Migration behaviour, wintering areas and conservation biology of brown skuas breeding in the subtropical Amsterdam Island

Migration behaviour, wintering areas and conservation biology of brown skuas breeding in the subtropical Amsterdam Island | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Migration behaviour, wintering areas and conservation biology of brown skuas breeding in the subtropical Amsterdam Island Karine Delord, Anne-Sophie Bonnet Lebrun, Yves Cherel, Cécile Ribout, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5874357/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 Feb, 2026 Read the published version in Marine Biology → Version 1 posted 5 You are reading this latest preprint version Abstract Invasive non-native species are a major threat to seabirds, leading to the implementation of numerous eradication campaigns. However, eradication can also affect non-targeted species. There are concerns over the fact that the invasive mammal eradication using poisonous bait planned on Amsterdam Island might affect negatively the local population of subtropical brown skuas Stercorarius antarcticus hamiltoni . Here, movements of 21 adult brown skuas breeding at Amsterdam Island, southern Indian Ocean, its most northerly breeding site were studied during the non-breeding period using geolocation, in order to provide relevant information for conservation prior to the eradication program. Post-breeding movements of brown skuas vary considerably, ranging from residency on the breeding grounds to long-range migrations to reach distant northern non-breeding zones in the Southern Hemisphere. Most individuals remained in the Indian Ocean (with the exception of one that wintered in the Tasman Sea), targeting areas along a continuum from the subantarctic to the tropics. Wintering grounds were generally situated in productive dynamic upwelling waters or frontal systems, with brown skuas avoiding the less productive area of the South Subtropical Gyre in the Central Indian Ocean. Inter-individual differences were not fully explained by sex: if males and females exhibited differences in activity metrics, they did not differ in duration or distance reached during the non-breeding period. Feather isotopic values confirmed that the birds mainly moulted their body feathers in the wintering area. The low δ 15 N values of feathers grown in mixed subtropical-subantarctic waters suggest that skuas feed on low trophic level prey in these areas. Overall, our results provided relevant information for conservation, and in particular helped identify the optimal period for scheduling land-based operations for eradicating introduced species on Amsterdam Island. inter-breeding strategy geolocator loggers activity patterns Stercorarius antarcticus hamiltoni Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Seabirds share their time between sea and land, with a particularly marked contrast between the breeding season – during which they must regularly return on land to incubate their eggs or to feed their chicks – and the non-breeding season, during which most seabirds migrate far from their colony to spend the entire period at sea. However, there is a wide difference in non-breeding strategies and movements among seabird species, with a gradient ranging from non-migratory ( e.g. , the resident Masked booby Sula dactylatra (Roy et al. 2021 )) to the longest animal migration ( e.g. , almost 20,000 km one-way travel of the Arctic tern Sterna paradisaea (Alerstam et al. 2019 )). Seabirds are of particular conservation concern, facing both at-sea and terrestrial threats (Dias et al. 2019 ). In addition to climate change and severe weather conditions, which can affect seabirds everywhere, threats at-sea are mainly attributable to fishing (bycatch and overfishing) and pollution, while on land the main threat to seabirds is invasive non-native species (Dias et al. 2019 ). Invasive species (Jones et al. 2016 ) are of particular concern on islands, leading to the implementation of numerous eradication campaigns for the conservation of many species of seabirds (Jones et al. 2016 ; Brooke et al. 2018 ; Barbraud et al. 2021 ). Nevertheless, invasive species eradication can affect other non-target species (Travers et al. 2021 ), generating an additional terrestrial threat to some species. To assess the threats facing populations, it is therefore important to know how individuals share their time between sea and land. In particular, understanding the non-breeding strategy of seabirds help identify whether individuals are residents or migrants and, if they migrate, when they leave and return to their colony. Amsterdam Island is a remote island of the Indian Ocean, which has been identified as one of the world’s top priority islands for seabird conservation and consequently a good candidate for eradicating introduced invasive predators as a priority conservation objective (Segonzac 1972 ; Brooke et al. 2007 , 2018 ). This was confirmed by a recent survey of seabirds prior to eradication, which revealed the presence of 14 breeding (or probably breeding) seabird species, including eight burrowing petrels, two of which have never described on the island (the Juan-Fernandez petrel Pterodroma externa and the sooty shearwater Ardenna grisea; (Lesage et al. 2024 )). A comprehensive eradication plan of invasive mammals – the feral cat Felis catus , the brown rat Rattus norvegicus and the house mouse Mus musculus – was therefore scheduled for 2024. Based on previous impact of similar plans, managers anticipated that eradication could in particular affect the population of brown skua Stercorarius antarcticus hamiltoni , a top predator seabird breeding on Amsterdam island, in two ways: through either lethal effects due to secondary poisoning or by a reduction in basic prey, reducing breeding attempts and reproductive success (Travers et al. 2021 ). The population of subtropical brown skua from Amsterdam is small ( i.e. , ~ 80 breeding pairs; (Lesage et al. 2024 )) and its taxonomic status remains unclear (Ritz et al. 2008 ). This tiny population therefore appears to be highly vulnerable. Stercoraridae (jaegers and skuas) are mainly migratory species exhibiting long-distance migration outside the breeding period (long-tailed skua Stercorarius longicaudus , van Bemmelen et al. ( 2017 ); Arctic skua S. parasiticus , van Bemmelen et al. 2023 ; brown skua Stercorarius antarcticus lonnbergi , (Schultz et al. 2018 ). Southern species of skuas display a gradient in migratory strategies and distance travelled from their breeding colony. The south polar skua Stercorarius maccormicki is known to be a long-distance trans-equatorial migrant (Kopp et al. 2011 ; Weimerskirch et al. 2015 ), while brown skuas remain in the Southern Hemisphere, exhibiting differences in strategies among populations, over a continuum from subantarctic to tropical waters (Krietsch et al. 2017 ; Delord et al. 2018 ). Higher latitude populations of brown skuas migrate longer distances than temperate ones (Schultz et al. 2018 , 2023 ). However, the migratory behaviour of brown skuas on Amsterdam Island, its most northerly breeding site, remains unknown. In particular, it is unknown whether all the individuals are migratory or whether some individuals remain on the island year-round (with consequences for the risk of secondary poisoning during the eradication campaign) and what their migratory schedule is ( i.e. , when birds are absent from the island, and therefore when the risk of secondary poisoning is the lowest). In addition, any information on the year-round distribution, activity and migratory connectivity with other populations of brown skuas could be useful to managers, to help alleviate other threats to the species, in this context of potential detrimental effects of the planned invasive species eradication program (Runge et al. 2014 ). The aim of the study was therefore to: a) describe the migratory strategies of the birds, and in particular, to estimate whether all birds are migratory, b) describe the migratory schedule of migrant birds to recommend an optimal period for scheduling land operations for eradicating invasive non-native species (to minimise the risk of detrimental effects on skuas), and c) to take advantage of the collected data to describe migratory movements and activity patterns during migration, and evaluate the level of individual variability in these patterns. Materials and methods Study site Field work was conducted on Amsterdam Island (37° 50’ S; 77° 33’ E) in the subtropical part of the southern Indian Ocean (Belkin and Gordon 1996 ) in a mild, oceanic climate. The volcanic island consists of a mountainous 500–800 m plateau ‘Plateau des Tourbières’ with cliffs on the western edge. Non-native invasive mammal species – house mice Mus musculus , brown rats Rattus norvegicu s and feral cats Felis catus – occur throughout the island (Micol and Jouventin 1995 ). Amsterdam has been identified as of high conservation priority due to its seabird populations (Segonzac 1972 ; Brooke et al. 2007 , 2018 ; Lesage et al. 2024 ), including three endangered species: the Indian yellow-nosed albatross Thalassarche carteri , the sooty albatross Phoebetria fusca and the northern rockhopper penguin Eudyptes moseleyi , along with the endemic, endangered Amsterdam albatross Diomedea amsterdamensis (due to a very small population of 300–350 individuals; Barbraud et al. unpublished data). The central plateau provides nesting habitat for subtropical brown skuas (~ 80 pairs, TAAF KIORE Services 2022). On Amsterdam Island, an eradication campaign of invasive mammals has just been completed (first half-year 2024), as part of the RECI (Restauration des Ecosystèmes Insulaires de l’Océan Indien, https://taaf.fr/missions-et-activites/protection-de-lenvironnement/actions-de-terrain-et-programmes-menes/projet-reci/ ), a project funded by the European Union, the French Development Agency (AFD) and the French Southern and Antarctic Territories administration (TAAF). Eradication of the three invasive mammals’ species is included in the National Plan of Actions to improve the conservation status of the Amsterdam albatross (2018–2027). The types of methods considered for the eradication campaigns are divided into: 1) feral cats -using trapping and shooting and, 2) rats and house mouse - using chemical rodenticide containing brodifacoum. The aerial helicopter spraying strategy consisted of two applications of rodenticide over the entire island. Aerial spraying was supplemented by manual ground spraying in specific areas around infrastructures during the same period. The optimal period for scheduling land operations for eradicating introduced species to minimize detrimental effects on seabirds was estimated to be from May to July, i.e. the period with the smaller proportion of breeding seabird populations present on land. Following this conservation recommendation and due to different constraints (meteorology, logistic, feasibility ...etc), the campaign was scheduled during the austral winter 2024 (from the end of May to the end of July). Study species and field methods The brown skua generally breeds in loose colonies and is highly territorial during breeding, with strong breeding site tenacity and mate fidelity (Furness 1987 ). The brown skua is an annual breeder, usually laying two eggs in late October-early November, with hatching in late November-early December, and chick fledging ~ 50 days later in early January (Hahn & Peter 2003 ). The post-reproduction period runs from February to November (hereafter non-breeding). Brown skuas in Amsterdam Island were monitored punctually (during late 1990’s) and annually since 2018, with all individuals within the monitoring colony individually marked (numbered stainless steel and plastic engraved colour bands; see (Pacoureau et al. 2019 ). Breeding adults were captured and global location sensing (GLS) loggers were deployed in December 2018. GLS loggers are archival light-recording loggers used to study distribution and activity of birds over periods lasting up to ~ 2 years, by recording ambient light level every 10 min, from which local sunrise and sunset hours can be inferred to estimate location every 12 h (Wilson et al. 1992 ). GLS loggers also recorded saltwater immersion data at regular 10-min intervals, by testing for saltwater immersion every 3 s and storing the proportion of positive samples (time in seawater) at the end of each 10-min period. Saltwater immersion data were used to estimate daily activity budgets, as time immersed can be interpreted as time sitting on the water, and time dry can be interpreted as time flying and/or time on land. Despite their high mean spatial error of location estimates (over 100 km; (Phillips et al. 2004 ), GLS loggers can track birds for prolonged periods of time with minimal disturbance. Twenty-one of the 28 GLS loggers deployed were retrieved. Molecular sexing A DNA extraction was conducted with 2 µl of blood cells using a chelex resin (Chelex 100 Molecular Biology Resin, BIO-RAD; 10%) associated with Proteinase K. Then, a PCR with amplification of the CHD gene was performed following a standard procedure (Fridolfsson and Ellegren 1999 ). Stable isotopes Following (Jaeger et al. 2009 ), carbon and nitrogen stable isotopes values ( δ 13 C and δ 15 N, respectively) were measured on four different fully-grown body feathers from the lower back per bird. They were collected upon recapture of each individual bird, thus corresponding to the previous moulting period at sea recorded by the GLS. In seabirds, including skuas, feather isotope values represent the foraging habitat ( δ 13 C) and diet/trophic position ( δ 15 N) during the non-breeding period because adult birds replace their plumage at that time (Higgins and Davies 1996 ; Cherel et al. 2008; but see Graña Grilli and Cherel ( 2017 )). To facilitate interpretation of adult isotopic values, feathers were also collected from large chicks as control birds reflecting the skua diet during the summer breeding period. For each chick, a single body feather was used for isotopic analyzes, because chick feathers grow almost synchronously and thus present low inter-feather δ 13 C and δ 15 N variations (Carravieri et al. 2014 ). Feather preparation and isotopic analyses were detailed by (Jaeger et al. 2009 ). In brief, feathers were cleaned using a 2:1 chloroform: methanol solution and then oven dried for 48 hr at 50°C. Every single whole body feather was homogenized by cutting it with stainless steel scissors into tiny fragments and a subsample of ~ 0.3 mg was packed into tin containers for stable isotope analysis. The relative abundance of carbon and nitrogen isotopes were determined with a continuous flow mass spectrometer (Thermo Scientific Delta V Plus) coupled to an elemental analyzer (Thermo Scientific Flash 2000). Results are presented in the usual d notation relative to Vienna PeeDee Belemnite and atmospheric N 2 for δ 13 C and δ 15 N, respectively. Replicate measurements of reference materials (USGS-61 and USGS-63) indicated measurement errors < 0.10‰ for both δ 13 C and δ 15 N values. For statistical analyses, feather δ 13 C and δ 15 N values were either grouped at the individual level (wintering zones) or at the feather level (moulting zone) (Table 1 ). In the former analysis, isotopic values of the four feathers per bird were assigned to oceanic zones according to their δ 13 C values (tropical, subtropical and subantarctic) according to (Jaeger et al. 2010 ). In the latter analysis, each single body feather was tentatively assigned to a moulting zone (Weimerskirch et al. 2015 ). The GLS tracks of birds that wintered in only one marine area were used to assign the corresponding feather isotope values to that area. The feather isotope values of skuas that spent the non-breeding period in more than one area were then carefully examined to correctly assign the isotopic values. Isotopic values could not reliably be assigned to a wintering area for four feathers using the described 2-step protocol (see ‘Unknown’ in Table 1 ). Table 1 Feather isotopic values of brown skuas according to individual wintering zones and to feather moulting zones (see text). Note that birds may moult in several different zones. Within wintering or moulting zones, values sharing the same superscript letters are not significantly different at the 0.05 level (see text). Values are means ± SD. Wintering areas and habitats Individuals Body feathers Feather δ 13 C Feather δ 15 N C : N mass (n) (n) (‰) (‰) ratio Wintering zones Tropical 4 15 -15.9 ± 0.2 a 13.0 ± 0.6 a 3.15 ± 0.02 Subtropical 15 52 -17.0 ± 0.6 b 15.1 ± 1.7 b 3.14 ± 0.03 Subantarctic 7 13 -19.6 ± 1.0 c 12.4 ± 3.0 a 3.15 ± 0.04 Chicks (Amsterdam) 10 10 -16.6 ± 0.4 d 15.8 ± 0.4 b 3.14 ± 0.02 Moulting zones North-west of Australia (tropical) 4 15 -15.9 ± 0.2 a 13.0 ± 0.6 a 3.15 ± 0.02 Amsterdam (subtropical) 3 9 -16.9 ± 0.6 b,c 16.0 ± 1.7 b 3.15 ± 0.03 East of Amsterdam (subtropical) 5 19 -17.1 ± 0.4 b 15.0 ± 1.4 b,c,d 3.13 ± 0.02 South of Australia (subtropical) 6 22 -17.0 ± 0.7 b 15.2 ± 1.3 b,c 3.16 ± 0.03 South of Amsterdam (subantarctic) 4 7 -20.1 ± 1.1 d 14.0 ± 1.7 d 3.18 ± 0.02 Individual DZ20236 (subantarctic) 1 4 -19.1 ± 0.1 d 8.5 ± 0.5 a 3.11 ± 0.02 Unknown 4 4 − − - Chicks (Amsterdam) 10 10 -16.6 ± 0.4 c 15.8 ± 0.4 b,c 3.14 ± 0.02 Analytical methods Individual locations were estimated using the probGLS package in R (Merkel et al. 2016 ). To improve the estimates, the daily median sea surface temperature SST recorded by GLS loggers was matched to satellite-derived SST (0.25° × 0.25°, NOAA OI SST V2 High- Resolution Dataset; (Merkel et al. 2016 )). Migration timing (departure/arrival dates from/at the colony/non-breeding grounds, and migration duration) was inferred by combining visual inspection of each track ( i.e. , longitudinal directional movement during three consecutive days) and of activity data ( i.e. , periods of no saltwater immersion) (Figures S1 & S2). Arrival at the non-breeding grounds was detected when movement stopped being directional, and arrival back at the colony was detected when rapid movement was followed by several days of no salt water immersion. The duration of the non-breeding period was calculated as the interval between departure and colony return, and the duration of outward and inward migrations as the interval between the initiation and end of migratory movements. For each individual, maximum distance from the breeding colony was calculated using the trip package in R (Sumner 2018 ). The spatial distribution of brown skuas was visualised using Gaussian kernel analysis with a cell size of 2° x 2° and a fixed smoothing parameter (h) of 2°, using the ‘adehabitatHR’ package in R (Calenge 2006 ). Both h value and grid cell size were based on the mean accuracy of the devices (Phillips et al. 2004 ). Five metrics describing daily activity were calculated: (1) daily time spent on water (sum of time spent immersed in each 10-min blocks in a day, to obtain hours in the water per day), (2) daily average wet bouts duration (duration of uninterrupted sequences of 10-min blocks of immersion data = 200, i.e. , time spent totally immersed), (3) daily average dry bouts duration (duration of uninterrupted sequences of 10-min blocks of immersion data = 0), (4) daily number of wet bouts , and (5) daily number of dry bouts . Although the loggers integrated activity within each 10-min block and so did not provide the exact timing of landings and take-offs, (Phalan et al. 2007 ) found for comparative purposes that bouts defined as a continuous sequence of 0 values for flight (dry) and a sequence of values of 1 or greater for wet bouts, were suitable proxies for activity. Unless stated otherwise, whenever GLS loggers contained data for two consecutive years, only the first year of data was used. Statistical analyses Differences between sexes in timing of non-breeding movements were tested using Wilcoxon rank tests (only one trip per individual). To assess how activity varied over time, sex and among individuals principal components analysis (PCA built with the ‘PCA’ function, FactoMineR package Lê et al. 2008 ) was first run over the five daily wet/dry activity metrics to circumvent collinearity issues and to avoid redundancy. The first three principal components explained 82.1% of the total variance (1st axe: 41.7%, 2nd axe: 20.6% and 3rd axe: 19.8%). The detailed results of PCA, the variables and their loadings for each axis are summarised in Table 2 . Differences in the three principal components between sexes and months were tested using Kruskal-Wallis tests followed by Dunn’s tests to identify which groups were different (Tomczak and Tomczak 2014 ). Only data for the months of April to August (the 5 months available for all individuals) were used in the analyses. Spatial and statistical analyses were performed using R (R Core Team 2024 ). Results are presented as means ± SD unless otherwise indicated. Table 2 Results of principal components analyses (PCA) on six wet/dry metrics on brown skuas. Principal components Total variance explained (%) Time spent on water Dry bouts duration Dry bouts number Wet bouts duration Wet bouts number First 41.7 + (r = 0.91) 1 - (r = -0.68) + (r = 0.88) Second 20.6 - (r = -0.75) + (r = 0.66) 1 the symbol used gives the sign of the correlation (+: positive, -: negative); the number in brackets indicates the value of the correlation coefficient r Results At the end of the breeding period, most birds dispersed widely, undertaking long-distance migrations, and spent the non-breeding season in the eastern part of the Indian Ocean up to the Tasman Sea (~ 7500 km from the breeding ground) exhibiting high inter-individual variability in area and distance reached from the colony (Figure S1 , Table S1 ). Individuals arrived at their non-breeding site between late February/early May and left between late July/late September (Table 3 ). On average, tracked individuals were away from the breeding colony for 154 ± 37 d, at a mean maximum distance to the colony of 3519 ± 2042 km (Table 3 ). Females and males did not differ in duration or distance reached during the non-breeding period. The factors driving differences in migratory strategy remained unclear with no evidence of sex difference in non-breeding movement metrics and a limitation due to the small sample sizes. A small proportion of the tracked skuas (~ 10%, n = 2) could be considered as resident on the island (“terrestrial” individuals) throughout the year on the basis of a combination of movement and activity patterns (Table S1 , Figure S1 ). Table 3 Timing of non-breeding movements of brown skuas from Amsterdam Island, which were tracked using GLS loggers in 2018–2019. For each parameter, values sharing the same superscript letter (a, b; Wilcoxon test) are not statistically significantly different. Mean ± SD (minimum – maximum). Non-breeding movements Sex Duration (days) Maximum distance to the colony (km) F 160 ± 31 (91–192) a 3695 ± 1979 (462–6317) b M 145 ± 42 (61–199) a 3232 ± 2108 (730–7529) b All 154 ± 37 3519 ± 2042 The migratory skuas ranged mainly between tropical and subtropical waters and punctually in subantarctic waters (Figs. 1 & S4). Individuals were predominantly distributed in subtropical waters (76 ± 18.2% of locations; Fig. 1 ), followed by subantarctic waters (23.6 ± 18.3%) and, very occasionally, Antarctic waters (0.4 ± 0.8%). Only 29% of individuals (n = 6) visited Antarctic waters, spending less than 3% of their locations there. The sea surface temperature recorded by geolocators varied between 18.0 ± 6.1°C (min: 7°C, max: 37°C) in May to 11.0 ± 2.7°C in August (min: 3°C, max: 32°C). Females and males occupied similar areas and habitats during the non-breeding period (15.8 ± 6.2°C and 14.9 ± 4.8°C, respectively). Seven birds were tracked for two consecutive years, out of which only one changed its migratory strategy, being resident the first year and migrating the following year (Figure S1 ). Over the non-breeding period, individuals were partly away from the breeding grounds during March to August, with a proportion of the tracked birds that were at sea varying from 43 to 90%. Apart from the two resident individuals that did not migrate and were considered to remain on the island, the migration schedule permitted to identify the period from May to July as the period when the proportion of the breeding population on land is the lowest (< 15% of the tracked birds). Only three individuals (from two breeding pairs) bred successfully during the season of deployment (failure for the other birds occurred at chick-rearing stage). The rate of breeding failure among tracked individuals was comparable to the high rate observed within the monitoring colony (86.7% versus 79.8 ± 8.0%, calculated as the 1-percentage of nests with eggs that have had one chick or more over the period 2019 to 2024, n = 22 nests). Activity characteristics Females tended to spend more time on water daily (higher percentage of time wet, longer and more numerous wet bouts) compared to males (Table 4 ). Table 4 Values of brown skua activity parameters (mean ± SD) recorded using Global Location Sensor (GLS), separated by sex. Females (n = 13) Males (n = 8) All (n = 21) Time spent on water (%) 73 ± 29 64 ± 34 69 ± 32 Wet bouts (sitting on water) duration (h) 1.0 ± 9.0 0.6 ± 0.5 0.89 ± 7.2 Dry bouts duration (h) 2.2 ± 8.9 3.5 ± 13.4 2.7 ± 10.8 Wet bouts (sitting on water) number 15.4 ± 8.5 14.8 ± 9.3 15.2 ± 8.8 Dry bouts number 3.3 ± 3.1 3.7 ± 3.1 3.5 ± 3.1 Component loadings indicated (Table 2 ) that the first axis integrated the duration of dry bouts (loading = -0.68) and the percentage of time spent wet and the number of wet bouts (loading = 0.91 and 0.88, respectively). The second and third axis integrated the number of dry bouts and the duration of wet bouts (Table 2 ). Brown skuas differed in the daily activity parameters by month and sex whatever the synthetic activity variables considered (1st and 2nd axes, Table 4 ). Males and females did not differ in the values of the first axis, except in August when females tended to have longer dry bouts than males (Fig. 2 ). Females also tended to exhibit higher percentage of time spent on water at the beginning of the period and longer dry bouts at the end (a moderate effect of the month on the first axis was detected; eta2[H] = 0.063, Fig. 2 a). Dry bouts duration appeared to be particularly longer in August. Furthermore, females tended to exhibit a higher number of dry bouts in August (compared to May; a small effect of the month on the second axis was detected; eta2[H] = 0.007, Fig. 2 b). There were no differences for males for the first axis from month to month, except at the end of the period (August) when individuals had longer dry bouts (a moderate effect of the month was detected; eta2[H] = 0.061, Fig. 2 a). Males exhibited longer wet bouts during April compared with all other month in the period (weak effect of month on the second axis detected; eta2[H] = 0.058, Fig. 2 b). Individuals differed in their activity characteristics (synthetic activity variables; Figures S3 & S5). In particular, the first principal component permitted to clearly discriminate resident individuals, that exhibited longer dry bouts (large effect size detected, eta2[H] = 0.3; Figures S3a & S5). These two individuals (a female DZ20234-B4100 and a male DZ28805-B4123) were resident all year long. Although the values of the second axis varied significantly between individuals (large effect size detected, eta2[H] = 0.182), this did not seem to be linked to whether individuals were migrants or residents. However, individuals differed, with some displaying longer wet bouts and others a higher number of dry bouts. There were therefore differences in the behaviour of individuals beyond migrating or not. Stable isotopes Body feathers were collected from 20 adult skuas (out of 21 individuals) that carried a GLS. Feather isotopic values of adult brown skuas from Amsterdam Island ranged widely, from − 21.0 to -15.4‰ (a 5.6‰ difference), and from 8.1 to 19.0‰ (10.9‰) for δ 13 C and δ 15 N values, respectively. Feather δ 13 C values indicated wintering in the tropical, subtropical and subantarctic zones, but not further South, in the Antarctic Zone. Some birds showed low intra-individual variations in isotopic values of their four feathers, while large SD indicated that other individuals wintered over different water masses. Combining GLS data and isotopic values at the feather level depicted an informative pattern (Fig. 3 ). Feather δ 13 C and δ 15 N values from different moulting zones were significantly different (Kruskal-Wallis: H = 51.1 and 39.7 for δ 13 C and δ 15 N, respectively, both p < 0.0001). Post-hoc pairwise Conover-Inman tests documented three notable features (Table 1 ): (i) feather δ 13 C values overall increased with decreasing latitudes, from the lower values of feathers that were moulted south of Amsterdam Island (-20.1‰) to the higher δ 13 C values of adults that moulted in tropical waters in north-west Australia (-15.9‰); (ii) feather isotopic values were identical for chicks and adults that moulted in the subtropics, whatever the moulting grounds (Amsterdam, east of Amsterdam and south of Australia, from western Australia to the Tasman Sea); (iii) one individual (ring number DZ20236) synthesized its four body feathers in subantarctic waters (-19.1‰), where it presented remarkable low δ 15 N values (8.5‰) that differed from all the other groups (13.0–16.0‰). Discussion Our study described the non-breeding movements of the most northerly breeding population of brown skuas, from the temperate Amsterdam Island in the southern Indian Ocean. Their latitudinal at-sea distribution outside of the breeding season was comparable to that of the subantarctic populations of the Crozet and Kerguelen archipelagos ((Delord et al. 2018 ); Fig. 4 ) in the southern Indian Ocean, but also from subantarctic islands in the southern Atlantic Ocean (Bird Island and King George Island; (Phillips et al. 2007 ; Carneiro et al. 2016 ; Krietsch et al. 2017 )) and from a temperate island in the southern Pacific Ocean (Chatham Island; (Schultz et al. 2018 )). The birds targeted distant areas distributed over neritic and oceanic waters of subantarctic, subtropical and tropical biomes. These targeted habitats were consistently found in other studies in the Indian Ocean (Delord et al. 2018 ), but also in other ocean basins, as evidenced by stable isotopes (Mills et al. 2023 ). During the non-breeding season, brown skuas from Amsterdam Island were completely segregated from populations from other ocean basins (southern Atlantic Ocean (Phillips et al. 2007 ; Carneiro et al. 2016 ; Krietsch et al. 2017 ); southern Pacific Ocean (Schultz et al. 2018 )). In contrast, they shared non-breeding grounds with other populations of the southern Indian Ocean: the Amsterdam Island area, along the Southeast Indian Ridge in the Eastern Indian Ocean and the waters off Australia (three main sectors: Tasmania, Indian Ocean Coast / Tropic of Capricorn and Great Australian Bight) (Delord et al. 2018 ); Fig. 4 ). Additionally, they shared non-breeding areas at sea with different populations of south polar skua Stercorarius maccormicki (Weimerskirch et al. 2015 ). Brown skuas from Amsterdam Island showed high levels of inter-individual variability in migratory behaviour. Such inter-individual variability was previously evidenced at inter-population and intra-population levels in several species of jaegers and skuas (Long-tailed skua Stercorarius longicaudus (van Bemmelen et al. 2017 ); Arctic skua S. parasiticus : van Bemmelen et al. 2023 ; brown skua Stercorarius antarcticus lonnbergi : (Krietsch et al. 2017 ; Schultz et al. 2018 ); Falkland skua S. a. antarctica (Phillips et al. 2007 ); south polar skua S. maccormicki : (Kopp et al. 2011 ; Weimerskirch et al. 2015 ). However, the population from Amsterdam Island appeared to be the only one to have resident birds, albeit in small numbers. This is likely related with the fact that Amsterdam Island hosts the most northerly population of the species in subtropical waters, where most individuals from various localities winter. Even for the only other temperate population of brown skuas (from the Chatham Islands that are located at the Subtropical Front), all birds were migratory. Although individuals exhibited the smallest spatiotemporal scale in non-breeding movement compared to subantarctic and Antarctic populations (ranges away from the colony: Crozet & Kerguelen Islands 4000 km, (Delord et al. 2018 ), Bird Island 1500–2700 km, (Carneiro et al. 2016 ), King George Island 1700–2500 km, (Krietsch et al. 2017 ), South East Island-Chatham 1500 km, (Schultz et al. 2018 )). Our study provides some insight into the intra-individual variability in migratory strategies of brown skuas from Amsterdam Island. Even though only seven individuals were tracked for two consecutive years, their strategies appeared nevertheless consistent across years (Figure S1 ). Such inter-annual consistency has been found for the species at the population level in South Georgia (Carneiro et al. 2016 ) and at the individual level in King George Island (Krietsch et al. 2017 ). However, in our study, one bird changed from being resident during the first non-breeding season to being a migrant during the next; Figure S1 ). Such flexibility in non-breeding movements was evidenced for long-tailed skuas (van Bemmelen et al. 2017 ). Nonetheless, our data did not permit us to estimate to what extent migratory birds might shift from a migratory to a resident strategy in response to environmental conditions. As previously found in brown skuas from the Kerguelen Islands (Delord et al. 2018 ), the δ 13 C values of Amsterdam skuas correspond well to the latitudinal δ 13 C gradient of Southern Ocean water masses (Cherel and Hobson 2007 ), with δ 13 C values of feathers that were synthesized in subantarctic waters (n = 13, -19.6 ± 1.0‰) and tropical waters (n = 15, -15.9 ± 0.2‰) being lower and higher, respectively, than values of subtropical feathers (n = 52, -17.0 ± 0.6‰). In agreement with wintering areas primarily located in the subtropics, feather δ 13 C values indicated that most body feathers were synthesized in subtropical waters. This precludes using δ 13 C values to differentiate between feathers that grew on the breeding and wintering grounds, as they did not present obvious isotopic differences. Feather δ 15 N values are difficult to interpret, because δ 15 N baselines vary in different water masses, thus obscuring the trophic interpretation of δ 15 N. However, the low δ 15 N values (8.1-9.0‰) of the four body feathers of the individual DZ20236 are puzzling. Such low δ 15 N values were previously found in many feathers of brown skuas from the Kerguelen Islands (Delord et al. 2018 ) and in a few feathers of South polar skuas (Weimerskirch et al. 2015 ), when they forage at similar latitudes in the southern Indian Ocean. This suggests that skuas fed on low trophic level prey in the area, but this remains to be confirmed. A comparison of the skua δ 15 N values with those of other subantarctic and subtropical organisms suggests that the unknown prey was not marine mammals, seabirds, cephalopods or fish, but instead macrozooplankton, probably crustaceans (Cherel et al. 2008b , 2010 ; Stowasser et al. 2012 ); this hypothesis needs to be thoroughly investigated. We found sex differences in activity metrics, as in the population from King Georges Island (Krietsch et al. 2017 ). These behavioural differences are probably linked to the reversed sexual size dimorphism in brown skuas (Phillips et al. 2002 ). However, contrary to other populations (Krietsch et al. 2017 ), females from Amsterdam island tended to spend on average more time on water and to make longer wet bouts than males. This could result from a difference in migratory strategy, males maybe staging at sea for shorter periods of time than females and/or they possibly forage more on terrestrial prey. Such a sex-related behaviour merits further investigation in relation to the diet, which is poorly known at Amsterdam Island (Carravieri et al. 2017 ; Renedo et al. 2018 , 2020 ). In general, the factors driving differences in migratory behaviour (inter-annual, inter-individual, sexual, etc.) are not entirely clear and require further study. Nevertheless, it is likely that different strategies lead to varying ecological and anthropogenic pressures across populations, which underscores the importance of considering such variability in future conservation planning and management (Carravieri et al. 2017 ). A thorough understanding of the distribution and movements of brown skuas from Amsterdam Island will contribute to a better understanding of epizootic pathways (Gorta et al. 2024 ). Brown skuas were already identified as spreaders of the pathogen of avian cholera ( Pasteurella multocida ; (Bourret et al. 2018 ; Jaeger et al. 2018 ) with conservation issues for the seabird community of the island (Brooke et al. 2007 ; Lamb et al. 2023 ). Furthermore, in a context of severe and widespread impacts of high-pathogenicity avian influenza virus (HPAIV H5N1) on wild animals (Klaassen and Wille 2023 ) with ongoing spread in the southern Hemisphere (Leguia et al. 2023 ; Bennet et al. 2024 ; Bennison et al. 2024 ), monitoring the movements of brown skuas is of increasing conservation and public health relevance. Finally, our results helped identify the optimal period for scheduling the first phase of land operations for eradicating introduced species on Amsterdam Island. The period of lower detrimental effect on skuas based on our results appeared to be from May to July, given that this was the period with the smallest proportion of the breeding population present on land. Following this conservation recommendation and considering other constraints (meteorology, logistic, feasibility, etc.), the campaign was scheduled from May to July 2024. The observed pre-eradication breeding failure was ~ 87% at Amsterdam Island and very high compared to other breeding sites ( e.g. , ~ 16% (95% CI: 12%-22%) in the Kerguelen archipelago; (Goutte et al. 2014 )), so although detrimental effects of the eradication campaign are to be feared, beneficial effects can be expected if eradication is successful, through a) an increase in reproductive success in the short term, and b) an increase in the population size of prey species in the medium term. However, mid- and long-term post-eradication surveys will be needed to confirm the potential positive effects of eradication of invasive non-native species on seabirds and the benefits for conservation purposes (for a review: Phillipe-Lesaffre et al. 2022). Genetic investigations are underway to elucidate the status of the Amsterdam Island population, and chances are that it is an evolutionary unit distinct from other populations in the southern Indian Ocean (i.e. Crozet Is. and Kerguelen Islands, Viricel et al. unpubl. data). Declarations Acknowledgements The authors thank fieldworkers involved in the monitoring program, namely Jérémy Dechartre, Anthony Le Nozahic, Anthony Buttet, Marie Fretin, Augustin Clessin, and Jérémy Tornos. They also thank the ECOPATH project n°1151 (French Polar Institute IPEV, PI T. Boulinier) for their support in the field and the “Plateforme d’Analyses Elémentaires” (LIENSs, La Rochelle) for stable isotope analysis. We are grateful to Benjamin Dupuis, David Pinaud and Samuel Peroteau for their advice on spatial data. We are indebted to Fabrice Le Bouard for operational details of the eradication campaign of invasive mammals on the Amsterdam Is., as part of the RECI-eradication program. We acknowledge Dominique Joubert for the management of the demographic CEBC French Southern Seabirds database. PB is an honorary member of the IUF (Institut Universitaire de France). Funding This monitoring program was supported financially and logistically by the French Polar Institute IPEV (project 109, PI C. Barbraud/H. Weimerskirch), the Zone Atelier Antarctique (CNRS-INEE), Terres Australes et Antarctiques Françaises. The Comité de l’Environnement Polaire and the Ministry of Research Ethics Committee approved protocols and activities undertaken in this program. The study is a part of the long-term Studies in Ecology and Evolution (SEE-Life) program of the CNRS (C. Barbraud). Authors’ contributions . ASBL and KD are joint first authors. Study design: KD, CB and YC. Data analysis and processing: KD, ASBL, YC, CR, GG. KD, ASBL, CB and YC wrote the text and all authors edited and revised the manuscript, gave final approval for publication and agreed to be held accountable for the content therein. Availability of data and material The data used in the present article will be provided for open access as supplementary. Code availability The custom code used in the present article will be provided for open access as supplementary. Compliance with ethical standards Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Ethics approval The Ethics Committee of French Polar Institute-IPEV and the Comité Environnement Polaire approved the field procedures for the French Southern Territories. Consent to participate All authors have agreed to participate in the study and its writing in the form of an article. 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Ellis Horward, Chichester, pp 131–134 Supplementary Files suskamsSI241212.docx Cite Share Download PDF Status: Published Journal Publication published 16 Feb, 2026 Read the published version in Marine Biology → Version 1 posted Editorial decision: Revise and Resubmit 04 Mar, 2025 Reviewers agreed at journal 23 Jan, 2025 Reviewers invited by journal 23 Jan, 2025 Editor assigned by journal 23 Jan, 2025 First submitted to journal 21 Jan, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5874357","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":406250076,"identity":"0aafb7d2-8d5f-4f9a-9c6f-d4f211cdd376","order_by":0,"name":"Karine Delord","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDUlEQVRIie3OMUvDQBTA8RceJMurXVOOxq8QyVAEqV8lIVBX3ToUPQjYpdA1hepn6FQQBE8OMlVcXV06KQjZiy/WSodc7djh/nAHx/HjPQCb7QDz+Sg+jvT4pj5AuPny5H8EK7LYIqTMBP5I43YP0hq+vOvLPrTHiMXX53036HjKKa8er4FEvRF0Eep8AdEkc9PJ3TyNTkcxinypgY7iWhJADzTvk8w0RdiYq2T2Bi6SUnBO9YsFzSWTFSRPP2Sqbn4JL2Ygwq+mSJ6CFZEqDtcEjaSV8xQq/CjXbupMi/TkYZRkgpQmE/Ffe1jS4Kw9HmYaPgbd446nn0teLDCRjdx+OLK6dwObzWaz7ewbIDFRKfo0GssAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0001-6720-951X","institution":"Centre d'Etudes Biologiques de Chizé, UMR 7372 CNRS","correspondingAuthor":true,"prefix":"","firstName":"Karine","middleName":"","lastName":"Delord","suffix":""},{"id":406250077,"identity":"96d76408-6920-4366-898f-c83a727cff35","order_by":1,"name":"Anne-Sophie Bonnet Lebrun","email":"","orcid":"","institution":"CNRS UMR7372: Centre d'Etudes Biologiques de Chize","correspondingAuthor":false,"prefix":"","firstName":"Anne-Sophie","middleName":"Bonnet","lastName":"Lebrun","suffix":""},{"id":406250078,"identity":"e42940c5-ac44-431e-9a66-0041e068b6f3","order_by":2,"name":"Yves Cherel","email":"","orcid":"","institution":"UMR7372: Centre d'Etudes Biologiques de Chize","correspondingAuthor":false,"prefix":"","firstName":"Yves","middleName":"","lastName":"Cherel","suffix":""},{"id":406250079,"identity":"4dddfba2-feec-42ae-b8b8-35e7318c35a8","order_by":3,"name":"Cécile Ribout","email":"","orcid":"","institution":"UMR7372: Centre d'Etudes Biologiques de Chize","correspondingAuthor":false,"prefix":"","firstName":"Cécile","middleName":"","lastName":"Ribout","suffix":""},{"id":406250080,"identity":"8f756c0f-d405-4f5d-93f9-6221c1ef2692","order_by":4,"name":"Gaël Guillou","email":"","orcid":"","institution":"UMR7266: Littoral Environnement et Societes","correspondingAuthor":false,"prefix":"","firstName":"Gaël","middleName":"","lastName":"Guillou","suffix":""},{"id":406250081,"identity":"982d170e-ef5d-4727-9e55-27fe85b0b07e","order_by":5,"name":"Paco Bustamante","email":"","orcid":"","institution":"UMR7266: Littoral Environnement et Societes","correspondingAuthor":false,"prefix":"","firstName":"Paco","middleName":"","lastName":"Bustamante","suffix":""},{"id":406250082,"identity":"766f9610-aaac-40ca-bfe2-6b094c606e35","order_by":6,"name":"Christophe Barbraud","email":"","orcid":"","institution":"UMR7372: Centre d'Etudes Biologiques de Chize","correspondingAuthor":false,"prefix":"","firstName":"Christophe","middleName":"","lastName":"Barbraud","suffix":""}],"badges":[],"createdAt":"2025-01-21 14:37:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5874357/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5874357/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00227-025-04770-w","type":"published","date":"2026-02-16T15:59:33+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":74925985,"identity":"ffb296d8-8d80-4c9b-8472-8ec2e29af98c","added_by":"auto","created_at":"2025-01-28 11:31:10","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":453607,"visible":true,"origin":"","legend":"\u003cp\u003eKernel densities of individual adult brown skuas from Amsterdam Island during their non-breeding period in 2019 (time between departure from the colony and arrival back at the colony for each bird, except the two residents for which we display locations between the time when the first migrant bird left the colony and when the last migrant bird returned). Salmon and blue dots show raw location data. Kernel density-based utilization distributions at 25% (semi-transparent polygons, red for females and blue for males). Land shown in grey. Breeding colony (black triangle) is indicated. The main frontal structures (obtained from Belkin and Gordon 1996), the Polar Front (PF), Southern Subtropical Front (SSTF) and Northern Subtropical Front (NSTF), are shown by grey lines.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5874357/v1/cf3c84028136358c2b17032a.png"},{"id":74926872,"identity":"86db50ee-0165-4291-b7ba-89a6cfc6a4fd","added_by":"auto","created_at":"2025-01-28 11:39:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":339616,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal components analysis (values are means ± SD of first and second axis) of activity parameters according to sex \u003cem\u003ei.e.,\u003c/em\u003efemale (red line) and male (black line) in brown skuas from Amsterdam Island. Differing letters (red: females, blue: males) indicate statistical difference within sex between months for both females and males (Kruskal-Wallis test). Stars indicate differences between sexes for a given month (Kruskal-Wallis test): ** for p\u0026lt;0.01, *** for p\u0026lt;0.001, **** for p\u0026lt;0.0001).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5874357/v1/7ca07c93c0b6d156178acbf4.png"},{"id":74925988,"identity":"30acd72d-3b52-499f-afbd-6a46eaa0253d","added_by":"auto","created_at":"2025-01-28 11:31:10","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":112454,"visible":true,"origin":"","legend":"\u003cp\u003eBody feather δ\u003csup\u003e15\u003c/sup\u003eN \u003cem\u003eversus\u003c/em\u003e δ\u003csup\u003e13\u003c/sup\u003eC values of adults and chicks (black circle) of brown skuas from Amsterdam Island according to their moulting zones. Values are means ± SD of all body feathers synthesized within the same habitat (see Table 1). Abbreviations: Ams, Amsterdam Island (black square); E Ams, east of Amsterdam Island (green diamond); NW Austr, north-west of Australia (red triangle up); S Ams, south of Amsterdam Island (cyan square); S Austr, south of Australia (dark green hex). DZ20236 (blue triangle down) refers to the ring number of an individual adult skua (see text).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5874357/v1/c7a7f01841c3a35e94aa1ea4.png"},{"id":74926004,"identity":"171312a9-88e2-4820-827f-766ed8b2ed16","added_by":"auto","created_at":"2025-01-28 11:31:12","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":335104,"visible":true,"origin":"","legend":"\u003cp\u003eNon-breeding distribution (Kernel utilization densities 25%) of five populations of skuas (in blue South Polar skuas \u003cem\u003eStercorarius maccormicki\u003c/em\u003e, and in red brown skuas \u003cem\u003eS. antarcticus\u003c/em\u003e) from subtropical to south polar breeding colonies: Amsterdam Is. (this study), Kerguelen and Crozet Is. (Delord et al. 2018), Adélie Land and Svarthamaren (Weimerskirch et al. 2015). Land shown in grey. Breeding colony (black triangle) is indicated. The main frontal structures (obtained from Belkin and Gordon 1996), the Polar Front (PF), Southern Subtropical Front (SSTF) and Northern Subtropical Front (NSTF), are shown by grey lines.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5874357/v1/dc7524e718a7dda153450cf0.png"},{"id":103251266,"identity":"c4603c5f-5ed7-4ec5-b1e3-d470b7d763c9","added_by":"auto","created_at":"2026-02-23 16:07:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1946728,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5874357/v1/cdf95a95-1d2b-4b3a-99fa-f77e3424453a.pdf"},{"id":74925995,"identity":"5bce3947-ae9a-4989-bf43-f9cc80ba6f42","added_by":"auto","created_at":"2025-01-28 11:31:11","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":2428115,"visible":true,"origin":"","legend":"","description":"","filename":"suskamsSI241212.docx","url":"https://assets-eu.researchsquare.com/files/rs-5874357/v1/a9326f2a29fb81b40d3a3ca3.docx"}],"financialInterests":"","formattedTitle":"Migration behaviour, wintering areas and conservation biology of brown skuas breeding in the subtropical Amsterdam Island","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSeabirds share their time between sea and land, with a particularly marked contrast between the breeding season \u0026ndash; during which they must regularly return on land to incubate their eggs or to feed their chicks \u0026ndash; and the non-breeding season, during which most seabirds migrate far from their colony to spend the entire period at sea. However, there is a wide difference in non-breeding strategies and movements among seabird species, with a gradient ranging from non-migratory (\u003cem\u003ee.g.\u003c/em\u003e, the resident Masked booby \u003cem\u003eSula dactylatra\u003c/em\u003e (Roy et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)) to the longest animal migration (\u003cem\u003ee.g.\u003c/em\u003e, almost 20,000 km one-way travel of the Arctic tern \u003cem\u003eSterna paradisaea\u003c/em\u003e (Alerstam et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)).\u003c/p\u003e \u003cp\u003eSeabirds are of particular conservation concern, facing both at-sea and terrestrial threats (Dias et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In addition to climate change and severe weather conditions, which can affect seabirds everywhere, threats at-sea are mainly attributable to fishing (bycatch and overfishing) and pollution, while on land the main threat to seabirds is invasive non-native species (Dias et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Invasive species (Jones et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) are of particular concern on islands, leading to the implementation of numerous eradication campaigns for the conservation of many species of seabirds (Jones et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Brooke et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Barbraud et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Nevertheless, invasive species eradication can affect other non-target species (Travers et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), generating an additional terrestrial threat to some species. To assess the threats facing populations, it is therefore important to know how individuals share their time between sea and land. In particular, understanding the non-breeding strategy of seabirds help identify whether individuals are residents or migrants and, if they migrate, when they leave and return to their colony.\u003c/p\u003e \u003cp\u003eAmsterdam Island is a remote island of the Indian Ocean, which has been identified as one of the world\u0026rsquo;s top priority islands for seabird conservation and consequently a good candidate for eradicating introduced invasive predators as a priority conservation objective (Segonzac \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e1972\u003c/span\u003e; Brooke et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2007\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This was confirmed by a recent survey of seabirds prior to eradication, which revealed the presence of 14 breeding (or probably breeding) seabird species, including eight burrowing petrels, two of which have never described on the island (the Juan-Fernandez petrel \u003cem\u003ePterodroma externa\u003c/em\u003e and the sooty shearwater \u003cem\u003eArdenna grisea;\u003c/em\u003e (Lesage et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)). A comprehensive eradication plan of invasive mammals \u0026ndash; the feral cat \u003cem\u003eFelis catus\u003c/em\u003e, the brown rat \u003cem\u003eRattus norvegicus\u003c/em\u003e and the house mouse \u003cem\u003eMus musculus\u003c/em\u003e \u0026ndash; was therefore scheduled for 2024. Based on previous impact of similar plans, managers anticipated that eradication could in particular affect the population of brown skua \u003cem\u003eStercorarius antarcticus hamiltoni\u003c/em\u003e, a top predator seabird breeding on Amsterdam island, in two ways: through either lethal effects due to secondary poisoning or by a reduction in basic prey, reducing breeding attempts and reproductive success (Travers et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The population of subtropical brown skua from Amsterdam is small (\u003cem\u003ei.e.\u003c/em\u003e, ~\u0026thinsp;80 breeding pairs; (Lesage et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)) and its taxonomic status remains unclear (Ritz et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). This tiny population therefore appears to be highly vulnerable.\u003c/p\u003e \u003cp\u003eStercoraridae (jaegers and skuas) are mainly migratory species exhibiting long-distance migration outside the breeding period (long-tailed skua \u003cem\u003eStercorarius longicaudus\u003c/em\u003e, van Bemmelen et al. (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e); Arctic skua \u003cem\u003eS. parasiticus\u003c/em\u003e, van Bemmelen et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2023\u003c/span\u003e ; brown skua \u003cem\u003eStercorarius antarcticus lonnbergi\u003c/em\u003e, (Schultz et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Southern species of skuas display a gradient in migratory strategies and distance travelled from their breeding colony. The south polar skua \u003cem\u003eStercorarius maccormicki\u003c/em\u003e is known to be a long-distance trans-equatorial migrant (Kopp et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Weimerskirch et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), while brown skuas remain in the Southern Hemisphere, exhibiting differences in strategies among populations, over a continuum from subantarctic to tropical waters (Krietsch et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Delord et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Higher latitude populations of brown skuas migrate longer distances than temperate ones (Schultz et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, the migratory behaviour of brown skuas on Amsterdam Island, its most northerly breeding site, remains unknown. In particular, it is unknown whether all the individuals are migratory or whether some individuals remain on the island year-round (with consequences for the risk of secondary poisoning during the eradication campaign) and what their migratory schedule is (\u003cem\u003ei.e.\u003c/em\u003e, when birds are absent from the island, and therefore when the risk of secondary poisoning is the lowest). In addition, any information on the year-round distribution, activity and migratory connectivity with other populations of brown skuas could be useful to managers, to help alleviate other threats to the species, in this context of potential detrimental effects of the planned invasive species eradication program (Runge et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe aim of the study was therefore to: a) describe the migratory strategies of the birds, and in particular, to estimate whether all birds are migratory, b) describe the migratory schedule of migrant birds to recommend an optimal period for scheduling land operations for eradicating invasive non-native species (to minimise the risk of detrimental effects on skuas), and c) to take advantage of the collected data to describe migratory movements and activity patterns during migration, and evaluate the level of individual variability in these patterns.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy site\u003c/h2\u003e \u003cp\u003eField work was conducted on Amsterdam Island (37\u0026deg; 50\u0026rsquo; S; 77\u0026deg; 33\u0026rsquo; E) in the subtropical part of the southern Indian Ocean (Belkin and Gordon \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) in a mild, oceanic climate. The volcanic island consists of a mountainous 500\u0026ndash;800 m plateau \u0026lsquo;Plateau des Tourbi\u0026egrave;res\u0026rsquo; with cliffs on the western edge. Non-native invasive mammal species \u0026ndash; house mice \u003cem\u003eMus musculus\u003c/em\u003e, brown rats \u003cem\u003eRattus norvegicu\u003c/em\u003es and feral cats \u003cem\u003eFelis catus\u003c/em\u003e \u0026ndash; occur throughout the island (Micol and Jouventin \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). Amsterdam has been identified as of high conservation priority due to its seabird populations (Segonzac \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e1972\u003c/span\u003e; Brooke et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2007\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Lesage et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), including three endangered species: the Indian yellow-nosed albatross \u003cem\u003eThalassarche carteri\u003c/em\u003e, the sooty albatross \u003cem\u003ePhoebetria fusca\u003c/em\u003e and the northern rockhopper penguin \u003cem\u003eEudyptes moseleyi\u003c/em\u003e, along with the endemic, endangered Amsterdam albatross \u003cem\u003eDiomedea amsterdamensis\u003c/em\u003e (due to a very small population of 300\u0026ndash;350 individuals; Barbraud et al. unpublished data). The central plateau provides nesting habitat for subtropical brown skuas (~\u0026thinsp;80 pairs, TAAF KIORE Services 2022).\u003c/p\u003e \u003cp\u003eOn Amsterdam Island, an eradication campaign of invasive mammals has just been completed (first half-year 2024), as part of the RECI (Restauration des Ecosyst\u0026egrave;mes Insulaires de l\u0026rsquo;Oc\u0026eacute;an Indien, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://taaf.fr/missions-et-activites/protection-de-lenvironnement/actions-de-terrain-et-programmes-menes/projet-reci/\u003c/span\u003e\u003cspan address=\"https://taaf.fr/missions-et-activites/protection-de-lenvironnement/actions-de-terrain-et-programmes-menes/projet-reci/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), a project funded by the European Union, the French Development Agency (AFD) and the French Southern and Antarctic Territories administration (TAAF). Eradication of the three invasive mammals\u0026rsquo; species is included in the National Plan of Actions to improve the conservation status of the Amsterdam albatross (2018\u0026ndash;2027). The types of methods considered for the eradication campaigns are divided into: 1) feral cats -using trapping and shooting and, 2) rats and house mouse - using chemical rodenticide containing brodifacoum. The aerial helicopter spraying strategy consisted of two applications of rodenticide over the entire island. Aerial spraying was supplemented by manual ground spraying in specific areas around infrastructures during the same period. The optimal period for scheduling land operations for eradicating introduced species to minimize detrimental effects on seabirds was estimated to be from May to July, i.e. the period with the smaller proportion of breeding seabird populations present on land. Following this conservation recommendation and due to different constraints (meteorology, logistic, feasibility ...etc), the campaign was scheduled during the austral winter 2024 (from the end of May to the end of July).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy species and field methods\u003c/h3\u003e\n\u003cp\u003eThe brown skua generally breeds in loose colonies and is highly territorial during breeding, with strong breeding site tenacity and mate fidelity (Furness \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1987\u003c/span\u003e). The brown skua is an annual breeder, usually laying two eggs in late October-early November, with hatching in late November-early December, and chick fledging\u0026thinsp;~\u0026thinsp;50 days later in early January (Hahn \u0026amp; Peter \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). The post-reproduction period runs from February to November (hereafter non-breeding).\u003c/p\u003e \u003cp\u003eBrown skuas in Amsterdam Island were monitored punctually (during late 1990\u0026rsquo;s) and annually since 2018, with all individuals within the monitoring colony individually marked (numbered stainless steel and plastic engraved colour bands; see (Pacoureau et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Breeding adults were captured and global location sensing (GLS) loggers were deployed in December 2018. GLS loggers are archival light-recording loggers used to study distribution and activity of birds over periods lasting up to ~\u0026thinsp;2 years, by recording ambient light level every 10 min, from which local sunrise and sunset hours can be inferred to estimate location every 12 h (Wilson et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). GLS loggers also recorded saltwater immersion data at regular 10-min intervals, by testing for saltwater immersion every 3 s and storing the proportion of positive samples (time in seawater) at the end of each 10-min period. Saltwater immersion data were used to estimate daily activity budgets, as time immersed can be interpreted as time sitting on the water, and time dry can be interpreted as time flying and/or time on land. Despite their high mean spatial error of location estimates (over 100 km; (Phillips et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), GLS loggers can track birds for prolonged periods of time with minimal disturbance. Twenty-one of the 28 GLS loggers deployed were retrieved.\u003c/p\u003e\n\u003ch3\u003eMolecular sexing\u003c/h3\u003e\n\u003cp\u003eA DNA extraction was conducted with 2 \u0026micro;l of blood cells using a chelex resin (Chelex 100 Molecular Biology Resin, BIO-RAD; 10%) associated with Proteinase K. Then, a PCR with amplification of the CHD gene was performed following a standard procedure (Fridolfsson and Ellegren \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1999\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eStable isotopes\u003c/h3\u003e\n\u003cp\u003eFollowing (Jaeger et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), carbon and nitrogen stable isotopes values (\u003cem\u003eδ\u003c/em\u003e\u003csup\u003e13\u003c/sup\u003eC and \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e15\u003c/sup\u003eN, respectively) were measured on four different fully-grown body feathers from the lower back per bird. They were collected upon recapture of each individual bird, thus corresponding to the previous moulting period at sea recorded by the GLS. In seabirds, including skuas, feather isotope values represent the foraging habitat (\u003cem\u003eδ\u003c/em\u003e\u003csup\u003e13\u003c/sup\u003eC) and diet/trophic position (\u003cem\u003eδ\u003c/em\u003e\u003csup\u003e15\u003c/sup\u003eN) during the non-breeding period because adult birds replace their plumage at that time (Higgins and Davies \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Cherel et al. 2008; but see Gra\u0026ntilde;a Grilli and Cherel (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)). To facilitate interpretation of adult isotopic values, feathers were also collected from large chicks as control birds reflecting the skua diet during the summer breeding period. For each chick, a single body feather was used for isotopic analyzes, because chick feathers grow almost synchronously and thus present low inter-feather \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e13\u003c/sup\u003eC and \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e15\u003c/sup\u003eN variations (Carravieri et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Feather preparation and isotopic analyses were detailed by (Jaeger et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). In brief, feathers were cleaned using a 2:1 chloroform: methanol solution and then oven dried for 48 hr at 50\u0026deg;C. Every single whole body feather was homogenized by cutting it with stainless steel scissors into tiny fragments and a subsample of ~\u0026thinsp;0.3 mg was packed into tin containers for stable isotope analysis. The relative abundance of carbon and nitrogen isotopes were determined with a continuous flow mass spectrometer (Thermo Scientific Delta V Plus) coupled to an elemental analyzer (Thermo Scientific Flash 2000). Results are presented in the usual d notation relative to Vienna PeeDee Belemnite and atmospheric N\u003csub\u003e2\u003c/sub\u003e for \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e13\u003c/sup\u003eC and \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e15\u003c/sup\u003eN, respectively. Replicate measurements of reference materials (USGS-61 and USGS-63) indicated measurement errors\u0026thinsp;\u0026lt;\u0026thinsp;0.10\u0026permil; for both \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e13\u003c/sup\u003eC and \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e15\u003c/sup\u003eN values.\u003c/p\u003e \u003cp\u003eFor statistical analyses, feather \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e13\u003c/sup\u003eC and \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e15\u003c/sup\u003eN values were either grouped at the individual level (wintering zones) or at the feather level (moulting zone) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In the former analysis, isotopic values of the four feathers per bird were assigned to oceanic zones according to their \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e13\u003c/sup\u003eC values (tropical, subtropical and subantarctic) according to (Jaeger et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In the latter analysis, each single body feather was tentatively assigned to a moulting zone (Weimerskirch et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The GLS tracks of birds that wintered in only one marine area were used to assign the corresponding feather isotope values to that area. The feather isotope values of skuas that spent the non-breeding period in more than one area were then carefully examined to correctly assign the isotopic values. Isotopic values could not reliably be assigned to a wintering area for four feathers using the described 2-step protocol (see \u0026lsquo;Unknown\u0026rsquo; in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFeather isotopic values of brown skuas according to individual wintering zones and to feather moulting zones (see text). Note that birds may moult in several different zones. Within wintering or moulting zones, values sharing the same superscript letters are not significantly different at the 0.05 level (see text). Values are means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWintering areas and habitats\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividuals\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBody feathers\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFeather δ\u003csup\u003e13\u003c/sup\u003eC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFeather δ\u003csup\u003e15\u003c/sup\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eC\u0026nbsp;: N mass\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026permil;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(\u0026permil;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eratio\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWintering zones\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTropical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-15.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubtropical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-17.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubantarctic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-19.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChicks (Amsterdam)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-16.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoulting zones\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth-west of Australia (tropical)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-15.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmsterdam (subtropical)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-16.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003csup\u003eb,c\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEast of Amsterdam (subtropical)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-17.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003csup\u003eb,c,d\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth of Australia (subtropical)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-17.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003csup\u003eb,c\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth of Amsterdam (subantarctic)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-20.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndividual DZ20236 (subantarctic)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-19.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChicks (Amsterdam)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-16.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003csup\u003eb,c\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eAnalytical methods\u003c/h3\u003e\n\u003cp\u003eIndividual locations were estimated using the probGLS package in R (Merkel et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). To improve the estimates, the daily median sea surface temperature SST recorded by GLS loggers was matched to satellite-derived SST (0.25\u0026deg; \u0026times; 0.25\u0026deg;, NOAA OI SST V2 High- Resolution Dataset; (Merkel et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)).\u003c/p\u003e \u003cp\u003eMigration timing (departure/arrival dates from/at the colony/non-breeding grounds, and migration duration) was inferred by combining visual inspection of each track (\u003cem\u003ei.e.\u003c/em\u003e, longitudinal directional movement during three consecutive days) and of activity data (\u003cem\u003ei.e.\u003c/em\u003e, periods of no saltwater immersion) (Figures \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e \u0026amp; S2). Arrival at the non-breeding grounds was detected when movement stopped being directional, and arrival back at the colony was detected when rapid movement was followed by several days of no salt water immersion. The duration of the non-breeding period was calculated as the interval between departure and colony return, and the duration of outward and inward migrations as the interval between the initiation and end of migratory movements. For each individual, maximum distance from the breeding colony was calculated using the trip package in R (Sumner \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The spatial distribution of brown skuas was visualised using Gaussian kernel analysis with a cell size of 2\u0026deg; x 2\u0026deg; and a fixed smoothing parameter (h) of 2\u0026deg;, using the \u0026lsquo;adehabitatHR\u0026rsquo; package in R (Calenge \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Both h value and grid cell size were based on the mean accuracy of the devices (Phillips et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFive metrics describing daily activity were calculated: (1) daily \u003cem\u003etime spent on water\u003c/em\u003e (sum of time spent immersed in each 10-min blocks in a day, to obtain hours in the water per day), (2) daily average \u003cem\u003ewet bouts duration\u003c/em\u003e (duration of uninterrupted sequences of 10-min blocks of immersion data\u0026thinsp;=\u0026thinsp;200, \u003cem\u003ei.e.\u003c/em\u003e, time spent totally immersed), (3) daily average \u003cem\u003edry bouts duration\u003c/em\u003e (duration of uninterrupted sequences of 10-min blocks of immersion data\u0026thinsp;=\u0026thinsp;0), (4) daily \u003cem\u003enumber of wet bouts\u003c/em\u003e, and (5) daily \u003cem\u003enumber of dry bouts\u003c/em\u003e. Although the loggers integrated activity within each 10-min block and so did not provide the exact timing of landings and take-offs, (Phalan et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) found for comparative purposes that bouts defined as a continuous sequence of 0 values for flight (dry) and a sequence of values of 1 or greater for wet bouts, were suitable proxies for activity. Unless stated otherwise, whenever GLS loggers contained data for two consecutive years, only the first year of data was used.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eDifferences between sexes in timing of non-breeding movements were tested using Wilcoxon rank tests (only one trip per individual). To assess how activity varied over time, sex and among individuals principal components analysis (PCA built with the \u0026lsquo;PCA\u0026rsquo; function, FactoMineR package L\u0026ecirc; et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) was first run over the five daily wet/dry activity metrics to circumvent collinearity issues and to avoid redundancy. The first three principal components explained 82.1% of the total variance (1st axe: 41.7%, 2nd axe: 20.6% and 3rd axe: 19.8%). The detailed results of PCA, the variables and their loadings for each axis are summarised in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Differences in the three principal components between sexes and months were tested using Kruskal-Wallis tests followed by Dunn\u0026rsquo;s tests to identify which groups were different (Tomczak and Tomczak \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Only data for the months of April to August (the 5 months available for all individuals) were used in the analyses. Spatial and statistical analyses were performed using R (R Core Team \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Results are presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD unless otherwise indicated.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of principal components analyses (PCA) on six wet/dry metrics on brown skuas.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrincipal components\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal variance explained (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTime spent on water\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDry bouts duration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDry bouts number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWet bouts duration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWet bouts number\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirst\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e+ (r\u0026thinsp;=\u0026thinsp;0.91)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e- (r = -0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+ (r\u0026thinsp;=\u0026thinsp;0.88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecond\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e- (r = -0.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+ (r\u0026thinsp;=\u0026thinsp;0.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e1\u003c/sup\u003e the symbol used gives the sign of the correlation (+: positive, -: negative); the number in brackets indicates the value of the correlation coefficient r\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eAt the end of the breeding period, most birds dispersed widely, undertaking long-distance migrations, and spent the non-breeding season in the eastern part of the Indian Ocean up to the Tasman Sea (~\u0026thinsp;7500 km from the breeding ground) exhibiting high inter-individual variability in area and distance reached from the colony (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Individuals arrived at their non-breeding site between late February/early May and left between late July/late September (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). On average, tracked individuals were away from the breeding colony for 154\u0026thinsp;\u0026plusmn;\u0026thinsp;37 d, at a mean maximum distance to the colony of 3519\u0026thinsp;\u0026plusmn;\u0026thinsp;2042 km (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Females and males did not differ in duration or distance reached during the non-breeding period. The factors driving differences in migratory strategy remained unclear with no evidence of sex difference in non-breeding movement metrics and a limitation due to the small sample sizes. A small proportion of the tracked skuas (~\u0026thinsp;10%, n\u0026thinsp;=\u0026thinsp;2) could be considered as resident on the island (\u0026ldquo;terrestrial\u0026rdquo; individuals) throughout the year on the basis of a combination of movement and activity patterns (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTiming of non-breeding movements of brown skuas from Amsterdam Island, which were tracked using GLS loggers in 2018\u0026ndash;2019. For each parameter, values sharing the same superscript letter (a, b; Wilcoxon test) are not statistically significantly different. Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (minimum \u0026ndash; maximum).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eNon-breeding movements\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eDuration (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMaximum distance to the colony (km)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e160\u0026thinsp;\u0026plusmn;\u0026thinsp;31 (91\u0026ndash;192) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3695\u0026thinsp;\u0026plusmn;\u0026thinsp;1979 (462\u0026ndash;6317) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e145\u0026thinsp;\u0026plusmn;\u0026thinsp;42 (61\u0026ndash;199) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3232\u0026thinsp;\u0026plusmn;\u0026thinsp;2108 (730\u0026ndash;7529) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e154\u0026thinsp;\u0026plusmn;\u0026thinsp;37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3519\u0026thinsp;\u0026plusmn;\u0026thinsp;2042\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe migratory skuas ranged mainly between tropical and subtropical waters and punctually in subantarctic waters (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u0026amp; S4). Individuals were predominantly distributed in subtropical waters (76\u0026thinsp;\u0026plusmn;\u0026thinsp;18.2% of locations; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), followed by subantarctic waters (23.6\u0026thinsp;\u0026plusmn;\u0026thinsp;18.3%) and, very occasionally, Antarctic waters (0.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8%). Only 29% of individuals (n\u0026thinsp;=\u0026thinsp;6) visited Antarctic waters, spending less than 3% of their locations there. The sea surface temperature recorded by geolocators varied between 18.0\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1\u0026deg;C (min: 7\u0026deg;C, max: 37\u0026deg;C) in May to 11.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7\u0026deg;C in August (min: 3\u0026deg;C, max: 32\u0026deg;C). Females and males occupied similar areas and habitats during the non-breeding period (15.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.2\u0026deg;C and 14.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8\u0026deg;C, respectively).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSeven birds were tracked for two consecutive years, out of which only one changed its migratory strategy, being resident the first year and migrating the following year (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOver the non-breeding period, individuals were partly away from the breeding grounds during March to August, with a proportion of the tracked birds that were at sea varying from 43 to 90%. Apart from the two resident individuals that did not migrate and were considered to remain on the island, the migration schedule permitted to identify the period from May to July as the period when the proportion of the breeding population on land is the lowest (\u0026lt;\u0026thinsp;15% of the tracked birds).\u003c/p\u003e \u003cp\u003eOnly three individuals (from two breeding pairs) bred successfully during the season of deployment (failure for the other birds occurred at chick-rearing stage). The rate of breeding failure among tracked individuals was comparable to the high rate observed within the monitoring colony (86.7% \u003cem\u003eversus\u003c/em\u003e 79.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.0%, calculated as the 1-percentage of nests with eggs that have had one chick or more over the period 2019 to 2024, n\u0026thinsp;=\u0026thinsp;22 nests).\u003c/p\u003e\n\u003ch3\u003eActivity characteristics\u003c/h3\u003e\n\u003cp\u003eFemales tended to spend more time on water daily (higher percentage of time wet, longer and more numerous wet bouts) compared to males (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eValues of brown skua activity parameters (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) recorded using Global Location Sensor (GLS), separated by sex.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemales (n\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMales (n\u0026thinsp;=\u0026thinsp;8)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAll (n\u0026thinsp;=\u0026thinsp;21)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime spent on water (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e73\u0026thinsp;\u0026plusmn;\u0026thinsp;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e64\u0026thinsp;\u0026plusmn;\u0026thinsp;34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e69\u0026thinsp;\u0026plusmn;\u0026thinsp;32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWet bouts (sitting on water) duration (h)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1.0\u0026thinsp;\u0026plusmn;\u0026thinsp;9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.89\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDry bouts duration (h)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.5\u0026thinsp;\u0026plusmn;\u0026thinsp;13.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;10.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWet bouts (sitting on water) number\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e15.4\u0026thinsp;\u0026plusmn;\u0026thinsp;8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e14.8\u0026thinsp;\u0026plusmn;\u0026thinsp;9.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e15.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDry bouts number\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e3.3\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e3.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eComponent loadings indicated (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) that the first axis integrated the duration of dry bouts (loading = -0.68) and the percentage of time spent wet and the number of wet bouts (loading\u0026thinsp;=\u0026thinsp;0.91 and 0.88, respectively). The second and third axis integrated the number of dry bouts and the duration of wet bouts (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Brown skuas differed in the daily activity parameters by month and sex whatever the synthetic activity variables considered (1st and 2nd axes, Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Males and females did not differ in the values of the first axis, except in August when females tended to have longer dry bouts than males (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Females also tended to exhibit higher percentage of time spent on water at the beginning of the period and longer dry bouts at the end (a moderate effect of the month on the first axis was detected; eta2[H]\u0026thinsp;=\u0026thinsp;0.063, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). Dry bouts duration appeared to be particularly longer in August. Furthermore, females tended to exhibit a higher number of dry bouts in August (compared to May; a small effect of the month on the second axis was detected; eta2[H]\u0026thinsp;=\u0026thinsp;0.007, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). There were no differences for males for the first axis from month to month, except at the end of the period (August) when individuals had longer dry bouts (a moderate effect of the month was detected; eta2[H]\u0026thinsp;=\u0026thinsp;0.061, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). Males exhibited longer wet bouts during April compared with all other month in the period (weak effect of month on the second axis detected; eta2[H]\u0026thinsp;=\u0026thinsp;0.058, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIndividuals differed in their activity characteristics (synthetic activity variables; Figures S3 \u0026amp; S5). In particular, the first principal component permitted to clearly discriminate resident individuals, that exhibited longer dry bouts (large effect size detected, eta2[H]\u0026thinsp;=\u0026thinsp;0.3; Figures S3a \u0026amp; S5). These two individuals (a female DZ20234-B4100 and a male DZ28805-B4123) were resident all year long. Although the values of the second axis varied significantly between individuals (large effect size detected, eta2[H]\u0026thinsp;=\u0026thinsp;0.182), this did not seem to be linked to whether individuals were migrants or residents. However, individuals differed, with some displaying longer wet bouts and others a higher number of dry bouts. There were therefore differences in the behaviour of individuals beyond migrating or not.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStable isotopes\u003c/h2\u003e \u003cp\u003eBody feathers were collected from 20 adult skuas (out of 21 individuals) that carried a GLS. Feather isotopic values of adult brown skuas from Amsterdam Island ranged widely, from \u0026minus;\u0026thinsp;21.0 to -15.4\u0026permil; (a 5.6\u0026permil; difference), and from 8.1 to 19.0\u0026permil; (10.9\u0026permil;) for \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e13\u003c/sup\u003eC and \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e15\u003c/sup\u003eN values, respectively. Feather \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e13\u003c/sup\u003eC values indicated wintering in the tropical, subtropical and subantarctic zones, but not further South, in the Antarctic Zone. Some birds showed low intra-individual variations in isotopic values of their four feathers, while large SD indicated that other individuals wintered over different water masses.\u003c/p\u003e \u003cp\u003eCombining GLS data and isotopic values at the feather level depicted an informative pattern (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Feather \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e13\u003c/sup\u003eC and \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e15\u003c/sup\u003eN values from different moulting zones were significantly different (Kruskal-Wallis: \u003cem\u003eH\u003c/em\u003e\u0026thinsp;=\u0026thinsp;51.1 and 39.7 for \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e13\u003c/sup\u003eC and \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e15\u003c/sup\u003eN, respectively, both \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Post-hoc pairwise Conover-Inman tests documented three notable features (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e): (i) feather \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e13\u003c/sup\u003eC values overall increased with decreasing latitudes, from the lower values of feathers that were moulted south of Amsterdam Island (-20.1\u0026permil;) to the higher \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e13\u003c/sup\u003eC values of adults that moulted in tropical waters in north-west Australia (-15.9\u0026permil;); (ii) feather isotopic values were identical for chicks and adults that moulted in the subtropics, whatever the moulting grounds (Amsterdam, east of Amsterdam and south of Australia, from western Australia to the Tasman Sea); (iii) one individual (ring number DZ20236) synthesized its four body feathers in subantarctic waters (-19.1\u0026permil;), where it presented remarkable low \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e15\u003c/sup\u003eN values (8.5\u0026permil;) that differed from all the other groups (13.0\u0026ndash;16.0\u0026permil;).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study described the non-breeding movements of the most northerly breeding population of brown skuas, from the temperate Amsterdam Island in the southern Indian Ocean. Their latitudinal at-sea distribution outside of the breeding season was comparable to that of the subantarctic populations of the Crozet and Kerguelen archipelagos ((Delord et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e); Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) in the southern Indian Ocean, but also from subantarctic islands in the southern Atlantic Ocean (Bird Island and King George Island; (Phillips et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Carneiro et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Krietsch et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)) and from a temperate island in the southern Pacific Ocean (Chatham Island; (Schultz et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)). The birds targeted distant areas distributed over neritic and oceanic waters of subantarctic, subtropical and tropical biomes. These targeted habitats were consistently found in other studies in the Indian Ocean (Delord et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), but also in other ocean basins, as evidenced by stable isotopes (Mills et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDuring the non-breeding season, brown skuas from Amsterdam Island were completely segregated from populations from other ocean basins (southern Atlantic Ocean (Phillips et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Carneiro et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Krietsch et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e); southern Pacific Ocean (Schultz et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)). In contrast, they shared non-breeding grounds with other populations of the southern Indian Ocean: the Amsterdam Island area, along the Southeast Indian Ridge in the Eastern Indian Ocean and the waters off Australia (three main sectors: Tasmania, Indian Ocean Coast / Tropic of Capricorn and Great Australian Bight) (Delord et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e); Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Additionally, they shared non-breeding areas at sea with different populations of south polar skua \u003cem\u003eStercorarius maccormicki\u003c/em\u003e (Weimerskirch et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBrown skuas from Amsterdam Island showed high levels of inter-individual variability in migratory behaviour. Such inter-individual variability was previously evidenced at inter-population and intra-population levels in several species of jaegers and skuas (Long-tailed skua \u003cem\u003eStercorarius longicaudus\u003c/em\u003e (van Bemmelen et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e); Arctic skua \u003cem\u003eS. parasiticus\u003c/em\u003e: van Bemmelen et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2023\u003c/span\u003e ; brown skua \u003cem\u003eStercorarius antarcticus lonnbergi\u003c/em\u003e: (Krietsch et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Schultz et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2018\u003c/span\u003e); Falkland skua \u003cem\u003eS. a. antarctica\u003c/em\u003e (Phillips et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2007\u003c/span\u003e); south polar skua \u003cem\u003eS. maccormicki\u003c/em\u003e: (Kopp et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Weimerskirch et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). However, the population from Amsterdam Island appeared to be the only one to have resident birds, albeit in small numbers. This is likely related with the fact that Amsterdam Island hosts the most northerly population of the species in subtropical waters, where most individuals from various localities winter. Even for the only other temperate population of brown skuas (from the Chatham Islands that are located at the Subtropical Front), all birds were migratory. Although individuals exhibited the smallest spatiotemporal scale in non-breeding movement compared to subantarctic and Antarctic populations (ranges away from the colony: Crozet \u0026amp; Kerguelen Islands 4000 km, (Delord et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), Bird Island 1500\u0026ndash;2700 km, (Carneiro et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), King George Island 1700\u0026ndash;2500 km, (Krietsch et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), South East Island-Chatham 1500 km, (Schultz et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)).\u003c/p\u003e \u003cp\u003eOur study provides some insight into the intra-individual variability in migratory strategies of brown skuas from Amsterdam Island. Even though only seven individuals were tracked for two consecutive years, their strategies appeared nevertheless consistent across years (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Such inter-annual consistency has been found for the species at the population level in South Georgia (Carneiro et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and at the individual level in King George Island (Krietsch et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). However, in our study, one bird changed from being resident during the first non-breeding season to being a migrant during the next; Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Such flexibility in non-breeding movements was evidenced for long-tailed skuas (van Bemmelen et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Nonetheless, our data did not permit us to estimate to what extent migratory birds might shift from a migratory to a resident strategy in response to environmental conditions.\u003c/p\u003e \u003cp\u003eAs previously found in brown skuas from the Kerguelen Islands (Delord et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), the \u003cem\u003eδ\u003c/em\u003e \u003csup\u003e13\u003c/sup\u003eC values of Amsterdam skuas correspond well to the latitudinal \u003cem\u003eδ\u003c/em\u003e \u003csup\u003e13\u003c/sup\u003eC gradient of Southern Ocean water masses (Cherel and Hobson \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), with \u003cem\u003eδ\u003c/em\u003e \u003csup\u003e13\u003c/sup\u003eC values of feathers that were synthesized in subantarctic waters (n\u0026thinsp;=\u0026thinsp;13, -19.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u0026permil;) and tropical waters (n\u0026thinsp;=\u0026thinsp;15, -15.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u0026permil;) being lower and higher, respectively, than values of subtropical feathers (n\u0026thinsp;=\u0026thinsp;52, -17.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u0026permil;). In agreement with wintering areas primarily located in the subtropics, feather \u003cem\u003eδ\u003c/em\u003e \u003csup\u003e13\u003c/sup\u003eC values indicated that most body feathers were synthesized in subtropical waters. This precludes using \u003cem\u003eδ\u003c/em\u003e \u003csup\u003e13\u003c/sup\u003eC values to differentiate between feathers that grew on the breeding and wintering grounds, as they did not present obvious isotopic differences. Feather \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e15\u003c/sup\u003eN values are difficult to interpret, because \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e15\u003c/sup\u003eN baselines vary in different water masses, thus obscuring the trophic interpretation of \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e15\u003c/sup\u003eN. However, the low \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e15\u003c/sup\u003eN values (8.1-9.0\u0026permil;) of the four body feathers of the individual DZ20236 are puzzling. Such low \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e15\u003c/sup\u003eN values were previously found in many feathers of brown skuas from the Kerguelen Islands (Delord et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and in a few feathers of South polar skuas (Weimerskirch et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), when they forage at similar latitudes in the southern Indian Ocean. This suggests that skuas fed on low trophic level prey in the area, but this remains to be confirmed. A comparison of the skua \u003cem\u003eδ\u003c/em\u003e\u003csup\u003e15\u003c/sup\u003eN values with those of other subantarctic and subtropical organisms suggests that the unknown prey was not marine mammals, seabirds, cephalopods or fish, but instead macrozooplankton, probably crustaceans (Cherel et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2008b\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Stowasser et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2012\u003c/span\u003e); this hypothesis needs to be thoroughly investigated.\u003c/p\u003e \u003cp\u003eWe found sex differences in activity metrics, as in the population from King Georges Island (Krietsch et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). These behavioural differences are probably linked to the reversed sexual size dimorphism in brown skuas (Phillips et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). However, contrary to other populations (Krietsch et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), females from Amsterdam island tended to spend on average more time on water and to make longer wet bouts than males. This could result from a difference in migratory strategy, males maybe staging at sea for shorter periods of time than females and/or they possibly forage more on terrestrial prey. Such a sex-related behaviour merits further investigation in relation to the diet, which is poorly known at Amsterdam Island (Carravieri et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Renedo et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In general, the factors driving differences in migratory behaviour (inter-annual, inter-individual, sexual, etc.) are not entirely clear and require further study. Nevertheless, it is likely that different strategies lead to varying ecological and anthropogenic pressures across populations, which underscores the importance of considering such variability in future conservation planning and management (Carravieri et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA thorough understanding of the distribution and movements of brown skuas from Amsterdam Island will contribute to a better understanding of epizootic pathways (Gorta et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Brown skuas were already identified as spreaders of the pathogen of avian cholera (\u003cem\u003ePasteurella multocida\u003c/em\u003e; (Bourret et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Jaeger et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) with conservation issues for the seabird community of the island (Brooke et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Lamb et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Furthermore, in a context of severe and widespread impacts of high-pathogenicity avian influenza virus (HPAIV H5N1) on wild animals (Klaassen and Wille \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) with ongoing spread in the southern Hemisphere (Leguia et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Bennet et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Bennison et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), monitoring the movements of brown skuas is of increasing conservation and public health relevance.\u003c/p\u003e \u003cp\u003eFinally, our results helped identify the optimal period for scheduling the first phase of land operations for eradicating introduced species on Amsterdam Island. The period of lower detrimental effect on skuas based on our results appeared to be from May to July, given that this was the period with the smallest proportion of the breeding population present on land. Following this conservation recommendation and considering other constraints (meteorology, logistic, feasibility, etc.), the campaign was scheduled from May to July 2024. The observed pre-eradication breeding failure was ~\u0026thinsp;87% at Amsterdam Island and very high compared to other breeding sites (\u003cem\u003ee.g.\u003c/em\u003e, ~\u0026thinsp;16% (95% CI: 12%-22%) in the Kerguelen archipelago; (Goutte et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014\u003c/span\u003e)), so although detrimental effects of the eradication campaign are to be feared, beneficial effects can be expected if eradication is successful, through a) an increase in reproductive success in the short term, and b) an increase in the population size of prey species in the medium term. However, mid- and long-term post-eradication surveys will be needed to confirm the potential positive effects of eradication of invasive non-native species on seabirds and the benefits for conservation purposes (for a review: Phillipe-Lesaffre et al. 2022). Genetic investigations are underway to elucidate the status of the Amsterdam Island population, and chances are that it is an evolutionary unit distinct from other populations in the southern Indian Ocean (i.e. Crozet Is. and Kerguelen Islands, Viricel et al. unpubl. data).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eThe authors thank fieldworkers involved in the monitoring program, namely J\u0026eacute;r\u0026eacute;my Dechartre, Anthony Le Nozahic, Anthony Buttet, Marie Fretin, Augustin Clessin, and J\u0026eacute;r\u0026eacute;my Tornos. They also thank the ECOPATH project n\u0026deg;1151 (French Polar Institute IPEV, PI T. Boulinier) for their support in the field and\u0026nbsp;the \u0026ldquo;Plateforme d\u0026rsquo;Analyses El\u0026eacute;mentaires\u0026rdquo; (LIENSs, La Rochelle) for stable isotope analysis. We are grateful to Benjamin Dupuis, David Pinaud and Samuel Peroteau for their advice on spatial data. We are indebted to Fabrice Le Bouard for operational details of the eradication campaign of invasive mammals on the Amsterdam Is., as part of the RECI-eradication program. We acknowledge Dominique Joubert for the management of the demographic CEBC French Southern Seabirds database. PB is an honorary member of the IUF (Institut Universitaire de France).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunding\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis monitoring program was supported financially and logistically by the French Polar Institute IPEV (project 109, PI C. Barbraud/H. Weimerskirch), the Zone Atelier Antarctique (CNRS-INEE), Terres Australes et Antarctiques Fran\u0026ccedil;aises. The Comit\u0026eacute; de l\u0026rsquo;Environnement Polaire and the Ministry of Research Ethics Committee approved protocols and activities undertaken in this program. The study is a part of the long-term Studies in Ecology and Evolution (SEE-Life) program of the CNRS (C. Barbraud).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e. ASBL and KD are joint first authors. Study design: KD, CB and YC. Data analysis and processing: KD, ASBL, YC, CR, GG. KD, ASBL, CB and YC wrote the text and all authors edited and revised the manuscript, gave final approval for publication and agreed to be held accountable for the content therein.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e The data used in the present article will be provided for open access as supplementary.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e The custom code used in the present article will be provided for open access as supplementary.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eCompliance with ethical standards\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u0026nbsp;\u003c/strong\u003eThe Ethics Committee of French Polar Institute-IPEV and the Comit\u0026eacute; Environnement Polaire approved the field procedures for the French Southern Territories.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e All authors have agreed to participate in the study and its writing in the form of an article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e All authors have given their consent for the article to be submitted to Marine Biology.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlerstam T, B\u0026auml;ckman J, Gr\u0026ouml;nroos J, Olofsson P, Strandberg R (2019) Hypotheses and tracking results about the longest migration: The case of the arctic tern. 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Ocean-scale variation in migration schedules of a long-distance migratory seabird is fully compensated upon return to the breeding site. bioRxiv, 2023-05 preprint doi: https://doi.org/10.1101/2023.05.27.542544\u003c/li\u003e\n\u003cli\u003eWeimerskirch H, Tarroux A, Chastel O, Delord K, Cherel Y, Descamps S (2015) Population-specific wintering distributions of adult south polar skuas over the three oceans. Marine Ecology-Progress Series 538:229\u0026ndash;237\u003c/li\u003e\n\u003cli\u003eWilson RP, Ducamp JJ, Rees G, Culik BM, Niekamp K (1992) Estimation of location: global coverage using light intensity. In: Priede IMSS (ed). Ellis Horward, Chichester, pp 131\u0026ndash;134\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"marine-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mabi","sideBox":"Learn more about [Marine Biology](https://www.springer.com/journal/227)","snPcode":"227","submissionUrl":"https://submission.nature.com/new-submission/227/3","title":"Marine Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"inter-breeding strategy, geolocator loggers, activity patterns, Stercorarius antarcticus hamiltoni","lastPublishedDoi":"10.21203/rs.3.rs-5874357/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5874357/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eInvasive non-native species are a major threat to seabirds, leading to the implementation of numerous eradication campaigns. However, eradication can also affect non-targeted species. There are concerns over the fact that the invasive mammal eradication using poisonous bait planned on Amsterdam Island might affect negatively the local population of subtropical brown skuas \u003cem\u003eStercorarius antarcticus hamiltoni\u003c/em\u003e. Here, movements of 21 adult brown skuas breeding at Amsterdam Island, southern Indian Ocean, its most northerly breeding site were studied during the non-breeding period using geolocation, in order to provide relevant information for conservation prior to the eradication program. Post-breeding movements of brown skuas vary considerably, ranging from residency on the breeding grounds to long-range migrations to reach distant northern non-breeding zones in the Southern Hemisphere. Most individuals remained in the Indian Ocean (with the exception of one that wintered in the Tasman Sea), targeting areas along a continuum from the subantarctic to the tropics. Wintering grounds were generally situated in productive dynamic upwelling waters or frontal systems, with brown skuas avoiding the less productive area of the South Subtropical Gyre in the Central Indian Ocean. Inter-individual differences were not fully explained by sex: if males and females exhibited differences in activity metrics, they did not differ in duration or distance reached during the non-breeding period. Feather isotopic values confirmed that the birds mainly moulted their body feathers in the wintering area. The low δ\u003csup\u003e15\u003c/sup\u003eN values of feathers grown in mixed subtropical-subantarctic waters suggest that skuas feed on low trophic level prey in these areas. Overall, our results provided relevant information for conservation, and in particular helped identify the optimal period for scheduling land-based operations for eradicating introduced species on Amsterdam Island.\u003c/p\u003e","manuscriptTitle":"Migration behaviour, wintering areas and conservation biology of brown skuas breeding in the subtropical Amsterdam Island","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-28 11:31:06","doi":"10.21203/rs.3.rs-5874357/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revise and Resubmit","date":"2025-03-04T10:54:21+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-01-23T17:33:21+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-01-23T15:49:55+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-01-23T10:37:59+00:00","index":"","fulltext":""},{"type":"submitted","content":"Marine Biology","date":"2025-01-21T09:33:28+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"marine-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mabi","sideBox":"Learn more about [Marine Biology](https://www.springer.com/journal/227)","snPcode":"227","submissionUrl":"https://submission.nature.com/new-submission/227/3","title":"Marine Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"d7c3b1cd-4830-4a90-a93a-aef7ea67c7db","owner":[],"postedDate":"January 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-23T16:04:38+00:00","versionOfRecord":{"articleIdentity":"rs-5874357","link":"https://doi.org/10.1007/s00227-025-04770-w","journal":{"identity":"marine-biology","isVorOnly":false,"title":"Marine Biology"},"publishedOn":"2026-02-16 15:59:33","publishedOnDateReadable":"February 16th, 2026"},"versionCreatedAt":"2025-01-28 11:31:06","video":"","vorDoi":"10.1007/s00227-025-04770-w","vorDoiUrl":"https://doi.org/10.1007/s00227-025-04770-w","workflowStages":[]},"version":"v1","identity":"rs-5874357","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5874357","identity":"rs-5874357","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}