearl River estuary (PRE) in the south (Fig. 1). The BS is a
semi-enclosed sea located in the north temperate zone of China. Influenced
by frequent human activities and seasonal variability in inputs from the
Yellow River, Liao River, Luan River, and Hai River, seasonal hypoxia is an
important characteristic of the BS (Chen,
2009). The YRE and the adjacent ECS, which receive a large amount of
nutrients from the largest river in Asia (Yangtze River: runoff
9.2 × 1011 m3 yr-1) (Zhang, 2002),
also exhibit seasonal hypoxia off the estuary from July to September because
of the enhanced primary productivity
(Zhu et al.,
2011). Both the JRE and PRE are located in densely populated and
industrialized subtropical areas, with runoffs of 1.44 × 1010 and 3.26 × 1011 m3 yr-1,
respectively
(Cao
et al., 2005; He et al., 2014). To clarify the potential contributions of
nitrification and denitrification to sources and sinks of N2O in
China's estuarine and coastal areas, the abundance and transcription
activity of six key microbial functional genes involved in nitrification and
denitrification (AOA and AOB amoA, nirS, nirK, nosZ clade I and II genes) were investigated
in the four estuarine areas. In addition, the nosZ clade II gene diversity and
N2O-reducing community composition were analyzed based on clone
libraries in order to assess the local N2O sink potential.
(a) Sampling sites in the four estuaries along China's coastline;
(b) Bohai Sea (BS); (c) Yangtze River estuary (YRE); (d) Jiulong River
estuary (JRE); (e) Pearl River estuary (PRE). The sampling time for each
region is shown in the subplots. The figure was produced by Ocean Data View 5.2.0 (http://odv.awi.de/, last access: 19 August 2020).
Materials and methodsSampling and biogeochemical parameter measurements
A total of 228 (130 for DNA and 98 for RNA) samples from 54 sites
were collected (Fig. 1). A total of 116 samples (58 for DNA and 58 for RNA) were collected from 20 stations with two or three depth layers
(3–63 m; Table S1) in the BS on the R/V Dongfanghong #2 from August to
September 2018. A total of 74 (41 for DNA and 33 for RNA) samples were
collected from 16 stations with one to four depth layers (3–55 m) in the
YRE on the R/V Yanping II from July to August 2017. Water samples were
collected using a rosette sampler fitted with Niskin bottles (SBE 911,
Sea-Bird Co). A total of 16 surface samples (9 for DNA and 7 for RNA) from a water
depth of ∼ 0.5 m were collected from the JRE on the R/V Ocean II during September 2016. A total of 22 samples for DNA were collected from 11
stations with two depth layers (0.5–18 m) in the PRE on the R/V Wanyu
during January 2017. Water samples were collected using an organic glass
hydrophore (1 L; Kedun Co., China). In addition, two and one surface sediment
samples were acquired using a grab sampler from the JRE in December 2015 and
from the YRE from July to August 2017, respectively. Water samples of
0.2–2.5 L were filtered through 0.22 µm pore-sized polycarbonate
membranes (Millipore, USA) within 1 h at a < 0.03 MPa pressure for
quantitative PCR (qPCR) analysis. Water samples were serially filtered
through 10, 3, and 0.22 µm pore size polycarbonate membranes
(Millipore, USA) for clone library analysis (Table S1). The membranes for
RNA extraction were immediately fixed with 1.5 mL of RNAlater (Invitrogen,
Life Technologies). All filters and sediment samples were quick-frozen in
liquid nitrogen and then stored at -80 ∘C for laboratory
analysis.
Temperature, salinity, and depth were measured using conductivity
temperature depth (CTD) (SBE 911, Sea-Bird Co.) in the BS, YRE, and PRE. In
the JRE, water temperature and salinity were continuously measured (every 3 s for 1 min) using a YSI6600D salinometer installed on an underway pumping
system (Yan et al., 2019). Dissolved oxygen (DO)
concentrations were measured using a WTW multiparameter portable meter
(Multi 3430, Germany). Ammonia was analyzed on deck using the indophenol
blue spectrophotometric method. Nitrate, nitrite, and silicate were measured
using an AA3 Autoanalyzer (Bran + Luebbe Co., Germany)
(Dai et al.,
2008).
Nucleic acid extraction, clone library, and phylogenetic analysis
DNA from water samples was extracted using the phenol-chloroform-isoamyl
alcohol method (Massana et al.,
1997) with minor modifications to maximize the DNA output. Briefly, tubes
containing shredded filters, approximately 0.5 g of 0.1 mm glass beads, and
800 µL of STE lysis buffer (0.75 M sucrose, 50 mM Tris-HCl, 40 mM
EDTA) were first agitated for 60 s on a FastPrep machine (MP Biomedicals,
Solon, OH, USA) at 4.5 m s-1. Then, the mixture was processed with
lysozyme (1 mg mL-1), proteinase K (0.5 mg mL-1), and sodium
dodecyl sulfate (SDS) (1 %) sequentially. At last, the lysate was
extracted twice with phenol-chloroform-isoamyl alcohol and once with
chloroform-isoamyl alcohol. The DNA was precipitated with isopropyl alcohol and
washed with 75 % ethyl alcohol before being dissolved in 50 µL sterile
water. DNA from sediment samples was extracted using a FastDNA SPIN Kit for
Soil (MP Biomedicals, USA). RNA from water samples was extracted using the
RNeasy Mini kit according to the manual (Qiagen, USA). Clean RNA, which was
verified by the amplification of the bacterial 16S rRNA gene with the primer
set 342F/798R, was reverse-transcribed to cDNA by the SuperScript III first
strand synthesis system (Invitrogen, Life Technologies) using random
hexamers following the user manual. The quality of both the DNA and cDNA was
checked by amplifying the full-length bacterial 16S rRNA gene before storage
at -80 ∘C.
A total of 19 DNA samples (16 from water and 3 from sediment) from the four
estuaries (Figs. 1 and 4) were used to construct clone libraries for the
clade II-type nosZ gene. A PCR was run with the primer set nosZ-II-F
(5′-CTIGGICCIYTKCAYAC-3′) and nosZ-II-R (5′-GCIGARCARAAITCBGTRC-3′)
according to a previously reported reaction mixture and program
(Jones et
al., 2013) with the minor modification of using 10 µg of bovine serum
albumin (BSA; Takara, Bio Inc.) instead of T4 gp32. PCR products were
purified using an agarose gel DNA purification kit (Takara, Bio Inc.),
ligated into the pMD19-T vector (Takara, Bio Inc.), and transformed into
high-efficiency competent cells of Escherichia coli according to the manufacturer's
instructions. A total of 40–127 positive nosZ clones were randomly selected from each
library, reamplified using the vector primers M13-F and RV-M, and sequenced
using the ABI 3730 automated DNA sequence analyzer (Applied Biosystems).
Poor-quality sequences with termination codons were manually checked and
removed, and chimeras were removed using UCHIME (Edgar et al., 2011). All
sequences were clustered into operational taxonomic units (OTUs) based on a
3 % sequence divergence cutoff (Jones et al., 2014; Wittorf et al., 2020).
The coverage (C) of each clone library was calculated by C= 100 % [1- (n/N)] (Mullins et al., 1995), where n is the number of unique OTUs and N the
total number of clones in a library. Alpha diversity indices (Shannon,
Simpson, and Chao1) of the clade II-type nosZ gene were calculated using the
Usearch package (Edgar et al., 2010). The representative sequences of OTUs
were translated and analyzed with the BLASTp tool (e value < 10-5). The top 10 most similar sequences of each OTU were used as
references. The deduplicated reference sequences and the representative
sequences of OTUs were aligned using MAFFT (Katoh and Standley, 2013) and
automatically trimmed using trimAl (Capella-Gutiérrez et al., 2009). A
maximum likelihood (ML) phylogenetic tree was constructed using Fasttree
(v2.7.1, default parameters) (Price
et al., 2010) with 500 bootstrap replicates for node support determination.
The taxonomy of the OTU was assigned according to the phylogenetic
relationship.
Quantitative PCR of six functional genes
Archaeal amoA, bacterial amoA, nirS, nirK, nosZ clade I, and nosZ clade II genes were quantified by
qPCR with DNA and cDNA as templates using a CFX96 (Bio-Rad Laboratories,
Singapore). Given the relatively high ammonia concentration in the
estuaries, the ammonia-oxidizing archaea (AOA) shallow cluster (Water Column
Cluster A; Francis et al., 2005) was targeted with the primer set
Arch-amoAFA and Arch-amoAR (Beman et al., 2008). Ammonia-oxidizing bacteria
(AOB) are mostly affiliated with two groups: Betaproteobacteria (β-AOB) and Gammaproteobacteria (γ-AOB)
(Lam et al., 2007). Since the latter was
below the detection limit in previous studies of Chinese estuaries
(Zheng et al., 2017; Hou et al.,
2018), only β-AOB was targeted with the primer set amoA-1F and amoA-r
New (Rotthauwe and Witzel, 1997; Hornek et al., 2006). Bacterial nirS and nirK genes
were quantified with the primer sets nirS-1F and nirS-3R (Braker et al.,
1998) and nirK876 and nirK1040 (Henry et al., 2004). Bacterial clade I-type nosZ
genes were quantified with the primer set nosZ2F and nosZ2R (Henry et al.,
2006).
For the clade II-type nosZ gene quantification, the previously published primer
sets were found to have less than 80 % amplification efficiency
(Jones
et al., 2013, 2014; Chee-Sanford et al., 2020). Here, we designed a new
primer set for use in our estuarine samples to quantify this gene.
Representative nucleotide sequences of each OTU obtained from the clone
libraries derived from the PRE samples (n=48) were translated into amino
acid sequences and then aligned with the representative reference sequences
(n=116; covering 87 genera) obtained from the Functional Gene Repository
(http://fungene.cme.msu.edu/index.spr, last access: 27 April 2017, Fish et al., 2013) by Clustal W. Two highly conserved
regions containing five and three amino acids in length were chosen to
design new primer fragments. The new primer pairs and the previously
published nosZ-II-F and nosZ-II-R primer sets (Jones et al., 2013) were all
evaluated by Primer Premier 6.0, and eligible primer sets (GC content:
40 %–60 %; optimal melting temperatures: 52–58 ∘C; stable 5′
end and specific 3′ end with no clamp or complementary structure) were
tested by qPCR. The best primer combination was nosZ-II-F and the newly
designed reverse primer (nosZ-II-Rnew: KGCRTAGTGIGGYTCDCC) with a ∼ 325 bp
target fragment length (Fig. S1). The qPCR system is shown in Table S2, and
the optimized qPCR program was as follows: an initial 5 min denaturing step
at 95∘C, followed by 35 cycles of 95∘C for 30 s, annealing
at 53∘C for 60 s, 72∘C extension for 60 s, and a final
extension at 72∘C for 10 min. The coverage of the primer sets was
evaluated using the Search_pcr2 command of Usearch with the
116 reference sequences mentioned above and all clone sequences (n=1378)
obtained from the clone libraries. A coverage of 93.5 % (≤2
mismatches) was obtained for the new primer set.
The presence of PCR inhibitors in DNA extracts was examined by qPCR with
different dilutions of DNA (1-, 10-, and 100-fold dilutions). The samples
with inhibitors were diluted 10 times to overcome the inhibitor effect
according to our evaluation. Standard curves were constructed for the six
genes using plasmid DNA from clone libraries generated from the PCR
products. qPCRs were performed in triplicate and analyzed against a range of
standards (101 to 108 copies µL-1). All specific primer
sequences, reactions, and programs for qPCR/PCR used in this study are shown
in Table S2. The amplification efficiencies ranged from 87 % to 109 %
with R2>0.99 for each qPCR run. The specificity of qPCR
products was verified by melting curves, agarose gel electrophoresis, and
sequencing.
Statistical analysis
Redundancy analysis (RDA) based on qPCR or clone library data was used to
analyze variations in the gene/transcription distribution and nosZ clade II
community composition under environmental constraints using R (R Core Team,
2017). The qPCR or clone library-based relative abundances and environmental
factors were normalized via Z transformation (Fayazbakhsh et al., 2009; Magalhães et al., 2008).
The collinearity between environmental parameters was excluded (variance
inflation factors >10; Palacin-Lizarbe et al., 2019). The null
hypothesis that the community structure was independent of environmental
parameters was tested using constrained ordination with a Monte Carlo
permutation test (999 permutations). Since a normal distribution of the
individual datasets was not always met, we used the nonparametric Wilcoxon
rank-sum tests for comparing two variables in GraphPad Prism software (San
Diego, CA, USA). The bivariate correlations were described by Spearman's
(ρ value) or Pearson's (r value) correlation coefficients. False
discovery rate-based multiple comparison procedures were applied to evaluate
the significance of multiple hypotheses and to identify truly significant
comparisons (false discovery rate-adjusted P value) (Pike, 2011).
ResultsEnvironmental characteristics of the four estuaries
Water temperature increased with decreasing latitude from the BS (16.1–26.4 ∘C) to the YRE (19.2–29.1 ∘C) and JRE (28.7–30.8 ∘C), where samples were all collected in summer. Samples were
collected in winter in the southernmost PRE, where the water temperature was
19.7–20.5 ∘C (Fig. 2). Salinity exhibited consistently high
values in all sites of the BS and YRE (26.4–34.6 ppt), except for two low
values (14.34 and 21.66 ppt) observed in the river mouth. In the JRE and
PRE, obvious salinity gradients were detected from 0.1 to 30.7. The DO
concentration varied in the range of 4.25–8.46 mg L-1 in the BS,
1.25–8.71 mg L-1 in the YRE, 4.04–6.89 mg L-1 in the JRE, and
2.22–9.22 mg L-1 in the PRE. There was a distinct DO gradient from
upstream to downstream in the PRE (Fig. 2). The dissolved inorganic nitrogen
(DIN: ammonium, nitrite, and nitrate) concentrations were generally lower in
the BS and YRE compared to those in the JRE and PRE. The ammonium
concentration was in the range of 0.006–1.27 µM in the BS, below
detection (BD) to 1.99 µM in the YRE, 7.01–36.78 µM in the
JRE, and 1.71–417.38 µM in the PRE. The nitrite concentration was in
the range of BD–5.65 µM in the BS and 0.004–2.5 µM in the
YRE, 7.24–30.87 µM in the JRE, and 0.41–69.23 µM in the PRE.
The nitrate concentration ranged from 0.067–13.97 µM in the BS,
0.23–65.09 µM in the YRE, 24.94–241.32 µM in the JRE, and
3.0–320.53 µM in the PRE. Clear DIN concentration gradients were
observed from upstream to downstream in the JRE and PRE, particularly in the
PRE.
Temperature (Temp), salinity, dissolved oxygen (DO), pH, ammonium, nitrite, and nitrate concentration distributions in the Bohai Sea (BS), Yangtze River estuary (YRE), Jiulong River estuary (JRE), and Pearl River estuary (PRE). Data from the surface layer (S), middle layer (M), and bottom layer (B) were shown for temperature, salinity, DO, and pH. Details about the depth of samples are listed in Table S1. Depth-integrated mean values were used for ammonium, nitrite, and nitrate concentration distributions.
Distribution of six key functional genes
The abundances of archaeal amoA, bacterial amoA, nirS, nirK, nosZ I, and nosZ II genes showed
distinct distribution patterns among the four estuaries (Fig. 3a–h). We
divided the six genes into two groups for analysis: one group included
archaeal and bacterial amoA, nirS, and nirK genes indicating nitrification and
denitrification related to N2O production (Fig. 3a–d), and the other
included bacterial nosZ I and nosZ II genes indicating N2O consumption (Fig. 3e–h). In the gene group of N2O production-related processes, archaeal
amoA was the most dominant in the BS (2.66 × 104–3.68 × 108 copies L-1) and YRE (4.86 × 103–9.47 × 107 copies L-1) (Wilcoxon test, P<0.01; Fig. 3a, b and
Table S3), accounting for 3.96 %–96.2 % and 2.84 %–99.67 % of
N2O production-related gene abundance, respectively. In contrast to the
northern estuaries, archaeal amoA (5.28 × 105–4.40 × 106 copies L-1) and bacterial nirS (2.57 × 105–6.29 × 106 copies L-1) genes codominated the
gene group of N2O production-related processes in the JRE (Fig. 3c),
accounting for 2.43 %–72.93 % and 25.03 %–93.77 %,
respectively. In the southernmost PRE, the nirS gene was the most abundant
(3.48 × 104–1.66 × 109 copies L-1),
especially upstream (P<0.05), accounting for 4.24 %–99.91 %
(Fig. 3d). Generally, archaeal amoA was widespread in all samples, and its
abundance decreased from north to south with differences of 1 to 2
orders of magnitude. A similar pattern was observed for bacterial amoA, with
lower abundances than archaeal amoA (Table S3). The abundance of the nirS gene was
highest in the PRE among the four estuaries, while the highest number of
copies of the nirK gene was present in the BS (Table S3). Among the different
water depths, only the bacterial amoA and nirS genes in the BS were observed to be
more highly distributed in the middle and bottom layers than in the surface
layer by one to three orders of magnitude (P<0.05).
Six key functional gene and transcript abundance distributions in
the Bohai Sea (BS), Yangtze River estuary (YRE), Jiulong River estuary
(JRE), and Pearl River estuary (PRE). S: surface layer; M: middle layer; B:
bottom layer. (a–d) Gene related to N2O production; (e–h) gene
related to N2O consumption; (i–k) transcript related to N2O
production; (l–n) transcript related to N2O consumption.
In the N2O-consuming genes, the abundances of the clade II-type nosZ gene
were 6.55 × 103–2.24 × 107 copies L-1 in
the BS (Fig. 3e), 6.14 × 103–8.11 × 106 copies L-1 in the YRE (Fig. 3f), and BD–1.17 × 107 copies L-1 in the PRE (Fig. 3h), outnumbering the clade I-type (P<0.01) with no significant differences among the three estuaries. However,
the clade II-type nosZ gene was below the detection limit in the JRE, and only
the clade I-type was detected with a range of 7.15 × 103–2.32 × 105 copies L-1 (Fig. 3g and Table S3).
The numbers of copies of the clade I-type nosZ gene were higher in the BS
estuary than in the other three estuaries (P<0.01).
Transcription activity of six key functional genes
For the four genes of N2O production-related processes, a generally
similar relative abundance distribution pattern was observed between
transcripts and genes in the BS (Fig. 3i). Archaeal amoA gene transcripts
(3.51 × 103–1.62 × 106 transcripts L-1) were
significantly more abundant than other transcripts (P<0.01),
accounting for 37.94 %–99.30 % of the total abundance of gene
transcripts (Table S4). Slightly different from the gene distribution in
which the number of copies of the bacterial amoA gene was relatively more
abundant than that of the archaeal amoA gene in the river mouth of the YRE (Fig. 3b), the archaeal amoA gene transcript was abundant in the whole YRE, accounting
for 9.1 %–100 % of the total abundance of gene transcripts, with a
dominant abundance of nirS gene transcripts in a few samples (Fig. 3j). A
different distribution pattern was also observed between transcripts and
genes in the JRE (Fig. 3c, k). Bacterial amoA (7.06 × 105–8.22 × 107 transcripts L-1) rather than archaeal
amoA transcripts (P<0.05) were codominant with nirS transcripts
(5.96 × 105–2.31 × 107 transcripts L-1)
(Fig. 3k). Notably, the total gene transcript abundance of N2O
production-related processes was higher in the JRE (1.31 × 106–9.76 × 107 transcripts L-1) than in the BS and
YRE (3.03 × 102–1.12 × 106 transcripts L-1)
(P<0.01; Table S4). Bacterial amoA gene transcripts, consistent with
the gene distribution, significantly increased with depth in the BS (P<0.05). No significant differences in transcript abundance were
observed among different depths for the six functional genes in the YRE.
For the N2O-consuming genes, only the clade I-type nosZ gene transcript was
determined (26.2–2.34 × 103 transcripts L-1), while the
clade II-type nosZ gene transcript was below the detection limit in the BS (Fig. 3l; Table S4). However, the nosZ II gene transcripts (below detection–1.81 × 105 transcripts L-1) dominated most stations in the
YRE, except for a dominant distribution of the nosZ I gene transcript in the
river mouth (Fig. 3m). Similar to the gene distribution, in the JRE, only
the nosZ I gene transcript was determined (1.23 × 103–5.37 × 104 transcripts L-1) (Fig. 3n). No RNA
samples were obtained in the PRE.
Phylogenetic diversity of the clade II nosZ gene
Clone libraries of nosZ clade II were constructed for 19 samples from the four
estuaries, resulting in a total of 1378 quality-controlled sequences that
were clustered into 441 OTUs at a similarity level of 97 %. The coverage
of each clone library ranged from 73.9 %–96.2 %. Higher gene diversity of
nosZ clade II was observed in the water and sediment samples from the JRE and
the sediment sample from the YRE than in the other samples (Fig. S2a). The
rarefaction curves of the samples from JRE and the sediment sample from YRE
did not reach a plateau (data not shown), suggesting that some of the
diversity of nosZ clade II remained unsampled. Phylogenetic analysis of the
representative sequences of all the OTUs indicated that the clade II nosZ gene
sequences were grouped with Bacteroidetes, Proteobacteria, Actinobacteria,
Chloroflexi, Chlorobi, Ignavibacteriae, Gemmatimonadetes, Cyanobacteria, and
Acidobacteria, in which the OTUs affiliated with Bacteroidetes,
Proteobacteria, Chloroflexi, and Actinobacteria were generally abundant
among all samples (Fig. 4b). The OTUs belonging to Bacteroidetes were
divided into two clusters according to the topological structure of the
phylogenetic tree. One cluster contained the reference sequences mainly derived from
marine habitats and the OTU sequences retrieved from the four estuaries,
while the other cluster included the reference sequences mainly derived from
terrestrial habitats and the OTU sequences retrieved only from the
low-latitude subtropical estuaries JRE and PRE. The OTU sequences affiliated
with Alpha-, Gamma-, Delta-, Epsilonproteobacteria, and Actinobacteria were retrieved
from the four estuaries, and the reference sequences were mainly from marine
habitats, while the OTUs related to Betaproteobacteria, Oligoflexia,
Chlorobi, and Candidatus Melainabacteria were retrieved only from the subtropical estuaries (JRE and
PRE), and the reference sequences were mainly from terrestrial habitats
(Fig. 4a). Most known clusters of nosZ clade II can be found in our libraries,
including a recently identified widespread clade II-type nosZ gene affiliated
with the class Oligoflexia
(Nakai
et al., 2014).
(a) Maximum likelihood phylogenetic tree of amino acid sequences
of the clade II-type nosZ. The colors of the inner circle indicate taxonomic
affiliations based on reference sequences. The colors of the outer circles
represent the sources of clone sequences. The phylogenetic tree was
bootstrapped 500 times. The scale bar represents the number of amino acid
substitutions per site. Numbers before and after the colons indicate the
number of reference sequences from marine and terrestrial habitats,
respectively. The figure was produced using the interactive tree of life
(http://itol.embl.de/, last access: 20 September 2019; Letunic and Bork, 2016). (b) Relative abundances of
community compositions of the clade II-type nosZ gene clone libraries in the
four estuaries. The colors of the bars indicate taxonomic affiliations. The
similarity was calculated from Bray–Curtis similarity. Black stars indicate
sediment samples.
A community structure shift of nosZ clade II was observed among the four
estuaries (Fig. 4b). Bacteroidetes was the most dominant group in the
samples from the BS (39.0 %–68.5 %), followed by Proteobacteria (Gamma-,
Delta-, and Alphaproteobacteria; 18.7 %–26.0 %). The sequences
phylogenetically grouped into Proteobacteria (Gamma-, Delta-, and
Epsilonproteobacteria; 23.0 %–70.6 %) dominated the clone libraries from
the YRE, followed by Chloroflexi (6.9 %–47.3 %). The sequences from the JRE
were also mainly affiliated with Proteobacteria (Beta-, Gamma-, Delta-, and
Alphaproteobacteria and Oligoflexia; 11.8 %–40.5 %), Bacteroidetes
(30.9 %–37.9 %), and Chloroflexi (12.1 %–50.9 %). In contrast to the three
estuaries, the sequences affiliated with Bacteroidetes were absolutely
dominant in the clone libraries of the PRE (>69.2 %). A
nonmetric multidimensional scaling (NMDS) analysis indicated that nosZ clade II
communities from the same estuary were clustered together at a >10 % Bray–Curtis similarity level, except for a separate cluster of the
sediment community from the YRE (Fig. S2b). The nosZ clade II communities from
the southern estuaries (JRE and PRE) and northern estuaries (YRE and BS)
were clustered separately at a >3 % Bray–Curtis similarity
level.
Correlations between six key functional genes and environmental factors
Variations in the gene–transcript distributions under environmental
constraints were analyzed by RDA. The first two RDA axes explained 19.98 %
and 5.36 % of the total variation in the gene–environment relationship
(Fig. 5a). Salinity, DO, nitrite, and ammonium concentrations were
significantly correlated with gene distribution (P<0.01). The main
variation in N2O source or sink process-related genetic potentials was
across a nirS vs. archaeal amoA abundance gradient. The nirS-rich samples corresponded
to those from the southern estuaries (JRE and PRE) with higher ammonium and
nitrite concentrations. In contrast, the samples with the highest abundance
of archaeal amoA were located in sites with high salinity and low ammonium
concentrations in the northern estuaries (BS and YRE). Notably, RDA of the
gene transcripts and environmental variables clearly separated the
transcripts from different estuaries along the axes, which explained
26.4 % and 8.27 % of the total variation (Fig. 5b). Variation in
transcript distribution was significantly correlated with pH, temperature,
nitrite, and nitrate concentration (P<0.01). The main variation of
these transcripts was distributed across archaeal and bacterial amoA vs.
nosZ clade II abundance gradients. The archaeal amoA transcript-rich samples
corresponded to those from the BS and YRE sites with lower temperatures. The
bacterial amoA gene was actively transcribed in the JRE and positively
correlated with nitrite and nitrate concentrations. The nosZ clade II
transcript-rich samples corresponded to those from the YRE sites with
relatively higher pH and temperature. The nosZ clade I and nirS transcript
distributions were also positively correlated with pH and temperature,
respectively.
Redundancy analysis of the relative abundances of
ammonia-oxidizing archaeal amoA (AOA-amoA), bacterial amoA (AOB-amoA), nirS, nirK, and nosZ clade I and
II (a) genes and (b) transcripts, as well as of (c) the community
composition of the nosZ clade II clone libraries under biogeochemical
constraints. Each circle, triangle, or square represents an individual
sample from the surface, middle, or bottom layer, respectively. The
fork-shaped symbol represents the functional gene, transcript, or nosZ clade II
OTU. Vectors represent environmental variables. Asterisks indicate
statistically significant variables. Temp, temperature; DO, dissolved
oxygen.
RDA based on the clone library data of the clade II-type nosZ gene revealed that
the nosZ II community composition was significantly affected by temperature (P<0.01; Fig. 5c). The first two RDA axes explained 33.29 % and
13.24 % of the total variation. The nosZ II gene community compositions in the
BS may prefer environments with relatively high salinity and temperature.
The community compositions in the JRE water may prefer environments with a
high temperature (the sediment samples were not included in this analysis
due to a lack of biogeochemical parameters). The nosZ clade II microbes in the
PRE and YRE may prefer to distribute in environments with high ammonium
concentrations.
DiscussionNiche differentiation of functional genes controlled by environmental
factors
There was a distinct large-scale spatial structure among the detected genes,
as shown in Fig. 3. The different sampling seasons between the PRE (January)
and the other three estuaries (June to September) may influence the spatial
distribution of functional genes across the four estuaries. However, the
niche differentiation of functional genes, spatially or temporally, is
essentially controlled by environmental factors, such as temperature,
salinity, oxygen and nutrient availabilities, and primary productivity.
Comparing the relative contributions of these functional genes to the total
number of gene copies across the study regions, there was a strong negative
correlation between the relative abundances of the archaeal amoA gene and
bacterial nirS gene (ρ=-0.89, P<0.01), and they showed
contrasting patterns along salinity and DIN gradients (Fig. S3). Samples
from the BS and YRE exhibited high salinity and low DIN concentrations. The
high abundance of the archaeal amoA gene in these areas is consistent with
previous findings of nitrifiers comprised predominantly of AOA in estuarine
environments with higher salinity and lower ammonia concentrations, since
archaeal nitrifiers exhibit a high ammonia affinity and salinity tolerance
(Martens-Habbena
et al., 2009; Abell et al., 2010; Bernhard et al., 2010; Zhang et al., 2014;
Hou et al., 2018; Hink et al., 2018; Ma et al., 2019). In contrast, both the
JRE and PRE are typical subtropical, eutrophic estuaries with high DIN inputs
from surrounding environments
(Cao
et al., 2005; He et al., 2014; X. Yan et al., 2012). Denitrifying bacteria are
more adaptable to environments with high organic carbon and nitrogen
concentrations because they usually have high requirements for substrates
(Braker et al., 2000; Smith et al., 2007; Mosier and Francis, 2010; Wang et
al., 2014; Wei et al., 2015; Lee and Francis, 2017). The presence of
nitrogen oxides was also shown to activate nirK and nirS gene expression under
anoxic conditions (Riya et al., 2017). Thus, the
nirS-containing group was more abundant upstream in the JRE and PRE. The
significant correlations between DIN and the nirS gene (Fig. S3) and transcript
(ρ=0.341, P<0.01; data not shown) are consistent with a
previous conclusion that high anthropogenic N loading stimulates
denitrification
(Beaulieu
et al., 2011; Cole and Caraco, 2001; Garnier et al., 2006; W. Yan et al.,
2012).
Previous studies of N2O-consuming gene abundance have mainly focused on
terrigenous ecosystems, e.g., in soil samples, the clade I- and II-type
nosZ genes ranged from 104 to 108 and 104 to 107 copies g
of dry soil-1, respectively (Jones et al., 2013, 2014). In marine
ecosystems, only the oxygen-depleted waters and coastal sediments have been
investigated, where the clade I-type was approximately 105 copies L-1 and both clades I and II ranged from 105 to 107 copies g
of wet sediment-1, respectively (Wittorf et al., 2020; Sun et al., 2021).
We detected that the number of copies of the nosZ gene ranged from
6.59 × 103 to 2.35 × 108 copies L-1, with
an average of 4.94 × 106 copies L-1 in China's estuarine
and coastal areas. There was a strong negative correlation between the
relative abundance of the clade I- and II-type nosZ genes (ρ=-1, P<0.01), indicating that the two types were affiliated with
different groups. The distribution of nosZ (clades I and II) gene transcripts was
significantly positively correlated with pH (Fig. 5b), suggesting that
acidification of the ocean may decrease N2O consumption potential.
N2O production influenced by pH has been observed in N-cycling water
engineering systems and terrestrial ecosystems
(Mørkved et al., 2007; Blum et
al., 2018). Therefore, some studies suggest that liming for acidic soils
could mitigate N2O emissions
(McMillan et al.,
2016; Wang et al., 2017; Senbayram et al., 2019). The nosZ genes and transcripts
showed significantly negative correlations with nitrate and/or nitrite (Fig. 5a and b), and similar correlations were also found in mountain lake
habitats
(Palacin-Lizarbe et
al., 2019). It is possible that high abundances of the nosZ gene and transcript activity lead
to high consumption of nitrate and nitrite. In addition, it was reported
that the presence of nitrate can inhibit the reduction of N2O to
N2 (Blackmer and
Bremner, 1978). DO also showed an important influence on denitrifying genes,
which is consistent with a previous conclusion that O2 concentrations
can impact the expression and metabolism of denitrification genes through
protein sensing of oxygen conditions (Qu et
al., 2016; Riya et al., 2017). Notably, we found that the distribution and
abundance of the nosZ gene and the nirS or nirK genes were distinctly different,
indicating that these functional genes were affiliated with different
denitrifiers. This may be because not all N2O-consuming bacteria
contain all denitrification genes
(Sanford et al., 2012).
Gene transcription expression controlled by environmental factors
The gene transcript abundance showed a certain regional distribution
difference with gene abundance (Fig. 3), suggesting that environmental
factors might have different influences on gene distribution and transcript
activity. The bacterial amoA gene was transcribed actively in the JRE, although
the archaeal amoA gene prevailed in gene abundance. Frequent water exchange may
result in a large amount of the archaeal amoA gene from the ocean, but AOB are
more active under high ammonium and low salinity conditions. AOB have been
indicated to be the primary N2O producer, even in an AOA-dominated
environment (Meinhardt et al., 2018). A meta-analysis also revealed that AOB
respond more strongly than AOA to nitrogen addition
(Carey et
al., 2016). High abundances of bacterial amoA and nirS gene transcripts make the JRE a potentially
more active area of N2O production compared to the northern
estuarine and coastal areas, which may be attributed to the nitrogen input of the JRE's surrounding environment. In contrast, in the mouth of the YRE,
although the bacterial amoA gene contributed a large proportion of the gene
abundance, the archaeal amoA gene was transcribed more actively. Flushing water
from the Yangtze River may transport a large amount of the bacterial amoA gene,
but the archaeal amoA gene is more competitive in low ammonium and oxygen
environments (Fig. 2) since the enzyme ammonia monooxygenase in AOA has a
higher affinity for ammonia and a lower oxygen requirement than the AOB
(Park et al., 2010; Molina et al., 2010; Martens-Habbena and Stahl,
2011). The nosZ clade I gene was transcribed more actively even though the
nosZ clade II gene was more abundant (e.g., the case in the BS shown in Fig. 3e
and l). The higher growth yields of clade II-type N2O-reducing bacteria
than those of clade I-type (Yoon et al., 2016) may lead to a preponderance
of the nosZ clade II gene. However, a microbial culture of clade I-type
N2O-reducing bacteria has been reported to have the capability of
continually synthesizing N2O reductase enzymes under oxic conditions to
allow for a rapid transition into anoxic environments (Lycus et al., 2018).
Such a strategy could result in the more abundant nosZ clade I transcripts
observed in the estuaries.
The ranges of (a) N2O concentration; (b) N2O flux; (c)ΔN2O (data from
Chen
et al., 2008; Lin et al., 2016, 2020; Ma et al., 2019; Song et al., 2015;
Wang et al., 2014, 2016; Wu et al., 2013; Xu et al., 2005; Zhan et al.,
2011; Zhang et al., 2008, 2010); (d) total archaeal and bacterial amoA gene
abundance; (e) total nirS and nirK gene abundance; (f) the ratio of total nir to amoA gene
abundance; (g) total nosZ clade I and II gene abundance; (h) the ratio of total
nir to nosZ clade I gene abundance; and (i) ratio of total nir to nosZ clade II gene
abundance in the Bohai Sea (BS), Yangtze River estuary (YRE), Jiulong River
estuary (JRE), and Pearl River estuary (PRE). Black circles represent the
value of each sample. Bars represent the mean values. Error bars indicate
standard deviation. N: no data or not determined.
N2O emissions potential implied by functional gene distribution
The community structure of nitrifiers and denitrifiers is thought to have an
important influence on N2O emissions. For example, the abundance and
expression of the archaeal amoA gene showed comparable patterns with N2O
production in the OMZ of the eastern tropical North Atlantic
(Löscher et al., 2012).
Reduction of the abundance of bacterial amoA genes in hyperthermophilic
composting was proven to decrease N2O emissions
(Cui et al., 2019). The expression of the nirK gene
induced by the addition of nitrate caused an increase in N2O production
in an anoxic soil slurry experiment (Riya et al.,
2017). Transcription of clade I-type nosZ mRNA in the lower N2O emission
system was one order of magnitude higher than that in the higher N2O
emission system in wastewater treatment plants
(Song et al., 2014). To assess
how community structure controls the regional N2O source or sink
potential across China's estuaries, we collected the data on N2O
concentration, N2O flux, and ΔN2O in the four estuaries
from the literature, covering January to November from 2002 to 2015 (Table S5;
Chen et al., 2008; Lin et al., 2016, 2020; Ma et al., 2019; Song et al.,
2015; Wang et al., 2014, 2016; Wu et al., 2013; Xu et al., 2005; Zhan et
al., 2011; Zhang et al., 2008, 2010) and analyzed their relationships with
the six functional gene distributions. The N2O concentration, N2O
flux, and ΔN2O all showed an increasing distribution pattern
from the northern, high-latitude to the southern, low-latitude estuaries
(Fig. 6a–c), with hot spots in the north and center of the BS, nearshore
of the YRE, and upstream of the JRE and PRE. Notably, total amoA gene abundances
displayed a contrary pattern, while total nir gene abundances and the ratio of
total nir to amoA gene abundances (nir/amoA) had generally consistent patterns with the
N2O concentration, N2O flux, and ΔN2O across the four
estuaries (Fig. 6d–f). A significant correlation was even observed between
the N2O flux and the nir/amoA ratio based on the four averages of the four
estuaries (r=0.95, n=4, P<0.05). Therefore, the
nir/amoA ratio can indicate the N2O emission potential in China's estuaries,
which is consistent with previous findings that the N2O production
yield of denitrification is higher than that of nitrification in the lab and
in situ experiments
(Frey
et al., 2019; Kester et al., 1997; Löscher et al., 2012; Stieglmeier et al.,
2014).
Notably, the total nosZ gene abundance of N2O-reducing denitrifiers seemed
to have a contrasting distribution pattern with the N2O concentration,
N2O flux, and ΔN2O across the four estuaries, with higher
abundances in the high-latitude BS and lower abundances in the low-latitude
JRE (Fig. 6g). The total nosZ gene abundances were one to two orders of
magnitude lower than the total nir gene abundances in the JRE and PRE, where the
N2O concentration and flux were higher than those in the BS and YRE.
This indicated a distinctly higher denitrification-derived N2O emission
potential in the JRE and PRE. The ratio of total nir to nosZ clade I gene abundances
(nir/nosZ I) had a highly similar pattern with the N2O concentration, N2O
flux, and ΔN2O across the four estuaries in general (Fig. 6h),
and significant correlations were also observed between the N2O flux
and nir/nosZ I (r=0.97, n=4, P<0.05). Therefore, the nir/nosZ I ratio
could be a better indicator of N2O emission potential in China's
estuaries. Abundances and activities of the N2O-producing (nirS or
nirK–bearing) community relative to the N2O-reducing (nosZ-bearing) community
have also been used to assess the N2O emission potential of soils
(Thompson, 2016; Zhao et al.,
2018). Similarly, the functional gene transcript distribution indicated that
the nir/nosZ I and nir/amoA gene transcript abundance ratios also had consistent patterns
with the N2O concentration, N2O flux, and ΔN2O across
the four estuaries in general (Fig. S4). The high load of DIN in estuaries
could be responsible for the high denitrification-derived N2O emission
potential. Both the nir/nosZ and nir/amoA ratios were positively correlated with the
NH4+, NO3-, and NO2- concentrations
(Spearman's ρ=0.32–0.68, n=114–122, P<0.01 for
each) and negatively correlated with salinity (Spearman's ρ=-0.45
to -0.66, n=114–122, P<0.01 for each). Previous studies in the
YRE have proven that nitrogen input accelerates N2O production in
estuaries
(W. Yan
et al., 2012; Zhang et al., 2010). Therefore, sufficient supplies of
substrates may support high rates of denitrification and thus high N2O
emissions.
Influence of N2O emissions by N2O reducer composition
The community structure and diversity of the clade II nosZ gene retrieved from
China's estuaries are different from those previously reported in soil and
marine OMZ water (Jones et al., 2013, 2014; Sun, 2021). The dominant nosZ clade
II-bearing groups are affiliated with Bacteroidetes, Chloroflexi, Gamma-,
and Betaproteobacteria in our four estuarine and coastal areas. However, the
most abundant nosZ clade II groups found in the OMZs of the eastern tropical
South and North Pacific and the Arabian Sea are affiliated with
Anaeromyxobacter (Deltaproteobacteria)
(Sun
et al., 2017; Sun et al., 2021) and those in the coastal OMZ waters of the
Golfo Dulce, Costa Rica, are affiliated with Gammaproteobacteria,
Marinimicrobia, Bacteroidetes, and SAR324 (Bertagnolli et al., 2020). The
nosZ clade II organisms from terrestrial systems show distinctly higher
diversity (Sanford et al., 2012; Jones et al., 2014; Hallin et al., 2018;
Zhao et al., 2018; Kato et al., 2018). The phylogenetically distinct
predominant N2O reducers can influence N2O emissions directly or
indirectly (Song et al.,
2014). According to genomic information, nosZ clade II carriers affiliated with
Deltaproteobacteria and Chlorobi have neither the nirK nor nirS gene, and less than
half of nosZ clade II organisms affiliated with Bacteroidetes, Chloroflexi,
Gamma-, and Epsilonproteobacteria harbor the nirK or nirS gene, while all of the
nosZ clade II microbes affiliated with Alpha- and Betaproteobacteria also have
the nirS gene (Hallin et al., 2018). Therefore, the distinct
nosZ clade II community structure among the four estuaries may contribute to
their different N2O emissions potential. For example, distinctly high
diversity of the nosZ clade II gene was retrieved from the JRE water and
sediment samples as well as the YRE sediment sample compared to the other
estuaries. The high diversity of the nosZ clade II gene may be caused by the
high temperature (e.g., in the low-latitude JRE) and sufficient nutrients at
those sites. Previous studies have also indicated that the biodiversity of
denitrifying bacteria increases in high-temperature seasons
(Castellano-Hinojosa et al., 2017)
and that nitrogen availability has a positive effect on denitrifying
bacteria in boreal lakes (Rissanen et al.,
2011). In addition, the habitat type may also affect the abundance and
diversity of N2O-reducing communities, e.g., silty mud and sandy
sediments have higher genetic potentials for N2O reduction than
cyanobacterial mat and Ruppia maritima meadow sediments
(Wittorf et al., 2020).
Summary
This study revealed the distinct distribution patterns of six key microbial
functional genes and transcripts related to N2O production and
consumption pathways in the BS, the YRE, the adjacent ECS, the JRE, and the
PRE. The archaeal amoA genes and transcripts were more abundant in the northern
BS, YRE, and the adjacent ECS, while the denitrifier nirS genes and transcripts
were more abundant in the southern JRE and PRE. The nosZ clade II gene was more
abundant than the clade I-type throughout the estuaries except for in the
JRE and a few sites of the BS, while the opposite transcript distribution
pattern was observed in these two estuaries. Water mass parameters
(temperature and salinity), substrates (ammonia/ammonium, nitrite, and
nitrate), and influencing parameters of substrate availability (DO and pH)
regulated the gene, transcript, and community composition distribution
patterns. The community structure of the clade II-type nosZ gene retrieved from
China's estuaries was distinctly different from those of the soil and marine
OMZ. Furthermore, combined with the N2O concentration, flux, and
ΔN2O data collected from previous studies, our analysis found
that, although both the clade I- and II-type nosZ genes of N2O reducers were
widely distributed in these estuaries, N2O production by the
denitrification pathway may be more important in determining the N2O
emissions patterns across the estuaries. Nitrogen loads may influence the
N2O source and sink processes by regulating the distribution of the
related functional microbial groups.
Data availability
All quality-controlled sequences were submitted to GenBank with accession
numbers OM567739–OM568649. All other data can be accessed in the form of
Excel spreadsheets via the corresponding author.
The supplement related to this article is available online at: https://doi.org/10.5194/bg-19-3757-2022-supplement.
Author contributions
YZ conceived and designed the study. XD, XW, MC, ET, and NC performed the
experiments and auxiliary data collection. XD analyzed the data. XD and YZ
wrote the paper. All authors contributed to the interpretation of the
results and critical revision.
Competing interests
The contact author has declared that none of the authors has any competing interests.
Disclaimer
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Acknowledgements
We thank Zuhui Zuo, Yufang Li, and Minyuan Liu for their assistance in
sampling and DNA/RNA extraction, as well as Jiaming Shen for his valuable
comments and suggestions in the preparation of the manuscript. Thanks are
also given to CEES Open Cruise for the Jiulong River estuary – Xiamen Bay
and Shuiying Huang and Jiezhong Wu for their organizational help.
Financial support
This research has been supported by the National Natural Science Foundation of China (grant nos. 42125603, 92051114, 91751207, 41721005, and 42188102).
Review statement
This paper was edited by Denise Akob and reviewed by two anonymous referees.
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