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  <front>
    <journal-meta>
<journal-id journal-id-type="publisher">OS</journal-id>
<journal-title-group>
<journal-title>Ocean Science</journal-title>
<abbrev-journal-title abbrev-type="publisher">OS</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Ocean Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1812-0792</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/os-13-337-2017</article-id><title-group><article-title>Seabirds as samplers of the marine environment – a case study of northern gannets</article-title>
      </title-group><?xmltex \runningtitle{Seabirds as samplers of the marine environment}?><?xmltex \runningauthor{S.~Garthe et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1">
          <name><surname>Garthe</surname><given-names>Stefan</given-names></name>
          <email>garthe@ftz-west.uni-kiel.de</email>
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Peschko</surname><given-names>Verena</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1 aff2">
          <name><surname>Kubetzki</surname><given-names>Ulrike</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Corman</surname><given-names>Anna-Marie</given-names></name>
          
        </contrib>
        <aff id="aff1"><label>1</label><institution>Research &amp; Technology Centre (FTZ), Kiel University, Hafentörn 1, 25761 Büsum, Germany</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>Department of Animal Ecology and Conservation, Biocentre Grindel, Hamburg University, Martin-Luther-King Platz 3, 20146 Hamburg, Germany</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Stefan Garthe (garthe@ftz-west.uni-kiel.de)</corresp></author-notes><pub-date><day>25</day><month>April</month><year>2017</year></pub-date>
      
      <volume>13</volume>
      <issue>2</issue>
      <fpage>337</fpage><lpage>347</lpage>
      <history>
        <date date-type="received"><day>29</day><month>April</month><year>2016</year></date>
           <date date-type="rev-request"><day>27</day><month>June</month><year>2016</year></date>
           <date date-type="rev-recd"><day>24</day><month>February</month><year>2017</year></date>
           <date date-type="accepted"><day>26</day><month>February</month><year>2017</year></date>
      </history>
      <permissions>
<license license-type="open-access">
<license-p>This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/3.0/">http://creativecommons.org/licenses/by/3.0/</ext-link></license-p>
</license>
</permissions><self-uri xlink:href="https://os.copernicus.org/articles/13/337/2017/os-13-337-2017.html">This article is available from https://os.copernicus.org/articles/13/337/2017/os-13-337-2017.html</self-uri>
<self-uri xlink:href="https://os.copernicus.org/articles/13/337/2017/os-13-337-2017.pdf">The full text article is available as a PDF file from https://os.copernicus.org/articles/13/337/2017/os-13-337-2017.pdf</self-uri>


      <abstract>
    <p>Understanding distribution patterns, activities, and
foraging behaviours of seabirds requires interdisciplinary approaches. In
this paper, we provide examples of the data and analytical procedures from a
new study in the German Bight (North Sea) tracking northern gannets (<italic>Morus bassanus</italic>) at their breeding colony on the island of Heligoland. Individual
adult northern gannets were equipped with different types of data loggers
for several weeks, measuring geographic positions and other parameters
mostly at 3–5 min intervals. Birds flew in all directions from the island to
search for food, but most flights targeted areas to the (N)NW (north–northwest) of Heligoland.
Foraging trips were remarkably variable in duration and distance; most trips
lasted 1–15 h and extended from 3 to 80 km from the breeding colony on
Heligoland. Dives of gannets were generally shallow, with more than half of
the dives only reaching depths of 1–3 m. The maximum dive depth was 11.4 m.
Gannets showed a clear diurnal rhythm in their diving activity, with dives
being almost completely restricted to the daylight period. Most flight
activity at sea occurred at an altitude between the sea surface and 40 m.
Gannets mostly stayed away from the wind farms and passed around them much
more frequently than flying through them. Detailed information on individual
animals may provide important insights into processes that are not
detectable at a community level.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <title>Introduction</title>
      <p>Seabirds are marine animals that live mostly at or near the air–water
interface. The dynamics of both these media may consequently have a strong
influence on the ecology of seabirds (Schneider, 1991). Many studies in the
world's oceans have shown that the physical environment has a substantial
influence on seabird distributions (e.g. Briggs et al., 1987; Hunt Jr., 1990).
Physical processes are particularly relevant to seabirds when they cause
predictable prey aggregations, either regular or irregular. However, other
opportunities (such as fisheries' discards; e.g. Ryan and Moloney, 1988;
Garthe et al., 1996) and constraints (such as the need to breed on land;
e.g. Schneider and Hunt Jr., 1984; Wilson et al., 1995a) may also influence
seabird distributions and related behaviours. An essential feature in the
marine system is “scale”. Quantitative relations between abiotic and biotic
variables are strongly influenced by the scale at which they are measured
(Schneider, 1994). Thus, general seabird distribution patterns often
correspond best with physical phenomena at large scales, whereas smaller-scale
patterns are associated with biological features such as foraging
range, social interactions, and prey availability (Schneider and Duffy,
1985; Hunt Jr. and Schneider, 1987). Most behaviours at sea are directly
related to foraging (e.g. searching, feeding) or the result of
foraging-related constraints (waiting for food to become available,
digesting, commuting). Several external and internal characteristics and
limitations influence foraging activities, e.g. diurnal rhythms, flight
manoeuvrability, feeding techniques, prey-detection capabilities, social
attractions, learning and age-dependent skills, foraging ranges, and dietary
preferences (Furness and Monaghan, 1987; Shealer, 2002).</p>
      <p>For decades, studies of seabird biology were mainly land based, with a
particular focus on the breeding period. Although there were understandable
logistic reasons for this, it has led to severe biases in our understanding
of seabird ecology. Two subsequent approaches focusing on the behaviours of
seabirds at sea have allowed significant progress in our understanding of
seabird ecology. One such approach involved studying seabird distributions
at sea from boats. Whereas early work was targeted towards establishing the
distribution patterns of seabirds (e.g. Brown, 1986; Tasker et al., 1987),
later studies concentrated on improving our understanding of the underlying
factors, including habitat parameters, mainly hydrographic features measured
synoptically at sea or by remote techniques, and food availability, assessed
by detecting and possibly quantifying prey at sea (e.g. Hunt Jr. et al., 1998;
Davoren et al., 2003; Jahncke et al., 2005). The second approach was to
equip seabirds with telemetric devices and/or data-logging units (e.g.
Jouventin and Weimerskirch, 1990; Wilson et al., 2002; Wilson and
Vandenabeele, 2012). These devices record the bird's position and/or other
parameters, such as temperature and depth, while the bird is at sea. Because
seabirds are fast-moving and wide-ranging animals, this approach also
enables us to study them in logistically inaccessible areas. Furthermore, it
allows information on individual birds to be collected, in contrast to
boat-based observations, which involve larger samples of birds but where
individuals cannot be tracked over larger areas or time spans.</p>
      <p>Understanding patterns in distributions, activities, and foraging behaviours
of seabirds requires interdisciplinary approaches. The physical properties
of the sea establish the basic habitat parameters with which both the
seabirds and their prey have to cope, while biological conditions influence
the birds' food supply (e.g. by prey behaviour) and foraging behaviours.
Furthermore, anthropogenic activities may also influence different aspects
of the marine environment, both directly on individual seabirds, and
indirectly by affecting habitat conditions and prey availability. A
combination of these methodological and conceptual approaches will further
improve our understanding of the ecology of seabirds within the study area.</p>
      <p>In this paper, we provide an overview of a new study in the German Bight (North Sea)
connected to the Coastal Observing System for Northern and Arctic
Seas (COSYNA) network. We started tracking northern gannets (<italic>Morus bassanus</italic>)
at their breeding colony on the island of Heligoland in 2014
(Garthe et al., 2017). Gannets were selected as they have the largest
foraging ranges of all abundant seabird species on Heligoland and are large
animals that can carry various types of data loggers. Here, we provide
examples of the data and analytical procedures based on selected data sets
from 2015, and explain the value and perspectives of such studies,
especially in relation to coastal observation systems such as COSYNA.</p>
</sec>
<sec id="Ch1.S2">
  <title>Methods</title>
<sec id="Ch1.S2.SS1">
  <title>Field work</title>
      <p>Field work was conducted on the island of Heligoland (54<inline-formula><mml:math id="M1" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>11<inline-formula><mml:math id="M2" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula> N,
7<inline-formula><mml:math id="M3" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>55<inline-formula><mml:math id="M4" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula> E) in the southeastern North Sea (Fig. 1). A total of 14
adult northern gannets that were either incubating or rearing chicks were
caught on 12–13 May, 17–18 June, or 22–23 July 2015. All birds were
equipped with data loggers. A total of 10 gannets each received a Bird Solar GPS
logger (e-obs GmbH, Munich, Germany) and the other four birds were equipped
with both a CatLog-S GPS logger (Catnip Technologies, Hong Kong SAR, China) and
a precision temperature–depth (PTD) logger (Earth and Ocean Technologies,
Kiel, Germany). All loggers were attached to the base of the four central
tail feathers using TESA<sup>®</sup> tape (Beiersdorf AG GmbH, Hamburg,
Germany; Fig. 2). Data obtained from these loggers covered durations of
0.4–10.9 weeks.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1"><caption><p>Breeding colony of northern gannets on the island of Heligoland.
Photo: S. Garthe.</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://os.copernicus.org/articles/13/337/2017/os-13-337-2017-f01.jpg"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2"><caption><p>Flying northern gannets with a Bird Solar GPS logger attached to
the tail feathers. Photo: K. Borkenhagen.</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://os.copernicus.org/articles/13/337/2017/os-13-337-2017-f02.jpg"/>

        </fig>

      <p>The total masses of the attached devices (including sealing, base plate, and
tape) were about 48 g (Bird Solar) and 64 g (CatLog-S plus PTD),
representing 1.5 and 1.9 %, respectively, of the mean gannet body mass
of 3286 g (Wanless and Okill, 1994). This is well below the potential
threshold of 3 % (Phillips et al., 2003; see Vandenabeele et al.,
2012). Although attachments to the tail may have a negative influence on
flight behaviour (Vandenabeele et al., 2014), most pairs successfully
incubated their eggs and/or raised their chicks, similar to non-handled
nests, with no visible effects on bird behaviour.</p>
</sec>
<sec id="Ch1.S2.SS2">
  <title>Technology</title>
<sec id="Ch1.S2.SS2.SSSx1" specific-use="unnumbered">
  <title>Bird Solar GPS logger</title>
      <p>These loggers recorded date, time, position (latitude, longitude), ground
speed, heading and acceleration. The sampling interval was mostly set to
3–5 min, and the triaxial accelerometer to 0.25–3 min. The onboard
memories were either 32 or 64 MB. The outer diameters of the devices were <inline-formula><mml:math id="M5" display="inline"><mml:mrow><mml:mn mathvariant="normal">63</mml:mn><mml:mo>×</mml:mo><mml:mn mathvariant="normal">22</mml:mn><mml:mo>×</mml:mo><mml:mn mathvariant="normal">16</mml:mn></mml:mrow></mml:math></inline-formula> mm, plus base plates and an antenna of 76 mm for
data transfer. Data could be downloaded remotely using a hand-held device
when approaching the birds in the colony.</p>
</sec>
</sec>
<sec id="Ch1.S2.SS3">
  <title>CatLog-S GPS logger</title>
      <p>These devices recorded date, time, and position (latitude, longitude) and
were set at an interval of 5 min. Dimensions varied slightly according to
battery type but were about <inline-formula><mml:math id="M6" display="inline"><mml:mrow><mml:mn mathvariant="normal">50</mml:mn><mml:mo>×</mml:mo><mml:mn mathvariant="normal">35</mml:mn><mml:mo>×</mml:mo><mml:mn mathvariant="normal">8</mml:mn></mml:mrow></mml:math></inline-formula> mm. The plate was
encased by a heatable plastic housing. Data were retrieved by recapturing
the bird and downloading data from the device.</p>
<sec id="Ch1.S2.SS3.SSSx1" specific-use="unnumbered">
  <title>PTD loggers</title>
      <p>These loggers had 2 MB onboard memory and measured date, time, pressure, and
internal and external temperatures (Earth and Ocean Technologies).
Temperature measurements were obtained from an external, fast-responding,
temperature sensor that allowed sampling of the water column with minimal
time lag in thermal signals (temperature-response time <inline-formula><mml:math id="M7" display="inline"><mml:mrow><mml:mi>T</mml:mi><mml:mn mathvariant="normal">0.9</mml:mn></mml:mrow></mml:math></inline-formula> (i.e. time to
reach 90 % <inline-formula><mml:math id="M8" display="inline"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>T</mml:mi></mml:mrow></mml:math></inline-formula>, following a temperature change) of approximately 1.8 s (Daunt
et al., 2003). The streamlined lightweight carbon-fibre composite casing
(outer diameter 19 mm, length 80 mm) weighed about 23 g. Recording intervals
for temperature and pressure were set at 3 s. Data could be retrieved by
recapturing the bird and downloading the data from the device.</p>
</sec>
</sec>
<sec id="Ch1.S2.SS4">
  <title>Northern gannets</title>
      <p>The northern gannet is the largest seabird species in the North Atlantic. It
has a body mass of 2.3–3.6 kg and breeds in colonies of up to several tens
of thousands of pairs. Northern gannets spend their entire life at sea,
except for breeding on land. They usually start breeding at 5–6 years old,
and may live to 20 years or older. They lay one egg that is incubated for 6 weeks,
followed by a chick-rearing period of about 13 weeks. Only one adult
of the pair is usually at the nest at any one time during incubation or
chick guarding, while the other is at sea (Nelson, 2002; Bauer et al.,
2005). Apart from short flights to collect nesting material or due to
disturbance/interactions at the nest site, gannets carry out foraging trips
to collect food for themselves and their offspring. They usually forage
using so-called plunge dives, which are initiated when flying (and
searching) at a few to several tens of metres above the sea surface (Nelson,
2002; Garthe et al., 2014). Two different dive types can be distinguished in
this species (Garthe et al., 2000). U-shaped dives occur when the birds
remain at a largely constant depth for a period after plunging into the
water, with little vertical movement, before returning to the sea surface.
In contrast, V-shaped dives are usually short and shallow, with the ascent
almost immediately following the descent.</p>
      <p>Northern gannets have recently been studied intensively by satellite
telemetry and data loggers in various places (e.g. Hamer et al., 2001; Pettex
et al., 2012; Wakefield et al., 2013), thus allowing comparisons among regions
and populations.</p>
</sec>
</sec>
<sec id="Ch1.S3">
  <title>Products and analyses</title>
<sec id="Ch1.S3.SS1">
  <title>Flight patterns</title>
      <p>Figure 3a and b show the flight patterns of two adult northern gannets
that were typical of 13 of the 14 individuals tracked in 2015. Birds flew in
all directions from the island to search for food, but most flights targeted
areas to the (N)NW (north–northwest) of Heligoland. Foraging trips (defined in this paper as
absences from the nest site of at least 20 min and of at least 2.0 km direct
distance) were remarkably variable in duration and distance; most trips
lasted 1–15 h and extended from 3 to 80 km from the breeding colony on
Heligoland. One individual's behaviour differed from that of the other
gannets by repeatedly flying far north to forage in the Skagerrak (Fig. 3c).
These long-distance foraging trips were almost identical in their structures
(<inline-formula><mml:math id="M9" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:math></inline-formula>; duration of 44.3–59.3 h, most distant location 375–388 km away,
total distance of 971–1019 km flown) and were interspersed with
“normal” foraging trips into the German Bight.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3" specific-use="star"><caption><p>Flight patterns of three northern gannets (NOGAs) breeding on
Heligoland in 2015. Birds were tracked over 8 <bold>(a)</bold>, 5 <bold>(b)</bold>, and 3.5 <bold>(c)</bold> weeks,
respectively.</p></caption>
          <?xmltex \igopts{width=426.791339pt}?><graphic xlink:href="https://os.copernicus.org/articles/13/337/2017/os-13-337-2017-f03.jpg"/>

        </fig>

</sec>
<sec id="Ch1.S3.SS2">
  <title>Diving behaviour</title>
      <p>Dives of gannets breeding on Heligoland and foraging in the (south) eastern
North Sea were generally shallow, with more than half of the dives only
reaching depths of 1–3 m (Fig. 4). The maximum dive depth was 11.4 m, and
the median dive depth was 2.2 m (<inline-formula><mml:math id="M10" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">4</mml:mn></mml:mrow></mml:math></inline-formula> individuals, <inline-formula><mml:math id="M11" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">2577</mml:mn></mml:mrow></mml:math></inline-formula> dives).
Most dives were V-shaped, though the measuring interval of 3 s did not allow
a precise determination of the proportions of U- and V-shaped dives (see
Garthe et al., 2000). The measuring interval of 3 s might also mask the
deepest parts of some dives and may thus underestimate dive depth in
general. We therefore re-analysed a random sample of 100 dives from Garthe
et al. (2014), where gannets exhibited a similar high percentage of V-shaped
dives, using both 1 and 3 s intervals (10 individuals, 10 dives each).
Scaling down to 3 s missed 10 % of the dives, while the median-detected
dive depth was only slightly smaller (4.3 vs. 4.5 m). These subtle
differences demonstrate the validity of 3 s measuring intervals to determine
the dive-depth pattern.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4"><caption><p>Dive depths of northern gannets in 2015. Data are based on 2557
dives recorded from four adults breeding on Heligoland. Vertical bars show
values averaged over the four individuals; extended lines show standard
errors. Immersions of &lt; 0.3 m were excluded as potentially
indicating bathing and other behaviours.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://os.copernicus.org/articles/13/337/2017/os-13-337-2017-f04.pdf"/>

        </fig>

      <p>These dives were shallow compared with previous studies conducted in the
northwestern North Sea (Lewis et al., 2002), the English Channel
(Grémillet et al., 2006), the northwest Atlantic (Garthe et al., 2000),
and the Gulf of Saint Lawrence, Canada (Garthe et al., 2007). Although the
sample sizes of individuals are small, this does not hold true for the number
of days the birds were tagged and the number of dives. Dive depths recorded
from Heligoland gannets in 2015 remained much shallower even when subsampling
small data sets from a large database from eastern Canada (S. Garthe et al.,
unpublished data).</p>
      <p>Gannets showed a clear diurnal rhythm in their diving activity (Fig. 5).
Dives were almost completely restricted to the daylight period, with the
remaining dives occurring around dawn and dusk. No dives were recorded
between 22:09 and 05:21 Central European Summer Time (CEST). This pattern
fits well previous studies (Garthe et al., 2000, 2003).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5"><caption><p>Diurnal rhythm in diving activity of northern gannets in the
German Bight in 2015. Data are for the period 12–31 May 2015 and are based on
dive recordings of three adults breeding on Heligoland. Each dot represents
one dive, showing the maximum depth during the dive. Vertical dashed lines
indicate sunrise and sunset for the median day of the period covered.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://os.copernicus.org/articles/13/337/2017/os-13-337-2017-f05.pdf"/>

        </fig>

</sec>
<sec id="Ch1.S3.SS3">
  <title>Habitat analyses</title>
      <p>Dive positions were analysed for the fixed habitat parameters including distance to
colony (Heligoland), water depth, and distance to nearest land (except for
Heligoland; Fig. 6). Almost two-thirds of the dives were carried out at a
distance of less than 50 km from the colony, with proportions declining
further away from the colony. However, at the largest distances, proportions
of dives increased again, strongly indicating that gannets may have
specifically targeted such distant foraging areas (see also Sect. 3.5,
Fig. 9). As related to water depth, gannets from Heligoland were diving most
often in waters of 20–40 m depths, less often in shallower, and rarely in
deeper waters (Fig. 6). For foraging, gannets mostly stayed away from the
coast, with the highest proportions at a distance of 40–60 km. This pattern
differs completely from studies in eastern Canada where gannets were found
to concentrate their diving efforts on the coastal zone (Garthe et al.,
2007). Both Heligoland (located approximately 43 km north of the East Frisian Islands)
and Funk Island (Newfoundland, Canada; located approximately 50 km away from the
coast) have a similar placement and, in consequence, the location of the
colonies cannot explain the observed difference in coastal focus. However,
the near-coastal waters in the Canadian study sites are characterised by
much more marine conditions and larger water depths compared to the Wadden
Sea coast with extended shallow waters in the German Bight.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6"><caption><p>Habitat relationships (upper graph: distance to colony; middle
graph: water depth; lower graph: distance to nearest land) of diving
northern gannets in 2015. Data are based on 2557 dives recorded from four
adults breeding on Heligoland. Vertical bars show mean values averaged over
the four individuals; extended lines show standard errors.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://os.copernicus.org/articles/13/337/2017/os-13-337-2017-f06.png"/>

        </fig>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T1" specific-use="star"><caption><p>Linear mixed model of two key dive parameters (dive depth and dive
duration) and their possible explanation by the three fixed habitat variables (distance to
colony, water depth, and distance to nearest land). AIC indicates Akaike's
information criterion. LRT indicates the likelihood ratio test. Significant results are shown in
bold.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="7">
     <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" colsep="1"/>
     <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:tbody>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry namest="col2" nameend="col4" align="center" colsep="1">Dive depth </oasis:entry>  
         <oasis:entry namest="col5" nameend="col7" align="center">Dive duration </oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry rowsep="1" colname="col2">AIC</oasis:entry>  
         <oasis:entry rowsep="1" colname="col3">LRT</oasis:entry>  
         <oasis:entry rowsep="1" colname="col4"><inline-formula><mml:math id="M12" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula></oasis:entry>  
         <oasis:entry rowsep="1" colname="col5">AIC</oasis:entry>  
         <oasis:entry rowsep="1" colname="col6">LRT</oasis:entry>  
         <oasis:entry rowsep="1" colname="col7"><inline-formula><mml:math id="M13" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">Full model</oasis:entry>  
         <oasis:entry colname="col2">4314.1</oasis:entry>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4">531.2</oasis:entry>  
         <oasis:entry colname="col5"/>  
         <oasis:entry colname="col6"/>  
         <oasis:entry colname="col7"/>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">Distance to colony</oasis:entry>  
         <oasis:entry colname="col2">4312.4</oasis:entry>  
         <oasis:entry colname="col3">0.265</oasis:entry>  
         <oasis:entry colname="col4">0.606</oasis:entry>  
         <oasis:entry colname="col5">531.9</oasis:entry>  
         <oasis:entry colname="col6">2.747</oasis:entry>  
         <oasis:entry colname="col7">0.097</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">Water depth</oasis:entry>  
         <oasis:entry colname="col2">4312.9</oasis:entry>  
         <oasis:entry colname="col3">0.760</oasis:entry>  
         <oasis:entry colname="col4">0.383</oasis:entry>  
         <oasis:entry colname="col5">537.4</oasis:entry>  
         <oasis:entry colname="col6">8.174</oasis:entry>  
         <oasis:entry colname="col7"><bold>0.004</bold></oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">Distance to nearest land</oasis:entry>  
         <oasis:entry colname="col2">4315.2</oasis:entry>  
         <oasis:entry colname="col3">3.102</oasis:entry>  
         <oasis:entry colname="col4">0.078</oasis:entry>  
         <oasis:entry colname="col5">530.5</oasis:entry>  
         <oasis:entry colname="col6">1.342</oasis:entry>  
         <oasis:entry colname="col7">0.247</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

      <p>Two Gaussian linear mixed models were used to analyse the impact of the
habitat parameters including distance to colony, water depth, and distance to nearest
land on (1) the dive depth and (2) the dive duration of the tagged birds
(using R version 3.3.2; R Development Core Team, 2016; package “lme4”,
function “lmer” by Bates et al., 2015). Both response variables were
log transformed to approach normality. The three habitat parameters were
used as numeric explanatory variables. Dive ID nested within bird ID was
taken as a random factor to avoid pseudo-replication due to multiple
measurements per bird. As the function lmer does not provide <inline-formula><mml:math id="M14" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> values, we
further used the function “drop1” to find the relevant habitat parameter
explaining the variance of dive depth and/or dive duration. This function
tests every term in the model as if it was the last entering the model. In
turn, every term in the model is omitted, and the reduced model is then
(automatically) compared to the full model by a likelihood ratio test under
1 degree of freedom (i.e. a so-called marginal frequentist <italic>F</italic> test;
Korner-Nievergelt et al., 2015). Though the sample size of individuals was
low, the temporal coverage (12–18 days) and the number of dives per
individual (381–773) were high. In this data set, dive depth could not be
explained statistically by any of the three fixed habitat variables, while
dive duration could be explained by water depth (Table 1). It is to be
expected that larger data sets that will be collected in the future may
exhibit more significant relationships to these and other habitat
parameters.</p>
</sec>
<sec id="Ch1.S3.SS4">
  <title>Flight altitudes</title>
      <p>The altitudes of flying birds are important in relation to their migratory
movements, prey-searching behaviour, and potential overlap with technical
installations at sea.</p>
      <p>The Bird Solar GPS loggers calculated height above the ellipsoid when
connecting with satellites during positional fixes, and altitude
measurements were therefore corrected for geoid height (39.1 m at colony
location). Altitude estimates are improved when connection time to the
satellite is increased (e.g. Corman and Garthe, 2014), and we therefore
used pulses of GPS fixes over 11–15 s and analysed the last and assumed
best altitude measurement from each pulse. Figure 7 shows non-smoothed
altitude measurements for one foraging trip of 22.7 h. Colony attendance was
derived from positional fixes and known nest position; on-water periods were
determined from ground speed (&lt; 3 km h<inline-formula><mml:math id="M15" display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> and positional fixes.
Although values fluctuated slightly even for fixed places, such as the nest
site in the colony and the sea surface, the measurements appeared reasonable
and showed that most flight activity occurred at an altitude between the sea
surface and 40 m, with maximum values in this study for when birds were
commuting to/from the colony. Measurements in the colony and on water can be
used to calibrate altitude measurements because of their relatively
well-known heights.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F7"><caption><p>Altitude measurements for a northern gannet tracked in summer 2015
on Heligoland. Altitude measurements are related to activities “in colony”
(before and after the 22.7 h foraging trip), swimming, and flying. For
details, see text. Please note that this device was switched off during the
core darkness hours to save energy, and because birds are known to either
stay at the nest site or rest at the sea surface during this period (as
shown here).</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://os.copernicus.org/articles/13/337/2017/os-13-337-2017-f07.pdf"/>

        </fig>

      <p>Flight heights of gannets have also been determined by radar measurements
(e.g. Krijgsveld et al., 2011), visual observations (e.g. Johnston et al.,
2014), and pressure sensors (Garthe et al., 2014; Cleasby et al.,
2015). Overall, flight heights of gannets tend to be low, with relatively
few flights above 50 m and very few recorded above 100 m, though no
comprehensive analysis has yet been published.</p>
</sec>
<sec id="Ch1.S3.SS5">
  <title>Behavioural patterns</title>
      <p>Animal movements can be tracked using motion sensors. Many data loggers
contain accelerometers that ideally cover all three axes (<inline-formula><mml:math id="M16" display="inline"><mml:mi>x</mml:mi></mml:math></inline-formula>, <inline-formula><mml:math id="M17" display="inline"><mml:mi>y</mml:mi></mml:math></inline-formula>, <inline-formula><mml:math id="M18" display="inline"><mml:mi>z</mml:mi></mml:math></inline-formula>), and
frequent measurements allow behavioural differentiation at a fine scale
(e.g. Sakamoto et al., 2009).</p>
      <p>Figure 8 shows an example of accelerometer measurements of a northern gannet
at a 0.25 min interval over 24 h. Recordings start when the bird is on its
nest, with very little activity, obviously sleeping. After about 3 h, the
bird remains on its nest but its activity increases, coinciding with dawn. A
few hours later, the bird leaves the nest and flies off, followed by a
period of about 10 h of mostly flying, interrupted by a few shorter swimming
periods. Towards the end of the recording period, the bird settles down on
the sea surface and remains floating there overnight (Fig. 8). Such
information is important in many ways. It may help identifying the relevance
of certain sea areas, i.e. whether areas are used for foraging or just for
resting, or for long(er)-distance movements. Quantifying birds' activities
is a well-established tool to measure energy expenditure. Such energy
budgets may, e.g. help unravelling seabird movement strategies as has been
shown by Garthe et al. (2012) for northern gannets wintering in different
regions of the northeast Atlantic. Analyses of these kinds will be done for
more birds in a separate study.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F8"><caption><p>Accelerometer measurements for a northern gannet breeding on
Heligoland. This example shows the values for the three different axes (red
indicates <inline-formula><mml:math id="M19" display="inline"><mml:mi>x</mml:mi></mml:math></inline-formula>, green indicates <inline-formula><mml:math id="M20" display="inline"><mml:mi>y</mml:mi></mml:math></inline-formula>, blue indicates <inline-formula><mml:math id="M21" display="inline"><mml:mi>z</mml:mi></mml:math></inline-formula>) over 24 h, from 02:00 to 02:00 CEST on the
next day. Different activities are indicated by arrows; higher peaks indicate
greater movement.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://os.copernicus.org/articles/13/337/2017/os-13-337-2017-f08.pdf"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F9"><caption><p>Foraging tracks and dive positions for the northern gannet shown
in Fig. 3c. Please note that the data set is smaller than in Fig. 1c because
only the synoptic GPS and pressure data are shown (the memory of the PTD
logger was full after about 18 days).</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://os.copernicus.org/articles/13/337/2017/os-13-337-2017-f09.png"/>

        </fig>

      <p>To determine the relevance of certain sea areas and to improve our
understanding of the flight patterns of the birds, it is necessary to know
when and where the birds are feeding. Because gannets almost always obtain
food by plunge diving, observing dives provides a good proxy for determining
feeding areas. Figure 9 shows the flight tracks and dive locations of the
gannet that flew repeatedly towards the Skagerrak. It shows that the gannet
was foraging intensively in the Skagerrak, while longer passages on outbound
and inbound flights were long-distance flights without much foraging
activity.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F10" specific-use="star"><caption><p>Overlap of flight patterns for the three northern gannets shown
in Fig. 3 with the locations of wind farms in the German Bight. Information
on the location and status of wind farms was collated from the Federal
Maritime and Hydrographic Agency (BSH, personal communication) and the Global
Offshore Wind Farms Database (<uri>http://www.4coffshore.com/offshorewind/</uri>). The upper graph shows the whole
German Bight; the lower graph shows the area with the three wind farms near
Heligoland only.</p></caption>
          <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://os.copernicus.org/articles/13/337/2017/os-13-337-2017-f10.png"/>

        </fig>

</sec>
<sec id="Ch1.S3.SS6">
  <title>Overlap with human pressures</title>
      <p>The ability to track seabird movements at small spatial and temporal scales
makes it possible to study the potential impacts of human activities at sea
comprehensively. A total of 12 offshore wind farms have been built and became
operational in the German Bight between 2008 and November 2016, and a
further 5 are currently under construction. Another 15 wind farms have
been given consent, and several tens more have been applied for. The impact
of wind farms on seabirds, which is currently a hot topic in conservation
biology and environmental policy (e.g. Furness et al., 2013; Masden et al.,
2015), can thus be studied comprehensively in German North Sea waters. In
2014, gannets were tracked near existing wind farms for the first time. All
three individuals largely avoided the wind farm area north of Heligoland
(Garthe et al., 2017).</p>
      <p>The flight tracks of the gannets shown in Fig. 3 were projected on top of
the wind farms that were operational or under construction during the
tracking period. The three gannets mostly stayed away from the wind farms and
passed around them much more frequently than flying through them (Fig. 10).
Wind farms further from Heligoland were not entered, but gannets visited
the areas around them. Focusing on the three wind farms north of Heligoland,
5 of the 14 gannets tracked in 2015 did not enter them, 4 only flew
into the wind farms once, while 4 visited them occasionally and 1
frequently.</p>
</sec>
</sec>
<sec id="Ch1.S4" sec-type="conclusions">
  <title>Conclusions and perspectives</title>
      <p>Tracking free-living animals such as seabirds can open up new dimensions in
biological, ecological, and environmental research (Kays et al., 2015). The
latest developments in microelectronics can even provide real-time data
transfer through mobile-phone networks (e.g. Gilbert et al., 2016).
Information collected by data loggers can be used for various purposes,
including applied topics, such as assessing the possible effects of wind
farms, as well as fundamental research. In a review of offshore wind-farm
studies, Bailey et al. (2014) concluded that traditional visual surveys of
birds and mammals from ships and aircraft were unlikely to have enough power
to detect changes in behaviour or fine-scale spatial or temporal shifts in
distribution, given that observers can only be in one place at a time and
can only reliably survey in calm sea conditions during daylight hours. Other
techniques such as GPS tracking are thus likely to provide more useful data
in many cases (Bailey et al., 2014).</p>
      <p>Substantial added-value information can be retrieved by combining
geographic-position information with other parameters. For birds feeding
under water, pressure sensors are essential to characterise foraging areas,
allowing diving activity to be described comprehensively (e.g. Boyd, 1997;
Ronconi and Burger, 2011). Pressure sensors and/or high-rate GPS
measurements can also be used to estimate flight heights (Corman and
Garthe, 2014; Scales et al., 2014). Further detailed behavioural and
energetic information can be derived from three-dimensional accelerometer
measurements (Gómez Laich et al., 2008; Sakamoto et al., 2009), making
this a topical research interest.</p>
      <p>To understand the distributions of food-searching seabirds and their
variation over time, analysing the birds' habitat choice is an important and
promising approach. While some habitat parameters may be collected by the
loggers on the birds directly (e.g. sea surface temperatures; Wilson et al.,
1995b), a full set of variables can only be derived from a combination of
remote-sensing and in situ measurements. In most studies tracking seabirds,
sea surface temperature and chlorophyll have been analysed and compared to
bird distributions, often with limited success (e.g. Grémillet et al.,
2008). In future activities of our study, we will make use of the project
consortium COSYNA (Baschek et al., 2016) which provides comprehensive and
relevant information on important habitat variables. We expect that
fixed-point measurements may be particularly valuable for studying seasonal
and/or annual variability of the foraging behaviour and distributions of
northern gannets, while moving and remote-sensing platforms may be best used
to unravel the spatial distribution of the birds at any time. The advantage
of COSYNA in this context will be the variety of measured variables as
well as the three-dimensional measurements so that stratification can be
assessed which would not be available from remote-sensing sources (Baschek
et al., 2016). Furthermore, the generation of models may prove particularly
valuable for analysing and possibly predicting the distribution of seabirds
(Breitbach et al., 2016; Stanev et al., 2016). Finally, information on the
marine environment may also be generated through the study of foraging
seabirds directly, as their distinct prey-search behaviours may also inform
physical oceanographers on the location of physical features, especially
small-scale features such as fronts (e.g. Sabarros et al., 2014; Scales et
al., 2014).</p>
</sec>

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

      <p>Data on flight tracks of northern gannets are available
at the COSYNA data portal, <ext-link xlink:href="http://dx.doi.org/10.17616/R3K02T" ext-link-type="DOI">10.17616/R3K02T</ext-link> (re3data.org, 2017).</p>
  </notes><notes notes-type="competinginterests">

      <p>The authors declare that they have no conflict of interest.</p>
  </notes><ack><title>Acknowledgements</title><p>This study was funded by the Federal Ministry for
Economic Affairs and Energy according to the decision of the German
Bundestag (HELBIRD, 0325751). The e-obs loggers used in this study were
provided through the COSYNA project led by the Helmholtz Zentrum Geesthacht
(HZG). Logistic support on Heligoland was provided by J. Dierschke and the
Institute of Avian Research on Heligoland. K. Borkenhagen, R. M. Borrmann, L. Enners,
K. Fließbach, N. Guse, J. Jeglinski, K. Lehmann-Muriithi, B. Mendel,
S. Müller, G. Schultheiß, H. Schwemmer, S. Vandenabeele, and
S. Weiel helped with fieldwork. S. Furness provided linguistic support. All
institutional and national guidelines for the handling and equipping of
birds were followed. Birds were equipped under a licence issued by the
Ministry of Energy Transition, Agriculture, Environment and Rural Areas
Schleswig-Holstein, Germany (file no. V 312-7224.121-37 (80-6/13)). All
animals were handled in strict accordance with good animal practice to
minimise handling times and stress.<?xmltex \hack{\newline}?><?xmltex \hack{\newline}?>
Edited by: H. Brix<?xmltex \hack{\newline}?>
Reviewed by: G. Hunt and M. Frederiksen</p></ack><ref-list>
    <title>References</title>

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    <!--<article-title-html>Seabirds as samplers of the marine environment – a case study of northern gannets</article-title-html>
<abstract-html><p class="p">Understanding distribution patterns, activities, and
foraging behaviours of seabirds requires interdisciplinary approaches. In
this paper, we provide examples of the data and analytical procedures from a
new study in the German Bight (North Sea) tracking northern gannets (<i>Morus
bassanus</i>) at their breeding colony on the island of Heligoland. Individual
adult northern gannets were equipped with different types of data loggers
for several weeks, measuring geographic positions and other parameters
mostly at 3–5 min intervals. Birds flew in all directions from the island to
search for food, but most flights targeted areas to the (N)NW (north–northwest) of Heligoland.
Foraging trips were remarkably variable in duration and distance; most trips
lasted 1–15 h and extended from 3 to 80 km from the breeding colony on
Heligoland. Dives of gannets were generally shallow, with more than half of
the dives only reaching depths of 1–3 m. The maximum dive depth was 11.4 m.
Gannets showed a clear diurnal rhythm in their diving activity, with dives
being almost completely restricted to the daylight period. Most flight
activity at sea occurred at an altitude between the sea surface and 40 m.
Gannets mostly stayed away from the wind farms and passed around them much
more frequently than flying through them. Detailed information on individual
animals may provide important insights into processes that are not
detectable at a community level.</p></abstract-html>
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