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  <front>
    <journal-meta>
<journal-id journal-id-type="publisher">BG</journal-id>
<journal-title-group>
<journal-title>Biogeosciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">BG</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Biogeosciences</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1726-4189</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>

    <article-meta>
      <article-id pub-id-type="doi">10.5194/bg-14-2697-2017</article-id><title-group><article-title>Functional diversity of microbial communities in pristine aquifers inferred
by PLFA- and sequencing-based approaches</article-title>
      </title-group><?xmltex \runningtitle{PLFA-based microbial communities in pristine aquifers}?><?xmltex \runningauthor{V. F. Schwab et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1 aff2">
          <name><surname>Schwab</surname><given-names>Valérie F.</given-names></name>
          <email>vf.schwab@uni-jena.de</email>
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3 aff4">
          <name><surname>Herrmann</surname><given-names>Martina</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Roth</surname><given-names>Vanessa-Nina</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Gleixner</surname><given-names>Gerd</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-4616-0953</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Lehmann</surname><given-names>Robert</given-names></name>
          
        <ext-link>https://orcid.org/0000-0001-5681-4431</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Pohnert</surname><given-names>Georg</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Trumbore</surname><given-names>Susan</given-names></name>
          
        <ext-link>https://orcid.org/0000-0003-3885-6202</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3 aff4">
          <name><surname>Küsel</surname><given-names>Kirsten</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Totsche</surname><given-names>Kai U.</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-2692-213X</ext-link></contrib>
        <aff id="aff1"><label>1</label><institution>Friedrich Schiller University, Institute of Geosciences, Jena,
Germany</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>Friedrich Schiller University, Institute for Inorganic and
Analytical Chemistry, Jena, Germany</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>Friedrich Schiller University, Institute of Ecology, Jena, Germany</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>German Centre for Integrative Biodiversity Research (iDiv),
Halle-Jena-Leipzig, Leipzig, Germany</institution>
        </aff>
        <aff id="aff5"><label>5</label><institution>Max-Planck-Institute for Biogeochemistry, Jena, Germany</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Valérie F. Schwab (vf.schwab@uni-jena.de)</corresp></author-notes><pub-date><day>31</day><month>May</month><year>2017</year></pub-date>
      
      <volume>14</volume>
      <issue>10</issue>
      <fpage>2697</fpage><lpage>2714</lpage>
      <history>
        <date date-type="received"><day>17</day><month>October</month><year>2016</year></date>
           <date date-type="rev-request"><day>3</day><month>November</month><year>2016</year></date>
           <date date-type="rev-recd"><day>23</day><month>March</month><year>2017</year></date>
           <date date-type="accepted"><day>4</day><month>April</month><year>2017</year></date>
      </history>
      <permissions>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/3.0/">https://creativecommons.org/licenses/by/3.0/</ext-link></license-p>
</license>
</permissions><self-uri xlink:href="https://bg.copernicus.org/articles/14/2697/2017/bg-14-2697-2017.html">This article is available from https://bg.copernicus.org/articles/14/2697/2017/bg-14-2697-2017.html</self-uri>
<self-uri xlink:href="https://bg.copernicus.org/articles/14/2697/2017/bg-14-2697-2017.pdf">The full text article is available as a PDF file from https://bg.copernicus.org/articles/14/2697/2017/bg-14-2697-2017.pdf</self-uri>


      <abstract>
    <p>Microorganisms in groundwater play an important role in aquifer
biogeochemical cycles and water quality. However, the mechanisms linking the
functional diversity of microbial populations and the groundwater
physico-chemistry are still not well understood due to the complexity of
interactions between surface and subsurface. Within the framework of Hainich
(north-western Thuringia, central Germany) Critical Zone Exploratory of the
Collaborative Research Centre AquaDiva, we used the relative abundances of
phospholipid-derived fatty acids (PLFAs) to link specific biochemical markers
within the microbial communities to the spatio-temporal changes of the
groundwater physico-chemistry. The functional diversities of the microbial
communities were mainly correlated with groundwater chemistry, including
dissolved O<inline-formula><mml:math id="M1" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, Fe<inline-formula><mml:math id="M2" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula> and NH<inline-formula><mml:math id="M3" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> concentrations.
Abundances of PLFAs derived from eukaryotes and potential nitrite-oxidizing
bacteria (11Me16:0 as biomarker for <italic>Nitrospira moscoviensis</italic>) were
high at sites with elevated O<inline-formula><mml:math id="M4" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> concentration where groundwater recharge
supplies bioavailable substrates. In anoxic groundwaters more rich in
Fe<inline-formula><mml:math id="M5" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula>, PLFAs abundant in sulfate-reducing bacteria (SRB),
iron-reducing bacteria and fungi increased with Fe<inline-formula><mml:math id="M6" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula> and
HCO<inline-formula><mml:math id="M7" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> concentrations, suggesting the occurrence of active iron
reduction and the possible role of fungi in meditating iron solubilization
and transport in those aquifer domains. In more NH<inline-formula><mml:math id="M8" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>-rich anoxic
groundwaters, anammox bacteria and SRB-derived PLFAs increased with
NH<inline-formula><mml:math id="M9" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> concentration, further evidencing the dependence of the anammox
process on ammonium concentration and potential links between SRB and anammox
bacteria. Additional support of the PLFA-based bacterial communities was
found in DNA- and RNA-based Illumina MiSeq amplicon sequencing of bacterial
16S rRNA genes, which showed high predominance of nitrite-oxidizing bacteria
<italic>Nitrospira</italic>, e.g. <italic>Nitrospira moscoviensis</italic>, in oxic aquifer
zones and of anammox bacteria in more NH<inline-formula><mml:math id="M10" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>-rich anoxic groundwater.
Higher relative abundances of sequence reads in the RNA-based datasets
affiliated with iron-reducing bacteria in more Fe<inline-formula><mml:math id="M11" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula>-rich
groundwater supported the occurrence of active dissimilatory iron reduction.
The functional diversity of the microbial communities in the biogeochemically
distinct groundwater assemblages can be largely attributed to the redox
conditions linked to changes in bioavailable substrates and input of
substrates with the seepage. Our results demonstrate the power of
complementary information derived from PLFA-based and sequencing-based
approaches.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <title>Introduction</title>
      <p>Continental and marine subsurface environments represent the largest habitat
on Earth for microbial life and therefore are of primary importance for
energy fluxes on a global scale (Edwards et al., 2012). In terrestrial
ecosystems, complex interactions between the surface and subsurface
compartments (including aquifers), such as groundwater recharge and rainfall
event-driven flow, influence the availability of O<inline-formula><mml:math id="M12" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, and the nature and
abundance of bioavailable organic matter (OM; Benner et al., 1995; Kalbus et
al., 2006). Young and shallow groundwaters tend to maintain the chemical
characteristics of surface, i.e. higher O<inline-formula><mml:math id="M13" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> levels and greater amounts of
bioavailable substrates (e.g. labile OM) which support aerobic heterotrophic
microbial activity (Landmeyer et al., 1996). In contrast, deep and especially
fossil groundwaters tend to reflect the chemistry of the aquifer materials.
They have typically lower concentrations of O<inline-formula><mml:math id="M14" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> and bioavailable
substrates which cause facultative anaerobes to switch to terminal electron
acceptors with lower energy yield such as NO<inline-formula><mml:math id="M15" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>, MnO<inline-formula><mml:math id="M16" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, FeOOH and
SO<inline-formula><mml:math id="M17" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> (Chapelle and Lovley, 1992). In pristine aquifers, a low amount
of OM typically results in a higher amount of terminal electron acceptors
than electron donors (Chapelle, 2001). As many chemo-lithoautotrophs can use
a variety of compounds to meet their energy needs in the dark subsurface, an
increasing number of studies report the importance of chemo-lithoautotrophy in groundwater (Stevens and McKinley,
1995; Emerson et al., 2015; Herrmann et al., 2015). However, it is still not
well understood how the composition and function of microbial communities in
groundwaters depend on hydrology, chemistry and the relationship to
groundwater recharge dynamics.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T1" specific-use="star"><caption><p>Lipid markers proposed to represent a group or genus of
microorganisms.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="3">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="justify" colwidth="199.169291pt"/>
     <oasis:thead>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1">Lipid marker</oasis:entry>  
         <oasis:entry colname="col2">Interpretation</oasis:entry>  
         <oasis:entry colname="col3">References</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>  
         <oasis:entry colname="col1">Branched PLFAs</oasis:entry>  
         <oasis:entry colname="col2">Gram-positive bacteria</oasis:entry>  
         <oasis:entry colname="col3">Harwood and Russell (1984)</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">Mono-saturated PLFAs</oasis:entry>  
         <oasis:entry colname="col2">Gram-negative bacteria</oasis:entry>  
         <oasis:entry colname="col3">Wilkinson (1988)</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">10Me18:0</oasis:entry>  
         <oasis:entry colname="col2">Actinomycetes</oasis:entry>  
         <oasis:entry colname="col3">Zogg et al. (1997); Zelles et al. (1997)</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">18:1<inline-formula><mml:math id="M18" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>9c. 18:2<inline-formula><mml:math id="M19" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>6c, 18:3<inline-formula><mml:math id="M20" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>6c, 18:3<inline-formula><mml:math id="M21" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>3c</oasis:entry>  
         <oasis:entry colname="col2">Fungi</oasis:entry>  
         <oasis:entry colname="col3">Frostegard and Bååth (1996)</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">10Me16:0, cy18:0(<inline-formula><mml:math id="M22" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>7,8)</oasis:entry>  
         <oasis:entry colname="col2"><italic>Desulfobacter</italic></oasis:entry>  
         <oasis:entry colname="col3">Dowling et al. (1986)</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">11Me16:0. 16:1<inline-formula><mml:math id="M23" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>11</oasis:entry>  
         <oasis:entry colname="col2"><italic>Nitrospira moscoviensis</italic></oasis:entry>  
         <oasis:entry colname="col3">Lipski et al. (2001)</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">i17 :1<inline-formula><mml:math id="M24" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>7c, i15 :1<inline-formula><mml:math id="M25" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>7c, i19:1<inline-formula><mml:math id="M26" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>7c</oasis:entry>  
         <oasis:entry colname="col2"><italic>Desulfovibrio</italic></oasis:entry>  
         <oasis:entry colname="col3">Edlund et al. (1985), Kohring et al. (1994)</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">17:1<inline-formula><mml:math id="M27" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>6, 15:1</oasis:entry>  
         <oasis:entry colname="col2"><italic>Desulfobulbus</italic></oasis:entry>  
         <oasis:entry colname="col3">Parkes and Calder (1985), Macalady et al. (2000)</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">i17 :1<inline-formula><mml:math id="M28" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>5, 10Me18:1<inline-formula><mml:math id="M29" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>6, 11Me18:1<inline-formula><mml:math id="M30" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>6</oasis:entry>  
         <oasis:entry colname="col2"><italic>Thiobacillus</italic></oasis:entry>  
         <oasis:entry colname="col3">Kerger et al. (1986, 1987)</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">20:2<inline-formula><mml:math id="M31" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>6, 20:3<inline-formula><mml:math id="M32" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>6, 20:4<inline-formula><mml:math id="M33" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>6, 22:5, 22:6</oasis:entry>  
         <oasis:entry colname="col2">Fungi, <italic>Protozoa,</italic> Algea</oasis:entry>  
         <oasis:entry colname="col3">Kennedy et al. (1993), Olsson (1999), White (1988); Volkman et al. (1989)</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">[3]-ladderane, [5]-ladderane</oasis:entry>  
         <oasis:entry colname="col2">Anammox</oasis:entry>  
         <oasis:entry colname="col3">Sinninghe Damsté et al. (2002, 2005)</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

      <p>There are a number of ways to assess the composition and function of
microbial communities in groundwaters. Intact polar lipids, mainly
phospholipids, are important constituents of bacterial and eukaryotic cell
membranes. They consist of a polar head group linked to a glycerol backbone
with two fatty acids esterified to it. Because various phospholipid-derived
fatty acids (PLFAs) are indicative of specific types or groups of bacteria in
soil (e.g. Frostegård and Bååth, 1996; Frostegård et al.,
2011) and aquifers (Green and Scow, 2000), PLFA-based studies are recognised
as a valuable approach to infer the presence of specific microbial groups and
to show trends in the spatial distribution of active microbial populations
related to specific substrate utilization patterns in environments (e.g.
Torsvik and Øvreås, 2002; Schneider et al., 2012). PLFAs that are
commonly associated with a group or genus of bacteria are listed in Table 1.
Additionally, the stable carbon isotope ratios (<inline-formula><mml:math id="M34" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>C values) of
PLFAs reflect a combination of the source of microbial carbon and kinetic
isotope fractionation effects associated with the carbon assimilation pathway
(e.g. heterotrophy, autotrophy, methanotrophy; Teece et al., 1999; Zhang et
al., 2003; Londry et al., 2004). Although a wide range of carbon isotope
effects have been measured, in general autotrophs are expected to have PLFA
<inline-formula><mml:math id="M35" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>C values more negative than heterotrophs (Blair et al., 1985;
Teece et al., 1999; van der Meer et al., 2001; Zhang et al., 2003; Londry et
al., 2004; Schouten et al., 2004). In particular, large isotope effects have
been associated with anammox bacteria that have PLFA <inline-formula><mml:math id="M36" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>C values as
much as 47 ‰ more negative than the dissolved inorganic carbon (DIC)
source (Schouten et al., 2004).</p>
      <p>Despite PLFAs being widely used in microbial ecology, their potential to
assess changes in microbial communities still remains the topic of many
research efforts. One of the major limitations of PLFA-based studies is the
definitive identification of the lipid sources, since many PLFAs commonly
associated with a group or genus of bacteria (Table 1) may also be found,
albeit in smaller amounts, in cell membranes of other organisms
(Frostegård et al., 2011). A few PLFAs are highly specific, for example
ladderanes are characteristic membrane constituents of anammox bacteria
(Sinninghe Damsté et al., 2002, 2005) and have commonly been used to
infer the presence of active anammox bacteria in diverse environments
(Kuypers et al., 2003; Jaeschke et al., 2009). As these organisms are capable
of anaerobically oxidizing ammonium with nitrite to molecular N<inline-formula><mml:math id="M37" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, they
play an essential role in N removal from marine (Dalsgaard et al., 2003;
Burgin and Hamilton, 2007) and lacustrine environments (Yoshinaga et al.,
2011). Yet their role in aquifer environments is only starting to be
considered (Humbert et al., 2009). Another important limitation may reside in
the PLFA extraction technique. Heinzelmann et al. (2014) showed that the
proposed method to separate the glycolipids and phospholipids is incomplete
and results in a significant proportion of glycolipids, betaine lipids and
sulfoquinovosyl diacylglycerols (SQDGs) in the phospholipids fraction.
Therefore, PLFA fractions might also contain fatty acids derived from
glycolipids, betaine lipids, and to some extent SQDGs, and thus might not
only reflect the active biomass.</p>
      <p>In an attempt to overcome some of these limitations, we combined a detailed
multivariate statistical analysis of PLFAs with PLFA <inline-formula><mml:math id="M38" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>C values,
and DNA- and RNA-based Illumina MiSeq amplicon sequencing of bacterial
16S rRNA genes in groundwaters with different redox conditions and water
chemistry (Kohlhepp et al., 2016). This approach allows for parallel study of
microbial community composition and specific substrate consumption by
evidencing specific PLFAs that respond significantly to changes in the
groundwater chemistry. Microbial community structure and potential function
assessed by PLFAs were confirmed by Illumina MiSeq amplicon sequencing
targeting 16S rRNA genes and transcripts, providing a more detailed insight
into bacterial community structure and taxonomic affiliation (Kozich et al.,
2013). We showed that such a PLFA-based study has particular relevance and
importance when trying to understand how micro-organisms in groundwater
interact with their environment. This study provides baselines for future
studies investigating the impact of changes in surface conditions on
microorganism in carbonate-rock aquifer ecosystems.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1" specific-use="star"><caption><p>Schematic geological cross section
of the Hainich monitoring well transect (without karst features). The wells
sampled for this study are numbered in black. The black colours in the wells
indicate screen sections and accessed depths of the aquifer assemblages.
Abbreviations: mm: Middle Muschelkalk; mo: Upper Muschelkalk; moTK:
Trochitenkalk formation; moM &amp; CB: Meissner formation with Cycloides-Bank;
moW: Warburg formation; ku: Lower Keuper.</p></caption>
        <?xmltex \igopts{width=384.112205pt}?><graphic xlink:href="https://bg.copernicus.org/articles/14/2697/2017/bg-14-2697-2017-f01.png"/>

      </fig>

</sec>
<sec id="Ch1.S2">
  <title>Sampling and methods</title>
<sec id="Ch1.S2.SS1">
  <title>Study site</title>
      <p>The sampled groundwater wells are part of the monitoring well transect of the
Hainich Critical Zone Exploratory (CZE: north-western Thuringia, central
Germany) of the Collaborative Research Centre (CRC) AquaDiva. AquaDiva aims
to determine how deep signals of surface environmental conditions can be
traced into the critical zone (Küsel et al., 2016). The wells access two
distinct aquifer assemblages in marine sediments of the Upper Muschelkalk
(mo) lithostratigraphic subgroup (Germanic Triassic, Middle Triassic epoch)
at different depths and locations (Fig. 1). Wells in the hilltop recharge
areas (H1, H2) were not sampled, due to very low groundwater levels or
desaturation. Aquifers predominantly receive surface recharge in their
outcrop areas at the eastern Hainich hillslope. The lower aquifer assemblage
(subsequently referred to as HTL) represents one aquifer hosted in the
Trochitenkalk formation (moTK), whereas the upper aquifer assemblage
(referred to as HTU) comprises several aquifers and aquitards of the Meissner
formation. The HTL, sampled at depths ranging from 41 to 88 m below the
surface, is rich in O<inline-formula><mml:math id="M39" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, whereas the upper aquifer found at depths from
12 to 50 m below the surface, is anoxic to sub-oxic. Both aquifer assemblages
are found in alternating sequences of limestones and marlstones that are
partly karstified (Kohlhepp et al., 2016). More details on the CZE and well
constructions can be found in Küsel et al. (2016) and Kohlhepp et
al. (2016).</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T2" specific-use="star"><caption><p>Well depths, sampling dates and stratigraphic units of the monitoring wells studied.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="6">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="left"/>
     <oasis:colspec colnum="5" colname="col5" align="left"/>
     <oasis:colspec colnum="6" colname="col6" align="justify" colwidth="142.26378pt"/>
     <oasis:thead>
       <oasis:row>  
         <oasis:entry colname="col1">Well</oasis:entry>  
         <oasis:entry colname="col2">Aquifer</oasis:entry>  
         <oasis:entry colname="col3">Well depth<inline-formula><mml:math id="M41" display="inline"><mml:msup><mml:mi/><mml:mo>*</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>  
         <oasis:entry colname="col4">Sampling</oasis:entry>  
         <oasis:entry colname="col5">Stratigraphic</oasis:entry>  
         <oasis:entry colname="col6">Notes</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1">name</oasis:entry>  
         <oasis:entry colname="col2">assemblage</oasis:entry>  
         <oasis:entry colname="col3">(m)</oasis:entry>  
         <oasis:entry colname="col4">dates</oasis:entry>  
         <oasis:entry colname="col5">unit</oasis:entry>  
         <oasis:entry colname="col6"/>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>  
         <oasis:entry colname="col1">H3.1</oasis:entry>  
         <oasis:entry colname="col2">HTL</oasis:entry>  
         <oasis:entry colname="col3">42.7–46.7</oasis:entry>  
         <oasis:entry colname="col4">June 2014</oasis:entry>  
         <oasis:entry colname="col5">moTK</oasis:entry>  
         <oasis:entry colname="col6">well almost dry. Pumped only 100 L</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">H3.2</oasis:entry>  
         <oasis:entry colname="col2">HTU</oasis:entry>  
         <oasis:entry colname="col3">15–22</oasis:entry>  
         <oasis:entry colname="col4">June, September 2014</oasis:entry>  
         <oasis:entry colname="col5">moM</oasis:entry>  
         <oasis:entry colname="col6">well dry in December 2014</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">H4.1</oasis:entry>  
         <oasis:entry colname="col2">HTL</oasis:entry>  
         <oasis:entry colname="col3">44.5–47.5</oasis:entry>  
         <oasis:entry colname="col4">June, September 2014</oasis:entry>  
         <oasis:entry colname="col5">moTK</oasis:entry>  
         <oasis:entry colname="col6">well not accessible in December 2014</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">H4.2</oasis:entry>  
         <oasis:entry colname="col2">HTU</oasis:entry>  
         <oasis:entry colname="col3">8.5-11.5</oasis:entry>  
         <oasis:entry colname="col4">June, September 2014</oasis:entry>  
         <oasis:entry colname="col5">moM</oasis:entry>  
         <oasis:entry colname="col6">well not accessible in December 2014</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">H4.3</oasis:entry>  
         <oasis:entry colname="col2">HTU</oasis:entry>  
         <oasis:entry colname="col3">8.5–12.5</oasis:entry>  
         <oasis:entry colname="col4">June, September 2014</oasis:entry>  
         <oasis:entry colname="col5">moM</oasis:entry>  
         <oasis:entry colname="col6">well not accessible in December 2014</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">H5.1</oasis:entry>  
         <oasis:entry colname="col2">HTL</oasis:entry>  
         <oasis:entry colname="col3">84–88</oasis:entry>  
         <oasis:entry colname="col4">June, September, December 2014</oasis:entry>  
         <oasis:entry colname="col5">moTK</oasis:entry>  
         <oasis:entry colname="col6"/>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">H5.2</oasis:entry>  
         <oasis:entry colname="col2">HTU</oasis:entry>  
         <oasis:entry colname="col3">65–69</oasis:entry>  
         <oasis:entry colname="col4">June, September, December 2014</oasis:entry>  
         <oasis:entry colname="col5">moM</oasis:entry>  
         <oasis:entry colname="col6"/>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">H5.3</oasis:entry>  
         <oasis:entry colname="col2">HTU</oasis:entry>  
         <oasis:entry colname="col3">47–50</oasis:entry>  
         <oasis:entry colname="col4">June, September, December 2014</oasis:entry>  
         <oasis:entry colname="col5">moM</oasis:entry>  
         <oasis:entry colname="col6"/>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table><table-wrap-foot><p><inline-formula><mml:math id="M40" display="inline"><mml:msup><mml:mi/><mml:mo>*</mml:mo></mml:msup></mml:math></inline-formula> Depth of well screen section below surface. HTL: Hainich transect lower aquifer assemblage. HTU: Hainich transect upper aquifer assemblage. moTK: Upper Muschelkalk, Trochitenkalk formation. moM: Upper Muschelkalk, Meissner formation.</p></table-wrap-foot></table-wrap>

</sec>
<sec id="Ch1.S2.SS2">
  <title>Groundwater sampling</title>
      <p>Groundwater was sampled for chemical analyses and colloidal and/or
particulate organic matter in June, September and December of 2014 (Table 2)
during regular sampling campaigns within the coordinated joint monitoring
program of the CRC. Groundwater samples were collected at locations H3, H4,
and H5 (i.e. the lower topographic positions of the well transect, Fig. 1).
Wells H3.2, H4.2, H4.3, H5.2 and H5.3 reach into the HTU, while wells H3.1,
H4.1 and H5.1 access the HTL aquifer (Fig. 1). The wells were originally
drilled between 2009 and 2011, and were specifically designed for sampling
groundwater (micro-) organisms and particles. Prior to sampling, stagnant
water (at least three well volumes) was pumped out and discarded until the
physico-chemical parameters pH, dissolved O<inline-formula><mml:math id="M42" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> concentration, redox
potential and specific electrical conductivity remained constant.
Subsequently, <inline-formula><mml:math id="M43" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 1000 L of groundwater were filtered on-site using a
submersible pump (Grundfos SQE 5-70, Grundfos, Denmark) connected to a
stainless steel filter device (diameter 293 mm, Millipore USA) equipped with
a removable pre-combusted (5 h at 500 <inline-formula><mml:math id="M44" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C) glass fiber filter
(Sterlitech, USA) of fine porosity (0.3 <inline-formula><mml:math id="M45" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>m), allowing a water flow
of ca. 20 L min<inline-formula><mml:math id="M46" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. Filters with the collected particulates were
carefully removed, immediately transferred to dry ice and stored at
<inline-formula><mml:math id="M47" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>80 <inline-formula><mml:math id="M48" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C until analysis. Groundwater extraction temperature, redox
potential, specific electrical conductivity, pH and dissolved O<inline-formula><mml:math id="M49" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>
concentration were monitored continuously during pumping in a flow-through
cell equipped with the probes TetraCon 925, FDO 925, SenTix 980, ORP 900 and
Multi 3430 IDS meter (WTW GmbH, Germany).</p>
      <p>During the sampling campaign of June 2014, groundwater was additionally
sampled for nucleic acid extraction. The groundwater was transferred to
sterile glass bottles and kept at 4 <inline-formula><mml:math id="M50" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C. Within a few hours after
sampling, 5–6 L of groundwater was filtered through
0.2 <inline-formula><mml:math id="M51" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>m pore size polyethersulfone (PES) filters (Pall Corporation,
USA), and 2 L were filtered through 0.2 <inline-formula><mml:math id="M52" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>m pore size polycarbonate
filters (Nuclepore, Whatman, United Kingdom) for extraction of DNA and RNA,
respectively. Filters were immediately transferred to dry ice and stored at
<inline-formula><mml:math id="M53" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>80 <inline-formula><mml:math id="M54" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C until nucleic acid extraction.</p>
</sec>
<sec id="Ch1.S2.SS3">
  <title>Groundwater chemistry analyses</title>
      <p>Concentration of the major anions (SO<inline-formula><mml:math id="M55" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula>, Cl<inline-formula><mml:math id="M56" display="inline"><mml:msup><mml:mi/><mml:mo>-</mml:mo></mml:msup></mml:math></inline-formula>, NO<inline-formula><mml:math id="M57" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> and
PO<inline-formula><mml:math id="M58" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula>; PES filter <inline-formula><mml:math id="M59" display="inline"><mml:mo>&lt;</mml:mo></mml:math></inline-formula> 0.45 <inline-formula><mml:math id="M60" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>m) were determined according
to DIN EN ISO 10304-1 (2009) using an ion chromatograph (DX-120, Dionex, USA;
equipped with an IonPac AS11-HC column and an IonPac AG11-HC pre-column). The
redox-sensitive parameters (Fe<inline-formula><mml:math id="M61" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula>, NO<inline-formula><mml:math id="M62" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>, NH<inline-formula><mml:math id="M63" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> were
determined by colorimetry (DR 890, Hach Company, USA) according to
manufacturer's protocol following APHA (1981) and Reardon et al. (1966). The
concentration of dissolved organic carbon (DOC) and
DIC(filter <inline-formula><mml:math id="M64" display="inline"><mml:mo>&lt;</mml:mo></mml:math></inline-formula> 0.45 <inline-formula><mml:math id="M65" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>m) were determined by high-temperature
catalytic oxidation (multi 18 N/C 2100S, Analytik Jena, Germany) according to
DIN EN 1484 (1997). Total S (S<inline-formula><mml:math id="M66" display="inline"><mml:mrow><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula>, Mn (Mn<inline-formula><mml:math id="M67" display="inline"><mml:mrow><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> and iron
(Fe<inline-formula><mml:math id="M68" display="inline"><mml:mrow><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> were analysed by ICP-OES (725 ES, Varian, Agilent, USA)
according to DIN EN ISO 11885 (2009). The acid and base neutralizing capacity
(ANC, BNC) by acid–base endpoint titration was determined according to
DIN 38409-7 (2005). The approximated concentrations of HCO<inline-formula><mml:math id="M69" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> and
CO<inline-formula><mml:math id="M70" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> were converted from ANC<inline-formula><mml:math id="M71" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">4.3</mml:mn></mml:msub></mml:math></inline-formula> and BNC<inline-formula><mml:math id="M72" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">8.2</mml:mn></mml:msub></mml:math></inline-formula> by simple
replacement (cCO<inline-formula><mml:math id="M73" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> (mmol L<inline-formula><mml:math id="M74" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) <inline-formula><mml:math id="M75" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> BNC<inline-formula><mml:math id="M76" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">8.2</mml:mn></mml:msub></mml:math></inline-formula>
(mmol L<inline-formula><mml:math id="M77" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula>; cHCO<inline-formula><mml:math id="M78" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> (mmol L<inline-formula><mml:math id="M79" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) <inline-formula><mml:math id="M80" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> BNC<inline-formula><mml:math id="M81" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">4.3</mml:mn></mml:msub></mml:math></inline-formula>
(mmol L<inline-formula><mml:math id="M82" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup><mml:mo>)</mml:mo><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula>, assuming that other buffering species than those are
negligible, in the nearly pH-neutral waters (Wisotzky, 2011).</p>
</sec>
<sec id="Ch1.S2.SS4">
  <title>PLFA extraction and pre-treatment</title>
      <p>To minimize external contamination, all material (including filters) and
glass in contact with the samples during extraction and purification were
baked at 500 <inline-formula><mml:math id="M83" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C for 5 h to remove organic contaminants. Only trace
levels of 16 : 0 fatty acid methyl ester (FAME) have been detected in blank
extracts. PLFAs were extracted from filters using a method slightly modified
from Bligh and Dyer (1959) and Seifert et al. (2013). The filters were cut
into small pieces and extracted in a phase solution of chloroform–methanol
(2 : 1; <inline-formula><mml:math id="M84" display="inline"><mml:mrow><mml:mi>v</mml:mi><mml:mo>/</mml:mo><mml:mi>v</mml:mi></mml:mrow></mml:math></inline-formula>) with a 0.005 M phosphate buffer. The solution was rotated
and shaken for 4 h. Chloroform and water (1 : 1; <inline-formula><mml:math id="M85" display="inline"><mml:mrow><mml:mi>v</mml:mi><mml:mo>/</mml:mo><mml:mi>v</mml:mi></mml:mrow></mml:math></inline-formula>) were then added to
the mixture. After shaking, the chloroform phase, containing the Bligh–Dyer
extract (BDE), was separated from the water–MeOH phase and concentrated by a
rotary evaporator. The BDE was then partitioned into the conventionally
defined neutral lipid, glycolipid and phospholipid fractions by
chromatography (solid phase extraction: SPE, 6 mL column) on pre-activated
silica gel (Merck silica mesh 230–400, 2 g pre-activated for 1 h at
100 <inline-formula><mml:math id="M86" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C) using chloroform (12 mL), acetone (12 mL) and methanol
(48 mL), respectively. The phospholipids were converted to FAMEs using
mild-alkaline hydrolysis and methylation (White et al., 1979). The different
fatty acids were then separated using NH<inline-formula><mml:math id="M87" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> column (Chromabond 3 mL,
500 mg) with 3 mL of hexane–DCM (3 : 1; <inline-formula><mml:math id="M88" display="inline"><mml:mrow><mml:mi>v</mml:mi><mml:mo>/</mml:mo><mml:mi>v</mml:mi></mml:mrow></mml:math></inline-formula>) for eluting the
unsubstituted FAMEs; 3 mL of DCM–ethylacetate (9 : 1; <inline-formula><mml:math id="M89" display="inline"><mml:mrow><mml:mi>v</mml:mi><mml:mo>/</mml:mo><mml:mi>v</mml:mi></mml:mrow></mml:math></inline-formula>) for the
hydroxy FAME and 6 mL of 2 % acetic acid in methanol for unsaponifiable
lipids. To quantify the recovery, the standard,
1,2-dinonadecanoyl-sn-glycero-3-phosphatidyl-choline (Avanti Polar Lipids,
Inc. USA) was added on clean pre-combusted glass filters that were treated
exactly the same as the samples following the above protocol. The formed
C19:0 FAME was quantified to calculate a mean recovery of 82 %. To test
the efficiency of the separation between the glycolipids and the
phospholipids, the glycolipid standard digalactosyl diglyceride (Sigma
Aldrich) and the phospholipid standard
1,2-dinonadecanoyl-sn-glycero-3-phosphatidyl-choline were run through the SPE
column using the above protocol. The absence of phospholipid-derived FA
(C19:0) in the glycolipid fraction and glycolipid-derived fatty acids (C17:2)
in the phospholipid fractions points to an efficient separation and thus a
major origin of the studied FAME from phospholipid head groups.</p>
</sec>
<sec id="Ch1.S2.SS5">
  <title>Nucleic acid extraction, amplicon sequencing, and sequence
analysis</title>
      <p>DNA was extracted from the PES filters using the Power Soil DNA extraction
kit (Mo Bio, CA, USA) following the manufacturer's instructions. RNA was
extracted from polycarbonate filters using the Power Water RNA Isolation Kit
(Mo Bio, CA, USA). Traces of co-extracted genomic DNA were removed using
Turbo DNA free (Thermo Fisher Scientific, Germany), and reverse transcription
to cDNA was performed using ArrayScript Reverse Transcriptase (Thermo Fisher
Scientific) as described previously (Herrmann et al., 2012). DNA and cDNA
obtained from the groundwater samples from PNK51 were shipped to LGC Genomic
GmbH (Berlin, Germany) for Illumina MiSeq amplicon sequencing of the V3–V5
region of 16S rRNA genes and transcripts, using the primer combination
Bakt_341F and Bakt_805R (Herlemann et al., 2011). Sequence analysis was
performed using Mothur v. 1.36 (Schloss et al., 2009), following the MiSeq
SOP (<uri>http://www.mothur.org/wiki/MiSeq_SOP</uri>; Kozich et al., 2013).
Quality-trimmed sequence reads were aligned to the SILVA reference database
(v 119; Quast et al., 2013). Potential chimeric sequences were detected and
removed using the UCHIME algorithm implemented in Mothur. Taxonomic
classification of sequence reads was based on the SILVA reference database
(v 119). To facilitate comparisons across samples, sequence-read numbers per
sample were normalized to the smallest number of sequence reads obtained
across all samples using the subsample command implemented in Mothur. Raw
data from 16S rRNA amplicon Illumina sequencing were submitted to the
European Nucleotide Archive database under the study accession number
PRJEB14968 and sample accession numbers ERS1270616 to ERS1270631.</p>
</sec>
<sec id="Ch1.S2.SS6">
  <title>Gas chromatography (GC) and gas chromatography–mass spectrometry</title>
      <p>A total of 10 % of the PLFA extracts were used for peak identification
and relative quantification using a gas chromatograph (Trace 1310 GC) coupled
to a triple quadrupole mass spectrometer (TSQ-8000; Thermo Fisher, Bremen,
Germany) at the Friedrich Schiller University Jena's Institute of Inorganic
and Analytical Chemistry (Germany). The GC was equipped with a TG 5silms
capillary column (60 m, 0.25 mm, 0.25 <inline-formula><mml:math id="M90" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>m film thickness). Helium
was used as carrier gas at a constant flow of 1.2 mL min<inline-formula><mml:math id="M91" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. The GC
oven was programmed to have an initial temperature of 70 <inline-formula><mml:math id="M92" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C (hold
1 min) and a heating rate of 2 <inline-formula><mml:math id="M93" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C min<inline-formula><mml:math id="M94" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> until 250 <inline-formula><mml:math id="M95" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C
followed by a heating rate of 50 <inline-formula><mml:math id="M96" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C min<inline-formula><mml:math id="M97" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> until
280 <inline-formula><mml:math id="M98" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C and held for 5 min. The PTV injector was operated in
splitless mode at an initial temperature of 70 <inline-formula><mml:math id="M99" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C. Upon injection,
the injector was heated to 280 <inline-formula><mml:math id="M100" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C at a programmed rate of
14.5 <inline-formula><mml:math id="M101" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C s<inline-formula><mml:math id="M102" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> and held at this temperature for 2 min.
Afterwards, the PTV was heated to 320 <inline-formula><mml:math id="M103" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C and held for 5 min. FAMEs
were quantified relative to an internal standard nonadecanoic acid-methyl
ester (19 : 0) added prior to GC analysis. FAMEs were identified based on
the mass spectra and on retention time of standards. Standard nomenclature is
used to describe PLFAs. The number before the colon refers to the total
number of C atoms; the number(s) following the colon refers to the number of
double bonds and their location (after the “<inline-formula><mml:math id="M104" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>”) in the fatty acid
molecule. The prefixes “me”, “cy”, “<inline-formula><mml:math id="M105" display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula>” and “<inline-formula><mml:math id="M106" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>” refer to the
methyl group, cyclopropane groups, and iso- and anteiso-branched fatty acids,
respectively.</p>
</sec>
<sec id="Ch1.S2.SS7">
  <title>PLFA distribution and statistical analyses</title>
      <p>The 47 PLFAs, expressed in percentage, were investigated in the different
wells (Supplement Table S1). The sum of the PLFAs considered to be
predominantly of bacterial origin (BactPLFA; <inline-formula><mml:math id="M107" display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula>15:0, <inline-formula><mml:math id="M108" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>15:0, 15:0,
16:1<inline-formula><mml:math id="M109" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>7, 16:0, cy17:0, 18:1<inline-formula><mml:math id="M110" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>7, 18:0 and cy19:0) was used as an
index of the bacterial biomass (Bossio and Scow, 1998; Frostegård and
Bååth, 1996). The fungal biomass (FunPLFA) was estimated from the sum
of the relative abundance of the 18:2<inline-formula><mml:math id="M111" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>6c (Bååth et al.,
1995), 18:3<inline-formula><mml:math id="M112" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>6c (Hamman et al., 2007) and 18:1<inline-formula><mml:math id="M113" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>9c (Myers et
al., 2001); these were all significantly correlated with each other.
Gram-positive (G<inline-formula><mml:math id="M114" display="inline"><mml:mrow><mml:mo>+</mml:mo><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> bacteria were represented by the sum of PLFAs: <inline-formula><mml:math id="M115" display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula>12:0,
<inline-formula><mml:math id="M116" display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula>13:0, <inline-formula><mml:math id="M117" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>15:0 and <inline-formula><mml:math id="M118" display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula>15:0 (Kaur et al., 2005). Gram-negative (G<inline-formula><mml:math id="M119" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>) bacteria
included 16:1<inline-formula><mml:math id="M120" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>7c, cy17:0, 18:1<inline-formula><mml:math id="M121" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>7c and cy19:0 (Kaur et al.,
2005). The ratios of FunPLFA <inline-formula><mml:math id="M122" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> BactPLFA and G<inline-formula><mml:math id="M123" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula> <inline-formula><mml:math id="M124" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> G<inline-formula><mml:math id="M125" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> were
calculated from the above PLFAs.</p>
      <p>The PLFA data and 29 environmental parameters were used for
principal component analysis (PCA) and redundancy analysis (RDA) using Canoco
for Windows, version 5 (Microcomputer Power, Ithaca, New York, United
States). Before regression, the data were centred and standardized. We used
PCA to emphasise strong variations and similarities of the PLFA distributions
between the wells and to identify patterns in the dataset. RDA is used to
determine PLFA variations and similarities (response variables) that can be
significantly explained by different environmental parameters (explanatory
variables). This technique helps to identify the environmental parameters
that have the highest effects on the PLFA distribution, i.e. on the microbial
communities in the different wells.</p>
      <p>Additionally, we used variation partitioning analyses with conditional
effects to determine the variations in PLFA composition between the different
wells that can be explained significantly by the preselected environmental
variables. To visualise the PLFAs acting significantly with the environmental
variables (predictor), we used PLFA environmental-variable <inline-formula><mml:math id="M126" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula>-value biplots
(Šmilauer and Lepš, 2014). These plots can be used to approximate the
<inline-formula><mml:math id="M127" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula>-value of the regression between a particular PLFA and an environmental
variable. The PLFAs are represented by arrows projecting from the origin.
Those with a preference for higher values of the environmental variable are
enclosed by a red (indicating positive relationship) circle. Inversely, those
with preference for low values of the corresponding environmental variable
have their arrow tips enclosed by a blue (indicating negative relationship)
circle.</p>
</sec>
<sec id="Ch1.S2.SS8">
  <title>Compound-specific stable isotope carbon measurements</title>
      <p>The carbon stable isotope composition of pre-purified PLFAs was determined
using a GC–C–IRMS system (Deltaplus XL, Finnigan MAT, Bremen, Germany) at
the Max Planck Institute for Biogeochemistry, Jena. Analyses were performed
using 50 % of the total amount of PLFA extracts. The gas chromatograph
(HP5890 GC, Agilent Technologies, Palo Alto USA) was equipped with a DB1-ms
column (60 m, 0.25 mm internal diameter, 0.52 <inline-formula><mml:math id="M128" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>m film thickness;
Agilent). The injector at 280 <inline-formula><mml:math id="M129" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C was operated in splitless mode with
a constant flow of 1 mL min<inline-formula><mml:math id="M130" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. The oven temperature was maintained for
1 min at 70 <inline-formula><mml:math id="M131" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C, heated with
4 <inline-formula><mml:math id="M132" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C min<inline-formula><mml:math id="M133" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> to 300 <inline-formula><mml:math id="M134" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C and held
for 15 min, then heated by 30 <inline-formula><mml:math id="M135" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C min<inline-formula><mml:math id="M136" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> to 330 <inline-formula><mml:math id="M137" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C and
held 3 min. Isotope values, expressed in the delta notation (‰),
were calculated with ISODAT version software relative to the reference
CO<inline-formula><mml:math id="M138" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>. Offset correction factor was determined on a daily basis using a
reference mixture of <inline-formula><mml:math id="M139" display="inline"><mml:mi>n</mml:mi></mml:math></inline-formula>-alkanes (<inline-formula><mml:math id="M140" display="inline"><mml:mi>n</mml:mi></mml:math></inline-formula>-C<inline-formula><mml:math id="M141" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">17</mml:mn></mml:msub></mml:math></inline-formula> to <inline-formula><mml:math id="M142" display="inline"><mml:mi>n</mml:mi></mml:math></inline-formula>-C<inline-formula><mml:math id="M143" display="inline"><mml:mrow><mml:msub><mml:mi/><mml:mn mathvariant="normal">33</mml:mn></mml:msub><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> of known
isotopic composition. The carbon isotopic composition of the reference
<inline-formula><mml:math id="M144" display="inline"><mml:mi>n</mml:mi></mml:math></inline-formula>-alkanes was determined off-line using a thermal conversion elemental
analyser (TCEA) (Thermo Fisher, Bremen, Germany) interfaced to the DELTA V
PLUS IRMS system via a Conflo III combustion interface (Thermo Fisher,
Bremen, Germany; Werner and Brand, 2001). The contribution of the methyl
carbon derived from the methanol after mild-alkaline hydrolysis and
methylation of the PLFAs to the FAME was removed by isotopic mass balance,
with <inline-formula><mml:math id="M145" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>C<inline-formula><mml:math id="M146" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">PLFA</mml:mi></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M147" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> [(<inline-formula><mml:math id="M148" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">PLFA</mml:mi></mml:msub><mml:mo>+</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula>) <inline-formula><mml:math id="M149" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> <inline-formula><mml:math id="M150" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>C<inline-formula><mml:math id="M151" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">FAME</mml:mi></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M152" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math id="M153" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>C<inline-formula><mml:math id="M154" display="inline"><mml:mrow><mml:msub><mml:mi/><mml:mi mathvariant="normal">MeOH</mml:mi></mml:msub><mml:mo>]</mml:mo><mml:mo>/</mml:mo><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">PLFA</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, where <inline-formula><mml:math id="M155" display="inline"><mml:mi>N</mml:mi></mml:math></inline-formula> is the number of carbon
atoms in the PLFA and <inline-formula><mml:math id="M156" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>C<inline-formula><mml:math id="M157" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">FAME</mml:mi></mml:msub></mml:math></inline-formula> stands for the measured
values of the methylated PLFAs (Kramer and Gleixner, 2006). The carbon
isotope composition of MeOH used for derivatization (<inline-formula><mml:math id="M158" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>C
value <inline-formula><mml:math id="M159" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> <inline-formula><mml:math id="M160" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>31.13 <inline-formula><mml:math id="M161" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.03 ‰) was determined off-line using a
thermal conversion elemental analyzer (TC/EA) (Thermo Fisher, Bremen,
Germany) interfaced to the DELTA V PLUS irMS system via a Conflo III
combustion interface (Thermo Fisher, Bremen, Germany).</p>
</sec>
</sec>
<sec id="Ch1.S3">
  <title>Results</title>
<sec id="Ch1.S3.SS1">
  <title>Groundwater physico-chemistry</title>
      <p>The deeper aquifer assemblage, HTL (wells H3.1, H4.1 and H5.1), had higher
mean concentration of O<inline-formula><mml:math id="M162" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> (3.7 <inline-formula><mml:math id="M163" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.0 mg L<inline-formula><mml:math id="M164" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> than the shallow
aquifer assemblage, HTU (wells H4.2, H4.3, H5.2 and H5.3). Groundwater
extracted from HTU wells were anoxic, with O<inline-formula><mml:math id="M165" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M166" display="inline"><mml:mo>&lt;</mml:mo></mml:math></inline-formula> 0.02 mg L<inline-formula><mml:math id="M167" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>
(Supplement Table S2 and Fig. 2), except for well H3.2 that had mean O<inline-formula><mml:math id="M168" display="inline"><mml:mrow><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mo>=</mml:mo><mml:mn mathvariant="normal">2.4</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.7</mml:mn></mml:mrow></mml:math></inline-formula> mg L<inline-formula><mml:math id="M169" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. No significant differences in the content of
DOC (mean <inline-formula><mml:math id="M170" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 2.3 <inline-formula><mml:math id="M171" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.0 mg L<inline-formula><mml:math id="M172" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> were
measured between the different aquifers. The HTL had higher mean
concentration of sulfate (183.5 <inline-formula><mml:math id="M173" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 110.9 mg L<inline-formula><mml:math id="M174" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> than the anoxic
HTU (76.4 <inline-formula><mml:math id="M175" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 3.1 mg L<inline-formula><mml:math id="M176" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula>. The highest concentrations of nitrate
were measured in the well H3.2 (30.0 <inline-formula><mml:math id="M177" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 3.3 mg L<inline-formula><mml:math id="M178" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> of the HTU.
Higher mean concentrations of total iron (Fe<inline-formula><mml:math id="M179" display="inline"><mml:mrow><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.1</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.08</mml:mn></mml:mrow></mml:math></inline-formula> mg L<inline-formula><mml:math id="M180" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula>, TIC (86.6 <inline-formula><mml:math id="M181" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 7.0 mg L<inline-formula><mml:math id="M182" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> and HCO<inline-formula><mml:math id="M183" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>
(4.69 <inline-formula><mml:math id="M184" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.07 mg L<inline-formula><mml:math id="M185" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula>, the latter measured as acid-neutralizing
capacity (Wisotzky, 2011), were found in the anoxic groundwater of the wells
H4.2 and H4.3 than of the wells H5.2 and H5.3, which had mean Fe<inline-formula><mml:math id="M186" display="inline"><mml:mrow><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.01</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.00</mml:mn></mml:mrow></mml:math></inline-formula> mg L<inline-formula><mml:math id="M187" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>, TIC <inline-formula><mml:math id="M188" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 75.6 <inline-formula><mml:math id="M189" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 5.4 mg L<inline-formula><mml:math id="M190" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> and
HCO<inline-formula><mml:math id="M191" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup><mml:mo>=</mml:mo><mml:mn mathvariant="normal">4.02</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.2</mml:mn></mml:mrow></mml:math></inline-formula> mg L<inline-formula><mml:math id="M192" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (Fig. 2). Inversely, mean
concentrations of total sulfur (S<inline-formula><mml:math id="M193" display="inline"><mml:mrow><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mn mathvariant="normal">26.1</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">4.9</mml:mn></mml:mrow></mml:math></inline-formula> mg L<inline-formula><mml:math id="M194" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula>, sulfate (76.7 <inline-formula><mml:math id="M195" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 14.8 mg L<inline-formula><mml:math id="M196" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> and ammonium
(0.62 <inline-formula><mml:math id="M197" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.16 mg L<inline-formula><mml:math id="M198" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> were higher in the anoxic groundwater of
the wells H5.2 and H5.3 than of the wells H4.2 and H4.3 that had mean
S<inline-formula><mml:math id="M199" display="inline"><mml:mrow><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mn mathvariant="normal">12.3</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.5</mml:mn></mml:mrow></mml:math></inline-formula> mg L<inline-formula><mml:math id="M200" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>, SO<inline-formula><mml:math id="M201" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup><mml:mo>=</mml:mo><mml:mn mathvariant="normal">37.6</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">2.0</mml:mn></mml:mrow></mml:math></inline-formula> mg L<inline-formula><mml:math id="M202" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> and NH<inline-formula><mml:math id="M203" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.13</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.06</mml:mn></mml:mrow></mml:math></inline-formula> mg L<inline-formula><mml:math id="M204" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (Fig. 2 and
Supplement Table S2).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2"><caption><p>Variations of the chemical compositions of the groundwaters relevant
for the discussion. HTL and HTU refer to the wells of the lower and upper
aquifer assemblage, respectively. Chemical compositions of the groundwater of
the wells H4.2–H4.3 and H5.2–H5.3 of the HTU are given separately for
comparison.</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://bg.copernicus.org/articles/14/2697/2017/bg-14-2697-2017-f02.png"/>

        </fig>

      <p>The PCA analyses, using the physico-chemical parameters of the groundwater,
separate the wells into three main groups (Fig. 3), with 73.6 % of the
variability explained by the first three principal components (PCs): PC1,
32.8 %; PC2, 23.8 %; and PC3, 16.9 %. The conductivity, redox
potential and the concentrations of Ca<inline-formula><mml:math id="M205" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula>, SO<inline-formula><mml:math id="M206" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula>, S<inline-formula><mml:math id="M207" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula>
and O<inline-formula><mml:math id="M208" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> positively correlated (response <inline-formula><mml:math id="M209" display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 0.5) with PC1 separating the
oxic to sub-oxic wells H5.1, H4.1, H3.1 and H3.2 from the anoxic wells
H4.2–H4.3 and H5.2–H5.3. The concentrations of
NH<inline-formula><mml:math id="M210" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>, K<inline-formula><mml:math id="M211" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula> and Mg<inline-formula><mml:math id="M212" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:math></inline-formula> inversely correlated (response <inline-formula><mml:math id="M213" display="inline"><mml:mo>&lt;</mml:mo></mml:math></inline-formula> 0.5)
with PC1, separating wells H5.2–H5.3 from the others. The Fe<inline-formula><mml:math id="M214" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula>,
TIC and HCO<inline-formula><mml:math id="M215" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> positively correlated along PC2 and mainly separated
the anoxic wells between location H4 and H5. Groundwaters in location H5 have
lower Fe<inline-formula><mml:math id="M216" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula>, TIC and HCO<inline-formula><mml:math id="M217" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> concentrations but higher
NH<inline-formula><mml:math id="M218" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>and K<inline-formula><mml:math id="M219" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula> concentrations, whereas higher Fe<inline-formula><mml:math id="M220" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula>, TIC
and HCO<inline-formula><mml:math id="M221" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> concentrations but lower NH<inline-formula><mml:math id="M222" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> and K<inline-formula><mml:math id="M223" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula>
concentrations were measured at location H4.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3"><caption><p>Principal component analysis (PCA) of the groundwater
physico-chemical compositions. Vectors indicate the steepest increase of the
respective physico-chemical parameter. The different wells are represented by
dots with different colours: blue for oxic groundwater, yellow for sub-oxic
groundwater, dark red and violet for anoxic groundwater richer in
Fe<inline-formula><mml:math id="M224" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula> and NH<inline-formula><mml:math id="M225" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>. Note the separation between the lower and
upper aquifer (HTL and HTU, respectively) and the anoxic wells at location
H4.2–H4.3 and H5.2–H5.3.</p></caption>
          <?xmltex \igopts{width=213.395669pt}?><graphic xlink:href="https://bg.copernicus.org/articles/14/2697/2017/bg-14-2697-2017-f03.pdf"/>

        </fig>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T3" specific-use="star"><caption><p>FunPLFA <inline-formula><mml:math id="M226" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> BactPLFA, G<inline-formula><mml:math id="M227" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math id="M228" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> G<inline-formula><mml:math id="M229" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula> and cy17:0 <inline-formula><mml:math id="M230" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> 16:1<inline-formula><mml:math id="M231" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>7c ratios averaged in the upper aquifer (HTU) and lower aquifer (HTL) as well as in the anoxic groundwater at locations H4 and H5.</p></caption><oasis:table frame="topbot"><?xmltex \begin{scaleboxenv}{.95}[.95]?><oasis:tgroup cols="13">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="right"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:colspec colnum="5" colname="col5" align="right"/>
     <oasis:colspec colnum="6" colname="col6" align="right"/>
     <oasis:colspec colnum="7" colname="col7" align="right"/>
     <oasis:colspec colnum="8" colname="col8" align="right"/>
     <oasis:colspec colnum="9" colname="col9" align="right"/>
     <oasis:colspec colnum="10" colname="col10" align="right"/>
     <oasis:colspec colnum="11" colname="col11" align="right"/>
     <oasis:colspec colnum="12" colname="col12" align="right"/>
     <oasis:colspec colnum="13" colname="col13" align="right"/>
     <oasis:thead>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2">FunPLFA</oasis:entry>  
         <oasis:entry colname="col3">SD</oasis:entry>  
         <oasis:entry colname="col4">G<inline-formula><mml:math id="M232" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula></oasis:entry>  
         <oasis:entry colname="col5">SD</oasis:entry>  
         <oasis:entry colname="col6">G<inline-formula><mml:math id="M233" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula></oasis:entry>  
         <oasis:entry colname="col7">SD</oasis:entry>  
         <oasis:entry colname="col8">FunPLFA <inline-formula><mml:math id="M234" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> BactPLFA</oasis:entry>  
         <oasis:entry colname="col9">SD</oasis:entry>  
         <oasis:entry colname="col10">G<inline-formula><mml:math id="M235" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula> <inline-formula><mml:math id="M236" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> G<inline-formula><mml:math id="M237" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula></oasis:entry>  
         <oasis:entry colname="col11">SD</oasis:entry>  
         <oasis:entry colname="col12">cy17:0 <inline-formula><mml:math id="M238" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> 16<inline-formula><mml:math id="M239" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>7c</oasis:entry>  
         <oasis:entry colname="col13">SD</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>  
         <oasis:entry colname="col1">HTL</oasis:entry>  
         <oasis:entry colname="col2">7.8</oasis:entry>  
         <oasis:entry colname="col3">3.3</oasis:entry>  
         <oasis:entry colname="col4">27.2</oasis:entry>  
         <oasis:entry colname="col5">7.1</oasis:entry>  
         <oasis:entry colname="col6">8.9</oasis:entry>  
         <oasis:entry colname="col7">2.6</oasis:entry>  
         <oasis:entry colname="col8">0.2</oasis:entry>  
         <oasis:entry colname="col9">0.1</oasis:entry>  
         <oasis:entry colname="col10">0.4</oasis:entry>  
         <oasis:entry colname="col11">0.2</oasis:entry>  
         <oasis:entry colname="col12">0.2</oasis:entry>  
         <oasis:entry colname="col13">0.1</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">HTU</oasis:entry>  
         <oasis:entry colname="col2">8.2</oasis:entry>  
         <oasis:entry colname="col3">9.2</oasis:entry>  
         <oasis:entry colname="col4">29.4</oasis:entry>  
         <oasis:entry colname="col5">8.0</oasis:entry>  
         <oasis:entry colname="col6">11.4</oasis:entry>  
         <oasis:entry colname="col7">4.4</oasis:entry>  
         <oasis:entry colname="col8">0.2</oasis:entry>  
         <oasis:entry colname="col9">0.2</oasis:entry>  
         <oasis:entry colname="col10">0.4</oasis:entry>  
         <oasis:entry colname="col11">0.2</oasis:entry>  
         <oasis:entry colname="col12">0.0</oasis:entry>  
         <oasis:entry colname="col13">0.0</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">H4.2–H4.3</oasis:entry>  
         <oasis:entry colname="col2">19.0</oasis:entry>  
         <oasis:entry colname="col3">7.8</oasis:entry>  
         <oasis:entry colname="col4">25.5</oasis:entry>  
         <oasis:entry colname="col5">4.5</oasis:entry>  
         <oasis:entry colname="col6">16.3</oasis:entry>  
         <oasis:entry colname="col7">1.5</oasis:entry>  
         <oasis:entry colname="col8">0.5</oasis:entry>  
         <oasis:entry colname="col9">0.2</oasis:entry>  
         <oasis:entry colname="col10">0.7</oasis:entry>  
         <oasis:entry colname="col11">0.1</oasis:entry>  
         <oasis:entry colname="col12">0.0</oasis:entry>  
         <oasis:entry colname="col13">0.0</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">H5.2–H5.3</oasis:entry>  
         <oasis:entry colname="col2">1.9</oasis:entry>  
         <oasis:entry colname="col3">2.0</oasis:entry>  
         <oasis:entry colname="col4">34.0</oasis:entry>  
         <oasis:entry colname="col5">8.4</oasis:entry>  
         <oasis:entry colname="col6">9.5</oasis:entry>  
         <oasis:entry colname="col7">3.2</oasis:entry>  
         <oasis:entry colname="col8">0.1</oasis:entry>  
         <oasis:entry colname="col9">0.1</oasis:entry>  
         <oasis:entry colname="col10">0.3</oasis:entry>  
         <oasis:entry colname="col11">0.1</oasis:entry>  
         <oasis:entry colname="col12">0.0</oasis:entry>  
         <oasis:entry colname="col13">0.0</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup><?xmltex \end{scaleboxenv}?></oasis:table></table-wrap>

<?xmltex \hack{\newpage}?>
</sec>
<sec id="Ch1.S3.SS2">
  <title>PLFA distribution and statistical analyses</title>
      <p>The 16:1<inline-formula><mml:math id="M240" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>7c (mean 22.2 <inline-formula><mml:math id="M241" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 8.9 %), 16:0 (mean
13.4 <inline-formula><mml:math id="M242" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2.3 %) and 18:1<inline-formula><mml:math id="M243" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>7c (mean 5.2 <inline-formula><mml:math id="M244" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2.6 %),
common in most bacteria, were the most abundant PLFAs in both aquifer
assemblages (Supplement Table S1). The PLFAs 10Me16:0 (mean
7.8 <inline-formula><mml:math id="M245" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 5.6 %), 17:1<inline-formula><mml:math id="M246" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>6c (mean 1.2 <inline-formula><mml:math id="M247" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.0 %) and
i17:1 (mean 0.8 <inline-formula><mml:math id="M248" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.7 %), derived from Deltaproteobacteria mainly
encompassing SRB, iron-reducing or iron-oxidizing bacteria, were dominant only
in the anoxic groundwater, whereas the 11Me16:0 (mean 4.2 <inline-formula><mml:math id="M249" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 4.7 %)
was found in high relative abundance in the oxic groundwaters. The [3]- and
[5]-ladderane PLFAs specific to anammox bacteria were found in the anoxic
wells H5.2 and H5.3 and the sub-oxic well H3.2 in a relative abundance of up
to 5.0 %. The highest fungal biomass, based on the FunPLFA ratios
(Table 3), was observed in the anoxic wells H4.2 and H4.3 (mean
19.0 <inline-formula><mml:math id="M250" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 7.8), whereas the lowest was observed in the anoxic wells H5.2 and H5.3 (mean
1.9 <inline-formula><mml:math id="M251" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2). The Gram-negative (G<inline-formula><mml:math id="M252" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>) bacteria were more abundant than
Gram-positive bacteria (G<inline-formula><mml:math id="M253" display="inline"><mml:mrow><mml:mo>+</mml:mo><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> in both HTU and HTL (Table 3: mean
G<inline-formula><mml:math id="M254" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula> <inline-formula><mml:math id="M255" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> G<inline-formula><mml:math id="M256" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> ratio <inline-formula><mml:math id="M257" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 0.4 <inline-formula><mml:math id="M258" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.2). The highest values of the
G<inline-formula><mml:math id="M259" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula> <inline-formula><mml:math id="M260" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> G<inline-formula><mml:math id="M261" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> ratios were in the anoxic wells H4.2 and H4.3 (mean
0.7 <inline-formula><mml:math id="M262" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.1).</p>
      <p>A PCA analysis explained 56.5 % of the PLFA variation. PC1 and PC2,
respectively explaining 29.1 and 15.9 % of overall variability (Fig. 4),
separated the wells into the same three groups evidenced by the PCA analysis
of the groundwater chemistry (Fig. 3). The wells of the HTU assemblage were
separated along PC1; wells from sites H4.2–H4.3 separated from those of the
sites H5.2–H5.3. Along PC2, the wells were separated between the oxic (wells
H3.1, H4.1 and H5.1), sub-oxic (well H3.2) and anoxic groundwaters (H4.2–H4.3 and H5.2–H.5.3). The RDA
analyses showed that O<inline-formula><mml:math id="M263" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, Fe<inline-formula><mml:math id="M264" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula> and NH<inline-formula><mml:math id="M265" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> concentrations
or O<inline-formula><mml:math id="M266" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, HCO<inline-formula><mml:math id="M267" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> and NH<inline-formula><mml:math id="M268" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> concentrations explained the
greatest proportion (39.9 %) of the PLFA variability (Fig. 5). Well
grouping obtained using the RDA analysis was consistent with the results of
the PCA. The first RDA axis (21.5 %) separated the anoxic wells of the
upper aquifer according to Fe<inline-formula><mml:math id="M269" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula> or HCO<inline-formula><mml:math id="M270" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> (wells H4.2–H4.3) and NH<inline-formula><mml:math id="M271" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> (wells H5.2–H5.3) concentration. The second
RDA axis (14.6 %) separated suboxic to oxic (mainly lower aquifer) from
anoxic groundwater (upper aquifer assemblage). In the following discussion,
the wells are separated according the PCA and RDA analyses into these three
main groups.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4"><caption><p>Principal component analysis (PCA) of PLFAs composition. The
different wells are represented by dots with different colours: blue for oxic
groundwater, yellow for sub-oxic or oxic groundwater, dark red and violet for
anoxic groundwater richer in Fe<inline-formula><mml:math id="M272" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula> and NH<inline-formula><mml:math id="M273" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>. Note the
separation between the lower and upper aquifer (HTL and HTU, respectively)
and the anoxic wells at locations H4.2–H4.3 and H5.2–H5.3.</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://bg.copernicus.org/articles/14/2697/2017/bg-14-2697-2017-f04.pdf"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5"><caption><p>Redundancy analysis (RDA) of PLFAs, used as species, and the most
significant environmental parameters O<inline-formula><mml:math id="M274" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, NH<inline-formula><mml:math id="M275" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> and
Fe<inline-formula><mml:math id="M276" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula> that explained 39.9 % of the variability. The different
wells are represented by dots with different colours: blue for oxic
groundwater, yellow for sub-oxic groundwater, dark red and violet for anoxic
groundwater richer in Fe<inline-formula><mml:math id="M277" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula> and NH<inline-formula><mml:math id="M278" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>.</p></caption>
          <?xmltex \igopts{width=193.47874pt}?><graphic xlink:href="https://bg.copernicus.org/articles/14/2697/2017/bg-14-2697-2017-f05.pdf"/>

        </fig>

      <?xmltex \floatpos{p}?><fig id="Ch1.F6" specific-use="star"><caption><p>Variation-partitioning <inline-formula><mml:math id="M279" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula>-value biplots showing the PLFAs
significantly correlated with the environmental
variables <bold>(a)</bold> O<inline-formula><mml:math id="M280" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, <bold>(b)</bold> Fe<inline-formula><mml:math id="M281" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula> and
<bold>(c)</bold> NH<inline-formula><mml:math id="M282" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>. Results of the significance test of the variation
partitioning are shown in the associated table. The PLFAs are represented by
arrows projecting from the origin. Concentration changes, between sampling
data of a particular PLFA, are significantly related to concentration changes
in the environmental variables, when the arrow tip of those PLFA is enclosed
within circles. The arrow tip is enclosed within the red circle for positive
correlation and inversely within the blue circle for negative correlation.</p></caption>
          <?xmltex \igopts{width=469.470472pt}?><graphic xlink:href="https://bg.copernicus.org/articles/14/2697/2017/bg-14-2697-2017-f06.pdf"/>

        </fig>

      <p>To identify the individual effects of O<inline-formula><mml:math id="M283" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, Fe<inline-formula><mml:math id="M284" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula> and
NH<inline-formula><mml:math id="M285" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> on the explained PLFA variation, we used variation partitioning
with conditional effects implemented in Canoco 5 (Heikkinen et al., 2004;
Roth et al., 2015). Because these environmental variables were the most
significant factors, their combined variation was set to explain 100 % of
total PLFA variation in each RDA plot. In our case, the following fractions explained the PLFA
distribution by effect of O<inline-formula><mml:math id="M286" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> alone: <inline-formula><mml:math id="M287" display="inline"><mml:mrow><mml:mi>a</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">19.7</mml:mn></mml:mrow></mml:math></inline-formula> %, effect of
NH<inline-formula><mml:math id="M288" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> alone; <inline-formula><mml:math id="M289" display="inline"><mml:mrow><mml:mi>b</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">22.0</mml:mn></mml:mrow></mml:math></inline-formula> %, effect of Fe<inline-formula><mml:math id="M290" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula> alone; <inline-formula><mml:math id="M291" display="inline"><mml:mrow><mml:mi>c</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">13.4</mml:mn></mml:mrow></mml:math></inline-formula> %, by combined effects of O<inline-formula><mml:math id="M292" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> and NH<inline-formula><mml:math id="M293" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>; <inline-formula><mml:math id="M294" display="inline"><mml:mrow><mml:mi>d</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">22.3</mml:mn></mml:mrow></mml:math></inline-formula> %, by combined effects of Fe<inline-formula><mml:math id="M295" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula> and NH<inline-formula><mml:math id="M296" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>; <inline-formula><mml:math id="M297" display="inline"><mml:mrow><mml:mi>e</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">29.2</mml:mn></mml:mrow></mml:math></inline-formula> %, by combined effect of O<inline-formula><mml:math id="M298" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> and Fe<inline-formula><mml:math id="M299" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula>; and <inline-formula><mml:math id="M300" display="inline"><mml:mrow><mml:mi>f</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">25.9</mml:mn></mml:mrow></mml:math></inline-formula> %. The fraction <inline-formula><mml:math id="M301" display="inline"><mml:mi>g</mml:mi></mml:math></inline-formula> (<inline-formula><mml:math id="M302" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>32.4 %) explained the combined effect
of the three environmental variables (Fig. 6). The PLFA
environmental-variable O<inline-formula><mml:math id="M303" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M304" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula>-plot (Fig. 6a) showed that the relative abundance of Me15:0,
16:1<inline-formula><mml:math id="M305" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>11c, cy17:0, 11Me16:0, 18:1, 22:5 and 22:6 increased
significantly with O<inline-formula><mml:math id="M306" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> concentration and the relative abundance of 10Me12:0,
<inline-formula><mml:math id="M307" display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula>13:0, <inline-formula><mml:math id="M308" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>15:0, 17:1 and [5]-ladderane decreased with O<inline-formula><mml:math id="M309" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>
concentration. The PLFA environmental-variable Fe<inline-formula><mml:math id="M310" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M311" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula>-values
biplot (Fig. 6b) showed that 10Me12:0, 17:1, 18:1<inline-formula><mml:math id="M312" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>9c, 18:1<inline-formula><mml:math id="M313" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>7c
and 12:0 relative
abundance increased with Fe<inline-formula><mml:math id="M314" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula> concentration, whereas 10Me16:0,
i17:1, [3]-ladderane and [5]-ladderane relative abundance decreased. Inversely, the PLFA
environmental-variable NH<inline-formula><mml:math id="M315" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M316" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula>-values biplot (Fig. 6c) showed that
10Me16:0, 17:1, [3]-ladderane and [5]-ladderane relative abundance increased with
NH<inline-formula><mml:math id="M317" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> concentration, whereas 10Me12:0, 12:0, 18:1<inline-formula><mml:math id="M318" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>9c,
18:1<inline-formula><mml:math id="M319" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>7c and 17:1 relative abundance decreased.</p>

<?xmltex \floatpos{p}?><table-wrap id="Ch1.T4" specific-use="star"><caption><p>PLFA <inline-formula><mml:math id="M320" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>C values averaged for the sampled month in the
different wells.</p></caption><oasis:table frame="topbot"><?xmltex \begin{scaleboxenv}{.95}[.95]?><oasis:tgroup cols="17">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="right"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:colspec colnum="5" colname="col5" align="right"/>
     <oasis:colspec colnum="6" colname="col6" align="right"/>
     <oasis:colspec colnum="7" colname="col7" align="right"/>
     <oasis:colspec colnum="8" colname="col8" align="right"/>
     <oasis:colspec colnum="9" colname="col9" align="right"/>
     <oasis:colspec colnum="10" colname="col10" align="right"/>
     <oasis:colspec colnum="11" colname="col11" align="right"/>
     <oasis:colspec colnum="12" colname="col12" align="right"/>
     <oasis:colspec colnum="13" colname="col13" align="right"/>
     <oasis:colspec colnum="14" colname="col14" align="right"/>
     <oasis:colspec colnum="15" colname="col15" align="right"/>
     <oasis:colspec colnum="16" colname="col16" align="right"/>
     <oasis:colspec colnum="17" colname="col17" align="right"/>
     <oasis:thead>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1">PLFA</oasis:entry>  
         <oasis:entry colname="col2">H3.2</oasis:entry>  
         <oasis:entry colname="col3">SD</oasis:entry>  
         <oasis:entry colname="col4">H4.2</oasis:entry>  
         <oasis:entry colname="col5">SD</oasis:entry>  
         <oasis:entry colname="col6">H4.3</oasis:entry>  
         <oasis:entry colname="col7">SD</oasis:entry>  
         <oasis:entry colname="col8">H5.2</oasis:entry>  
         <oasis:entry colname="col9">SD</oasis:entry>  
         <oasis:entry colname="col10">H5.3</oasis:entry>  
         <oasis:entry colname="col11">SD</oasis:entry>  
         <oasis:entry colname="col12">H3.1</oasis:entry>  
         <oasis:entry colname="col13">SD</oasis:entry>  
         <oasis:entry colname="col14">H4.1</oasis:entry>  
         <oasis:entry colname="col15">SD</oasis:entry>  
         <oasis:entry colname="col16">H5.1</oasis:entry>  
         <oasis:entry colname="col17">SD</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>  
         <oasis:entry colname="col1"><inline-formula><mml:math id="M321" display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula>13:0</oasis:entry>  
         <oasis:entry colname="col2"><inline-formula><mml:math id="M322" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>39.2</oasis:entry>  
         <oasis:entry colname="col3">3.5</oasis:entry>  
         <oasis:entry colname="col4"><inline-formula><mml:math id="M323" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>42.9</oasis:entry>  
         <oasis:entry colname="col5"/>  
         <oasis:entry colname="col6"><inline-formula><mml:math id="M324" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>37.7</oasis:entry>  
         <oasis:entry colname="col7">0.8</oasis:entry>  
         <oasis:entry colname="col8"><inline-formula><mml:math id="M325" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>53.6</oasis:entry>  
         <oasis:entry colname="col9">1.6</oasis:entry>  
         <oasis:entry colname="col10"><inline-formula><mml:math id="M326" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>51.2</oasis:entry>  
         <oasis:entry colname="col11">10.3</oasis:entry>  
         <oasis:entry colname="col12"><inline-formula><mml:math id="M327" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>38.8</oasis:entry>  
         <oasis:entry colname="col13"/>  
         <oasis:entry colname="col14"><inline-formula><mml:math id="M328" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>40.7</oasis:entry>  
         <oasis:entry colname="col15">1.8</oasis:entry>  
         <oasis:entry colname="col16"><inline-formula><mml:math id="M329" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>40.4</oasis:entry>  
         <oasis:entry colname="col17">3.4</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"><inline-formula><mml:math id="M330" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula>15:0</oasis:entry>  
         <oasis:entry colname="col2"><inline-formula><mml:math id="M331" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>40.3</oasis:entry>  
         <oasis:entry colname="col3">0.7</oasis:entry>  
         <oasis:entry colname="col4"><inline-formula><mml:math id="M332" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>40.8</oasis:entry>  
         <oasis:entry colname="col5"/>  
         <oasis:entry colname="col6"><inline-formula><mml:math id="M333" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>35.9</oasis:entry>  
         <oasis:entry colname="col7">0.3</oasis:entry>  
         <oasis:entry colname="col8"><inline-formula><mml:math id="M334" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>45.4</oasis:entry>  
         <oasis:entry colname="col9">1.4</oasis:entry>  
         <oasis:entry colname="col10"><inline-formula><mml:math id="M335" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>43.0</oasis:entry>  
         <oasis:entry colname="col11">2.8</oasis:entry>  
         <oasis:entry colname="col12"/>  
         <oasis:entry colname="col13"/>  
         <oasis:entry colname="col14"><inline-formula><mml:math id="M336" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>40.5</oasis:entry>  
         <oasis:entry colname="col15">0.8</oasis:entry>  
         <oasis:entry colname="col16"><inline-formula><mml:math id="M337" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>37.1</oasis:entry>  
         <oasis:entry colname="col17">1.5</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"><inline-formula><mml:math id="M338" display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula>15:0</oasis:entry>  
         <oasis:entry colname="col2"><inline-formula><mml:math id="M339" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>43.7</oasis:entry>  
         <oasis:entry colname="col3">0.0</oasis:entry>  
         <oasis:entry colname="col4"><inline-formula><mml:math id="M340" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>47.4</oasis:entry>  
         <oasis:entry colname="col5"/>  
         <oasis:entry colname="col6"><inline-formula><mml:math id="M341" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>36.3</oasis:entry>  
         <oasis:entry colname="col7">0.8</oasis:entry>  
         <oasis:entry colname="col8"><inline-formula><mml:math id="M342" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>55.0</oasis:entry>  
         <oasis:entry colname="col9">3.3</oasis:entry>  
         <oasis:entry colname="col10"><inline-formula><mml:math id="M343" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>56.8</oasis:entry>  
         <oasis:entry colname="col11">12.7</oasis:entry>  
         <oasis:entry colname="col12"/>  
         <oasis:entry colname="col13"/>  
         <oasis:entry colname="col14"><inline-formula><mml:math id="M344" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>46.0</oasis:entry>  
         <oasis:entry colname="col15">0.8</oasis:entry>  
         <oasis:entry colname="col16"><inline-formula><mml:math id="M345" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>42.1</oasis:entry>  
         <oasis:entry colname="col17">2.5</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">16:17<inline-formula><mml:math id="M346" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>c</oasis:entry>  
         <oasis:entry colname="col2"><inline-formula><mml:math id="M347" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>47.4</oasis:entry>  
         <oasis:entry colname="col3">0.6</oasis:entry>  
         <oasis:entry colname="col4"><inline-formula><mml:math id="M348" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>37.9</oasis:entry>  
         <oasis:entry colname="col5">1.6</oasis:entry>  
         <oasis:entry colname="col6"><inline-formula><mml:math id="M349" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>36.0</oasis:entry>  
         <oasis:entry colname="col7">2.3</oasis:entry>  
         <oasis:entry colname="col8"><inline-formula><mml:math id="M350" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>44.9</oasis:entry>  
         <oasis:entry colname="col9">2.3</oasis:entry>  
         <oasis:entry colname="col10"><inline-formula><mml:math id="M351" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>44.3</oasis:entry>  
         <oasis:entry colname="col11">1.3</oasis:entry>  
         <oasis:entry colname="col12"><inline-formula><mml:math id="M352" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>42.1</oasis:entry>  
         <oasis:entry colname="col13"/>  
         <oasis:entry colname="col14"><inline-formula><mml:math id="M353" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>40.0</oasis:entry>  
         <oasis:entry colname="col15">3.8</oasis:entry>  
         <oasis:entry colname="col16"><inline-formula><mml:math id="M354" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>40.2</oasis:entry>  
         <oasis:entry colname="col17">2.1</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">16:1<inline-formula><mml:math id="M355" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>11c</oasis:entry>  
         <oasis:entry colname="col2"><inline-formula><mml:math id="M356" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>44.4</oasis:entry>  
         <oasis:entry colname="col3">2.4</oasis:entry>  
         <oasis:entry colname="col4"><inline-formula><mml:math id="M357" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>40.5</oasis:entry>  
         <oasis:entry colname="col5">1.8</oasis:entry>  
         <oasis:entry colname="col6"><inline-formula><mml:math id="M358" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>36.0</oasis:entry>  
         <oasis:entry colname="col7">4.0</oasis:entry>  
         <oasis:entry colname="col8"><inline-formula><mml:math id="M359" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>36.0</oasis:entry>  
         <oasis:entry colname="col9">1.7</oasis:entry>  
         <oasis:entry colname="col10"><inline-formula><mml:math id="M360" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>34.6</oasis:entry>  
         <oasis:entry colname="col11">4.1</oasis:entry>  
         <oasis:entry colname="col12"><inline-formula><mml:math id="M361" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>39.4</oasis:entry>  
         <oasis:entry colname="col13"/>  
         <oasis:entry colname="col14"><inline-formula><mml:math id="M362" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>27.8</oasis:entry>  
         <oasis:entry colname="col15">2.4</oasis:entry>  
         <oasis:entry colname="col16"><inline-formula><mml:math id="M363" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>28.1</oasis:entry>  
         <oasis:entry colname="col17">0.7</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">C16:0</oasis:entry>  
         <oasis:entry colname="col2"><inline-formula><mml:math id="M364" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>45.2</oasis:entry>  
         <oasis:entry colname="col3">3.0</oasis:entry>  
         <oasis:entry colname="col4"><inline-formula><mml:math id="M365" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>34.8</oasis:entry>  
         <oasis:entry colname="col5">2.6</oasis:entry>  
         <oasis:entry colname="col6"><inline-formula><mml:math id="M366" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>34.4</oasis:entry>  
         <oasis:entry colname="col7">1.2</oasis:entry>  
         <oasis:entry colname="col8"><inline-formula><mml:math id="M367" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>45.3</oasis:entry>  
         <oasis:entry colname="col9">2.4</oasis:entry>  
         <oasis:entry colname="col10"><inline-formula><mml:math id="M368" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>42.9</oasis:entry>  
         <oasis:entry colname="col11">3.4</oasis:entry>  
         <oasis:entry colname="col12"><inline-formula><mml:math id="M369" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>36.4</oasis:entry>  
         <oasis:entry colname="col13"/>  
         <oasis:entry colname="col14"><inline-formula><mml:math id="M370" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>34.3</oasis:entry>  
         <oasis:entry colname="col15">1.0</oasis:entry>  
         <oasis:entry colname="col16"><inline-formula><mml:math id="M371" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>35.4</oasis:entry>  
         <oasis:entry colname="col17">2.2</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">10Me16:0</oasis:entry>  
         <oasis:entry colname="col2"><inline-formula><mml:math id="M372" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>49.9</oasis:entry>  
         <oasis:entry colname="col3">0.9</oasis:entry>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5"/>  
         <oasis:entry colname="col6"><inline-formula><mml:math id="M373" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>42.7</oasis:entry>  
         <oasis:entry colname="col7"/>  
         <oasis:entry colname="col8"><inline-formula><mml:math id="M374" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>57.6</oasis:entry>  
         <oasis:entry colname="col9">3.3</oasis:entry>  
         <oasis:entry colname="col10"><inline-formula><mml:math id="M375" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>54.6</oasis:entry>  
         <oasis:entry colname="col11">7.4</oasis:entry>  
         <oasis:entry colname="col12"><inline-formula><mml:math id="M376" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>42.2</oasis:entry>  
         <oasis:entry colname="col13"/>  
         <oasis:entry colname="col14"/>  
         <oasis:entry colname="col15"/>  
         <oasis:entry colname="col16"><inline-formula><mml:math id="M377" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>40.0</oasis:entry>  
         <oasis:entry colname="col17">2.2</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">11Me16:0</oasis:entry>  
         <oasis:entry colname="col2"><inline-formula><mml:math id="M378" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>30.5</oasis:entry>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5"/>  
         <oasis:entry colname="col6"/>  
         <oasis:entry colname="col7"/>  
         <oasis:entry colname="col8"/>  
         <oasis:entry colname="col9"/>  
         <oasis:entry colname="col10"/>  
         <oasis:entry colname="col11"/>  
         <oasis:entry colname="col12"><inline-formula><mml:math id="M379" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>28.3</oasis:entry>  
         <oasis:entry colname="col13"/>  
         <oasis:entry colname="col14"><inline-formula><mml:math id="M380" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>26.5</oasis:entry>  
         <oasis:entry colname="col15">0.6</oasis:entry>  
         <oasis:entry colname="col16"><inline-formula><mml:math id="M381" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>25.7</oasis:entry>  
         <oasis:entry colname="col17">2.5</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">cy17:0</oasis:entry>  
         <oasis:entry colname="col2"/>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5"/>  
         <oasis:entry colname="col6"/>  
         <oasis:entry colname="col7"/>  
         <oasis:entry colname="col8"/>  
         <oasis:entry colname="col9"/>  
         <oasis:entry colname="col10"/>  
         <oasis:entry colname="col11"/>  
         <oasis:entry colname="col12"><inline-formula><mml:math id="M382" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>33.2</oasis:entry>  
         <oasis:entry colname="col13"/>  
         <oasis:entry colname="col14"/>  
         <oasis:entry colname="col15"/>  
         <oasis:entry colname="col16"><inline-formula><mml:math id="M383" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>26.3</oasis:entry>  
         <oasis:entry colname="col17">1.6</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">i17:1</oasis:entry>  
         <oasis:entry colname="col2"><inline-formula><mml:math id="M384" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>45.1</oasis:entry>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5"/>  
         <oasis:entry colname="col6"/>  
         <oasis:entry colname="col7"/>  
         <oasis:entry colname="col8"><inline-formula><mml:math id="M385" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>42.6</oasis:entry>  
         <oasis:entry colname="col9">2.0</oasis:entry>  
         <oasis:entry colname="col10"><inline-formula><mml:math id="M386" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>46.1</oasis:entry>  
         <oasis:entry colname="col11"/>  
         <oasis:entry colname="col12"/>  
         <oasis:entry colname="col13"/>  
         <oasis:entry colname="col14"/>  
         <oasis:entry colname="col15"/>  
         <oasis:entry colname="col16"/>  
         <oasis:entry colname="col17"/>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">18:1<inline-formula><mml:math id="M387" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>9c</oasis:entry>  
         <oasis:entry colname="col2"><inline-formula><mml:math id="M388" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>34.0</oasis:entry>  
         <oasis:entry colname="col3">0.5</oasis:entry>  
         <oasis:entry colname="col4"><inline-formula><mml:math id="M389" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>30.2</oasis:entry>  
         <oasis:entry colname="col5">0.1</oasis:entry>  
         <oasis:entry colname="col6"><inline-formula><mml:math id="M390" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>30.9</oasis:entry>  
         <oasis:entry colname="col7">3.5</oasis:entry>  
         <oasis:entry colname="col8"><inline-formula><mml:math id="M391" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>36.7</oasis:entry>  
         <oasis:entry colname="col9">1.8</oasis:entry>  
         <oasis:entry colname="col10"><inline-formula><mml:math id="M392" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>33.4</oasis:entry>  
         <oasis:entry colname="col11">0.0</oasis:entry>  
         <oasis:entry colname="col12"><inline-formula><mml:math id="M393" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>32.1</oasis:entry>  
         <oasis:entry colname="col13"/>  
         <oasis:entry colname="col14"><inline-formula><mml:math id="M394" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>31.4</oasis:entry>  
         <oasis:entry colname="col15">0.0</oasis:entry>  
         <oasis:entry colname="col16"><inline-formula><mml:math id="M395" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>31.0</oasis:entry>  
         <oasis:entry colname="col17">1.4</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">18:1<inline-formula><mml:math id="M396" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>7c</oasis:entry>  
         <oasis:entry colname="col2"><inline-formula><mml:math id="M397" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>42.5</oasis:entry>  
         <oasis:entry colname="col3">0.3</oasis:entry>  
         <oasis:entry colname="col4"><inline-formula><mml:math id="M398" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>32.5</oasis:entry>  
         <oasis:entry colname="col5">0.3</oasis:entry>  
         <oasis:entry colname="col6"><inline-formula><mml:math id="M399" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>32.2</oasis:entry>  
         <oasis:entry colname="col7">1.8</oasis:entry>  
         <oasis:entry colname="col8"><inline-formula><mml:math id="M400" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>39.6</oasis:entry>  
         <oasis:entry colname="col9">2.3</oasis:entry>  
         <oasis:entry colname="col10"><inline-formula><mml:math id="M401" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>40.2</oasis:entry>  
         <oasis:entry colname="col11">2.1</oasis:entry>  
         <oasis:entry colname="col12"><inline-formula><mml:math id="M402" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>32.4</oasis:entry>  
         <oasis:entry colname="col13"/>  
         <oasis:entry colname="col14"><inline-formula><mml:math id="M403" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>34.9</oasis:entry>  
         <oasis:entry colname="col15">2.5</oasis:entry>  
         <oasis:entry colname="col16"><inline-formula><mml:math id="M404" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>34.6</oasis:entry>  
         <oasis:entry colname="col17">1.2</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">18:1<inline-formula><mml:math id="M405" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>5c</oasis:entry>  
         <oasis:entry colname="col2"/>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4"><inline-formula><mml:math id="M406" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>33.5</oasis:entry>  
         <oasis:entry colname="col5"/>  
         <oasis:entry colname="col6"><inline-formula><mml:math id="M407" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>30.0</oasis:entry>  
         <oasis:entry colname="col7"/>  
         <oasis:entry colname="col8"/>  
         <oasis:entry colname="col9"/>  
         <oasis:entry colname="col10"><inline-formula><mml:math id="M408" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>31.7</oasis:entry>  
         <oasis:entry colname="col11"/>  
         <oasis:entry colname="col12"><inline-formula><mml:math id="M409" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>35.1</oasis:entry>  
         <oasis:entry colname="col13"/>  
         <oasis:entry colname="col14"><inline-formula><mml:math id="M410" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>31.6</oasis:entry>  
         <oasis:entry colname="col15"/>  
         <oasis:entry colname="col16"/>  
         <oasis:entry colname="col17"/>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">18:0</oasis:entry>  
         <oasis:entry colname="col2"><inline-formula><mml:math id="M411" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>35.5</oasis:entry>  
         <oasis:entry colname="col3">4.4</oasis:entry>  
         <oasis:entry colname="col4"><inline-formula><mml:math id="M412" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>42.1</oasis:entry>  
         <oasis:entry colname="col5">1.0</oasis:entry>  
         <oasis:entry colname="col6"><inline-formula><mml:math id="M413" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>36.7</oasis:entry>  
         <oasis:entry colname="col7">1.3</oasis:entry>  
         <oasis:entry colname="col8"><inline-formula><mml:math id="M414" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>36.1</oasis:entry>  
         <oasis:entry colname="col9"/>  
         <oasis:entry colname="col10"><inline-formula><mml:math id="M415" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>33.5</oasis:entry>  
         <oasis:entry colname="col11"/>  
         <oasis:entry colname="col12"><inline-formula><mml:math id="M416" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>32.9</oasis:entry>  
         <oasis:entry colname="col13"/>  
         <oasis:entry colname="col14"><inline-formula><mml:math id="M417" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>32.9</oasis:entry>  
         <oasis:entry colname="col15"/>  
         <oasis:entry colname="col16"><inline-formula><mml:math id="M418" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>31.5</oasis:entry>  
         <oasis:entry colname="col17">1.7</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">cy19:0</oasis:entry>  
         <oasis:entry colname="col2"><inline-formula><mml:math id="M419" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>45.2</oasis:entry>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5"/>  
         <oasis:entry colname="col6"/>  
         <oasis:entry colname="col7"/>  
         <oasis:entry colname="col8"/>  
         <oasis:entry colname="col9"/>  
         <oasis:entry colname="col10"/>  
         <oasis:entry colname="col11"/>  
         <oasis:entry colname="col12"/>  
         <oasis:entry colname="col13"/>  
         <oasis:entry colname="col14"/>  
         <oasis:entry colname="col15"/>  
         <oasis:entry colname="col16"/>  
         <oasis:entry colname="col17"/>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">20:4</oasis:entry>  
         <oasis:entry colname="col2"><inline-formula><mml:math id="M420" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>42.3</oasis:entry>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5"/>  
         <oasis:entry colname="col6"/>  
         <oasis:entry colname="col7"/>  
         <oasis:entry colname="col8"/>  
         <oasis:entry colname="col9"/>  
         <oasis:entry colname="col10"/>  
         <oasis:entry colname="col11"/>  
         <oasis:entry colname="col12"/>  
         <oasis:entry colname="col13"/>  
         <oasis:entry colname="col14"><inline-formula><mml:math id="M421" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>33.1</oasis:entry>  
         <oasis:entry colname="col15">1.0</oasis:entry>  
         <oasis:entry colname="col16"><inline-formula><mml:math id="M422" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>34.7</oasis:entry>  
         <oasis:entry colname="col17">0.9</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">20:5</oasis:entry>  
         <oasis:entry colname="col2"><inline-formula><mml:math id="M423" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>41.0</oasis:entry>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5"/>  
         <oasis:entry colname="col6"/>  
         <oasis:entry colname="col7"/>  
         <oasis:entry colname="col8"/>  
         <oasis:entry colname="col9"/>  
         <oasis:entry colname="col10"/>  
         <oasis:entry colname="col11"/>  
         <oasis:entry colname="col12"/>  
         <oasis:entry colname="col13"/>  
         <oasis:entry colname="col14"><inline-formula><mml:math id="M424" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>33.4</oasis:entry>  
         <oasis:entry colname="col15">0.0</oasis:entry>  
         <oasis:entry colname="col16"/>  
         <oasis:entry colname="col17"/>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">[3]-lad</oasis:entry>  
         <oasis:entry colname="col2"><inline-formula><mml:math id="M425" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>62.9</oasis:entry>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5"/>  
         <oasis:entry colname="col6"/>  
         <oasis:entry colname="col7"/>  
         <oasis:entry colname="col8"><inline-formula><mml:math id="M426" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>64.0</oasis:entry>  
         <oasis:entry colname="col9">0.3</oasis:entry>  
         <oasis:entry colname="col10"><inline-formula><mml:math id="M427" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>63.7</oasis:entry>  
         <oasis:entry colname="col11">0.8</oasis:entry>  
         <oasis:entry colname="col12"/>  
         <oasis:entry colname="col13"/>  
         <oasis:entry colname="col14"/>  
         <oasis:entry colname="col15"/>  
         <oasis:entry colname="col16"/>  
         <oasis:entry colname="col17"/>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">[5]-lad</oasis:entry>  
         <oasis:entry colname="col2"><inline-formula><mml:math id="M428" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>68.8</oasis:entry>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5"/>  
         <oasis:entry colname="col6"/>  
         <oasis:entry colname="col7"/>  
         <oasis:entry colname="col8"><inline-formula><mml:math id="M429" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>67.0</oasis:entry>  
         <oasis:entry colname="col9">0.9</oasis:entry>  
         <oasis:entry colname="col10"><inline-formula><mml:math id="M430" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>67.7</oasis:entry>  
         <oasis:entry colname="col11">1.5</oasis:entry>  
         <oasis:entry colname="col12"/>  
         <oasis:entry colname="col13"/>  
         <oasis:entry colname="col14"/>  
         <oasis:entry colname="col15"/>  
         <oasis:entry colname="col16"/>  
         <oasis:entry colname="col17"/>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">mean</oasis:entry>  
         <oasis:entry colname="col2"><inline-formula><mml:math id="M431" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>44.6</oasis:entry>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4"><inline-formula><mml:math id="M432" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>38.3</oasis:entry>  
         <oasis:entry colname="col5">1.2</oasis:entry>  
         <oasis:entry colname="col6"><inline-formula><mml:math id="M433" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>35.4</oasis:entry>  
         <oasis:entry colname="col7"/>  
         <oasis:entry colname="col8"><inline-formula><mml:math id="M434" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>48.0</oasis:entry>  
         <oasis:entry colname="col9"/>  
         <oasis:entry colname="col10"><inline-formula><mml:math id="M435" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>46.0</oasis:entry>  
         <oasis:entry colname="col11"/>  
         <oasis:entry colname="col12"><inline-formula><mml:math id="M436" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>35.7</oasis:entry>  
         <oasis:entry colname="col13"/>  
         <oasis:entry colname="col14"><inline-formula><mml:math id="M437" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>34.9</oasis:entry>  
         <oasis:entry colname="col15"/>  
         <oasis:entry colname="col16"><inline-formula><mml:math id="M438" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>34.4</oasis:entry>  
         <oasis:entry colname="col17"/>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">SD</oasis:entry>  
         <oasis:entry colname="col2">9.4</oasis:entry>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4">5.4</oasis:entry>  
         <oasis:entry colname="col5">1.0</oasis:entry>  
         <oasis:entry colname="col6">3.5</oasis:entry>  
         <oasis:entry colname="col7"/>  
         <oasis:entry colname="col8">10.5</oasis:entry>  
         <oasis:entry colname="col9"/>  
         <oasis:entry colname="col10">11.4</oasis:entry>  
         <oasis:entry colname="col11"/>  
         <oasis:entry colname="col12">4.5</oasis:entry>  
         <oasis:entry colname="col13"/>  
         <oasis:entry colname="col14">5.5</oasis:entry>  
         <oasis:entry colname="col15"/>  
         <oasis:entry colname="col16">5.5</oasis:entry>  
         <oasis:entry colname="col17"/>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup><?xmltex \end{scaleboxenv}?></oasis:table></table-wrap>

</sec>
<sec id="Ch1.S3.SS3">
  <?xmltex \opttitle{PLFA $\delta^{{13}}$C values}?><title>PLFA <inline-formula><mml:math id="M439" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>C values</title>
      <p>The PLFA <inline-formula><mml:math id="M440" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>C values for individual compounds ranged from <inline-formula><mml:math id="M441" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>26 to
<inline-formula><mml:math id="M442" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>68.8 ‰ (Supplement Table S3, Fig. 7 and
Table 4). The most negative mean <inline-formula><mml:math id="M443" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>C
values were found in the anoxic groundwater from locations H5.2 and H5.3
(<inline-formula><mml:math id="M444" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>48.0 <inline-formula><mml:math id="M445" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 10.5 ‰ and <inline-formula><mml:math id="M446" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>45.9 <inline-formula><mml:math id="M447" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 11.7 ‰,
respectively) and in the suboxic groundwater at the location H3.2
(<inline-formula><mml:math id="M448" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>45.4 <inline-formula><mml:math id="M449" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 9.0 ‰) and coincided with the presence of the [5]-
and [3]-ladderane. In those wells, the <inline-formula><mml:math id="M450" display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula>13:0
(<inline-formula><mml:math id="M451" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>52.4 <inline-formula><mml:math id="M452" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2.0 ‰), <inline-formula><mml:math id="M453" display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula>15:0 (<inline-formula><mml:math id="M454" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>55.6 <inline-formula><mml:math id="M455" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2.0 ‰),
10Me16:0 (<inline-formula><mml:math id="M456" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>56.1 <inline-formula><mml:math id="M457" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2.1 ‰) and i17:1
(<inline-formula><mml:math id="M458" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>44.3 <inline-formula><mml:math id="M459" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2.0 ‰) were slightly <inline-formula><mml:math id="M460" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:math></inline-formula>C-enriched compared to
both [5]- and [3]-ladderane (<inline-formula><mml:math id="M461" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>65.6 <inline-formula><mml:math id="M462" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2.0 ‰). More positive
mean PLFA <inline-formula><mml:math id="M463" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>C values were measured in the anoxic wells H4.2 and
H4.3 (<inline-formula><mml:math id="M464" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>36.8 <inline-formula><mml:math id="M465" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2.1 ‰) and in the oxic wells H5.1, H4.1 and
H3.1 (<inline-formula><mml:math id="M466" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>35.3 <inline-formula><mml:math id="M467" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.1 ‰). In those wells, the <inline-formula><mml:math id="M468" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>C
values of the i13:0, <inline-formula><mml:math id="M469" display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula>15:0 and 10Me16:0 were in the same range as the other
PLFAs (Fig. 7). The most positive <inline-formula><mml:math id="M470" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>C values were measured for
16:1<inline-formula><mml:math id="M471" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>11c and 11Me16:0 in the oxic wells H5.1 and H4.1 (mean
<inline-formula><mml:math id="M472" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>28.2 <inline-formula><mml:math id="M473" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2.5 ‰) and for 18:1<inline-formula><mml:math id="M474" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>9c (mean
<inline-formula><mml:math id="M475" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>30.2 <inline-formula><mml:math id="M476" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 2.3 ‰) in the anoxic wells H4.2 and H4.3.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F7" specific-use="star"><caption><p>PLFA <inline-formula><mml:math id="M477" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>C values averaged in the different wells for June,
September and December. The dotted and full lines represent the
<inline-formula><mml:math id="M478" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>C values of 11Me16:0 and ladderanes associated with nitrite-oxidizing bacteria (e.g. <italic>Nitrospira moscoviensis</italic>) and anammox
bacteria, respectively.</p></caption>
          <?xmltex \igopts{width=426.791339pt}?><graphic xlink:href="https://bg.copernicus.org/articles/14/2697/2017/bg-14-2697-2017-f07.pdf"/>

        </fig>

</sec>
<sec id="Ch1.S3.SS4">
  <title>Bacterial community composition based on 16S rRNA gene sequences</title>
      <p>Based on Illumina sequencing of DNA-based 16S rRNA gene amplicons, bacterial
communities were largely dominated by members of the phylum Nitrospirae and
of Candidate Division OD1, followed by Delta- and Betaproteobacteria,
Planctomycetes, and Alpha- and Gammaproteobacteria (Fig. 8a). Members of the
Nitrospirae were especially abundant in the groundwater of the anoxic wells
H5.2 and H5.3 as well as the oxic wells H4.1 and H5.1, while this phylum only
contributed a minor fraction to the groundwater of the anoxic wells H4.2 and
H4.3 and the oxic wells H3.1 and H3.2 (Fig. 8a). In addition, we performed
sequencing of 16S rRNA amplicons derived from the extracted RNA to get
insight into which taxonomic groups harbour protein synthesis potential, as
proposed by Blazewicz et al. (2013). RNA-based community analysis targeting
16S rRNA sequences has traditionally been used as an approximation of the
currently active fraction of the microbial community. However, this
interpretation is critical since many cells may retain high ribosome contents
even in a dormant state (Filion et al., 2009; Sukenik et al., 2012), and thus
rRNA content of cells does not necessarily indicate current metabolic
activity, especially in low-nutrient environments such as groundwater
(reviewed in Blazewicz et al., 2013). Here, we used this approach to
investigate whether key microbial groups identified by PLFA-based analysis
were supported to be metabolically active or have the potential to resume
metabolic activities based on the detection of the corresponding 16S rRNA
gene sequences on the RNA level. In general, members of the Candidate
Division OD1 formed only a minor part of the community obtained by RNA-based
amplicon sequencing, while members of the phyla Nitrospirae, Planctomycetes
and Proteobacteria showed the largest relative abundances (Fig. 8b). Members
of the phylum Nitrospirae were especially highly represented in the RNA-based
analyses of wells H3.2, H4.1, H5.2 and H5.3. Among the Proteobacteria,
Deltaproteobacteria were more frequently represented in the RNA-based
analysis of communities of wells H3.1, H3.2, H5.2 and H5.3, while
Alphaproteobacteria showed a higher relative abundance in the groundwater of
wells H4.2, H4.3 and H5.1 (Fig. 8b).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F8"><caption><p>Taxonomic classification (phylum level) of the bacterial communities
in the groundwater of the eight different wells from the upper aquifer
assemblages (HTU) or the lower aquifer (HTL). <bold>(a)</bold> Bacterial
communities based on sequencing of 16S rRNA genes from extracted genomic DNA.
<bold>(b)</bold> Bacterial communities based on sequencing of RNA-derived
16S rRNA amplicons.</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://bg.copernicus.org/articles/14/2697/2017/bg-14-2697-2017-f08.pdf"/>

        </fig>

      <p>Bacterial phyla and classes may harbour organisms with a high diversity of
different metabolisms. Therefore, as some source-specific PLFAs displayed
strong relationships with the environmental variables O<inline-formula><mml:math id="M479" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, NH<inline-formula><mml:math id="M480" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>
and Fe<inline-formula><mml:math id="M481" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula>, we specifically focused on groups potentially involved
in iron oxidation and reduction, sulfate reduction, anammox, and nitrite
oxidation. Here, relative fractions of reads assigned to bacterial genera
known to be involved in either of these processes were summed up to get an
estimation of the potential for these processes within the microbial
community with both DNA- and RNA-based analyses. On the level of DNA-based
sequencing, bacteria involved in iron oxidation accounted for 0.25 to
6.2 % of the sequence reads across sites (Fig. 9a), while they accounted
for 0.24 to 2.8 % on the level of the RNA-based analyses with the highest
relative fraction of bacteria potentially involved in iron oxidation at wells
H5.1 and H5.3 (Fig. 9b). Differences across sites and aquifers were more
pronounced for bacteria involved in iron reduction, which were accounted for
by 0.16 to 3.7 % of the sequence reads on the DNA level but for 0.15 to
20.4 % on the RNA level, with the highest number of sequence reads
affiliated with known iron reducers in the groundwater of well H4.3
(Fig. 9b). Bacteria related to the genera <italic>Acidiferrobacter</italic>,
<italic>Gallionella</italic> and <italic>Sideroxydans</italic> were the most frequent genera
among the known iron oxidizers, while members of the genera
<italic>Albidiferax</italic> and <italic>Ferribacterium</italic> dominated the iron-reducing
groups. Bacterial groups potentially involved in sulfur reduction included
the genera <italic>Desulfacinum</italic>, <italic>Desulfovibrio</italic>,
<italic>Desulfosporosinus</italic> and <italic>Desulfatiferula</italic> as the most frequent
groups and accounted for 0.2 to 2.8 % of the sequence reads on the DNA
level and 0.4 to 10.4 % on the RNA level, with the maximum in the anoxic
well H4.2 (Fig. 9). Anammox bacteria mostly represented by the Candidatus
genera <italic>Brocadia</italic> and <italic>Kuenenia</italic> accounted for 0.6 to 3.0 %
of the sequence reads on the DNA level and for 1.1 to 16.8 % on the RNA
level, with the highest fractions in the groundwater of the wells H3.1, H5.1,
H5.2 and H5.3 (Fig. 9). Finally, we observed large fractions of potential
nitrite oxidizers mostly related to the genus <italic>Nitrospira</italic>, with the
vast majority of the <italic>Nitrospira</italic>-affiliated reads especially in the
lower aquifer assemblage showing a high sequence similarity to the 16S rRNA
gene sequence of <italic>Nitrospira moscoviensis</italic> (96–99 %). Moreover,
reads associated with the genus <italic>Nitrospira</italic> may also include
potential comammox organisms (Pinto et al., 2016). Relative fractions of
sequence reads affiliated with this genus on the DNA and RNA level were
highest in the oxic groundwater of the well H4.1 and lowest in the anoxic
groundwater of wells H4.2 and H5.2 (Fig. 9). Since nitrifiers such as
<italic>Nitrospira</italic> are known to retain a high ribosome content even if cells
are not active (Morgenroth et al., 2000), these results do not necessarily
indicate high nitrite oxidation activity at the time point of sampling but
point to nitrite oxidizers forming a large fraction of the microbial
community with protein synthesis potential.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F9"><caption><p>Fractions of sequence reads affiliated with iron oxidizing or iron
reducing bacteria, sulfate-reducing bacteria, anammox bacteria, and nitrite
oxidizers (<italic>Nitrospira moscoviensis</italic>-related and others) within the
bacterial community <bold>(a)</bold> DNA-based analysis, <bold>(b)</bold> RNA-based
analysis. Only those sequence reads were considered which were unambiguously
classified to described taxa on the genus level.</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://bg.copernicus.org/articles/14/2697/2017/bg-14-2697-2017-f09.pdf"/>

        </fig>

</sec>
</sec>
<sec id="Ch1.S4">
  <title>Discussion</title>
<sec id="Ch1.S4.SS1">
  <title>PLFA distribution</title>
      <p>The PCA of PLFAs indicated that the oxic, suboxic and anoxic groundwaters had
distinct bacterial communities, with the anoxic groundwater additionally
differentiated into two distinct bacterial communities (Fig. 4). Of the
environmental variables tested, the variation partitioning showed that
NH<inline-formula><mml:math id="M482" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>, O<inline-formula><mml:math id="M483" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> and Fe<inline-formula><mml:math id="M484" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula> concentration explained 22.0, 19.7
and 13.4 % of the PLFA variations, respectively (Fig. 6), and
differentiated between those three bacterial communities. Variation partitioning
analyses revealed, along those environmental variables, clusters of covarying
PLFAs that may originate from the same functional group of organisms or
closely affiliated organisms that react similarly to certain environmental
conditions. While the ladderanes are unequivocally attributed to anammox
bacteria (Sinninghe Damsté et al., 2002, 2005), the other PLFAs are not
exclusive to a phylogenetic or functional microbial group, which complicates
their use in understanding the role of microbes in environments. The <inline-formula><mml:math id="M485" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula>-value
biplots of variation partitioning analyses evidenced the PLFAs that
significantly correlated with the environmental variables O<inline-formula><mml:math id="M486" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> (Fig. 6a),
Fe<inline-formula><mml:math id="M487" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula> (Fig. 6b) and NH<inline-formula><mml:math id="M488" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> (Fig. 6c), and provided better
insights into the functional diversity of active microorganisms in the
subdivided groundwaters. Additional supports of the bacterial community
structure, assessed by the PLFA patterns, were found in the 16S rRNA-based
results. Although a large fraction of the microbial community remains poorly
classified and thus precludes the knowledge of the metabolic capacities, high
sequence similarity to genera known to be involved in iron oxidation or
reduction, sulfate reduction, anammox, and nitrite oxidation allowed an
estimation of the fraction of the microbial population potentially involved
in these processes. By combining the PLFA-based and sequencing-based
approaches, we aimed, here, to compensate for biases introduced by PCR as
well as for the limited phylogenetic resolution of PLFA-based analysis. This
combined approach resulted in highly supported evidence of some key
microbial players and associated biogeochemical processes in physico-chemical
distinct aquifer assemblages of the aquifer transect.</p>
<sec id="Ch1.S4.SS1.SSS1">
  <title>PLFA cluster in oxic to suboxic groundwater (wells 5.1, 4.1, 3.1
and 3.2)</title>
      <p>A cluster of the covarying 20:4, 20:5, 22:5 and 22:6 PLFAs has to our
knowledge heretofore never been observed in groundwater. Associations of
those PLFAs have been commonly found in eukaryotes such as microalgae
(Volkman et al., 1989; Shinmen et al., 1989; Kennedy et al., 1993; Olsson,
1999; Qi et al., 2004) and protozoans (White, 1988), etc. Protozoa act as
detritivores and are expected to be key predators in the microbial loop
feeding on different subsets of the bacterial communities and other protozoa
(Brad et al., 2008; Akob and Küsel, 2011). Consistently, sessile and
free-swimming suspension-feeding flagellates (e.g. <italic>Spumella</italic> sp.),
mobile naked amoebae, and ciliates could be detected in this aquifer, with a
cultivable protist abundance of up to 8000 cells L<inline-formula><mml:math id="M489" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (Risse-Buhl et
al., 2013). The 18S rRNA gene sequences
also revealed high relative fractions of <italic>Spumella</italic>-like
Stramenopiles, and sequences affiliated with fungi and metazoan grazers.
DNA-based pyro-tag sequencing of fungal internal transcribed spacer sequences
revealed a fungi community structure dominated by Ascomycota and
Basidiomycota (Nawaz et al., 2016), with the majority of the observed fungal
groups being involved in ectomycorrhizal symbioses. In general, the abundance
of micro-eukaryotes in pristine groundwater is estimated to be low, because
they are limited in nutrients and space and are unable to cope with oxygen
limitations (Akob and Küsel, 2011). Consistently, they are commonly found
in higher concentrations in OM-rich contaminated groundwaters (Ludvigsen et
al., 1997). In pristine aquifers, the origin of those eukaryotic organisms is
difficult to determine as they may be autochthonous, allochthonous or both.
In the studied sites, the close relation of eukaryotic PLFA biomarkers with
O<inline-formula><mml:math id="M490" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> concentrations (Fig. 6a) suggests their association with recharging
groundwater within larger conduits prone to faster water flow. Freshly
introduced surface OC and O<inline-formula><mml:math id="M491" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> could fuel the heterotrophic bacterial
growth in groundwater. This may subsequently stimulate protists that
selectively graze on the prokaryotic biomass and result in the observed
relationship between the eukaryotic PLFAs and the O<inline-formula><mml:math id="M492" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> concentration. It
is possible to speculate that some surface microorganisms would also survive
the transport from surface to the aquifer (Dibbern et al., 2014), especially
if the transport is fast. In this case, high cy17:0-to-16:1<inline-formula><mml:math id="M493" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>7c ratios
(Table 3) may show physiological stress due to change of the environmental
conditions within the Gram-negative communities (Balkwill et al., 1998).</p>
      <p>The 16:1<inline-formula><mml:math id="M494" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>11c and particularly the 11Me16:0 are major components of
<italic>Nitrospira moscoviensis</italic> (Lipski et al., 2001) cell
membrane, an obligatory
chemo-lithoautotrophic nitrite-oxidizing bacterium (Ehrich et al., 1995). In
the oxic groundwater, the occurrence of 16S rRNA gene sequence reads that are
closely related to <italic>Nitrospira moscoviensis</italic> (Herrmann et al., 2015)
further supports the potential of 11Me16:0 as a biomarker for
<italic>Nitrospira moscoviensis </italic>and confirms previous assumptions about an
important role of nitrite oxidizers within the autotrophic community of the
lower aquifers (Herrmann et al., 2015). The correlation of 11Me16:0 and
16:1<inline-formula><mml:math id="M495" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>11c with O<inline-formula><mml:math id="M496" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> (Fig. 6a) indicated the occurrence of active
nitrification in oxic zones of the aquifers, in agreement with observation of
experiments (Satoh et al., 2003). <italic>Nitrospira</italic> use the reverse
tricarboxylic acid cycle as the pathway for CO<inline-formula><mml:math id="M497" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> fixation (Lücker et
al., 2010), which leads to small <inline-formula><mml:math id="M498" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:math></inline-formula>C fractionation (2–6 ‰)
between biomass and CO<inline-formula><mml:math id="M499" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> (van der Meer et al., 1998). The
<inline-formula><mml:math id="M500" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:math></inline-formula>C-enrichment of 11Me16:0 and 16:1<inline-formula><mml:math id="M501" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>11c relative to the other
PLFAs (up to 18 ‰ in well H4.1) thus supports a major
<italic>Nitrospira</italic> contribution to those PLFAs found in oxic groundwaters
(Fig. 7).</p>
</sec>
<sec id="Ch1.S4.SS1.SSS2">
  <?xmltex \opttitle{PLFA cluster in anoxic, more Fe${}_{\mathrm{t}}$-rich groundwater (wells
H4.2 and H4.3)}?><title>PLFA cluster in anoxic, more Fe<inline-formula><mml:math id="M502" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula>-rich groundwater (wells
H4.2 and H4.3)</title>
      <p>In groundwater, the concentration of dissolved iron is often inversely related
to oxygen, as O<inline-formula><mml:math id="M503" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> in water will chemically oxidize iron that will
precipitate as insoluble iron-hydroxides at neutral pH. In the wells
H4.2 and H4.3, the increase of the PLFAs 10Me12:0, 12:0, 17:1, 18:1<inline-formula><mml:math id="M504" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>7c and
18:1<inline-formula><mml:math id="M505" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>9c with concentrations of Fe<inline-formula><mml:math id="M506" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula>, Fe<inline-formula><mml:math id="M507" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> and
HCO<inline-formula><mml:math id="M508" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> (Figs. 5 and 6b) and the DNA- and RNA-based analyses (Fig. 9)
suggested degradation of OM by anaerobic iron-reducing bacteria (IRB).
Because many IRB are highly versatile, i.e. they can use different metal
substrates as electron acceptors coupled to the oxidation of the OM (Coleman
et al., 1993; Lovley et al., 1993; Holmes et al., 2004), specific PLFAs
linked to the reduction of iron in anoxic environments are poorly described.
The two most studied genera of IRB are <italic>Geobacter</italic> and
<italic>Shewanella</italic>, which contain most of those PLFAs (Coleman et al., 1993;
Lovley et al., 1993; Hedrick et al., 2009). However, none of these PLFAs are
specific to a certain genus or species. The 17:1 is generally related to
anaerobic SRB (Dowling et al., 1986) as <italic>Desulfobulbus </italic>(Parkes and
Calder, 1985; Macalady et al., 2000) but also occurs in dissimilatory IRB as
<italic>Shewanella </italic>(Coleman et al., 1993). The ability of some sulfate
reducers to reduce iron rather than sulfate has long been recognized in
groundwater (Coleman et al., 1993).</p>
      <p>The 18:1<inline-formula><mml:math id="M509" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>9c is common and abundant in fungi (Frostegård and
Bååth, 1996; Kaiser et al., 2010), but may also occur in micro-algae
(Arts et al., 2001) and Gram-negative bacteria (Kandeler, 2007). The
18:1<inline-formula><mml:math id="M510" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>9c, 18:2<inline-formula><mml:math id="M511" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>6,9 and 18:3<inline-formula><mml:math id="M512" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>6 are typically used as
fungi biomarkers in soil (Frostegård and Bååth, 1996; Ruzicka et
al., 2000; Bååth and Anderson, 2003) and more particularly for
saprotrophs (Etingoff, 2014). The correlations between 18:1<inline-formula><mml:math id="M513" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>9c,
18:2<inline-formula><mml:math id="M514" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>6,9 and 18:3<inline-formula><mml:math id="M515" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>6 suggested a major fungal origin of those
PLFAs in the studied groundwaters. In soil, fungi are well known for their
role in accelerating weathering and solubilisation of iron-containing
minerals by excreting organic acids including phenolic compounds,
siderophores and protons (Arrieta and Grez, 1971; Landeweert et al., 2001).
By forming dense hyphae tunnelling in soils and shallow rocks, fungi mediate
and facilitate iron transport in plants and increase iron availability in the
environment (van Schöll et al., 2008). Therefore, several studies have
linked enhanced rates of iron cycling to the presence of fungal biomass
(Gadd, 2010). Moreover, in a recent study, it is been shown that rhizoplanes
are important root channels for preferential vertical transport from soil to
seepage area of soil colloids including microbes (Dibbern et al., 2014).
Limitation of ferric iron may restrain the growth and activity of IRB in the
subsurface (O'Neil et al., 2008). In the groundwater of wells H4.2 and H4.3,
the close relation of 18:1<inline-formula><mml:math id="M516" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>9c and 18:2<inline-formula><mml:math id="M517" display="inline"><mml:mi mathvariant="italic">ω</mml:mi></mml:math></inline-formula>6,9 with
Fe<inline-formula><mml:math id="M518" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula> concentration (Fig. 6b) suggested that fungal biomass may, by
mediating and facilitating the transport of different types of organic and/or
inorganic particles and colloids, play a key
role in iron bioavailability and thus sustain IRB growth and activity.</p>
</sec>
<sec id="Ch1.S4.SS1.SSS3">
  <?xmltex \opttitle{PLFA cluster in anoxic, more NH${}_{{4}}{}^{{+}}$-rich groundwater (wells
H5.2, H5.3 and H3.2)}?><title>PLFA cluster in anoxic, more NH<inline-formula><mml:math id="M519" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>-rich groundwater (wells
H5.2, H5.3 and H3.2)</title>
      <p>To our knowledge, this is the first time
phospholipid [3]-ladderane and [5]-ladderane, which attest the presence of
viable or recently degraded anammox bacteria (Jaeschke et al., 2009), have
been identified in groundwater. The occurrence of anammox bacteria in those
groundwaters is consistent with the DNA- and RNA-based analyses (Fig. 9) and
coincided with higher concentrations of ammonium (Fig. 2). The difference
between DIC and ladderane <inline-formula><mml:math id="M520" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>C values of 55 ‰ was within
the range previously reported for anammox in the Black Sea (Schouten et al.,
2004), further suggesting that autotrophic carbon fixation pathways within
the diverse group of anaerobic ammonium-oxidizing bacteria are similar. In
the sub-oxic (well H3.2) and anoxic groundwaters (well H5.2 and H5.3), the
increasing concentration of ladderane lipids derived from anammox bacteria
with decreasing O<inline-formula><mml:math id="M521" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> concentration (Fig. 6a) agrees well with the reported
high sensitivity of the anammox process to O<inline-formula><mml:math id="M522" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> (Kalvelage et al., 2011).
Denitrification and anammox are the dominant nitrogen loss pathways in
aquatic ecosystems (Burgin and Hamilton, 2008; Koeve and Kähler, 2010).
The occurrence of lipids derived from anammox bacteria in those groundwaters
indicates that the anammox process may be critically important in the
nitrogen loss from this part of the aquifer assemblage.</p>
      <p>High amounts of 10Me16:0 are typically found in SRB (Dowling et al., 1986;
Vainshtein et al., 1992; Kohring et al., 1994) but also occur in anammox
bacteria (Sinninghe Damsté et al., 2002). Anammox bacteria strongly
fractionate against <inline-formula><mml:math id="M523" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:math></inline-formula>C, producing ladderane lipids which are
<inline-formula><mml:math id="M524" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:math></inline-formula>C-depleted by 47 ‰ compared to the inorganic carbon source
(Schouten et al., 2004). Relative to ladderanes, SRB-derived lipids are
expected to be <inline-formula><mml:math id="M525" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:math></inline-formula>C-enriched as cultured SRB under heterotrophic and
autotrophic growth fractionated against <inline-formula><mml:math id="M526" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:math></inline-formula>C by up 27 ‰ (Londry
et al., 2004). Therefore, the <inline-formula><mml:math id="M527" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:math></inline-formula>C-enrichment of 10Me16:0 (up to
19 ‰) relative to the ladderanes supported major SRB contribution to
the 10Me16:0 found in these groundwaters. The i13:0, <inline-formula><mml:math id="M528" display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula>15:0 and i17:1 are
typically, as with 10Me16:0, associated with SRB (Edlund et al., 1985; Kohring et
al., 1994). In those groundwaters, similar <inline-formula><mml:math id="M529" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">13</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>C values, in the
<inline-formula><mml:math id="M530" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>44 to <inline-formula><mml:math id="M531" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>56 ‰ range, also supported a common SRB origin of those
PLFAs.</p>
      <p>Variation partitioning analyses showed that the concentrations of
[3]-ladderane, [5]-ladderane, 10Me16:0 and i17:1 correlated with NH<inline-formula><mml:math id="M532" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>
concentration (Fig. 6c). Many studies in other aquatic environments showed
that the relative importance of the anammox process is directly related to
the availability of NH<inline-formula><mml:math id="M533" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> (Dalsgaard and Thamdrup, 2002; Kuypers et
al., 2003). Commonly, the breakdown of OM via ammonification or dissimilatory
nitrate reduction to ammonia is presumed to be the major source of
NH<inline-formula><mml:math id="M534" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> for anammox (Kartal et al., 2007). However, the recent discovery
of comammox organisms capable of complete nitrification underlines the
complexity of the nitrogen cycle and the variability of ammonium sources for
anammox (van Kessel et al., 2015). The availability of OM is known as an
additional important factor influencing the anammox process. Higher anammox
activity has been observed in OM-poor environments and interpreted as a
decrease in competition for NO<inline-formula><mml:math id="M535" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> by heterotrophic denitrifiers (Hu et
al., 2011). Consistently, high anammox activity was observed in redox zones
associated with sulfate reduction or sulfur oxidation (Mills et al., 2006;
Canfield et al., 2010; Prokopenko et al., 2013; Wenk et al., 2013). In the
groundwater of the wells H5.2 and H5.3, the occurrence of anammox bacteria
and SRB thus supported low groundwater–surface interactions which likely
threatened the availability of generically favourable electron acceptors and
labile OM.</p>
</sec>
</sec>
</sec>
<sec id="Ch1.S5" sec-type="conclusions">
  <title>Conclusion</title>
      <p>In this study, we used constrained ordination to show environmental variables
that significantly correlated with PLFA relative abundances in groundwater of
distinct carbonate-rock aquifer assemblages. This technique shows that the
active subsurface microbial communities were mainly affected by variations in
dissolved O<inline-formula><mml:math id="M536" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, Fe<inline-formula><mml:math id="M537" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:math></inline-formula> and NH<inline-formula><mml:math id="M538" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> concentrations. Variation
partitioning identified PLFA-based microbial functional groups that were
directly supported by results of DNA- and RNA-based amplicon sequencing
targeting bacterial 16S rRNA genes. Higher O<inline-formula><mml:math id="M539" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> concentration resulted in
increased eukaryotic biomass and higher relative fractions of nitrite
oxidizing bacteria (e.g. <italic>Nitrospira moscoviensis</italic>) but impeded
anammox bacteria, sulfate-reducing bacteria and iron-reducing bacteria. In
anoxic groundwater, concomitant increase of total iron (Fe<inline-formula><mml:math id="M540" display="inline"><mml:mrow><mml:msub><mml:mi/><mml:mi mathvariant="normal">t</mml:mi></mml:msub><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula>,
HCO<inline-formula><mml:math id="M541" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> and PLFAs abundant in Gram-negative bacteria and fungi
suggested the occurrence of active dissimilatory iron reduction and a
possible role of fungi in meditating iron solubilisation and transport in
those aquifer assemblages. The relative abundance of PLFA derived from
anammox bacteria correlated with NH<inline-formula><mml:math id="M542" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> concentrations, showing the
dependence of the anammox process on the availability of NH<inline-formula><mml:math id="M543" display="inline"><mml:mrow><mml:msubsup><mml:mi/><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>. Our
study shows that different relationships among the microbial community
structures, estimated based on both the PLFA patterns and 16S rRNA
gene-targeted next generation sequencing, reflected changes in the
physiological strategies of microorganisms related to a decrease in substrate
bioavailability and redox potential of the groundwater.</p>
</sec>

      
      </body>
    <back><notes notes-type="dataavailability">

      <p>All data are accessible in the Supplement.</p>
  </notes><app-group>
        <supplementary-material position="anchor"><p><bold>The Supplement related to this article is available online at <inline-supplementary-material xlink:href="http://dx.doi.org/10.5194/bg-14-2697-2017-supplement" xlink:title="zip">doi:10.5194/bg-14-2697-2017-supplement</inline-supplementary-material>.</bold></p></supplementary-material>
        </app-group><notes notes-type="competinginterests">

      <p>The authors declare that they have no conflict of
interest.</p>
  </notes><ack><title>Acknowledgements</title><p>The work has been funded by the Deutsche Forschungsgemeinschaft (DFG) CRC
1076 “AquaDiva”. Field work permits were issued by the responsible state
environmental offices of Thuringia. We thank Heiko Minkmar and Falko
Gutmann for sampling and on-site measurements, Christine Hess for scientific
coordination and the Hainich National Park administration for help and
support. Patricia Geesink is acknowledged for assistance in DNA and RNA
extractions. Illumina MiSeq amplicon sequencing was financially supported by
the German Center for Integrative Biodiversity Research (iDiv)
Halle-Jena-Leipzig, funded by the Deutsche Forschungsgemeinschaft (FZT 118).
The authors would like to thank two anonymous referees and the Associate
Editor Marcel van der Meer for their helpful comments in Biogeosciences
Discussions.<?xmltex \hack{\newline}?><?xmltex \hack{\newline}?> Edited by: M. van der
Meer<?xmltex \hack{\newline}?> Reviewed by: two anonymous referees</p></ack><ref-list>
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<abstract-html><p class="p">Microorganisms in groundwater play an important role in aquifer
biogeochemical cycles and water quality. However, the mechanisms linking the
functional diversity of microbial populations and the groundwater
physico-chemistry are still not well understood due to the complexity of
interactions between surface and subsurface. Within the framework of Hainich
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groundwater physico-chemistry. The functional diversities of the microbial
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Abundances of PLFAs derived from eukaryotes and potential nitrite-oxidizing
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iron-reducing bacteria and fungi increased with Fe<sub>t</sub> and
HCO<sub>3</sub><sup>−</sup> concentrations, suggesting the occurrence of active iron
reduction and the possible role of fungi in meditating iron solubilization
and transport in those aquifer domains. In more NH<sub>4</sub><sup>+</sup>-rich anoxic
groundwaters, anammox bacteria and SRB-derived PLFAs increased with
NH<sub>4</sub><sup>+</sup> concentration, further evidencing the dependence of the anammox
process on ammonium concentration and potential links between SRB and anammox
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found in DNA- and RNA-based Illumina MiSeq amplicon sequencing of bacterial
16S rRNA genes, which showed high predominance of nitrite-oxidizing bacteria
<i>Nitrospira</i>, e.g. <i>Nitrospira moscoviensis</i>, in oxic aquifer
zones and of anammox bacteria in more NH<sub>4</sub><sup>+</sup>-rich anoxic groundwater.
Higher relative abundances of sequence reads in the RNA-based datasets
affiliated with iron-reducing bacteria in more Fe<sub>t</sub>-rich
groundwater supported the occurrence of active dissimilatory iron reduction.
The functional diversity of the microbial communities in the biogeochemically
distinct groundwater assemblages can be largely attributed to the redox
conditions linked to changes in bioavailable substrates and input of
substrates with the seepage. Our results demonstrate the power of
complementary information derived from PLFA-based and sequencing-based
approaches.</p></abstract-html>
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