DOI: 10.5061/dryad.gmsbcc2q6
title: Year-round at-sea movements of fairy prions from south-eastern Australia

description: Effective conservation assessments require detailed information of
 species’ ecological niches during the whole annual cycle. For seabirds,
 this implies investigating the at-sea distribution and foraging behaviour
 during both the breeding and non-breeding periods. However, until
 recently, collecting information about the smallest species has been
 precluded by the excessive size of the required devices. This lack of
 knowledge is exacerbated in the case of polytypic genera with species
 sharing very similar appearance and behaviour, such as the super-abundant
 prions (Pachyptila spp.). The present study investigates the year-round
 at-sea distribution and foraging ecology of the fairy prion (Pachyptila
 turtur) in south-eastern Australia. Using miniaturized GPS during the
 breeding season and geolocators (GLS) during the non-breeding period, the
 results highlight the importance of the continental shelf-edge waters for
 fairy prions throughout the year. In addition, contrary to previous
 assumptions, the GLS data revealed an unsuspected post-breeding migration
 to the waters south of Australia, during which individuals likely undergo
 a rapid moult of flight feathers. Understanding the at-sea distribution
 and ecology of prions during the whole annual cycle will be fundamental to
 their conservation as it can reveal species- or population-specific
 threats that have been overlooked because of their status of abundant
 species.
description: <strong>Animal handling and
 instrumentation</strong> The study was conducted
 during breeding (incubation and chick-rearing) and non-breeding periods
 over four consecutive years at Kanowna Island (39º15’ S, 146º30’ E) in
 northern Bass Strait, south-eastern Australia. Seven seabird species breed
 on this island (Fromant et al. 2020b), including 1000-4000 breeding pairs
 of fairy prion, which represent 1-4% of the Bass Strait population
 (Schumann et al. 2014). To evaluate the at-sea
 movements of fairy prions during the breeding season (incubation and
 chick-rearing periods), adult breeding birds were equipped with a
 miniaturized GPS data logger (nanoFix-GEO, Pathtrack Ltd, Otley,
 United-Kingdom), attached to two central tail feathers using waterproof
 tape (Tesa 4651; Beiersdorf AG). The GPS loggers were programmed to record
 locations at 20 min and 10 min interval during the incubation and
 chick-rearing periods, respectively. The total mass of logger attachments
 corresponded to 2.4 ± 0.2% of body mass (124 ± 10 g), which was unlikely
 to have impacted the foraging and breeding parameters of the equipped
 individuals (Fromant et al. 2021). Individuals were weighed (± 2 g;
 Pesola), and bill, tarsus (± 0.1 mm; Vernier callipers) and wing length (±
 1 mm; ruler) were measured. To determine the at-sea
 distribution of fairy prions during the non-breeding period, adult birds
 were equipped with leg-mounted GLS (Migrate Technology, model C65, United
 Kingdom). The total mass of logger attachments corresponded to 1.2 ± 0.1%
 of body mass of the equipped birds. Breeding individuals were equipped at
 the end of the breeding season and were recaptured during the following
 breeding season. In addition, the timing of wing moult was inferred from
 information provided by the GLS on the time spent on the sea surface (wet
 and dry sensor). Since flight feather renewal directly affects flying
 ability (Cherel et al. 2016), the peak of time spent on the water during
 the non-breeding period was used to identify the period when fairy prions
 moult their wing flight feathers. Finally, the dates of last and first
 burrow attendance, as well as the periods of burrow attendance during the
 non-breeding period, were determined by combining information from the GLS
 of activity (wet-dry) and movement data (presence of the bird in the
 breeding area) (Fromant et al. 2020c). When a burrow attendance was
 detected during the non-breeding period, it was not possible to confirm
 that the individuals returned to the exact same breeding colony due to the
 low spatial accuracy of GLS (Phillips et al. 2004). However, fairy prions
 are highly philopatric at the colony level (Ovenden et al. 1991) and it
 was assumed that tracked individuals were attending burrows at their
 colony during the non-breeding season. When individuals
 were recaptured, six body feathers and blood (0.2 mL from the brachial
 vein) were collected for sexing and stable isotope analysis. Sex was
 determined by DNA analysis (DNA solutions, Wantirna South, Australia) from
 either blood or a single body feather. Stable isotope ratios of carbon
 (δ<sup>13</sup>C) and nitrogen (δ<sup>15</sup>N)
 in whole blood and body feathers were used as proxies of foraging habitat
 and diet/trophic level, respectively. Specifically, isotopic values of
 whole blood (hereafter blood) reflect dietary integration of approximately
 two to four weeks, while body feathers reflect dietary intake when they
 were synthesized (Cherel et al. 2000) from the end of the breeding season
 and throughout the non-breeding period (Marchant and Higgins 1990).
 Therefore, isotopic values of blood were used to determine the trophic
 ecology of the fairy prion throughout the breeding season (incubation and
 chick-rearing), while body feathers were used for the non-breeding period.
 One body feather per individual was analysed to determine the inter-annual
 variations. In addition, in 2018-2019, four feathers per individual were
 analysed to investigate intra-individual variation.
 <strong>Data processing and
 analyses</strong> All data analyses were
 processed within the R statistical environment (R Core Team 2021). A speed
 filter with a threshold at 20 m·s<sup>-1</sup> was applied to
 remove erroneous locations (Spear and Ainley 1997). Because of poor
 satellite reception when the birds are feeding or sitting on the water,
 linear interpolation was applied to correct for unequal sampling
 frequencies between foraging and commuting. For each complete foraging
 trip (defined as the time spent at sea between the departure from, and the
 return to, the burrow), the following basic parameters were calculated:
 trip duration (h), total horizontal distance travelled (km), and maximum
 distance from the colony (km). Incomplete records of trips were only used
 to estimate maximum distance from the colony. During the chick-rearing
 period, trips were classified in two categories based on the data
 distribution of trip duration: short (≤ 2 d at sea) or long (&gt; 2 d
 at sea). Such a dual foraging strategy (alternating short and long trips)
 is common in procellariiform species, including prions (Weimerskirch et
 al. 1994). The expectation maximization binary
 clustering (EMBC) was used to infer fairy prion at-sea foraging behaviour
 (R package <em>EMbC</em>; Garriga et al. 2016, R Core Team
 2021). This method classifies four different movement types based on
 travel speed and turning angle between subsequent locations:
 travelling−commuting (high-speed low turn, HL), resting on the water
 (low-speed low turn, LL), and intensive (low-speed high turn, LH) and
 extensive searching (high-speed high turn, HH). This method has been shown
 to be well suited to interpreting ecologically meaningful behaviours from
 movement data for a range of procellariiform species (de Grissac et al.
 2017, Clay et al. 2019, Weimerskirch et al. 2020).
 Processing and calculations of GLS data were conducted using the
 <em>GeoLight </em>package in the R statistical environment
 (Lisovski et al. 2012, R Core Team 2021). The device records the maximum
 light intensity for each 5 min interval, and the determination of morning
 and evening twilights enables longitude (timing of local midday and
 midnight) and latitude (duration of day and night) to be estimated,
 providing two positions per day with an average accuracy of 186 ± 114 km
 (mean ± SD; Phillips et al. 2004). Before spatial analyses were conducted,
 data for two weeks before and after the autumn and spring equinoxes were
 excluded because latitude estimations around these periods are unreliable
 (Wilson et al. 1992). The dates of last and first burrow attendance were
 determined by combining information on activity (wet-dry: 100% dry for a
 period &gt; 8 h) and movement data (presence of the bird within 200 km
 from the breeding colony). These data were then used to estimate the
 duration and the total distance travelled during the post-breeding
 migration. The moulting period of flight feathers was determined for each
 individual using the period of maximum proportion of time spent on the
 water (wet-dry sensor being wet &gt; 90% per day; Cherel et al. 2016).
 Wet-dry data were sampled every 30 s with the number of samples wet and
 maximum conductivity recorded every 4 h. For both GPS
 and GLS data, filtered locations were used to generate kernel utilization
 distribution (UD) estimates. For GPS data, a smoothing parameter of h =
 0.2 was used with a grid of 0.1° × 0.1° cells (to avoid
 over-fragmentation), while for GLS data a h of 1.8 was selected
 (corresponding to a search radius of ~ 200 km) with a 1º x 1º grid cell
 size (based on the mean accuracy of the device). The 50% (core foraging
 area) and 95% (home range) kernel UD contours were obtained. Spatial
 analyses were performed using the <em>adehabitatHR</em> R
 package (Calenge 2006; R Core Team 2021). For stable
 isotope analyses, blood samples were freeze-dried, ground to powder and
 homogenized. Body feathers were cleaned of surface lipids and contaminants
 using a 2:1 chloroform:methanol solution in a ultrasonic bath, followed by
 two successive methanol rinses and air dried 24 h at 50°C (Fromant et al.
 2016). Each feather was then cut with scissors to produce a fine powder
 for homogenization before carbon and nitrogen isotope ratio determination
 using a continuous flow mass spectrometer (Delta V Plus or Delta V
 Advantage both with a Conflo IV interface, Thermo Scientific, Bremen,
 Germany) coupled to an elemental analyser (Flash 2000 or Flash EA 1112,
 Thermo Scientific, Milan, Italy) at the LIENSs laboratory (La Rochelle
 Université, France). Stable isotope values were expressed in conventional
 notation (<em>δX </em>=
 [(<em>R</em><sub>sample</sub>/<em>R</em><sub>standard</sub>) – 1]) where X is <sup>13</sup>C or <sup>15</sup>N and R represent the corresponding ratio <sup>15</sup>N/<sup>14</sup>N or <sup>13</sup>C/<sup>12</sup>C. <em>R</em><sub>standard</sub> values were based on Vienna Pee Dee Belemnite for <sup>13</sup>C, and atmospheric nitrogen (N<sub>2</sub>) for <sup>15</sup>N. Replicates of internal laboratory standards (Caffeine USGS-61 and USGS-62) indicate measurement errors &lt; 0.10 ‰ for δ<sup>13</sup>C and 0.15 ‰ for δ15N.