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ORIGINAL PAPER
Methanogenic community compositions in surface sediment
of freshwater aquaculture ponds and the influencing factors
Limin Fan .Wei Wu .Liping Qiu .Chao Song .Shunlong Meng .
Yao Zheng .Gengdong Hu .Dandan Li .Jiazhang Chen
Received: 3 March 2017 / Accepted: 17 August 2017 / Published online: 24 August 2017
ÓSpringer International Publishing AG 2017
Abstract Aquaculture ponds represent ecologically
relevant environments to study the community com-
position and diversity of methanogenic assemblages,
as well as their interactions with cultivated species and
chemical indicators. In this study, aquaculture ponds
with crab (Eriocheir sinensis), oriental river prawn
(Macrobrachium nipponense), perch (Micropterus
salmonides) and Wuchang fish (Parabramis pekinen-
sis) were sampled, and Illumina high-throughput
sequencing was used to investigate the methanogenic
communities. The results revealed that the abundant
methanogenic orders in surface sediment were Metha-
nomicrobiales,Methanosarcinales and Methanocel-
lales. The relative abundance of Methanocellales was
higher in crab and prawn ponds as compared to other
ponds. Methanogenic 16S rRNA gene abundance and
beta diversity of the community was affected by the
cultivated species. Methanogenic communities in
aquaculture ponds with higher contents of total
nitrogen and organic matter had decreased species
richness, while those with higher contents of ammonia
and nitrite had an overall decreased abundance of
methanogens and their respective diversities. Overall,
in addition to the differences in cultivated species, the
consequent differences in farming practices including
the types and amounts of feeds used, the contents of
total nitrogen, organic matter, ammonia and nitrite
could all influence the methanogenic community in
surface sediment of aquaculture ponds.
Keywords Methanogenic community Sediment
Aquaculture pond Influencing factors
Introduction
Many food system activities give rise to the production
of greenhouse gases (GHGs), among which agricul-
tural production processes contribute significantly to
emissions. Aquaculture provides a large amount of
aquatic products to consumers, and the relatively high
densities of cultivated species and the continuous
nutrient input are the main features of this system.
However, even though we know aquaculture is a
significant source of GHGs (Hu et al. 2014; Yang et al.
2015), few field measurements have been taken. More
measurements must be taken for us to gain further
insight into national and global levels of GHGs (Liu
et al. 2015). Furthermore studies relating GHG
Electronic supplementary material The online version of
this article (doi:10.1007/s10482-017-0932-5) contains supple-
mentary material, which is available to authorized users.
L. Fan W. Wu L. Qiu C. Song S. Meng
Y. Zheng G. Hu D. Li J. Chen (&)
Freshwater Fisheries Research Center, Chinese Academy
of Fishery Sciences, Scientific Observing and
Experimental Station of Fishery Resources and
Environment in the Lower Reaches of the Yangtze River,
Wuxi 214081, China
e-mail: chenjz@ffrc.cn
123
Antonie van Leeuwenhoek (2018) 111:115–124
https://doi.org/10.1007/s10482-017-0932-5
emission levels to microbial communities in aquacul-
ture systems would provide important insights.
Methanogens, which are strictly anaerobic
microorganisms that occur in almost all anoxic
habitats on earth, are traditionally thought to belong
to the phylum Euryarchaeota, and until recently were
classified into seven orders: Methanobacteriales,
Methanococcales,Methanocellales,Methanomicro-
biales,Methanopyrales,Methanosarcinales and
Methanomassiliicoccales (Iino et al. 2013;So
¨llinger
et al. 2015). Moreover, according to So
¨llinger et al.
(2015), the methanogenic orders obtained according
to the database within the class Thermoplasmata
should be Methanomassiliicoccales. Methane has a
relative global warming potential (GWP) 28 times
that of carbon dioxide (CO
2
) on mass basis over a
100 year time horizon (Allen et al. 2013). Methano-
genesis is a final product of organic matter degrada-
tion in anoxic environments (Conrad 2010) including
aquaculture pond sediments. The increased input of
organic nutrition supply the initial carbon sources for
methanogenesis and promotes the formation of
anaerobic conditions in pond sediments. Since
anaerobic conditions predominate in these environ-
ments, methanogenesis and methanogenic communi-
ties in these systems must be investigated further.
Additionally, the investigation of methanogenic
community composition and the influencing factors
in aquaculture ponds sediment could help provide
insight into the distributions of these environmentally
relevant populations, and to provide data for finding
ways of reducing methane emissions from the
system.
As an important agricultural habitat, rice paddy soil
has been given significant attention by researchers in
the investigation of agriculturally relevant methano-
genic communities (Großkopf et al. 1998; Watanabe
et al. 2004; Liu et al. 2015,2016b; Zu et al. 2016). Rice
is the world’s most important agronomic plant, with
nearly 150 million ha under cultivation globally
(Roger 1996). It has been reported that rice paddy
soil generates about 12.5% of anthropogenic CH
4
(Allen et al. 2013). Aquaculture ponds are another
kind of important agriculture habitat, similar to rice
paddy soil because of the flooded, anaerobic condi-
tions. These systems are also an important source of
atmospheric methane, although no exact global
accounting numbers have been reported. In addition,
aquaculture ponds are physicochemically diverse
owing to the feeding and physiological characteris-
tics of the cultivated species. Accordingly, in this
study, aquaculture ponds with crab, oriental river
prawn, perch and Wuchang fish were selected to
investigate methanogenic communities in surface
sediment and the influencing factors, to improve our
understanding of the methanogens in aquaculture
pond systems.
Materials and methods
Sample collection
Two crab ponds, two oriental river prawn ponds, two
perch ponds and two Wuchang fish ponds were
selected as the target ponds to investigate the
methanogenic communities and their responses to
cultivated species and some chemical indicators. The
farm locations and coordinates are listed in Table S1
and all the ponds in this survey have been continuously
used for cultivation of the corresponding species for
many years. In the process of crab and oriental river
prawn cultivations, the submerged aquatic plants need
to be planted. Trash fish (mainly including hemiculter
leucisculus and small crucian carp) plus corn was the
main food for crab. The perch cultivation mainly
depended on fresh ice fish. The Wuchang fish and
oriental river prawn cultivation mainly depended on
formulated feeds. Based on previous experience, the
average yields were about 0.1, 0.15 and 3.7 kg m
2
for
crab, orential river prawn, Wuchang fish cultivation
and perch cultivation, respectively.
The surface sediment samples were collected with a
gravity-type cylindrical sampler from all the ponds on
May 30 and August 14, 2016. After that, all the
samples were transported with liquid nitrogen to the
laboratory and stored at -80 °C until further analysis.
At the end of the experiment, six samples per pond
were obtained, denoted by the labels OP11_1,
OP11_2, and OP11_3, where OP represented Oriental
river prawn pond sediment samples, the first number
‘‘1’’ represented the No. 1 pond, and the second
number ‘‘1’’ represented the first time collection (May
30), and the numbers after the underline represented
the three different samples in each pond per time.
Similar labeling was used for Crab sediment samples
(CP), Wuchang fish samples (WP), and Perch samples
(PP).
116 Antonie van Leeuwenhoek (2018) 111:115–124
123
DNA extraction, methanogenic 16S rRNA gene
amplification, and high-throughput sequencing
analysis
Microbial DNA was extracted in duplicate from about
0.5 g of each sediment sample using the PowerSoil
DNA Isolation Kit (MO BIO, USA) according to the
manufacturer’s protocols. The DNA was quantified
and then stored at -20 °C for further usage.
The methanogenic 16S ribosomal RNA gene were
amplified by PCR(95 °C for 3 min, followed by 30
cycles at 95 °C for 30 s, 55 °C for 30 s, and 72 °C for
45 s and a final extension at 72 °C for 10 min)using
primers 0357F 50-barcode-CCCTACGGGGCGCAG-
CAG-30and 0691R 50-GGATTACARGATTTC–AC-
30(Watanabe et al. 2004), where the barcode was an
eight-base sequence unique to each sample. PCR
reactions were performed in triplicate 20 lL mixture
containing 10 ng of template DNA, 2 lLof109
FastPfu Buffer (TransGen Biotech, China), 2 lLof
2.5 mM dNTPs, 0.8 lL of each primer (5 lM), 0.2 lL
of FastPfu Polymerase (TransGen Biotech, China),
and 0.2 lL of Bovine serum albumin (BSA).
The PCR products from the three replicate ampli-
fications were extracted from 2% agarose gels,
purified using the AxyPrep DNA Gel Extraction Kit
(Axygen Biosciences, Union City, CA, US) and
quantified with a QuantiFluorTM-ST fluorometer
(Promega, USA) and pooled in equimolar concentra-
tions. Amplicons were then paired-end sequenced
(2 9300) on an Illumina MiSeq platform according
to the standard protocols at Majorbio Bio-Pharm
Technology Co., Ltd., Shanghai, China.
Real-time quantitative PCR
The methanogenic 16S rRNA gene quantitative PCR
was conducted in triplicate using the SYBR Green
Real-Time PCR Kit [ABI Power SybrGreen qPCR
Master Mix (2X)]. The real-time PCR (qPCR) assays
were performed on an ABI 7500 qPCR System.
Primers used in this study were the same as those used
for Illumina sequencing of methanogenic 16S rRNA
gene.
Bioinformatics analysis
The acquired raw fastq sequences were demultiplexed,
quality-filtered by removing primers and barcodes
using Trimmomatic (Bolger et al. 2014) and FLASH
(Reyon et al. 2012) software. The criteria and main
steps were the same as described previously (Fan et al.
2016). Operational taxonomic units (OTUs) were
clustered with a similarity threshold of 97% using
Usearch (version 7.1) (Tonge et al. 2014), and
chimeric sequences were identified and removed
using Usearch (version 7.1). The 16S rRNA gene
sequences were then assigned to taxa using the
Ribosomal Database Project (RDP) Classifier (Cole
et al. 2009) against the SILVA 16S rRNA database
(Quast et al. 2013) at a 70% confidence level. The
Good’s coverage, the ACE index and the Shannon
index values were all generated by using MOTHUR
(Version 1.34.3) (Schloss et al. 2009). Analysis of
Similarity (ANOSIM) was performed using PRIMER-
E (version 5.2.8) (Clarke and Gorley 2001). Redun-
dancy Analysis (RDA) and the following environ-
mental interpretations were all conducted by using R
software (Team CR 2012).
Determination of chemical parameters
The sediment nutrient contents, i.e. ammonium nitro-
gen and nitrite nitrogen were measured using the
Nessler colorimetric. Organic matter (OM) was
determined using the oxidation. Total nitrogen (TN)
and total phosphorous (TP) were measured using the
Kjeldhal method and UV spectrophotometry.
Statistical analysis
The one-way ANOVA and the Spearman correlation
analysis were all performed using IBM SPSS Statistics
20.0 software (Feeney 2012). The multiple compar-
isons were performed with the Least-significant dif-
ference (LSD) method. A pvalue of \0.05 was
accepted as statistically significant.
Results
Variations of chemical parameters in surface
sediment of aquaculture ponds
Figure 1shows the average content of total phospho-
rous, total nitrogen, organic matter, ammonia nitrogen
and nitrite nitrogen in surface sediment of crab ponds,
oriental river prawn ponds, perch ponds and Wuchang
Antonie van Leeuwenhoek (2018) 111:115–124 117
123
fish ponds. Furthermore, we compared the content of
the five environmental variables between different
cultivated ponds. The results revealed that the contents
of total nitrogen, total phosphorous and organic matter
were all significantly (p\0.05) higher in surface
sediment of Wuchang fish ponds than in any other
cultivated ponds. The contents of nitrite and ammonia
nitrogen showed no significant differences between
different cultivated ponds (p[0.05).
Methanogenic communities in surface sediment
of aquaculture ponds and the influencing factors
After Illumina sequencing and quality filtering, we
excluded the OTUs that did not belong to the phylum
Euryarchaeota and obtained a total of 740, 570 reads
(covering a proportion of 99.41% of the total reads)
and 277 OTUs from each of the sediment samples. The
rarefaction curves approached the saturation plateau
(Fig. S1), indicating that a reasonable number of
methanogens had been sampled. Good’s coverage
estimations revealed that 99.76–99.94% of the metha-
nogenic species were obtained in each sediment
sample, indicating that the sequencing depth was
sufficient for a community analysis.
As mentioned above, all methanogens were observed
to most probably comprise of members from the
seven orders of Methanobacteriales,Methanococcales,
Methanocellales,Methanomicrobiales,Methanopyrales,
Methanosarcinales and Methanomassiliicoccales.Thus
we investigated the methanogenic community composi-
tions at the order level. The main orders are listed in
Fig. 2,asMethanomicrobiales (representing 50.2% of
the relative average abundance), Methanosarcinales
(31.7%), Methanocellales (11.1%), Thermoplasmatales
(3.8%) and Thermoplasmata_unclassified (1.2%).
Furthermore, we investigated the factors influenc-
ing the distributions of the five main methanogenic
orders. At first, we compared the relative abundance of
the five orders between the ponds of different culti-
vated species, and the results revealed that only the
abundances of Methanocellales and Thermoplas-
mata_unclassified showed significant differences
between ponds of different cultivated species
(p\0.05). Among them, Methanocellales showed
the highest abundance in oriental river prawn ponds,
and Thermoplasmata_unclassified showed the lowest
abundance in crab ponds. When the Spearman corre-
lation analysis was performed on environmental
variables and the five main methanogenic orders, the
results showed that Methanocellales correlated posi-
tively with ammonia and nitrite (p\0.05). While the
Thermoplasmatales correlated negatively with TP, TN
and OM (p\0.05) (Table 1).
Methanogen16S rRNA gene abundance also
showed significant (p\0.05) differences between
ponds of different cultivated species (Fig. 3). They
showed the lower abundances in crab ponds and perch
Fig. 1 Chemical parameter results for sediment samples
collected in the four species of aquaculture ponds. a–eRepresent
the contents of TP, TN, OM, ammonia nitrogen and nitrite
nitrogen respectively (wet weight); the letters at the right side of
the columns show the differences between groups. The same
letters mean no significant differences, while different letters
mean that there are statistically significant differences between
groups at 95% level
118 Antonie van Leeuwenhoek (2018) 111:115–124
123
ponds. Furthermore, correlation analysis revealed that
they negatively correlated with the ammonia content
in surface sediment (p\0.05) (Table 2).
Alpha diversity of methanogenic communities
and the influencing factors
Besides the specific orders present in these agricul-
turally relevant environments, the study also covers
the alpha diversity of these methanogenic communi-
ties and their influencing factors. The results are
shown in Fig. 4and Table 2. We found that there was
no significant difference for species richness (Ace
index) and diversity (Shannon index) among the
methanogens in the ponds of four cultivated species
(Fig. 4). However, the values of these two indices
showed different response patterns to the concentra-
tion changes of environmental variables (Table 2).
The Ace index values correlated negatively with the
total nitrogen and organic matter content in the
aquaculture pond surface sediment (p\0.05). The
Shannon index values exhibited no correlation with
any of the five environmental variables (p[0.05).
Fig. 2 The methanogenic
community compositions in
order level in surface
sediment of aquaculture
ponds. The same letters
mean no significant
differences, while different
letters mean that there are
statistically significant
differences between groups
at 95% level
Table 1 Spearman correlation analysis on environmental variables and the main methanogenic orders
Dependent variables TP TN OM Ammonia Nitrite
RpRpRpRpRp
Methanomicrobiales 0.116 0.481 -0.066 0.689 0.123 0.455 -0.249 0.126 -0.260 0.109
Methanosarcinales 0.024 0.884 0.019 0.906 0.029 0.858 -0.001 0.994 -0.039 0.814
Methanocellales -0.168 0.306 -0.168 0.305 -0.255 0.117 0.392 0.014* 0.362 0.023*
Thermoplasmatales -0.446 0.004* -0.331 0.039* -0.352 0.028* -0.144 0.379 -0.233 0.154
Thermoplasmata_unclassified -0.297 0.067 -0.005 0.977 -0.231 0.157 -0.312 0.053 -0.316 0.050
* denotes significance at 95% level
Fig. 3 The methanogenic archaeal 16S rRNA gene abundances
in surface sediment of aquaculture ponds. The same letters mean
no significant differences, while different letters mean that there
are statistically significant differences between groups at 95%
level
Antonie van Leeuwenhoek (2018) 111:115–124 119
123
Similarity analysis of methanogenic communities
and the influencing factors
We performed the ANOSIM to test whether there were
significant differences between the four groups repre-
senting methanogenic communities in surface sediment
of aquaculture ponds with four species cultivated. The
result are shown in Table 3. From the table, we found
that there were several significant differences between
the four groups, and that variations were mainly from
the differences between Wuchang fish ponds and two
kinds of crustacean ponds.
In order to further investigate what kind of envi-
ronmental variables affected the ordinations of the
methanogenic communities in surface sediment,
redundancy analysis was performed (Fig. 5) and the
effects of environmental interpretations were tested
(Table 4). The results showed that methanogenic
communities in surface sediment of Wuchang fish
ponds visually differed from those in other cultivated
species’s ponds, which was consistent with the
previous ANOSIM results. The content of TP, TN
and OM were related to the methanogenic communi-
ties in surface sediment of Wuchang fish ponds, and
the content of nitrite and ammonia were related to that
of other ponds. Nevertheless, only the influences by
the organic matter and nitrite contents were significant
(p\0.05).
Discussion
Detailed taxonomic information on methanogenic
communities in sediment of aquaculture ponds
and the influencing factors
Here, we described the first high-depth coverage
taxonomic survey of methanogenic communities in
Table 2 Spearman
correlation analysis on
environmental variables and
Ace index, Shannon index
and methanogenic 16S
rRNA gene abundances
* denotes significance at
95% level
Environmental variables Ace Shannon 16S rRNA gene abundance
Pr Pr P r
Total phosphorous 0.058 -0.307 0.398 0.139 0.995 -0.001
Total nitrogen 0.009* -0.145 0.694 0.065 0.372 0.147
Organic matter 0.024* -0.361 0.656 -0.074 0.147 0.237
Ammonia 0.162 0.228 0.841 -0.033 0.001* -0.520
Nitrite 0.557 -0.097 0.439 -0.127 0.657 0.073
Fig. 4 Richness (the Ace index) and diversity (the Shannon
index) of methanogenic communities in surface sediment of
aquaculture ponds. aand brepresent the changes of the Ace
index values and Shannon index values respectively. The same
letters mean no significant differences between groups at 95%
level
Table 3 The ANOSIM of methanogenic communities in
aquaculture pond sediment
Groups R value pvalue
Global 0.182 0.001*
Crab/oriental river prawn 0.060 0.150
Crab/perch 0.093 0.182
Crab/Wuchang fish 0.369 0.001*
Oriental river prawn/perch 0.027 0.311
Oriental river prawn/Wuchang fish 0.260 0.006*
Perch/Wuchang fish 0.148 0.119
Crab and oriental river prawn/fish 0.200 0.001*
* denotes significance at 95% level
120 Antonie van Leeuwenhoek (2018) 111:115–124
123
surface sediment of aquaculture ponds. The
results showed that most of the sequences were
affiliated with Methanomicrobiales,Methanosarci-
nales,Methanocellales and Thermoplasmatales. The
two most abundant orders in the present study,
Methanomicrobiales and Methanosarcinales, have
been reported to mainly comprise hydrogenotrophic
methanogens and acetoclastic methanogens, respec-
tively (Garcia et al. 2000), indicating that both
hydrogenotrophic and acetoclastic methanogenesis
was occurring, and the hydrogenotrophic methano-
gens dominated the system. That was different from
some previous reports on freshwater wetlands (Conrad
1999; Banning et al. 2005), that acetoclastic methano-
gens were the dominant methanogenic groups. Mean-
while, Methanocellales, the third most abundant order
in the present study, was commonly found to be active
in rice soil and wetland where low H
2
concentrations
of 1–10 pa prevailed (Thauer et al. 2008). This might
indicate that some of them also have good adaptability
to H
2
concentrations. As for the sequences classified to
the order Thermoplasmatales, as mentioned above,
these sequences actually belong to the seventh order of
methanogenic archaea, Methanomassiliicoccales
(Borrel et al. 2014;So
¨llinger et al. 2015)(Thermo-
plasmatales-related).
In comparison, the main composition in surface
sediment of aquaculture ponds was different from
another important agriculture habitat, the rice soils,
which were Methanocellales,Methanomicrobiales,
Methanobacteriales and Methanosarcinales (Wu et al.
2009). Owing to the fact that the order Methanomas-
siliicoccales was only proposed and confirmed in 2012
(Dridi et al. 2012; Paul et al. 2012), then the main
differences in the methanogenic orders between the
two habitats could only be summarized that the order
Methanobacteriales was not the dominant member in
surface sediment of aquaculture pond in the present
study. One of the main differences between the
environments is the depth of the flooded water,
combined with the fact that the rice stems can
transport air into the rice soils, raising oxygen content
of the soils when compared to the sediment of the
aquaculture ponds. These could be contributing fac-
tors driving the differences in methanogenic commu-
nities observed in aquaculture ponds and rice paddy
soil. In addition, the rice cultivar and N fertilizer (Wu
et al. 2009), climate change (Liu et al. 2016a), and the
Fig. 5 Redundancy
analysis (RDA) of
methanogenic archaeal 16S
rRNA gene in surface
sediment of aquaculture
ponds. The sample names
start with C,O,W,
Prepresented the samples
collected from the ponds of
crab, oriental river prawn,
Wuchang fish and perch
respectively. The blue arrow
showed the chemical
parameters of sediment
Table 4 The tests of correlation significance on environmen-
tal vectors and RDA ordinations of methanogenic communities
in surface sediment of aquaculture ponds
Environmental variables R
2
pvalue
TP 0.1307 0.0819
TN 0.1466 0.0619
OM 0.2775 0.0029*
Ammonia 0.0079 0.8601
Nitrite 0.2839 0.0049*
* denotes significance at 95% level
Antonie van Leeuwenhoek (2018) 111:115–124 121
123
time of the continuous planting (Liu et al. 2016b)
could all affect methanogenic communities in rice
soil, which make the situation in rice soils much more
complicated. Additionally, aquaculture ponds were
characterized by a large number of organic feed inputs
and the existence of cultivated organisms. The amount
of organic feeds input coupled with the different
cultivated organisms would be the potential factors
influencing the different methanogenic communities
that are in sediment of aquaculture ponds. Further-
more, the different methanogens might prefer habitats
with different organic matter content.
As for the habitat of aquaculture pond systems, the
methanogenic communities could have been affected
by the differences in cultivated species. Because
different cultivated species have different physiolog-
ical characteristics, including different types and
amounts of feed demands. The results of the present
study support the possibility that the order of
Methanocellales could be affected by the cultivated
species. The order of Methanocellales was observed at
higher abundances in crab and prawn pond sediment,
indicating a positive response to the culture of crab and
oriental river prawn, although it could also be related
to the use of formula feed in these ponds. Ammonia
positively correlated to the Methanocellales abun-
dance, but not to the different culture species, which
indicated that ammonia was not the key factor to make
the Methanocellales abundance in aquaculture ponds
surface sediment being different between different
cultivated species. However, nitrite showed the pos-
sibilities of making the Methanocellales abundance in
surface sediment of crab ponds, oriental river prawn
ponds, and perch ponds higher.
Abundance and diversity of methanogenic
communities in sediment of aquaculture ponds
and the influencing factors
In the present study, the abundances of methanogenic
16S rRNA genes, rather than the Ace and Shannon
indices values of methanogenic communities in sed-
iment of aquaculture ponds, showed significant dif-
ferences between different cultivated species. This
might indicate that the differences of cultivated
species and the consequent differences of farming
practices have not significantly affected the alpha
diversity of methanogenic communities, but affected
the numbers of methanogens in surface sediment of
aquaculture ponds. The oriental river prawn and
Wuchang fish ponds showed higher abundances of
methanogenic 16S rRNA gene in sediment, a situation
that might be related to these two cultivated organisms
being fed on formula feeds. Meanwhile, the methano-
genic 16S rRNA gene abundance correlated nega-
tively to the ammonia content, and the Ace index
value, rather than the Shannon index value. They also
correlated negatively to the contents of total nitrogen
and organic matter. This might indicate that more
nutrient inputs could cause a decline in methanogenic
archaeal species richness in surface sediment of
aquaculture ponds. It was observed that the increase
of ammonia content significantly decreased the abun-
dances of some abundant species, which was consis-
tent with the fact that ammonia is known to have an
inhibitory effect on methanogenesis (Sossa et al.
2004).
Furthermore, similarity analysis by ANOSIM
showed that the methanogenic community in sediment
of Wuchang fish ponds was significantly different
from that in pond sediment of other cultivated species.
And this could be supported by ordination analysis
with RDA. Moreover, the RDA analysis and the test
on environmental vectors and RDA ordinations
showed that the higher contents of organic matter
were closely related to RDA ordinations of methano-
genic communities in sediment of Wuchang fish
ponds. As mentioned above, methanogenic archaea
are responsible for the final degradation step of
organic matter in anoxic sediments. Thus, the avail-
ability of organic matter is important in aquaculture
ponds, as is generally known for methanogenesis
(Matheuscarnevali 2009). In Wuchang fish ponds, the
higher stocking densities and the use of formulated
feed could make more bait and feces sink into the
sediment, which was the key factor increasing the
availability of organic matter, which made the
methanogenic communities here different from other
culture ponds. Still, as mentioned above, the metha-
nogenic 16S rRNA gene abundances in surface
sediment of Wuchang fish ponds were also the highest.
Thus, increasing the organic matter availability was so
important to methanogenesis that it could affect not
only the methanogenic community diversity, but also
the number of methanogens.
Although the methanogenic communities in surface
sediment of oriental river prawn ponds presented no
significant differences from that of other culture
122 Antonie van Leeuwenhoek (2018) 111:115–124
123
species such as Wuchang fish, the methanogenic 16S
rRNA gene abundance in these ponds were also higher
than that in crab and perch ponds. This might be
attributed to the fact that oriental river prawns in these
ponds were also fed on formula feeds, although the
feeding amounts were not as high as that for Wuchang
fish. The common feed coefficients for oriental river
prawn and Wuchang fish in China were about 1–1.5
and 1–1.2, respectively). Therefore, whether the
formula feed used was an important factor for the
number of methanogens in surface sediment of
aquaculture ponds. In addition, the content of nitrite
in surface sediment of aquaculture ponds was another
factor that could affect methanogenesis. The present
study showed that the contents of nitrite in sediment
were related to the RDA ordinations of methanogenic
communities, and the lower contents helped to make
the methanogenic communities in surface sediment of
Wuchang fish ponds different from others. Thus, the
study established that the contents of nitrite in
sediment could not only inhibit the production of
CH
4
(Klu
¨ber and Conrad 1998), but also cause
changes in methanogenic community diversity.
Conclusion
In summary, the abundant methanogenic orders in sur-
face sediment of the aquaculture ponds were Metha-
nomicrobiales,Methanosarcinales,Methanocellales
and Methanomassiliicoccales, among which the rela-
tive abundance of Methanocellales were higher in crab
and prawn ponds than those in other ponds. This might
be related to the uses of formula feeds in these ponds.
Meanwhile, although the differences of cultivated
species have not affected the alpha diversity of the
archaeal methanogenic community, it could affect the
number of methanogens and the beta diversity of
archaeal methanogenic communities. The types and
amounts of the feeds were the two important factors
influencing the archaeal methanogenic communities
and might be important causes of making the archaeal
methanogenic communities’ being affected by the
differences of cultivated species. In addition, more
nutrient inputs represented by higher contents of total
nitrogen and organic matter could reduce the archaeal
methanogenic species richness, while the contents of
ammonia and nitrite could affect the archaeal
methanogenic communities by decreasing the number
of methanogens and influencing their diversities
respectively.
Acknowledgement This research was supported by the
Special Fund of Fundamental Scientific Research Business
Expense of the Central Public Research Institutes (Grant No.
2015JBFM12).
Conflict of interest All the authors declare that we have no
financial and personal relationships with other people or orga-
nizations that can inappropriately influence our works, there is
also no professional or other personal interest of any nature or
kind in any product, service and/or company that could be
construed as influencing the position presented in, or the review
of, the manuscript entitled.
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