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<!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing with OASIS Tables v3.0 20080202//EN" "journalpub-oasis3.dtd">
<article xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:oasis="http://docs.oasis-open.org/ns/oasis-exchange/table" xml:lang="en" dtd-version="3.0" article-type="research-article">
  <front>
    <journal-meta><journal-id journal-id-type="publisher">WE</journal-id><journal-title-group>
    <journal-title>Web Ecology</journal-title>
    <abbrev-journal-title abbrev-type="publisher">WE</abbrev-journal-title><abbrev-journal-title abbrev-type="nlm-ta">Web Ecol.</abbrev-journal-title>
  </journal-title-group><issn pub-type="epub">1399-1183</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/we-22-21-2022</article-id><title-group><article-title>Spatial heterogeneity of <italic>Cladonia rangiformis</italic> and <italic>Erica</italic> spp. induces variable effects on soil microbial communities which are most robust<?xmltex \hack{\break}?> in bare-soil microhabitats</article-title><alt-title>Spatial heterogeneity in microbes induced by <italic>C. rangiformis</italic> and <italic>Erica</italic> spp.</alt-title>
      </title-group><?xmltex \runningtitle{Spatial heterogeneity in microbes induced by \textit{C. rangiformis} and \textit{Erica} spp.}?><?xmltex \runningauthor{T.~Dostos et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Dostos</surname><given-names>Theofilos</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Kapagianni</surname><given-names>Pantelitsa D.</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Monokrousos</surname><given-names>Nikolaos</given-names></name>
          
        <ext-link>https://orcid.org/0000-0001-5465-5588</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Stamou</surname><given-names>George P.</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="yes" rid="aff1">
          <name><surname>Papatheodorou</surname><given-names>Efimia M.</given-names></name>
          <email>papatheo@bio.auth.gr</email>
        <ext-link>https://orcid.org/0000-0003-1776-9126</ext-link></contrib>
        <aff id="aff1"><label>1</label><institution>Department of Ecology, School of Biology, Aristotle University,
54124 Thessaloniki, Greece</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>University Center of International Programmes of Studies,
International Hellenic University, <?xmltex \hack{\break}?>57001 Thessaloniki, Greece</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Efimia M. Papatheodorou (papatheo@bio.auth.gr)</corresp></author-notes><pub-date><day>8</day><month>April</month><year>2022</year></pub-date>
      
      <volume>22</volume>
      <issue>1</issue>
      <fpage>21</fpage><lpage>31</lpage>
      <history>
        <date date-type="received"><day>21</day><month>October</month><year>2021</year></date>
           <date date-type="rev-recd"><day>13</day><month>February</month><year>2022</year></date>
           <date date-type="accepted"><day>18</day><month>February</month><year>2022</year></date>
      </history>
      <permissions>
        <copyright-statement>Copyright: © 2022 Theofilos Dostos et al.</copyright-statement>
        <copyright-year>2022</copyright-year>
      <license license-type="open-access"><license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p></license></permissions><self-uri xlink:href="https://we.copernicus.org/articles/22/21/2022/we-22-21-2022.html">This article is available from https://we.copernicus.org/articles/22/21/2022/we-22-21-2022.html</self-uri><self-uri xlink:href="https://we.copernicus.org/articles/22/21/2022/we-22-21-2022.pdf">The full text article is available as a PDF file from https://we.copernicus.org/articles/22/21/2022/we-22-21-2022.pdf</self-uri>
      <abstract><title>Abstract</title>

      <p id="d1e137">Biological soil crust (BSC) is an essential part of arid and semiarid regions;
however information concerning the spatial heterogeneity of the interactions
between crust, plants and soil microbes is limited. Sampling was confined to
an area either covered with <italic>Erica</italic> spp. shrubs interspaced by crust cover
(<italic>Cladonia rangiformis)</italic> or uncovered by crust. Along a straight line of 100 cm from the
base of the shrubs towards their periphery and at successive distances of 20 cm, soil samples were collected once. The biomass, the composition and the
network of interactions among the members of the soil microbial communities
as well as the activity of soil enzymes involved in the C, N and P cycle were
estimated. Crust coverage exerted a significant allelopathic negative effect
on soil microbial biomasses due to the leaching of lichen's antimicrobial
substances. In contrast, the crust effect on enzyme activity was positive,
probably due to the amelioration of soil abiotic conditions. The distance
from the base of <italic>Erica</italic> spp. affected the total microbial and bacterial biomass,
with lower values at the base of the shrubs. The composition of microbial
communities between the different sampling points exhibited significant
dissimilarities. Network analysis revealed that in uncrusted soils the most
connected microbial network was at samples collected from a distance
of <inline-formula><mml:math id="M1" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">60</mml:mn></mml:mrow></mml:math></inline-formula> cm (bare soils), while in crusted soils this was at samples
collected at the base of shrubs. We concluded that microbial biomass showed
limited response to spatial heterogeneity, while the composition and the
topology of interactions among the microbial members reflected a
heterogeneous soil environment existing on a small spatial scale in
Mediterranean areas. The microbial community in bare soil appeared to be the
most robust against future disturbances.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <label>1</label><title>Introduction</title>
      <p id="d1e168">Biological soil crust (BSC) is a complex microbial association composed of microorganisms, soil particles and extracellular polymeric substances. For
the arid regions of the planet, it is estimated that biocrust covers up to
45 % of the soil surface, while for the Mediterranean region the
percentage of coverage is almost 70 % (Steven et al., 2014). However,
while BSCs are by definition found in arid and semiarid areas, this being their
key component, they are also known as inhabitants of mesic ecosystems (Bowker, 2010).</p>
      <p id="d1e171">Biocrusts are highly complex systems where the abiotic environment interacts
with local soil organisms, including cyanobacteria, algae, lichens and
mosses, bacteria, fungi, and various types of microfauna, inducing a series
of geomorphological features, such as soil stabilization (Maier et al.,
2018), increased corrosion resistance (Bu et al., 2015) and formation of a
rough dust-trapping texture (Williams et al., 2012). In addition, crusts
have an effect on the soil hydrological characteristics by altering water
infiltration (Kidron et al., 2020), runoff intensity (Rodriguez-Caballiero
et al., 2012) and evaporation rate (Kidron et al., 2020). Finally, crusts
alter the soil surface temperature (Couradeau et al., 2016) and soil water
content (Bu et al., 2015).</p>
      <p id="d1e174">Given the environmental hardness predominating in arid and semiarid
environments, the interaction of crusts with the vascular plants is vital
for plants' survival (Bainbridge, 2012). Vegetation has an effect on
biocrust formation by altering various microclimatic and territorial
properties (Zhang et al., 2016). The type of plants, their density and the
size of the canopy affect parameters such as the level of radiation
reaching the soil, the quality of the litter produced and the soil
temperature through the layer formed by the fallen leaves. Further plants
interact with the biocrusts through the activity of their root system (Zhang
et al., 2016). In crusted areas enhanced porosity and increased high soil
humidity are recorded beneath plants (Menon et al., 2011). For its part,
biological soil crust increases soil fertility and generally has a positive
effect on soil quality, a fact that is reflected in the increase in soil
enzyme activity underneath the crust (Liu et al., 2014). Especially in arid
areas, where nutrient concentration is low, BSC presence is associated with
increased levels of soil organic matter and available nitrogen through the
fixation of atmospheric nitrogen (Weber et al. 2015), thus promoting the
growth of vascular plants (Havrilla et al., 2019). Apart from increasing
nutrients, the organisms of BSCs secrete exopolysaccharides especially at
the initial stage of their development (Cania et al., 2020) and contain
lipids, which act as energy reserves, contributing further to the
development of an important energy source for soil biota (Ngosong et al.,
2020). However, although in most cases the effects of biocrusts on soil
properties were positive, Papatheodorou et al. (2020) mentioned that the
abundance of soil microbes in areas covered by <italic>Cladonia rangiformis</italic> decreased after a rainy event. Similarly, Delgado-Baquerizo et al. (2015) found contrasting soil
microbial abundances under the different biocrust-forming lichens.
Specifically, the lichens <italic>Fulgensia subbracteata</italic> and <italic>Diploschistes diacapsis</italic> were negatively related to the abundance of
soil bacteria.</p>
      <p id="d1e186">Considering the importance of the BSCs' interplay with the local vegetation,
in this study we focused on the effect of the interactions between the plant
<italic>Erica</italic> spp. (a drought-tolerant shrub species predominating in Mediterranean
areas) and the biocrust layer dominated by the lichen <italic>Cladonia rangiformis,</italic> on soil microbial
biomass; community composition; and the activity of acid phosphatase, <inline-formula><mml:math id="M2" display="inline"><mml:mi mathvariant="italic">β</mml:mi></mml:math></inline-formula>-glucosidase, peroxidase, polyphenol oxidase, <inline-formula><mml:math id="M3" display="inline"><mml:mi mathvariant="italic">β</mml:mi></mml:math></inline-formula>-N-acetylglucosamine,
leucine aminopeptidase and urease soil enzymes. In addition, in order to
examine the effects of the spatial heterogeneity induced by crust's
presence or absence combined with the plant presence on soil microbial
attributes, the samples were collected along a straight line of 100 cm from
the trunk of the shrubs towards their periphery in crusted and uncrusted
soils. Soil habitats in Mediterranean areas are characterized as highly
heterogeneous in time and space (fine grained mosaic; Stamou, 1998), where
biotic and abiotic drivers affect the assemblages of soil communities across
scales ranging from hectares to square centimeters (Wu et al., 2013). In
this study, we hypothesized that the spatial heterogeneity will be reflected
in quantitative microbial estimates. Higher microbial biomass and enzyme
activity were expected at the base of the shrubs (0 to 20 cm from the trunk)
in crust-covered areas where both biotic and abiotic conditions were
favorable; high amounts of organic input (dead organic material and root
exudates) are inserted into the soil, while crust cover acts as a buffer system for
soil life against abiotic stress. Apart from quantitative estimates, we
expected differences in the soil microbial community composition and the
network of interactions among the microbial members even at distances of a
few centimeters.</p>
</sec>
<sec id="Ch1.S2">
  <label>2</label><title>Materials and methods</title>
<sec id="Ch1.S2.SS1">
  <label>2.1</label><title>Experimental design and sampling</title>
      <p id="d1e224">The sampling area was located in the Sithonia peninsula, at Halkidiki,
northern Greece (40<inline-formula><mml:math id="M4" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>08<inline-formula><mml:math id="M5" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula>59.8<inline-formula><mml:math id="M6" display="inline"><mml:mrow><mml:mi mathvariant="normal">`</mml:mi><mml:mi mathvariant="normal">`</mml:mi></mml:mrow></mml:math></inline-formula> N, 23<inline-formula><mml:math id="M7" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>54<inline-formula><mml:math id="M8" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula>56.2<inline-formula><mml:math id="M9" display="inline"><mml:mrow><mml:mi mathvariant="normal">`</mml:mi><mml:mi mathvariant="normal">`</mml:mi></mml:mrow></mml:math></inline-formula> E). The
climate of Sithonia is characterized by warm and dry summers and mild and
moderately rainy winters. The area was dominated by <italic>Ericaceous</italic> shrubs interspaced with
open areas covered by a well-developed biocrust layer, which consisted
of the lichen <italic>Cladonia rangiformis</italic> (80 % cover) and mosses (Fig. S1 in the Supplement). The soil
texture was sandy-loam (4 % clay, 20 % silt and 76 % sand), and the pH
was 5.8 (soil <inline-formula><mml:math id="M10" display="inline"><mml:mo>:</mml:mo></mml:math></inline-formula> water ratio <inline-formula><mml:math id="M11" display="inline"><mml:mrow><mml:mn mathvariant="normal">1</mml:mn><mml:mo>:</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula>).</p>
      <p id="d1e309">In early autumn (end of September), soil samples were collected at
successive distances from the trunk of <italic>Erica </italic>spp. shrubs towards their periphery,
at intervals of 20 cm along a straight line of 100 cm (six sampling
points in total), in shrubs with crust-covered surrounding area (crusted shrub area)
and those without crust (uncrusted shrub area). We sampled five crusted and
five uncrusted shrubs that were distributed randomly in the wider area. For
sampling, a soil auger of 5 cm diameter was used, and soil was collected
from the upper 10 cm. The collected soil samples were placed in plastic bags
after the removal of the crust in crust-covered samples, transferred to
a laboratory, passed through a 2 mm sieve and stored at 4 <inline-formula><mml:math id="M12" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C until
analysis.</p>
</sec>
<sec id="Ch1.S2.SS2">
  <label>2.2</label><title>Biochemical parameters</title>
      <p id="d1e332">Soil water content (WC) was determined by a gravimetric method. Soil organic C
was determined by a wet oxidation titration procedure using an acid
dichromate system and soil organic nitrogen by the Kjeldahl method (Allen,
1974).
<?xmltex \hack{\newpage}?></p>
</sec>
<sec id="Ch1.S2.SS3">
  <label>2.3</label><title>Enzyme activity</title>
      <p id="d1e344">We assessed enzyme activity involved in C, P and N cycles. The enzymes
b-glucosidase (BG), peroxidase (POD) and polyphenol oxidase (PPO)
participate in the C cycle; BG hydrolyzes cellobiose to glucose (Knight and
Dick, 2004), while POD and PPO catalyze the oxidation of recalcitrant
aromatic compounds, such as lignin, into more readily available substrates
(Cullen and Kersten, 1996). Acid phosphatase (AP) participates in the P cycle by
hydrolyzing phosphomonoesters and in some cases phosphodiesters, releasing
phosphate (Turner et al., 2002), while N-acetyl-glucosaminidase (NAG),
leucine aminopeptidase (LAP) and urease (UR) are enzymes that participate in
the N cycle. NAG degrades chitin (Felse and Panda, 1999), and LAP hydrolyzes
leucine and other hydrophobic amino acids (Stursova et al., 2006), while UR
decomposes urea into carbon dioxide and ammonium (Sinsabaugh et al., 2000).
The activity of all enzymes was determined according to the methods
described in detail by Kapagianni et al. (2020). The activity of AP, BG and
NAG was expressed as <inline-formula><mml:math id="M13" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">mol</mml:mi></mml:mrow></mml:math></inline-formula> pNP g<inline-formula><mml:math id="M14" 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> soil h<inline-formula><mml:math id="M15" 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>, LAP as <inline-formula><mml:math id="M16" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">mol</mml:mi></mml:mrow></mml:math></inline-formula> pNA g<inline-formula><mml:math id="M17" 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> soil h<inline-formula><mml:math id="M18" 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>, PPO and POD as <inline-formula><mml:math id="M19" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">mol</mml:mi></mml:mrow></mml:math></inline-formula> L-DOPA g<inline-formula><mml:math id="M20" 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> soil h<inline-formula><mml:math id="M21" 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 that of UR as <inline-formula><mml:math id="M22" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">mol</mml:mi></mml:mrow></mml:math></inline-formula> NH4<inline-formula><mml:math id="M23" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula> g<inline-formula><mml:math id="M24" 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> soil h<inline-formula><mml:math id="M25" 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>.</p>
</sec>
<sec id="Ch1.S2.SS4">
  <label>2.4</label><title>Determination of microbial biomass and community composition by the phospholipid fatty acid (PLFA) method</title>
      <p id="d1e502">The total microbial PLFAs are widely used as an index of total microbial
biomass (Nikolaidou et al., 2021; Papatheodorou et al., 2021; Kapagianni et
al., 2020). Extraction and analysis of phospholipid fatty acids from
soil samples were performed within a week of post-sampling. Concisely, the
procedure entails extraction of lipids; separation of phospholipids by
column chromatography; methylation of esterified fatty acids in the
phospholipid fraction; and chromatographic separation and identification of
the main components on a Trace GC Ultra gas chromatograph (Thermo Finnigan,
San Jose, CA) coupled with a Trace ISQ mass spectrometry (MS) detector, a
split–splitless injector and an Xcalibur MS platform. Each fatty acid (nmol g<inline-formula><mml:math id="M26" 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> was quantified by one-point calibration against the GC
response of the internal standard <inline-formula><mml:math id="M27" display="inline"><mml:mrow><mml:mn mathvariant="normal">19</mml:mn><mml:mo>:</mml:mo><mml:mn mathvariant="normal">0</mml:mn></mml:mrow></mml:math></inline-formula> methyl ester.</p>
      <p id="d1e532">A total of 20 fatty acid methyl esters were identified and considered for further
analysis, including the internal standard <inline-formula><mml:math id="M28" display="inline"><mml:mrow><mml:mn mathvariant="normal">19</mml:mn><mml:mo>:</mml:mo><mml:mn mathvariant="normal">0</mml:mn></mml:mrow></mml:math></inline-formula>. The PLFA biomarkers were
assigned to functional groups as follows: 15:0, i–15:0, a–15:0, i–16:0, 17:0
and i–17:0 (gram-positive bacteria) (McKinley et al., 2005); 16:1<inline-formula><mml:math id="M29" display="inline"><mml:mrow><mml:mi mathvariant="italic">ω</mml:mi><mml:mn mathvariant="normal">7</mml:mn></mml:mrow></mml:math></inline-formula>c,
18:1<inline-formula><mml:math id="M30" display="inline"><mml:mrow><mml:mi mathvariant="italic">ω</mml:mi><mml:mn mathvariant="normal">9</mml:mn></mml:mrow></mml:math></inline-formula>t and cyc17:0 (gram-negative bacteria) (Zhang et al., 2010);
10Me16:0, 10Me17:0 and 10Me18:0 (actinomycetes) (White et al., 1996);
18:2<inline-formula><mml:math id="M31" display="inline"><mml:mrow><mml:mi mathvariant="italic">ω</mml:mi><mml:mn mathvariant="normal">9</mml:mn><mml:mo>,</mml:mo><mml:mn mathvariant="normal">12</mml:mn></mml:mrow></mml:math></inline-formula> (fungi) (Rillig et al., 2006); 20:0 (microeukaryotes)
(Smith et al., 1986). The PLFA biomarker 16:0 may derive from bacteria and fungi and 18:1<inline-formula><mml:math id="M32" display="inline"><mml:mrow><mml:mi mathvariant="italic">ω</mml:mi><mml:mn mathvariant="normal">9</mml:mn></mml:mrow></mml:math></inline-formula>c from both gram-negative bacteria and fungi, while 11:0, 14:0 and
18:2<inline-formula><mml:math id="M33" display="inline"><mml:mrow><mml:mi mathvariant="italic">ω</mml:mi><mml:mn mathvariant="normal">6</mml:mn></mml:mrow></mml:math></inline-formula>t are mainly of microbial origin (Rousidou et al., 2013;
Monokrousos et al., 2021). The sum of all identified lipid quantities was used
as an index of total microbial biomass, and the ratio iso<inline-formula><mml:math id="M34" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula>anteiso was used
as an index of environmental stress (Siliakus et al., 2017). We further
estimated the ratios gram<inline-formula><mml:math id="M35" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup><mml:mo>/</mml:mo></mml:mrow></mml:math></inline-formula>gram<inline-formula><mml:math id="M36" display="inline"><mml:msup><mml:mi/><mml:mo>-</mml:mo></mml:msup></mml:math></inline-formula>, fungi<inline-formula><mml:math id="M37" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula>bacteria and saturated<inline-formula><mml:math id="M38" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula>unsaturated PLFAs.</p>
</sec>
<sec id="Ch1.S2.SS5">
  <label>2.5</label><title>Data analysis</title>
      <p id="d1e653">To test the effects of BSC coverage regime and distance from the trunk of
<italic>Erica</italic> spp. (0, 20, 40, 60, 80 and 100 cm) on water content, organic carbon, organic
nitrogen, microbial biomasses and enzyme activity, we applied two-way ANOVA (analysis of variance) on data (<inline-formula><mml:math id="M39" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">60</mml:mn></mml:mrow></mml:math></inline-formula> for each parameter, 2 BSC coverage regimes <inline-formula><mml:math id="M40" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 6 distances
from <italic>Erica </italic>spp. <inline-formula><mml:math id="M41" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 5 replicates). In cases where the data did not meet the
assumptions of analysis of variance, a transformation was performed (PLFA
values were logarithmically transformed, while the square transformation was
applied on LAP and BG values). Analysis of variance was carried out using
the Statistica 7.0 software.</p>
      <p id="d1e688">To check for similarities in the composition of soil microbial communities
collected at different sampling points, we applied one-way ANOSIM (analysis
of similarities) on individual phospholipids' data sets with the Bray–Curtis
index as a similarity index. The analyses were performed using PAST version
3.24 (Hammer et al., 2001).</p>
      <p id="d1e691">A network analysis was applied to analyze the network of relationships
between individual PLFA markers under BSC coverage regimes (presence and
absence of crust) at three successive distances from the trunk of the <italic>Erica</italic> spp. shrubs. We applied network analysis on data collected from distances of 0–20,
40 and 60–100 cm. We divided the data collected along the line of 100 cm into
three parts: those collected from a distance of 0–20 cm, where <italic>Erica</italic> had the greatest
influence; at a distance of 40 cm, where the projection of the canopy of <italic>Erica</italic> was ended; and
at a distance of <inline-formula><mml:math id="M42" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">40</mml:mn></mml:mrow></mml:math></inline-formula> cm (60–100 cm). The last distance in crust-covered areas was covered by crust, while in uncrusted areas it was represented
by bare soil. The nodes of the valued network represented PLFA biomarkers, while ties stood for the significant correlations between them
(Stamou et al., 2019). The networks were analyzed with the Cytoscape and
Ucinet packages and results visualized with an attribute circle layout.</p>
      <p id="d1e713">Six networks were analyzed (2 BSC coverage regimes <inline-formula><mml:math id="M43" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 3 distance groups; 0–0.2, 0.40 and 0.60–1 m). In total, five network parameters were
considered; three of them describe the cohesion of the network. These were
density (the total of all correlation values divided by the number of
possible ties), shortest path and clustering coefficient. Shortest path is
the number of links contained in the shortest path that connects two nodes.
Two nodes of a network could be connected by following different paths. They
could be connected directly, the shortest path being 1; indirectly through
another node, the shortest path being 2; indirectly through two other nodes, the shortest path being 3; etc. Thus, the mean shortest path of a network is
the mean value of the lowest number of links that connect all pairs of nodes.
The lower the shortest path, the more direct the connections between the
nodes. The maximum value of compactness is 1, while smaller values indicate
less compact networks. The clustering coefficient is the sum of the correlation
coefficients between a node and its neighbors, and the weighted overall
clustering coefficient is the weighted mean of the clustering coefficient of
all nodes, each one weighted by its degree. Finally, the small-worldness
index (SW) indicates whether a network exhibits small-world properties. This
happens if the estimated length of shortest path (<inline-formula><mml:math id="M44" display="inline"><mml:mrow><mml:msub><mml:mi>L</mml:mi><mml:mi mathvariant="normal">real</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) is more or
less equal to the shortest path (<inline-formula><mml:math id="M45" display="inline"><mml:mrow><mml:msub><mml:mi>L</mml:mi><mml:mi mathvariant="normal">rand</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) estimated for an equivalent
random network (<inline-formula><mml:math id="M46" display="inline"><mml:mrow><mml:msub><mml:mi>L</mml:mi><mml:mi mathvariant="normal">real</mml:mi></mml:msub><mml:mo>≈</mml:mo><mml:msub><mml:mi>L</mml:mi><mml:mi mathvariant="normal">rand</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>), while the clustering
coefficient of the network (<inline-formula><mml:math id="M47" display="inline"><mml:mrow><mml:mi>C</mml:mi><mml:msub><mml:mi>l</mml:mi><mml:mi mathvariant="normal">real</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) is much higher than that for the
random counterpart (<inline-formula><mml:math id="M48" display="inline"><mml:mrow><mml:mi>C</mml:mi><mml:msub><mml:mi>l</mml:mi><mml:mi mathvariant="normal">real</mml:mi></mml:msub><mml:mi mathvariant="italic">&gt;&gt;</mml:mi><mml:mi>C</mml:mi><mml:msub><mml:mi>l</mml:mi><mml:mi mathvariant="normal">rand</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>), i.e., if SW<inline-formula><mml:math id="M49" display="inline"><mml:mrow><mml:mo>=</mml:mo><mml:mo>(</mml:mo><mml:mi>C</mml:mi><mml:msub><mml:mi>l</mml:mi><mml:mi mathvariant="normal">real</mml:mi></mml:msub><mml:mo>/</mml:mo><mml:mi>C</mml:mi><mml:msub><mml:mi>l</mml:mi><mml:mi mathvariant="normal">rand</mml:mi></mml:msub><mml:mo>)</mml:mo><mml:mo>/</mml:mo><mml:mo>(</mml:mo><mml:msub><mml:mi>L</mml:mi><mml:mi mathvariant="normal">real</mml:mi></mml:msub><mml:mo>/</mml:mo><mml:msub><mml:mi>L</mml:mi><mml:mi mathvariant="normal">rand</mml:mi></mml:msub><mml:mo>)</mml:mo><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula> (Humphries and Gurney, 2008; Stamou et al., 2019). For testing departure from
randomness the outputs of each experimental network were tested against
those provided by 999 corresponding Erdős–Rényi random networks
with the same number of nodes and density by using Student's <inline-formula><mml:math id="M50" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula> test for
a single sample and <inline-formula><mml:math id="M51" display="inline"><mml:mrow><mml:mi>N</mml:mi><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">30</mml:mn></mml:mrow></mml:math></inline-formula>.</p>
</sec>
</sec>
<sec id="Ch1.S3">
  <label>3</label><title>Results</title>
<sec id="Ch1.S3.SS1">
  <label>3.1</label><title>Physicochemical variables</title>
      <p id="d1e885">Distance had no effect on soil water content. However, significant
differences in water content were observed in relation to biocrust coverage
(<inline-formula><mml:math id="M52" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.001</mml:mn></mml:mrow></mml:math></inline-formula>); BSC soils had higher mean water content by 50 %
compared to uncrusted soils. Organic carbon was not affected by the
distance, coverage regime and their interaction. In contrast, organic N
was affected significantly by the combination crust coverage <inline-formula><mml:math id="M53" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> distance
(Kruskal–Wallis ANOVA; chi-square: 24.96; <inline-formula><mml:math id="M54" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula>); significantly high
soil N was recorded at distances of 0 and 20 cm in BSC soils, and
significantly low soil N was recorded at a distance of 100 cm in soils without crust coverage.</p>
</sec>
<sec id="Ch1.S3.SS2">
  <label>3.2</label><title>Microbial biomass and community composition</title>
      <p id="d1e927">Soil microbial biomass of bacteria, fungi, actinomycetes and microeukaryotes
was not affected by the combination of crust coverage <inline-formula><mml:math id="M55" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> distance. Biocrust
coverage per se significantly affected the biomass of all microbial groups and
their ratios, except the fungi<inline-formula><mml:math id="M56" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula>bacteria ratio (Table 1); higher microbial
biomasses were recorded in uncrusted soils. In contrast, the ratios
gram<inline-formula><mml:math id="M57" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup><mml:mo>/</mml:mo></mml:mrow></mml:math></inline-formula>gram<inline-formula><mml:math id="M58" display="inline"><mml:msup><mml:mi/><mml:mo>-</mml:mo></mml:msup></mml:math></inline-formula> bacteria and saturated<inline-formula><mml:math id="M59" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula>unsaturated PLFAs displayed higher values in crusted soils. Distance affected the total biomass, the
biomass of actinomycetes and that of bacteria as well as the iso<inline-formula><mml:math id="M60" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula>anteiso ratio.
The lowest bacterial and actinomycete biomass was recorded at the base of
<italic>Erica</italic> shrubs (at a distance of 0 cm) and the highest at a distance of 40 cm in both crusted
and uncrusted soils. The iso<inline-formula><mml:math id="M61" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula>anteiso ratio was low until the distance of 60 cm but increased at larger distances (Fig. 1).</p>

<?xmltex \floatpos{p}?><table-wrap id="Ch1.T1" specific-use="star"><?xmltex \currentcnt{1}?><label>Table 1</label><caption><p id="d1e993">Effect of the crust presence or absence (“Crust coverage”), distance (0, 20,
40, 60, 80 and 100 cm), and their interaction (“Coverage <inline-formula><mml:math id="M62" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> distance”) on the
biomass of various microbial groups. The asterisk indicates the level of significance (<inline-formula><mml:math id="M63" display="inline"><mml:mo lspace="0mm">∗</mml:mo></mml:math></inline-formula>: <inline-formula><mml:math id="M64" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>; <inline-formula><mml:math id="M65" display="inline"><mml:mrow><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo></mml:mrow></mml:math></inline-formula>: <inline-formula><mml:math id="M66" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula>; <inline-formula><mml:math id="M67" display="inline"><mml:mrow><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo></mml:mrow></mml:math></inline-formula>: <inline-formula><mml:math id="M68" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.001</mml:mn></mml:mrow></mml:math></inline-formula>; and ns: not statistically significant). All microbial groups are expressed in nanomoles per gram.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="9">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="right"/>
     <oasis:colspec colnum="3" colname="col3" align="right" colsep="1"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:colspec colnum="5" colname="col5" align="right" colsep="1"/>
     <oasis:colspec colnum="6" colname="col6" align="right"/>
     <oasis:colspec colnum="7" colname="col7" align="right" colsep="1"/>
     <oasis:colspec colnum="8" colname="col8" align="center"/>
     <oasis:colspec colnum="9" colname="col9" align="center"/>
     <oasis:thead>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry rowsep="1" namest="col2" nameend="col3" align="center" colsep="1">Mean values <inline-formula><mml:math id="M69" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> SE  </oasis:entry>
         <oasis:entry rowsep="1" namest="col4" nameend="col5" align="center" colsep="1">Crust coverage </oasis:entry>
         <oasis:entry rowsep="1" namest="col6" nameend="col7" align="center" colsep="1">Distance </oasis:entry>
         <oasis:entry rowsep="1" namest="col8" nameend="col9">Crust coverage <inline-formula><mml:math id="M70" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> distance </oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Microbial groups</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M71" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>BSC</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M72" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>BSC</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M73" display="inline"><mml:mi>F</mml:mi></mml:math></inline-formula> ratio</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M74" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> level</oasis:entry>
         <oasis:entry colname="col6"><inline-formula><mml:math id="M75" display="inline"><mml:mi>F</mml:mi></mml:math></inline-formula> ratio</oasis:entry>
         <oasis:entry colname="col7"><inline-formula><mml:math id="M76" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> level</oasis:entry>
         <oasis:entry colname="col8"><inline-formula><mml:math id="M77" display="inline"><mml:mi>F</mml:mi></mml:math></inline-formula> ratio</oasis:entry>
         <oasis:entry colname="col9"><inline-formula><mml:math id="M78" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> level</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">Actinomycetes</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M79" display="inline"><mml:mrow><mml:mn mathvariant="normal">1.85</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.13</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M80" display="inline"><mml:mrow><mml:mn mathvariant="normal">6.21</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.76</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">85.75</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M81" display="inline"><mml:mrow><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">2.52</oasis:entry>
         <oasis:entry colname="col7"><inline-formula><mml:math id="M82" display="inline"><mml:mo>∗</mml:mo></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col8">1.61</oasis:entry>
         <oasis:entry colname="col9">ns</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Fungi</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M83" display="inline"><mml:mrow><mml:mn mathvariant="normal">3.93</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.28</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M84" display="inline"><mml:mrow><mml:mn mathvariant="normal">10.33</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">1.31</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">50.74</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M85" display="inline"><mml:mrow><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">2.30</oasis:entry>
         <oasis:entry colname="col7">ns</oasis:entry>
         <oasis:entry colname="col8">1.23</oasis:entry>
         <oasis:entry colname="col9">ns</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Bacteria</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M86" display="inline"><mml:mrow><mml:mn mathvariant="normal">20.83</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">1.32</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M87" display="inline"><mml:mrow><mml:mn mathvariant="normal">60.44</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">7.23</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">86.56</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M88" display="inline"><mml:mrow><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">2.66</oasis:entry>
         <oasis:entry colname="col7"><inline-formula><mml:math id="M89" display="inline"><mml:mo>∗</mml:mo></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col8">1.40</oasis:entry>
         <oasis:entry colname="col9">ns</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Fungi<inline-formula><mml:math id="M90" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula>bacteria</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M91" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.19</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M92" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.17</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">2.12</oasis:entry>
         <oasis:entry colname="col5">ns</oasis:entry>
         <oasis:entry colname="col6">0.87</oasis:entry>
         <oasis:entry colname="col7">ns</oasis:entry>
         <oasis:entry colname="col8">0.21</oasis:entry>
         <oasis:entry colname="col9">ns</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Gram<inline-formula><mml:math id="M93" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M94" display="inline"><mml:mrow><mml:mn mathvariant="normal">12.97</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.88</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M95" display="inline"><mml:mrow><mml:mn mathvariant="normal">36.11</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">4.44</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">76.70</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M96" display="inline"><mml:mrow><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">2.55</oasis:entry>
         <oasis:entry colname="col7"><inline-formula><mml:math id="M97" display="inline"><mml:mo>∗</mml:mo></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col8">1.39</oasis:entry>
         <oasis:entry colname="col9">ns</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Gram<inline-formula><mml:math id="M98" display="inline"><mml:msup><mml:mi/><mml:mo>-</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M99" display="inline"><mml:mrow><mml:mn mathvariant="normal">6.02</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.33</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M100" display="inline"><mml:mrow><mml:mn mathvariant="normal">18.11</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">2.07</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">99.90</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M101" display="inline"><mml:mrow><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">2.81</oasis:entry>
         <oasis:entry colname="col7"><inline-formula><mml:math id="M102" display="inline"><mml:mo>∗</mml:mo></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col8">1.38</oasis:entry>
         <oasis:entry colname="col9">ns</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Gram<inline-formula><mml:math id="M103" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula>/gram<inline-formula><mml:math id="M104" display="inline"><mml:msup><mml:mi/><mml:mo>-</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M105" display="inline"><mml:mrow><mml:mn mathvariant="normal">2.13</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M106" display="inline"><mml:mrow><mml:mn mathvariant="normal">1.99</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.04</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">5.10</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M107" display="inline"><mml:mo>∗</mml:mo></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">0.53</oasis:entry>
         <oasis:entry colname="col7">ns</oasis:entry>
         <oasis:entry colname="col8">1.25</oasis:entry>
         <oasis:entry colname="col9">ns</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Total microbial biomass</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M108" display="inline"><mml:mrow><mml:mn mathvariant="normal">27.19</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">1.66</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M109" display="inline"><mml:mrow><mml:mn mathvariant="normal">76.26</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">8.98</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">83.70</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M110" display="inline"><mml:mrow><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">2.58</oasis:entry>
         <oasis:entry colname="col7"><inline-formula><mml:math id="M111" display="inline"><mml:mo>∗</mml:mo></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col8">1.32</oasis:entry>
         <oasis:entry colname="col9">ns</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Saturated<inline-formula><mml:math id="M112" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula>unsaturated</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M113" display="inline"><mml:mrow><mml:mn mathvariant="normal">1.54</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.03</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M114" display="inline"><mml:mrow><mml:mn mathvariant="normal">1.38</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.04</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">12.19</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M115" display="inline"><mml:mrow><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">0.83</oasis:entry>
         <oasis:entry colname="col7">ns</oasis:entry>
         <oasis:entry colname="col8">1.43</oasis:entry>
         <oasis:entry colname="col9">ns</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Iso<inline-formula><mml:math id="M116" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula>anteiso</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M117" display="inline"><mml:mrow><mml:mn mathvariant="normal">7.35</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.48</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M118" display="inline"><mml:mrow><mml:mn mathvariant="normal">12.07</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.77</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">45.00</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M119" display="inline"><mml:mrow><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">4.50</oasis:entry>
         <oasis:entry colname="col7"><inline-formula><mml:math id="M120" display="inline"><mml:mrow><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col8">1.88</oasis:entry>
         <oasis:entry colname="col9">ns</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1"><?xmltex \currentcnt{1}?><?xmltex \def\figurename{Figure}?><label>Figure 1</label><caption><p id="d1e1895">Mean values (<inline-formula><mml:math id="M121" display="inline"><mml:mo lspace="0mm">±</mml:mo></mml:math></inline-formula> SE) of soil microbial biomass at 0, 20, 40,
60, 80 and 100 cm distance, respectively, from the trunk of <italic>Erica</italic> spp. The letters a, b, c and d indicate the significant differences between distances revealed by a least squares distance (LSD) test.</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://we.copernicus.org/articles/22/21/2022/we-22-21-2022-f01.png"/>

        </fig>

      <p id="d1e1915">ANOSIM examined similarities in the composition of the microbial communities
sampled at different distances from the base of <italic>Erica</italic> spp. in crusted and
uncrusted soils. The analysis revealed significant dissimilarities in
communities' composition in both coverage regimes (Table 2). Each soil point
has a distinct microbial community.</p>

<?xmltex \floatpos{p}?><table-wrap id="Ch1.T2" specific-use="star"><?xmltex \currentcnt{2}?><label>Table 2</label><caption><p id="d1e1924">ANOSIM (<inline-formula><mml:math id="M122" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> values) applied on individual PLFAs based on the Bray–Curtis index of similarity to detect dissimilarities in microbial community composition between different local communities (at different distances from the trunk of <italic>Erica</italic> spp. shrubs in crust-covered (<inline-formula><mml:math id="M123" display="inline"><mml:mo lspace="0mm">+</mml:mo></mml:math></inline-formula>BSC) and uncrusted (<inline-formula><mml:math id="M124" display="inline"><mml:mo lspace="0mm">-</mml:mo></mml:math></inline-formula>BSC) soils). For <inline-formula><mml:math id="M125" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> values <inline-formula><mml:math id="M126" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula> dissimilarities are statistically significant.</p></caption><oasis:table frame="topbot"><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>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M127" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>BSC</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M128" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>BCS</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M129" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>BSC</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M130" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>BSC</oasis:entry>
         <oasis:entry colname="col6"><inline-formula><mml:math id="M131" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>BSC</oasis:entry>
         <oasis:entry colname="col7"><inline-formula><mml:math id="M132" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>BSC</oasis:entry>
         <oasis:entry colname="col8"><inline-formula><mml:math id="M133" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>BSC</oasis:entry>
         <oasis:entry colname="col9"><inline-formula><mml:math id="M134" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>BCS</oasis:entry>
         <oasis:entry colname="col10"><inline-formula><mml:math id="M135" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>BSC</oasis:entry>
         <oasis:entry colname="col11"><inline-formula><mml:math id="M136" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>BSC</oasis:entry>
         <oasis:entry colname="col12"><inline-formula><mml:math id="M137" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>BSC</oasis:entry>
         <oasis:entry colname="col13"><inline-formula><mml:math id="M138" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>BSC</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">(0)</oasis:entry>
         <oasis:entry colname="col3">(20)</oasis:entry>
         <oasis:entry colname="col4">(40)</oasis:entry>
         <oasis:entry colname="col5">(60)</oasis:entry>
         <oasis:entry colname="col6">(80)</oasis:entry>
         <oasis:entry colname="col7">(100)</oasis:entry>
         <oasis:entry colname="col8">(0)</oasis:entry>
         <oasis:entry colname="col9">(20)</oasis:entry>
         <oasis:entry colname="col10">(40)</oasis:entry>
         <oasis:entry colname="col11">(60)</oasis:entry>
         <oasis:entry colname="col12">(80)</oasis:entry>
         <oasis:entry colname="col13">(100)</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1"><inline-formula><mml:math id="M139" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>BSC (0)</oasis:entry>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">0.008</oasis:entry>
         <oasis:entry colname="col4">0.008</oasis:entry>
         <oasis:entry colname="col5">0.008</oasis:entry>
         <oasis:entry colname="col6">0.007</oasis:entry>
         <oasis:entry colname="col7">0.008</oasis:entry>
         <oasis:entry colname="col8">0.008</oasis:entry>
         <oasis:entry colname="col9">0.007</oasis:entry>
         <oasis:entry colname="col10">0.006</oasis:entry>
         <oasis:entry colname="col11">0.007</oasis:entry>
         <oasis:entry colname="col12">0.006</oasis:entry>
         <oasis:entry colname="col13">0.007</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"><inline-formula><mml:math id="M140" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>BSC (20)</oasis:entry>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3"/>
         <oasis:entry colname="col4">0.007</oasis:entry>
         <oasis:entry colname="col5">0.009</oasis:entry>
         <oasis:entry colname="col6">0.009</oasis:entry>
         <oasis:entry colname="col7">0.007</oasis:entry>
         <oasis:entry colname="col8">0.008</oasis:entry>
         <oasis:entry colname="col9">0.016</oasis:entry>
         <oasis:entry colname="col10">0.008</oasis:entry>
         <oasis:entry colname="col11">0.007</oasis:entry>
         <oasis:entry colname="col12">0.008</oasis:entry>
         <oasis:entry colname="col13">0.008</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"><inline-formula><mml:math id="M141" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>BSC (40)</oasis:entry>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3"/>
         <oasis:entry colname="col4"/>
         <oasis:entry colname="col5">0.007</oasis:entry>
         <oasis:entry colname="col6">0.007</oasis:entry>
         <oasis:entry colname="col7">0.008</oasis:entry>
         <oasis:entry colname="col8">0.007</oasis:entry>
         <oasis:entry colname="col9">0.008</oasis:entry>
         <oasis:entry colname="col10">0.018</oasis:entry>
         <oasis:entry colname="col11">0.008</oasis:entry>
         <oasis:entry colname="col12">0.009</oasis:entry>
         <oasis:entry colname="col13">0.006</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"><inline-formula><mml:math id="M142" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>BSC (60)</oasis:entry>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3"/>
         <oasis:entry colname="col4"/>
         <oasis:entry colname="col5"/>
         <oasis:entry colname="col6">0.008</oasis:entry>
         <oasis:entry colname="col7">0.008</oasis:entry>
         <oasis:entry colname="col8">0.007</oasis:entry>
         <oasis:entry colname="col9">0.006</oasis:entry>
         <oasis:entry colname="col10">0.008</oasis:entry>
         <oasis:entry colname="col11">0.007</oasis:entry>
         <oasis:entry colname="col12">0.009</oasis:entry>
         <oasis:entry colname="col13">0.007</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"><inline-formula><mml:math id="M143" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>BSC (80)</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">0.008</oasis:entry>
         <oasis:entry colname="col8">0.007</oasis:entry>
         <oasis:entry colname="col9">0.008</oasis:entry>
         <oasis:entry colname="col10">0.006</oasis:entry>
         <oasis:entry colname="col11">0.007</oasis:entry>
         <oasis:entry colname="col12">0.023</oasis:entry>
         <oasis:entry colname="col13">0.009</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"><inline-formula><mml:math id="M144" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>BSC (100)</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">0.009</oasis:entry>
         <oasis:entry colname="col9">0.008</oasis:entry>
         <oasis:entry colname="col10">0.01</oasis:entry>
         <oasis:entry colname="col11">0.007</oasis:entry>
         <oasis:entry colname="col12">0.008</oasis:entry>
         <oasis:entry colname="col13">0.007</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"><inline-formula><mml:math id="M145" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>BSC (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">0.007</oasis:entry>
         <oasis:entry colname="col10">0.008</oasis:entry>
         <oasis:entry colname="col11">0.007</oasis:entry>
         <oasis:entry colname="col12">0.008</oasis:entry>
         <oasis:entry colname="col13">0.008</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"><inline-formula><mml:math id="M146" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>BSC (20)</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">0.007</oasis:entry>
         <oasis:entry colname="col11">0.008</oasis:entry>
         <oasis:entry colname="col12">0.009</oasis:entry>
         <oasis:entry colname="col13">0.008</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"><inline-formula><mml:math id="M147" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>BSC (40)</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">0.009</oasis:entry>
         <oasis:entry colname="col12">0.007</oasis:entry>
         <oasis:entry colname="col13">0.009</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"><inline-formula><mml:math id="M148" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>BSC (60)</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">0.008</oasis:entry>
         <oasis:entry colname="col13">0.006</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"><inline-formula><mml:math id="M149" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>BSC (80)</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"/>
         <oasis:entry colname="col13">0.007</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

</sec>
<sec id="Ch1.S3.SS3">
  <label>3.3</label><title>Enzyme activity</title>
      <p id="d1e2659">Similar to microbial abundances, no combined effect was detected for soil
enzymes as well. Almost all soil enzymes responded to coverage status (Table 3). The majority of them presented higher values in areas covered with BSC,
except LAP, which responded conversely. Distance affected only the activity of
urease; lower values were recorded at distances larger than 60 cm (Fig. 2).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2"><?xmltex \currentcnt{2}?><?xmltex \def\figurename{Figure}?><label>Figure 2</label><caption><p id="d1e2664">Mean values (<inline-formula><mml:math id="M150" display="inline"><mml:mo lspace="0mm">±</mml:mo></mml:math></inline-formula> SE) of urease activity at 0, 20, 40, 60, 80
and 100 cm distance, respectively, from the trunk of <italic>Erica</italic> spp. The letters a, b, c and d indicate the significant differences between distances revealed by an LSD test.</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://we.copernicus.org/articles/22/21/2022/we-22-21-2022-f02.png"/>

        </fig>

<?xmltex \floatpos{p}?><table-wrap id="Ch1.T3" specific-use="star"><?xmltex \currentcnt{3}?><label>Table 3</label><caption><p id="d1e2686">Mean values of enzyme activity (<inline-formula><mml:math id="M151" display="inline"><mml:mo lspace="0mm">±</mml:mo></mml:math></inline-formula> SE) and effect of crust
coverage (presence, <inline-formula><mml:math id="M152" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>BSC, and absence,<inline-formula><mml:math id="M153" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>BSC, of crust), distance (0, 20,
40, 60, 80 and 100 cm away from trunk of <italic>Erica</italic> spp.) and their interaction on soil
activity (AP: acid phosphomonoesterase; BG: b-glucosidase; POD: peroxidase;
PPO: polyphenol oxidase; NAG: N-acetylglucosaminidase; LAP:
leucine aminopeptidase; and UR: urease). The asterisk <inline-formula><mml:math id="M154" display="inline"><mml:mo>∗</mml:mo></mml:math></inline-formula> indicates the level
of significance (<inline-formula><mml:math id="M155" display="inline"><mml:mo lspace="0mm">∗</mml:mo></mml:math></inline-formula> <inline-formula><mml:math id="M156" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M157" display="inline"><mml:mrow><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M158" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M159" display="inline"><mml:mrow><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M160" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.001</mml:mn></mml:mrow></mml:math></inline-formula> and ns: not statistically significant).</p></caption><oasis:table frame="topbot"><?xmltex \begin{scaleboxenv}{.95}[.95]?><oasis:tgroup cols="9">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="right"/>
     <oasis:colspec colnum="3" colname="col3" align="right" colsep="1"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:colspec colnum="5" colname="col5" align="right" colsep="1"/>
     <oasis:colspec colnum="6" colname="col6" align="center"/>
     <oasis:colspec colnum="7" colname="col7" align="center" colsep="1"/>
     <oasis:colspec colnum="8" colname="col8" align="center"/>
     <oasis:colspec colnum="9" colname="col9" align="center"/>
     <oasis:thead>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry rowsep="1" namest="col2" nameend="col3" align="center" colsep="1">Mean values <inline-formula><mml:math id="M161" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> SE </oasis:entry>
         <oasis:entry rowsep="1" namest="col4" nameend="col5" align="center" colsep="1">Crust coverage </oasis:entry>
         <oasis:entry rowsep="1" namest="col6" nameend="col7" colsep="1">Distance </oasis:entry>
         <oasis:entry rowsep="1" namest="col8" nameend="col9">Crust coverage <inline-formula><mml:math id="M162" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> distance </oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Enzymes</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M163" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula>BSC</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M164" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>BSC</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M165" display="inline"><mml:mi>F</mml:mi></mml:math></inline-formula> ratio</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M166" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> level</oasis:entry>
         <oasis:entry colname="col6"><inline-formula><mml:math id="M167" display="inline"><mml:mi>F</mml:mi></mml:math></inline-formula> ratio</oasis:entry>
         <oasis:entry colname="col7"><inline-formula><mml:math id="M168" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> level</oasis:entry>
         <oasis:entry colname="col8"><inline-formula><mml:math id="M169" display="inline"><mml:mi>F</mml:mi></mml:math></inline-formula> ratio</oasis:entry>
         <oasis:entry colname="col9"><inline-formula><mml:math id="M170" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> level</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">AP (<inline-formula><mml:math id="M171" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">mol</mml:mi></mml:mrow></mml:math></inline-formula> pNP g<inline-formula><mml:math id="M172" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msup></mml:math></inline-formula> h<inline-formula><mml:math id="M173" 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>)</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M174" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.35</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.02</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M175" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.29</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.02</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">6.71</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M176" display="inline"><mml:mo>∗</mml:mo></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">2.39</oasis:entry>
         <oasis:entry colname="col7">ns</oasis:entry>
         <oasis:entry colname="col8">0.49</oasis:entry>
         <oasis:entry colname="col9">ns</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">BG (<inline-formula><mml:math id="M177" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">mol</mml:mi></mml:mrow></mml:math></inline-formula> pNP g<inline-formula><mml:math id="M178" 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> h<inline-formula><mml:math id="M179" 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>)</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M180" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.89</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.07</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M181" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.58</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.04</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">4.38</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M182" display="inline"><mml:mo>∗</mml:mo></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">1.05</oasis:entry>
         <oasis:entry colname="col7">ns</oasis:entry>
         <oasis:entry colname="col8">1.89</oasis:entry>
         <oasis:entry colname="col9">ns</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">POD (<inline-formula><mml:math id="M183" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">mol</mml:mi></mml:mrow></mml:math></inline-formula> L-DOPA g<inline-formula><mml:math id="M184" 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> soil h<inline-formula><mml:math id="M185" 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>)</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M186" display="inline"><mml:mrow><mml:mn mathvariant="normal">5.17</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.41</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M187" display="inline"><mml:mrow><mml:mn mathvariant="normal">2.36</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.23</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">35.10</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M188" display="inline"><mml:mrow><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">1.14</oasis:entry>
         <oasis:entry colname="col7">ns</oasis:entry>
         <oasis:entry colname="col8">0.75</oasis:entry>
         <oasis:entry colname="col9">ns</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">PPO (<inline-formula><mml:math id="M189" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">mol</mml:mi></mml:mrow></mml:math></inline-formula> L-DOPA g<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> soil h<inline-formula><mml:math id="M191" 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>)</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M192" display="inline"><mml:mrow><mml:mn mathvariant="normal">15.44</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.73</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M193" display="inline"><mml:mrow><mml:mn mathvariant="normal">15.09</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.81</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">0.10</oasis:entry>
         <oasis:entry colname="col5">ns</oasis:entry>
         <oasis:entry colname="col6">1.10</oasis:entry>
         <oasis:entry colname="col7">ns</oasis:entry>
         <oasis:entry colname="col8">0.78</oasis:entry>
         <oasis:entry colname="col9">ns</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">NAG (<inline-formula><mml:math id="M194" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">mol</mml:mi></mml:mrow></mml:math></inline-formula> pNP g<inline-formula><mml:math id="M195" 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> h<inline-formula><mml:math id="M196" 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>)</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M197" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.33</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M198" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.21</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">56.44</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M199" display="inline"><mml:mrow><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">1.04</oasis:entry>
         <oasis:entry colname="col7">ns</oasis:entry>
         <oasis:entry colname="col8">1.85</oasis:entry>
         <oasis:entry colname="col9">ns</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">LAP (<inline-formula><mml:math id="M200" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">mol</mml:mi></mml:mrow></mml:math></inline-formula> leucine g<inline-formula><mml:math id="M201" 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> h<inline-formula><mml:math id="M202" 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></oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M203" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.19</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.02</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M204" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.29</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.03</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">8.42</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M205" display="inline"><mml:mrow><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">1.81</oasis:entry>
         <oasis:entry colname="col7">ns</oasis:entry>
         <oasis:entry colname="col8">1.93</oasis:entry>
         <oasis:entry colname="col9">ns</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">UR (<inline-formula><mml:math id="M206" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">mol</mml:mi></mml:mrow></mml:math></inline-formula> NH<inline-formula><mml:math id="M207" 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> g<inline-formula><mml:math id="M208" 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> h<inline-formula><mml:math id="M209" 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></oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M210" display="inline"><mml:mrow><mml:mn mathvariant="normal">1.85</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.09</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M211" display="inline"><mml:mrow><mml:mn mathvariant="normal">1.07</mml:mn><mml:mo>±</mml:mo><mml:mn mathvariant="normal">0.09</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">55.44</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M212" display="inline"><mml:mrow><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">6.97</oasis:entry>
         <oasis:entry colname="col7"><inline-formula><mml:math id="M213" display="inline"><mml:mrow><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo><mml:mo>∗</mml:mo></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col8">0.51</oasis:entry>
         <oasis:entry colname="col9">ns</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup><?xmltex \end{scaleboxenv}?></oasis:table></table-wrap>

</sec>
<sec id="Ch1.S3.SS4">
  <label>3.4</label><title>Microbial networks</title>
      <p id="d1e3602">The networks in soils covered only by <italic>Erica</italic> spp. (<inline-formula><mml:math id="M214" display="inline"><mml:mo lspace="0mm">-</mml:mo></mml:math></inline-formula>BSC) showed a gradual increase
in their topological features, with the exception of the shortest path as the
distance from the trunk increased (Table 4). The network recorded at the
distance until 20 cm was the least connected, exhibiting the lowest values in
the estimates of density, compactness and weighted clustering coefficient and
the highest value of the shortest path compared to the values recorded in
networks of distances larger than 20 cm. The high value of the shortest path
denotes mainly indirect connections between the nodes. Contrary to the
networks recorded in uncrusted soils, in crusted ones (<inline-formula><mml:math id="M215" display="inline"><mml:mo lspace="0mm">+</mml:mo></mml:math></inline-formula>BSC) the most
connected network was that at a distance of 0–20 cm. This network presented the
highest density and weighted clustering coefficient and the lowest average
shortest path compared to networks recorded at distances larger than 20 cm.
As concerns the small-worldness index, its highest value (5.11) was
estimated for the network in crusted soil at 40 cm. Small values of the
small-worldness index were recorded in almost all networks, while the network in
uncrusted soil at distances larger than 60 cm did not show characteristics
of small-worldness.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T4" specific-use="star"><?xmltex \currentcnt{4}?><label>Table 4</label><caption><p id="d1e3625">Values of certain global metrics estimated for the network of interactions between individual PLFAs under two crust coverage regimes at successive distances from the trunk to the periphery of <italic>Erica</italic> spp. shrubs. Comparisons of metrics with those produced by random networks with the same number of ties and nodes are also presented. In all cases the differences between real (underlined values) and random (Ran) networks were significant, with the exception of average distance and compactness estimated for uncrusted soils at a distance of 60–100 cm.</p></caption><oasis:table frame="topbot"><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" colsep="1"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:colspec colnum="5" colname="col5" align="right" colsep="1"/>
     <oasis:colspec colnum="6" colname="col6" align="right"/>
     <oasis:colspec colnum="7" colname="col7" align="right" colsep="1"/>
     <oasis:colspec colnum="8" colname="col8" align="right"/>
     <oasis:colspec colnum="9" colname="col9" align="right" colsep="1"/>
     <oasis:colspec colnum="10" colname="col10" align="right"/>
     <oasis:colspec colnum="11" colname="col11" align="right" colsep="1"/>
     <oasis:colspec colnum="12" colname="col12" align="right"/>
     <oasis:colspec colnum="13" colname="col13" align="right"/>
     <oasis:thead>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry rowsep="1" namest="col2" nameend="col7" align="center" colsep="1">Crust-covered soils </oasis:entry>
         <oasis:entry rowsep="1" namest="col8" nameend="col13" align="center">Uncrusted soils </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry rowsep="1" namest="col2" nameend="col3" align="center" colsep="1">0–20 cm </oasis:entry>
         <oasis:entry rowsep="1" namest="col4" nameend="col5" align="center" colsep="1">40 cm </oasis:entry>
         <oasis:entry rowsep="1" namest="col6" nameend="col7" align="center" colsep="1">60–100 cm </oasis:entry>
         <oasis:entry rowsep="1" namest="col8" nameend="col9" align="center" colsep="1">0–20 cm </oasis:entry>
         <oasis:entry rowsep="1" namest="col10" nameend="col11" align="center" colsep="1">40 cm </oasis:entry>
         <oasis:entry rowsep="1" namest="col12" nameend="col13" align="center">60–100 cm </oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">Real</oasis:entry>
         <oasis:entry colname="col3">Ran</oasis:entry>
         <oasis:entry colname="col4">Real</oasis:entry>
         <oasis:entry colname="col5">Ran</oasis:entry>
         <oasis:entry colname="col6">Real</oasis:entry>
         <oasis:entry colname="col7">Ran</oasis:entry>
         <oasis:entry colname="col8">Real</oasis:entry>
         <oasis:entry colname="col9">Ran</oasis:entry>
         <oasis:entry colname="col10">Real</oasis:entry>
         <oasis:entry colname="col11">Ran</oasis:entry>
         <oasis:entry colname="col12">Real</oasis:entry>
         <oasis:entry colname="col13">Ran</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">Density</oasis:entry>
         <oasis:entry colname="col2"><underline>0.53</underline></oasis:entry>
         <oasis:entry colname="col3"/>
         <oasis:entry colname="col4"><underline>0.27</underline></oasis:entry>
         <oasis:entry colname="col5"/>
         <oasis:entry colname="col6"><underline>0.35</underline></oasis:entry>
         <oasis:entry colname="col7"/>
         <oasis:entry colname="col8"><underline>0.25</underline></oasis:entry>
         <oasis:entry colname="col9"/>
         <oasis:entry colname="col10"><underline>0.54</underline></oasis:entry>
         <oasis:entry colname="col11"/>
         <oasis:entry colname="col12"><underline>0.74</underline></oasis:entry>
         <oasis:entry colname="col13"/>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Shortest path</oasis:entry>
         <oasis:entry colname="col2"><underline>1.18</underline></oasis:entry>
         <oasis:entry colname="col3">1.47</oasis:entry>
         <oasis:entry colname="col4"><underline>1.25</underline></oasis:entry>
         <oasis:entry colname="col5">1.92</oasis:entry>
         <oasis:entry colname="col6"><underline>1.82</underline></oasis:entry>
         <oasis:entry colname="col7">1.71</oasis:entry>
         <oasis:entry colname="col8"><underline>2.32</underline></oasis:entry>
         <oasis:entry colname="col9">1.99</oasis:entry>
         <oasis:entry colname="col10"><underline>1.37</underline></oasis:entry>
         <oasis:entry colname="col11">1.46</oasis:entry>
         <oasis:entry colname="col12"><underline>1.28</underline></oasis:entry>
         <oasis:entry colname="col13">1.26</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Compactness</oasis:entry>
         <oasis:entry colname="col2"><underline>0.59</underline></oasis:entry>
         <oasis:entry colname="col3">0.77</oasis:entry>
         <oasis:entry colname="col4"><underline>0.31</underline></oasis:entry>
         <oasis:entry colname="col5">0.60</oasis:entry>
         <oasis:entry colname="col6"><underline>0.55</underline></oasis:entry>
         <oasis:entry colname="col7">0.66</oasis:entry>
         <oasis:entry colname="col8"><underline>0.46</underline></oasis:entry>
         <oasis:entry colname="col9">0.58</oasis:entry>
         <oasis:entry colname="col10"><underline>0.69</underline></oasis:entry>
         <oasis:entry colname="col11">0.77</oasis:entry>
         <oasis:entry colname="col12"><underline>0.87</underline></oasis:entry>
         <oasis:entry colname="col13">0.87</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Weighted clustering</oasis:entry>
         <oasis:entry colname="col2"><underline>0.89</underline></oasis:entry>
         <oasis:entry colname="col3">0.53</oasis:entry>
         <oasis:entry colname="col4"><underline>0.87</underline></oasis:entry>
         <oasis:entry colname="col5">0.26</oasis:entry>
         <oasis:entry colname="col6"><underline>0.75</underline></oasis:entry>
         <oasis:entry colname="col7">0.34</oasis:entry>
         <oasis:entry colname="col8"><underline>0.65</underline></oasis:entry>
         <oasis:entry colname="col9">0.24</oasis:entry>
         <oasis:entry colname="col10"><underline>0.81</underline></oasis:entry>
         <oasis:entry colname="col11">0.54</oasis:entry>
         <oasis:entry colname="col12"><underline>0.85</underline></oasis:entry>
         <oasis:entry colname="col13">0.74</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Coefficient</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"/>
         <oasis:entry colname="col13"/>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Small-worldness (SW)</oasis:entry>
         <oasis:entry colname="col2"><underline>2.00</underline></oasis:entry>
         <oasis:entry colname="col3"/>
         <oasis:entry colname="col4"><underline>5.11</underline></oasis:entry>
         <oasis:entry colname="col5"/>
         <oasis:entry colname="col6"><underline>1.96</underline></oasis:entry>
         <oasis:entry colname="col7"/>
         <oasis:entry colname="col8"><underline>2.44</underline></oasis:entry>
         <oasis:entry colname="col9"/>
         <oasis:entry colname="col10"><underline>1.67</underline></oasis:entry>
         <oasis:entry colname="col11"/>
         <oasis:entry colname="col12"><underline>1.16</underline></oasis:entry>
         <oasis:entry colname="col13"/>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

</sec>
</sec>
<sec id="Ch1.S4">
  <label>4</label><title>Discussion</title>
      <p id="d1e4028">Biological crusts play an important role in plants' establishment and growth
and vice versa. In this study, we examined the influence of the interplay
between <italic>Cladonia rangiformis</italic> and <italic>Erica</italic> spp. and whether the spatial heterogeneity created by their
interactions affected the biomass, the composition and the network of
interactions among the members of the soil microbial communities. Soil water
content was higher in areas covered by BSC than in those where biocrust was
absent. By definition, BSC is a cohesive layer that can retain higher levels
of moisture (Pointing and Belnap, 2012). Although it is frequently reported
that BSCs resulted in significant stocks of soil C and N in arid and
semiarid areas (Chamizo et al., 2012), this was not reported in this study.
Gao et al. (2010) found that BSCs had no effect on these parameters at deep
soil depths, suggesting that the effect of BSCs on soil carbon and nitrogen
is restricted to the upper soil layer (up to 5 cm). This is probably the
explanation for the lack of effect in our study since the samples were
collected from the upper 10 cm of the soil.</p>
      <p id="d1e4037">The saturated<inline-formula><mml:math id="M216" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula>unsaturated ratio is indicative of the concentration of carbon
or nutrients in the soil and increases as the concentration of nutrients
decreases (Fierer et al., 2003). This ratio was higher in soils covered both
by <italic>Erica</italic> and BSCs, denoting possible nutrient limitation in these soils and
implying competition between <italic>C. rangiformis</italic>, <italic>Erica</italic> shrubs and soil microbes for nutrient
uptake. It seems that, although biological crusts are known for their
ability to fix atmospheric N, a fact that was in agreement with the higher
organic N recorded at the base of the shrubs (0 cm distance) in crusted
soils, this was not adequate to alleviate nutrient limitations.
Further, the changes in saturated<inline-formula><mml:math id="M217" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula>unsaturated ratio could indicate changes
in the composition of the microbial community. A positive relation between
the gram<inline-formula><mml:math id="M218" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup><mml:mo>/</mml:mo></mml:mrow></mml:math></inline-formula>gram<inline-formula><mml:math id="M219" display="inline"><mml:msup><mml:mi/><mml:mo>-</mml:mo></mml:msup></mml:math></inline-formula> ratio and the saturated<inline-formula><mml:math id="M220" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula>unsatured ratio was
mentioned by Konstantinou et al. (2019) and is based on the fact that most
gram-positive bacteria contain saturated PLFAs (Cho and Salton, 1966). The
changes in community composition were supported by changes in the
gram<inline-formula><mml:math id="M221" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup><mml:mo>/</mml:mo></mml:mrow></mml:math></inline-formula>gram<inline-formula><mml:math id="M222" display="inline"><mml:msup><mml:mi/><mml:mo>-</mml:mo></mml:msup></mml:math></inline-formula> ratio, which was increased in crusted soils. This
increase could be attributed to the decreased C availability or the
exhaustion of labile substrates (Fanin et al., 2019). Given that the area is
covered by the drought-tolerant evergreen sclerophyllous <italic>Erica</italic> spp., which
exhibit slow rates of nutrient recycling (Mediavilla and Escudero, 2003),
the low labile carbon in crusted soils could be attributed to consumption of
labile C by the BSC microorganisms. The latter, in combination with the
fact that through fungal metabolism lichens produce phenolic compounds which
are considered recalcitrant, could explain the increase in the gram<inline-formula><mml:math id="M223" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup><mml:mo>/</mml:mo></mml:mrow></mml:math></inline-formula>gram<inline-formula><mml:math id="M224" display="inline"><mml:msup><mml:mi/><mml:mo>-</mml:mo></mml:msup></mml:math></inline-formula> ratio. Furthermore, other possible explanations for the increased
gram<inline-formula><mml:math id="M225" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup><mml:mo>/</mml:mo></mml:mrow></mml:math></inline-formula>gram<inline-formula><mml:math id="M226" display="inline"><mml:msup><mml:mi/><mml:mo>-</mml:mo></mml:msup></mml:math></inline-formula> ratio could be due to the resistant (against exogenous
factors) cell wall of gram<inline-formula><mml:math id="M227" display="inline"><mml:msup><mml:mi/><mml:mo>+</mml:mo></mml:msup></mml:math></inline-formula> bacteria (Rohde, 2019) that protects
bacteria from the excretions of the lichen.</p>
      <p id="d1e4168">In crusted soils significantly lower values of the iso<inline-formula><mml:math id="M228" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula>anteiso ratio
were recorded, implying better abiotic conditions (temperature, humidity)
compared to uncrusted ones since a high value of this ratio is generally used
as an environmental stress indicator (Pettersson and Baath, 2003). Bacteria
could decrease the content of anteiso fatty acids when growing under adverse
conditions to decrease the viscosity of their cytoplasmic membranes. The
high values of the ratio in uncrusted soils could be the result of the harsh
temperature or moisture conditions prevailing in these soils. In fact, the
water content in uncrusted soils was half of those in crusted ones.</p>
      <p id="d1e4178">Despite better abiotic conditions prevailing in crusted soils, microbial
biomasses were almost 4 times lower compared to soils covered only with
<italic>Erica</italic> shrubs. The latter contrasts literature data reporting a positive relation between the abundance of microorganisms and the presence of BSC (Guan et
al., 2018) in arid and semiarid soils due to crusts' influence on the
distribution of soil moisture. Therefore, the reduction in microbial
biomasses in the present study may be explained as a negative by-product of
<italic>Cladonia</italic> activity. It is thought that the allelochemicals' secondary metabolites of
this organism containing aliphatic, aromatic and terpenoid halogenated
components are involved in various chemical interactions, responsible for
their antimicrobial properties (Kosanić et al., 2014). This idea is
reinforced by a number of studies that show the negative effect of these
lichens' substances on the biomass of soil microbes, tested both in the
field and the laboratory (Pandey, 2017; Kalra et al., 2021).</p>
      <p id="d1e4188">Soil enzyme activity displayed an opposite pattern compared to that of
microbial biomass, with higher values in crusted soils except for LAP and
PPO. Besides, it is well documented that enzymes originate from a variety of
sources such as living and dead microbes, plant roots, residues and soil
animals (Sun et al., 2013). Thus, enzyme activity is not necessarily
associated with microbial biomass. Ghiloufi et al. (2019) has reported that
enzyme activity is high in soils covered by BSC because in most cases the
presence of crusts is associated with high soil moisture, nutrients and
organic matter content. In our study, by the inspection of
the saturated<inline-formula><mml:math id="M229" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula>unsaturated ratio we identified nutrient limitation in soils
covered by crust and <italic>Erica</italic> shrubs. Hence, soil microbial communities possibly
produced enzymes for substrate degradation to increase nutrient availability
for their nutritional needs according to the nutrient allocation theory
(Allison and Vitousek, 2005). Also, if we consider the enzyme activity per
unit of microbial biomass, this was much higher in the microbes of crusted
soils, indicating more metabolically active microbial communities. The latter
could be partially supported by the better abiotic conditions prevailing in
these soils.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3" specific-use="star"><?xmltex \currentcnt{3}?><?xmltex \def\figurename{Figure}?><label>Figure 3</label><caption><p id="d1e4203">Network of interactions among the members of the soil microbial
community (various PLFA biomarkers) under two crust coverage regimes, along
a straight line of 100 cm at successive distances from the trunk to the
periphery of <italic>Erica</italic> spp. shrubs. The size of each node represents its eigenvector
centrality; the larger the node the higher the eigenvector centrality and
the higher the influence of the corresponding node.</p></caption>
        <?xmltex \igopts{width=369.885827pt}?><graphic xlink:href="https://we.copernicus.org/articles/22/21/2022/we-22-21-2022-f03.png"/>

      </fig>

      <p id="d1e4215">It is interesting that spatial heterogeneity had a limited effect on microbial
biomasses and enzyme activity. We observed a common pattern concerning the
effect of distances on the microbial biomass, regardless of the presence of
BSC. The microbial groups that were affected negatively by shrub presence
were bacteria and actinomycetes, which displayed the lowest biomass at 0 cm
distance from the shrubs and the highest at 40 cm. The fact that bacteria
exhibited some kind of spatial heterogeneity is probably related to their
limited ability to move and absorb nutrients. The active modes of their
dispersal are limited to the scale of (connected) soil pores or aggregates
(Yang and van Elsas, 2018). In contrast, the hyphal growth form of fungi
likely conveys several advantages to these organisms, chief of which is the
translocation of nutrients and resources from microsites where they are
abundant to sites where they are limiting (Frey et al., 2003). As concerns
the decrease in total microbial biomass at the shrub base, this could be
attributed to the roots' increased density underneath the trunk, resulting
in stronger competition for nutrients. Furthermore, phenolic compounds, which
seem to have antimicrobial effects, are abundant in <italic>Ericaceae</italic> species (Malik, 1995).
In some <italic>Ericaceae</italic> species such as <italic>E. andevalensis</italic>, a variety of phenols and flavonoids have been
isolated and have proven to have allelopathic antimicrobial activity
(Marquez-Garcia et al., 2009). Also, it has been found that this plant
requires an acidic soil environment for its growth; however, this
characteristic may provoke a quite inhospitable environment for the majority
of soil microorganisms (Vazquez et al., 2020).</p>
      <p id="d1e4227">Beside quantitative measurements such as biomass and activity that displayed
limited spatial heterogeneity, the composition of the local microbial
communities was totally different from one point to another. At each soil
point along a line of 100 cm from the trunk to the periphery of the shrubs,
unique microbial communities were identified. This can be viewed as an
effect of the fine-grained mosaic that characterizes the Mediterranean
ecosystems (Stamou, 1998). The effect of spatial heterogeneity was mirrored
at the microbial network topological features as well. The network in the
area without cover (bare soils; Fig. 3f) was very well organized; the crust
itself resulted in network fragmentation (Fig. 3c) probably due to released
antimicrobial substances that acted selectively to the members of the
microbial communities. Through negative effects on microbes, because of the
acid soil environment and allelochemical substances contained in litter, the
network in areas with only <italic>Erica</italic> seems to have collapsed (Fig. 3d). Remarkably,
when both <italic>Erica</italic> and crust acted together (Fig. 3a), the microbial network was
organized quite well as if the selective action of the crust on microbes were
compensated by the selective action of <italic>Erica</italic> spp. or the opposite. Also, by
comparing the networks in Fig. 3a and f we observed that the substances
leached by <italic>Erica</italic> spp. and crust acted much more selectively for the microbial
interactions than the adverse abiotic conditions prevailing in bare soil.
The well-organized network in soils uncovered by <italic>Erica</italic> and crust soils with a high number
of direct interconnections of relatively high intensity reflects a
microbial community adapted to adverse abiotic conditions of the
Mediterranean areas (Stamou et al., 1998). However, this was the only network
that did not show characteristics of small-worldness. According to Peng et
al. (2016) there is a trade-off between small-worldness and robustness.
Thus, the organization of interactions between the members of the microbial
communities in Mediterranean bare soils revealed them as the more robust.
For these communities the risk of transition from stability to instability
in the case of future disturbances such as trampling, fire or extreme
watering is low. A similar response was reported by Papatheodorou et al. (2020) for the same Mediterranean area; the composition and the biomass of
soil microbial communities in bare soils showed higher resistance to
frequent-watering events than the communities in crust-covered soils.</p>
</sec>
<sec id="Ch1.S5" sec-type="conclusions">
  <label>5</label><title>Conclusions</title>
      <p id="d1e4254">We studied the effect of the spatial heterogeneity created by the crust <italic>C. rangiformis</italic> and
the shrub <italic>Erica </italic>spp. on microbial biomass, community composition, network of
interactions and enzyme activity in the soil. The quantitative measurements
such as biomass and activity showed limited and no response to spatial
heterogeneity, respectively; they changed mainly in relation to coverage
regime. In contrast, the qualitative characteristics of the microbial
communities such as their composition and networks' topology confirmed the
idea of a fine-grained mosaic existing in the Mediterranean areas within
distances of a few centimeters. Although the most well-organized and robust
network was that in bare soils, it seems that <italic>Erica</italic> spp. and crust coverage acted
in concert and conditioned the development of more connected networks compared
to that produced by each agent alone. The interactions between soil
microbial community, soil functionality, BSC and local vegetation are
particularly complex. Hence, a multifaceted approach is recommended where
qualitative and quantitative aspects are examined jointly.</p>
</sec>

      
      </body>
    <back><notes notes-type="dataavailability"><title>Data availability</title>

      <p id="d1e4270">The data are original and have been produced during this study. They are available at a public GitHub repository under the MIT license: <ext-link xlink:href="https://doi.org/10.5281/zenodo.6411849" ext-link-type="DOI">10.5281/zenodo.6411849</ext-link> (papatheo1, 2022).</p>
  </notes><app-group>
        <supplementary-material position="anchor"><p id="d1e4276">The supplement related to this article is available online at: <inline-supplementary-material xlink:href="https://doi.org/10.5194/we-22-21-2022-supplement" xlink:title="pdf">https://doi.org/10.5194/we-22-21-2022-supplement</inline-supplementary-material>.</p></supplementary-material>
        </app-group><notes notes-type="authorcontribution"><title>Author contributions</title>

      <p id="d1e4285">TD and PDK conducted the soil analyses and wrote the original draft; NM analyzed the data; GPS and EMP conceived and designed the study; EMP wrote and edited the paper.</p>
  </notes><notes notes-type="competinginterests"><title>Competing interests</title>

      <p id="d1e4291">The contact author has declared that neither they nor their co-authors have any competing interests.</p>
  </notes><notes notes-type="disclaimer"><title>Disclaimer</title>

      <p id="d1e4297">Publisher’s note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p>
  </notes><notes notes-type="sistatement"><title>Special issue statement</title>

      <p id="d1e4303">This article is part of the special issue “Biological soil crusts”. It is not associated with a conference.</p>
  </notes><ack><title>Acknowledgements</title><p id="d1e4309">We would like to thank Eleni Zimvrakaki from the School of Agriculture,
Aristotle University of Thessaloniki, for her contribution to PLFA analysis.</p></ack><notes notes-type="reviewstatement"><title>Review statement</title>

      <p id="d1e4314">This paper was edited by Laura Concostrina-Zubiri and reviewed by two anonymous referees.</p>
  </notes><ref-list>
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