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<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">
  <front>
    <journal-meta><journal-id journal-id-type="publisher">ESSD</journal-id><journal-title-group>
    <journal-title>Earth System Science Data</journal-title>
    <abbrev-journal-title abbrev-type="publisher">ESSD</abbrev-journal-title><abbrev-journal-title abbrev-type="nlm-ta">Earth Syst. Sci. Data</abbrev-journal-title>
  </journal-title-group><issn pub-type="epub">1866-3516</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/essd-12-293-2020</article-id><title-group><article-title>Multi-scale data on intertidal macrobenthic<?xmltex \hack{\break}?> biodiversity and environmental features in<?xmltex \hack{\break}?> three New Zealand harbours</article-title><alt-title>Multi-scale data on intertidal macrobenthic biodiversity</alt-title>
      </title-group><?xmltex \runningtitle{Multi-scale data on intertidal macrobenthic biodiversity}?><?xmltex \runningauthor{C. Kraan et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1 aff2 aff5">
          <name><surname>Kraan</surname><given-names>Casper</given-names></name>
          <email>casper.kraan@thuenen.de</email>
        <ext-link>https://orcid.org/0000-0003-2062-6222</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Greenfield</surname><given-names>Barry L.</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4">
          <name><surname>Thrush</surname><given-names>Simon F.</given-names></name>
          
        </contrib>
        <aff id="aff1"><label>1</label><institution>Helmholtz Institute for Functional Marine Biodiversity at the
University of Oldenburg,<?xmltex \hack{\break}?> Ammerländer Heerstraße 231, 23129 Oldenburg, Germany</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>Department of Functional Ecology, Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>National Institute of Water and Atmospheric Research, P.O. Box 11-115, Hamilton 3216, New Zealand</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>Institute of Marine Science, University of Auckland, Private Bag
92019, Auckland 1142, New Zealand</institution>
        </aff>
        <aff id="aff5"><label>a</label><institution>currently at: Thünen Institute of Sea Fisheries,
Herwigstraße 31, 27572 Bremerhaven, Germany</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Casper Kraan (casper.kraan@thuenen.de)</corresp></author-notes><pub-date><day>10</day><month>February</month><year>2020</year></pub-date>
      
      <volume>12</volume>
      <issue>1</issue>
      <fpage>293</fpage><lpage>297</lpage>
      <history>
        <date date-type="received"><day>27</day><month>August</month><year>2019</year></date>
           <date date-type="rev-request"><day>16</day><month>September</month><year>2019</year></date>
           <date date-type="rev-recd"><day>19</day><month>January</month><year>2020</year></date>
           <date date-type="accepted"><day>21</day><month>January</month><year>2020</year></date>
      </history>
      <permissions>
        <copyright-statement>Copyright: © 2020 Casper Kraan et al.</copyright-statement>
        <copyright-year>2020</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://essd.copernicus.org/articles/12/293/2020/essd-12-293-2020.html">This article is available from https://essd.copernicus.org/articles/12/293/2020/essd-12-293-2020.html</self-uri><self-uri xlink:href="https://essd.copernicus.org/articles/12/293/2020/essd-12-293-2020.pdf">The full text article is available as a PDF file from https://essd.copernicus.org/articles/12/293/2020/essd-12-293-2020.pdf</self-uri>
      <abstract><title>Abstract</title>
    <p id="d1e132">Understanding how the plants and animals that live in the
sea floor vary in their spatial patterns of diversity and abundance is
fundamental to gaining insight into the role of biodiversity in maintaining
ecosystem functioning in coastal ecosystems, as well as advancing the
modelling of species distributions under realistic assumptions. Yet, it is
virtually unknown how the relationships between abundance patterns and
different biotic and environmental processes change depending on spatial
scales, which is mainly due to a lack of data. Within the project Spatial
Organization of Species Distributions: Hierarchical and Scale-Dependent
Patterns and Processes in Coastal Seascapes at the National Institute for
Water and Atmospheric Research (NIWA) in New Zealand we collected
multi-scale and high-resolution data on macrobenthic biodiversity. We found
146 species dominated by bivalves, polychaetes, and crustaceans
(<inline-formula><mml:math id="M1" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">500</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M2" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m) that live hidden in marine sandflats and
collected point measurements of important environmental variables (sediment
grain-size distributions, chlorophyll <inline-formula><mml:math id="M3" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula> concentration, organic content, and
visible sandflat parameters) in three large intertidal harbours (Kaipara,
Tauranga, and Manukau). In each harbour we sampled 400 points for
macrobenthic community composition and abundances, as well as the full set
of environmental variables. Using an elaborate sampling design, we were able
to cover scales from 30  cm to a maximal extent of 1 km. All data
and extensive metadata are available from the data publisher PANGAEA via the
persistent identifier <ext-link xlink:href="https://doi.org/10.1594/PANGAEA.903448" ext-link-type="DOI">10.1594/PANGAEA.903448</ext-link> (Kraan et al.,
2019).</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <label>1</label><title>Introduction</title>
      <p id="d1e172">Understanding how the plants and animals that live in the sea floor vary in
their spatial patterns of diversity, biomass, and abundance is fundamental
to gaining insight into the role of biodiversity in maintaining ecosystem
functioning in coastal ecosystems, as well as advancing the modelling of
species distributions under realistic assumptions. Yet, it is virtually
unknown how the relationships between abundance patterns and different
biotic and environmental processes change depending on spatial scales (e.g.
Lohrer et al., 2015; Kraan et al., 2015).</p>
      <p id="d1e175">Most broad-scale research on mapping species distributions ignores spatial
patterns (Kraan et al., 2010), scale-dependent variability (Kraan et al.,
2015), and biotic interactions (Dormann et al., 2018), rendering these
topics a main frontier in ecology (Araújo and Luoto, 2007). Moreover,
twisting these often separate lines of research together requires the
availability of data to support such research. At present, data that allow
for bridging the gap between<?pagebreak page294?> small-scale and landscape-scale ecological
research, enabling a full inference of patterns and processes from the individual
to the landscape scale across environmental gradients, are scarce.</p>
      <p id="d1e178">The research project Spatial Organization of Species Distributions:
Hierarchical and Scale-Dependent Patterns and Processes in Coastal Seascapes
at the National Institute for Water and Atmospheric Research (NIWA) in New
Zealand aimed to assess scale-dependent variation in species distributions
across environmental gradients in estuarine communities dominated by
bivalves, polychaetes, and crustaceans that live hidden in marine sandflats.
By employing an elaborate sampling scheme, we covered a large number of
different spatial scales with enough replicate samples within each scale to
allow for explicit spatial analysis and warrant statistical power during
analysis (see Kraan et al., 2015; Greenfield et al., 2016). This efficient
sampling design allowed us to map intertidal macrobenthic fauna from the
scale of a few centimetres to a maximal extent of 1 km. We focussed on
macrobenthos (organisms <inline-formula><mml:math id="M4" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">500</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M5" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m) due to their role in
ecosystem functioning (e.g. Thrush et al., 2017), their ability to serve as
sentinels for change (e.g. Hewitt and Thrush, 2009; Kraan et al., 2009), and
the relative ease of collecting samples (Fig. 1). To increase the generality
of our field study, we performed this sampling along an environmental
gradient from the mangroves to the lower end of the intertidal zone in three
large intertidal harbours (Manukau, Kaipara, and Tauranga harbours in the
North Island, New Zealand).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1"><?xmltex \currentcnt{1}?><label>Figure 1</label><caption><p id="d1e202"><bold>(a)</bold> Example of a sampling area during low tide and the low-tech
gear used for sampling. Examples of <bold>(b)</bold> a high-density seagrass sampling
point and <bold>(c)</bold> a sandy sampling point (photos: Casper Kraan).</p></caption>
        <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://essd.copernicus.org/articles/12/293/2020/essd-12-293-2020-f01.jpg"/>

      </fig>

      <p id="d1e219"><?xmltex \hack{\newpage}?>Given the scarcity of large-scale high-resolution biodiversity data
identified to the lowest taxonomic level possible, as well as associated
point measurements of environmental features like sediment grain-size
parameters, chlorophyll <inline-formula><mml:math id="M6" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula> concentration, organic content, and visible
sandflat parameters, such as the coverage of seagrass or shell hash (broken
shell fragments), we publish these one-of-a-kind data (see Kraan et
al., 2019) here so that they can serve as key data to advance and support future
multi-scale biodiversity studies.</p>
</sec>
<sec id="Ch1.S2">
  <label>2</label><title>Material and methods</title>
<sec id="Ch1.S2.SS1">
  <label>2.1</label><title>Fieldwork</title>
      <p id="d1e245">Sampling of macrobenthic fauna and environmental variables was conducted during
austral summer 2012 in Kaipara, Manukau, and Tauranga harbours, North
Island, New Zealand (Table 1). Physical descriptions of each of these areas
can be sourced from a large number of publications by Simon F. Thrush and
co-workers (e.g. Thrush et al., 2003). In each harbour we took 400 cores (13 cm diameter, 20 cm deep) on a predetermined grid (four 1000 m transects, spaced
at 100 m) on foot during low tide (<inline-formula><mml:math id="M7" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">3</mml:mn><mml:mo>⋅</mml:mo><mml:mn mathvariant="normal">400</mml:mn></mml:mrow></mml:math></inline-formula>; 1200 in total), thereby
covering the area from the high- to low-water mark (Fig. 1 for an
illustration). Sampling points along transects were spaced at distances of
30 cm, 1 m, 5 m, 10 m, 30 m, 50 m, 100 m, 500 m, and 1000 m (see Fig. 1 in
Kraan et al., 2015), located by using a measuring tape and handheld GPS. Given
the close proximity of sampling locations we provide sampling coordinates in
NZTM (New Zealand Transverse Mercator; Geodetic CRS: NZGD2000; unit: metres)
at the data publisher PANGAEA (Kraan et al., 2019). Cores were sieved in the
field (500 <inline-formula><mml:math id="M8" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m mesh) and the residue preserved with 70 % isopropyl
alcohol.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T1" specific-use="star"><?xmltex \currentcnt{1}?><label>Table 1</label><caption><p id="d1e275">Regional summary of collected data and their mean values to give an
impression of their physical appearance and the macrobenthic benthic
biodiversity they harbour.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="4">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="left"/>
     <oasis:colspec colnum="4" colname="col4" align="left"/>
     <oasis:thead>
       <oasis:row>
         <oasis:entry colname="col1">Fieldwork 2012</oasis:entry>
         <oasis:entry rowsep="1" namest="col2" nameend="col4" align="center">Region </oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">Manukau</oasis:entry>
         <oasis:entry colname="col3">Tauranga</oasis:entry>
         <oasis:entry colname="col4">Kaipara</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">Sampling</oasis:entry>
         <oasis:entry colname="col2">4–5 May</oasis:entry>
         <oasis:entry colname="col3">23–25 April</oasis:entry>
         <oasis:entry colname="col4">18–19 April</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Sediment samples (<inline-formula><mml:math id="M9" display="inline"><mml:mi>n</mml:mi></mml:math></inline-formula>)</oasis:entry>
         <oasis:entry colname="col2">320</oasis:entry>
         <oasis:entry colname="col3">320</oasis:entry>
         <oasis:entry colname="col4">320</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Organic content samples (<inline-formula><mml:math id="M10" display="inline"><mml:mi>n</mml:mi></mml:math></inline-formula>)</oasis:entry>
         <oasis:entry colname="col2">320</oasis:entry>
         <oasis:entry colname="col3">320</oasis:entry>
         <oasis:entry colname="col4">320</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Chlorophyll <inline-formula><mml:math id="M11" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula> samples (<inline-formula><mml:math id="M12" display="inline"><mml:mi>n</mml:mi></mml:math></inline-formula>)</oasis:entry>
         <oasis:entry colname="col2">320</oasis:entry>
         <oasis:entry colname="col3">320</oasis:entry>
         <oasis:entry colname="col4">320</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Visible sandflat parameters (<inline-formula><mml:math id="M13" display="inline"><mml:mi>n</mml:mi></mml:math></inline-formula> photos)</oasis:entry>
         <oasis:entry colname="col2">318</oasis:entry>
         <oasis:entry colname="col3">319</oasis:entry>
         <oasis:entry colname="col4">297</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Lost photos due to water coverage</oasis:entry>
         <oasis:entry colname="col2">m.1.10.9, m.4.39.7</oasis:entry>
         <oasis:entry colname="col3">k1.4.2, k2.19.4, k2.19.5,</oasis:entry>
         <oasis:entry colname="col4">t1.8.5</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">k2.19.6, k2.19.7, k2.19.8,</oasis:entry>
         <oasis:entry colname="col4"/>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">k2.19.9, k2.19.10, k2.20.1,</oasis:entry>
         <oasis:entry colname="col4"/>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">k2.20.2, k2.20.3, k2.20.4,</oasis:entry>
         <oasis:entry colname="col4"/>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">k2.20.5, k2.20.6, k2.20.7,</oasis:entry>
         <oasis:entry colname="col4"/>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">k2.20.8, k2.20.9, k2.20.10,</oasis:entry>
         <oasis:entry colname="col4"/>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">k4.31.1, k4.31.2, k4.31.3,</oasis:entry>
         <oasis:entry colname="col4"/>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">k4.37.3, k4.38.10</oasis:entry>
         <oasis:entry colname="col4"/>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Macrobenthos samples (<inline-formula><mml:math id="M14" display="inline"><mml:mi>n</mml:mi></mml:math></inline-formula>)</oasis:entry>
         <oasis:entry colname="col2">400</oasis:entry>
         <oasis:entry colname="col3">399</oasis:entry>
         <oasis:entry colname="col4">398</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Lost macrobenthos samples</oasis:entry>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">T4.35.5</oasis:entry>
         <oasis:entry colname="col4">K3.24.3, k4.35.5</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry namest="col1" nameend="col4">Results of laboratory work 2012–2014 </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Species identified (<inline-formula><mml:math id="M15" display="inline"><mml:mi>n</mml:mi></mml:math></inline-formula>)</oasis:entry>
         <oasis:entry colname="col2">109</oasis:entry>
         <oasis:entry colname="col3">81</oasis:entry>
         <oasis:entry colname="col4">114</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Individuals (<inline-formula><mml:math id="M16" display="inline"><mml:mi>n</mml:mi></mml:math></inline-formula>)</oasis:entry>
         <oasis:entry colname="col2">26 573</oasis:entry>
         <oasis:entry colname="col3">25 394</oasis:entry>
         <oasis:entry colname="col4">21 846</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Median grain size (<inline-formula><mml:math id="M17" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m)</oasis:entry>
         <oasis:entry colname="col2">166</oasis:entry>
         <oasis:entry colname="col3">197</oasis:entry>
         <oasis:entry colname="col4">213</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Silt (% <inline-formula><mml:math id="M18" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">63</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M19" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m)</oasis:entry>
         <oasis:entry colname="col2">14</oasis:entry>
         <oasis:entry colname="col3">5</oasis:entry>
         <oasis:entry colname="col4">1</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Very fine sediments (% 63–125 <inline-formula><mml:math id="M20" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m)</oasis:entry>
         <oasis:entry colname="col2">17</oasis:entry>
         <oasis:entry colname="col3">17</oasis:entry>
         <oasis:entry colname="col4">6</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Fine sediments (% 125–250 <inline-formula><mml:math id="M21" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m)</oasis:entry>
         <oasis:entry colname="col2">48</oasis:entry>
         <oasis:entry colname="col3">44</oasis:entry>
         <oasis:entry colname="col4">6</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Medium sediments (% 250–500 <inline-formula><mml:math id="M22" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m)</oasis:entry>
         <oasis:entry colname="col2">18</oasis:entry>
         <oasis:entry colname="col3">28</oasis:entry>
         <oasis:entry colname="col4">32</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Coarse sediments (% <inline-formula><mml:math id="M23" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">500</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M24" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m)</oasis:entry>
         <oasis:entry colname="col2">3</oasis:entry>
         <oasis:entry colname="col3">6</oasis:entry>
         <oasis:entry colname="col4">0.4</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Organic content (%)</oasis:entry>
         <oasis:entry colname="col2">2</oasis:entry>
         <oasis:entry colname="col3">2</oasis:entry>
         <oasis:entry colname="col4">0.8</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Chlorophyll <inline-formula><mml:math id="M25" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula> (mg g<inline-formula><mml:math id="M26" 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">23</oasis:entry>
         <oasis:entry colname="col3">11</oasis:entry>
         <oasis:entry colname="col4">5</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Bare sand cover (%)</oasis:entry>
         <oasis:entry colname="col2">79</oasis:entry>
         <oasis:entry colname="col3">73</oasis:entry>
         <oasis:entry colname="col4">84</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Shell hash cover (%)</oasis:entry>
         <oasis:entry colname="col2">16</oasis:entry>
         <oasis:entry colname="col3">3</oasis:entry>
         <oasis:entry colname="col4">2</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Seagrass cover (%)</oasis:entry>
         <oasis:entry colname="col2">5</oasis:entry>
         <oasis:entry colname="col3">23</oasis:entry>
         <oasis:entry colname="col4">13</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

      <?pagebreak page295?><p id="d1e872">Prior to destructive sampling, we took a photograph of 50 cm <inline-formula><mml:math id="M27" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 50 cm at each
sampling point (<inline-formula><mml:math id="M28" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">960</mml:mn></mml:mrow></mml:math></inline-formula>) to assess the coverage of seagrass (<italic>Zostera muelleri</italic>), bare sand, and
shell hash. In addition, at each point (<inline-formula><mml:math id="M29" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">960</mml:mn></mml:mrow></mml:math></inline-formula>), we pooled three surface
sediment cores (2 cm diameter, 2 cm deep) for sediment grain-size analyses
(median grain-size and sediment fractions), chlorophyll <inline-formula><mml:math id="M30" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula> measurements, and
determination of the organic content of the sediment (Table 1). These samples were
stored in the dark on ice immediately after collecting. Note that at the
smallest spatial scale, i.e. 30 cm, we took three adjoining benthic cores, but
we limited ourselves to taking one photograph and one sediment sample to
represent the environmental features for these three locations. This was
done to economically manage our time in the field and our financial budget
for processing samples, leading to 320 photographs and 320 sediment samples
per harbour. See Kraan et al. (2015, 2019) or Greenfield et al. (2016) for
details.
<?xmltex \hack{\newpage}?></p>
</sec>
<sec id="Ch1.S2.SS2">
  <label>2.2</label><title>Macrobenthic data</title>
      <p id="d1e925">In the laboratory, rose-bengal-stained (2 %) taxa were identified to the
lowest practical taxonomic resolution and their abundance assessed. In total
we identified 146 species, mostly bivalves, polychaetes, and crustaceans,
encompassing 73 813 individuals (Table 1; Supplement, Kraan et al., 2019). For bivalves,
the longest shell axis was also measured, allowing adults and juveniles to
be distinguished, because habitat preferences can differ between adults and
juveniles (Kraan et al., 2010, 2013). Size classes were categorized as
<inline-formula><mml:math id="M31" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula>, 1–5, 5–10, 10–15, 15–20, 20–25, 25–30, 30–35,
35–40, and <inline-formula><mml:math id="M32" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">40</mml:mn></mml:mrow></mml:math></inline-formula> mm. Each sample was sorted and its taxa
identified by Casper Kraan, after which Barry L. Greenfield verified species
identifications on each sample (Kraan et al., 2019).</p>
</sec>
<sec id="Ch1.S2.SS3">
  <label>2.3</label><?xmltex \opttitle{Chlorophyll $a$ measurements}?><title>Chlorophyll <inline-formula><mml:math id="M33" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula> measurements</title>
      <p id="d1e964">Sediment samples were freeze-dried upon arrival in the laboratory. Prior to
freeze-drying, seagrass and bivalves were removed. For measuring, 0.1 g of
sediment was weighed, topped up with 90 % acetone buffer, and
centrifuged for 10 min at 3300 rpm. Chlorophyll <inline-formula><mml:math id="M34" display="inline"><mml:mi>a</mml:mi></mml:math></inline-formula> and pheophytin
concentrations (<inline-formula><mml:math id="M35" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">960</mml:mn></mml:mrow></mml:math></inline-formula>) were determined with a fluorometer using
standard methods (see Kraan et al., 2015). The first sample was measured on 10 May 2012, and the last sample was measured on 28 June 2012,
avoiding degradation of samples over time (see Kraan et al., 2019).</p>
</sec>
<sec id="Ch1.S2.SS4">
  <label>2.4</label><title>Sediment grain-size distributions</title>
      <p id="d1e994">To determine sediment median grain-size and sediment fractions (silt
<inline-formula><mml:math id="M36" display="inline"><mml:mrow><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">63</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M37" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m, very fine 63–125 <inline-formula><mml:math id="M38" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m, fine 125–250 <inline-formula><mml:math id="M39" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m, medium
250–500 <inline-formula><mml:math id="M40" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m, and coarse <inline-formula><mml:math id="M41" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">500</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M42" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m), sediment grain sizes
were measured (<inline-formula><mml:math id="M43" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">960</mml:mn></mml:mrow></mml:math></inline-formula>), following standard methods for using a Malvern
Mastersizer 2000 with a particle range of 0.02–2000 <inline-formula><mml:math id="M44" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m (see Kraan et
al., 2015). This involved digesting about a teaspoon of sediment by adding
10 % hydrogen<?pagebreak page296?> peroxide to remove organic content from the sediment, leaving it
to digest for 7 d, and stirring every couple of days.</p>
</sec>
<sec id="Ch1.S2.SS5">
  <label>2.5</label><title>Organic content of the sediment</title>
      <p id="d1e1087">Organic content (<inline-formula><mml:math id="M45" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">960</mml:mn></mml:mrow></mml:math></inline-formula>) was determined after burning a teaspoon of
freeze-dried sediment for 5.5 h in a furnace at 560 <inline-formula><mml:math id="M46" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C, i.e. the
loss-on-ignition approach.</p>
</sec>
<sec id="Ch1.S2.SS6">
  <label>2.6</label><title>Visible sandflat parameters</title>
      <p id="d1e1119">The coverage of seagrass, shell hash, and bare sand within each photograph (<inline-formula><mml:math id="M47" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">960</mml:mn></mml:mrow></mml:math></inline-formula>) was estimated based on 75 random points within a photograph using the
software CPCe (Kohler and Gill, 2006) (see Kraan et al., 2019).</p>
</sec>
</sec>
<sec id="Ch1.S3">
  <label>3</label><title>Data availability</title>
      <p id="d1e1143">All data collected during this project, including extensive metadata, are
available from the data publisher PANGAEA (Kraan et al., 2019). For
convenience, all data are grouped into a parent dataset
(<ext-link xlink:href="https://doi.org/10.1594/PANGAEA.903448" ext-link-type="DOI">10.1594/PANGAEA.903448</ext-link>; Kraan et al., 2019).</p>
      <p id="d1e1149">A number of scientific studies have used these data. For example, Kraan et
al. (2015) described the cross-scale variation in biodiversity–environment
links using Moran's eigenvector mapping (MEM). Greenfield et al. (2016)
focussed on the spatial distribution of functional groups to gain insight into
the scale dependency of resilience. Thrush et al. (2017) and Douglas et al. (2017) based their experimental set-up on the spatial distribution of
functional hot and cold spots to experimentally study the impact of
nutrient loading on ecosystem functioning and resilience.</p>
</sec>

      
      </body>
    <back><app-group>
        <supplementary-material position="anchor"><p id="d1e1151">The supplement related to this article is available online at: <inline-supplementary-material xlink:href="https://doi.org/10.5194/essd-12-293-2020-supplement" xlink:title="zip">https://doi.org/10.5194/essd-12-293-2020-supplement</inline-supplementary-material>.</p></supplementary-material>
        </app-group><notes notes-type="authorcontribution"><title>Author contributions</title>

      <p id="d1e1162">CK and SFT designed the study, and CK and BLG
carried it out. CK prepared this paper  with contributions and the final
approval of all authors.</p>
  </notes><notes notes-type="competinginterests"><title>Competing interests</title>

      <p id="d1e1168">The authors declare that they have no conflict of interest.</p>
  </notes><ack><title>Acknowledgements</title><p id="d1e1175">We thank Sylvia de Juan, Andres Ospina, Katie Cartner, Kelly Carter, Sarah Hailes, Hazel Needham, Clarisse Niemand, Rachel Harris, and Rebecca Gladstone-Gallagher for their help during fieldwork and laboratory work.</p></ack><?xmltex \hack{\newpage}?><?xmltex \hack{\newpage}?><notes notes-type="financialsupport"><title>Financial support</title>

      <p id="d1e1181">This research has been supported by the Royal Society of New Zealand, Marsden Fund (grant no. NIW-1102) and the FP7 People: Marie-Curie Actions (BAYESIANMETAFLATS (grant no. 298380)).</p>
  </notes><notes notes-type="reviewstatement"><title>Review statement</title>

      <p id="d1e1187">This paper was edited by Francois Schmitt and reviewed by Clément Garcia and Olivier Beauchard.</p>
  </notes><ref-list>
    <title>References</title>

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  </ref-list></back>
    <!--<article-title-html>Multi-scale data on intertidal macrobenthic biodiversity and environmental features in three New Zealand harbours</article-title-html>
<abstract-html><p>Understanding how the plants and animals that live in the
sea floor vary in their spatial patterns of diversity and abundance is
fundamental to gaining insight into the role of biodiversity in maintaining
ecosystem functioning in coastal ecosystems, as well as advancing the
modelling of species distributions under realistic assumptions. Yet, it is
virtually unknown how the relationships between abundance patterns and
different biotic and environmental processes change depending on spatial
scales, which is mainly due to a lack of data. Within the project Spatial
Organization of Species Distributions: Hierarchical and Scale-Dependent
Patterns and Processes in Coastal Seascapes at the National Institute for
Water and Atmospheric Research (NIWA) in New Zealand we collected
multi-scale and high-resolution data on macrobenthic biodiversity. We found
146 species dominated by bivalves, polychaetes, and crustaceans
( &gt; 500&thinsp;µm) that live hidden in marine sandflats and
collected point measurements of important environmental variables (sediment
grain-size distributions, chlorophyll <i>a</i> concentration, organic content, and
visible sandflat parameters) in three large intertidal harbours (Kaipara,
Tauranga, and Manukau). In each harbour we sampled 400 points for
macrobenthic community composition and abundances, as well as the full set
of environmental variables. Using an elaborate sampling design, we were able
to cover scales from 30 &thinsp;cm to a maximal extent of 1&thinsp;km. All data
and extensive metadata are available from the data publisher PANGAEA via the
persistent identifier <a href="https://doi.org/10.1594/PANGAEA.903448" target="_blank">https://doi.org/10.1594/PANGAEA.903448</a> (Kraan et al.,
2019).</p></abstract-html>
<ref-html id="bib1.bib1"><label>1</label><mixed-citation>
Araújo, M. B. and Luoto, M.: The importance of biotic interactions for
modelling species distributions under climate change, Global Ecol.
Biogeogr., 16, 743–753, <a href="https://doi.org/10.1111/j.1466-8238.2007.00359.x" target="_blank">https://doi.org/10.1111/j.1466-8238.2007.00359.x</a>,
2007.
</mixed-citation></ref-html>
<ref-html id="bib1.bib2"><label>2</label><mixed-citation>
Dormann, C. F., Bobrowski, M., Dehling, D. M., Harris, D. J., Hartig, F.,
Lischke, H., Moretti, M., Pagel, J., Pinkert, S., Schleuning, M., Schmidt,
S. I., Sheppard, C. S., Steinbauer, M. J., Zeuss, D., and Kraan, C.: Biotic
interactions in species distribution modelling: ten questions to guide
interpretation and avoid false conclusions, Global Ecol. Biogeogr., 27,
1004–1016, <a href="https://doi.org/10.1111/geb.12759" target="_blank">https://doi.org/10.1111/geb.12759</a>, 2018.
</mixed-citation></ref-html>
<ref-html id="bib1.bib3"><label>3</label><mixed-citation>
Douglas, E. J., Pilditch, C. A., Kraan, C., Schipper, L. A., Lohrer, A. M.,
and Thrush, S. F.: Macrofaunal functional biodiversity provides resilience
to nutrient enrichment in coastal sediments, Ecosystems, 7, 1324–1336,
<a href="https://doi.org/10.1007/s10021-017-0113-4" target="_blank">https://doi.org/10.1007/s10021-017-0113-4</a>, 2017.
</mixed-citation></ref-html>
<ref-html id="bib1.bib4"><label>4</label><mixed-citation>
Greenfield, B. L., Kraan, C., Pilditch, C. A., and Thrush, S. F.: Mapping
functional groups can provide insight into ecosystem functioning and
potential resilience of intertidal sand flats, Mar. Ecol.-Prog. Ser., 548,
1–10, <a href="https://doi.org/10.3354/meps11692" target="_blank">https://doi.org/10.3354/meps11692</a>, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib5"><label>5</label><mixed-citation>
Hewitt, J. E. and Thrush, S. F.: Reconciling the influence of global climate
phenomena on macrofaunal temporal dynamics at a variety of spatial scales,
Glob. Change Biol., 15, 1911–1929,
<a href="https://doi.org/10.1111/j.1365-2486.2008.01825.x" target="_blank">https://doi.org/10.1111/j.1365-2486.2008.01825.x</a>, 2009.
</mixed-citation></ref-html>
<ref-html id="bib1.bib6"><label>6</label><mixed-citation>
Kohler, K. E. and Gill, S. M.: Coral Point Count with Excel extensions
(CPCe): A Visual Basic program for the determination of coral and substrate
coverage using random point count methodology, Comput.  Geosci., 32,
1259–1269, <a href="https://doi.org/10.1016/j.cageo.2005.11.009" target="_blank">https://doi.org/10.1016/j.cageo.2005.11.009</a>, 2006.
</mixed-citation></ref-html>
<ref-html id="bib1.bib7"><label>7</label><mixed-citation>
Kraan, C., van Gils, J. A., Spaans, B., Dekinga, A., Bijleveld, A. I., van
Roomen, M., Kleefstra, R., and Piersma, T.: Landscape-scale experiment
demonstrates that Wadden Sea intertidal flats are used to capacity by
molluscivore migrant shorebirds, J. Anim. Ecol., 78, 1259–1268,
<a href="https://doi.org/10.1111/j.1365-2656.2009.01564.x" target="_blank">https://doi.org/10.1111/j.1365-2656.2009.01564.x</a>, 2009.
</mixed-citation></ref-html>
<ref-html id="bib1.bib8"><label>8</label><mixed-citation>
Kraan, C., Aarts, G., van der Meer, J., and Piersma, T.: The role of
environmental variables in structuring landscape-scale species distributions
in seafloor habitats, Ecology, 91, 1583–1590,
<a href="https://doi.org/10.1890/09-2040.1" target="_blank">https://doi.org/10.1890/09-2040.1</a>, 2010.
</mixed-citation></ref-html>
<ref-html id="bib1.bib9"><label>9</label><mixed-citation>
Kraan, C., Aarts, G., Piersma, T., and Dormann, C. F.: Temporal variability
of ecological niches: a study on intertidal benthic fauna, Oikos, 122,
754–760, <a href="https://doi.org/10.1111/j.1600-0706.2012.20418.x" target="_blank">https://doi.org/10.1111/j.1600-0706.2012.20418.x</a>, 2013.

</mixed-citation></ref-html>
<ref-html id="bib1.bib10"><label>10</label><mixed-citation>
Kraan, C., Dormann, C. F., Greenfield, B. L., and Thrush, S. F.: Cross-scale
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