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Movement patterns of Sanderling (Calidris alba) in the East Asian–Australasian Flyway and a comparison of methods for identification of crucial areas for conservation



Most migratory shorebird populations around the world are in jeopardy, none more so than those of the East Asian Australasian Flyway (EAAF). In order to preserve these highly mobile species detailed understanding of their use of fuelling and resting sites along the flyway is required. In this study we used light-level geolocators and new analytical tools to reveal individual breeding locations and detailed migration routes of 13 Sanderlings (Calidris alba) that spend their non-breeding season in South Australia. We then used these individual migration routes to identify the timing and location of important stopping areas and compared this with assessments based on leg-flag resightings and count data. During both northward and southward migration Sanderlings were found to make extensive use of five major areas distributed along the Chinese coastline, the Yellow Sea and the northern end of the Sakhalin Peninsula. Insights gained from these individual migration routes highlighted inherent biases in only using count and resighting data to identify important fuelling and resting sites along the flyway. These findings suggest that individual movement data may therefore be crucial to effective conservation planning of shorebirds in the EAAF and elsewhere in the world.
Movement patterns of Sanderling (Calidris alba) in the East
AsianAustralasian Flyway and a comparison of methods
for identication of crucial areas for conservation
Simeon Lisovski
, Ken Gosbell
, Maureen Christie
, Bethany J. Hoye
, Marcel Klaassen
Iain D. Stewart
, Alice J. Taysom
and Clive Minton
Deakin University, School of Life and Environmental Sciences, Centre for Integrative Ecology,
75 Pigdons Road, Geelong, Vic. 3220, Australia.
Victorian Wader Study Group, c/o 165 Dalgetty Road, Beaumaris, Vic. 3193, Australia.
Applied Ecology Research Group, College of Engineering and Science, Victoria University Footscray Park
Campus, PO Box 14428, Melbourne MC, Vic. 8001, Australia.
Corresponding author. Email:
Abstract. Worldwide, most populations of migratory shorebirds are in jeopardy, none more so than those of the East
AsianAustralasian Flyway (EAAF). In order to preserve these highly mobile species a detailed understanding of their use
of feeding and resting sites along the yway is required. In this study we used light-level geolocators and new analytical
tools to reveal individual breeding locations and migration routes of 13 Sanderlings (Calidris alba) that spend their non-
breeding season in South Australia. We then used these individual migration routes to identify the timing and location of
important stopping areas and compared this with assessments based on resightings of leg-agged birds and count data.
During both northward and southward migration, Sanderlings were found to make extensive use of ve main areas of the
Chinese coastline, the Yellow Sea and the northern end of the Sakhalin Peninsula. Insights gained from the individual
migration routes highlight inherent biases in using only count and resighting data to identify important feeding and resting
sites along the Flyway. These ndings suggest that data on individual movements may be crucial to effective conservation
planning of shorebirds in the EAAF and elsewhere in the world.
Additional keywords: banding data, bird counts, bird migration, conservation planning, light-level geolocation, MCMC
path estimation, migratory connectivity, resightings.
Received 20 April 2015, accepted 1 December 2015, published online 10 March 2016
Animal migration is thought to have evolved in response to
spatiotemporal variation in the abundance of resources and
threats (e.g. Alerstam et al.2003; Dingle and Drake 2007;
McKinnon et al.2010). Despite the immense costs involved in
performing regular, and often long-distance, journeys, migration
is a common and widespread phenomenon in the animal kingdom
(Dingle and Drake 2007). In particular, most species of shorebirds
are migratory (Kirby et al.2008), some of which undertake
migratory movements of up to 30000 km per year (e.g. Harring-
ton 2001; Gill et al.2009; Minton et al.2010).
In order to meet the physiological demands of migration
most migratory birds partition their journey into a series of ights
interrupted by periods of intense feeding and resting (Piersma
1987; Colwell 2010). Consequently most migratory birds depend
on a network of suitable feeding and resting sites along their
yway for successful migration and survival. This reliance on
multiple sites is thought to render migratory species highly
susceptible to changes on a local and global scale (Piersma and
Baker 2000; Runge et al.2014) and, as a result, migratory
populations across a wide range of taxa have declined in recent
decades (Wilcove and Wikelski 2008). Migratory shorebirds in
all global yways, and especially the East AsianAustralasian
Flyway (EAAF), are emblematic of these declines (Bamford
et al.2008; Amano et al.2010).
Effective protection of highly mobile species is predicated
on detailed understanding of how migrants make use of their
yway, and hence the areas and sites that are crucial for conser-
vation (Holdo and Roach 2013; Runge et al.2014). Counts of
birds and bird-banding programs, including leg-agging and
subsequent resightings, have traditionally been used to develop
an initial understanding of migratory movements and to initiate
conservation measures (e.g. Bamford et al.2008; Minton et al.
2011). The effectiveness of these methods is highly dependent
on the spatiotemporal distribution of observers. Accurate tracks
from individual migratory shorebirds equipped with satellite
transmitters have revealed considerably more detail on migration
schedules and routes than traditional methods (Gill et al.2009;
Emu,2016, 116, 168177
Journal compilation BirdLife Australia 2016
Battley et al.2012). Despite the ongoing development of in-
creasingly lighter devices, the use of satellite transmitters is
restricted to a small number of species of larger body mass.
Light-level geolocators (hereafter geolocators) are considerably
lighter than satellite transmitters (<1 g; Bridge et al.2011), and
therefore provide the opportunity to track smaller migratory
birds and greatly expanding the number of species that may
be studied. Initial application of geolocators to shorebirds has
provided valuable information on the migratory movements of
several species using the EAAF (e.g. Minton et al.2010,2013).
However, our ability to make detailed and accurate descriptions
of migratory movements based on geolocator data has, so far,
been hindered by coarse spatial resolution (Lisovski et al.2012)
and the inability to determine spatial location during the equinox
owing to equal daylength across the globe and during the
breeding season owing to constant daylight on the Arctic
breeding grounds of these shorebirds. Consequently, the identi-
cation of critical sites used by large proportions of a population
has thus far remained a key challenge to conservation along the
EAAF, but the ongoing development of geolocator devices and
processing tools offers signicant potential for progress.
In this study, we used new-generation light-level geolocators
that record the full light range, in combination with recently
developed analytical tools, to determine individual movement
tracks and associated uncertainty estimates, providing detailed
understanding of migration patterns of Sanderlings (Calidris
alba) in the EAAF. Sanderlings have a worldwide distribution
and perform some of the longest distance migrations yet
recorded (Lanting 1984; Reneerkens et al.2009; Minton et al.
2013). The species breeds in the Arctic along the northern coast
of European and Siberian Russia, in parts of Alaska, in the
Canadian Arctic and in northern Greenland. During the non-
breeding season Sanderlings use a wide range of wintering sites,
including around 4045N in western Europe, North America
and Asia (MacWhirter et al.2002), and to the southern tips of
South America, Africa and Australia.
Our aims were twofold: (1) to provide a detailed description
of the biannual migration of Sanderlings in the EAAF; and
(2) to compare three different methods count data, leg-ag
resightings, and individual geolocator tracks for identifying
critical areas for shorebird conservation in the EAAF. Geolocator
tracks were processed and compared using the most frequently
used method, hereafter referred to as the simple threshold
method(Lisovski and Hahn 2012), and a recently developed
and more sophisticated Bayesian framework using Markov Chain
Monte Carlo methods to estimate location posterior, hereafter
referred to as MCMC path estimates.In describing the move-
ments of Sanderlings along the EAAF, we further aimed to show
that the recent advances in light-level geolocation allow us to
(1) reveal detailed migration schedules and routes; (2) estimate
the location of the high Arctic breeding sites of the species;
and (3) describe and quantify the degree of within-population
migratory connectivity over the annual cycle.
Animal capture and tracking data
A total of 44 light-level geolocators (Intigeo-W65, Migrate
Technology Ltd, Cambridge, UK) were deployed in March
2012 at Canunda National Park, in south-eastern South Australia
(140110E, 37370S) under approval from the South Australian
Department of Environment, Water and Natural Resources.
Canunda National Park is an important wintering site for Sander-
lings during the boreal winter (austral summer), with typically
between 200 and 400 individuals present from October to April
each year (Bamford et al.2008). Sanderlings were caught, using
cannon nets, in a single catch, on the ocean beach where they
forage and roost. A geolocater was placed on the left tibia of
each bird. The geolocater was fastened to a leg-ag (made from
adarvikPCV sheet) using Kevlar thread reinforced with
Araldite resin cement. To comply with the Australian Bird and
Bat Banding Scheme for South Australia, two additional ags
were employed (orange above yellow). In order to individually
identify birds on which we deployed geolocators, we used an
engraved ag from the orange (upper) ag. This ag was 0.6 mm
thick, bi-coloured material with the orange engraved through to
reveal the black below. Geolocators weighed 0.65 g, making the
total weight, including the ag, ~1 g. This represents <2% of the
mean (lean) body mass of Sanderlings (for measurements, see
supplementary material S1, available online). Based on multiple
reports it appears that shorebirds readily adapt to carrying geo-
locators on their legs and that the device has no signicant effect
on annual survival (e.g. Conklin et al.2010; Niles et al.2010). A
total of 14 geolocators were retrieved (32%), 13 from birds caught
at the site where they had been rst caught and geolocators
deployed, and one from a bird shot in Sakhalin, eastern Siberia,
in May 2013. Retrieval rates of geolocators in other shorebird
studies conducted by the Victorian Wader Study Group and
the Australasian Wader Studies Group varied between 10%
(Great Knot (Calidris tenuirostris)) and 50% (Ruddy Turnstone
(Arenaria interpres)). These retrieval rates reect the ability to
detect and catch the individuals as well as their site-delity
and not their actual probability of survival. Other individuals
carrying geolocators have been seen occasionally at or near this
location, including one as recently as September 2016. The bird
shot in Siberia during northward migration in 2013 also indicates
that the detection rate is not 100% because the geolocator data
revealed that this individual spent the non-breeding season
of 2012 near the deployment site. All individuals, except the
bird shot in Siberia (B013), were sexed molecularly, using the
primers P8 and P2 according to the method described by
Grifths et al.(1998). We used a principal component analysis
based on morphological measurements to assign B013 the status
of female with a probability of 0.7 (see S1 in Supplementary
Analysis of geolocator data
Light-intensity recordings from geolocators were used to rst
estimate the breeding sites of each individual and subsequently,
using the derived breeding site position, to estimate the full
migration path.
Breeding sites
Sanderlings breed at high Arctic latitudes (Lappo et al.2012)
and thus experience constant daylight during this part of their
annual cycle. Conventional methods to estimate positions from
light-intensity recordings over time (i.e. geolocation by light)
Sanderling migration in the EAAF Emu 169
usually fail to produce reliable position estimates under condi-
tions of 24-h daylight as the light sensor generally does not
record any variation in light intensity through the day (Lisovski
et al.2012). However, the light sensor in the geolocators used
in this study recorded the full range of light intensities for
each day, allowing the breeding location to be estimated. We
developed a template-t analysis to estimate the positons of the
breeding sites. For each individual, light-intensity records from
the deployment site in Australia, recorded on the bird during
the stationary period after deployment or before retrieval of
the device, were used to generate a calibration curve of light
intensity as a function of zenith angles, using astronomical
functions within the R package SGAT (Wotherspoon et al.
2013). This calibration curve allowed generation of expected
light at any location for a given time or zenith angle. Using the
individual, geolocator-specic calibration curves, predictions
were made on the temporal variations in daily light intensity for
the entire breeding season for every 50 50-km grid-cell across
the entire Russian Arctic. Next, the predicted light values were
compared with the observed light data. We calculated the per-
centage of single light-intensity recordings that exceeded the
predicted values within each grid-cell. Observations can only
have been recorded within grid-cells where 100% of the observed
light-intensity values were below the predicted values. This
approach assumes that birds were resident during the entire
breeding period. To correct for potential travel after arrival at or
before departure from the Arctic we excluded observations
from three days after arriving in the region experiencing
24-h daylight and three days before departure from that region.
In the best-case scenario, when light-intensity measurements
are little inuenced by shading of any kind, the 100% likelihood
contour line plotted across the potential breeding area is char-
acterised by a v-shape (or u-shape) with the highest likelihood
slightly above the minima of this contour line (see supplementary
material S2). We selected the closest position on land to this
lowest latitudinal position above the 100% contour line. From
data recorded at the deployment and retrieval site in South
Australia we estimated geolocation error to be <200 km. How-
ever, since the variation in elevation angle of the sun at the
breeding grounds is low and signal-to-noise ratio high (owing
to incubation and habitat) we expect location accuracy of the
estimated breeding sites to be up 100300 km lower (for more
details, code and explanations see S2 in Supplementary material).
Migration pathway
Daily positions, and hence migration pathways, for each
individual were estimated from raw light-level data using the
threshold method of estimating positions based on sunrise and
sunset events (Lisovski et al.2012). Daily sunrise and sunset
times as well as initial positions based on the simple threshold
method were calculated using the R package GeoLight (Lisovski
and Hahn 2012). A light-intensity threshold of 0.8 was used for
all individuals. The corresponding zenith angle was dened
from sunrise and sunset times recorded while the birds were at
the deployment site. The dened zenith angle varied between
individuals and ranged from 93.4 to 96.5. To derive more
accurate positions, we used a Bayesian framework that incorpo-
rates the observed sunrise and sunset times together with
prior knowledge of Sanderling behaviour to provide location
estimates with associated measurements of uncertainty. The R
package SGAT (Sumner et al.2009; Wotherspoon et al.2013)
uses MCMC simulations that permit a spatial probability mask,
prior denition of the error distribution of twilight events
(twilight model) and plausible ight-speed values (behavioural
model), which collectively allowed us to rene the tracks derived
from the sunrise and sunset times (for detailed description of
the model assumptions, see Sumner et al.2009). The spatial
probability maskis based on the premise that, during migration,
Sanderlings are most commonly found on coastal sandy
beaches, although they may also occur on tidal mudats and the
shores of lakes and rivers. Estimated positions were therefore
considered to be more likely if close to a shoreline and indepen-
dent of the habitat type: the relative probability was assumed to
decrease exponentially (from 4 to 1) with increasing distance
from the shoreline, using the equation
1þ5expððd=50 000Þ3Þ
We used a spatial shoreline dataset with a 1:75000 scale (http://, accessed
1 September 2014). For the twilight model, the discrepancy
between observed and expected times of twilight was assumed
to follow a log-normal distribution. For sunrise, positive values
correspond to an observed sunrise occurring after the expected
time of sunrise, whereas for sunset, positive values correspond
to an observed sunset occurring before the expected time of
sunset. We chose a conservative prior (log-normal distribution,
with meanlog = 1.65, sdlog = 0.9) since error in twilight detection
potentially varies greatly over the annual cycle. For the
behavioural model, we assumed that migratory shorebirds
perform stepwise migrations, with fairly long staging periods
between periods of movement (Piersma 1987; Warnock 2010).
We modelled ight-speed (ground-speed) using a gamma distri-
bution (shape = 0.7, scale = 0.05) assuming that the speed with
the highest probability was <1 (i.e. the bird is most likely to be
stationary at any given time), and that maximum ight speeds up
to 80 km h
were likely to occur during migration (Pennycuick
et al.2013). For each individual we used these parameters and
started by drawing an initial 10000 samples for burn-in and
tuning of the proposal distribution. One sample reects one set
of positions between each twilight event along the migration
path. The proposal distribution is the conditional probability
here the spatial probability distribution of the individual that is
calculated after all available information was taken into account.
A further 40000 samples were drawn to visually evaluate chain
convergence. A nal draw of 5000 samples was then generated
to describe the posterior distribution. (R-code for individual
location estimation is available from the authors upon request.)
Analysis of migratory movements
We used the median of the posterior distribution as our estimate
for the most likely daily position of each individual and hence
their most likely migration path. We evaluated the timing of
migration and whether the individual was moving on a given day
during migration using a rst-passage-time(FPT) analysis:
the FPT describes the time required for an individual to cross
a circle with a radius of 500 km (Fauchald and Tveraa 2003). In
170 Emu S. Lisovski et al.
a second step, FTP was used to identify periods of residency
periods of stable FTP within the dened radius. All posterior
distributions, 5000 positions per day per individual, were com-
bined to calculate the aggregated time the tracked population
spent in each grid-cell. Furthermore, those posterior distributions
were used to analyse migratory connectivity and, in particular,
the spatial spread of the individuals from the tracked population
over time resulting from the temporal synchrony within the
population (Bauer et al.2015). To quantify the within-population
connectivity, a minimum convex hull was generated around
the 0.6 and 0.95 quartile contour lines the space that includes
60% and 95% of the samples forming the posterior distribution
across ve-day intervals using the mcp function of the R package
adehabitatHR (Calenge 2006). The area where the convex hulls
and the Flyway, dened as the 0.4 quartile contour line of all
posterior distributions from all individuals, overlap were used
to quantify the spatial spread of the population for each ve-day
Resightings of leg-ags
To compare leg-ag resightings with our tracking results we
used resightings of Sanderlings originally agged on the coast
of south-eastern South Australia, where the geolocator devices
were deployed. Leg-ags placed on shorebirds at this site are
orange over yellow, and a total of 3638 Sanderlings have been
agged. Resightings of leg-ags from across the Flyway have
been drawn from the Australasian Wader Studies Group
database (, accessed 1
September 2014). We further limited our use of resightings to
those reported during the migration periods (15 April 1 July
for northward migration,; 1 July 1 November for southward
migration). Flag sightings were aggregated on a 500 500-km
spatial grid.
Bird counts
Counts of Sanderling were extracted from estimates of shorebird
populations within the EAAF based on a review of count data in
Bamford et al.(2008, pp. 9193). This report provides spatial
information on counts per species and for the periods of north-
ward migration, southward migration, breeding and non-breed-
ing, between 1979 and 2003. Here we used the count data from
identied internationally important sites that regularly support
1% of the individuals of a population of one species or subspecies
(Criterion 6 of the Ramsar Convention (Ramsar Convention
Bureau 1971)). Maximum counts were aggregated on a 500
500-km spatial grid.
Breeding sites
The estimated positions of breeding sites spanned an area from
the New Siberian Islands of eastern Siberia, 300 km south to the
Siberian mainland of Russia and 1300 km west to the Taimyr
Peninsula (Fig. 1). The highest aggregation of estimated
breeding sites was on the New Siberian Islands.
Migration pathways
Thirteen individuals were recorded performing a complete mi-
gration cycle from the deployment site in South Australia to the
Arctic breeding grounds and back. Detailed individual migration
itineraries are shown in S3 in Supplementary material. Only
one individual (ID2030) did not perform a complete migration;
this individual left on 15 May 2012, made an extended stopover
of 35 days in Borneo and another of 35 days in the area of
Hainan Island, southern China before returning to Australia.
We excluded this individual from all further analyses.
2019 2018
New Siberian
110˚E 150˚E
200 km
Fig. 1. Estimated breeding locations of tracked Sanderlings (black dots = females; white dots = males;
numbers = bird IDs), based on light-intensity records (light-level geolocators). The locations are estimates
and are therefore associated with an error (see Methods and Supplementary material S2).
Sanderling migration in the EAAF Emu 171
Northward migration
After deployment with geolocators, the Sanderlings remained
at Canunda National Park until departure for their rst migratory
leg between 26 April and 10 May 2012 (mean date of departure
s.d.: population, 2 May 4.5 days; females, 3 May 5 days;
males, 1 May 4 days; Fig. 2b). In general, individuals made
a single long-distance ight from South Australia, across the
Equator, to the coasts of Vietnam and China. The coasts of
Hainan Island, central China, Taiwan and the Yellow Sea were
used intensively for extended stopovers (Fig. 3a). All but one
individual (ID2007) also made an additional stopover along
the coast of the Sea of Okhotsk, at the northern end of Sakhalin
Island. Sanderlings arrived on their breeding sites between 5 and
16 June 2012 (mean date s.d.: population, 11 June 6 days;
females, 11 June 5 days; males, 10 June 6 days; Fig. 2b).
Northward migration, on average, was completed within 40 days
of departure, ranging from a maximum of 48 days (ID2003) to
a minimum of 35 days (ID2007).
Southward migration
All tracked individuals left their breeding sites between
13 July and 22 August 2012 (mean dates s.d.: population,
23 July 11 days; females, 1 Aug 19 days; males, 19
July 6 days; Fig. 2c) after staying between 32 days (ID2009)
and 66 days (ID2018) in their breeding areas. Like northward
migration, all but one individual (ID2006) used the coast of the
Sea of Okhotsk as the rst major stopover site after crossing the
Arctic Circle (Fig. 3); in contrast, ID2006 used an inland route
via Mongolia before stopping on the coast of central China and
Taiwan. Most individuals had subsequent stops along the coasts
of China, Taiwan and Korea, although considerably fewer indi-
viduals visited the Yellow Sea during southward compared
with northward migration. In contrast to northward migration,
all individuals made at least one additional stopover in tropical
or subtropical regions (Philippines, Indonesia and Malaysia)
before returning to Australia. Furthermore, more than half of
the individuals (7) used at least one stopover site on the
Australian continent before returning to, or close to, Canunda
National Park. Sanderlings arrived at these wintering sites be-
tween 20 September and 12 November 2012 (mean date s.d.:
population, 9 October 27 days; females, 8 October 28 days;
males, 9 October 17 days; Fig. 2c). The timing of return
of males and females was almost the same even though, on
average, females left the breeding grounds c. 2 weeks later than
males. Southward migration, on average, was completed in
78 days, ranging from a maximum of 108 days (ID2038) to a
minimum of 57 days (ID2019).
Resightings of leg-ags
Until September 2014, there had been 488 resightings of the
3638 individual Sanderlings banded in south-eastern South
Australia reported during the migratory period. Of these, 208
were recorded during northward migration and 280 during south-
ward migration. On northward migration, most resightings
were in the Yellow Sea region (n= 137; 66%). Another 26
resightings (12%) were from the northern part of Sakhalin
Island, Russia, and 25 (12%) from the coast of central China
and Taiwan. During southward migration only one resighting
was recorded within the Yellow Sea. During southward migra-
tion, most resightings were instead from Japan (n= 145; 55%),
along with resightings from the northern end of Sakhalin Island,
Russia, (n= 31; 11%) and the coasts of central China and Taiwan
(n= 32; 11%).
Count data
After collating the maximum counts of Sanderlings from all
internationally important sites on a 500 500-km grid, we
retained a total of 12 grid-cells: seven from the period of north-
ward migration and 11 from the period of southward migration.
Two areas adjacent to the geolocator deployment site in south-
eastern Australia, two areas within the Yellow Sea (Yenchenk
National Nature Reserve and Linghekou, China) and three
areas in Japan (multiple sites in central and southern Japan) and
southern South Korea (Nakdong Estuary) were identied for
northward migration based on counts. For southward migration,
ve additional areas of importance were identied: the northern
end of Sakhalin Island (Sakhalinsky Bay, Russia), the south-
eastern Yellow Sea (Kum Estuary, South Korea), two in north-
western Australia (Roebuck Bay and Eighty Mile Beach) and
one in Tasmania (Blanchet Point).
26 Apr 16 May 5 Jun 25 Jun 10 Jul 30 Jul 19 Aug 8 Sep 28 Sep 18 Oct 17 Nov
Latitude (°)
Date (2012)
(b) Northward migration (c) Southward migration
itude (°)
(a) Flyway Female
Fig. 2. (a) The EastAsian Australasian Flyway and the latitudinal movement of the 13 Sanderlings tracked using light-level geolocators over time for
(b) northward migration and (c) southward migration.
172 Emu S. Lisovski et al.
Fig. 3. Comparison of methods for identifying important stopover areas during Sanderling migration. Days spent at
each area (bold numbers in Markov Chain Monte Carlo (MCMC) path estimation map) during northward (upper panel)
and southward migration (lower panel) are tabulated for two analyses of 13 individual birds tracked using light-level
geolocators, as well as the sum of maximum counts (numbers in population count maps) and leg-ag resightings (numbers in
leg-ag resighting maps). Percentage values indicate the relative proportion of time spent, all resightings or all counts across all
areas, with bold values representing the maximum value for each method. Maps represent time spent for geolocation methods
on a 100 100-km grid, and the sum of leg-ag resightings or maximum counts on a 500 500-km grid.
Sanderling migration in the EAAF Emu 173
Comparison of methods for identifying important sites
Based on the merged posterior distributions of all individual
MCMC path estimates, ve areas could be identied as being
used extensively by the tracked individuals and are therefore
classied as areas of major importance. The number of days
spent within these areas based on the MCMC path estimates,
simple threshold estimates, leg-ag resightings and the sum of
maximum Sanderling counts are shown Fig. 2(within included
tables). Although the relative number of days spent between the
important areas are concordant between the two different geolo-
cator analysis methods, the leg-ag resightings and bird counts
overestimated the use of certain areas by the population (e.g.
southern and central Japan) and underestimated or even omitted
the use of other areas (e.g. the coastlines of central China and
Taiwan; Fig. 3).
Spatiotemporal patterns of migratory connectivity
Before departure on northward migration, the spatial spread
across the population of tracked individuals was low (60%
convex hull: 1.5
; 90% convex hull: 1.3
and hence the connectivity within the population was high.
With the onset of northward migration, spatial spread increased
considerably, reaching a maximum of 1.4
(60% and
90% convex hulls) between 3 and 8 May (Fig. 4a). The area
subsequently decreased, to 1.6
, between 23 and
28 May (Fig. 4b), before increasing again to 5.8
between 2 and 7 June, shortly before the arrival of Sanderlings
on the breeding grounds (where the population spread over
). Soon after the onset of southward migration,
the area used by the Sanderlings increased, peaking at 1.6
between 25 and 30 September (Fig. 4b). Thereafter,
the area used steadily decreased until the population returned
to the fairly small area around the deployment site in South
Comparison of methods for identifying important sites
When identifying areas of importance for the conservation of
highly mobile species, several methods are frequently used.
Our results for Sanderlings suggest that although individual
tracking methods, leg-ag resightings and bird counts show
considerable overlap, critical detail may be lost when relying on
the latter two more traditional methods alone. All four methods
assessed here invariably identied the coastline of the Yellow
Sea as the major stopover area for Sanderlings during northward
migration, and both geolocator data and leg-ag resightings
indicated extensive use of a large swathe of the central Asian
coastline. All methods also highlighted the use of the West
Australian coastline as Sanderlings returned to their wintering
sites, and that these areas were skipped during northward migra-
tion. Indeed, our results suggest that areas of importance to the
population may by underestimated or even missed when assess-
ments are based solely on on-the-ground observations. Although
several clear areas of importance coincided between both geo-
locator analysis methods, the population counts and leg-ag
resightings showed substantial differences. Critically, the impor-
tance of ve areas, notably those in tropical and subtropical
regions, was generally underestimated using leg-ag resightings,
and even omitted when relying on count data. Strikingly, the
coasts of central and southern Japan were prominent in the
count data for both migration legs, and for southward migration
in the leg-ag resightings, yet only one of the tracked Sanderlings
(B013) showed a migration route via Japan.
Clearly, all methods discussed here have limitations and
some of the discrepancies between the count data and the other
three methods may be partly explained by the fact that we
obtained tracking data from a small number of individuals from
a single wintering population only. Additional tracking data
would undoubtedly improve the accuracy of our estimates, but
leg-ag resightings from Sanderlings caught and agged at
other wintering sites along the EAAF show very similar spatial
patterns to the individuals agged in South Australia (Minton
Apr May Jun Jul Aug Sep Oct Nov Dec
Area (km2)
25 May–30 May 27 Sep–2 Oct
Fig. 4. Migratory connectivity within the Sanderling population over time.
The spatial spread of the population for a given period was calculated as
the area of the minimum convex hull enclosing 60% (grey bars and dark-
grey polygon) or 95% (line bars and light-grey polygons) of the combined
MCMC-estimated paths from all 13 individuals. The maps show two
extremes: periods of the greatest (left) and least (right) connectivity within
the population. The dashed line indicates the boundaries of the Flyway used
by the tracked Sanderlings.
174 Emu S. Lisovski et al.
et al.2011). Finally, the count data presumably include indivi-
duals from several wintering populations, and yet key sites used
by our tracked individuals were not recorded in these data.
Those sites might not have been counted or do not appear in
Bamford et al. (2008) for other reasons, such as the counts may
have been too small to meet the 1% of the Flyway population
criterion. We also recognise that studies of population counts
and leg-ag resightings are primarily intended for purposes
other than identifying crucial areas for conservation, including
the study of population dynamics and estimating mortality rates.
However, these data resources constitute the most extensive
information on species-specic movements and are therefore
frequently used to identify areas of importance and to inform
conservation planning. The discrepancy between counts, leg-
ag resightings and individual movement data shown here
highlights the value of integrating multiple data sources in order
to inform conservation planning, determining priorities and
resource allocation on ground.
Geolocator analysis
The correspondence between both geolocator methods used
here is initially surprising, given the low precision and accuracy
of the simple threshold method (Lisovski et al.2012). However,
most shorebird species have a preference for open habitats,
resulting in little noise in light-intensity recordings. Moreover,
the equinoxes periods with comparatively low accuracy and
precision in the simple threshold estimates (Lisovski et al.2012)
did not coincide with periods in which the Sanderlings visited
the ve important foraging or resting areas. The two methods
might thus yield very different results in other species, especially
in those using more vegetated or heterogeneous habitats. Addi-
tionally the MCMC path estimates feature important advantages
over the simple threshold estimates in that the Bayesian method
provides a framework that enables additional information, such
as species-specic habitat preferences, movement behaviour
and home-ranges, to be incorporated. This greatly reduces the
probability of erroneous, incompatible location estimates. More-
over, the method allows estimation of condence intervals for
location estimates that reect the quality of the data. Finally,
the method permits the estimation of a continuous path, whereby
each observation is used and evaluated in relation to all other
observations, rather than the rather arbitrary qualication of
each position in isolation and hence the potential omission or
inclusion of positions derived by simple threshold estimates
(Sumner et al.2009).
Our template-t analysis allowed for the breeding areas of
the tracked Sanderlings to be identied (Fig. 1). Supporting the
analysis, the 100%- and 99%-likelihood contour lines for the
individual breeding areas showed identiable and concurrent
minima on or close to locations on land (for more details, see
supplementary material S2). Six individuals migrated and prob-
ably bred on the New Siberian Islands, well known as an area of
breeding shorebirds, including Sanderlings (Lappo et al.2012).
The breeding locations of two individuals were estimated to be
just below the New Siberian Islands in the coastal Siberian
mainland. Although Sanderlings are not recorded as breeding in
this area (Lappo et al.2012), it should to be noted that based on
our template-t analysis, locations on the Islands are equally
likely and are well within the latitudinal accuracy of the position
estimates. The location estimates for the remaining ve indivi-
duals were west of the New Siberian Islands, as far as the eastern
part of Taimyr Peninsula (Fig. 2). Both the eastern coastal
areas of Taimyr Peninsula and the Lena Delta are conrmed
breeding areas of Sanderlings (Lappo et al.2012).
The rapid and highly-synchronised northward migration of
Sanderlings (Fig. 3) concurs with other observations on migratory
birds (reviewed by Nilsson et al.2013). In fact, the tracked
population spent twice as long on southward migration as north-
ward migration. Such patterns are thought to be related to high
selection pressure on a timely arrival at the breeding grounds (e.g.
McNamara et al.1998; Kokko 1999; Both and Visser 2001)
with northward migration therefore considered a period of con-
siderable time constraint. Similarly, the migratory connectivity
within the population varied over time and between the two
migration legs. As a result of the highly synchronised northward
migration, the area used by the population shrank by an order
of magnitude once all individuals arrived on the central Asian
coastline (Fig. 4b). In contrast, spatial connectivity was very low
during southward migration, to the extent that as some Sander-
lings arrived at wintering sites in South Australia others had
only just arrived at the Yellow Sea, lagging ~9000 km behind
(Fig. 4c).
We observed no differences between males and females in
their timing of northward migration. However, the schedule of
departure from the breeding grounds seemed to be sex-specic.
All males left within a short time period (within 14 days of
one another), whereas all but one female left later, after the last
male, and with considerably more variation between individuals
(Fig. 2c). Although very little is known about sex-specic
parental investment in Sanderlings, Tomkovich and Soloviev
(2001) and Reneerkens et al.(2014) observed that only single
birds cared for hatchlings and that more males attended broods
from earlier clutches, whereas females predominantly cared for
late clutches. This could explain our observed differences in
departure dates between the sexes and suggests that some
females may have had two clutches, as observed in other areas
(Reneerkens et al.2009), with females caring for the second
During northward migration, Sanderlings made an initial,
long, migratory ight across the Equator, after which they all
made three to ve stops before crossing the Arctic Circle and
arriving at their breeding grounds. In contrast, most Sanderlings
used as many as six or seven stops during southward migration.
This hopping between sites during southward migration and the
latter stage of northward migration is similar to that observed in
Ruddy Turnstones (Minton et al.2010) but contrasts with what
we know from tracking studies of other species within the EAAF
(Driscoll and Ueta 2002; Battley et al.2012; Minton et al.
2010,2013). These other species (Bar-tailed Godwit (Limosa
lapponica), Greater Sand Plover (Chardrius leschenaultia) and
Eastern Curlew (Numenius madagascariensis)) use one or two
major stopover sites during both northward and southward
migrations. Sanderlings and Ruddy Turnstones are generalist
feeders (Piersma et al.1996) and may thus be less restricted in
their habitat use than the other species. Alternatively, the rather
high number of stops observed in Sanderlings and Ruddy Turn-
stones may be related to their body size (cf. Piersma 1987;
Sanderling migration in the EAAF Emu 175
Warnock 2010), both species being among the smallest species
tracked within the EAAF thus far.
Given the apparent value of integrating tracking studies with
existing leg-ag resightings and count data to identify crucial
areas for conservation, we urgently require more detailed indi-
vidual migration tracks for the entire range of migratory shorebird
species and populations using the EAAF. Study designs should
emphasise acquisition of sufcient individual tracks to infer
distributions both within and between populations throughout
the migration period. Increased understanding of how species
and populations use the network of sites along the Flyway
would also assist predictions of how shorebirds are likely to
respond to the rapid changes to their habitats within the Flyway.
Tracking studies, combined with the systematic monitoring of
the population through marking, resighting and counting, there-
fore form an essential part of the empirical research fundamental
to conserving the many threatened migratory populations in the
EAAF and elsewhere in the world.
We would like to thank the late Ren de Garais who (together with Ian
D. Steward) rst drew our attention to the presence of Sanderlingswith
leg-ags on the shores of the south-eastern coast of South Australia. We
also thank all members of the Victorian Wader Study Group (VWSG) for
deploying and retrieving geolocators from Sanderlings. We specically
thank Roger Standen for providing the leg-ag resightings of Sanderlings,
and Simon Wotherspoon and Michael Sumner for their work on the SGAT
software (Wotherspoon et al.2013) and their support in the analyses. Heiko
Schmaljohann and Theunis Piersma provided valuable comments on a
former draft of the manuscript. Several individuals and organisations,
notably the Norman Wettenhall Foundation, provided funding to the VWSG
to conduct this geolocator project. Friends of Shorebirds South East also
raised signicant funding to pay for geolocators. Banding permits were
supplied by the Australian Bird and Bat Banding Scheme, Canberra. Animal
ethics (D0001404067) and state approvals to undertake scientic research
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Sanderling migration in the EAAF Emu 177
... While light-level geolocators have long been deployed to provide an understanding of a range of animal movements, it is over the last 10 years that they have been used on a number of shorebird species to track migratory movements and identify breeding, stopover, and wintering areas (Bridge et al. 2011, Tomkovich 2016, Lisovski et al. 2016a). These devices measure and store ambient light levels which can be used to determine latitude and longitude when the data are downloaded. ...
... We used the template-fit method described in Lisovski et al. (2016a) to estimate the positions of the breeding sites. The level of accuracy of the estimated breeding sites is 100-300 km Lisovski et al. (2016a). ...
... We used the template-fit method described in Lisovski et al. (2016a) to estimate the positions of the breeding sites. The level of accuracy of the estimated breeding sites is 100-300 km Lisovski et al. (2016a). ...
Full-text available
The tracking of birds using light-level geolocators has become a relatively frequent technique in the study of migratory shorebirds. The geolocator program, commenced in Australia by the Victorian Wader Studies Group in 2009, has provided insights into many of the strategies and outcomes of the species studied. The most numerous of these studies have been on the Ruddy Turnstone Arenaria interpres. While an increasing number of these are multiple tracks for the same bird, there are relatively few with field sightings to enable supporting calibration and confirmation of computed locations, hence the value of the sightings in Newcastle of Ruddy Turnstone with leg flag WMA described in this paper. The migrations of this bird, described over three consecutive years, show southward tracks over the Pacific Ocean and stopovers in Newcastle on its return journeys to King Island (Tasmania). Information regarding breeding locations and incubation characteristics are also described.
... Our data also suggest that the birds need to obtain resources for migration and other annual cycle stages (e.g., molt) in these countries. A similar migration pattern of the little ringed plover has been reported in the local population of Sweden 28 and in other small shorebirds in the EAAF, such as sanderling 34 and ruddy turnstone 8 . However, the migration routes and wintering areas of the six plovers we studied had less variability compared with the Swedish population, which showed a variety of migration routes among seven studied plovers. ...
... However, the migration routes and wintering areas of the six plovers we studied had less variability compared with the Swedish population, which showed a variety of migration routes among seven studied plovers. In addition, the migration routes and distances of the two plovers with complete migration data were similar in autumn and spring, as has been reported in sanderling 34 . The birds' small body size may restrict their selection of favorable stopover sites, with the sea acting as an ecological barrier. ...
Full-text available
To maintain and recover populations of migratory waders, we must identify the important stopover sites and habitat use along migration routes. However, we have little such information for waders that depend on inland freshwater areas compared with those that depend on coastal areas. Recent technological developments in tracking devices now allow us to define habitat use at a fine scale. In this study, we used GPS loggers to track both spring and autumn migration along the East Asian-Australasian flyway of the little ringed plover (Charadrius dubius) as birds moved to and from their breeding grounds, gravel riverbeds in Japan. The birds we tracked overwintered in the Philippines and made stopovers mainly in Taiwan and the Philippines. The most important habitat during the non-breeding season was rice paddy fields. Our findings imply that changes in agriculture management policy in the countries along the migration route could critically affect the migration of waders that depend on rice paddy fields. To maintain populations of migrant inland waders that move within the East Asian-Australasian flyway, it is necessary not only to sustain the breeding habitat but also wetlands including the rice paddy fields as foraging habitat for the non-breeding season.
... Light-level geolocators accordingly do not track daily finescale movements and provide only "inexact" approximations of the general migratory route [70,71]. Furthermore, location estimates may be even less accurate at high altitudes during summer [71], especially if they are not analysed in a sophisticated way [72,73]. To assess the accuracy and precision of the location estimates, many studies apply ground truthing in breeding areas or wintering grounds. ...
... Since most songbird species probably encounter favourable feeding habitats along their migration route on a regular basis, the drive to accumulate large energy stores and extensively build up muscles before departure is generally less pronounced than in waders, for example. In the latter group, the occurrence of the first migratory fuelling period and extensive muscle development before the first migratory flight is a common phenomenon [129,130] because these species often migrate over long distances to reach the next favourable stopover area, e.g., [72,131]. Zhao et al. [22,132] minimized this issue in waders by estimating the partial speed of migration. ...
Full-text available
Background: Anthropogenic changes in the climate and environment have globally affected ecological processes such that the spatiotemporal occurrence of the main annual cycle events (i.e., breeding, wintering, moulting, and migration) has shifted in migratory birds. Variation in arrival timing at migratory destinations can be proximately caused by an altered start of migration, total migration distance, and/or total speed of migration. Quantifying the relative contributions of these causes is important because this will indicate the mechanisms whereby birds could potentially adjust their annual cycle in response to global change. However, we have relatively little quantitative information about how each of these factors contributes to variation in arrival timing. My main aims are to estimate how arrival timing is correlated with variation in the start of migration and the total migration distance and how the total speed of migration may change with the total migration distance and body mass in a comprehensive analysis including multiple species. Methods: For this purpose, I considered individual tracks covering complete migrations from multiple species and distinguished between within- and between-species effects. Results: Assuming that the within- and between-species effects quantified under this approach agree with the effects acting at the individual level, starting migration one day later or increasing the total migration distance by 1000 km would result in later arrival timing by 0.4-0.8 days or 2-5 days, respectively. The generality with which the start of migration is correlated with arrival timing within species suggests that this is the general biological mechanism regulating arrival timing, rather than the total migration distance. The total speed of migration was positively correlated with the total migration distance but not with the bird's body mass. Conclusions: As the start of migration is endogenously controlled and/or affected by hatching date, directional selection can probably act on existing within-species/within-population variation to alter arrival timing. This factor and the importance of variation in the start of migration for arrival timing suggest that migratory species/populations in which there is sufficient variation in the start of migration and transgenerational processes affect the corresponding timing may present an advantage over others in coping with anthropogenic-induced global changes.
... (b) The feedback process between individual stopover duration and population dynamics processes such as sex differences and a mixture distribution of migratory tactics. Males often migrate earlier than females in the northward migration to occupy the best breeding territories (Kokko et al., 2006;Newton, 2011), and some individuals might abort migration without making any breeding attempt (Lisovski et al., 2016;Shaw & Levin, 2011). However, as the lack of individual-identified information on both timing, energy reserves and migrating trajectory, we chose to ignore them in this model. ...
Full-text available
Populations can rapidly respond to environmental change via adaptive phenotypic plasticity, which can also modify interactions between individuals and their environment, affecting population dynamics. Bird migration is a highly plastic resource‐tracking tactic in seasonal environments. However, the link between the population dynamics of migratory birds and migration tactic plasticity is not well‐understood. The quality of staging habitats affects individuals' migration timing and energy budgets in the course of migration and can consequently affect individuals' breeding and overwintering performance, and impact population dynamics. Given staging habitats being lost in many parts of the world, our goal is to investigate responses of individual migration tactics and population dynamics in the face of loss of staging habitat and to identify the key processes connecting them. We started by constructing and analysing a general full‐annual‐cycle individual‐based model with a stylized migratory population to generate hypotheses on how changes in the size of staging habitat might drive changes in individual stopover duration and population dynamics. Next, through the interrogation of survey data, we tested these hypotheses by analysing population trends and stopover duration of migratory waterbirds experiencing the loss of staging habitat. Our modelling exercise led to us posing the following hypotheses: the loss of staging habitat generates plasticity in migration tactics, with individuals remaining on the staging habitat for longer to obtain food due to a reduction in per capita food availability. The subsequent increasing population density on the staging habitat has knock‐on effects on population dynamics in the breeding and overwintering stage. Our empirical results were consistent with the modelling predictions. Our results demonstrate how environmental change that impacts one energetically costly life‐history stage in migratory birds can have population dynamic impacts across the entire annual cycle via phenotypic plasticity.
... However, taking more population-specific and connectivity-based approaches to conserving Dunlin on the EAAF would require a more detailed understanding of subspecific migration patterns and site use than is currently available. To address this knowledge gap we recommend a coordinated effort that combines deploying tracking devices at breeding sites to quantify subspecies' use of migration routes (e.g., Bridge et al. 2011, Kays et al. 2015, Brown et al. 2017 with the collection of morphological measurements, genetic samples (Gates et al. 2013, Miller et al. 2015, and flock counts at nonbreeding sites to quantify subspecies' use of nonbreeding areas (e.g., Lopes et al. 2006, Lisovski et al. 2016. Collectively these efforts would provide the greatest opportunity to scale our understanding of Dunlin space-time dynamics from dozens of individuals to entire populations, and ultimately enable more effective conservation efforts for Dunlin on the EAAF , Barter 2004, Bowlin et al. 2010. ...
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The degree to which individuals migrate among particular breeding, migration, and wintering sites can have important implications for prioritizing conservation efforts. Four subspecies of Dunlin (Calidris alpina) migrate along the East Asian−Australasian Flyway. Each subspecies has a distinct and well-defined breeding range, but their migration and winter ranges are poorly defined or unknown. We assessed the migratory connectivity of 3 of these subspecies by evaluating a dataset that encompasses 57 yr (1960–2017), and comprises more than 28,000 Dunlin banding records and 818 observations (71 recaptures and 747 band resightings). We present some of the first evidence that subspecific segregation likely occurs, with arcticola Dunlin wintering in areas of Japan, and other arcticola, actites, and sakhalina Dunlin wintering in areas of the Yellow and China seas. Observations indicate that whether an arcticola Dunlin winters in Japan or the Yellow and China seas is independent of their breeding location, sex, or age. Furthermore, observations indicate that ≥83% of arcticola Dunlin exhibit interannual site fidelity to specific wintering sites. This suggests that the degradation of specific wetland areas may negatively affect particular individuals of a particular subspecies (or combination of subspecies), and, if widespread, could result in population declines. Given the possible biases inherent in analyzing band recovery data, we recommend additional flyway-wide collaboration and the use of lightweight tracking devices and morphological and genetic assignment techniques to better quantify subspecies’ migratory movements and nonbreeding distributions. This information, when combined, will enable effective conservation efforts for this species across the East Asian−Australasian Flyway.
Technical Report
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Recognising the urgent need for updated waterbird population status information, East Asian - Australasian Flyway Partnership Partners adopted Decision 12 at MoP10 that requested Wetlands International to produce a 1st edition of the EAAF Conservation Status Report (CSR1). The report has been prepared in collaboration with EAAF Partners, Working Groups and experts and jointly organised with the EAAFP Secretariat. This is the first review of the conservation status of all EAAF migratory waterbird populations since the 5th edition of Waterbird Population Estimates (WPE5) in 2012. • Size estimates and 1% thresholds are provided for 248 (90%) of the 276 EAAF biogeographic populations of 216 migratory waterbird species. • 32 (12%) of 1% thresholds, are lower than previous assessments (WPE5) and 57 (21%) are higher. 22 (8%) populations have population size estimates and 1% thresholds for the first time. These new thresholds should be used for all future EAAF Flyway Network Site designations. • Of the 159 populations with a known trend, 67 (42%) are decreasing and only 43 (27%) are increasing, with 48 (30%) stable or fluctuating. Trends could not be assessed for 118 (43%) populations. • 34 (16%) of the EAAFP populations belong to species on the IUCN Red List of Threatened Species 2021 and a further 25 (12%) are of Near Threatened species. • Boundary maps for all EAAF biogeographic populations have been produced for the first time. These will support the use of population information for designation and management of Flyway Network Sites, prioritization of species and populations for research and conservation - but will require further refinement. • Major gaps and limitations in knowledge about the distribution, size estimates and trends of many populations have been identified and recommendations provided to address these. • These gaps can only be addressed by strengthening existing monitoring programmes, establishing new monitoring programmes and improving the systems and procedures to collate and synthesise new information. This will require local and national stakeholder engagement along with international partnerships. • All population size estimates, trends, 1% thresholds and boundary maps are available on the Waterbird Populations Portal following formally adoption by the EAAFP Technical Sub-Committee. Populations of eight families of more pelagic waterbird species, including those recently added to the Partnership list will be included in future editions.
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The Cerulean Warbler (Setophaga cerulea) is a declining Nearctic–Neotropical migratory songbird of conservation concern. Implementing full annual cycle conservation strategies to facilitate recovery has been difficult because we know little about the migratory period or strength of migratory connectivity between North American breeding and South American nonbreeding regions. Between 2014 and 2017, we deployed geolocators on 282 males at 14 study sites throughout the species’ range to (1) evaluate the strength and pattern of connectivity between breeding and nonbreeding regions, (2) identify approximate routes and stopover regions, and (3) document migration phenology. We obtained data from 26 birds and observed moderate migratory connectivity overall but documented strong parallel migration for birds breeding in two longitudinally disparate regions. Most (14 of 15; 93%) Appalachian breeders spent the stationary nonbreeding period in the Colombian/Venezuelan Andes, whereas most (5of 7; 71%) Ozark breeders spent the stationary nonbreeding period in Peru/Ecuador. The majority of spring migration (62%) was spent in Central America at multiple stopover locations between Panama and southern Mexico. The 2 migratory periods were approximately equal in duration: 38 ± 2 days (SE) in fall and 42 ± 2 days (SE) in spring. Based on the observed connectivity pattern, conservation of Appalachian breeding populations during the stationary nonbreeding period should focus on forest conservation and restoration in premontane/lower montane forests of Colombia and Venezuela, whereas Ozark breeding population conservation should focus on forest conservation and restoration efforts in Ecuador and Peru. Further conservation efforts are also needed on the breeding grounds, especially for the most sharply declining populations. And finally, conservation of forests used by Cerulean Warblers during stopover periods throughout Central America and southern Mexico, in southeastern United States coastal areas, and in the Mississippi Alluvial Valley will benefit individuals from multiple breeding locations and populations.
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The Pacific Basin, by virtue of its vastness and its complex aeroscape, provides unique opportunities to address questions about the behavioral and physiological capabilities and mechanisms through which birds can complete spectacular flights. No longer is the Pacific seen just as a formidable barrier between terrestrial habitats in the north and the south, but rather as a gateway for specialized species, such as shorebirds, to make a living on hemispherically distributed seasonal resources. This recent change in perspective is dramatic, and the research that underpins it has presented new opportunities to learn about phenomena that often challenge a sense of normal. Ancient Polynesians were aware of the seasonal passage of shorebirds and other landbirds over the Pacific Ocean, incorporating these observations into their navigational “tool kit” as they explored and colonized the Pacific. Some ten centuries later, systematic visual observations and tracking technology have revealed much about movement of these shorebirds, especially the enormity of their individual nonstop flights. This invites a broad suite of questions, often requiring comparative studies with bird migration across other ocean basins, or across continents. For example, how do birds manage many days of nonstop exercise apparently without sleep? What mechanisms explain birds acting as if they possess a Global Positioning System? How do such extreme migrations evolve? Through advances in both theory and tracking technology, biologists are poised to greatly expand the horizons of movement ecology as we know it. In this integrative review, we present a series of intriguing questions about trans-Pacific migrant shorebirds and summarize recent advances in knowledge about migratory behavior operating at temporal scales ranging from immediate decisions during a single flight, to adaptive learning throughout a lifetime, to evolutionary development of migratory pathways. Recent advances in this realm should stimulate future research across the globe and across a broad array of disciplines.
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Stable isotopes are well documented as effective intrinsic markers to infer migratory connectivity which provides key information for establishing an effective conservation strategy in migratory birds. However, there are few studies using stable isotopes that have been applied to long-distance migratory shorebirds globally and such studies are especially scarce along the East Asian–Australasian Flyway. We used stable isotope analysis (δ ² H, δ ¹³ C and δ ¹⁵ N) to infer breeding and wintering areas and examine the differences in those values among populations of Terek Sandpipers ( Xenus cinereus) at stopover sites in South Korea. The range of δ ² H in feathers sampled from birds caught in the Korean peninsula at spring and autumn migration stopover sites was consistent with them being grown at sites throughout their flyway as confirmed by leg flag resightings of birds on this flyway. The eastern Siberia region from Yakutsk to Norilsk and Chukotka in Russia was inferred as the most probable breeding area of the population. Papua New Guinea in the Melanesia region, Malaysia and Indonesia were identified as the most probable wintering areas. Isotope values of populations at different stopover sites and different seasons were consistent. These results suggest that stable isotopes can be effectively used alongside other existing methods (e.g. ringing, coloured leg flags, light level geolocation, satellite tag telemetry) to infer the migratory connectivity for long-distance migratory shorebird species that occur over many countries and continents.
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Satellite‐based technologies that track individual animal movements enable the mapping of their spatial and temporal patterns of occurrence. This is particularly useful in poorly studied or remote regions where there is a need for the rapid gathering of relevant ecological knowledge to inform management actions. One such region is East Asia, where many intertidal habitats are being degraded at unprecedented rates and shorebird populations relying on these habitats show rapid declines. We examine the utility of satellite tracking to accelerate the identification of coastal sites of conservation importance in the East Asian–Australasian Flyway. In 2015–2017, we used solar‐powered satellite transmitters to track the migration of 32 great knots ( Calidris tenuirostris ), an “Endangered” shorebird species widely distributed in the Flyway and fully dependent on intertidal habitats for foraging during the non‐breeding season. From the great knot tracks, a total of 92 stopping sites along the Flyway were identified. Surprisingly, 63% of these sites were not known as important shorebird sites before our study; in fact, every one of the tracked individuals used sites that were previously unrecognized. Site knowledge from on‐ground studies in the Flyway is most complete for the Yellow Sea and generally lacking for Southeast Asia, Southern China and Eastern Russia. Synthesis and applications . Satellite tracking highlighted coastal habitats that are potentially important for shorebirds but lack ecological information and conservation recognition, such as those in Southern China and Southeast Asia. At the same time, the distributional data of tracked individuals can direct on‐ground surveys at the lesser known sites to collect information on bird numbers and habitat characteristics. To recognize and subsequently protect valuable coastal habitats, filling knowledge gaps by integrating bird tracking with ground‐based methods should be prioritized.
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Geolocators were deployed on waders in Australia for a third successive year, in Feb/Apr 2011 including on Eastern Curlew and Sanderling for the first time. Retrieval rates, in the 2011/12 austral summer, varied markedly between species. Technical performance of the geolocators was better than in previous years. However units on Greater Sand Plovers, migrating to breeding grounds in the Gobi Desert, China/Mongolia, again behaved erratically, and exhibited symptoms suggesting extraneous electromagnetic interference. Generally, for each species studied, the results confirm earlier indications that the first step of northward migration from Australia is a long non-stop flight. Subsequent movements to breeding areas are usually shorter with up to three stopovers in SE Asia or Siberia. Similarly southward migration strategies include at least one long nonstop flight, though this is usually the second (or later) leg of the journey. The timing of migration appears to be particularly related to breeding latitude. Eastern Curlews, which breed at relatively southern latitudes, depart from SE Australia from early March, reach the breeding grounds and lay eggs in April, set off on return migration in early June and, after a long stopover in the Yellow Sea, arrive back in SE Australia in early August. In contrast arctic-breeding Ruddy Turnstones do not depart from SE Australia until mid/late April and do not arrive back at their non-breeding locations until October, with the last individuals (which have taken a trans-Pacific route) not returning until late November/early December. Recorded migration speeds (assuming the birds take a great circle route) were quite variable, ranging from 32 to 84 km/h, presumably due to wind conditions. They generally averaged nearer to 50 km/h rather than the 60–70 km/h which waders are known to be capable of achieving and which has been the basis of some past flight range calculations.
Shorebirds are model organisms for illustrating the principles of ecology and excellent subjects for research. Their mating systems are as diverse as any avian group, their migrations push the limits of endurance, and their foraging is easily studied in the open habitats of estuaries and freshwater wetlands. This comprehensive text explores the ecology, conservation, and management of these fascinating birds. Beginning chapters examine phylogenetic relationships between shorebirds and other birds, and cover shorebird morphology, anatomy, and physiology. A section on breeding biology looks in detail at their reproductive biology. Because shorebirds spend much of their time away from breeding areas, a substantial section on non-breeding biology covers migration, foraging ecology, and social behavior. The text also covers shorebird demography, population size, and management issues related to habitat, predators, and human disturbances. Throughout, it emphasizes applying scientific knowledge to the conservation of shorebird populations, many of which are unfortunately in decline.