DOI: 10.5061/dryad.nk98sf7v1
title: Sympatrically-breeding congeneric seabirds (Stercorarius spp.) from Arctic Canada migrate to four oceans

description: 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.
description: 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<sup>[22]</sup> 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. <i>Tag
 programming and processing</i> 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.<sup>[23]</sup> using the <i>foieGras</i>
 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<sup>[24]</sup>. However, this method was shown to be
 biased south in winter and north in summer when applied to an Arctic
 seabird<sup>[25]</sup>. 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<sup>[26]</sup>. 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
 <i>ukfsst</i> package in R.
description: The raw datasets in this study are available publicly under a
 creative commons license as a part of the Arctic Animal Movement
 Archive<sup>[52]</sup> on www.movebank.org
 (Study Numbers: 973570814, 630339095, 300812056).