# Do penguins care about on-paper boundaries? Conservation implications of spatio-temporal winter consistency in an Antarctic sentinel species

Zuzana Zajková, Akiko Kato, Thierry Raclot, Frederic Angelier, Jean-Baptiste

Thiebot, Akinori Takahashi, Yan Ropert-Coudert

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Zuzana Zajková, Akiko Kato, Thierry Raclot, Frederic Angelier, Jean-Baptiste Thiebot, et al. Do penguins care about on-paper boundaries? Conservation implications of spatio-temporal winter consistency in an Antarctic sentinel species. Biological Conservation, 2026, 313, pp.111507. 10.1016/j.biocon.2025.111507. hal-05339253

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# Do penguins care about on-paper boundaries? Conservation implications of spatio-temporal winter consistency in an Antarctic sentinel species

Zuzana Zajková<sup>a,b,*</sup>, Akiko Kato<sup>b</sup>, Thierry Raclot<sup>c</sup>, Frederic Angelier<sup>b</sup>, Jean-Baptiste Thiebot<sup>d</sup>, Akinori Takahashi<sup>c</sup>, Yan Ropert-Coudert<sup>b</sup>

## ARTICLE INFO

**Keywords:**

Adélie penguin

Non-breeding season

Tracking

Sea ice

Marine Protected Area

CCAMLR

## ABSTRACT

Understanding the spatial and temporal at-sea distribution of marine predators throughout their annual cycle is crucial for identifying priority areas for conservation in the Southern Ocean. However, the delimitation of boundaries of the proposed East Antarctic Marine Protected Area (EAMPA) is largely based on species' breeding distributions, overlooking seasonal and annual shifts driven by sea ice variability. We studied the non-breeding distribution and space use of a key Antarctic eco-indicator species, the Adélie penguin, by tracking 62 individuals from Terre Adélie over five years using geolocators. Moulting occurred in areas of low sea ice concentration (SIC), whereas during winter, penguins migrated on average 1550 km westward from the colony to areas along the sea ice edge with high SIC (75 %). The inter-annual overlap of wintering grounds revealed high spatio-temporal consistency, indicating productive regions. Despite variability across years, tracked individuals moulted predominantly outside the proposed EAMPA, and only 16.3 % of winter locations fell within its boundaries. These findings provide new insights into the non-breeding ecology of Adélie penguins, and highlight a relevant gap in spatial coverage of critical moulting and wintering areas of this highly mobile species in the current EAMPA proposal.

## 1. Introduction

Understanding the spatial distributions of marine predators throughout their annual cycle is crucial for identifying their potential threats and priority areas for conservation (Davies et al., 2021; Handley et al., 2021; Reisinger et al., 2022a), particularly in dynamic ecosystems undergoing rapid environmental change. In the Southern Ocean, highly-mobile predators, such as seabirds and marine mammals, often concentrate in productive regions and their foraging grounds indicate biodiversity hotspots (Hindell et al., 2020; Raymond et al., 2015). The growing availability of tracking data of marine predators, combined with advances in analytical approaches, offers new opportunities to understand space-use patterns and inform the delimitation of important conservation areas (Beal et al., 2021; Becker et al., 2024). However, short-term or seasonally limited studies may fail to capture the full annual variability in species' space use, limiting their robustness and

their utility for conservation planning.

The remoteness and seasonal inaccessibility of Antarctica pose a challenge to monitoring species' full annual distribution, often resulting in biases in data availability. This is particularly relevant for the proposed East Antarctic Marine Protected Area (EAMPA) which boundaries delimitation primarily relied on the summer foraging grounds of the penguins and seals during the breeding season (CCAMLR, 2019). Such bias may potentially exclude important habitats used during the extensive non-breeding period, despite its crucial role in their annual life cycle. Recent tracking studies have indeed revealed that after the breeding season, adult Adélie and juvenile Emperor penguins can greatly expand their at-sea distribution range away from their breeding colonies (Labrousse et al., 2019; Thiebot et al., 2019), and thus beyond the boundaries of the proposed summer-based MPA.

Adélie penguin (*Pygoscelis adeliae*) is an ice-obligate predator and one of the most broadly distributed penguin species (Ainley, 2002).

<footnote><sup>a</sup> Institut de Ciències del Mar (ICM-CSIC), Barcelona, Spain</footnote>

<footnote><sup>b</sup> Centre d'Études Biologiques de Chizé (CEBC), UMR 7372, CNRS – La Rochelle Université, Villiers-en-Bois, France</footnote>

<footnote><sup>c</sup> UMR 7178 IPHC DEPE, CNRS – Université de Strasbourg, Strasbourg, France</footnote>

<footnote><sup>d</sup> Graduate School of Fisheries Sciences, Hokkaido University, Japan</footnote>

<footnote><sup>e</sup> National Institute of Polar Research, Tokyo, Japan</footnote>

<footnote>* Corresponding author at: Institut de Ciències del Mar (ICM-CSIC), Pg. Marítim de la Barceloneta, 37, 08003, Barcelona, Spain.
E-mail address: zajkova@icm.csic.es (Z. Zajková).</footnote>
Owing to its pan-Antarctic distribution and sensitivity to changes in the environment, it is considered a key eco-indicator and sentinel species of Antarctic marine ecosystems (Ainley, 2002). Despite the large estimated total population of Adélie penguins (~10,000,000 adult individuals, BirdLife International, 2020), predictions indicate that intensive krill exploitation by fisheries and climate change may result in drastic declines in Adélie penguin populations (Cimino et al., 2016; Forcada and Trathan, 2009; Gimeno et al., 2024). In fact, certain colonies have experienced strong declines in recent years (Emmerson and Southwell, 2022; Juáres et al., 2015) while others remain stable or are slightly increasing (Barbraud et al., 2020; Lyver et al., 2014). Recent changes in environmental conditions have also been associated with extreme climatic events that led to massive breeding failures in East Antarctica (Ropert-Coudert et al., 2018). In addition, serious concerns have been raised regarding decreases in the juvenile survival that could be related to early-winter sea ice conditions after the fledging (Barracho et al., 2024).

The non-breeding period of Adélie penguins, which includes the moult and wintering, spans eight months across the austral winter. During this prolonged phase spent at sea, the birds may adopt different movement strategies (Black et al., 2018) driven by the need to locate favourable foraging habitats. Adélie penguins may remain in the vicinity of the breeding colony (Erdmann et al., 2011) or undertake long-distance migrations up to 2500 km from the colony (Ballard et al., 2010; Clarke et al., 2003; Dunn et al., 2011; Hinke et al., 2015; Takahashi et al., 2018; Thiebot et al., 2019). Before migrating to their wintering areas, Adélie penguins undergo a complete moult to replace their whole plumage after breeding (Black, 2016). The moult takes place ashore (Clarke et al., 2003; Penney, 1967) or on ice floes away from the breeding colony (Ainley, 2002; Schmidt et al., 2023). Throughout both the moulting and wintering periods, Adélie penguins rely on sea ice habitats, which are crucial for foraging, resting and protection from predators (Ainley, 2002). This marked dependence on sea ice makes the species especially vulnerable to changes in sea ice conditions. The relationship between sea ice conditions and population dynamics of Adélie penguins is complex (Iles et al., 2020; Viollat et al., 2024). However, the sea ice conditions that penguins encounter during winter may affect their breeding success in the next breeding season through carry-over effects and therefore impact their population dynamics (Che-Castaldo et al., 2017; Jenouvrier et al., 2006).

Sea ice concentration and extent in Antarctica shows considerable regional and inter-annual variability (Turner et al., 2015). Due to regional differences and opposite effects, the overall trend in the Antarctic sea ice extent was considered relatively stable, although it has been declining over the past decade (Ludescher et al., 2019; Purich and Doddridge, 2023), leading to an exceptionally low record in 2023 (Gilbert and Holmes, 2024). The presence of sea ice-related habitats limits the geographical distribution of Antarctic krill (Euphausia superba) (David et al., 2021), a key species in the Southern Ocean and a main component of the Adélie penguin diet, along with fish (Ainley, 2002). Consequently, fluctuations in sea ice conditions may lead to annual shifts in penguins' movements and distribution in response to changing environmental conditions and prey availability, thereby influencing the selection of moulting and wintering areas of Adélie penguins.

Conducting multi-year and year-round tracking studies of key marine predators is therefore essential for adequately accounting for the seasonal movements of marine predators and understanding their inter-annual shifts in distribution under varying environmental conditions. In this context, we aim to leverage a multi-year tracking dataset of non-breeding movements of an eco-indicator species, the Adélie penguin from Terre Adélie (East Antarctica), to provide new insights into their space use patterns during the non-breeding season. Specifically, we aim to (1) identify moultling and wintering areas of Adélie penguins; (2) measure the inter-annual spatial consistency in the utilization of the wintering areas; (3) examine the influence of sea ice conditions on the selection of moultling and wintering areas; (4) quantify the space use of

the East Antarctic MPA proposed management areas during moultling and wintering. Overall, this study aims to provide new insights into the non-breeding ecology of a key Antarctic eco-indicator species, that may be relevant for the effective design and management of an ecosystem-based network of MPAs dedicated to the conservation of Antarctic marine ecosystems.

## 2. Material and methods

### 2.1. Study site and species

The study colony is located in the vicinity of the Dumont d'Urville Station on the Ile des Pétrels, Pointe Géologie Archipelago, Terre Adélie, in Eastern Antarctica (66°39'46"S, 140°00'05"E). This colony holds ca. 20,000–50,000 breeding pairs of Adélie penguins (Barbraud et al., 2020), breeding during the austral summer in November–February. The study design was approved by the Council for Polar Science and Technology Programmes and the Terres Australes et Antarctiques Françaises.

### 2.2. Deployment of light-level geolocators

Over 5 years (2015–2020, except 2016), we tagged 88 breeding adults with light-level geolocation and immersion loggers (GLS logger hereafter) to study their seasonal movements at sea. A logger was mounted on a flexible band and attached to the penguin's leg using a cable tie (following Ratcliffe et al., 2014) at the end of the breeding period (chick-rearing) in mid-January. Exceptionally, the loggers recording data for the winter 2019 were deployed early in November 2018. Handling generally lasted a few minutes and the penguin was immediately released afterwards. We used Biotrack logger models MK3005 and MK3006 (2.5 g), except in 2015 when we deployed Lotek2500 model (8 × 36 mm, 3.6 g). The logger weight represented 0.05–0.08 % of the birds' body mass (mean ± SD 4596 ± 607 g on deployment, this study, n = 87). To facilitate the individual identification and subsequent recovery, animals were also tagged with Passive Integrated Transponder (PIT). The GLS loggers were recovered at the onset of the next breeding season in October–November, providing movement data for the non-breeding (wintering) period of tracked individuals. One logger deployed in January 2017 was recovered in November 2018, providing 2 seasons of data from the same individual. One logger deployed in 2015 was recovered in November 2016, but winter data were available only for 2015. Two individuals were each tagged over two different years with different loggers. Most tracked birds were males; females were tagged only in 2019 (11 females tagged and 6 recovered, 11 males tagged and 10 recovered). Due to the small female sample size and unbalanced dataset, sex-related differences were not included in the analysis.

### 2.3. Location estimation

GLS loggers measure light levels across time, in the aim to identify the daily times of sunrise and sunset, from which two daily locations can be derived. The Lotek loggers directly provided location estimates, but we re-estimated these locations; in all other cases we estimated the daily locations from light records. We used "probGLS" R package (Merkel et al., 2016) to estimate two daily locations for each track. This method allows for position estimation also during the equinox periods, reducing the median position estimation error to 145 km (Merkel et al., 2016). The probGLS package implements an algorithm using an iterative forward step selection process. The algorithm generates a cloud of possible locations (2000 particles in this study) which are weighted based on animal behaviour and travel speed. We assumed the mean swimming travelling speed (when the logger was immersed) of 2 m.s⁻¹ (maximum 3 m.s⁻¹ and standard deviation 1 m.s⁻¹) and the mean travelling speed when the logger was emerged as 1 m.s⁻¹ (maximum 2 m.s⁻¹ and SD 1 m. s⁻¹) (Thiebot et al., 2019). Additionally, location estimations accounted
for the land mask and environmental covariates, including daily mean of sea-surface temperature (SST) and sea ice concentration (SIC) at 0.25° x 0.25° spatial grid (NOAA OI SST V2 High Resolution Dataset https://psl.noaa.gov/data/gridded/data.noaa.oisst.v2.highres.html). Following Thiebot et al. (2019), a 3 °C tolerance around observed and the satellite-derived SST was applied, and locations with SIC >99 % were considered implausible. Across 100 iterations, multiple potential trajectories were generated and the most probable trajectory was calculated as their geographical median.

We filtered estimated locations for outliers using an iterative speed filter (McConnell et al., 1992) implemented in the “argsofilter” R package function vmask (Freitas, 2012), using a threshold of 2 m.s⁻¹. Afterwards, we visually checked and manually eliminated isolated locations. One logger (ID 3031, year 2015) did not provide sufficient location points and was excluded from the spatial analysis. However, the immersion data from this logger were sufficient for phenology estimations (see *Phenology and moulting*). Three loggers (ID 3016, 3023 and 3025, all year 2015) stopped recording before the recovery. The final dataset for spatial analysis contained 23,986 locations.

## 2.4. Phenology and moulting

In this study, we focused on the non-breeding period; therefore, we restricted the following analysis to the period from the start of the moult until the return of animals to the colony from wintering. Based on both location and immersion data (see the following paragraph), we inferred several phenological events: (1) onset of moult, (2) duration of moult, (3) end of moult, corresponding to the start of the wintering period, (4) timing of the most distant location reached from the colony, and (5) return to the breeding colony, which was considered as the end of the wintering period.

We used immersion data to identify the moulting period as a prolonged period of continuous dry records, calculated as the proportion of day spent in dry state. We observed occasional interruptions of the dry records by short periods of wet records (daily duration range 6 s – 82 min), and therefore we included days where the sum of wet records was less than 2 h as part of the moulting period. We estimated the timing of return to the colony as the first day with at least two following days of continuous dry records in October–November, before the logger recovery. Three loggers with incomplete position records and one logger excluded from spatial analysis provided sufficient immersion data to estimate moult parameters, but we excluded them from the averages of the winter phenology parameters.

## 2.5. Interannual distribution analysis

First, we computed kernel utilization distribution (UD) of wintering locations of Adélie penguins and extracted the 50 % and 95 % contours for each year using the *kernelUD* function (parameters h = 200 km, grid = 1000) from the “adehabitatHR” R package version 0.4.19 (Calenge, 2006). Second, we assessed the consistency in the utilization of wintering areas across years by calculating two conditional overlap indices for the 50 % and 95 % UD areas using the *kerneloverlap* function from the “adehabitatHR” R package. The Bhattacharyya affinity (BA) index indicates the similarity between UDs, and the resulting values range from 0 (no overlap) to 1 (identical UDs). The utilization distribution overlap index (UDOI) indicates the space use sharing, where the values range from 0 to 1, but can be >1 in the case of nonuniformly distributed and high-degree overlap UDs (Fieberg and Kochanny, 2005). Following Delord et al. (2020), we tested the null hypothesis that there was no difference in the spatial distribution of Adélie penguins between years, by performing a randomization procedure. We randomly assigned the year to individual trips and calculated the interannual overlap indices. The procedure was repeated 1000 times, and we used a one-tailed test to evaluate whether the observed overlap is smaller than random overlap at level $\alpha = 0.05$.

We evaluated the representativeness of the tracking data sample as whole and per year following Lascelles et al. (2016), using the *repAssess* function in the “track2KBA” R package version 1.0.2 (Beal et al., 2021), running 100 iterations. The assumption is that the sample is adequately representative if the representativeness value is equal or higher than 70 % (Lascelles et al., 2016). Finally, we used the function *findSite* from the “track2KBA” R package to highlight the key wintering area of Adélie penguins as an area of potential interest for conservation. Individual 50 % kernel UDs were overlapped and for each grid cell the proportion of overlapping UDs was calculated. This value was multiplied by estimated representativeness value and by the minimal estimated number of breeding adults at the studied colony ($n = 40,000$; Barbraud et al., 2020) to estimate the number of animals predictably using the area (Beal et al., 2021).

## 2.6. Sea ice conditions

We characterized the sea ice conditions that birds encountered during the moulting and wintering period. Daily sea ice concentration (SIC) data on the 6.25 km grid were downloaded from the University of Bremen webpage (https://seaice.uni-bremen.de/data/amsr2/asi_daygri_d_swath/s6250/netcdf/, Sreen et al., 2008). We used the “exactextract” R package (Baston, 2021) to extract the mean SIC value within the 100 km radius of each animal location, accounting this way for the spatial error of the location estimation. We also calculated the distance to the ice edge (defined as 15 % SIC) for each animal location, determining if the locations were within the closed ice (SIC >15 %) or in open water (SIC <15 %). The position of the Southern Antarctic Circumpolar Front (SACCF) was downloaded using the R package “orsifronts” (Orsi et al., 1995).

## 2.7. Overlap with the proposed marine protected area

We assessed the spatial overlap between Adélie penguin distribution and three management units of the proposed EAMPA (D'Urville Sea-Mertz, Drygalski and MacRobertson) by calculating the proportion of penguin locations during moulting and wintering periods that fell within the spatial boundaries of these areas (see Suppl. Data for more details).

## 2.8. Statistical analysis

We used linear mixed-effects models (LMM) to test for differences among years in phenological (moult start and end dates, moult duration, wintering duration, return date) and spatial (distance of the moulting centroid from the colony, maximum distance during wintering) parameters, using the “lme4” R package (Bates et al., 2015). The year was included as a categorical fixed effect and individual ID was included as a random effect in all models.

We evaluated the effect of the year and month (fixed factors) on the distance from the sea ice edge using generalized linear mixed-effects models (GLMM) with a gamma distribution, including individual ID as a random effect.

Model selection was conducted using likelihood ratio tests, comparing nested models with and without the predictor variable. Post-hoc pairwise comparisons were calculated using the *emmeans* function from the “emmeans” R package (Lenth et al., 2022), applying the Tukey adjustment for multiple comparisons.

We used Kruskal-Wallis rank sum test to evaluate effect of year and month on sea ice concentration habitats selected by individuals during moult and wintering. On significant test results, we further applied Dunn's test with Bonferroni correction for post-hoc comparison.

We report average values as mean ± standard deviation (SD). Distance from the sea ice edge, which showed a skewed distribution, is instead reported as median with interquartile range (IQR).

All data processing, analysis and visualization was done in R programming language version 4.1.2 (R Core Team, 2021).
## 2.9. Data availability statement

The tracking dataset generated and analysed in this study is available in the Movebank repository (https://www.movebank.org/, study ID: 4778411162). Code is available from the GitHub repository (https://github.com/zuzulaz/Paper_Adelies_GLSwinter_EAMPA) and from Figshare repository (https://doi.org/10.6084/m9 figshare.27947100.v2).

## 3. Results

In subsequent years, we reencountered 71 individuals tagged with GLS (80.7 % of deployed birds), and retrieved the logger from 61 individuals (69.3 %); the other 10 individuals (11.4 %) had lost their logger (Table S1). The final dataset for spatial analysis of moult and wintering distribution included 61 and 58 individual GLS tracks, respectively.

### 3.1. Timing and location of moulting areas

Adélie penguins started to moult on average (mean ± SD) on March 5 ± 9.6 days (range February 13 – March 19, *n* = 62). We found significant differences among years: in 2017, the birds advanced the moult comparing to years 2018 (*p* = 0.005) and 2019 (*p* = 0.011). The average

moult duration was 19.8 ± 2.0 days (range 15–24, *n* = 62), and there was no clear difference among years. Adélie penguins moulted in areas northward and westward from the breeding colony (Fig. 1). The centroids of moulting areas, spread between the 110–145°E, were located on average 653 ± 274 km away from the colony (range 153–1224 km, *n* = 61). This distance varied significantly among years: in 2019, the penguins moulted further away compared to 2015 (*p* = 0.013) and 2017 (*p* = 0.023). Birds finished moulting on March 24 ± 9.2 days on average (range March 4 – April 8, *n* = 62). We found significant differences among years: in 2017, the birds finished moulting earlier compared to the years 2018 (*p* = 0.003) and 2019 (*p* = 0.008). (Table 1, Table S2).

### 3.2. Wintering movements

After the moult, Adélie penguins showed several movement strategies. Most of tracked birds travelled westward and northward, however several individuals dispersed northwards and stayed in the longitudinal vicinity of the colony across winter. Birds reached the most distant point 1544 ± 551 km from the colony (range 496–2789 km, only complete trips, *n* = 58) on average on August 2 ± 32.6 (range April 4 – October 13, *n* = 58). We found significant differences among years in the maximum distance reached: the birds travelled further from the colony in 2019 compared to 2015 (*p* = 0.048) and in 2018 compared to 2015 (*p* <

<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Centroids of moulting locations of Adélie penguins tracked with GLS from Île des Pétrels, Terre Adélie, in Eastern Antarctica in years 2015, 2017–2020 (*n* = 61). Colours correspond to different years of tracking. Yellow triangle represents the location of the breeding colony. Black lines and numbers indicate borders and codes of the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) statistical subareas, respectively. Dark blue dotted polygon represents one zone of the proposed East Antarctic Marine Protected Area (EAMPA), D’Urville Sea-Mertz. White line represents the Southern Antarctic Circumpolar Front (SACCF). The inset figure shows the two established (South Orkney Islands Southern Shelf, Ross Sea region; in sky blue) and three proposed marine protected areas (Domain 1 Marine Protected Area in the Antarctic Peninsula, Weddell Sea Marine Protected Area, EAMPA; in dark blue). The three zones of the proposed EAMPA are highlighted as dotted polygons. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>
<caption>**Table 1**</caption>

Chronology of the movement and activity of Adélie penguins tracked with GLS from Île des Pétrels, Terre Adélie, in Eastern Antarctica, in years 2015, 2017–2020. Values are mean ± SD. Statistics indicate results of likelihood ratio tests of linear mixed models assessing the effect of year for each parameter. Values in bold indicate *p* < 0.05.

<table><thead><tr><th>Parameter</th><th>2015</th><th>2017</th><th>2018</th><th>2019</th><th>2020</th><th>All</th><th>Statistics</th></tr></thead><tbody><tr><td>Moult start date</td><td>2 Mar ± 10.2</td><td>21 Feb ± 5.5</td><td>10 Mar ± 7</td><td>7 Mar ± 8.7</td><td>6 Mar ± 7.4</td><td>5 Mar ± 9.6</td><td>χ<sup>2</sup> = 24.369, <strong>p</strong> < 0.001</td></tr><tr><td>Moult duration (days)</td><td>19.2 ± 2.2</td><td>21.1 ± 2.2</td><td>19.4 ± 1.9</td><td>20.4 ± 1.5</td><td>19.2 ± 1.9</td><td>19.8 ± 2</td><td>χ<sup>2</sup> = 8.440, <strong>p</strong> = 0.077</td></tr><tr><td>Moulting centroid distance from the colony (km)</td><td>498 ± 345</td><td>458 ± 254</td><td>713 ± 204</td><td>823 ± 219</td><td>609 ± 201</td><td>653 ± 274</td><td>χ<sup>2</sup> = 17.060, <strong>p</strong> = 0.002</td></tr><tr><td>Moult end date</td><td>20 Mar ± 9.7</td><td>12 Mar ± 4.3</td><td>29 Mar ± 6.7</td><td>26 Mar ± 8.7</td><td>24 Mar ± 7.2</td><td>24 Mar ± 9.2</td><td>χ<sup>2</sup> = 22.232, <strong>p</strong> < 0.001</td></tr><tr><td>N</td><td>13</td><td>7</td><td>16</td><td>16</td><td>10</td><td>62</td><td>–</td></tr><tr><td>Max. distance during wintering (km)</td><td>1090 ± 371</td><td>1151 ± 432</td><td>1984 ± 369</td><td>1682 ± 427</td><td>1306 ± 6176</td><td>1544 ± 551</td><td>χ<sup>2</sup> = 30.281, <strong>p</strong> < 0.001</td></tr><tr><td>Date of max. distance during wintering</td><td>14 Aug ± 37.5</td><td>20 Aug ± 19.1</td><td>9 Aug ± 24.5</td><td>18 Jul ± 23.4</td><td>23 Jul ± 48.7</td><td>2 Aug ± 32.6</td><td>χ<sup>2</sup> = 8.023, <strong>p</strong> = 0.091</td></tr><tr><td>Wintering duration (days)</td><td>227.3 ± 12</td><td>231.1 ± 6.6</td><td>211.5 ± 9.1</td><td>216.2 ± 8.3</td><td>218.2 ± 7.1</td><td>218.8 ± 10.9</td><td>χ<sup>2</sup> = 26.715, <strong>p</strong> < 0.001</td></tr><tr><td>Return date</td><td>30 Oct ± 4.0</td><td>28 Oct ± 4.0</td><td>25 Oct ± 5.1</td><td>27 Oct ± 4.5</td><td>27 Oct ± 2.3</td><td>27 Oct ± 4.4</td><td>χ<sup>2</sup> = 7.663, <strong>p</strong> = 0.105</td></tr><tr><td>N</td><td>9</td><td>7</td><td>16</td><td>16</td><td>10</td><td>58</td><td>–</td></tr></tbody></table>

0.001), 2017 (*p* = 0.003) and 2020 (*p* = 0.004). The date of reaching the maximum distance was not significantly different among years. The average duration of wintering was 218.8 ± 10.9 days (range 198–244, *n* = 58), with significant differences among years. Birds spent more time wintering in 2017 compared to 2018 (*p* < 0.001) and 2019 (*p* = 0.011), and in 2015 compared to 2018 (*p* = 0.002). Adélie penguins returned to the breeding colony on October 27 ± 4.4 days on average (range October 17 – November 9, *n* = 58), without significant differences among years. (Table 1, Table S2).

The annual datasets and the complete dataset provided a robust representation of the sampling population, with the representativeness scores consistently above 75 % (range 75.4–97 % for annual subsets, 98.2 % for the complete dataset) (Fig. S1).

### 3.3. Interannual consistency in the use of wintering areas

We observed high values for Bhattacharyya's affinity (BA) overlap index for both 50 and 95 % UD s (Table 2A). Significant BA values for years 2018 and 2019 compared with years 2015, 2017 and 2020 indicate dissimilar UD s. The observed values for the Utilization distribution overlap index (UDOI) were low for the 50 % UD, but >1 for the 95 % UD s in many cases (Table 2B). The shared UD was significantly lower for years 2018 and 2019 compared with years 2015, 2017 and 2020.

### 3.4. Sea ice conditions during the moult and wintering

The mean SIC over the moult period of each individual was 17.0 ±

<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Kernel utilization distribution 50 % (solid lines) and 95 % (transparent polygons) of wintering locations of Adélie penguins tracked with GLS from Île des Pétrels, Terre Adélie, in Eastern Antarctica in years 2015, 2017–2020 (*n* = 61). Colours correspond to different years of tracking. Yellow triangle represents the location of the breeding colony. Black lines and numbers indicate borders and codes of CCAMLR subareas, respectively. Dark blue dotted polygons represent the proposed East Antarctic Marine Protected Area. White line represents the Southern Antarctic Circumpolar Front (SACCF). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>
<caption>**Table 2**</caption>

Estimated inter-annual overlap A) Bhattacharyya's affinity and B) Utilization distribution overlap index (UDOI) in utilization distributions (UD) of Adélie penguins from *Ile des Pétrels*, Terre Adélie, in Eastern Antarctica, tracked with GLS (n = 61). Values in bold indicate *p* < 0.05 for one-sided t-test comparing whether observed overlap is less than the randomized overlap.

<table><thead><tr><th rowspan="2">A)<br>Winter years</th><th colspan="3">50 % UD</th><th colspan="3">95 % UD</th></tr><tr><th>Observed overlap</th><th>Randomized overlap</th><th>p-value</th><th>Observed overlap</th><th>Randomized overlap</th><th>p-value</th></tr></thead><tbody><tr><td>2015–2017</td><td>0.425</td><td>0.363</td><td>1</td><td>0.920</td><td>0.876</td><td>1</td></tr><tr><td>2015–2018</td><td>0.208</td><td>0.392</td><td>< 0.001</td><td>0.744</td><td>0.899</td><td>< 0.001</td></tr><tr><td>2015–2019</td><td>0.247</td><td>0.390</td><td>< 0.001</td><td>0.779</td><td>0.898</td><td>< 0.001</td></tr><tr><td>2015–2020</td><td>0.445</td><td>0.379</td><td>1</td><td>0.898</td><td>0.889</td><td>1</td></tr><tr><td>2017–2018</td><td>0.210</td><td>0.369</td><td>< 0.001</td><td>0.766</td><td>0.880</td><td>< 0.001</td></tr><tr><td>2017–2019</td><td>0.270</td><td>0.370</td><td>< 0.001</td><td>0.815</td><td>0.881</td><td>< 0.001</td></tr><tr><td>2017–2020</td><td>0.401</td><td>0.363</td><td>1</td><td>0.896</td><td>0.874</td><td>1</td></tr><tr><td>2018–2019</td><td>0.410</td><td>0.399</td><td>1</td><td>0.907</td><td>0.904</td><td>1</td></tr><tr><td>2018–2020</td><td>0.165</td><td>0.388</td><td>< 0.001</td><td>0.811</td><td>0.895</td><td>< 0.001</td></tr><tr><td>2019–2020</td><td>0.215</td><td>0.386</td><td>< 0.001</td><td>0.833</td><td>0.894</td><td>< 0.001</td></tr></tbody></table>

<table><thead><tr><th rowspan="2">B)<br>Winter years</th><th colspan="3">50 % UD</th><th colspan="3">95 % UD</th></tr><tr><th>Observed overlap</th><th>Randomized overlap</th><th>p-value</th><th>Observed overlap</th><th>Randomized overlap</th><th>p-value</th></tr></thead><tbody><tr><td>2015–2017</td><td>0.186</td><td>0.141</td><td>1</td><td>1.253</td><td>1.154</td><td>1</td></tr><tr><td>2015–2018</td><td>0.044</td><td>0.164</td><td>< 0.001</td><td>0.759</td><td>1.248</td><td>< 0.001</td></tr><tr><td>2015–2019</td><td>0.063</td><td>0.163</td><td>< 0.001</td><td>0.860</td><td>1.248</td><td>< 0.001</td></tr><tr><td>2015–2020</td><td>0.208</td><td>0.152</td><td>1</td><td>1.220</td><td>1.209</td><td>0.99</td></tr><tr><td>2017–2018</td><td>0.045</td><td>0.148</td><td>< 0.001</td><td>0.850</td><td>1.180</td><td>< 0.001</td></tr><tr><td>2017–2019</td><td>0.077</td><td>0.148</td><td>< 0.001</td><td>1.055</td><td>1.184</td><td>< 0.001</td></tr><tr><td>2017–2020</td><td>0.167</td><td>0.138</td><td>1</td><td>1.290</td><td>1.150</td><td>1</td></tr><tr><td>2018–2019</td><td>0.176</td><td>0.172</td><td>0.99</td><td>1.345</td><td>1.279</td><td>1</td></tr><tr><td>2018–2020</td><td>0.028</td><td>0.159</td><td>< 0.001</td><td>0.947</td><td>1.230</td><td>< 0.001</td></tr><tr><td>2019–2020</td><td>0.047</td><td>0.159</td><td>< 0.001</td><td>1.079</td><td>1.236</td><td>< 0.001</td></tr></tbody></table>

12.6 % (range 0–64.7 %, n = 61). Several individuals were found to moult in areas with nil SIC. There was a significant effect of year on the SIC over the moult period (Kruskal-Wallis, $\chi^2 = 18.433$, df = 4, $p = 0.001$) (Table S3A). Penguins moulted in areas with the highest SIC in 2018 (27.8 ± 20.8 %), in contrast to years 2019 (10.3 ± 13.0 %) and 2020 (11.2 ± 12.6 %), when penguins moulted in areas with the lowest SIC (Fig. 4A). The median distance from the sea ice edge during moult within the pack ice (SIC >15 %; 42.7 % of locations) was 39.4 km (IQR: 15.8–75.7), with significant differences between years (GLMM, $\chi^2 = 16.248$, df = 4, $p = 0.003$). Penguins stayed closer to the sea ice edge in 2018 compared to 2019 ($p = 0.018$) (Table S4A). Moulting locations in the open water (SIC <15 %; 57.3 % of locations) were located within the median distance of 51.2 km (IQR: 23.8–87.3), with significant differences between years (GLMM, $\chi^2 = 30.498$, df = 4, $p < 0.001$) (Table S4B). Penguins remained closer to the sea ice edge in 2018 compared to all other years and farther in 2019 compared to 2015.

Following moult, as the sea ice extent started to increase, Adélie penguins encountered areas with higher SIC. Throughout the wintering period, the mean SIC of individual locations was 75.3 ± 13.4 % (range 2.0–86.7 %, n = 61). There were no significant differences between years (Kruskal-Wallis, $\chi^2 = 5$, df = 4, $p = 0.3$), but between months (Kruskal-Wallis, $\chi^2 = 242$, df = 8, $p < 0.001$) (Fig. 4B, Fig. S3B, Table S3B). Penguins encountered conditions with the highest SIC during June–August, with mean values over 85 %. The highest intra-annual and individual variability in SIC were observed in March, April and November (Fig. 4B).

In total, 93.5 % of winter locations were within the closed ice (SIC >15 %), with a median distance from the sea ice edge of 83.8 km (IQR: 39.1–138.2). Significant differences were found among years and months (GLMM, $\chi^2 = 46.571$, df = 8, $p < 0.001$): the birds stayed closer to the sea ice edge in 2015, 2018 and 2020 and farther in 2017 and 2019 (Table S5A, Fig. S4). When spending time in open water (6.5 % of locations, 60 % of them during 2019), penguins remained a median distance 79.1 km (IQR: 32.2–146.6) from the sea ice edge with differences

among years and months (GLMM, $\chi^2 = 60.812$, df = 8, $p < 0.001$) (Table S5B, Fig. S4).

### 3.5. Overlap with proposed MPA boundaries

Overall, Adélie penguins spent on average 11.7 ± 29.4 % and 16.3 ± 21.9 % of their moulting and wintering periods, respectively, within the spatial limits of the proposed EAMPA (Table 3, Suppl. Data). The lowest values were recorded between June and August, and during the years 2018–2020 (Fig. S5). While penguins used the D’Urville Sea-Mertz and Drygalski zones, no locations were found within the spatial limits of the MacRobertson zone.

Except for several locations in September 2020, Adélie penguins distributed within the boundaries of the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) management areas, particularly in the areas 58.4.1, 58.4.2, 58.4.3b and 88.1 (Fig. 2, Fig. 3, Fig. S2).

## 4. Discussion

Our study provides valuable insights into the non-breeding habitat use of Adélie penguins in East Antarctica, with potential implications for the management and conservation of these habitats. By using GLS tracking over a five-year period, we identified moulting and wintering areas of Adélie penguins. Our results confirmed a consistent westward migration pattern and, despite individual variation, the penguins’ tendency to select extensive wintering areas, particularly those with high sea ice concentration. Notably, during both moult and winter, penguins spent a substantial amount of time outside the boundaries of the proposed East Antarctica Marine Protected Area (EAMPA). This study underscores the importance of conducting long-term and year-round studies to effectively assess and optimize the design and management of Marine Protected Areas.
<caption>**Table 3**</caption>

Proportion of locations of Adélie penguins located within the spatial boundaries of proposed East Antarctic MPA, zones D'Urville Sea-Mertz (DUSM) and Dry-galski during moult and wintering. No location was found within the spatial limits of the MacRobertson area. Birds were tracked with GLS from *Île des Pétrels*, Terre Adélie, in Eastern Antarctica, in the years 2015, 2017–2020. Values are mean ± SD of individual values.

<table><thead><tr><th>Parameter</th><th>2015</th><th>2017</th><th>2018</th><th>2019</th><th>2020</th><th>All</th></tr></thead><tbody><tr><td>Proportion of locations within DUSM during moult (%)</td><td>41.6 ± 46.8</td><td>30.3 ± 38.2</td><td>0 ± 0</td><td>0 ± 0</td><td>0.2 ± 0.7</td><td>11.7 ± 29.4</td></tr><tr><td>N</td><td>12</td><td>7</td><td>16</td><td>16</td><td>10</td><td>61</td></tr><tr><td>Proportion of locations within DUSM during wintering (%)</td><td>24.1 ± 28.5</td><td>22.3 ± 34.5</td><td>5.2 ± 6.7</td><td>4.4 ± 3.9</td><td>14.4 ± 26.7</td><td>11.6 ± 20.8</td></tr><tr><td>N</td><td>9</td><td>7</td><td>16</td><td>16</td><td>10</td><td>58</td></tr><tr><td>Proportion of locations within Drygalski during wintering (%)</td><td>0 ± 0</td><td>0 ± 0</td><td>8.7 ± 13.4</td><td>5.5 ± 12.8</td><td>4.3 ± 13.7</td><td>4.7 ± 11.4</td></tr><tr><td>N</td><td>9</td><td>7</td><td>16</td><td>16</td><td>10</td><td>58</td></tr><tr><td>Proportion of locations within EAMPA during wintering (%)</td><td>24.1 ± 28.5</td><td>22.3 ± 34.5</td><td>13.9 ± 11.9</td><td>10.0 ± 13.2</td><td>18.7 ± 28.7</td><td>16.3 ± 21.9</td></tr><tr><td>N</td><td>9</td><td>7</td><td>16</td><td>16</td><td>10</td><td>58</td></tr></tbody></table>

## 4.1. Moult strategies

Several factors may alter the timing and duration of moult in Adélie penguins (Ainley, 2002), an energetically demanding period (Croxall, 1982) during which birds must remain undisturbed (Penney, 1967). Penguins tracked in this study were consistent in the moult duration and completed the moult in similar time frame to penguins from other colonies in the East Antarctica (19.8 days, Penney, 1967; 17.2 days,

Takahashi et al., 2018), the Ross Sea (19.6 days, Schmidt et al., 2023), in the Antarctic Peninsula (16.1 and 18.7 days in two tracked years, Zaldúa et al., 2024) or South Orkney Islands (18.6 days, Dunn et al., 2011). However, penguins showed flexibility in moult timing and location. The earliest onset of moult recorded in the colony in 2017 was presumably triggered by a breeding failure experienced by the entire colony (Ropert-Coudert et al., 2018). Similar results were observed for several birds in Lützow-Holm Bay, where breeding failure led to precocious moult (Takahashi et al., 2018). Our study further suggest that Adélie penguins from Terre Adélie moult on pack ice along the sea ice edge west of the colony, presumably drifting on ice floes in areas with low sea ice concentration (SIC). Notably, in several years, some individuals were found to moult north of the 64°S in areas with nil SIC, which may be related to the resolution of the sea ice product used and GLS location error. Alternatively, Adélie penguins may moult on land, as is commonly observed at several colonies (Ainley, 2002; Clarke et al., 2003; Penney, 1967). Despite this uncertainties, our results reinforce the importance of suitable sea ice conditions during this critical period for survival, as birds moulting in areas of higher SIC showed higher return rates to the colony after winter (Schmidt et al., 2023).

## 4.2. Wintering distribution and sea ice conditions

Adélie penguins migrated large distances and spent nearly seven months replenishing energy and body reserves in wintering areas. Relieved from their breeding constraints, penguins showed certain individual flexibility in the selection of winter foraging grounds. While several individuals spent at least a part of winter north of the colony, most of tracked penguins followed the clockwise migratory pattern described from other East-Antarctic colonies (Clarke et al., 2003; Takahashi et al., 2018). After leaving their moulting grounds by the end of March-early April, penguins headed west, following sea ice movement pushed by the Antarctic Slope Current (Bindoff et al., 2000). Adélie penguins typically forage in productive coastal polynyas, the marginal

<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Key areas of potential importance for wintering Adélie penguins from *Île des Pétrels*, Terre Adélie, in Eastern Antarctica. Colour scale indicates estimated number of individuals per cell that could potentially use the area during the wintering season (March – November). The estimation is based on individual kernel UD of animals tracked with GLS in years 2015, 2017–2020 (n = 61) and weighted by estimated minimal number of breeding adults in the colony (n = 40,000). Yellow triangle represents the location of the breeding colony. Black lines and numbers indicate borders and codes of CCAMLR subareas, respectively. Dark blue dotted polygons represent the proposed East Antarctic Marine Protected Area. White line represents the Southern Antarctic Circumpolar Front (SACCF). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>**Fig. 4.** Mean sea ice concentration (%) within a 100 km buffer around locations of Adélie penguins tracked with GLS from Île des Pétreils, Terre Adélie, in Eastern Antarctica, in years 2015, 2017–2020: A) during the moult and B) during the wintering period, where each facet corresponds to a month. Colours represent different years. See Table 1 for detailed phenological parameters.</figcaption></figure>

ice zone and cracks in the pack ice (Ainley et al., 2017). Our results indicate that throughout the season they may have used multiple polynyas located along the East Antarctic coast (Arrigo and van Dijken, 2003; Portela et al., 2022), although the location error prevents clear confirmation. Penguins returned towards the breeding colony in September–October along the eastward flowing Antarctic Circumpolar Current. This clock-wise pattern is partially similar to migrations of Adélie penguins from the Ross Sea (Ballard et al., 2010; Jongsomjit et al., 2024). In contrast, Adélie penguins from the West Antarctic Peninsula migrated in the counter-clockwise and spent the winter in the southern Scotia Sea and northern Weddell Sea (Hinke et al., 2015; Zaldúa et al., 2024), in areas similar to penguins from Signy Island which migrated south to the Weddell Sea (Dunn et al., 2011). Another wintering strategy was selected by penguins in the Marguerite Bay, Antarctic Peninsula, which dispersed in the vicinity of the breeding colony during the winter (Erdmann et al., 2011). Substantial variation in migration strategies highlights the need for future international collaborative studies across the species' distribution range to assess potential threats and to implement effective MPA strategies.

The pack sea ice habitats are essential foraging areas of sea ice obligate Adélie penguins during winter (Ainley et al., 1994). Penguins from Terre Adélie spent the winter in pack ice areas with high sea ice concentration along the sea ice edge. These results are consistent with penguins tracked from other colonies in East Antarctica (Takahashi et al., 2018), Ross Sea (Ballard et al., 2010), Signy Islands (Dunn et al., 2011) and King George Island (Zaldúa et al., 2024). However, contrasting results were found for penguins from West Antarctic Peninsula that used areas with much lower SIC (15–50%; Hinke et al., 2015). Even though the projections of sea ice extent in Antarctica are uncertain and regionally variable (Meredith, 2022; Turner et al., 2015), the overall sea ice extent in Antarctica has been declining over the last decade (Ludescher et al., 2019; Purich and Doddridge, 2023). Together with other factors (Ainley, 2002), this trend may limit the selection of winter

foraging grounds of Adélie penguins and force them to winter in sub-optimal areas (Wilson et al., 2001), potentially affecting their survival, breeding success and overall population dynamics (Ballerini et al., 2009; Che-Castaldo et al., 2017; Emmerson and Southwell, 2011; Jenouvrier et al., 2006; Kato et al., 2002).

Spatial and temporal variability in the distribution of highly mobile marine predators reflects prey availability (Weimerskirch, 2007). Particularly for an eco-indicator species, such as Adélie penguin, the areas consistently used over time indicate high productivity regions. Antarctic krill is a base of the food web in the Southern Ocean and constitutes a relevant part of Adélie penguin's diet year-round (Cherel, 2008; Jafari et al., 2021; Juáres et al., 2016). Since 2000, the exploitation of the East Antarctica by krill fisheries has declined, as fisheries target waters around the Antarctic peninsula (Santa Cruz et al., 2022). However, CCAMLR maintains a precautionary krill catch limit for the statistical division 58.4.1, encompassing the main wintering grounds of Adélie penguins, set to 440,000 t in any fishing season (CCAMLR, 2008). Within the proposed EAMPA, the D'Urville Sea-Mertz zone is planned as krill no take zone (CCAMLR, 2019), which may increase the biomass of krill and its predators under future climate change scenarios (Dahood et al., 2020; Sala and Giakoumi, 2018). However, the increasing krill demand, the efficacy of krill fisheries and the expansion of fishing into winter months in other areas (Santa Cruz et al., 2022) could lead to increased fishing pressure in the 58.4.1 area in the future.

### 4.3. Utilization of the proposed EAMPA

The proposed EAMPA aims to preserve representative benthic and pelagic marine habitats and their biodiversity, focusing on high-productivity areas vital for the foraging of marine predators (CCAMLR, 2019). This target would be achieved for foraging grounds of Adélie penguins from Terre Adélie during their breeding season, when they forage within the D'Urville Sea-Mertz zone (Michelot et al., 2021;
Widmann et al., 2015). However, our results indicate that the current version of the EAMPA proposal would not adequately protect Adélie penguins' foraging grounds during the moulting and wintering periods, which represent over 65 % of their annual life cycle. Furthermore, hundreds Adélie penguins' colonies are located along the East Antarctic coast within the 58.4.1 and 58.4.2 CCAMLR areas (Lynch and LaRue, 2014; Southwell and Emmerson, 2013; Raymond et al., 2015). While information on the winter distribution of penguins from these colonies is limited, if they follow the westward migratory pattern, it is plausible that thousands of individuals could moult and winter in the area between the D'Urville Sea-Mertz and Mac Robertson zones. Future tracking studies will be essential to resolve this knowledge gap. Importantly, the area located off the Wilkes Land (115° – 125°E, 64°N) was identified as an important wintering area not only for Adélie penguins from Terre Adélie, but for other marine predators, such as juvenile Emperor penguins (Labrousse et al., 2019) and petrel species (Delord et al., 2016; Viola et al., 2023). Given its ecological significance, this area could be reconsidered for inclusion as an additional zone within the EAMPA and expanding protection to this zone might enhance the overall conservation impact.

## 4.4. Management strategies for highly mobile species facing environmental change

During the non-breeding season, Adélie penguins were highly mobile and flexible in selecting the moulting and wintering grounds. This underscores the limitations of static MPAs in effectively protecting wide-ranging species (Hyrenbach et al., 2000; Oppel et al., 2018; Runge et al., 2014) and in maintaining migratory connectivity (Dunn et al., 2019). Furthermore, static MPAs in the Southern Ocean and Antarctica may be challenged by environmental changes driven by climate change, including increasing sea temperatures, changes in the sea ice extent and concentration, more frequent extreme weather events (Bracegirdle et al., 2008; Meredith, 2022; Morley et al., 2020; Siegert et al., 2023). These changes may ultimately affect marine ecosystems (Bestley et al., 2020; Chown and Brooks, 2019; Constable et al., 2014) and drive shifts in species' habitat use and distribution (Ainley et al., 2010; Atkinson et al., 2022; Green et al., 2023; Hückstädt et al., 2020; Krüger et al., 2018; Ouled-Cheikh et al., 2024; Reisinger et al., 2022b). One way to address these challenges is through adaptive strategies, such as dynamic management or mobile MPAs (Maxwell et al., 2020, 2015), which allow flexible adjustment of MPA boundaries in response to animal movement and environmental conditions (Houzin et al., 2022; Maxwell et al., 2020). In East Antarctica, for instance, Thiebot et al. (2019) proposed extending the boundaries of the proposed EAMPA to establish a dynamic winter connection between its three zones, which would help safeguard winter habitats essential for the survival of Adélie penguins (Emmerson and Southwell, 2011) and other pagophilic species. In the longer term, additional mechanisms such as climate-smart ocean planning (Santos et al., 2024a, 2024b) may further improve conservation outcomes and increase the resilience of the species and habitats under future climate scenarios in the Southern Ocean.

## 4.5. Capturing the full picture of species' distribution

To support effective conservation strategies, more representative and comprehensive tracking data are needed. While tracking marine predators has been crucial for identifying zones of ecological importance and priority conservation areas in the Southern Ocean (Ballard et al., 2012; Becker et al., 2024; Handley et al., 2021; Hindell et al., 2020; Raymond et al., 2015), many studies have relied on the movements and distribution during the breeding season only, overlooking areas used by migratory species outside this period. Additionally, the prevailing bias towards tracking adult individuals of one sex (Hazen et al., 2012; this study) underscores the need to achieve a balanced sex ratio in tracking efforts and to prioritise juvenile tracking, as their spatial distributions

remain largely understudied (Houzin et al., 2022; Shillinger et al., 2012). This study advocates for the inclusion of non-breeding distribution into future research aimed at developing conservation measures and delimiting MPAs boundaries. Incorporating critical knowledge on migratory pathways and winter distribution into MPA design and management could safeguard year-round protection of marine predators and their essential habitats.

## 5. Conclusions

The designation of MPAs in the Southern Ocean by CCAMLR is a complex process requiring accurate scientific assessment (CCAMLR, 2009; Sylvester and Brooks, 2020) and unanimous agreement among member states (Brooks, 2013; Brooks et al., 2020). The Adélie penguin, recognized both as an ecosystem indicator (Agnew, 1997) and bioindicator species (Cusset et al., 2023), plays a key role in monitoring the health of the Antarctic marine ecosystem. Therefore, protection of its marine habitats may benefit the whole ecosystem. Our study highlights a relevant gap in the spatial coverage of critical moulting and wintering areas of this highly mobile species within the current EAMPA proposal. Re-assessment and potential extension of the proposal, together with implementation of a dynamic winter connection between EAMPA zones, may enhance the effectiveness of protection of migratory species. More broadly, such adaptations may improve the connectivity and resilience of the proposed MPA network within the Southern Ocean.

## CRediT authorship contribution statement

**Zuzana Zajková:** Writing – original draft, Visualization, Methodology, Investigation, Formal analysis, Data curation, Conceptualization.
**Akiko Kato:** Writing – review & editing, Supervision, Resources, Methodology, Investigation, Funding acquisition, Data curation, Conceptualization.
**Thierry Raclot:** Writing – review & editing, Resources, Investigation.
**Frederic Angelier:** Writing – review & editing, Resources, Investigation.
**Jean-Baptiste Thiebot:** Writing – review & editing, Resources, Investigation.
**Akinori Takahashi:** Writing – review & editing, Resources, Investigation, Funding acquisition.
**Yan Ropert-Coudert:** Writing – review & editing, Supervision, Resources, Project administration, Methodology, Investigation, Funding acquisition, Conceptualization.

## Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgements

The authors thank Coline Marciau and Timothée Poupart for collecting data during fieldwork at Dumont d'Urville station over several seasons. The logistic and financial support was provided by the Institut Polaire Français Paul-Émile-Victor through the programme 1091. We received additional funding from WWF-UK, the Ecos Sud Program (project PU20B01/U20B03) and the Japan Society for the Promotion of Science (Kakenhi Grant-in-Aid #26840153 and #22 K18432). ZZ was supported by the MOPGA post-doctoral grant 2020 from Campus France. This work acknowledges the Spanish government through the 'Severo Ochoa Centre of Excellence' accreditation (CEX2019-000928-S funded by MCIN/AEI 10.13039/5011000111033, ICM-CSIC), the project SOSPEN (Spanish National Plan for Scientific and Technical Research and Innovation, 2021, PID2021-1248310A-I00) and the project SEA-Sentinels (Spanish National Plan for Scientific and Technical Research and Innovation, 2023, CNS2022-135631).

This study is part of the long-term Studies in Ecology and Evolution (SEE-Life) program and the Zone Atelier Antarctique of the CNRS. This
work is a contribution to the Integrated Science to Inform Antarctic and
Southern Ocean Conservation (Ant-ICON) Scientific Research Pro-
gramme of the Scientific Committee on Antarctic Research (SCAR).

Penguin and Antarctica drawings used in the graphical abstract are
artwork of Lourdes Berzas.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.
org/10.1016/j.biocon.2025.111507.

Data availability

The tracking dataset generated and analyzed in this study is available
in the Movebank repository, study ID: 4778411162. Code is available
from https://doi.org/10.6084/m9 figshare.27947100.v2.

References

Agnew, D.J., 1997. Review—the CCAMLR ecosystem monitoring Programme. Antarc. Sci. 9, 235–242. https://doi.org/10.1017/S095410209700031X.

Ainley, D., Ribic, C.A., Fraser, W.R., 1994. Ecological structure among migrant and resident seabirds of the Scotia-Weddell Confluence Region. J. Anim. Ecol. 63, 347–364. https://doi.org/10.2307/5553.

Ainley, D.G., 2002. The Adélie Penguin: Bellwether of Climate Change. Columbia University Press.

Ainley, D.G., Russell, J., Jenouvrier, S., Woehler, E., Lyver, P.O., Fraser, W.R., Kooyman, G.L., 2010. Antarctic penguin response to habitat change as Earth's troposphere reaches 2°C above preindustrial levels. Ecol. Monogr. 80, 49–66. https://doi.org/10.1890/08-2289.1.

Ainley, D.G., Woehler, E.J., Lescroël, A., 2017. Birds and Antarctic Sea Ice. In: Sea Ice. John Wiley & Sons, Ltd, pp. 570–582. https://doi.org/10.1002/9781118778371.ch24.

Arrigo, R.K., van Dijken, G.L., 2003. Phytoplankton dynamics within 37 Antarctic coastal polynya systems. J. Geophys. Res. Oceans 108. https://doi.org/10.1029/2002JC001739.

Atkinson, A., Hill, S.L., Reiss, C.S., Pakhomov, E.A., Beaugrand, G., Tarling, G.A., Yang, G., Steinberg, D.K., Schmidt, K., Edwards, M., Rombolá, E., Perry, F.A., 2022. Stepping stones towards Antarctica: switch to southern spawning grounds explains an abrupt range shift in krill. Glob. Change Biol. 28, 1359–1375. https://doi.org/10.1111/gcb.16009.

Ballard, G., Toniolo, V., Ainley, D.G., Parkinson, C.L., Arrigo, K.R., Trathan, P.N., 2010. Responding to climate change: Adélie penguins confront astronomical and ocean boundaries. Ecology 91, 2056–2069. https://doi.org/10.1890/09-0688.1.

Ballard, G., Jongsomitj, D., Veloz, S.D., Ainley, D.G., 2012. Coexistence of mesopredators in an intact polar ocean ecosystem: the basis for defining a Ross Sea marine protected area. Biol. Conserv. 156, 72–82. https://doi.org/10.1016/j.biocon.2011.11.017. Seabirds and Marine Protected Areas planning.

Ballerini, T., Tavecchia, G., Olmastroni, S., Pezzo, F., Focardi, S., 2009. Nonlinear effects of winter sea ice on the survival probabilities of Adélie penguins. Oecologia 161, 253–265. https://doi.org/10.1007/s00442-009-1387-9.

Barbraud, C., Delord, C., Bost, C.A., Chaigne, A., Marteau, C., Weimerskirch, H., 2020. Population trends of penguins in the French southern territories. Polar Biol. 43, 835–850. https://doi.org/10.1007/s00300-020-02691-6.

Barracho, T., Bardon, R., Choquet, R., Houlin, A., Winterl, A., Beaulieu, M., Blanchard, P., Cornet, C.C., Cristofari, R., Raclot, T., Richter, S., Chatelain, N., Courteuisse, J., Brucker, M., Zitterbart, D.P., Lecomte, M., Bohec, C.L., 2024. Declining juvenile survival of Adélie penguins in Antarctica. https://doi.org/10.1101/2024.08.23.609289.

Baston, D., 2021. Exactextractr: fast extraction from raster datasets using polygons.

Bates, D., Mächler, M., Bolker, B., Walker, S., 2015. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48. https://doi.org/10.18637/jss.v067.i01.

Beal, M., Oppel, S., Handley, J., Pearmain, E.J., Morera-Pujol, V., Carneiro, A.P.B., Davies, T.E., Phillips, R.A., Taylor, P.R., Miller, M.G.R., Franco, A.M.A., Catry, I., Patricio, A.R., Regalla, A., Staniland, I., Boyd, C., Catry, P., Dias, M.P., 2021. track2KBA: an R package for identifying important sites for biodiversity from tracking data. Methods Ecol. Evol. 12, 2372–2378. https://doi.org/10.1111/2041-210X.13713.

Becker, S.L., Boyd, C., Handley, J.M., Raymond, B., Reisinger, R., Ropert-Coudert, Y., Apelgren, N., Davies, T.E., Lea, M.-A., Santos, M., Trathan, P.N., Van de Putte, A.P., Huckstadt, L.A., Charrassain, J.-B., Brooks, C.M., 2024. Scaling up ocean conservation through recognition of key biodiversity areas in the Southern Ocean from multispecies tracking data. Conserv. Biol. e14345. https://doi.org/10.1111/cobi.14345 n/a.

Bestley, S., Ropert-Coudert, Y., Bengtson Nash, S., Brooks, C.M., Cotté, C., Dewar, M., Friedlaender, A.S., Jackson, J.A., Labrousse, S., Lowther, A.D., McMahon, C.R., Phillips, R.A., Pistorius, P., Puskic, P.S., Reis, A.O. de A., Reisinger, R.R., Santos, M., Tarszisz, E., Tixier, P., Trathan, P.N., Wege, M., Wienecke, B., 2020. Marine ecosystem assessment for the Southern Ocean: birds and marine mammals in a changing climate. Front. Ecol. Evol. 8.

Bindoff, N.L., Rosenberg, M.A., Warner, M.J., 2000. On the circulation and water masses over the Antarctic continental slope and rise between 80 and 150°E. Deep Sea res. Part II Top. Stud. Oceanogr. 47, 2299–3236. https://doi.org/10.1016/S0967-0645 (00)00038-2.

BirdLife International, 2020. Adélie Penguin (Pygoscelis adeliae) - BirdLife Species Factsheet.

Black, C., Southwell, L., Emerson, L., Lunn, D., Hart, T., 2018. Time-lapse imagery of Adélie penguins reveals differential winter strategies and breeding site occupation. PLoS One 13, e0193532. https://doi.org/10.1371/journal.pone.0193532.

Black, C.E., 2016. A comprehensive review of the morphology of Pygoscelis penguins. Polar Biol. 39, 405–432. https://doi.org/10.1007/s00300-015-1807-8.

Bracegirdle, T.J., Connolly, W.M., Turner, J., 2008. Antarctic climate change over the twenty first century. J. Geophys. Res. Atmospheres 113. https://doi.org/10.1029/2007JD008933.

Brooks, C.M., 2013. Competing values on the Antarctic high seas: CCAMLR and the challenge of marine-protected areas. Polar J. 3, 277–300. https://doi.org/10.1080/2154896X.2013.854597.

Brooks, C.M., Crowder, L.B., Osterblom, H., Strong, A.L., 2020. Reaching consensus for conserving the global commons: the case of the Ross Sea, Antarctica. Conserv. Lett. 13, e12676. https://doi.org/10.1111/conl.12676.

Calenge, C., 2006. The package "adehabitat" for the R software: a tool for the analysis of space and habitat use by animals. Ecol. Model. 197, 516–519. https://doi.org/10.1016/j.ecolmodel.2006.03.017.

CCAMLR, 2008. Conservation measure 51-02. Precautionary Catch Limitation on *Euphausia superba* in Statistical Division 58.4.1. Hobart, Australia, 27 October - 7 November 2008.

CCAMLR, 2009. Resolution 31/XXVIII. Best available science.

CCAMLR, 2019. Report of the thirty-eight meeting of the commission. CCAMLR-38/21. Proposal to establish an East Antarctic marine protected area. Hobart, Australia, 21 October - 1 November 2019.

Che-Castaldo, C., Jenouvrier, S., Youngflesh, C., Shoemaker, K.T., Humphries, G., McDowall, P., Landrum, L., Holland, M.M., Li, Y., Ji, R., Lynch, H.J., 2017. Pan-Arctic analysis aggregating spatial estimates of Adélie penguin abundance reveals robust dynamics despite stochastic noise. Nat. Commun. 8, 832. https://doi.org/10.1038/s41467-017-00890-0.

Cherel, Y., 2008. Isotopic niches of emperor and Adélie penguins in Adélie land, Antarctica. Mar. Biol. 154, 813–821. https://doi.org/10.1007/s00227-008-0974-3.

Chown, S.L., Brooks, C.M., 2019. The state and future of Antarctic environments in a global context. Annu. Rev. Environ. Resour. 44, 1–30. https://doi.org/10.1146/annurev-environ-101718-033236.

Cimino, M.A., Lynch, H.J., Saba, V.S., Oliver, M.J., 2016. Projected asymmetric response of Adélie penguins to Antarctic climate change. Science. Rep. 6, 28785. https://doi.org/10.1038/srep28785.

Clarke, J., Kerry, K., Fowler, C., Lawless, R., Eberhard, S., Murphy, R., 2003. Post-fledging and winter migration of Adélie penguins Pygoscelis adeliae in the Mawson region of East Antarctica. Mar. Ecol. Prog. Ser. 248, 267–278. https://doi.org/10.3354/meps248267.

Constable, A.J., Melbourne-Thomas, J., Corney, S.P., Arrigo, K.R., Barbraud, C., Barnes, D.K.A., Bindoff, N.L., Boyd, P.W., Brandt, A., Costa, D.P., Davidson, A.T., Ducklow, H.W., Emerson, L., Fukuchi, M., Gutt, J., Hindell, M.A., Hofmann, E.E., Hosie, G.W., Iida, T., Jacob, S., Johnston, N.M., Kawaguchi, S., Kokubun, N., Koubbi, P., Lea, M.-A., Makhado, A., Massom, R.A., Meiners, K., Meredith, M.P., Murphy, E.J., Nicol, S., Reid, K., Richerson, K., Riddle, M.J., Rintoul, S.R., Smith Jr., W.O., Southwell, C., Stark, J.S., Sumner, M., Swadling, K.M., Takahashi, K. T., Trathan, P.N., Welsford, D.C., Weimerskirch, H., Westwood, K.J., Wienecke, B.C., Wolf-Gladrow, D., Wright, S.W., Xavier, J.C., Ziegler, P., 2014. Climate change and Southern Ocean ecosystems I: how changes in physical habitats directly affect marine biota. Glob. Change Biol. 20, 3004–3025. https://doi.org/10.1111/gcb.12623.

Croxall, J.P., 1982. Energy costs of incubation and moult in petrels and penguins. J. Anim. Ecol. 51, 177–194. https://doi.org/10.2307/4318.

Cusset, F., Bustamante, P., Carravieri, A., Bertin, C., Brasso, R., Corsi, I., Dunn, M., Emmerson, L., Guillou, G., Hart, T., Juáres, M., Kato, A., Machado-Gaye, A.L., Michelot, C., Olmastroni, S., Polito, M., Raclot, T., Santos, M., Schmidt, A., Southwell, C., Soutullo, A., Takahashi, A., Thiebot, J.-B., Trathan, P., Vivion, P., Waluda, C., Fort, J., Cherel, Y., 2023. Circumpolar assessment of mercury contamination: the Adélie penguin as a bioindicator of Antarctic marine ecosystems. Ecotoxicology 32, 1024–1049. https://doi.org/10.1007/s10646-023-02709-9.

Dahood, A., de Mutsert, K., Watters, G.M., 2020. Evaluating Antarctic marine protected area scenarios using a dynamic food web model. Biol. Conserv. 251, 108766. https://doi.org/10.1016/j.biocon.2020.108766.

David, C.L., Schaafsma, F.L., van Franeker, J.A., Pakhomov, E.A., Hunt, B.P.V., Lange, B. A., Castellani, G., Brandt, A., Flores, H., 2021. Sea-ice habitat minimizes grazing impact and predation risk for larval Antarctic krill. Polar Biol. 44, 1175–1193. https://doi.org/10.1007/s00300-021-02868-7.

Davies, T.E., Carneiro, A.P.B., Tarzia, M., Wakefield, E., Hennicke, J.C., Frederiksen, M., Hansen, E.S., Campos, B., Hazin, C., Lascelles, B., Anker-Nilssen, T., Arnaudóttir, H., Barrett, R.T., Biscoito, M., Bollache, L., Boulinier, T., Catry, P., Ceia, F.R., Chastel, O., Christensen-Dalsgaard, S., Cruz-Flores, M., Danielsen, J., Daunt, F., Dunn, E., Egevang, C., Fagundes, A.I., Fayet, A.L., Fort, J., Furness, R.W., Gilg, O., González-Solís, J., Granadeiro, J.P., Grémillet, D., Guilford, T., Hanssen, S.A., Harris, M.P., Hedd, A., Huffeldt, N.P., Jessopp, M., Kolbeinson, Y., Krietsch, J., Lang, J., Linnebjerg, J.F., Lorentsen, S.-H., Madeiros, J., Magnusdottir, E., Mallory, M.L., McFarlane Tranquilla, L., Merkel, F.R., Militão, T., Moe, B., Montevecchi, W.A., Morera-Pujol, V., Mosbech, A., Neves, V., Newell, M.A., Olsen, B., Paiva, V.H., Peter, H.-U., Petersen, A., Phillips, R.A., Ramírez, I., Ramos, J.
A., Ramos, R., Ronconi, R.A., Ryan, P.G., Schmidt, N.M., Sigurðsson, I.A., Sittler, B., Steen, H., Stenhouse, I.J., Strøm, H., Systad, G.H.R., Thompson, P., Thórarsson, T. L., van Bemmelen, S.R.A., Wanless, S., Zino, F., Dias, M.P., 2021. Multispecies tracking reveals a major seabird hotspot in the North Atlantic. Conserv. Lett. 14, e12824. https://doi.org/10.1111/conl.12824.

Delord, K., Pinet, P., Pinaud, D., Barbraud, C., De Grissac, S., Lewden, A., Cherel, Y., Weimerskirch, H., 2016. Species-specific foraging strategies and segregation mechanisms of sympatric Antarctic fulmar petrels throughout the annual cycle. *Ibis* 158, 569-586. https://doi.org/10.1111/ibt.12365.

Delord, K., Barbraud, C., Pinaud, D., Letourner, D., Jaugeon, B., Goraguer, H., Lazure, P., Lormée, H., 2020. Movements of three alcid species breeding sympatically in Saint Pierre and Miquelon, northwestern Atlantic Ocean. J. Ornithol. 161, 359-371. https://doi.org/10.1007/s10336-019-01725-z.

Dunn, D.C., Harrison, A.-L., Curtice, C., DeLand, S., Donnelly, B., Fujioka, E., Heywood, E., Kot, C.Y., Poulin, S., Whitten, M., Åkesson, S., Alberini, A., Appeltans, W., Arcos, J.M., Bailey, H., Ballance, L.T., Block, B., Blondin, H., Boustany, A.M., Brenner, J., Catry, P., Cejudo, D., Cleary, J., Corkeron, P., Costa, D. P., Coyne, M., Crespo, G.O., Davies, T.E., Dias, M.P., Douvere, F., Ferretti, F., Formia, A., Freestone, D., Friedlaender, A.S., Frisch-Nwakanma, H., Froján, C.B., Gjerde, K.M., Glowka, L., Godley, B.J., Gonzalez-Solis, J., Granadeiro, J.P., Gunn, V., Hashimoto, Y., Hawkes, L.M., Hays, G.C., Hazin, C., Jimenez, J., Johnson, D.E., Luschi, P., Maxwell, S.M., McClellan, C., Modest, M., Notarbartolo di Sciara, G., Palacio, A.H., Palacios, D.M., Pauly, M., Rayner, M., Rees, A.F., Salazar, E.R., Secor, D., Sequeira, A.M.M., Spalding, M., Spina, F., Van Parijs, S., Wallace, B., Varo-Cruz, N., Virtue, M., Weimerskirch, H., Wilson, L., Woodward, B., Halpin, P.N., 2019. The importance of migratory connectivity for global ocean policy. Proc. R. Soc. B Biol. Sci. 286, 20191472. https://doi.org/10.1098/rsbp.2019.1472.

Dunn, M.J., Silk, J.R.D., Trathan, P.N., 2011. Post-breeding dispersal of Adélie penguins (*Pygoscelis adeliae*) nesting at Signy Island, South Orkney Islands. Polar Biol. 34, 205-214. https://doi.org/10.1007/s00300-010-0870-4.

Emmerson, L., Southwell, C., 2011. Adélie penguin survival: age structure, temporal variability and environmental influences. Oecologia 167, 951-965. https://doi.org/10.1007/s00442-011-2044-7.

Emmerson, L., Southwell, C., 2022. Environment-triggered demographic changes cascade and compound to propel a dramatic decline of an Antarctic seabird metapopulation. Glob. Change Biol. 29, 7234-7249. https://doi.org/10.1111/gcb.16437.

Erdmann, E.S., Ribic, C.A., Patterson-Fraser, D.L., Fraser, W.R., 2011. Characterization of winter foraging locations of Adélie penguins along the Western Antarctic Peninsula, 2001-2002. Deep Sea res. Part II top. Stud. Oceanogr., Understanding the Linkages between Antarctic Food Webs and the Environment: A Synthesis of Southern Ocean GLOBEC Studies 58, 1710-1718. https://doi.org/10.1016/j.dsr2.2010.10.054.

Fieberg, J., Kochanny, C.O., 2005. Quantifying home-range overlap: the importance of the utilization distribution. J. Wildl. Manag. 69, 1346-1359. https://doi.org/10.2193/0022-541X(2005)69[1346:QHOTIO]2.0.CO;2.

Forcada, J., Trathan, P.N., 2009. Penguin responses to climate change in the Southern Ocean. Glob. Change Biol. 15, 1618-1630. https://doi.org/10.1111/j.1365-2486.2009.01909.x.

Freitars, C., 2012. ArgoFiter: Argos locations filter.

Gilbert, E., Holmes, C., 2024. 2023's Antarctic Sea ice extent is the lowest on record. Weather 79, 46-51. https://doi.org/10.1002/wea.4518.

Gimeno, M., Giménez, J., Chiaradia, A., Davis, L.S., Seddon, P.J., Ropert-Coudert, Y., Reisinger, R.R., Coll, M., Ramírez, F., 2024. Climate and human stressors on global penguin hotspots: current assessments for future conservation. Glob. Change Biol. 30, e17143. https://doi.org/10.1111/gcb.17143.

Green, C.-P., Green, D.B., Ratcliffe, N., Thompson, D., Lea, M.-A., Baylis, A.M.M., Bond, A.L., Bost, C.-A., Crofts, S., Cuthbert, R.J., González-Solis, J., Morrison, K.W., Poisbleau, M., Pütz, K., Rey, A.R., Ryan, P.G., Sagar, P.M., Steinfurth, A., Thiebot, J.-B., Tierney, M., Whitehead, T.O., Witherspoon, S., Hindell, M.A., 2023. Potential for redistribution of post-moulf habitat for Eudyptes penguins in the Southern Ocean under future climate conditions. Glob. Change Biol. 29, 648-667. https://doi.org/10.1111/gcb.16500.

Handley, J., Rouyer, M.-M., Pearman, E.J., Warwick-Evans, V., Teschke, K., Hinke, J.T., Lynch, H., Emmerson, L., Southwell, C., Griffith, G., Cárdenas, C.A., Franco, A.M.A., Trathan, P., Dias, M.P., 2021. Marine important bird and biodiversity areas for penguins in Antarctica, targets for conservation action. Front. Mar. Sci. 7.

Hazen, E., Maxwell, S., Bailey, H., Bograd, S., Hamann, M., Gaspar, P., Godley, B., Shillinger, G., 2012. Ontogeny in marine tagging and tracking science: technologies and data gaps. Mar. Ecol. Prog. Ser. 457, 221-240. https://doi.org/10.3354/meps09857.

Hindell, M.A., Reisinger, R.R., Ropert-Coudert, Y., Hückstädt, L.A., Trathan, P.N., Bornemann, H., Charrassin, J.-B., Chown, S.L., Costa, D.P., Danis, B., Lea, M.-A., Thompson, D., Torres, L.G., Van de Putte, A.P., Alderman, R., Andrews-Goff, V., Arthur, B., Ballard, G., Bengtson, J., Bester, M.N., Blix, A.S., Boehme, L., Bost, C.-A., Boveng, P., Cleeland, J., Constantine, R., Corney, S., Crawford, R.J.M., Dalla Rosa, L., de Bruyn, P.J.N., Delord, K., Descamps, S., Double, M., Emmerson, L., Fedak, M., Friedlaender, A., Gales, N., Goebel, M.E., Goetz, K.T., Guinet, C., Goldsworthy, S.D., Harcourt, R., Hinke, J.T., Jeros, K., Kato, A., Kerry, K.R., Kirkwood, R., Kooyman, G.L., Kovacs, K.M., Lawton, K., Lowerth, A.D., Lydersen, C., Lyver, P.O., Makhado, A.B., Márquez, M.E.I., McDonald, B.I., McMahon, C.R., Muelbert, M., Nachtsheim, D., Nicholls, K.W., Nordøy, E.S., Olmstedson, S., Phillips, R.A., Pistorius, P., Plötz, J., Pütz, K., Ratcliffe, N., Ryan, P.G., Santos, M., Southwell, C., Staniland, I., Takahashi, A., Tarroux, A., Trivelpiece, W., Wakefield, E., Weimerskirch, H., Wienecke, B., Xavier, J.C., Witherspoon, S., Jonsen, I.D., Raymond, B., 2020. Tracking of marine predators to protect Southern

Ocean ecosystems. Nature 580, 87-92. https://doi.org/10.1038/s41586-020-2126-y.

Hinke, J.T., Polito, M.J., Goebel, M.E., Jarvis, S., Reiss, C.S., Thorrold, S.R., Trivelpiece, W.Z., Watters, G.M., 2015. Spatial and isotopic niche partitioning during winter in chinstrap and Adélie penguins from the South Shetland Islands. Ecosphere 6, art125. https://doi.org/10.1890/ES14-00287.1.

Houstan, A., Zitterbart, D.P., Heerah, K., Eisen, O., Planas-Bielsa, V., Fabry, B., Le Bohec, C., 2022. Juvenile emperor penguin range calls for extended conservation measures in the Southern Ocean. R. Soc. Open Sci. 9, 211708. https://doi.org/10.1098/rosos.211708.

Hückstädt, L.A., Pinones, A., Palacios, D.M., McDonald, B.I., Dinniman, M.S., Hofmann, E.E., Burns, J.M., Crocker, D.E., Costa, D.P., 2020. Projected shifts in the foraging habitat of craneater seals along the Antarctic peninsula. Nat. Clim. Chang. 10, 472-477. https://doi.org/10.1038/s41558-020-0745-9.

Hyrenbach, K.D., Forney, K.A., Dayton, P.K., 2000. Marine protected areas and ocean basin management. Aquat. Conserv. Mar. Freshw. Ecosyst. 10, 437-458. https://doi.org/10.1002/1099-0755(200011)12:10<6:437:AID-AQC425>3.0.CO;2-Q.

Iles, D.T., Lynch, H., Ji, R., Barbraud, C., Delord, K., Jenouvrier, S., 2020. Sea ice predicts long-term trends in Adélie penguin population growth, but not annual fluctuations: results from a range-wide multiscale analysis. Glob. Change Biol. 26, 3788-3798. https://doi.org/10.1111/gcb.15085.

Jafari, V., Zitterbart, D., Careddu, G., Sporta Caputi, S., Calizza, E., Rossi, L., Costantini, M.L., 2021. Spatial and temporal diet variability of Adélie (Pygoscelis adeliae) and emperor (Aptenodytes forsteri) penguin: a multi tissue stable isotope analysis. Polar Biol. 44, 1869-1881. https://doi.org/10.1007/s00300-021-02925-1.

Jenouvrier, S., Barbraud, C., Weimerskirch, H., 2006. Sea ice affects the population dynamics of Adélie penguins in Terre Adélie. Polar Biol. 29, 413-423. https://doi.org/10.1007/s00300-005-0073-6.

Jongsomjit, D., Escroël, A., Schmidt, A.E., Lisovski, S., Ainley, D.G., Hines, E., Elrod, M., Dugger, K.M., Ballard, G., 2024. Going with the floe: sea-ice movement affects distance and destination during Adélie penguin winter movements. Ecology 105, e4196. https://doi.org/10.1002/ecy.4196.

Juáres, M.A., Santos, M., Negrete, J., Mennucci, J.A., Perchivale, P.J., Casaux, R., Coria, N.R., 2015. Adélie penguin population changes at stranger point: 19 years of monitoring. Antarct. Sci. 27, 455-461. https://doi.org/10.1017/S0954102015000152.

Juáres, M.A., Santos, M., Mennucci, J.A., Coria, N.R., Mariano-Jelicich, R., 2016. Diet composition and foraging habits of Adélie and gentoo penguins in three different stages of their annual cycle. Mar. Biol. 163, 105. https://doi.org/10.1007/s00227-016-2886-y.

Kato, A., Ropert-Coudert, Y., Naito, Y., 2002. Changes in Adélie penguin breeding populations in Lützow-Holm Bay, Antarctica, in relation to sea-ice conditions. Polar Biol. 25, 934-938. https://doi.org/10.1007/s00300-002-0434-3.

Krüger, L., Ramos, J.A., Xavier, J.C., Grémillet, J., González-Solis, J., Petry, M.V., Phillips, R.A., Wanless, R.M., Paiva, V.H., 2018. Projected distributions of Southern Ocean albatrosses, petrels and fisheries as a consequence of climatic change. Ecography 41, 195-208. https://doi.org/10.1111/ecog.02590.

Labrousse, S., Orgeret, F., Solow, A.R., Barbraud, C., Bost, C.A., Sallée, J.-B., Weimerskirch, H., Jenouvrier, S., 2019. First odyssey beneath the sea ice of juvenile emperor penguins in East Antarctica. Mar. Ecol. Prog. Ser. 609, 1-16. https://doi.org/10.3354/meps12831.

Lascelles, B.G., Taylor, P.R., Miller, M.G.R., Dias, M.P., Oppel, S., Torres, L., Hedd, A., Le Corre, M., Phillips, R.A., Shaffer, S.A., Weimerskirch, H., Small, C., 2016. Applying global criteria to tracking data to define important areas for marine conservation. Divers. Distrib. 22, 422-431. https://doi.org/10.1111/ddi.12411.

Lenth, R.V., Bolker, B., Buerkner, P., Herve, M., Jung, M., Love, J., Miguez, F., Piaskowski, J., Riebl, H., Singmann, H., 2022. Emennes: estimated marginal means, aka least-squares means.

Ludescher, J., Yuan, N., Bunde, A., 2019. Detecting the statistical significance of the trends in the Antarctic Sea ice extent: an indication for a turning point. Clim. Dyn. 53, 237-244. https://doi.org/10.1007/s00382-018-4579-3.

Lynch, H.J., LaRue, M.A., 2014. First global census of the Adélie penguin. Auk 131, 457-466. https://doi.org/10.1642/AUK-14-31.1.

Lyver, P.O., Barron, M., Barton, K.J., Ainley, D.G., Pollard, A., Gordon, S., McNeill, S., Ballard, G., Wilson, P.R., 2014. Trends in the breeding population of Adélie penguins in the Ross Sea, 1981-2012: a coincidence of climate and resource extraction effects. PLoS One 9, e91188. https://doi.org/10.1371/journal.pone.0091188.

Maxwell, S., Gjerde, K., Conners, M., Crowder, L., 2020. Mobile protected areas for biodiversity on the high seas. Science 367, 252-254. https://doi.org/10.1126/science.aaz9327.

Maxwell, S.M., Hazen, E.L., Lewison, R.L., Dunn, D.C., Bailey, H., Bograd, S.J., Briscoe, D.K., Fossette, S., Hobday, A.J., Bennett, M., Benson, S., Caldwell, M.R., Costa, D.P., Dewar, H., Eguchi, T., Hazen, L., Kohin, S., Sippel, T., Crowder, L.B., 2015. Dynamic Ocean management: defining and conceptualizing real-time management of the ocean. Mar. Policy 58, 42-50. https://doi.org/10.1016/j.marpol.2015.03.014.

McConnell, B.J., Chambers, C., Fedak, M.A., 1992. Foraging ecology of southern elephant seals in relation to the bathymetry and productivity of the Southern Ocean. Antarct. Sci. 4, 393-398. https://doi.org/10.1017/S0954102092000580.

Meredith, M., 2022. Polar regions, in: intergovernmental panel on climate change (IPCC). In: the ocean and cryosphere in a changing climate: special report of the intergovernmental panel on climate change. Cambridge university press, Cambridge, pp. 203-320. https://doi.org/10.1017/9781009157964.005.

Merkel, B., Phillips, R.A., Descamps, S., Yoccoz, N.G., Moe, B., Strøm, H., 2016. A probabilistic algorithm to process geolocation data. Mov. Ecol. 4, 26. https://doi.org/10.1186/s40462-016-0091-8.
Michelot, C., Kato, A., Raclot, T., Ropert-Coudert, Y., 2021. Adélie penguins foraging consistency and site fidelity are conditioned by breeding status and environmental conditions. PLoS One 16, e0244298. https://doi.org/10.1371/journal.pone.0244298.

Morley, S.A., Abele, D., Barnes, D.K.A., Cárdenas, C.A., Cotté, C., Gutt, J., Henley, S.F., Höfer, J., Hughes, K.A., Martin, S.M., Moffat, C., Raphael, M., Stammerjohn, S.E., Suckling, C.C., Tulloch, V.J.D., Waller, C.L., Constable, A.J., 2020. Global drivers on Southern Ocean ecosystems: changing physical environments and anthropogenic pressures in an earth system. Front. Mar. Sci. 7. https://doi.org/10.3389/fmar.2020.547188.

Oppel, S., Bolton, M., Carneiro, A.P.B., Dias, M.P., Green, J.A., Masello, J.F., Phillips, R. A., Owen, E., Quillfeldt, P., Beard, A., Bertrand, S., Blackburn, J., Boersma, P.D., Borges, A., Broderick, A.C., Catry, P., Cleasby, I., Clingham, E., Creuwels, J., Crofts, S., Cuthbert, R.J., Dallmeijer, H., Davies, D., Davies, R., Dilley, B.J., Dinis, H. A., Dossa, J., Dunn, M.J., Efe, M.A., Fayet, A.L., Figueiredo, L., Frederico, A.P., Gjerdrum, C., Godley, B.J., Granadeiro, J.P., Guilford, T., Hamer, K.C., Hazin, C., Hedd, A., Henry, L., Hernández-Montero, M., Hinke, J., Kokubun, N., Leat, E., Tranquilla, L.M., Metzger, B., Militão, T., Montrond, G., Mullié, W., Padget, O., Pearmain, E.J., Pollet, I.L., Pütz, K., Quintana, F., Ratcliffe, N., Ronconi, R.A., Ryan, P.G., Saldanha, S., Shoji, A., Sim, J., Small, C., Soanes, L., Takahashi, A., Trathan, P., Trivelpiece, W., Veen, J., Wakefield, E., Weber, N., Weber, S., Zango, L., Daunt, F., Ito, M., Harris, M.P., Newell, M.A., Wanless, S., González-Solís, J., Croxall, J., 2018. Spatial scales of marine conservation management for breeding seabirds. Mar. Policy 98, 37–46. https://doi.org/10.1016/j.marpol.2018.08.024.

Orsi, A.H., Whitworth, T., Nowlin, W.D., 1995. On the meridional extent and fronts of the Antarctic Circumpolar Current. Deep Sea res. Part Oceanogr. Res. Pap. 42, 641–673. https://doi.org/10.1016/0967-0637(95)00021-W.

Ouled-Cheikh, J., March, D., Borras-Chavez, R., Drago, M., Goebel, M.E., Fariña, J.M., Gazo, M., Coll, M., Cardona, L., 2024. Future climate-induced distribution shifts in a sexually dimorphic key predator of the Southern Ocean. Glob. Change Biol. 30, e17191. https://doi.org/10.1111/gcb.17191.

Penney, R.L., 1967. Molt in the Adélie penguin. Auk 84, 61–71. https://doi.org/10.2307/4083255.

Portela, E., Rintoul, S.R., Herraz-Borreguero, L., Roquet, F., Bestley, S., van Wijk, E., Tamura, T., McMahon, C.R., Guinet, C., Harcourt, R., Hindell, M.A., 2022. Controls on dense shelf water formation in four East Antarctic polynyas. J. Geophys. Res. Oceans 127. https://doi.org/10.1029/2022JC018804 e0222JC018804.

Purich, A., Doddridge, E.W., 2023. Record low Antarctic Sea ice coverage indicates a new sea ice state. Commun. Earth Environ. 4, 1–9. https://doi.org/10.1038/s43247-023-00961-9.

R Core Team, 2021. R: A Language and Environment for Statistical Computing.

Ratcliffe, N., Takahashi, A., Oulton, C., Fukuda, M., Fry, B., Crofts, S., Brown, R., Adlard, S., Dunn, M.J., Trathan, P.N., 2014. A leg-band for mounting geolocator tags on penguins. Mar. Ornithol. 42, 23–26.

Raymond, B., Lea, M.-A., Patterson, T., Andrews-Goff, V., Sharples, R., Charrassin, J.-B., Cottin, M., Emmerson, L., Gales, N., Gales, R., Goldsworthy, S.D., Harcourt, R., Kato, A., Kirkwood, R., Lawton, K., Ropert-Coudert, Y., Southwell, C., van den Hoff, J., Wienecke, B., Woehler, E.J., Wotherspoon, S., Hindell, M.A., 2015. Important marine habitat off East Antarctica revealed by two decades of multi-species predator tracking. Ecography 38, 121–129. https://doi.org/10.1111/ecog.01021.

Reisinger, R.R., Brooks, C.M., Raymond, B., Freer, J.J., Cotté, C., Xavier, J.C., Trathan, P. N., Bornemann, H., Charrassin, J.-B., Costa, D.P., Danis, B., Hückstädt, L., Jonsen, I. D., Lea, M.-A., Torres, L., Van de Putte, A., Wotherspoon, S., Friedlaender, A.S., Ropert-Coudert, Y., Hindell, M., 2022a. Predator-derived bioregions in the Southern Ocean: characteristics, drivers and representation in marine protected areas. Biol. Conserv. 272, 109630. https://doi.org/10.1016/j.biocon.2022.109630.

Reisinger, R.R., Corney, S., Raymond, B., Lombard, A.T., Bester, M.N., Crawford, R.J.M., Davies, D., de Bruyn, P.J.N., Dilley, B.J., Kirkman, S.P., Makhado, A.B., Ryan, P.G., Schoombie, S., Stevens, K.L., Tosh, C.A., Wege, M., Whitehead, T.O., Sumner, M.D., Wotherspoon, S., Friedlaender, A.S., Cotté, C., Hindell, M.A., Ropert-Coudert, Y., Pistorius, P.A., 2022b. Habitat model forecasts suggest potential redistribution of marine predators in the southern Indian Ocean. Divers. Distrib. 28, 142–159. https://doi.org/10.1111/ddd.13447.

Ropert-Coudert, Y., Kato, A., Shiomi, K., Barbraud, C., Angelier, F., Delord, K., Poupart, T., Koubbi, P., Raclot, T., 2018. Two recent massive breeding failures in an Adélie penguin Colony call for the creation of a marine protected area in D'Urville Sea/Mertz. Front. Mar. Sci. 5. https://doi.org/10.3389/fmars.2018.00264.

Runge, C.A., Martin, T.G., Possingham, H.P., Willis, S.G., Fuller, R.A., 2014. Conserving mobile species. Front. Ecol. Environ. 12, 395–402. https://doi.org/10.1890/130237.

Sala, E., Giakoumi, S., 2018. No-take marine reserves are the most effective protected areas in the ocean. ICES J. Mar. Sci. 75, 1166–1168. https://doi.org/10.1093/icesjms/fsx059.

Santa Cruz, F., Krüger, L., Cárdenas, C.A., 2022. Spatial and temporal catch concentrations for Antarctic krill: implications for fishing performance and precautionary management in the Southern Ocean. Ocean Coast. Manag. 223, 106146. https://doi.org/10.1016/j.ocecoaman.2022.106146.

Santos, C.F., Agardy, T., Brooks, C., Gjerde, K.M., Payne, C., Wedding, L.M., Xavier, J.C., Crowder, L.B., 2024a. Taking climate-smart governance to the high seas. Science 384, 734–737. https://doi.org/10.1122/science.adp4379.

Santos, C.F., Agardy, T., Crowder, L.B., Day, J.C., Pinsky, M.L., Himes-Cornell, A., Reimer, J.M., García-Morales, S., Bennett, N.J., Lombard, A.T., Calado, H., Scherer, M., Flannery, W., Wedding, L.M., Gissi, E., 2024b. Key components of sustainable climate-smart ocean planning. NPJ Ocean Sustain. 3, 1–10. https://doi.org/10.1038/s44183-024-00045-x.

Schmidt, A.E., Lescroël, A., Lisovski, S., Elrod, M., Jongsomjit, D., Dugger, K.M., Ballard, G., 2023. Sea ice concentration decline in an important Adélie penguin melt area. Proc. Natl. Acad. Sci. 120, e2306840120. https://doi.org/10.1073/pnas.2306840120.

Shillinger, G.L., Bailey, H., Bograd, S.J., Hazen, E.L., Hamann, M., Gaspar, P., Godley, B. J., Wilson, R.P., Spotila, J.R., 2012. Tagging through the stages: technical and ecological challenges in observing life histories through biologging. Mar. Ecol. Prog. Ser. 457, 165–170. https://doi.org/10.3354/meps09816.

Siegert, M.J., Bentley, M.J., Atkinson, A., Bracegirdle, T.J., Convey, P., Davies, B., Downie, R., Hogg, A.E., Holmes, C., Hughes, K.A., Meredith, M.P., Ross, N., Rumble, J., Wilkinson, J., 2023. Antarctic extreme events. Front. Environ. Sci. 11. https://doi.org/10.3389/fenvs.2023.1229283.

Southwell, C., Emmerson, L., 2013. Large-scale occupancy surveys in East Antarctica discover new Adélie penguin breeding sites and reveal an expanding breeding distribution. Antarct. Sci. 25, 531–535. https://doi.org/10.1017/S0954102012001174.

Sreen, G., Kaleschke, L., Heygster, G., 2008. Sea ice remote sensing using AMSR-E 89-GHz channels. J. Geophys. Res. Oceans 113. https://doi.org/10.1029/2005JC003384.

Sylvester, Z.T., Brooks, C.M., 2020. Protecting Antarctica through co-production of actionable science: lessons from the CCAMLR marine protected area process. Mar. Policy 111, 103720. https://doi.org/10.1016/j.marpol.2019.103720.

Takahashi, A., Ito, M., Nagai, K., Thiebot, J.-B., Mitamura, H., Noda, T., Trathan, P.N., Tamura, T., Watanabe, Y.Y., 2018. Migratory movements and winter diving activity of Adélie penguins in East Antarctica. Mar. Ecol. Prog. Ser. 589, 227–239. https://doi.org/10.3354/meps12438.

Thiebot, J.-B., Ropert-Coudert, Y., Raclot, T., Poupart, T., Kato, A., Takahashi, A., 2019. Adélie penguins' extensive seasonal migration supports dynamic marine protected area planning in Antarctica. Mar. Policy 109, 103692. https://doi.org/10.1016/j.marpol.2019.103692.

Turner, J., Hosking, J.S., Bracegirdle, T.J., Marshall, G.J., Phillips, T., 2015. Recent changes in Antarctic Sea ice. Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 373, 20140163. https://doi.org/10.1098/rsta.2014.0163.

Viola, B., Wienecke, B., Green, C.-P., Corney, S., Raymond, B., Southwell, C., Sumner, M. D., Virtue, P., Wotherspoon, S., Emmerson, L., 2023. Marine distribution and habitat use by snow pretels Pagodroma nivea in East Antarctica throughout the non-breeding period. Front. Mar. Sci. 10. https://doi.org/10.3389/fmars.2023.1278229.

Viollat, L., Quéroué, M., Delord, K., Gimenez, O., Barbraud, C., 2024. Bottom-up effects drive the dynamic of an Antarctic seabird predator-prey system. Ecology 105, e4367. https://doi.org/10.1002/ecy.4367.

Weimerskirch, H., 2007. Are seabirds foraging for unpredictable resources? Deep Sea res. Part II Top. Stud. Oceanogr. 54, 211–223. https://doi.org/10.1016/j.dsr2.2006.11.013.

Widmann, M., Kato, A., Raymond, B., Angelier, F., Arthur, B., Chastel, O., Pellé, M., Raclot, T., Ropert-Coudert, Y., 2015. Habitat use and sex-specific foraging behaviour of Adélie penguins throughout the breeding season in Adélie land, East Antarctica. Mov. Ecol. 3, 30. https://doi.org/10.1186/s40462-015-0052-7.

Wilson, P.R., Ainley, Nur, N., Jacobs, Barton, K.J., Ballard, G., Comiso, J.C., 2001. Adélie penguin population change in the Pacific sector of Antarctica: relation to sea-ice extent and the Antarctic circumpolar current. Mar. Ecol. Prog. Ser. 213, 301–309. https://doi.org/10.3354/meps213301.

Zaldúa, N., Zajková, Z., Machado-Gaye, A.L., Franco-Trecu, V., Cosse, M., Ropert-Coudert, Y., Kato, A., Soutullo, A., 2024. Changing the focus: the need for cross-scale dynamic management in the Southern Ocean and implications for holistic conservation of Antarctic marine living resources. Mar. Policy 170, 106361. https://doi.org/10.1016/j.marpol.2024.106361.