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Geolocator Data Reveal the Migration Route and Wintering Location of a Caribbean Martin ( Progne dominicensis )

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Caribbean Martins (Progne dominicensis) are common breeders on most Caribbean islands, where they regularly roost and nest in urban areas from February through August. However, from September through January, the basic ecology of this species-its migration and wintering locations-are largely unknown. In 2012, we deployed seven geolocators, and in 2014, we recovered one geolocator from a female Caribbean Martin on the Commonwealth of Dominica, a small eastern Caribbean island. Her wintering location was the western portion of the State of Bahia, Brazil, ∼3550 km southeast of Dominica. Although the location of the non-breeding grounds changed minimally, the fall departure date, migration route, and length of migration to western Bahia, Brazil, was different between years. In October 2012, the female followed a coastal migration route along the Atlantic coast of South America, then flew south to the non-breeding grounds. However in Oct 2013, she flew south from Dominica through Guyana, spent a few days in the Amazon rain forest, and then migrated southeast to the non-breeding grounds. These results provide insight into the repeatability of migration routes and wintering locations by this species, and serves as a first step in better understanding the Caribbean Martin's full life-cycle.
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Geolocator Data Reveal the Migration Route and Wintering
Location of a Caribbean Martin (Progne dominicensis)
Author(s): Noah G. Perlut, Thomas C. Klak, and Eldar Rakhimberdiev
Source: The Wilson Journal of Ornithology, 129(3):605-610.
Published By: The Wilson Ornithological Society
https://doi.org/10.1676/16-142.1
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The Wilson Journal of Ornithology 129(3):605–610, 2017
Geolocator Data Reveal the Migration Route and Wintering Location of a
Caribbean Martin (Progne dominicensis)
Noah G. Perlut,
1,4
Thomas C. Klak,
1
and Eldar Rakhimberdiev
2,3
ABSTRACT.—Caribbean Martins (Progne dominicensis)
are common breeders on most Caribbean islands, where they
regularly roost and nest in urban areas from February
through August. However, from September through January,
the basic ecology of this species—its migration and
wintering locations—are largely unknown. In 2012, we
deployed seven geolocators, and in 2014, we recovered one
geolocator from a female Caribbean Martin on the
Commonwealth of Dominica, a small eastern Caribbean
island. Her wintering location was the western portion of the
State of Bahia, Brazil, ~3550 km southeast of Dominica.
Although the location of the non-breeding grounds changed
minimally, the fall departure date, migration route, and
length of migration to western Bahia, Brazil, was different
between years. In October 2012, the female followed a
coastal migration route along the Atlantic coast of South
America, then flew south to the non-breeding grounds.
However in Oct 2013, she flew south from Dominica
through Guyana, spent a few days in the Amazon rain forest,
and then migrated southeast to the non-breeding grounds.
These results provide insight into the repeatability of
migration routes and wintering locations by this species,
and serves as a first step in better understanding the
Caribbean Martin’s full life-cycle. Received 25 August 2016.
Accepted 26 January 2017.
Key words: Commonwealth of Dominica, Progne
dominicensis, State of Bahia Brazil.
Recent technological advances such as satellite
transmitters and geolocators are rapidly expanding
our understanding of the life-histories of migratory
birds (McKinnon et al. 2013). For example, these
tracking devices have revealed long non-stop
flights (DeLuca et al. 2015), foraging patterns that
allow managers to better plan fisheries’ activities
(Phillips et al. 2006), and migratory connectivity
for landbird populations (Ryder et al. 2011). Even
with the availability of these technologies, the
basic ecology of many common and rare species
remains unknown.
Although the breeding range of Caribbean
Martins (Progne dominicensis) is well documented
(BirdLife International 2012), their migration
routes and wintering areas are largely unknown
(Turner 2004). Some reports of Caribbean Martins
during the non-breeding season have been pub-
lished from the southern Caribbean islands of
Trinidad and Barbados, and from Suriname and
French Guiana in South America (Voous 1983,
Murphy and Hayes 2001, Wells and Wells 2005,
Ottema et al. 2009, Renaudier and de Guyane
2010). The greatest number of observations come
from Suriname (n¼8), but only half of the records
are from the period from November to January
(Ribot 2017). However, these generally represent
observations of individual birds and provide no
information about where the birds came from, the
routes taken to get there, or other locations that
might be used during migration.
We used a geolocator to identify the migration
routes and non-breeding areas of a Caribbean
Martin. In 2012, we deployed seven geolocators
on the Commonwealth of Dominica. In 2014, we
retrieved one geolocator from a female and
documented her movements over a 2-year period.
METHODS
We captured Caribbean Martins on the Common-
wealth of Dominica, an eastern Caribbean island
country with a land surface of 750 km
2
and a
population of about 70,000. Here, Caribbean Martins
roost and nest in both natural cliff faces and crevices
in roof-tops. We focused on a colony in the village of
St. Joseph (15824016; 61825034), where birds used
the eaves of a small bakery located 50 m from the
Caribbean Sea and 20 m from the St. Joseph River.
1
Department of Environmental Studies, University of
New England, 11 Hills Beach Road, Biddeford, ME
04005, USA.
2
Department of Marine Ecology, NIOZ Royal Nether-
lands Institute for Sea Research, P.O. Box 59, 1790 AB
Den Burg, Texel, The Netherlands.
3
Department of Vertebrate Zoology, Lomonosov Mos-
cow State University, 119991, Leninskiye Gory 1,
Moscow, Russia.
4
Corresponding author; e-mail: nperlut@une.edu
605SHORT COMMUNICATIONS
FIG. 1. Migration route of a female Caribbean Martin over 2 years estimated from solar geolocator data; she bred on the
Commonwealth of Dominica, a 750-km
2
island in the eastern Caribbean, and she wintered in the western portion of Bahia,
Brazil. Daily median positions are shown with the lines (green ¼fall 2012; orange ¼spring 2013; pink ¼fall 2013) and
overall probability of occurrence regions with color (darker sections indicate higher probability). Fall migration in 2012
started on 1 Oct with arrival in the wintering area on about 31 October. Spring 2013 migration began about 19 February, and
fall 2013 migration started about 11 September, with the female arriving in the wintering area on 20 October. Blue square
shows extent of the main wintering area zoomed at Figure 3. Circles represent stationary periods in the breeding period,
diamonds during the non-breeding period, and triangles represent movement periods.
606 THE WILSON JOURNAL OF ORNITHOLOGY Vol. 129, No. 3, September 2017
We deployed 0.65-g solar geolocators (Intigeo-
P65C2-7, Migrate Technology Ltd., Cambridge,
United Kingdom) at nesting colonies using a leg-
loop backpack harness made of 0.10-in (~0.25-cm)
Teflon tape (Bally Ribbon Mills). To increase the
probability of recovering geolocators, we aimed to
deploy units on breeding birds. Prior to fieldwork, we
believed that the breeding season would begin in mid-
to late-March (B. Jno Baptiste, pers. comm.). From
6–10 Apr 2012, we caught birds with hand nets as
they emerged from their night roost, and we deployed
seven geolocators on birds assumed to be breeding.
All birds were banded with a numbered band on one
leg and a unique combination of two color bands on
the other leg. We identified sex by plumage. We
returned to Dominica from 5–9 May 2013 and 3–8
May 2014 to collect geolocators from birds.
Data were downloaded and formatted in In-
tiProc v1.03 (Migrate Technology) and are avail-
able at https://github.com/eldarrak/FLightR/tree/0.
3.6/examples/Caribean_Martin. All subsequent
data processing and estimation were done in R
(R Core Team 2015). First, we selected twilight
periods without strong patterns in shading in the
BAStag package (Wotherspoon et al. 2013) and
then used the template-fit method (Ekstrom 2007)
in the FLightR package (Rakhimberdiev et al.
2015) to estimate positions from the light-level
recordings. The BAStag output with preselected
twilights and all analysis details are available at the
github page referenced above. We calibrated the
data during the second breeding period (15 Jun–30
Aug 2013) when the bird was likely on its
breeding grounds in Dominica. We then used the
particle filter in FLightR to map migration routes
and identify the posterior distribution for the non-
breeding locations (Rakhimberdiev et al. 2015).
FLightR uses a hidden Markov chain model to
obtain the most probable tracks of migrating
animals from geolocator data. Because Caribbean
Martins breed on islands, we used spatio-behav-
ioral flight constraints allowing the bird to fly over
(oceanic) water but not to remain stationary there.
FLightR is able to estimate positions during
migration and during equinoxes (Rakhimberdiev
et al. 2016), but our tagged bird combined these
two complications and migrated during equinox
periods making estimated latitudinal positions for
the migration period (Fig. 1) especially imprecise
(see latitudinal credible intervals at Fig. 2).
FLightR estimated arrival and departure days
within the function ‘‘stationary.migration.sum-
mary.’’ The function automatically finds sedentary
periods and estimates when animals arrived and
left the sedentary periods.
RESULTS
Of seven birds color-banded in 2012, we
resighted four birds in 2013 and 2014, but we
were unable to recapture them. Three of the four
birds still had their geolocators attached. On 5 May
2014, we recaptured one of the four birds and
recovered its geolocator; this bird was a female,
initially banded on 4 April 2012. This female
returned to the same non-breeding area in both
years, an area located ~3,550 km southeast of the
Dominican breeding grounds (Fig. 1). The winter-
ing location was in the western portion of the State
of Bahia (44.38,12.38) in Brazil, located ~700
km west of the city of Salvador; the bird spent
35%of the wintering period in one grid cell with
an area of ~2,000 km
2
.
Fall migration routes of the female Caribbean
Martin differed between years. In 2012, the
migration route from Dominica was along the
Atlantic coast of South America. However in
2013, the female first flew due south from
Dominica, through Guyana, likely into the Ama-
zon rainforest in the eastern portion of the State of
Amazonas, Brazil, for a few days, then traveled
southeast to the wintering area. Fall migration in
2012 started on 1 October, arriving on the winter
location near 31 October (Table 1; Fig. 2), with a
total migration duration of 30 days, and migration
route length of ~5,930 km. The spring 2013
migration—which was similar to the fall 2012
route along the Atlantic coast—began around 19
February, with the female arriving in Dominica on
1 March, with a total migration duration of 11 days
and migration route length of ~4,170 km. The fall
2013 migration started around 11 September, and
the female arrived at the wintering location on
about 20 October, with a total migration duration
of 39 days, and migration route length of ~6,370
km. Migration in spring 2014 apparently occurred
sometime during the period from mid-February to
early March, because the geolocator battery failed
on 14 February while the female was still in the
wintering area.
607SHORT COMMUNICATIONS
DISCUSSION
Over 2 years, we found that a single female
Caribbean Martin captured on Dominica used the
same wintering area in the southern portion of the
State of Bahiain Brazil. This area is ~2,100 km
farther south than areas where Caribbean Martins
have previously been reported during the winter in
the scientific literature (Voous 1983, Murphy and
Hayes 2001, Wells and Wells 2005, Ottema et al.
2009, Renaudier and de Guyane 2010) and
through citizen science observations (eBird
2017). Fall migration routes likely differed be-
tween years, with the female taking a coastal route
FIG. 2. Longitudes (upper panel) and latitudes (lower panel) of a track of a Caribbean Martin as estimated by FLightR.
The medians of twilight positions estimated by FLightR include quartile ranges and 95%credible intervals.
TABLE 1. Summary departure and arrival dates,
including migration lengths for a female Caribbean Martin
who bred on Dominica and carried a geolocator for 2 years.
2012 2013
Fall migration departure date 1 Oct 11 Sep
Arrival to winter location 31 Oct 20 Oct
Fall migration length 5,930 km 6,370 km
Spring migration departure date 19 Feb .14 Feb
Arrival to breeding grounds 1 Mar
Spring migration length 4,170 km
608 THE WILSON JOURNAL OF ORNITHOLOGY Vol. 129, No. 3, September 2017
one year and an inland route the next. The inland
route is similar to the route taken by a Purple
Martin (Progne subis) that migrating south from
North America, took a southeasterly land-route
from Central America to Brazil (Stutchbury et al.
2009). Likewise, some Barn Swallows (Hirundo
rustica) migrating from northeastern North Amer-
ica followed both routes identified in our study
(Hobson et al. 2015), although annual variation
within individuals was not assessed. In fact, few
geolocator studies have assessed the repeatability
of fall migration—and thus we know little about
what factors drive variation in routes within
individuals. A study of Wood Thrushes (Hyloci-
chla mustelina) found repeatable timing but non-
repeatable migration routes (Stanley et al. 2012).
Stanley et al. (2012) measured route repeatability
by comparing longitude locations of the Wood
Thrushes that were crossing 23.48N during spring
and fall migration; the researchers suggested that
this lack of repeatability was likely caused by
individual energetic condition and variable weath-
FIG. 3. The wintering region of the Caribbean Martin was ~700 km west of the city of Salvador (see box in Fig. 1);
colored contours correspond to the smallest regions that contain 25%(purple), 50%(blue) and 75%(gray) of modeled
probability of occurrence. This region consists primarily of sparsely forested uplands, cattle and other livestock rearing,
forestry, small-scale agriculture along a network of roads, and scattered towns and villages.
609SHORT COMMUNICATIONS
er patterns. For the Caribbean Martin we tracked,
fall migration started 20 days earlier in 2013 than
2012; this difference could indicate improved
autumn body condition between years, or variation
in favorable weather conditions.
The western portion of Bahia is a remote, semi-
arid and economically-marginal interior region. It
consists primarily of sparsely forested uplands
(~60%of land cover), cattle and other livestock
rearing, forestry, and small-scale agriculture along
a network of roads (30%), and scattered towns and
villages (10%). The region is transitional between
scrub lands called the Serta˜o to the east and
moister, heavily irrigated, and densely cropped
agricultural region called the Cerrado to the west
(Fig. 3; IBGE 2016; TCK, pers. obs.).
We acknowledge that these results represent the
migration routes and wintering locations of a
single individual over 2 years and may or may not
be representative of the species as a whole.
Nonetheless, these results provide insight into the
repeatability of migration routes and wintering
locations by this species, and serves as a first step
in better understanding the full life-cycle of
Caribbean Martins.
ACKNOWLEDGMENTS
Funding for this project came from the Blake-Nuttall Fund of
the Nutall Ornithological Club and the College of Arts and
Sciences and the Department of Environmental Studies at the
University of New England. The Forestry, Wildlife and Parks
Division of the Ministry of Agriculture and Forestry in the
Commonwealth of Dominica authorized this research. Wethank
J. Fox for helping retrieve the data from the geolocator. And, we
thank B. Jno Baptiste for his guidance and support on
Dominica, and to S. Neumann for field assistance.
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... Noah Perlut et al. (2017) relate how they attached geolocators to seven hirundines on the Caribbean island of Dominica in 2012. Two years later, they recovered data from one device attached to a female Caribbean Martin and found that she had wintered around 3,350 km southeast of Dominica in western Bahia, Brazil. ...
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Many fundamental aspects of migration remain a mystery, largely due to our inability to follow small animals over vast spatial areas. For more than 50 years, it has been hypothesized that, during autumn migration, blackpoll warblers (Setophaga striata) depart northeastern North America and undertake a non-stop flight over the Atlantic Ocean to either the Greater Antilles or the northeastern coast of South America. Using miniaturized light-level geolocators, we provide the first irrefutable evidence that the blackpoll warbler, a 12 g boreal forest songbird, completes an autumn transoceanic migration ranging from 2270 to 2770 km (mean ± s.d.: 2540 ± 257) and requiring up to 3 days (62 h ± 10) of non-stop flight. This is one of the longest non-stop overwater flights recorded for a songbird and confirms what has long been believed to be one of the most extraordinary migratory feats on the planet. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
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Bird migration is a spectacular natural phenomenon that has generated wonder and interest for centuries. Feats of migration in-spire amazement—individual birds that weigh less than 200 g may log more than 80,000 km annually (Egevang et al. 2010), travel more than 600 km day –1 (Stutchbury et al. 2009, Åkesson et al. 2012), and cross huge geographic barriers such as oceans (Bairlein et al. 2012) and inhospitable deserts (Tøttrup et al. 2012b). Despite the vast geography covered during migration, many birds return to the same territories year after year. Although incredible progress has been made in our understanding of bird migration (Newton 2008), many gaps remain in our knowledge of the migration of small birds. The development of miniaturized tracking technology has produced a wave of research into the migratory behavior of small birds (Fig. 1). The inaugural application of miniaturized geoloca-tors (or "geologgers") on small songbirds in 2007 (Stutchbury et al. 2009) initiated a rapid increase in the number of studies of small landbird migration; there are currently more than 100 permits in North America alone for attaching geolocators to small birds. This technology has been so enthusiastically applied because it provides information critical to conservation and management of declining songbird populations (Faaborg et al. 2010a), as well as the opportunity to test long-standing hypotheses related to en-dogenous control mechanisms, navigation, and energetics (Rob-inson et al. 2010). Although more accurate devices may someday be available for tracking small birds, geolocators are currently the only option for migrants that weigh <50 g (Bridge et al. 2011). The main goal of many geolocator studies to date has been the description of little-known migratory routes and wintering sites (e.g., Beason et al. 2012, Stach et al. 2012). As this technique becomes more widely applied (both geographically within spe-cies and taxonomically across a broad spectrum of small land-birds), researchers can begin to test hypotheses about migration, non-breeding ecology, and behavior to inform conservation mea-sures. Many migratory species are declining; thus, a comprehen-sive understanding of the annual cycle is timely and important for management of species at risk. The purpose of our review is to summarize, for the first time, patterns emerging from geolo-cator studies. We review new data on (1) migratory connectivity, (2) migratory routes and stopovers, (3) intratropical migration of wintering birds, and (4) migration schedules. We then explore questions that can be answered with emerging geolocator studies, and provide a "flight plan" for future work as direct-tracking tech-nology becomes increasingly smaller and more broadly applied.
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Understanding the connectivity between breeding and nonbreeding populations of migratory birds is fundamental to our knowledge of biological phenomena such as population dynamics and dispersal. Moreover, our ability to quantify migratory connectivity has inevitable consequences for both conservation and management of species that utilize distinct geographic locations. Technology is rapidly advancing our ability to track birds throughout the annual cycle and to collect data on the degree of connectivity among breeding and nonbreeding populations. We combined two direct methods, mark recapture (n = 17) and geolocation (n = 6), to estimate the migratory connectivity of breeding and nonbreeding populations of Gray Catbirds (Dumetella carolinensis). Data from geolocators show that birds breeding in the Mid-Atlantic overwinter in both Cuba and southern Florida. Mark recapture data supported our geolocator results but also provided a broader spatial perspective by documenting that Mid-Atlantic and Midwestern populations occupy distinct geographic localities during the nonbreeding period. This research underscores the importance of geolocators, as well as other tools, to advance our understanding of migratory connectivity. Finally, our results highlight the potential value of U.S. Geological Survey (USGS) Bird Banding Laboratory mark recapture data, which are often underutilized in ornithological research. Received 6 January 2011, accepted 24 April 2011.
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Template-fit geolocation offers an opportunity to estimate error in each individual day's position results. The estimate requires determining an empirical calibration constant for latitude and another for longitude based on a trial against realistic noise in irradiance field data, which typically display strong point-to-point correlations. Such a calibration is reported here, making the error estimate available for use. The calibration is based on a 458-day set of blue-light irradiance data taken by an archival tag (Lotek LTD750) at a known location on land (48.57°N, 122.94°W). For the data studied, median values of the estimated daily standard deviations were 0.42° in longitude, 0.95° in latitude. The error estimates include the effects of weather and other data noise, latitude, and season, so (1) they vary widely from day to day and with season, and (2) they can be cautiously expected to remain valid in situations other than the particular one tested. A change in the character of the data noise is the only factor expected to have a significant effect on the calibration; this work should be repeated to sample the expected range of data noise types.