Vertical Methane Fluxes Driven by Methanogen in Riparian Buffers of
Urban Wetlands
Abstract
Abstract Background, Aims and Scope. Wetland soil is one of the largest
natural contributors to methane emissions, which is a prevalent
greenhouse gas. The vertical flux pattern of methane in soils is
unclear. To investigate the relationship between methane vertical flux,
soil total organic carbon (TOC) and methanogen, we were monitored in the
riparian buffer of a wetland park from August 2018 to January 2020. The
objectives of this study were to (1) analyze the vertical variation in
methane fluxes within the riparian buffer and (2) investigate the
vertical space relationships between methane fluxes, TOC and
methanogens. Furthermore, the results of this study could provide better
information for understanding the vertical linkage between methane, TOC
and methanogens. Methods. The study area is the Living Water Garden
(LWG), a wetland park in Chengdu, Sichuan Province, western China
(30◦40’ N, 104◦05’ E), which is a city park using a constructed wetland
system (CW) to treat polluted water from the Jin River. The sampling
site is close to the park inlet, located on the bank of the Jin River, a
flat riparian buffer with an area of about 100 m2 (Fig. 1c, the red
dashed box). Methane flux was measured once per month (in mid-month)
using a portable greenhouse gas flux measurement system (WS-L1820, WEST
Ltd., Italy). The sampling frequency is one time on a selected day and
the sampling time was between 11:00 am and 12:00 am. There are 6
selected monitoring sites with 4 monitoring depths including surface,
5cm, 10cm and 15cm. Soil sampling and methane flux measurements are
performed on the same days. After methane flux monitoring, soil samples
were collected. Soil sampling sites were also same as the methane
monitoring sites. At each sampling site, soil samples were excavated at
depths of 0-5 cm, 5-10 cm and 10-15 cm. Gene copies of the methanogens
(mcrA) were determined by q-PCR on the ABI 9700 Real-Time PCR system.
Sequencing data was processed using the quantitative insights into the
microbial ecology (QIIME) pipeline. SPSS software (version 21, SPSS
Inc., USA) and the software package R (R Foundation for Statistical
Computing, Austria) were used for statistical analyses and data
graphing. Structural equation model (SEM) was conducted using the AMOS
statistical software (version 21, IBM SPSS, USA). Results. During the
study period, the average surface methane emission was 81.86 mg m-2 h-1
and ranged from 20.42 mg m-2 h-1 to 190.75 mg m-2 h-1. Cumulative
methane emissions from studied area was 7.26 kg CO2eq m−2 year−1 and the
global warming potential (GWP) was at a moderate level. The results
reveal that the Methanobacteriaceae, Methanosarcinaceae and
Methanoregulaceae were the major methanogenic microorganisms in the
study area. The mathematical regression of methane flux (z, mg m-2 h-1)
with soil depth (x, cm) and TOC (y, g kg-1) was as follows: z = 52860.66
+ 54.44x - 2.96x2 - 26788.64y + 4487.80y2 - 249.34y3 (R2=0.82). It
indicates that the relatio