10.5061/DRYAD.NK98SF7V1
Harrison, Autumn-Lynn
0000-0002-6213-1765
Smithsonian Institution
Woodard, Paul
Canadian Wildlife Service
Mallory, Mark
Acadia University
Rausch, Jennie
Canadian Wildlife Service
Sympatrically-breeding congeneric seabirds (Stercorarius spp.) from Arctic
Canada migrate to four oceans
Dryad
dataset
2021
FOS: Biological sciences
Arctic seabirds
animal tracking
2022-12-15T00:00:00Z
2022-12-15T00:00:00Z
en
181064 bytes
3
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Polar systems of avian migration remain unpredictable. For seabirds
nesting in the Nearctic, it is often difficult to predict which of the
world’s oceans birds will migrate to after breeding. Here we report on
three related seabird species that migrated across four oceans following
sympatric breeding at a central Canadian high Arctic nesting location.
Using telemetry we tracked pomarine jaeger (Stercorarius pomarinus, n=1)
to the Arctic Ocean to the western Pacific Ocean; parasitic jaeger (S.
parasiticus, n=4) to the western Atlantic Ocean, and long-tailed jaeger
(S. longicaudus, n=2) to the eastern Atlantic Ocean and western Indian
Ocean. We also report on extensive nomadic movements over ocean during the
post-breeding period (19,002 km) and over land and ocean during the
pre-breeding period (5,578 km) by pomarine jaeger, an irruptive species
whose full migrations and nomadic behavior have been a mystery. While the
small sample sizes in our study limit the ability to make generalizable
inferences, our results provide a key input to the knowledge of jaeger
migrations. Understanding the routes and migratory divides of birds
nesting in the Arctic region has implications for understanding both the
glacial refugia of the past and the Anthropocene-driven changes in the
future.
We captured adult jaegers during incubation (late June to early July) 2018
and 2019 at Nanuit Itillinga (Polar Bear Pass) National Wildlife Area,
Bathurst Island, Nunavut, Canada (NINWA, 75° 43' N, 98° 24' W).
We used 5 g (LTJA, n=2) and 9.5 g (PAJA, n=2 and POJA, n=1) Argos
solar-powered satellite tags (Microwave Telemetry Inc., deployed
2018-2019) to track seabird movements. Satellite tags were attached using
a leg-loop harness[22] made of 4.7625mm wide tubular Teflon Ribbon (Bally
Ribbon Mills) secured with copper crimps. The total tag and attachment
weight comprised 0.4-2.1% of the body mass of known-weight individuals
(Table 1). We assessed wing and leg mobility prior to release and watched
birds until they flew out of sight. Data previously collected from two
PAJA breeding on nearby Nasaruvaalik Island, Nunavut, Canada (58 km from
NINWA, 75° 47' N, 96° 17' W) were also contributed to this
study. These birds were tracked using archival light-level geolocators
(GLS tags) attached with plastic cable ties to darvic leg-bands (Lotek
Inc. LAT2900, 2.1g). Tags were deployed in July, 2010 (n=1) and June, 2011
(n=1) and recovered the following year by recapturing the birds. Tags also
recorded sea surface temperature (SST) when immersed for more than 120
seconds and stored the minimum daily value. Tag programming and processing
Satellite tags were duty-cycled to maximize solar charging (10 hours on,
48 hours off). Given sampling irregularity and the telemetry error of
position estimates (see supplemental material for details), we used a
model to estimate most probable paths. We applied the continuous-time
random walk model of Jonsen et al.[23] using the foieGras package in R and
estimated movement paths at 24-hour intervals to standardize sampling
across birds tracked with different technologies (the maximum resolution
of GLS tags was one position per day). Light-level data from geolocator
tags were initially processed using the manufacturer’s built-in template
fit algorithm to estimate locations[24]. However, this method was shown to
be biased south in winter and north in summer when applied to an Arctic
seabird[25]. We therefore applied a sea surface temperature (SST)
correction to further refine position estimates by comparing tag-collected
SST measurements with remotely sensed SST data available for the same
dates. We applied an unscented Kalman filter, a state-space model that
incorporates measurement error estimation and the smoothing of the SST
field directly in a single model to estimate the most probable track[26].
We formulated the model with a “solstice” error structure to account for
highly erroneous positions near the equinoxes when light level is similar
across the globe (defined by the model as September 16-October 2, March
10-March 27) and during which time positions were not estimated. Models
were fit using the ukfsst package in R.
The raw datasets in this study are available publicly under a creative
commons license as a part of the Arctic Animal Movement Archive[52] on
www.movebank.org (Study Numbers: 973570814, 630339095, 300812056).