Annual movements of a migratory seabird—the NW European red-throated diver (Gavia stellata)—reveals high individual repeatability but low migratory connectivity

Abstract

In this study, the annual movements of a seabird species, the red-throated diver (Gavia stellata), were investigated in space and time. Between 2015 and 2017, 33 individuals were fitted with satellite transmitters at the German Bight (eastern North Sea). In addition, stable isotope analyses of feathers (δ13C) were used to identify staging areas during the previous moult. The German Bight is an important area for this species, but is also strongly affected by anthropogenic impacts. To understand how this might affect populations, we aimed to determine the degree of connectivity and site fidelity, and the extent to which seasonal migrations vary among different breeding locations in the high Arctic. Tagged individuals migrated to Greenland (n = 2), Svalbard (n = 2), Norway (n = 4) and northern Russia (n = 25). Although individuals from a shared breeding region (northern Russia) largely moved along the same route, individuals dispersed to different, separate areas during the non-breeding phase. Kernel density estimates also overlapped only partially, indicating low connectivity. The timing of breeding was correlated with the breeding longitude, with 40 days later arrival at the easternmost than westernmost breeding sites. Repeatability analyses between years revealed a generally high individual site fidelity with respect to spring staging, breeding and moulting sites. In summary, low connectivity and the distribution to different sites suggests some resilience to population decline among subpopulations. However, it should be noted that the majority of individuals breeding in northern Russia migrated along a similar route and that disturbance in areas visited along this route could have a greater impact on this population. In turn, individual site fidelity could indicate low adaptability to environmental changes and could lead to potential carry-over effects. Annual migration data indicate that conservation planning must consider all sites used by such mobile species.

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Marine Biology (2022) 169: 114
https://doi.org/10.1007/s00227-022-04096-x
ORIGINAL PAPER
Annual movements ofamigratory seabird—the NW European
red‑throated diver (Gavia stellata)—reveals high individual
repeatability butlow migratory connectivity
BirgitKleinschmidt1,2 · ClaudiaBurger2· PacoBustamante7,8· MonikaDorsch2· StefanHeinänen3,6·
JuliusMorkūnas4· RamūnasŽydelis3,5· GeorgNehls2· PetraQuillfeldt1
Received: 27 December 2021 / Accepted: 29 July 2022 / Published online: 22 August 2022
© The Author(s) 2022
Abstract
In this study, the annual movements of a seabird species, the red-throated diver (Gavia stellata), were investigated in space
and time. Between 2015 and 2017, 33 individuals were fitted with satellite transmitters at the German Bight (eastern North
Sea). In addition, stable isotope analyses of feathers (δ13C) were used to identify staging areas during the previous moult.
The German Bight is an important area for this species, but is also strongly affected by anthropogenic impacts. To under-
stand how this might affect populations, we aimed to determine the degree of connectivity and site fidelity, and the extent
to which seasonal migrations vary among different breeding locations in the high Arctic. Tagged individuals migrated to
Greenland (n = 2), Svalbard (n = 2), Norway (n = 4) and northern Russia (n = 25). Although individuals from a shared breed-
ing region (northern Russia) largely moved along the same route, individuals dispersed to different, separate areas during
the non-breeding phase. Kernel density estimates also overlapped only partially, indicating low connectivity. The timing of
breeding was correlated with the breeding longitude, with 40days later arrival at the easternmost than westernmost breeding
sites. Repeatability analyses between years revealed a generally high individual site fidelity with respect to spring staging,
breeding and moulting sites. In summary, low connectivity and the distribution to different sites suggests some resilience to
population decline among subpopulations. However, it should be noted that the majority of individuals breeding in northern
Russia migrated along a similar route and that disturbance in areas visited along this route could have a greater impact on
this population. In turn, individual site fidelity could indicate low adaptability to environmental changes and could lead to
potential carry-over effects. Annual migration data indicate that conservation planning must consider all sites used by such
mobile species.
Keywords Red-throated diver· Red-throated loon· Satellite tracking· Stable isotopes· Temporal-spatial pattern·
Migratory connectivity· Site fidelity· Anthropogenic pressure
Responsible Editor: T.A. Clay.
* Birgit Kleinschmidt
Birgit.Kleinschmidt@bio.uni-giessen.de
1 Department ofAnimal Ecology andSystematics, Justus
Liebig University Giessen, 35392Giessen, Germany
2 BioConsult SH, 25813Husum, Germany
3 DHI, 2970Hørsholm, Denmark
4 Marine Research Institute, Klaipėda University,
92294Klaipėda, Lithuania
5 Present Address: Ornitela UAB, 03228Vilnius, Lithuania
6 Present Address: Novia University ofApplied Sciences,
Raseborgsvägen 9, 10600Ekenäs, Finland
7 Littoral Environnement et Sociétés (LIENSs), UMR 7266,
CNRS-Université de la Rochelle, 2 rue Olympe de Gouges,
17000LaRochelle, France
8 Institut Universitaire de France (IUF), 1 rue Descartes,
75005Paris, France
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Marine Biology (2022) 169: 114
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Background
Migratory birds are increasingly affected by environmental
changes, disturbances and threats along their migration
routes (Wilcove and Wikelski 2008). Therefore, infor-
mation about annual movements is important for effec-
tive conservation and management (Marra etal. 2018;
Johnston etal. 2020). Many species, such as seabirds, are
long-lived with delayed sexual maturity and low annual
reproductive rates (Schreiber and Burger 2001). Survival
of adult birds, as well as reproductive success, therefore,
influence their population growth rates (Sæther and Bakke
2000). Different migratory strategies, including different
winter locations, can influence fitness differently, through
variable energy costs and winter habitat conditions (Alves
etal. 2013). Altered environmental conditions in the sta-
tionary non-breeding periods can affect migratory timing
or carry-over to affect survival and reproduction in the
breeding areas (Marra etal 1998; Harrison etal. 2011;
Winkler etal. 2014; Rushing etal. 2016). Information
about the site use of migratory birds throughout the whole
annual cycle and their ability to respond to environmental
change is, therefore, important to conserve such long-lived
and mobile species (Moore etal. 2005; Runge etal. 2014).
Migratory connectivity, i.e. the degree to which indi-
viduals from one breeding or wintering population stay
together and use similar sites along the annual cycle, pro-
vides essential information to assess the impact of envi-
ronmental change in habitats along the migratory route
(Webster etal. 2002; Martin etal. 2007). The degree of
migratory connectivity determines to which extent differ-
ent breeding populations experience similar non-breeding
conditions (Esler 2000; Taylor and Norris 2010; Cress-
well 2014; Finch etal. 2017). Migratory connectivity is
defined along a continuum from strong connectivity (low
interpopulation spread and use of population-specific non-
breeding areas) to a low or diffuse connectivity (high inter-
population spread) (Webster etal. 2002; Newton 2008;
Finch etal. 2017). In a low connectivity scenario, indi-
viduals from a given breeding population may mix with
individuals from other breeding regions during the non-
breeding season (Finch etal 2017). Recent studies (i.e.
Gilroy etal. 2016) introduced further terms such as migra-
tory diversity which expresses the within-population vari-
ability in migratory movements and suggest that migra-
tory diversity may help to facilitate species responses to
environmental change.
To understand how migrants might be affected by envi-
ronmental change in breeding and non-breeding sites, we
need to understand the migratory pattern in space and
time such as the variation in migration duration, number
of staging stops and temporal pattern among the different
migration routes and breeding sites. These baseline meas-
urements are necessary to monitor future shifts in tim-
ing or to identify carry-over effects (Gordo 2007; Studds
etal. 2008; Duijns etal. 2017). Migratory movements
and their timings can be linked with geographic position,
resource allocation or climatic variables on the breeding
areas (Conklin 2010). Climatic conditions on the winter-
ing grounds can also affect migratory timing, with some
species responding to milder winters with earlier arrival
on the breeding grounds (Gunnarson and Tómasson 2011).
The total duration of migration and thus the arrival time
at the destination may also depend on the conditions at
stop-over sites, which influence the decision to stay or
continue (Weber and Houston 1997; Klinner etal. 2020).
Local resource availability and competition at moulting,
wintering or stop-over habitats are important for migra-
tory movements (Kokko 1999; Moore 2005; Kölzsch etal.
2016; Fayet etal. 2017). Reduced habitat quality at these
locations could result in delayed or extended stays and
altered timing of annual movements (Marra etal. 1998).
Individual fidelity towards sites used throughout the year,
as well as temporal repeatability, could also be important
for predicting the response of migrants to environmental
change. Individual behavioural consistency might deter-
mine how individuals respond to environmental change
and how much populations could be affected by habitat
changes and possible carry-over effects (Reed etal. 2009;
Dias etal. 2010). Individuals with a high site fidelity may
be less flexible to voluntarily change sites and more sensi-
tive to displacement caused by disturbance. Consequently,
less flexible individuals might adapt more slowly to a new
environment, than an individual that is familiar with mul-
tiple sites and can use flexible strategies (Catry etal. 2004;
McFarlane etal. 2014; Merkel etal. 2021). Individual site
utilisation and movements within and between years are,
therefore, important to consider in conservation decisions
(Croxall etal. 2005; González-Solís etal. 2007).
In this study, we analysed the migratory behaviour of a
seabird species, the red-throated diver (Gavia stellata), that
is increasingly influenced by human activities in one of their
most important winter and spring staging areas in Europe,
the German Bight (eastern North Sea) (Garthe etal. 2007,
2015; Dierschke etal. 2012; Burger etal. 2019; Mendel
etal. 2019; Heinänen etal. 2020). In this winter population,
strong avoidance of offshore wind farm areas was observed
(Mendel etal. 2019; Heinänen etal. 2020; Vilela etal. 2021)
but, so far, no decline in wintering population numbers of
this long-lived species (Vilela etal. 2021). Red-throated
divers are listed in Annex II of the Bern Convention, Annex
I of the EU Birds Directive and as critically endangered on
the HELCOM (Helsinki Commission) convention (BirdLife
International 2022). The species is widespread in the Holarc-
tic, with breeding areas in the Arctic tundra regions north of
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Marine Biology (2022) 169: 114
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60° latitude and wintering areas in temperate coastal ocean
waters. Breeding populations in Shetland, Sweden, Finland
and Greenland have been linked with wintering areas such as
the Baltic Sea, Skagerrak, the North Sea and further south to
the Bay of Biscay (Cramp and Simmons 1977; Okill 1994;
Wetlands International 2019). Ring recoveries suggest that
younger birds move further south during winter than older
birds (Okill 1994).
Moult is one of the three main energy-demanding events
in the annual cycle of birds and usually occurs at a different
time from breeding and migration (Newton 2009, 2011).
Information about space use in this sensitive period of the
year is important for conservation measures, but little is
known about the temporal and spatial patterns of moult in
red-throated divers. To date, it is known that red-throated
divers moult their wing feathers simultaneously, render-
ing them temporarily flightless. Wing moult takes place in
autumn (August to November, Stresemann and Stresemann
1966), in an area that is visited after leaving the breeding
area. Recoveries of dead birds washed up on the coast in the
North and Baltic Sea have shown that the birds moult their
wing feathers in this period and also change from breeding
to winter plumage (Berndt and Drenckhahn 1974, Mendel
etal. 2008). In the following spring, birds moult their body
feathers back into the breeding plumage (Stresemann and
Stresemann 1966).
We used satellite telemetry which has been shown to
be highly suitable to study migratory movements and spa-
tial–temporal patterns of red-throated divers within and
between years (Schmutz 2014; Paruk etal. 2015; Spiegel
etal. 2017; McCloskey etal. 2018). Additionally, we used
carbon stable isotope analyses of neck feathers in combi-
nation with satellite tracking data to infer moulting areas
used prior to capture. Stable isotope values of a predator are
related to those of its prey and the area where the predator
foraged. Stable isotope values of prey vary with its trophic
position and geographic region. Nitrogen stable isotope val-
ues (δ15N) increase with trophic position, while carbon sta-
ble isotope values (δ13C) depend more on the carbon uptake
by the primary producer and thus differs among habitats
(Peterson and Frey 1987; Frey 1988; Hobson 1999; Cherel
and Hobson 2007).
We aimed to describe the annual cycle of red-throated
divers captured in the eastern German Bight. We focussed
on migratory connectivity, how the breeding location influ-
ences the temporal pattern of annual movements and on indi-
vidual site fidelity between years. In particular, we aimed to
test the following hypotheses: (1) in accordance with ring
recoveries of individuals from Sweden, Britain and other
regions in the capture area (Okill 1994; Hemmingson and
Eriksson 2002) red-throated divers display a low degree of
migratory connectivity, in particular: (1a) individuals from
one or more breeding region mix in one non-breeding area
(capture site) and (1b) individuals from one breeding region
spread during migration and their stationary non-breeding
home ranges do not overlap, (2) the location of the breed-
ing area (longitude/latitude) affects the timing and pattern
of annual movements, (3) similar to the high site fidelity to
their breeding areas (Okill 1992), individual red-throated
divers repeatedly utilise the same areas during their key life
history stages between years.
Methods
Fieldwork
We obtained positions of 33 red-throated divers equipped
with Argos satellite transmitters (platform transmitter termi-
nals, PTTs) in late winter to early spring (February–April)
of 2015 to 2017. Birds were captured in the eastern part of
the German Bight (North Sea), approximately 20km west
of the islands of Sylt and Amrum. We captured divers using
the night-lighting technique (Whitworth etal. 1997; Ronconi
etal. 2010). For a detailed description of tagging, see Burger
etal. (2019), Kleinschmidt etal. (2019), Heinänen etal.
(2020) and www. diver track ing. com. We used implantable
PTTs manufactured by Telonics, Inc. (40 units) and Sirtrack,
Ltd (5 units). Transmitters were programmed using vary-
ing duty cycles with 3 or 4 transmission hours and 12–24h
intervals during winter and 60–68h intervals between trans-
missions during the breeding season. Blood samples were
taken and stored on Whatman FTA cards (Whatman FTA
card technology, Sigma Aldrich) to sex the birds geneti-
cally. As the proportion of male birds (6 out of 33) was
clearly underrepresented, we did not pursue further analyses
regarding sex-specific differences, but combined male and
female data for further analyses. A detailed description on
the genetic sex determination is provided in the supplemen-
tary material (A9).
Data filtering
The tracking data were filtered to reduce noise from location
fixes with low or unknown accuracy. Filtering followed the
approach in Dorsch etal. (2019), Burger etal. (2019), and
Heinänen etal. (2020) and was conducted using the package
‘argosfilter’ (Freitas etal. 2008) in R (R Core Team 2018).
First, the sdafilter Filter (lat, lon, dtime, lc, vmax = 20) was
applied. Then, all locations with unrealistic swimming/fly-
ing speeds were removed, using the McConnell algorithm
(McConell etal. 1992), unless the point was located at less
than 5km from the previous location. Second, ArcGISv.10.1
(ESRI 2012) was used to further inspect the filtered data-
set and any remaining obvious outliers, such as unrealistic
positions were removed from the dataset. Finally, positions
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Marine Biology (2022) 169: 114
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recorded during the first 2weeks after the transmitter
implantation were excluded from the data set due to possi-
ble impacts of capture and surgery on the behaviour during
recovery period.
Altogether we received 29,053 satellite transmitter posi-
tions. After filtering, 22,744 positions were left for further
analyses. Considering the quality of the data, we found that
39.4% (n = 8,962) of the positions were categorised in loca-
tion classes 3–1 and 60.6% (n = 13,782) of positions were
assigned to location classes 0-B (TableA2, CLS 2013).
Data collection anddefinition ofterms andseasons
We used the migratory pattern observed in this dataset to
define seasons within the annual cycle (Fig.1, Table1).
The timing of site use varied from individual to individual
and from year to year (Fig.1). Therefore, we decided to
define each season by the months in which at least one diver
showed activity consistent with that season (i.e. migratory
movements, or settlement during breeding, moulting or win-
tering season, Table1). After spending some time on inland
lakes, presumably for nesting, some red-throated divers
moved to adjacent marine waters. Depending on the time
period, they spent for nesting, these individuals are likely
failed breeders or non-breeders. We did not consider these as
staging periods as long as the diver stayed in the presumed
breeding area.
Autumn moult takes place in areas located along the
migration route between breeding and wintering areas
(Berndt and Drenckhahn 1990; Mendel etal. 2008) and is
assumed to involve a stationary period of ≥ 21days, includ-
ing a flightless period. Hence, we divided the autumn migra-
tion from breeding to moult and from moult to wintering
(Table1).
We defined staging sites along migration routes as
areas where an individual diver spent ≥ 5days. Short stop-
overs < 5days were not considered in separate analyses. This
classification of staging and stop-over behaviour followed
Warnock (2010).
Analysing tracking data
PTTs were deployed over three separate years so ordinal date
(day of the year) was used as the temporal variable allowing
comparisons to be made across years.
We used ArcGISv.10.1 (ESRI 2012), QGISv2.18 (QGIS
Development Team 2018) and two projections (Lambert
Azimuthal Equal Area projection: ETRS89/ETRS-LAEA
Fig. 1 Longitudinal migration pattern of all tracked red-throated
divers (n = 33) during three consecutive years. Important regions uti-
lised during breeding, moulting and wintering season are indicated on
the right side. Individuals that did not show a clear breeding settle-
ment are indicated with a dotted line
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Marine Biology (2022) 169: 114
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(EPSG: 3035), North Pole Azimuthal Equidistant projec-
tion (EPSG: 102016)) to inspect migratory patterns and to
quantify migratory movements. We calculated migratory
distances between capture and breeding sites by summing
the length of all vectors created from point to point of the
PTT locations from the first day of departure from a site
to first day of arrival at the new site. We did not include
movements within staging areas and sites into the distance
calculation.
We used R (v 3.6.1) (R Core Team 2018) to analyse and
plot longitudinal migratory patterns, home range estimates
and repeatability of site use between 2 consecutive years. We
used the R package stats4 (R Core Team 2018) to calculate
correlations. A Pearson's correlation was run to determine
the relationship between spatial (breeding longitude/lati-
tude) and temporal variables (arrival/departure/time of stay).
Additionally, we tested if the distance moved between cap-
ture area and breeding sites affected the duration of migra-
tion and staging behaviour.
For analysing migratory connectivity, we first defined
the breeding regions to determine the extent to which indi-
viduals from a wintering area head to the same breeding
region and use similar migratory routes. We divided breed-
ing regions either by distance (> 700km), or if separated by
a large body of water (as breeding is constrained to land).
Migratory routes were then assigned to the respective breed-
ing region, namely Greenland, Scandinavia (Norway and
Svalbard) and northern Russia. We analysed migratory con-
nectivity between the breeding and non-breeding sites by
quantifying the number of individuals of which positions
were located along the same path using three analytical sec-
tions of the migration route (i) from the same starting point
(capture site) to the same breeding region (n = 33), (ii) from
one shared breeding region to their moulting destination
(n = 19) and (iii) from one shared breeding region to their
winter destination (n = 13). We analysed migratory connec-
tivity during autumn migration (ii and iii) only for birds
breeding in northern Russia (Siberian Arctic) as sample
sizes from other regions were too small for further analy-
ses. In addition, we assessed the strength of connectivity
by calculating the Mantel correlation coefficient within the
R package ade4 (Dray and Dufour 2007; Ambrosini etal.
2009; Trierweiler etal. 2014; Cohen etal. 2018). Statisti-
cal significance was determined using 9999 permutations
(Trierweiler etal. 2014; Ambrosini etal. 2009). The Mantel
correlation coefficient (rM) was calculated between pairwise
(orthodromic) distance matrices of (i) individual positions at
capture and breeding (n = 31 individuals with a fixed breed-
ing position), (ii) breeding and moulting (n = 13 individuals
breeding in Siberian Russia), and (iii) breeding and winter
Table 1 Definition of terms and seasons and corresponding data collection used in this dataset
Season Spring
migration
Arrival breeding Departure
breeding
Moult
migration
Arrival in
potential
moult
Depar-
ture from
potential
moult
Autumn
migration
Arrival
winter
Departure
winter
Definition Trajectory
from
capture/
winter
site to
breeding
site
(Directional
move-
ments)
1st position
after a long-
distance flight
(> 100km),
min.
stay > 31days
1st position
outside
the breed-
ing site
Trajectory
from
breeding
site to
moulting
site
(Direc-
tional
move-
ments)
1st position
after a long-
distance
flight
(> 100km),
min. stay
> 21days)
1st posi-
tion out-
side the
moulting
site
Trajectory
from
moulting
site to
wintering
site
(Direc-
tional
move-
ments),
1st position in
an area after
a long-dis-
tance flight
(> 100km),
min. stay
> 31days
1st position
outside
the winter
site,
Phenology March–
June
June–September August–
Septem-
ber
September–December October–
January
December –May
Number of
indi-
viduals
analysed
for the 1st
year
N = 33 N = 31 N = 19 N = 19 N = 19 N = 13 N = 13 N = 13 N = 10
Number of
indi-
viduals
analysed
for the
2nd year
N = 9 N = 7 N = 4 N = 3 N = 3 N = 1 N = 1 N = 1 N = 0
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Marine Biology (2022) 169: 114
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(n = 9 individuals breeding in Siberian Russia). Mantel cor-
relation coefficient values range from 0 to 1, and indicate
the strength of a population’s migratory connectivity. Val-
ues ≤ 0.25 suggest no spatial structure, values 0.26 to 0.50
indicate a weak structure, values 0.51 to 0.70 indicate a rea-
sonable structure, and values > 0.71 indicate strong structure
(Ambrosini etal. 2009).
We compared home range estimates for an overlapping
site use during moult and winter (after the first breeding
season) and between individuals from shared and non-shared
breeding regions within the same season. We calculated 95%
and 50% kernel density contours using the adehabitatHR
package (Calenge 2011) in R, using h = ”LSCV/h-ref” as the
smoothing parameter. We used only data from individuals
that covered a full season and only one position of the best
location class per day to avoid overrepresentation of some
intervals. To calculate sizes of home ranges and core areas in
km2, we converted the area of kernels to UTM units and cre-
ated a new kernel (95% and 50%) based on the UTM coor-
dinates. The UTM zone was chosen individually depend-
ing in which zone the estimated area was located using the
WGS1984 datum.
We furthermore used these kernel density estimates to
compare consistency in site use and a potential spatial over-
lap of individual home ranges between 2 consecutive years.
When the same time period during winter (n = 4) and moult
(n = 1) in consecutive years was available, 50% and 95%
density contours were calculated. Consistency and flex-
ibility of individual migratory movements, phenology and
site utilisation between the 2years was calculated using an
ANOVA-based repeatability index (also called the intra-
class correlation coefficient R) as an agreement of measure-
ments between consecutive years (Nakagawa and Schielzeth
2010). The repeatability index offers information about the
proportion of the total variation that is reproducible among
repeated measurements of the same subject or group (Les-
sells and Boag 1987). The repeatability index is based on
variance components derived from a one-way analysis of
variance (ANOVA). This ANOVA-based method is one of
the most commonly used methods to calculate repeatabil-
ity in behavioural and evolutionary biology (Nakagawa and
Schielzeth 2010) and has been applied in several studies
on shore- and seabirds (Battley 2006; Vardanis etal. 2011;
Conklin etal. 2013; Ruthrauff etal. 2019). The F table of an
ANOVA, with the individual identities treated as factorial
predictors, were used to calculate ANOVA-based repeatabil-
ity estimates (RA). The repeatability (RA) was calculated by
the formula introduced by Lessels and Boag (1987), where
the mean between individual sum of squares (MSA), the
mean within-individual (residual) sum of squares (MSw)
and the sample size for each individual (2years’ data) are
considered. We considered all repeatabilities with 0 as no
repeatability, all repeatabilites = 1 as total repeatability, all
repeatabilities < 0.5 as low repeatability and all relatabili-
ties > 0.5 as medium–high repeatability. The applicability
of the method was confirmed in comparison with Linear
mixed-effects model (LMM)-based methods (Stoffel etal.
2017), as both methods showed identical results (Appendix
A3, TableA1). The utilisation of sites between 2 consecutive
years was compared during spring staging (n = 9 individuals
and 13 locations utilised in both years), breeding (n = 7 indi-
viduals) and moulting (n = 3 individuals by tracking data,
n = 19 individuals by isotope data). We estimated repeatabil-
ity between 2 consecutive years using Gaussian distributed
data of position information, such as longitude/latitude on
a small scale or isotope value on a broad scale (only for
moult location) and the phenology (arrival/departure) using
ordinal dates as the response variable and ID as the explana-
tory variable of the ANOVA (see Table1, A1). Additionally,
individual tracks were mapped where two seasons of each
spring (n = 7) and autumn migration (n = 3) were available.
All estimates of averages are provided with standard
deviations.
Stable isotope analyses
Stable isotope ratios are used in studies of the foraging
ecology of seabirds, because they are proxies for the origin
of resources (stable carbon isotope ratios δ13C) and rela-
tive trophic levels (stable nitrogen isotope ratios δ15N, e.g.
Bedolla-Guzman etal. 2021). Feathers are used for stable
isotope analyses, because feather proteins, formed during
moult, reflect the stable isotope values of the diet at the time
of their synthesis and can thus provide information on dis-
tribution and diet at the time of moult (Hobson and Clark
1992; Oppel and Powell 2008). Once grown, feathers are
metabolically inert (Hobson 1999; Atkinson etal. 2005) and
if potential moulting areas differ in their stable isotope val-
ues, it is possible to infer from δ13C values where the feather
was grown (Hobson 1999).
We sampled the white neck feathers that are characteristic
for the winter plumage and are grown during the autumn
moult area (Streseman and Streseman 1966, Berndt and
Drenckhahn 1974, Mendel etal. 2008) from all red-throated
divers tracked during this project (n = 33). We used these
feathers to determine the area where these feathers are grown
and thus, the autumn moulting sites in the season previous to
capture on a broad scale using stable isotope analyses. The
white neck feathers of red-throated divers are particularly
suitable for this purpose as they are easy to distinguish to
ensure that this feather sample and its stable isotope values
are representative of the autumn moult.
We linked isotope values to moulting regions for birds
tracked with satellite transmitters, assuming that birds are
faithful to regions between years. We used a sub-sample
set of individual data (n = 10) provided by the satellite
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Marine Biology (2022) 169: 114
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transmitters and determined the moult location of each bird
to relate the isotopic information of feathers to geographic
regions (North Sea vs. Baltic Sea). Then, we used these val-
ues to assign moult locations for the remaining birds tracked
with satellite transmitters (n = 9) and for birds where no
information from tracking data was available (n = 14). The
feathers we sampled from satellite tracked birds were grown
in the year before and thus tracking data collected in this
study did not include the time when the sampled feathers
were grown. Therefore, additionally literature of isotope val-
ues in the North and Baltic Sea were incorporated to confirm
the classification. We revised carbon isotope values from
muscle, eggshells and feathers of piscivorous vertebrates
whose diets overlap with that of the red-throated divers (Das
etal 2004, Céline Mahfouz etal. 2017, Corman etal 2018,
Kleinschmidt etal. 2019, St John Glew etal. 2019, Christie
2021, Table2) to obtain information on differences in carbon
stable isotope values between the two seas. Stable isotope
values were finally compared (North Sea vs. Baltic Sea)
using the Wilks’ Lambda test and a One-way MANOVA
(Bartlett Chi2) and the package rrcov (Todorov and Filz-
moser 2009) to reveal if they statistically differ.
The isotope data were used to assign pre-capture moult
locations to all birds tracked in this study (n = 33). When
information about utilised moulting sites after capture was
given by the tracking data (n = 19), it could be compared
with the moulting sites assigned by isotope data. Therefore,
moulting areas could be identified on a broad scale through-
out the year and between years.
Samples were analysed at LIENSs Stable Isotope Facility
at the University of La Rochelle. The treatment of feather
samples and information about running the stable isotope
analyses followed the approach described in Dorsch etal.
(2019) and is provided in the supplementary material (A8).
Results
Migratory routes andutilised sites
Breeding destinations of red-throated divers captured
in the eastern German Bight (n = 33) covered the whole
breeding range of the NW European wintering population
(65°W–98°E) specified by Wetlands International (2018,
2022). The breeding areas included destinations in Green-
land (n = 2), Svalbard (n = 2), Norway (n = 4) and norther n
Russia (n = 25) (Fig.2). Divers from one capture site dis-
played both, a longitudinal migration (eastern direction to
Russia, n = 25; western direction to Greenland, n = 2) and
a latitudinal migration (central direction to Norway, n = 4,
Svalbard, n = 2). Consequently, migratory directions are in
the following termed as the Greenland direction, the Scan-
dinavian direction (Svalbard and Norway) and the Russian
direction. Of birds with a settlement in a breeding site in
northern Russia (n = 24), 79% of breeding positions (n = 19)
were located in the Siberian Arctic (Yamal, Gydan and Tai-
myr peninsulas and West Siberian Plain) (65°E–98°E) and
21% (n = 5) in the European part of northern Russia (Kola
Peninsula, Kanin Peninsula, Pechora Sea (Tobseda Island)
and Novaya Zemlya) (40°E–55°E). The migratory pathways
of single individuals from all breeding areas were mixed on
the route towards the Scandinavian direction (east Green-
land n = 1, Svalbard n = 2, Norway n = 4, and northern Rus-
sia n = 1) and overlapped spatially from 54°N (capture site)
till 68/70°N before leading to the final migration direction
(Fig.2).
Along the route to northern Russia (n = 25), we identified
12 staging sites of which 7 were located within the Baltic
Sea. High frequented staging sites were the Skagerrak-Kat-
tegat (7%), the Pomeranian Bight (10%), the Gulf of Bothnia
and in particular the Gulf of Riga (24%, n = 9, Fig.1, A4).
In this context, the following winter showed that the cap-
ture area itself (eastern German Bight) served as a staging
area (40%, n = 10) if individuals spent the winter elsewhere
(Fig.4).
In autumn, on the way back from the breeding areas, most
red-throated divers followed the directions and pathways
they have already used during the spring migration with 77%
of red-throated divers performing a step-wise migration with
separate moult and winter migrations (Figs.2 and 6).
All birds moulting in the North Sea according to track-
ing data had δ13C > -18‰, while birds that moulted in the
Baltic Sea had δ13C < -18‰. This threshold was confirmed
by the literature values. We thus applied this classification
to all birds tracked through the annual cycle (n = 33) and
assigned moulting regions in the Baltic Sea and the North
Table 2 Isotope values from
North and Baltic Sea assigned
by published data and data from
this study
Organism Tissue δ13C North Sea δ13C Baltic Sea References
Harbour porpoise Muscle Average −16.5 ‰ Average −18.25‰ Das etal 2004
Herring gull eggs Eggshell −16 to (−19) ‰ −21‰ Corman etal. 2018
Puffin Feather − 15.87 (0.38) to − 16.81 (0.72) n.a Glew etal. 2019
Razorbill Feather − 16.47 (0.71) to−16.48 (0.68) n.a Glew etal. 2019
Common Guillemot Feather − 16.77 (0.91) n.a Christie 2021
Red-throated diver Feather > −18 ‰ to (−15.5) < −18 ‰ – (−22) Our study
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114 Page 8 of 19
Fig. 2 1st year spring and autumn migration tracks of red-throated
divers (n = 31, n = 19) from the capture location in the German Bight
to their breeding areas (above) and from potential breeding locations
to potential moulting locations and to wintering sites (below). Col-
ours of migration tracks indicate different breeding regions (violet
to Greenland; light blue to Svalbard; orange to Norway, black to the
eastern arctic of northern Russia; grey to the Siberian arctic of north-
ern Russia). Individual time of stay in spring staging areas along the
migration route to Northern Russia for 32 staging stops performed by
n = 23 individuals is visualized as zoom included in the map
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Marine Biology (2022) 169: 114
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Page 9 of 19 114
Sea to a similar number (51% and 49%, respectively). The
isotope values from red-throated divers probably indicated a
split between moulting in North Sea and Baltic Sea (Fig.3).
Clusters of SI were significantly different between samples
(Wilks' Lambda = 0.084, χ2 = 76.61, DF = 2.00, p < 0.001)
that would, based on literature on other species (Table2), be
considered to come from the Baltic Sea or from the North
Sea.
Tracking data revealed that wintering sites were distrib-
uted in the Baltic Sea, North Sea (eastern German Bight and
southern Bight) and Irish Sea with the highest proportion
using the eastern German Bight (60%, n = 10, Fig.4) either
during the complete season or temporarily.
Migratory connectivity
Starting on the capture site, red-throated divers spread out
over a large geographic range for breeding (Figs.2 and
5). Considering connectivity among individuals from one
breeding region, only individuals from northern Russia
were included as the sample size for the other regions were
too small to show meaningful results. Individuals breeding
in northern Russia used mainly routes via the Baltic Sea
to migrate to and from breeding sites, with one exception
that moved along the Northern Cape (Fig.2). During spring
migration individuals breeding in northern Russia showed no
consistent pattern with varying staging stop locations, stag-
ing stop durations and travel times (Fig.2, Table3). These
individuals spread out to several moulting sites (stationary
period from September to December > 21days) in the North
and Baltic (38% and 62%, respectively, Figs.2, 4 and Fig.5).
Within the Baltic Sea, the majority of birds (n = 67%) spent
the potential moulting time in the Gulf of Riga. During
winter, 50% of the tracked birds breeding in northern Rus-
sia utilised the German Bight, whereas the other 50% dis-
tributed elsewhere (25% in the southern Bight, 8% in the
Irish Sea and 17% in the Baltic Sea), (Figs.4 and 5). Kernel
density estimation of individuals from one breeding region
showed only partly overlapping home ranges but these indi-
viduals mixed with individuals from other breeding regions
(northern Russia n = 4, Svalbard n = 1, Fig.4). The distance
between individual areas within the moulting period as well
as within the winter period was up to 1000km. Combina-
tion of tracking data (n = 19, Figs.4 and 5) and additional
birds determined by stable isotopes (n = 13) revealed that
individuals that moulted in the Baltic Sea (n = 15) migrated
all from northern Russia but red-throated divers that moulted
in the North Sea (n = 17) were composed of individuals from
several breeding regions, northern Russia (52.9%), Norway
(23.5%), Svalbard (11.8%) and Greenland (11.8%). Migra-
tory patterns varied between individuals with the majority
performing a separate moult and autumn migration and a
few individuals performing a direct migration (migration to
a site that was utilised during moult and winter).
Quantification of migratory connectivity between indi-
viduals captured in the German Bight (eastern North Sea)
indicated no relation between individuals from one breeding
region (i) to moulting or (ii) wintering sites. Calculation of
a Mantel correlation coefficient indicate no spatial structure
and a low connectivity but gave no significant results: cap-
ture site to breeding: rM; = 0.069, n = 31, p = 0.202; breed-
ing to moult (Siberian ind.): rM = 0.135, n = 13, p = 0.215;
breeding to winter (Siberian ind.): rM = 0.274, n = 9,
p = 0.103.
Thus, individuals from northern Russia spread out to sev-
eral winter sites with no uniform pattern of individuals from
this breeding region and various utilisation areas and mix
with individuals from other breeding regions (Figs.4 and 5).
Timing ofmigration andgeographic relations
Migration distances can only be given as minimum esti-
mates assuming straight flight paths between consecutive
Argos positions. Referring to Cox (2010) and Rappole
(2013), the majority of red-throated divers in this study
migrated > 1000km and can be considered as long-distance
migrants (87.9%) and just a small number of birds moved
short distances < 1000km to Norway (12.1%) (Table3).
Breeding location was significantly correlated with dura-
tion of migration (longitude: r = 0.407, n = 29, p = 0.027;
latitude: r = 0.384, n = 29, p = 0.039). Overall, individuals
breeding at a higher longitude in Russia needed a longer trav-
elling time (Fig. A2a). The longest travel time during spring
migration was 65days and this bird headed to Taymir Pen-
insula in northern Russia. Departure date (ordinal date-day
Fig. 3 Stable isotope values of 33 red-throated diver feather samples
assigned to the region where they were moulted. Data points show
feathers of 16 individuals moulted in the Baltic Sea and 17 individu-
als that moulted in the North Sea
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Marine Biology (2022) 169: 114
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Fig. 4 Areas used by red-throated divers during moult (above) and
during winter (below). The legend on top informs about individual
colours and corresponding breeding region. Estimated Kernel densi-
ties 95% and 50% for utilised areas in Baltic and North Sea during
moult season (n = 13) and in Baltic, North and Irish Sea during win-
ter season (n = 10) for a time period that lasts from the first date in
the area (arrival) until last date (departure). Individual maps are dis-
played when birds utilised the same area and their home ranges are
not distinguishable, (moult: Eastern German Bight n = 2, Bay of Riga
n = 6, winter: Eastern German Bight n = 5). 95% kernel density con-
tours are displayed with 70% transparency and 50% kernel density
(core habitat use) with 50% transparency
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Marine Biology (2022) 169: 114
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of year) from wintering sites was significantly correlated
with breeding latitude but not with breeding longitude (lon-
gitude: r = 0.335, n = 9, p = 0.344; latitude: r = 0.714, n = 9,
p = 0.020). More northerly located breeders departed later
from their wintering site than southerly located breeders,
suggesting a latitudinal gradient (Fig. A2c). Arrival date to
breeding areas (ordinal date-day of year) was significantly
correlated with a higher breeding longitude but not with
a higher breeding latitude (longitude: r = 0.695, n = 29,
p < 0.001; latitude: r = 0.373, n = 29, p = 0.078). More east-
erly located breeders arrived later at their breeding sites than
westerly located breeders with up to 40days later arrival,
suggesting a longitudinal gradient (Fig. A2b). Departure
date from breeding sites was neither correlated with breed-
ing longitude (n = 20, p = 0.941) nor with breeding latitude
(n = 20, p = 0.285, Fig. A1b).
We observed no correlation between breeding positions
(long/lat) and duration of staging (n = 25, p = 0.852, Fig.
A1a) but a significant correlation between a longer travel-
ling time and a longer duration of staging (r = 0.643, n = 27,
p < 0.001, Fig. A3) that was correlated with a higher num-
ber of staging stops (rs = 0.468, n = 27, p = 0.014, Fig. A3).
Although staging time was positively correlated with travel-
ling time, the distance itself had no effect on either staging
time (n = 25, p = 0.986, Fig. A1c) or travelling time (n = 31,
p = 0.116, Fig. A1c).
Repeatability ofyear‑round movements andsite
utilisation betweenconsecutive years
Not all birds caught in the German Bight in winter and
spring returned to this location during the following winter.
32% of the tracked birds used this area for moult and 54%
for wintering. Individuals that did not use this area during
moult or wintering used this area as a staging site or a short
stop along migration.
The temporal pattern and repeated site utilisation
with regard to spring staging sites, breeding and moult-
ing areas showed high individual consistency between
years (Fig.6, TableA1). Visual inspection of individual
Fig. 5 Population spread and interpopulation mixing of red-throated
divers from the NW European winter population starting at the cap-
ture site (eastern German Bight) heading to breeding regions and
from breeding regions to moult and winter sites. From capture site
to breeding data are based on tracking data, from breeding to moult
data are combined of tracking and additional birds determined by
stable isotopes and from moult to winter data are based on tracking
data. Each breeding region is presented in a specific colour consist-
ent with the with the division made in Fig. 1 (violet = Greenland,
orange = Norway, light blue = Svalbard and dark blue = Norther n Rus-
sia) and Boxes show number of individuals using this region
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Marine Biology (2022) 169: 114
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migratory pathways between consecutive years showed
similar movements in six of seven individuals, however,
one individual (146,444) used different pathways between
two spring migrations (Fig.6). Kernel density estimates
from individuals for which tracking data were available
from an overlapping period during moult and winter in
consecutive years showed that home ranges overlapped or
were close, indicating consistent site use in consecutive
years (Fig.6).
Repeatability (TableA1) towards number of indi-
vidual spring staging stops was moderate between
years (RA = 0.407, F8,9 = 2, p = 0.161). The repeatability
towards individual spring staging longitudes (RA = 0.954,
F 12,13 = 42.9, p < 0.001) and spring staging latitudes
(RA = 0.982, F12,13 = 107.8, p < 0.001), that appeared in
both years, was high. High repeatability’s were also found
for breeding longitudes (RA = 1, F6,7 = 24,945, p < 0.001),
breeding latitudes (RA = 1, F6,7 = 9125, p < 0.001) and
moulting locations by isotope analyses (RA = 0.785,
F18,19 = 8.278, p < 0.001). Between year repeatability
of migratory timing indicated a less consistent pattern
for arrival times in spring staging times (RA = 0.604,
F12,13 = 4.1, p = 0.009), departure times from spring stag-
ing sites (RA = 0.751, F12,13 = 7.0, p = 0.001), arrival times
in breeding areas (RA = 0.552, F6,7 = 3.5, p = 0.064), depar-
ture times from breeding areas (RA = 0.408, F3,4 = 2.4,
p = 0.211) and arrival times in moulting areas (RA = 0.876,
F2,3 = 15.11, p = 0.027).
Discussion
Based on tracking data and stable isotope analyses, we
obtained a comprehensive dataset on annual movements of
NW European red-throated divers that addressed our hypoth-
eses as outlined below. Tracking data lasted for up to 2 con-
secutive years and thus allowed to assign individual site uti-
lisation within and between years. Stable isotope analyses
added information about moulting sites where no tracking
data were available. Isotopic values in our study seem to be
clearly separable between North and Baltic Sea and in line
with the locations determined by the tracking data. Although
matching of isotope data and tracking data without tempo-
ral overlap may have some uncertainties, published isotopic
values from the North and Baltic Sea backed up our assign-
ment of moulting sites. This approach has previously been
used successfully by Oppel and Powell (2008) to determine
winter locations of eiders (Somateria spectabilis). They also
used information from satellite tracked birds to isotopically
delineate regions and assigned feathers of birds not tracked
with satellite transmitters to regions using their stable iso-
tope values.
Do red‑throated divers have alow degree
ofmigratory connectivity?
Considering ring recoveries in coastal areas around the
North Sea (Okill 1994), we expected a mix of individuals
Table 3 Temporal pattern and distances within the first year moved of red-throated divers from different breeding regions during spring and
autumn migration (mean ± SD)
Breeding
region
Migration
route
Migration
distance (km)
Travel time
(days)
Staging stop
No
(> 5days)
Duration per
staging stop
(days)
Breeding:
arrival/
departure
date ± days
Moult:
arrival/
departure
date ± days
Winter:
arrival/
departure
date ± days
Spring Northern
Russia
(n = 24)
Russian
direction
4,015 ± 751 42.30 ± 12.6 1.5 ± 0.8 13.21 ± 744 09.06. ± 13
(n = 24)
07.09. ± 13
(n = 20)
n.a n.a
Norway
(n = 4)
Scandina-
vian direc-
tion
1403 ± 641 31 ± 24.8days 1.3 ± 1.2 11.2 ± 975 25.05. ± 6
(n = 3)
n.a
n.a n.a
Greenland
(n = 2)
Greenland
direction
4,457 ± 1213 34.5 ± 10.6 2 ± 0 9.75 ± 303 22.06 ± 5
(n = 2)
31.08. ± 0
n.a n.a
Svalbard
(n = 2)
Scandina-
vian direc-
tion
2,303 ± 301 12.5 ± 1.4 0,5 ± 0,5 3 ± 3 27.05. ± 2
(n = 2)
14.09. ± 0
n.a n.a
Autumn Northern
Russia
(n = 18)
Russian
direction
3,830 ± 668 97 ± 23.76 Moult 53.67 ± 1422 n.a 05.10 ± 12
(n = 18)
24.11 ± 16
(n = 13)
20.12 ± 17
(n = 12)
08.04. ± 22
(n = 10)
Svalbard
(n = 1)
Scandina-
vian direc-
tion
2090.6 22 Moult 43 n.a 07.10. ± 0
18.11. ± 0
25.11 ± 0
08.05. ± 0
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Marine Biology (2022) 169: 114
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from several breeding regions in this area and thus a low
degree of connectivity. We found individuals from four
different breeding regions captured in one local area dur-
ing late winter and early spring. The distances and water
bodies between these breeding regions indicates a delimita-
tion of these regions. We captured red-throated divers in
one relatively local wintering/spring staging site and not in
the breeding area, as most other studies analysing migra-
tory connectivity do. A possible bias could have been that
the connectivity would have been overestimated if all birds
would have headed from the same winter region to the same
breeding region and back. In this case, individuals from a
shared breeding region that use other winter regions, would
have been missed as they were out of our sample range. In
our case, however, we found a relatively high spread from
individuals heading to distant breeding regions and of indi-
viduals from one breeding region to several non-breeding
regions and therefore this bias is unlikely to affect the results.
However, that individuals migrated along their routes to a
shared breeding area in northern Russia indicates some
degree of connectivity, as most of these individuals moved
along the Baltic Sea and used similar staging sites along
this route. In another study, McCloskey etal. (2018) tagged
red-throated divers in four breeding regions in Alaska. These
individuals also followed similar migration routes, indicating
some degree of connectivity, but did not display a discrete
use of population-specific non-breeding areas. The fact that
almost all red-throated divers in this study that bred in north-
ern Russia migrated along the Baltic Sea could also be due
to the fact, that they follow an established migration route
that is used by various species of waterfowl, the Northeast
Atlantic Flyway (BirdLife International 2010), rather than to
the fact that they exhibit community-specific patterns (Boere
and Straud 2006). On a smaller scale and considering site
Fig. 6 Migration routes of individuals during two subsequent years
(first year = solid line, second year = dotted line, the black arrow
indicates the direction of movement). The left side shows individual
spring migration tracks marked by colour (n = 7) from capture site
to potential breeding sites in the first year and from wintering site
to potential breeding sites in the second year. The right side shows
individual moult migration tracks marked by colour from potential
breeding sites to potential moulting sites (n = 3) and to wintering
sites (n = 1) for two consecutive seasons. Individual home ranges
when data transmission allowed for two overlapping time periods
during winter and moult in consecutive years are visualized as zoom
included in the map
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Marine Biology (2022) 169: 114
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utilisation during the stationary non-breeding season (moult
and winter), red-throated divers in this study spread to dis-
tinct areas. Following the ‘weak–strong’ continuum defined
by Webster etal. (2002), this pattern would suggest that red-
throated divers displayed a low or diffuse connectivity with
individually variable movements and no specific or uniform
pattern of individuals from one site or migratory direction.
Statistical tests showed no significant correlation between
utilised breeding regions, moulting or wintering sites, which
supports the low connectivity indicated by Fig.5. Also, ker-
nel density estimation during moult and winter in the season
after capture showed only partly overlapping home ranges
between individuals from a given breeding region (Fig.4).
Our results are consistent with the study of Gray (2021) who
found low connectivity of red-throated divers in eastern
North America, indicating that red-throated divers display a
highly individual movement behaviour that is adapted rather
to individual qualities and environmental conditions than to
community-specific patterns.
Does thelocation ofbreeding area (longitude/
latitude) affect thetiming andspatial pattern
ofannual movements?
Like other species, red-throated divers seem to follow an
endogenous schedule of migration together with the strong
phenological gradient along the spring migration route to
Arctic breeding areas (Gordo 2007; McNamara etal. 2011;
Shariatinajafabadi etal. 2014; Smith etal. 2020). Arrival
dates in more westerly located Arctic breeding sites were
about 40days earlier than arrival in more easterly Arctic
breeding sites, indicating a longitudinal gradient. We did
not find a correlation between departure from breeding sites
and breeding location, which could be related to variations
in breeding success. Birds from more northern breeding
areas departed later from wintering areas, consistent with
the pattern of later arrival at breeding areas. The temporal
pattern seems to confirm that timing of migration appears to
follow environmental conditions (e.g. growing seasons, ice-
free conditions and temperatures) in arctic breeding regions,
similar to other waterfowl and shorebirds (Schwartz 1998;
Shariatinajafabadi etal. 2014; Smith etal. 2020). Migratory
movements and breeding events of shorebirds and avian her-
bivores can be constrained by plant phenology and spring
salt marsh productivity (Shariatinajafabadi etal. 2014; Smith
etal. 2020). Winkler etal (2014) stated that migration strat-
egies can be seen as the mapping of actions (e.g. feeding,
departure) on cues (e.g. daylength, feeding or wind condi-
tions). Although red-throated divers are piscivorous seabirds
and do not directly depend on plant phenology, other factors
such as seasonal day length and temperatures could be indi-
cators that lead birds to hit the right time with suitable con-
ditions at breeding sites. In this case, a later arrival time at
more easterly located breeding locations might also explain
why a longer travel time (duration of the spring migration)
was significantly correlated with a more easterly breeding
location, but not with distance travelled (Fig. A1c, A2a).
Another factor that should be taken into account here is the
individual need to refuel along the route (Weber and Hou-
ston 1997). We found a significant correlation between a
longer travelling time and a longer duration of staging and a
higher number of staging stops (Fig. A30). In this context, as
medium-sized birds with weight varying between 1400 and
2000g (own observations) and high wing loading (Storer
1958; Lovvorn and Jones 1994) using flapping flight, the
energy expenditure of divers is relatively high (Pennycuick
1989). To refuel energy reserves, divers, travelling to more
distant areas (longitudes) may, therefore, need more and
longer staging stops, thus increasing the total travel time.
The high energy expenditure though might be counteracted
by the use of favourable wind conditions (tailwinds), or
very good foraging conditions at staging sites. However, our
results are in line with the finding of McCloskey etal. (2018)
and Gray (2021) who found red-throated divers to perform
long/slow migrations with many stop-overs.
Do individuals faithfully utilise areas duringtheir
key life history stages betweenyears?
Information about individual consistency between years
helps to understand the capacity to cope with habitat change
and selection pressures (Dias etal 2010, Conklin etal. 2013,
McFarlane etal 2014, Merkel etal. 2020). Based on a high
site fidelity observed in breeding areas (Okill 1992; Poessel
etal. 2020), we expected a similar high site fidelity for the
non-breeding sites. The sample size for individual site utili-
sation in two consecutive years was rather small with data of
(n = 9) individuals for spring migration and of (n = 7) indi-
viduals for breeding sites. The data set of (n = 3) individuals
tracked for moulting sites could be enhanced by the isotopic
data (n = 19). Although the sample size is rather small, the
results of the repeatability analyses of annual migratory
movements seem to confirm and extend previous studies on
site fidelity (Okill 1992; Poessel etal. 2020).
Similar to the strong winter site fidelity (85%) of com-
mon loons/ great-northern divers (Gavia immer) shown by
Paruk etal. (2015) red-throated divers exhibit a relatively
high fidelity towards the different areas visited during
the annual cycle: migration routes, staging, breeding and
moulting areas, however, with some variation for individu-
als and temporal pattern. Home ranges estimated by Ker-
nel densities in 2 consecutive years and during the same
time period in moult and winter could only be shown on
the basis of a few individuals (n = 4), but revealed that
these individuals had either some home range overlap in
consecutive seasons, or the home ranges were located in
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Marine Biology (2022) 169: 114
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Page 15 of 19 114
the same area and close to each other. Home range estima-
tion and calculation of repeatability might indicate that
site selection is driven by macro-selection of a larger area
with sufficient frequency of opportunistic prey encounters.
Once such a profitable area with suitable feeding condi-
tions is found, it is used faithfully from year to year. In
this study, we only have 2 years of data and in the context
of fidelity and flexibility, it is equally plausible that red-
throated divers exhibit fidelity only until a site of use is no
longer suitable, in which case the flexibility of the divers
would be expressed. Skov and Prins (2001) have shown
that the eastern German Bight is known to be particularly
attractive to red-throated divers due to the frontal zone
and resulting favourable feeding conditions with suitable
prey species (Guse etal. 2009; Kleinschmidt etal. 2019).
If habitat selection is driven by a macro-selection, it could
be that habitat change has an effect on a smaller spatial
scale and displacement is a process happening at smaller
scales. However, in this context, results from studies on
red-throated diver distributions and displacement effects
in the eastern German Bight showed that red-throated
divers remained in the general area, but shifted their dis-
tribution and congregated outside disturbed areas (Men-
del etal. 2019; Vilela etal. 2021). Mendel etal. (2019)
analysed long-term datasets of aerial and ship based sur-
veys, whereas Vilela etal. (2021) analysed long-term
datasets of aerial surveys. However, no population decline
was observed (Vilela etal. 2021). Considering this, our
data based on the visualised tracks, single home ranges
(Fig.6) and statistical analyses of individual repeatabil-
ity (TableA1) show an individual consistent site use in
consecutive years, considered over a broad scale. Com-
bined with the findings of Mendel etal. (2019) and Vilela
etal. (2021), these data suggest that red-throated divers
are somewhat flexible to change sites at small scales, but
may have limited flexibility to change sites at large scales
in response to large-scale habitat loss.
Arrival and departure times were more consistent at
non-breeding sites than at breeding sites. The high consist-
ency in arrival times in moulting areas might limit their
flexibility in responding to anthropogenic change during
that time period when birds are flightless. Similar to other
medium-to-large sized diving bird species, divers are
expected to perform a synchronous wing moult (Thomp-
son and Kitaysky 2004) rendering them flightless and thus
require undisturbed areas during this time. Arctic breed-
ing areas on the other hand are characterised by a short
arctic summer and thus a narrow seasonal window where
breeding can take place (Klaassen 2003). Therefore, this
Arctic breeding bird species may have adapted to a more
flexible timing of arrival to match optimal conditions in
breeding areas, triggered by colder or warmer winter or
spring temperatures.
Conclusions andimplication forconservation
In agreement with prior research (e.g., Mendel and Garthe
2010; Dierschke etal. 2012; Mendel etal. 2019), our study
confirms the importance of the North Sea, in particular
the eastern German Bight, as a wintering area, staging site
before spring migration and moulting area for red-throated
divers. The consistent use of the Gulf of Riga in our study
in spring and autumn confirmed that this area is another
important site for red-throated divers migrating from north-
ern Russia and moving to the North Sea and adjacent waters
(Berndt and Drenckhahn 1990; Helcom 2013).
Low connectivity might indicate resilience to environ-
mental change on a population level, but the high fidelity
towards sites during the stationary non-breeding season indi-
cates a rather high consistency of annual movements which
may result in a low individual flexibility. These findings are
highly important to be considered for future appropriate con-
servation measures. All divers in this study were captured in
the eastern German Bight but migrated to separate breeding
areas and used this area with varying intensity in the fol-
lowing season. The observed low or diffuse connectivity of
individuals from one breeding region distributes the effect to
only a proportion of individuals from each breeding region.
Compared to a high connectivity, where all individuals
from one breeding region would experience the same non-
breeding conditions over the same time in this area, a higher
resilience can be suggested (Newton 2008; Rushing etal.
2016). Interannual movements of red-throated divers on the
other hand showed a relatively high individual repeatabil-
ity and consistent site use. Consistent use of high energetic
mobile prey species (Guse etal. 2009; Kleinschmidt etal.
2019) indicates that the occurrence of these prey species
seem to be an important habitat criteria. Considering the use
of multiple core areas during winter and the dependence of
divers on these mobile prey species in dynamic marine habi-
tats, could also indicate some flexibility. Regarding anthro-
pogenic pressures and altered environmental conditions, a
poor wintering habitat quality can carry-over to breeding
sites and influence reproductive success (Marra etal. 1998;
Moore 2005; Harrison etal. 2011; Rushing etal. 2016). The
winter population of red-throated divers shows strong avoid-
ance towards the increasing anthropogenic pressure (Garthe
etal. 2015; Mendel etal. 2019) but does not decline (Vilela
etal. 2021). The low connectivity could counteract a quick
population decline by having only small effects on popula-
tions of this long-lived species. If the impact always affects
only one number or a proportion, but not the entire popula-
tion, it may take longer for the impact to become apparent.
More research on reproductive success in the arctic breed-
ing regions is needed to link population estimates between
breeding and non-breeding areas. If a breeding population
experiences individually different travel times, caused by
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Marine Biology (2022) 169: 114
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114 Page 16 of 19
altered conditions in the non-breeding areas, this may result
in different arrival times at the breeding site and a possible
mismatch (Marra etal. 1998; Moore 2005; Rushing etal.
2016). It should also be noted here that, climate warming
can alter ice-free periods in Arctic breeding areas which has
the potential to alter the timing of migration (Walther etal.
2002; Catry etal. 2013; Wauchope etal. 2017).
Although anthropogenic pressures in the North Sea
appear to be distributed among individuals from multiple
populations, when considered cumulatively and taking into
account individuals breeding in northern Russia, multiple
threats during migration come together, such as gillnet fish-
ing and pollution of the Baltic Sea (Dagys and Žydelis 2002;
Rubarth etal. 2011; Žydelis 2013). When it comes to future
spatial planning, our data support the finding that all infor-
mation on species abundance and sites used along the migra-
tion route needs to be considered, regardless of whether they
are geographically or politically distant (Runge etal. 2014;
Johnston etal. 2020).
Supplementary Information The online version contains supplemen-
tary material available at https:// doi. org/ 10. 1007/ s00227- 022- 04096-x.
Acknowledgements We thank G. Guillou from the Plateforme Analy-
ses Isotopiques of LIENSs laboratory for running the stable isotope
analyses. Thanks are due to the CPER (Contrat de Projet Etat-Région)
and the FEDER (Fonds Européen de Développement Régional) for
funding the IRMS of LIENSs laboratory. The Institut Universitaire de
France (IUF) is acknowledged for its support to PB as a Senior Mem-
ber. Many thanks to Nadja Küpper and Yvonne Schumm for helpful
discussion and support with the statistics. We greatly thank everybody
involved in the capture of divers for their support. Thomas Grünkorn
and Jorg Welcker completed our field team and supplied valuable sup-
port. Thomas Grünkorn also contributed by ringing of the captured
red-throated divers. Sören Zenner (OS-Energy) allowed flexible organi-
sation and provision of ships during the field seasons and we thank the
ship captains and crews of the MS Madog and MS Arctic Hunter for
their reliability and support during fieldwork. Finally, we thank the
reviewers for their valuable recommendations.
Author contributions All authors were involved either field work, lab
work or in the writing of the manuscript. All authors read and approved
the final manuscript.
Funding Open Access funding enabled and organized by Projekt
DEAL. The DIVER project is supported by the Federal Ministry for
Economic Affairs and Energy on the basis of a decision by the German
Bundestag (funding ID 0325747 A/B).
Data availability All data have been deposited in the Movebank
repository.
Declarations
Conflict of interest The authors explicitly declare that they have no
competing interests.
Ethical approval The ethical rules as well as the legal requirements for
the fieldwork have been met. All fieldwork (animal capture, sampling
and tagging) was approved by BfN (Federal Agency for Nature Con-
servation, Germany, 05.08.2014; and Ministry of Environment and
Food Denmark, Danish Veterinary and Food Administration, permit
no. 2014-15-0201-00239, issued 18.12.2014).
Consent for publication All co-authors have seen and agreed with the
contents of the manuscript for publication.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article's Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
the article's Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.
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