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RESEARCH PAPER
On the hidden diversity and niche specialization of the
microbial realm of subterranean estuaries
Elisa Calvo-Martin
1,2
| Eva Teira
3
| Xosé Ant
on
´
Alvarez-Salgado
1
|
Carlos Rocha
4
| Shan Jiang
4,5
| Maider Justel-Díez
3
|
Juan Severino Pino Ib
anhez
1,4
1
Organic Geochemistry Lab, Department of
Oceanography, Instituto de Investigaci
ons
Mariñas, Consejo Superior de Investigaciones
Científicas (CSIC), Vigo, Spain
2
PhD Program in Marine Science, Technology
and Management, Universidade de Vigo,
Vigo, Spain
3
Departamento de Ecología y Biología
Animal, Universidade de Vigo, Centro de
Investigaci
on Mariña da Universidade de Vigo
(CIM-UVigo), Vigo, Spain
4
School of Natural Sciences, Trinity College
Dublin, Dublin 2, Ireland
5
State Key Laboratory of Estuarine and
Coastal Research, East China Normal
University, Shanghai, China
Correspondence
Elisa Calvo-Martin and Juan Severino Pino
Ib
anhez, Organic Geochemistry Lab,
Department of Oceanography, Instituto de
Investigaci
ons Mariñas (IIM-CSIC), Rúa
Eduardo Cabello, 6, 36208 Vigo, Pontevedra,
Spain.
Email: ecalvo@iim.csic.es and jseverino@iim.
csic.es
Funding information
Agencia Estatal de Investigaci
on (Spain),
Grant/Award Numbers: CTM2017-83362-R,
IN606A-2021/022, INTERESproject; H2020
Marie Skłodowska-Curie Actions, Irish
Research Council, Grant/Award Numbers:
713279, CLNE/2017/210; Spanish
Government, Grant/Award Number: FPU PhD
grant number FPU20/04707; Axencia Galega
de Innovaci
on, Grant/Award Number: IN606A-
2021/022
Abstract
Subterranean estuaries (STEs) modulate the chemical composition of conti-
nental groundwater before it reaches the coast, but their microbial commu-
nity is poorly known. Here, we explored the microbial ecology of two
neighbouring, yet contrasting STEs (Panx
on and Ladeira STEs; Ría de
Vigo, NW Iberian Peninsula). We investigated microbial composition (16S
rRNA gene sequencing), abundance, heterotrophic production and their
geochemical drivers. A total of 10,150 OTUs and 59 phyla were retrieved
from porewater sampled during four surveys covering each STE seepage
face. In both STEs, we find a very diverse microbial community composed
by abundant cosmopolitans and locally restricted rare taxa. Porewater oxy-
gen and dissolved organic matter are the main environmental predictors of
microbial community composition. More importantly, the high variety of ben-
thic microbiota links to biogeochemical processes of different elements in
STEs. The oxygen-rich Panx
on beach showed strong associations of the
ammonium oxidizing archaea Nitrosopumilales with the heterotrophic com-
munity, thus acting as a net source of nitrogen to the coast. On the other
hand, the prevailing anoxic conditions of Ladeira beach promoted the domi-
nance of anaerobic heterotrophs related to the degradation of complex and
aromatic compounds, such as Dehalococcoidia and Desulfatiglans, and the
co-occurrence of methane oxidizers and methanogens.
INTRODUCTION
In the permeable, underground land–ocean interface,
seawater mixes with fresh groundwater within coastal
aquifers forming subterranean estuaries (STEs:
Moore, 1999; Rocha et al., 2021). There, terrestrially
derived solutes such as nutrients, trace elements and
organic pollutants are transferred to the coast
Received: 4 April 2022 Accepted: 2 August 2022
DOI: 10.1111/1462-2920.16160
This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any
medium, provided the original work is properly cited and is not used for commercial purposes.
© 2022 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.
Environ Microbiol. 2022;1–23. wileyonlinelibrary.com/journal/emi 1
(Moore, 2010), where they may regulate primary pro-
duction (Lecher & Mackey, 2018) and trigger eutrophi-
cation (Hwang et al., 2005). The discharge at sea of
terrestrial groundwater is comprised within the wider
phenomenon of submarine groundwater discharge
(SGD). SGD refers to all the water flowing across the
seabed to coastal waters (Burnett et al., 2003), includ-
ing seawater recirculated inside the sediment and ter-
restrial groundwater. The combination of tidal, wave
and terrestrial hydraulic forcing, among other drivers,
generate complex advective porewater dynamics within
the seaward end of coastal aquifers (Robinson
et al., 2018) supporting a chemically reactive zone that
alters the composition of both terrestrial groundwater
and seawater entering it, before the resulting mixture is
discharged to coastal waters. Thus, STEs are hotspots
for the production, consumption and transformation of
nitrogen (Couturier et al., 2017;Ib
anhez et al., 2013;
Ib
anhez & Rocha, 2017; Spiteri, Slomp, Charette,
et al., 2008; Spiteri, Slomp, Tuncay, et al., 2008),
organic matter (Huettel et al., 2014;Ib
anhez &
Rocha, 2014; Jiang et al., 2020), phosphorus and trace
elements (Charette & Sholkovitz, 2002; Spiteri, Slomp,
Charette, et al., 2008; Spiteri, Slomp, Tuncay,
et al., 2008) as well as methane and CO
2
(Brankovits
et al., 2018; Pain et al., 2019).
Recently, the coastal aquifer microbiome has
gained attention due to the large diversity of microbial
processes occurring in STEs (reviewed by Archana
et al., 2021; Ruiz-Gonz
alez et al., 2021). In contrast
with the relative stability found in terrestrial aquifers
(Griebler & Lueders, 2009), the microbial community of
STEs needs to adapt to rapid and fluctuating changes
to their immediate environment. This flexibility results in
a highly diverse community composed by a mixture of
autochthonous microorganisms with seawater and
groundwater-associated taxa (Adyasari et al., 2019;
Chen et al., 2020; Degenhardt et al., 2020; Lee
et al., 2017). Microbial functional groups are distributed
following advective porewater circulation flowpaths
(Adyasari et al., 2019; McAllister et al., 2015), along
vertical and horizontal gradients of temperature, salinity
and redox-sensitive species (Adyasari et al., 2019,
2020; Degenhardt et al., 2020; Hong et al., 2019),
which oscillate with tidal forces (Lee et al., 2017).
Although information on the temporal variability of
microbial community composition is still scarce (Ruiz-
Gonz
alez et al., 2021), Degenhardt et al. (2020) found
that STEs contain a core of generalist microbes that is
relatively stable in time, similarly to that observed in
tidal sandy beaches (Boehm et al., 2014).
The study of the microbial community structure
within STEs has uncovered the potential roles of these
systems in the turnover of chemical elements at the
coast (Adyasari et al., 2019,2020; Degenhardt
et al., 2020), on local acidification (Héry et al., 2014)
and on the support of coastal aquifer food-webs
(Brankovits et al., 2017). Insights derived from these
studies include the identification of potential indicators
of faecal and pathogen pollution (Adyasari et al., 2019)
and potentially useful taxa for wastewater treatment
and bioremediation (Chen et al., 2020; Jin et al., 2021;
Ye et al., 2016). Nevertheless, the links between micro-
bial composition and the physical and geochemical
characteristics of STEs are still poorly described. The
limited environmental information available hinders the
identification of the geochemical drivers of microbial
community structure and composition in STEs
(Archana et al., 2021; Ruiz-Gonz
alez et al., 2021).
Here, we aim to understand prokaryote community
dynamics and their hydraulic and geochemical con-
straints inside STEs, at the seepage faces of sandy
beach aquifers. To this end, we studied the spatial and
temporal patterns of prokaryote community diversity
and composition, as well as prokaryotic abundance
and heterotrophic production at two distinct STEs. We
made, in parallel, an extensive characterization of envi-
ronmental geochemistry, including the dissolved
organic matter, frequently ignored in STEs as an envi-
ronmental driver despite evidence of being determinant
(Brankovits et al., 2017; Degenhardt et al., 2020;
Huang et al., 2021; Jiang et al., 2020). We also ana-
lysed the co-occurrence patterns between the prokary-
otic core taxa in relation with the biogeochemical
functioning of STEs.
EXPERIMENTAL PROCEDURES
Study site
The Ría de Vigo is a V-shaped coastal embayment
located at the northern limit of the Eastern Boundary
Upwelling Ecosystem of the Iberian-Canary current
(Arístegui et al., 2009). Water circulation in the outer
Ría de Vigo is largely controlled by coastal winds,
which favour upwelling from April to September and
downwelling for the remainder of the year, and riverine
discharge, which drives the estuarine circulation at the
inner part of the Ría ( ´
Alvarez-Salgado et al., 2003). As
a result of seasonal upwelling, the Ría de Vigo is
known for its high productivity, which sustains exten-
sive mussel aquaculture, shellfish gathering and small-
scale fisheries (Fern
andez et al., 2016). To date,
upwelling has been accepted as the main allochtho-
nous source of nutrients to the Ría de Vigo (58% of the
inorganic nitrogen input), followed by benthic minerali-
zation (23%), sewage (17%) and continental and atmo-
spheric sources (2%) (Fern
andez et al., 2016). The
contribution of sewage to inorganic nitrogen inputs has
reduced to less than 4% (unpublished data) by a
recently commissioned wastewater treatment plant.
Groundwater discharge was recently found to be a sig-
nificant source of freshwater to the Ría de Vigo,
2CALVO-MARTIN ET AL.
particularly important at the inner San Sim
on and
Baiona Bays (Figure 1A;Ib
anhez et al., 2021), and the
solute transport associated with this previously over-
looked source of continental waters is starting to
emerge (Calvo-Martin et al., 2021).
Two high-energy, wave-dominated beaches were
chosen at Baiona bay: Panx
on and Ladeira
(Figure 1A). Tidal regime in Baiona bay is semi-diurnal,
ranging from 3–3.5 m during spring tides to 1.5–2m
during neap tides (Martín Míguez, 2002). Ladeira beach
is located at the innermost, protected flank of Baiona
bay. It shows a reflective profile, with a well-developed
supra-tidal and a marked berm (Figure 1B). Behind
Ladeira beach, the Miñor, A Groba and Belesar rivers
converge in the A Ramallosa beach-barrier-lagoon
complex (Figure 1A). Fluvial sediments influence the
sedimentary composition of Ladeira beach, resulting in
the dominance of siliciclastic sands. Mean grain size is
0.245 mm with carbonate content below 5% (Queralt
et al., 2002). Seaweed accumulates at the intertidal
during autumn and spring (Alejo & Vilas, 1987). Com-
paratively, Panx
on beach is more exposed to the ener-
getic waves that enter Baiona bay during winter storms
(Alejo et al., 1999) and shows the typical profile of a
dissipative beach (Figure 1B). At the south, Panx
on is
limited by the mouth of the river Muiños, which also
influences the composition of beach sediments. Unimo-
dal fine sands dominate there, with a mean grain size
of 0.234 mm and high carbonate content (60%–65%;
´
Alvarez-V
azquez et al., 2003; Queralt et al., 2002).
Over the period covered by this study (February to
October 2019), both beaches showed similar porosity
(0.47 0.02 in Panx
on and 0.46 0.06 in Ladeira),
but slightly different particulate organic matter content
(1.33 0.10% dry weight in Panx
on and 0.93 0.40%
dry weight in Ladeira beach) and sediment organic C:N
molar ratio (10.7 3.5 in Ladeira and 3.2 0.8 in
Panx
on; Calvo-Martin et al., 2021).
Sampling strategy
Seasonal surveys were performed at the selected
STEs in February, May, July and October of 2019.
Those in February (winter) and May (spring) were pre-
ceded by storm events whereas those in July (summer)
and October (autumn) benefited from calm conditions.
Aquifer recharge was based on the water balance
FIGURE 1 (A) Location of the two studied STEs from Panx
on (42.14N, 8.82W) and Ladeira beaches (42.11N, 8.83W) within Baiona
Bay (Ría de Vigo, NW Iberian Peninsula). The surrounding rivers are marked in blue. (B) Schematic view of the main circulation patterns
observed inside Ladeira and Panx
on beaches. Red zones indicate low radon activities (i.e. coastal seawater influence), whereas blue zones
indicate high radon activities (i.e. continental groundwater influence). Source: Data used in the schemes correspond to those obtained during
may in Ladeira beach and October in Panx
on beach (taken from the study by Calvo-Martin et al., 2021). Sampled depths are marked with
circles. The schematic representation of the water table level at high tide (HT) and low tide (LT) is shown. FDT, fresh-groundwater discharge
tube; USP, upper saline plume
DIVERSITY OF STE MICROBIAL COMMUNITIES 3
conducted a month prior to each survey. October had
the highest water balance, followed by February and
May. July was characterized by low precipitation, yield-
ing a negative water balance (Calvo-Martin
et al., 2021). Surveys were always conducted during
spring tides to guarantee uniformity of oceanic forcing
between different field campaigns. Details of the sam-
pling strategy and conditions can be found in the study
by Calvo-Martin et al. (2021). Briefly, push–pull piezom-
eters (M.H.E. Products, USA) were used to sample the
upper (St3), middle (St2) and lower (St1) limits of the
permanently saturated, intertidal beach faces during
low tide (Figure 1B). At each sampling station across
the beach face, porewater was collected from 178 cm
(deep sampling depth) and 29 cm depth (shallow sam-
pling depth) using air-tight syringes connected to pie-
zometers with a screened section of 4 cm. The
presence of a gravel layer in Panx
on beach ( ´
Alvarez-
V
azquez et al., 2003) complicated the installation of the
178 cm piezometer and thus, the depth reached there
was variable (between 178 and 116 cm depth). In ben-
thic porewater studies, the available volume for extrac-
tion limits the vertical resolution of porewater solute
profiles. As much volume is extracted, as larger is the
volume of sediment affected and thus, the higher is the
potential interference among sampled depths. Depths
were chosen to ensure the biogeochemical gradients
observed in both STEs (Calvo-Martin et al., 2021) and
the three water bodies that shape tidal STEs (Calvo-
Martin et al., 2021; Robinson et al., 2006), were repre-
sented within sampling limitations.
Collected porewater samples were used to deter-
mine temperature, salinity, total alkalinity, pH, dis-
solved oxygen, radon (
222
Rn) and radium (
226
Ra)
activities, dissolved inorganic carbon (DIC), dissolved
inorganic nutrients (NO
3
,NO
2
,NH
4+
,PO
43
and
Si(OH)
4
), dissolved organic carbon (DOC), total dis-
solved nitrogen (TDN), coloured (CDOM) and fluores-
cent dissolved organic matter (FDOM), heterotrophic
prokaryote production (HPP), prokaryote abundance
(PA) and prokaryote community taxonomic composi-
tion using partial 16S rRNA gene sequencing. An
approximated total porewater volume of 1.5 L was col-
lected at each sampling depth, where 1 L was used for
microbial analyses. Samples for salinity, pH, DIC,
DOC, dissolved inorganic nutrients, TDN, CDOM and
FDOM were filtered on-site with pre-washed GF/F fil-
ters (Whatman, 25 mm of diameter). Samples for oxy-
gen, total alkalinity and pH determinations were
immediately transferred to the laboratory and analysed
on the same day. Samples for DOC, CDOM, and
FDOM were stored in the fridge and analysed within
3 days after collection. Aliquots for nutrient determina-
tions were kept frozen until analysis. Samples for DIC
were poisoned with HgCl
2
and kept in dark until analy-
sis. Sediment samples were taken to determine water
content, organic matter and total nitrogen and organic
carbon with mini coring liners (Calvo-Martin
et al., 2021). Porosity was determined as in the study
by Ib
anhez and Rocha (2014) (see Supplementary
Materials S1 for details on calculations).
Analytical methods
Chemical analysis
All the analytical methods were adapted to low sample
volumes. Temperature was measured in situ with an
accuracy of 0.1C. Salinity was measured in a Guildline
Portasal salinometer. Radon (
222
Rn) and radium
(
226
Ra) activities were determined in a Rad7 Radon
detector with a RAD H
2
O accessory (Durridge Com-
pany, Inc.). Samples (70 ml) were diluted in
222
Rn-free
water (250 ml final volume) and
222
Rn activities deter-
mined within 2 days after collection. Corrections were
applied for dilution and for internal
222
Rn decay during
the time span between collection and measurement.
Afterwards, the degassed samples were stored for
about 30 days (i.e. five times the half-life of
222
Rn) to
reach secular equilibrium between
226
Ra and
222
Rn.
226
Ra activities were then measured as the equilibrium
ingrowth of
222
Rn produced by
226
Ra. Porewater
222
Rn
equilibrium activities were obtained from the incubation
of sediment samples taken from both beaches with
222
Rn-free water in air-tight bottles for 30–40 days
(200 g dry weight; n=9 for each beach; Colbert &
Hammond, 2008). Inorganic nutrients were analysed
on an Alliance Futura segmented flow autoanalyser fol-
lowing standard colorimetric methods (Grasshoff
et al., 2009). Ammonium was analysed in the same
instrument following the fluorimetric method of Kérouel
and Aminot (1997). The spectrophotometric Winkler
method (Labasque et al., 2004) was used to measure
dissolved oxygen. An Aquatrode Plus electrode
(Methrom, Switzerland) was used to measure pH, with
an error of 0.01 units. Results are expressed in the
NBS scale at 25C. DIC was determined by flow injec-
tion analysis with conductivity detection (Hall &
Aller, 1992). For total alkalinity, samples were collected
directly from the piezometers in air-tight syringes and
measured within 24 h after sampling in a semi-
enclosed cell under a N
2
atmosphere following Perez
and Fraga (1987). An in-line GF/F filter (Whatman,
25 mm diameter) was used to remove particulate inor-
ganic carbon while transferring the sample to the
measuring cell.
The high-temperature catalytic oxidation method
(´
Alvarez-Salgado & Miller, 1998) was used to analyse
DOC and TDN after acidification to pH < 2 and removal
of DIC by de-bubbling with high purity N
2
. DOC and
TDN analysis were performed in a Shimadzu TOC-V
analyser connected in line to a nitrogen chemilumines-
cence measuring unit TNM-1.
4CALVO-MARTIN ET AL.
CDOM and FDOM were analysed in a 1 cm quartz
cuvette at room temperature (25C). First, CDOM
absorbance was recorded in a Beckham Coulter DU
800 spectrophotometer from 250 to 700 nm. Record-
ings were baseline corrected by subtracting the aver-
age absorbance between 600 and 700 nm from the
measured spectrum. The corrected absorbance was
multiplied by 2.303 and divided by the cuvette optical
path (0.01 m) to transform absorbance the Napierian
absorption coefficient (in m
1
). Absorption coefficients
at 254 nm (a
CDOM
(254)) and 340 nm (a
CDOM
(340);
Romera-Castillo et al., 2011) were used as proxies for
the abundance of conjugated carbon double bonds
(i.e. to DOC) and aromatic rings (i.e. to aromatic DOC),
respectively (Catal
a et al., 2018; Helms et al., 2008;
Weishaar et al., 2003). The ratio between the absorp-
tion coefficients at 254 nm and 365 nm (a(254/365))
was used as an indicator of the average molecular
weight of CDOM; the higher a(254/365), the lower aver-
age molecular weight (Weishaar et al., 2003). The ratio
between the spectral slopes at 275–295 nm and 350–
400 nm (SR) was used as an indicator of the origin of
CDOM (SR < 1 indicates terrestrial origin and SR > 1
marine origin; Helms et al., 2008). Subsequently,
FDOM was determined in a Perkin Elmer LS55 spectro-
fluorometer. FDOM was recorded at Peak A (general
humic substances), excitation/emission (Ex/Em) wave-
lengths of 250 nm/435 nm; Peak M (marine humic-like
substances), Ex/Em 320 nm/410 nm; Peak C (terres-
trial humic-like substances), Ex/Em 340 nm/440 nm;
and Peak T (protein-like material), Ex/Em
280 nm/350 nm (Coble, 1996; Nieto-Cid et al., 2005;
Stedmon & Nelson, 2015). Normalization to the Raman
area (Murphy et al., 2010) and corrections for inner fil-
tering effects (Ohno, 2002) were applied to the
measurements.
Prokaryotic abundance and heterotrophic
production
For prokaryote abundance, 3 μm pre-filtered samples
(10 ml) were fixed with 0.2 μm pre-filtered formaldehyde
(2% final concentration) for 30 min and thereafter fil-
tered in a multiple position filtration device connected to
a vacuum pump. Samples were filtered through a white
polycarbonate filter (0.2 μm pore size and 25 mm diam-
eter) with a nitrate cellulose filter holder (0.45 μm pore
size and 25 mm diameter) to guarantee the homoge-
nous distribution of cells. Filters were then washed
twice with Milli-Q water and dried at room temperature.
Filters were stored in vials at 20C until the analysis.
Prokaryotes were counted under a Leica DMBL
microscope equipped with a 100-W Hg-lamp. Cells
were stained with a mixture of DAPI (4-6-diamidinum-
2-phenidiol) with 5.5 part of Citifluor (Citifluor Ltd), 1 part
of Vectashield (Laboratorios vector Inc.) and 0.5 part of
saline phosphate with DAPI buffer solution (1 mg ml
1
of final concentration). Appropriate filter sets for DAPI
were used. More than 200 DAPI-stained cells were
counted per sample.
3
H-Leucine incorporation method modified by Smith
and Azam (1992) was used to estimate the heterotro-
phic prokaryote production (HPP). The 1 ml of 3 μm
pre-filtered samples (three replicates and two killed
controls) were spiked with 40 μl of leucine (47 μCi ml
1
specific activity stock solution) and incubated for 90 min
in the dark at in situ temperature. Leucine uptake rates
were converted to carbon uptake rates using a carbon
conversion factor of 3.1 kg C mol Leu
1
(Smith &
Azam, 1992).
DNA extraction, amplification, and sequencing
For sequencing analysis, porewater samples (1 L of vol-
ume) were filtered through 3 μm pore-size polycarbonate
filters and 0.2 μm pore size Sterivex Filter Units, immedi-
ately frozen with liquid nitrogen and stored at 80C.
The >3 μm fraction was not used since it retained vari-
able amounts of mineral particles. The DNA retained in
the 0.2 μm filters was extracted with a PowerWater DNA
isolation kit (Qiagen) following the manufacturer’s instruc-
tions. Qubit
®
2.0 fluorometer and Qubit dsDNA HS
Assay Kit (Thermo Fischer Scientific Inc, Massachusetts,
USA) were used to quantify DNA concentration. V4-V5
hypervariable region of 16S rRNA gene was amplified
using the primers 515F-Y (50-GTGYCAGCMGCCGCGG-
TAA-30) and 926R (50-CCGYCAATTYMTTTRAGTTT-30)
(Parada et al., 2015). This region was sequenced using
Illumina MiSeq platform and a minimum 2 250 bp
paired-end reads at the Fasteris Laboratory (Geneva,
Switzerland).
The data for this study have been deposited in the
NCBI GenBank (https://www.ncbi.nlm.nih.gov/
genbank) under accession numbers PRJNA822065.
Bioinformatics and statistical methods
Logares (2018) workflow was used to process
sequence reads. Raw reads were corrected with the
BayesHammer method (Nikolenko et al., 2013;
Schirmer et al., 2015) and corrected paired-end reads
were merged with PEAR software (Zhang et al., 2014).
Errors on sequences over 200 bp were checked and
de-replication was applied using the VSEARCH 2.14.1
tool (Rognes et al., 2016). To obtain OTU read abun-
dances, OTUs were mapped back at 99% similarity.
Chimera check and removal was performed using SIL-
VA_132_SSURef_Nr99 reference database (Quast
et al., 2013). Taxonomic assignment of 16S OTU reads
was obtained using BLAST (Altschul et al., 1990)
against SILVA database. OTUs with less than 200 bp,
DIVERSITY OF STE MICROBIAL COMMUNITIES 5
<60% coverage, <90% similarity and/or with 0.000001
e-values were removed. All OTUs that represented
chloroplasts, mitochondria, or eukaryote OTUs were
removed.
Statistical analyses were carried out in R v4.0.3
(Rstudio v1.4.1106 editor) using the ‘Vegan’(Oksanen
et al., 2020) and ‘phyloseq’v1.34.0 (McMurdie &
Holmes, 2013) packages, except for the Redundancy
Analysis from Distance-based Linear Modelling
(DistLM-RDA), which was performed in PRIMER
6 (Clarke & Gorley, 2006). Adjusted R
2
was used as a
selection criterion for the DistLM-RDA.
Overall, 467,829 reads and 19,150 OTUs were
retrieved from the microbial sequencing analysis of the
48 porewater samples from Panx
on and Ladeira bea-
ches. To normalize the total number of reads from each
sample, OTU abundance was rarefied to 1095 reads
per sample using the function rarefy_even_depth from
the ‘phyloseq’package, leaving the composition of the
microbial community in 52,560 reads and 10,150
OTUs. Centred-log ratio (CLR) transformation was
applied to the rarefied data prior to statistical analyses
(Gloor et al., 2017), except for the calculation of diver-
sity indexes (Shannon index, richness and Pielou’s
evenness) and the relative abundances of OTUs. Zero
values were replaced by 0.65 prior to CLR transforma-
tion (Gloor et al., 2017; Lubbe et al., 2021; Martín-
Fern
andez et al., 2003). Temperature, salinity, dis-
solved oxygen,
222
Rn,
226
Ra, total alkalinity, pH, DIC,
nitrate, nitrite, ammonium, phosphate, silicate, DOC,
TN, FDOM peak C and T, a
CDOM
(254), a
CDOM
(340), a
(254/365) and SR were selected as potential explica-
tive variables from all the environmental parameters
determined based on a variance inflation factor (VIF)
analysis. The mean values of these variables and their
standard deviations were included in the text. Then, Z-
score standardization was applied to the selected envi-
ronmental variables, heterotrophic production, and pro-
karyotic abundance. Spearman’s correlation between
phyla abundance and environmental factors was used
to cluster both community and environmental data in a
heatmap. Only significant correlations (ρvalue < 0.05)
were highlighted in the heatmap. Spearman’s correla-
tion among environmental values and among phyla
abundances were transformed into distances
(distance =1-rvalue) and added to the heatmap as
clusters for environmental and community data. Rela-
tionships among the top 75 OTUs present at least in
20% of the samples were explored through microbial
network analysis with Gephi (v.0.9.2.) based on Spear-
man’s correlations (ρ< 0.01) (Brisson et al., 2019).
Habitat filtering was applied on CLR-transformed rela-
tive abundance data before performing the community
network (Brisson et al., 2019). The significance of the
microbial community network was tested by comparing
its topological attributes with the averaged topological
attributes of 1000 random microbial co-occurrence
networks generated with Erdos–Renyi method from the
igraph v1.2.10 R package. Non-metric multidimensional
scaling (NMDS) was applied to both community and
environmental matrices, using Euclidean distances.
Non-parametric analysis of similarities (ANOSIM) was
performed to test whether the differences among sta-
tions, depths, beaches, and seasons were significant
for prokaryote community data. A modified version of
the Venn’s diagram was performed with UpSetR v1.4.0
package (Conway et al., 2017) for the most common
(mean relative read abundance in individual samples
higher than 0.1%) and uncommon orders (mean rela-
tive read abundance below 0.1%). The percentage
used to filter the common and rare orders was varied
and similar results were obtained (data not shown).
Only the intersections sharing at least 2 orders were
included in the plot (intersection size ≥2). Shapiro
Wilk’s test was applied to test whether prokaryotic
abundance and heterotrophic bacterial production
values followed a normal distribution. Then, the
Kruskall–Wallis and Wilcoxon tests were performed to
test for significant differences between months, sta-
tions, beaches, or depths. Spearman’s correlation was
also calculated between heterotrophic bacterial produc-
tion, prokaryotic abundance, and the environmental
variables.
RESULTS
Porewater biogeochemistry
The two studied STEs, Panx
on and Ladeira, are in
Baiona Bay, Ría de Vigo (NW Iberian Peninsula;
Figure 1A). Continental groundwater discharge is a sig-
nificant freshwater source to the Ría de Vigo (up to
23% of the freshwater discharged by rivers; Ib
anhez
et al., 2021), particularly at the inner part of Baiona bay,
where the STEs are located (Calvo-Martin et al., 2021;
Figure 1A). The interior of the Panx
on and Ladeira bea-
ches contain porewaters with
222
Rn activities that
largely surpassed those supported by sediment-
porewater
222
Rn equilibrium (3698 251 Bq m
3
in
Panx
on and 1610 329 Bq m
3
in Ladeira sediments),
thus providing evidence of the presence of continental
groundwater (Calvo-Martin et al., 2021).
Porewater samples were collected at three sam-
pling stations distributed through the permanently satu-
rated beach face during low tide (St1, St2 and St3;
Figure 1B) in February, May, July and October 2019
with piezometers screened in shallow (29 cm depth)
and deep sediments (116–178 cm depth). The three
sampling stations were selected to cover the three dis-
tinct porewater circulation zones typical of the beach
face of tidal STEs (Figure 1B; Calvo-Martin et al., 2021;
Robinson et al., 2006), which were identified in the
beach profile using salinity and Rn activities as tracers.
6CALVO-MARTIN ET AL.
In the shallow beach aquifer layers, salinity was gener-
ally higher than in the deep layers, and Rn activities
dropped below those supported by sediment-porewater
radon equilibrium, thus indicating recent seawater intru-
sion (Figure 1B). The tidal circulation cell or upper
saline plume (USP) is located at the upper limit of the
permanently saturated intertidal sediments of Panx
on
and Ladeira STEs (shallow depths of St3; Figure 1B).
Underneath the USP, a well-developed freshwater dis-
charge tube (FDT) is observed in both beach aquifers
at the deep layers, seeping from the beach face
between St2 and St1 and bound from beneath by a
saltwater wedge (Figure 1B). The presence of a gravel
layer at about 1 m depth in the Panx
on beach aquifer
further enhances porewater circulation. This feature
contributes to the large oxygenation of the Panx
on
beach aquifer by promoting the fast transfer of oxygen
to the beach interior. Good oxygenation is matched with
high (between 30 and 150 μM) nitrate levels linked to
the presence of continental groundwater. In contrast,
anoxic conditions prevail in Ladeira, and oxygen was
only detected in the USP (Figure 2and Table 1). As a
result, the chemical composition of the water within the
FDT at both beaches was very distinct (Figure 2and
Table 1; see the Supplementary material S1 for further
details on the measured environmental data).
Higher phosphate concentrations were also
observed in Ladeira compared to Panx
on beach
(p< 0.001, n=48, 1.5–59.5 μM in Ladeira and 1.3–
9.6 μM in Panx
on). Phosphate generally peaked at the
deeper layers of the beach aquifer (up to 59.5 μM). Sili-
cate also peaked at the deep layer, but no significant
differences in silicate content were observed between
beaches (p> 0.05, n=48). DIC and total alkalinity ran-
ged from 2702 59 to 5977 29 μM and from
2327 3 to 5346 0μM, respectively, and were com-
parable between beaches (Table 1). Significant differ-
ences were only observed in DIC between sampling
months (p< 0.001, n=48), although shallow layers
had generally higher DIC concentrations (Table 1).
Conversely, pH was significantly higher in Panx
on than
in Ladeira beach (p< 0.001, n=48; Table 1). In both
beaches, pH was higher in the deep layer (p< 0.01,
n=48; Table 1). DOC concentration was generally
higher in Ladeira compared to Panx
on beach, peaking
in the deep layer of St1 in Ladeira beach (Table 1;
Figure 2). Nevertheless, DOC was generally higher at
shallow than deeper depths in both beaches, probably
because of the presumably higher particulate organic
matter content of the surface sediments fed by seawa-
ter infiltration during high tide (Ib
anhez & Rocha, 2016).
Ladeira porewaters also had higher CDOM content
(a
CDOM
(254); p< 0.01; n=47; Ladeira: 10.42 12.71
and Panx
on: 5.22 5.15; Table 1), with higher aroma-
ticity (a
CDOM
(340); p< 0.01, n=47; Ladeira:
3.27 3.50 and Panx
on: 2.53 4.69; Table 1) but
unexpectedly, lower averaged molecular weight (a
(254/365) ratio; p< 0.05, n=47; Ladeira: 5.66 3.55
and Panx
on: 4.00 3.10; Table 1) compared to
Panx
on porewaters. The ratio between the spectral
slopes at 275–295 nm and at 350–400 nm (SR) was
between 0.23 and 3.38 in Ladeira and between 0.02
and 3.21 in Panx
on, indicating both terrestrial and
marine origin of CDOM. Differences in SR were only
significant among months (p< 0.05, n=46). Similarly,
FIGURE 2 Monthly averaged distribution of DOC, oxygen, nitrate
and ammonium in the seepage face of Ladeira and Panx
on STEs
represented over the monthly averaged beach profile
DIVERSITY OF STE MICROBIAL COMMUNITIES 7
both humic-like (represented by fluorescence of
Peak C, as the three humic-like FDOM peaks were
highly correlated; ρ=0.98–1, p< 0.001) and protein-
like (fluorescence of peak T) FDOM were significantly
higher in Ladeira than in Panx
on porewaters
(p< 0.001, n=48; Table 1).
TABLE 1 Environmental parameters averaged by beach and depth and its standard deviation
Ladeira deep Ladeira shallow Panxon deep Panxon shallow
Temperature (C) 16.95 1.64 17.15 2.24 16.32 1.92 16.43 2.39
Salinity 27.69 2.96 29.8 2.63 28.53 2.43 29.09 2.46
Oxygen (μM) 6.3 5.0 6.4 13.9 150.9 75.6 44.8 69.8
Rn-222 (Bq m
3
) 7132 3764 4236 2260 5923 1445 5420 1587
Ra-226 (Bq m
3
) 333 270 410 448 362 431 540 302
Total alkalinity (μM) 3387 789 3471 950 3199 338 3141 283
pH 7.48 0.11 7.28 0.09 7.61 0.11 7.55 0.07
DIC (μM) 3906 1015 4440 1495 3649 585 4268 1117
NO
3
(μM) 0.6 0.7 6.9 15.6 69.1 30.7 33.7 32.9
NO
2
(μM) 0.0 0.1 0.1 0.1 0.0 0.0 1.3 2.9
NH
4+
(μM) 19.6 29.2 35.9 41.9 0.7 0.9 5.6 10.9
PO
43
(μM) 14.1 14.6 14.6 15.1 2 0.4 3.3 2.1
SiO
2
(μM) 52.6 22.3 32.4 14.0 39.2 5.9 38.2 7.1
DOC (μM) 115.9 87.8 89.4 20.5 44.3 7.6 54.5 12.5
TDN (μM) 33.1 44.1 55.5 32.6 78.4 37.8 49.9 32.7
FDOM-C (r.u.) 0.391 0.456 0.137 0.053 0.037 0.017 0.049 0.031
FDOM-T (r.u.) 0.070 0.070 0.039 0.014 0.023 0.008 0.025 0.011
a
CDOM
(254) 13.91 16.7 6.62 4.27 2.96 1.61 5.59 7.00
a
CDOM
(340) 3.67 3.41 2.84 3.71 1.42 1.24 3.64 6.46
a(254/365) 5.97 3.49 5.73 3.66 2.95 0.96 4.96 4.04
SR 1.2 0.80 1.09 0.94 0.69 0.53 1.13 1.07
Note: Only the environmental parameters selected during VIF analysis were included.
Abbreviations: CDOM, coloured dissolved organic carbon; DOC, dissolved organic carbon; FDOM, fluorescent dissolved organic matter; TDN, total dissolved
nitrogen; VIF, variance inflation factor.
FIGURE 3 Non-metric multidimensional scaling (NMDS) ordination performed with (A) the environmental variables and (B) the microbial
community data from Panx
on and Ladeira beaches. The asterisk (*) marks the deeper porewater sample of St1 in October at Ladeira beach.
8CALVO-MARTIN ET AL.
The seasonal variability linked to aquifer recharge
and wave conditions affected the porewater circulation
patterns inside both STEs, particularly in Ladeira
beach. There, the FDT migrated upwards through the
beach profile during February and May, and thus,
fresh-groundwater was absent from St1 and detected
in the shallow layer of St2 (Figure 1B). The USP was
evident at St3 during February and May but nearly
absent during July and October (Figure 1B). Here, dis-
solved oxygen and nitrate were only detected at the
USP (shallow sample at St3; Figure 2). Coinciding with
the migration of the FDT during February and May,
ammonium accumulated in the porewater of the lower
end of Ladeira beach (St 1).
NMDS performed with environmental data
(Figure 3A) separated porewater samples from Panx
on
and Ladeira along the X axis. Differences were only
observed between depths at Panx
on beach (ANOSIM,
p< 0.05). The deeper porewater sample of St1 at
Ladeira beach in October appeared particularly distant
from the rest of the samples in the environmental ordi-
nation (Figure 3A), mainly because of the high DOC
values observed there (378 μM).
Diversity and composition of the porewater
microbial community
The microbial communities in the porewaters of Panx
on
and Ladeira were very diverse (Shannon index), rich,
and fairly even (Pielou’s index; Figure 4). The most
diverse sample was found in Panx
on even if median
values of the Shannon index were higher in Ladeira.
Richness, Pielou’s evenness and especially the Shan-
non diversity index were significantly higher in the dee-
per beach layers (p< 0.05; Figure 4).
Porewater samples from Panx
on and Ladeira were
clearly separated into four groups by beach and sam-
pled sediment layer along both axes of the NMDS per-
formed on the microbial community data (Figure 3B;
ANOSIM p< 0.001). This implies that the microbial
community in Panx
on and Ladeira STEs was stable
throughout the year, and distance from the shoreline
did not explain differences observed in the microbial
community (ANOSIM test p> 0.05). The microbial com-
munity of both STEs showed higher similarity when
comparing the same depth (shallow or deep) from dif-
ferent beaches than within the same beach
(Figure 3B). Moreover, the shallow samples of Ladeira
STE appeared more dispersed than those from Panx
on
and the deep samples, indicating higher differences
among months and stations than in Panx
on beach
(Figure 3B).
Fifty-nine phyla composed of 183 classes and
383 orders were identified: 47 in Panx
on and 56 in
Ladeira. In Panx
on, the most abundant phylum was
Thaumarchaeota, followed by Proteobacteria,
Nanoarchaeaeota and Chloroflexi (27.3%, 24.1%,
14.1% and 7.3% of the total relative abundance,
respectively). In Ladeira, the dominant phyla were
Chloroflexi, Proteobacteria, Nanoarchaeaeota and
Omnitrophicaeota (21.1%, 15.5%, 14.4% and 8.88% of
FIGURE 4 Richness, Shannon index and Pielou’s evenness from Panx
on and Ladeira beaches grouped by beach and depth. Thick lines
inside each box represent the median value.
DIVERSITY OF STE MICROBIAL COMMUNITIES 9
the total relative abundance, respectively; Figure 5).
Among the most common orders (mean relative read
abundance in the individual samples >0.1%, 119 orders;
Figure 6A), 12 orders belonging to Proteobacteria,
Nanoarchaeaeota, Euryarchaeota, Lentisphaerae,
Omnitrophicaeota and Gemmatimonadetes were pre-
sent in all the sampled times, depths and beaches. The
Proteobacteria order Betaproteobacteriales was ubiqui-
tously present and increased its abundance with depth,
similarly to the widely distributed Proteobacteria Altero-
monodales (9.2% and 9.1% of the total relative read
abundance of Proteobacteria, respectively; the relative
abundances of the orders and classes of Thaumarch-
aeota, Proteobacteria, Nanoarchaeaeota, Chloroflexi
and Euryarchaeota are presented in Supplementary
Materials S1). Within Nanoarchaeaeota, an uncultured
archaeon from the Woesearchaeia class was highly
abundant and widely present (32.3% of the total relative
read abundance).
Five of the observed 119 most common orders were
exclusive to Ladeira and only 1 to Panx
on (Figure 6A).
These five common orders exclusive to Ladeira are
vadinBA26 and t0.6.f from Chloroflexi, the order Marine
Benthic Group D from Euryarchaeota, and two orders
belonging to Altiarchaeota and Diapherotrites. Elusimi-
crobiales was the only identified most common order
exclusive to Panx
on.
Spatially, 12 of the most common identified orders
were exclusive to the deeper porewaters while 6 were
exclusive to the shallow samples (Figure 6A). The Delta-
proteobacteria Desulfobacterales, Oligoflexales and
Bdellovibrionales prevailed in shallow samples (13.7%,
12.7% and 9.5% of the total relative read abundance of
Proteobacteria, respectively). Cyanobacteria appeared
sporadically in important numbers in the shallow samples
of Panx
on (up to 21.3% of the relative read abundance
at the shallow depth of St2 in October; Figure 5). Con-
versely, Lentisphaerae and Euryarchaeota prevailed at
shallow depths in St1 at Ladeira (Figure 5), coinciding
with the anoxic conditions found at the salt-wedge during
this sampling period. Thaumarchaeota were ubiquitous
and relatively abundant in the USP of both beaches, with
Nitrosopumilales being the most representative order
(97.8% of the total relative read abundance of Thau-
marchaeota). Probably because of the high oxygenation
of the shallow samples taken outside of the USP of
FIGURE 5 Relative abundance (in %) of reads assigned to each phylum organized by sampling site, month and depth
10 CALVO-MARTIN ET AL.
FIGURE 6 Venn’s diagram grouped by beaches and depths and UpsetR modified Venn’s diagram (Conway et al., 2017) grouped by beach,
survey and depth performed at the order level with (A) relative read abundances higher than 0.1% (i.e. abundant order) and (B) relative read
abundances lower than 0.1% (i.e. rare orders). Numbers inside ellipsis at the Venn’s diagram indicate the number of orders shared by each set.
Set sizes in the UpsetR modified Venn’s diagram (horizontal bars) indicate the total number of orders used for the diagram at each group.
Intersection sizes (vertical bars) indicate the total number of orders that are shared by the groups marked in the matrix below. Only sets with an
intersection size higher than 2 were plotted in the UpsetR modified Venn’s diagram. Groups were defined following the results of the ANOSIM
test performed with community data (p< 0.05 for beaches and depths and p=0.051 for survey).
DIVERSITY OF STE MICROBIAL COMMUNITIES 11
Panx
on, the microbial community there was similar to
that found in the USP of both beaches (St3; Figure 5).
The ammonium oxidizing bacteria (AOB) were also pre-
sent in Panx
on and Ladeira STEs (0.24% and 1.30% of
the total relative read abundance, respectively; see Sup-
plementary Materials S1), represented by the phylum
Nitrospirae and the Gammaproteobacteria Nitrosococca-
ceae and Nitrosomonadaceae.
In depth, Chloroflexi was the dominant clade in
Ladeira and the fourth most abundant in Panx
on
(Figure 5). Dehalococcoidia was the most abundant
class of Chloroflexi, with the ubiquitously present
SAR202 and Sh765B-AG-111 clades being the most
abundant (29.5% and 12.5% of the total relative read
abundance, respectively). Thaumarchaeota also pre-
vailed within the oxygenated, deeper samples taken at
Panx
on (Figure 5), but the deep Thaumarchaeota com-
munity (mainly Nitrosopumilales) was characterized by
different OTU assemblages in comparison to the shal-
low Thaumarchaeota community (see Supplementary
Materials S1 for a list of the top 75 OTUs of both STEs).
High abundances of Nitrosopumilales were also found
in the deep sample of St1 in Ladeira despite the anoxic
conditions (Figure 5). Group1.1c and Marine Benthic
Group A were important only in the deeper porewater
samples of Ladeira, where Thaumarchaeota were
poorly represented. The deep AOB community reached
up to 3% of the total relative abundance in Panx
on and
0.27% in Ladeira. Taxa associated with anoxic nitrogen
removal such as Planctomycetes were detected in both
shallow and deep samples taken from both beaches,
but in low abundances (<5%).
Conversely, most rare orders (mean relative read
abundance <0.1% abundance in the individual sam-
ples, 264 orders; Figure 6B) were detected only during
specific months, at different depths in either beach, with
only 16 orders present at both beaches. The largest
group of exclusive rare orders was found in the deep
samples of Panx
on during February (n=14,
Figure 6B). The detection of rare orders was limited to
smaller areas or specific timeframes by comparison to
the common orders, which were more ubiquitously
distributed.
Prokaryotic abundance and production
Prokaryotic abundance was significantly higher at
Ladeira than Panx
on (p< 0.01; 5.55 10
3
to
9.81 10
6
cell ml
1
and 6.96 10
3
to 1.02 10
6
cell
ml
1
, respectively; Figure 7). Prokaryotic abundance
decreased with depth, except at St3 at Panx
on in
February and St1 at Ladeira in July. Prokaryotic cells
were more abundant in October than February, but the
difference was not significant (p> 0.05).
Heterotrophic prokaryotic production (HPP;
Figure 7) ranged from 0.05 to 2.97 μgC L
1
d
1
in
Panx
on and from 0.27 to 3.85 μgC L
1
d
1
in Ladeira.
No significant differences with season or location were
observed (p> 0.05). Nevertheless, HPP decreased
with depth in most cases (17 of 24 stations: Figure 7).
HPP was higher in the deep layer at both beaches
essentially in October, when also the highest HPP
value was recorded at Ladeira (3.85 μgC L
1
d
1
).
Prokaryotic abundance was more tightly correlated
with FDOM peaks (Spearman’sr0.4–0.6; p< 0.01;
n=48), dissolved oxygen (ρ=0.51, p< 0.001), alka-
linity (ρ=0.53, p< 0.001), pH (ρ=0.60, p< 0.001)
and temperature (ρ=0.71, p< 0.001) and loosely cor-
related with
226
Ra (ρ=0.30, p< 0.05), nitrite (ρ=0.34,
p< 0.05), DOC (ρ=0.36, p< 0.01), a
CDOM
(254)
(ρ=0.37, p< 0.05), DIC (ρ=0.46, p< 0.05), phos-
phate (ρ=0.47, p< 0.001), nitrate (ρ=0.47,
p< 0.001). HPP was significantly correlated only with
temperature (ρ=0.32, p< 0.05). No relationship was
observed between prokaryotic abundance and HPP.
Prokaryote co-occurrence network
Co-occurrence analysis showed a highly connected
microbial network, with 75 nodes (Figure 8; see Supple-
mentary Materials S1 for taxonomic details of the
75 OTUs selected for the network) and 678 significant
edges, a clustering coefficient (i.e. probability that two
randomly selected neighbours of a node are neigh-
bours with each other) of 0.649, an average length path
(i.e. the average shortest path between two nodes) of
2.058 and an average degree (i.e. number of connec-
tions between each node and others) of 18.08. This
microbial co-occurrence network was compared with
1000 other randomly generated networks to test
whether the observed relationships among OTUs were
significant. The randomly generated networks had a
mean clustering coefficient of 0.243 0.006 and a
mean averaged path length of 1.753 0.002, both
lower than those observed in the prokaryote co-
occurrence network of the Panx
on and Ladeira STEs.
OTUs from the autotrophic nitrifying Nitrosopumi-
laceae family, dominant among the top 75 OTUs
(36/75 OTUs; Supplementary Materials S1), were
grouped into two distinct associations (Figure 8). The
first included Nitrosopumilaceae OTUs predominantly
found in shallow samples that were related to Oligo-
flexaceae (Deltaproteobacteria) and Woesearchaeia
(Nanoarchaeaeota). The second included OTUs
found mainly in deep samples that were more con-
nected to other taxa, such as Subgroup 6 (Acidobac-
teria), Nitrospira, Woesearchaeia and bacteria p25
(Myxococcales from Deltaproteobacteria). Most of the
remaining OTUs were grouped into a third cluster,
dominated by Chloroflexi and CK-2C2-2 members.
Pseudoalteromonas OTUs were distanced from the
clusters and were associated mainly with each other.
12 CALVO-MARTIN ET AL.
Relationships between microbial
community at phyla level and
environmental variables
The correlation clustering of phyla defined two groups,
one including from Marinimicrobia (SAR406 clade) to
Fibrobacteres and the other from Actinobacteria to
FCPU426 (represented in the X-axis, Figure 9). The first
grouping was negatively correlated with nitrate and oxy-
gen, and positively with FDOM peaks, DOC, a
CDOM
(340),
a
CDOM
(254) and ammonium, suggesting heterotrophs
prevailed within this association of taxa. Interestingly, the
abundant Chloroflexi phyla only showed weak positive
correlations with
222
Rn, and negative with nitrite. The
second group of phyla followed the exact opposite
behaviour (Figure 9), suggesting autotrophs prevailed
there. Because of their high correlations and abundance
(jρj> 0.5; Figure 5), Thaumarchaeota were the most rep-
resentative taxon of this group.
Besides Chloroflexi and
222
Rn, few phyla were corre-
lated with water circulation tracers (
222
Rn,
226
Ra and
salinity). Cyanobacteria was positively correlated with
226
Ra, and salinity was only positively correlated with
Dependentiae (Figure 9). Stepwise DistLM-RDA showed
that dissolved oxygen, FDOM peak C, pH,
222
Rn, DIC,
DOC, a
CDOM
(340), a
CDOM
(254) and total alkalinity were
the main drivers of the microbial community composition
(Figure 10) and explained 29% of the total variation of
the microbial community (R
2
: 0.29, Adj R
2
: 0.15;
Figure 10). The first axis (dbRDA1; Figure 10) explained
15.65% of the variation of the fitted model (8.04% of the
total variation), whereas the second axis (dbRDA2)
explained 13.75% (7.06% of the total variation). Beaches
and depths appeared well differentiated, particularly the
deeper samples from both beaches. Exceptions
appeared in the deep layer of St1 in Ladeira during May,
close to the deep layer of Panx
on (Figure 10). Deep
samples from Panx
on were closely related with oxygen,
a
CDOM
(254) and pH, and negatively related with
a
CDOM
(340) and DOC. Radon, alkalinity, FDOM peak C,
a
CDOM
(254), a
CDOM
(340) and pH were closely related to
the shallow samples, particularly to those from Ladeira.
Shallow samples appeared very close to DIC.
DISCUSSION
Representation of the microbial
community
Current primer-based sequencing approaches are
biased towards publicly available collections while the
FIGURE 7 Prokaryotic abundance (PA; grey bars) and heterotrophic production (HPP; black dots) at each beach, depth, sampling station
and season. Horizontal error bars are shown for both HPP and PA. Prokaryotic abundance is represented in logarithmic scale.
DIVERSITY OF STE MICROBIAL COMMUNITIES 13
use of 0.2-μm-pore-size filters may limit the representa-
tiveness of the STE microbial community data, espe-
cially because of the possible underestimation of ultra-
small and novel prokaryote lineages (Ruiz-Gonz
alez
et al., 2021). Thus, the superphylum
Ca. Patescibacteria and the ultra-small archaea
(i.e. the superphylum composed by Diapherotrites, Par-
varchaeota, Aenigmarchaeota, Nanoarchaeaeota and
Nanohaloarchaeota or DPANN), as well as other filter-
able microorganisms (Nakai, 2020), are probably
underrepresented in our porewater samples. Despite
these possible artefacts, Nanoarchaeaeota contributed,
on average, 14% to the total prokaryote reads in the
porewater samples taken in our study, which agrees
with the relatively good coverage of this archaeal group
reported by Ruiz-Gonz
alez et al. (2021) for the selected
primer set. On the other hand, Diapherotrites were rela-
tively well represented in the shallow samples taken in
July and October at Ladeira (1%–3%). The superphy-
lum Ca. Patescibacteria, which is expected to be less
well covered by our primer set, was mostly detected at
Ladeira beach in October, where it contributed 3%–
4.4% to the total prokaryote reads in St3 (Figure 5).
Since DNA-based techniques include both active and
inactive taxa, the use of DNA-based, rather than RNA-
based taxa identification, restricts characterization of
STE functionality using microbial community composi-
tion beyond the rarer groups (Ruiz-Gonz
alez
et al., 2021).
The sampling strategy highlights another challenge
that groundwater microbiology studies face to appropri-
ately represent microbial community structure in situ.
The heterogeneity of the sediment and the large, oscil-
lating biogeochemical gradients limit an accurate char-
acterization of the spatiotemporal variability of the
microbial community structure of STEs. Despite the
intense interaction between porewater and sediments
in STEs, much of the microbial community lives
attached to the solid matrix, forming micro-colonies and
biofilms (Griebler & Lueders, 2009; Ruiz-Gonz
alez
et al., 2021). Although the ratio of attached versus free-
living microbes has not yet been formally studied in
STEs (Archana et al., 2021; Ruiz-Gonz
alez
et al., 2021), sediment-attached microbes seem to be
more abundant (10
9
cells per gram of sediment
vs. 10
5
–10
7
cells ml
1
in porewater samples; Ruiz-
Gonz
alez et al., 2021; Santoro et al., 2008; Velasco
Ayuso, Acebes, et al., 2009; Velasco Ayuso, Guerrero,
et al., 2009) and more active than free-living porewater
microbes (one to two orders of magnitude higher het-
erotrophic production in sediment-attached microbes;
Jiang et al., 2020; Ruiz-Gonz
alez et al., 2021; Velasco
FIGURE 8 Microbial correlation network of the 75 top most abundant OTUs present at least in 20% of the samples from Panx
on and
Ladeira STEs. Each circle represents an OTU. Colours indicate the phylum to which the OTU belongs. Labels inside the circles indicate the
lowest taxa rank identified for each OTU. Red lines indicate negative correlations among OTUs and blue lines positive correlations. OTUs were
grouped in the network according to their relationships. The microbial correlation network was performed with the Spearman’s correlation (ρ)
value between the relative abundances of the OTUs after applying a habitat filtering.
14 CALVO-MARTIN ET AL.
Ayuso et al., 2010). Nevertheless, at least at the phyla
level, the dominant clades are shared by both the
sandy matrix and the surrounding porewater (Gobet
et al., 2012), reducing the potential limitations arising
from the choice of porewater samples over sediment.
Still, the body of work focusing on porewater and
sediment-attached microbial communities is minimal.
Future work might aim to quantitatively assess the rep-
resentativeness of sampling porewater over sediment
in microbial studies.
Prokaryotic abundance and heterotrophic
production in Panx
on and Ladeira STEs
The prokaryotic abundance in the Panx
on and Ladeira
STEs was in line with observations reported by previ-
ous studies on sandy coastal aquifers (10
5
–10
7
cells
ml
1
; Santoro et al., 2008; Velasco Ayuso et al., 2010),
but their heterotrophic prokaryotic production (HPP)
was lower than in other groundwater systems
(4.32 17.28 μgC L
1
d
1
, Velasco Ayuso et al., 2010;
0.02–21.78 μgC L
1
d
1
, Wilhartitz et al., 2009). Het-
erotrophic prokaryotic production (HPP) provides an
estimate of the active utilization of organic carbon by
the heterotrophic prokaryotic community through the
incorporation of leucine. In order to compare both bea-
ches, the time the microbial community needs to dupli-
cate biomass (i.e. turnover times) were calculated by
transforming prokaryotic abundance into biomass,
assuming a constant cell C content of 20 fg C cell
1
,
then dividing biomass by heterotrophic production
(Lee & Fuhrman, 1987; see Supplementary
Materials S1 for the results obtained for turnover times
obtained this way). It is important to note that these
turnover times consider only biomass production
through heterotrophic processes, while including total
prokaryote abundance. Still, most of the calculated
turnover times (0.2–440.4 days for Panx
on, 0.2–
392.6 days for Ladeira) were within the range previ-
ously observed in tidal sands (2–18 days; Böer
et al., 2009) and coastal aquifers (0.03–87.26 days;
Velasco Ayuso et al., 2010) and suggested that the
Panx
on microbial community (median: 4.1 days) was
generally more active than that of Ladeira (median:
21.1 days).
Microbial abundances and activities in groundwater
systems are essentially regulated by temperature,
FIGURE 9 Correlation matrix between phylum relative abundances and environmental variables. The correlation matrix was performed with
Spearman’s correlation (p< 0.05) between environmental variables (including prokaryotic abundance and HPP) and phylum CLR-transformed
abundances. Red colour indicates negative correlations and blue, positive correlations. Clustering at X-axis and Y-axis indicate the relationships
among phylum CLR-abundances (X-axis, top) and among environmental values (Y-axis, left side). Clustering was performed with Spearman’s
correlation (p< 0.05) and using 1-ρas distance. Positively related variables are thus the closest and negatively related variables are the furthest.
DIVERSITY OF STE MICROBIAL COMMUNITIES 15
porewater velocity, supply of organic matter and nutri-
ents, and mineralogy (Jiang et al., 2020; Mauck &
Roberts, 2007; Velasco Ayuso, Acebes, et al., 2009;
Velasco Ayuso, Guerrero, et al., 2009; Velasco Ayuso
et al., 2010; Wilhartitz et al., 2009). In our study, pro-
karyotic abundance correlated with temperature, pH,
phosphate and organic matter content and quality, thus
suggesting that the microbial community might be lim-
ited by phosphate and organic matter (Table S1). In
contrast, HPP was only significantly linked to tempera-
ture (p< 0.05). The lack of correlation between pro-
karyotic abundance and HPP suggests that regulation
of reaction rates is physical rather than biological. Pore-
water advection has been related to chemical reactivity
(Ib
anhez & Rocha, 2017), active microbial biomass
(Velasco Ayuso et al., 2010) and HPP (Jiang
et al., 2020). Thus, the lower turnover times found in
Panx
on STE might be linked to higher porewater veloc-
ities promoted by the higher permeability of its gravel
layer (Calvo-Martin et al., 2021), which may stimulate
HPP. Nevertheless, the retention at shallow depths of
particulate organic matter supplied by seawater infiltra-
tion during high tide (Ib
anhez & Rocha, 2016) could
explain the generally higher HPP and prokaryotic abun-
dance of the shallow samples compared to the deep
ones at both beaches (Figure 7). The scarce particulate
organic matter supply converts the DOC in the main
organic matter substrate at the deep layers (Ib
anhez &
Rocha, 2016), where DOC quality appeared to contrib-
ute significantly to explain the differences observed in
depth among months, stations and beaches. Thus,
although no significant differences were observed
among the sampling months in HPP, the seasonal
oscillations of temperature, porewater velocities and
organic matter supply seem to influence HPP. Our find-
ings highlight the importance of physical environmental
factors to the activity of the heterotrophic microbial
community.
The microbial community of STEs:
Cosmopolitan abundant phyla and locally
restricted rare taxa
The Panx
on and Ladeira STEs host very rich, diverse,
and even microbial communities. The three diversity
indexes fall in the upper range of the diversity index
values previously observed in STEs (Adyasari
et al., 2020; Hong et al., 2019; Ye et al., 2016). More-
over, the median values of both diversity (5.5) and equi-
tability (0.9) were higher than those observed in the
nearby coastal waters (Shannon index: 4.8, Pielou’s
index: 0.8; Gutiérrez-Barral et al., 2021). The microbial
community of the Panx
on and Ladeira STEs clustered
into four significantly distinct communities, well sepa-
rated by beach and depth (Figure 3B). Conversely,
most abundant phyla (>5% of the relative read abun-
dance) were present at both STEs and depths
(Figure 6A). The cosmopolitan Proteobacteria, Thau-
marchaeota, Nanoarchaeaeota and Chloroflexi (Boehm
et al., 2014), together with the ubiquitous but less abun-
dant Omnitrophicaeota, Lentisphaerae, Euryarchaeota,
Elusimicrobia and Gemmatimonadetes (Figure 5),
formed the shared core community at both beaches.
Tidal STEs are exposed to oscillating hydrodynamic
forces (Robinson et al., 2018), which drive strong
changes in biogeochemical gradients within beach
aquifers at short timescales. Despite such stimulus,
these four communities remain largely stable through-
out the year. The distance from the shoreline also did
not result in significant changes to the community struc-
ture, thus confirming the resilience of STE microbial
communities (Degenhardt et al., 2020). Despite the lim-
ited temporal coverage during our surveys, the selected
sampling times included enough contrasting environ-
mental conditions to support the hypothesis of a resil-
ient core microbial community existing within STEs.
Shallow communities at both beaches had a higher
degree of similarity between them than deeper commu-
nities (Figure 10). This was probably due to similar
adaptations to organic matter, oxygen, and nutrient
supply by tidal and wave pumping and to the input of
microorganisms from the coastal endmember, which is
similar in both STEs due to the proximity of both bea-
ches. The microbial communities living deeper within
the beach aquifer and affected by terrestrial groundwa-
ter were also more diverse, as previously observed in
other STEs (Degenhardt et al., 2020; Lee et al., 2017).
FIGURE 10 Redundancy analysis from Distance-based Linear
Modelling (DistLM-RDA) performed with microbial community and
environmental data from the shallow (triangles) and deep (circles)
samples of Panx
on (black) and Ladeira (grey) STEs. Red arrows and
labels indicate the environmental variables that better explain the
microbial community data variance. Length of vectors indicates the
strength of the correlation, and the circle indicates a correlation of
1. The asterisk (*) marks the deep sample from station 1 in May from
Ladeira beach.
16 CALVO-MARTIN ET AL.
Contrasting with the core ubiquitous community,
rare taxa appeared more localized at Panx
on and
Ladeira STEs (Figure 6B). Biogeochemical processes
in groundwater and porewater are essentially con-
ducted by taxa that perform single steps in sequential
redox reactions, rather than by microorganisms that
can complete a whole redox sequence (Anantharaman
et al., 2016). Rare species fulfil an important role since
they are usually highly specialized (Jousset
et al., 2017) and constitute a microbial seed-bank that
can grow under specific environmental conditions
(Lennon & Jones, 2011). The high proportion of diverse
and rare microorganisms found at Panx
on and Ladeira
show the potential capability of STEs to adapt to the
changing conditions, but also reflect the possible role of
STEs as a reservoir of microorganisms for the nearby
aquifer and coastal waters when their environmental
conditions are altered. For example, the total relative
read abundance of Campylobacter
(Epsilonbacteraeota) in Panx
on and Ladeira STEs was
below 0.1% (Figure 5), but under organic matter and
sulfate rich, reduced conditions this taxon can prevail in
STEs, as documented in a tropical karst STE in the
Yucatan Peninsula (Huang et al., 2021). Rare taxa are
known to be as sensitive to environmental changes as
abundant taxa (Gobet et al., 2012; Yamamoto
et al., 2019). In the case of Panx
on and Ladeira STEs,
the very specific location of the rare taxa at particular
times, stations and depths, suggest that they can be
even more sensitive than the core community to subtle
spatial and temporal environmental gradients derived
from seasonal changes (Figure 6A,B).
Functionality and environmental drivers of
the microbial community of STEs
STEs regulate groundwater-borne nitrogen loads to the
coast (Calvo-Martin et al., 2021; Couturier et al., 2017;
Ib
anhez et al., 2013; Kroeger & Charette, 2008; Rocha
et al., 2009). If oxygen is available, production of nitrate
occurs coupled to organic matter consumption in STEs
(Ib
anhez et al., 2013; Rocha et al., 2009). Thus, the
large contribution of autotrophic nitrifiers to the overall
microbial community composition of STEs is not sur-
prising, especially when porewater oxygenation leads
to nitrate accumulation (Rogers & Casciotti, 2010;
Santoro et al., 2008). The heterotrophic microbial com-
munity present in the USP of Ladeira and Panx
on was
dominated by Deltaproteobacteria and by the probably
symbiotic or parasitic nanoarchaea Woesearchaeia
(Nanoarchaeaeota; Castelle et al., 2015; Liu
et al., 2021). The latter has been detected in other
STEs (Adyasari et al., 2020; Baricz et al., 2021; Liu
et al., 2021). Interestingly, some representatives of
these taxa appeared strongly associated in the micro-
bial correlation network with many OTUs belonging to
the autotrophic ammonia oxidizing archaea (AOA;
mostly Nitrosopumilales within the Thaumarchaeota
phylum) and a representative from the Nitrospira
genus. Although Nitrospira can perform complete nitrifi-
cation (Daims et al., 2015), the higher affinity of AOA
for ammonium (Martens-Habbena et al., 2009) and the
observed link between AOA and Nitrospira might indi-
cate that the latter were preferentially acting as nitrite
oxidizing bacteria (NOB).
The increased porosity of the gravel layer within the
Panx
on STE likely enhances the transfer of oxygen into
the beach interior, promoting the dominance of AOA
and thus the production of nitrate (Calvo-Martin
et al., 2021). Like Rogers and Casciotti (2010), we
observed that the deep and shallow AOA communities
were genetically distinct. The nitrifier community found
deeper in Panx
on beach was likely driven by both
anaerobic heterotrophs, such as Woesearcheia or Myx-
ococcales, and aerobic heterotrophs, such as Acido-
bacteria, commonly found in estuarine benthic
sediments (Wei et al., 2022) and STEs (Degenhardt
et al., 2021; Hong et al., 2019; Jiang et al., 2020). More-
over, the deeper AOA community established stronger
associations with Nitrospirae than the shallow AOA
community. This might indicate that complete nitrifica-
tion by coupling between AOA and NOB was the pref-
erential nitrogen transformation pathway deeper into
Panx
on beach.
Denitrifying taxa associated with tidal sands, such
as some belonging to Flavobacteriales from Bacteroi-
detes or Alteromonodales from Gammaproteobacteria
(Jiang et al., 2021; Jones et al., 2008; Marchant
et al., 2017; Mills et al., 2008; Wu et al., 2021), and
Anammox taxa, mostly related to Planctomycetes
(Santoro, 2010; Wu et al., 2021), were also observed
irrespective of oxygen availability, together with the
heterotroph-nitrifier association previously discussed.
The strong variable biogeochemical gradients in STEs
and the small-scale heterogeneity of permeable sedi-
ments stimulate the development of micro-niches with
contrasting oxygen conditions, enabling the co-
occurrence of both oxic inorganic nitrogen production
and anoxic nitrogen removal (Decleyre et al., 2015;
Ib
anhez & Rocha, 2016,2017; Marchant et al., 2017;
Rao et al., 2008). The followed sampling strategy fol-
lowed limits the identification of small-scale heteroge-
neity in Panx
on and Ladeira STEs. Future studies
aiming at disentangling small-scale heterogeneity in
STEs would permit evaluation of their importance in the
overall microbial community composition and biogeo-
chemical functioning of STEs. Denitrifiers, mostly from
Bacteroidetes, were generally less abundant in the
deeper than in the shallower sediments. This may be
related to the limited organic matter supply to deeper
beach sediments, by comparison to shallower layers
which receive organic matter from tidal and wave
pumping (Huettel et al., 2014;Ib
anhez & Rocha, 2016);
DIVERSITY OF STE MICROBIAL COMMUNITIES 17
and the higher oxygen concentrations present in depth
at Panx
on STE (Supplementary Materials S1 and
Calvo-Martin et al., 2021), which can inhibit denitrifica-
tion. Thus, the contrasting microbial composition of the
Panx
on and Ladeira STEs, likely derived from the dif-
ferent degree of oxygenation, determined the opposing
role of these STEs in processing groundwater-borne
nitrogen, with Panx
on acting mainly as a net source of
DIN and Ladeira as a net sink of DIN (Calvo-Martin
et al., 2021).
In the anoxic areas outside the USP of Ladeira
beach, AOA and aerobic heterotrophs were outnum-
bered by anaerobic heterotrophs (e.g. Lentisphaerae,
Omnitrophicaeota, Euryarchaeota) and sulfate
reducers (e.g. members from Deltaproteobacteria). The
relative high dynamism of the bacterial community at
this location could result from the eventual bloom of
opportunistic bacteria responding quickly to subtle
changes in oxygen and DOM quantity and quality. Like-
wise, Degenhardt et al. (2020) reported that the accu-
mulation of organic matter and the anoxic conditions at
the salt-wedge occasionally promoted blooms of oppor-
tunistic anaerobes inside the sediment. The presence
of Euryarchaeota, mostly represented by groups asso-
ciated with anaerobic protein degradation (e.g. Marine
Benthic Group D; Lloyd et al., 2013) and methanogen-
esis (e.g. Methanomicrobia and Methanofastidiosales;
Nobu et al., 2016; Thauer et al., 2008) in the Ladeira
STE suggest that the last steps of anaerobic carbon
mineralization occur in this beach (Liu et al., 2021). Fur-
thermore, the presence of the methanotrophic Eur-
yarchaeota (e.g. ANaerobic MEthanotrophic archaea,
ANME; Lloyd et al., 2011) could indicate that production
and oxidation of methane co-occur in Ladeira.
In the poorly oxygenated deeper areas of Ladeira
beach, the decomposition of organic C was likely pro-
moted by the microbial association formed by Desulfati-
glans (Deltaproteobacteria), Chloroflexi (mostly
Dehalococcoidia) and CK-2C2-2. Marine Desulfatiglans
have been recently shown to encode different path-
ways for the degradation of aromatic compounds, orga-
nosulfonates, and organohalides, rather than being
sulfate-reducing microbes (Jochum et al., 2018). Deha-
lococcoidia are widely distributed in anoxic marine and
freshwater sediments (Wasmund et al., 2014; Yang
et al., 2020). A recent study based on genome recon-
struction of marine subseafloor Chloroflexi unveiled the
capability to degrade complex carbohydrates as well as
other detrital compounds coupled with the ability to
reduce CO
2
(Fincker et al., 2020). More recently, Beg-
matov et al. (2021) found that most Chloroflexi lineages
in deep sediments in the Barents Sea were anaerobic
heterotrophs capable of the fermentation of carbohy-
drates, fatty acids, and proteins. In our STEs, Chloro-
flexi was positively related to radon, which might
indicate a relationship with the terrestrial, groundwater
endmember. Interestingly, Dehalococcoidia seems to
be more prevalent in Ladeira compared to Panx
on
beach. Oxygen-deficient conditions and the presence
of aromatic CDOM of low-molecular weight (possibly
attributed to fulvic acids; Hayase & Tsubota, 1985; Del
Vecchio & Blough, 2004) in Ladeira might have
favoured Dehalococcoidia growth. The functional role
of members of the CK-2C2-2 phylum remains enig-
matic, but the strong association with Chloroflexi and
the strong positive correlation with DOM-related param-
eters suggest their involvement in the anaerobic degra-
dation of organic matter.
Overall, environmental predictors explained about
one third of the variance observed in STE microbial
community structure. Nevertheless, some key environ-
mental variables that were not measured, such as S
compounds, could partially explain the remaining vari-
ance. For instance, the Panx
on and Ladeira STEs har-
bour a high proportion of Desulfobacterales,
highlighting the importance of sulfur cycling within the
beaches. The advection of microbes from both the con-
tinental and seawater endmembers may also affect the
composition of the microbial community in both STEs.
For instance, the occasional presence of Cyanobac-
teria in the shallow layers of Panx
on might be linked to
tidal and wave pumping (Adyasari et al., 2019,2020;
Boehm et al., 2014). Transport processes could also
explain the presence of Nitrosopumilales in the deep
layer of the anoxic salt-wedge (St1) during May in
Ladeira. The Proteobacteria classes Rhodobacterales,
SAR11 clade, Vibrionales and Oceanospiralles, and
the Euryarchaeota class Thermoplasmata could have
been also transported by coastal seawater infiltration
as they have been also observed in the surface waters
of the Ría de Vigo (Gutiérrez-Barral et al., 2021). The
Chloroflexi SAR202 clade has been observed in marine
waters (Mehrshad et al., 2017). Although it has not
been observed in the Ría de Vigo yet, its presence in
the deep porewater samples could be seeded by the
seawater endmember. Lastly, stochastic processes
and microbial interrelations are also crucial for microbial
community assembly and might explain part of the
observed variance (Fillinger et al., 2019,2021).
CONCLUSIONS
We found that the microbial communities of two STEs
with contrasting redox conditions are very diverse, even
and rich. Shallow porewaters hosted higher prokaryotic
abundance and heterotrophic prokaryotic production,
but deeper layers accommodated a more diverse com-
munity. The microbial community of STEs comprises
both resilient, abundant cosmopolitans, and rare,
locally restricted taxa, which constitute an important
seed bank in the variable environmental conditions typi-
cal of STEs. The microbial community structure is
remarkably stable throughout seasons and along the
18 CALVO-MARTIN ET AL.
beach profile, in contrast with the strong geochemical
variability, suggesting a large functional microbial diver-
sity providing high resilience to these understudied eco-
systems. Differences in microbial composition between
beaches and depths could be explained by persistent
differences in organic matter content and oxygenation.
The microbial community structure in oxygenated pore-
waters of the Panx
on STE revealed strong associations
between heterotrophs and autotrophic nitrifiers, overall
archaea, and indicated a community focused on
organic matter mineralization and nitrogen oxidation,
although anoxic micro-niches might enable other nitro-
gen transformation pathways. In the anoxic zones of
the Ladeira STE, the microbial community structure
highlighted the important role STEs play in the anaer-
obic carbon cycle. Production and oxidation of meth-
ane may be co-occurring in the Ladeira STE, and
taxa related to the degradation of complex and aro-
matic organic compounds were found in the deep
samples. Although the extensive geochemical char-
acterization of the STEs at Panx
on and Ladeira pro-
vided invaluable information on the drivers of
microbial community composition, a large part of the
observed compositional variability remains unex-
plained. We suggest that taxa transported by ground-
water advection from both the coast and aquifer
endmembers might contribute to explain this variabil-
ity. This study thus reveals the large variety of bio-
geochemical processes that may occur in STEs,
driven by their diverse and specialized microbial com-
munity, and highlights the potentially high biogeo-
chemical reactivity hidden within these environments.
ACKNOWLEDGEMENTS
The authors wish to thank Vanesa Vieitez (Instituto de
Investigaci
ons Mariñas-CSIC), María José Paz
o
(Instituto de Investigaci
ons Mariñas-CSIC), Ester Jeru-
salén (Instituto de Investigaci
ons Mariñas-CSIC) and
Uxúe Uribe (University of Vigo) for their help during the
surveys and their support during porewater analysis.
The authors also thank Cecilia Costas (University of
Vigo) for her help in the microbial network analysis.
This research was financed by the SUBACID project
(SUBmarine groundwater discharge (SGD) impact on
coastal ACIDification processes in contrasting Atlantic
Shores: toward securing ecosystem services and food
production), funded by the Irish Research Council and
the European Union’s Horizon 2020 Research and
Innovation Program under the Marie Skłodowska-Curie
grant agreement No. 713279 through the CAROLINE
program (CLNE/2017/210) and the INTERES project,
funded by the Spanish Ministry of Economy and Com-
petitiveness (CTM2017-83362-R). E. Calvo-Martin
received funding from the Spanish government through
the FPU PhD grant number FPU20/04707 and from the
Galician government through the PhD grant number
IN606A-2021/022.
DATA AVAILABILITY STATEMENT
The environmental data used in this study can be found
in the supplementary materials. The sequencing data
for this study have been deposited in the NCBI Gen-
Bank (https://www.ncbi.nlm.nih.gov/genbank) under
accession number PRJNA822065
CONFLICT OF INTEREST
The authors declare no conflict of interest.
ORCID
Elisa Calvo-Martin https://orcid.org/0000-0002-6936-
8175
Eva Teira https://orcid.org/0000-0002-4333-0101
Xosé Ant
on
´
Alvarez-Salgado https://orcid.org/0000-
0002-2387-9201
Carlos Rocha https://orcid.org/0000-0002-2257-1352
Juan Severino Pino Ib
anhez https://orcid.org/0000-
0001-6093-3054
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SUPPORTING INFORMATION
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How to cite this article: Calvo-Martin, E., Teira,
E., ´
Alvarez-Salgado, X.A., Rocha, C., Jiang, S.,
Justel-Díez, M. et al. (2022) On the hidden
diversity and niche specialization of the microbial
realm of subterranean estuaries. Environmental
Microbiology,1–23. Available from: https://doi.
org/10.1111/1462-2920.16160
DIVERSITY OF STE MICROBIAL COMMUNITIES 23
