The Emperor Penguin - Vulnerable to Projected Rates of Warming and Sea Ice

Home , Cape Colbeck, Cape Washington, Emperor Island, Halley Bay, Mertz Glacier, Rothschild Island

The emperor penguin - vulnerable to projected rates of warming and sea ice

loss

Philip N. Trathan1, *, Barbara Wienecke2, Christophe Barbraud3, Stéphanie

Jenouvrier3, 4, Gerald Kooyman5, Céline Le Bohec6, 7, David G. Ainley8, André

Ancel9, 10, Daniel P. Zitterbart11, 12, Steven L. Chown13, Michelle LaRue14, Robin

Cristofari15, Jane Younger16, Gemma Clucas17, Charles-André Bost3, Jennifer A.

Brown18, Harriet J. Gillett1, Peter T. Fretwell1

1 British Antarctic Survey, Natural Environment Research Council, High Cross, Madingley Road, Cambridge CB30ET UK

2 Australian Antarctic Division, 203 Channel Highway, Tasmania 7050, Australia

3 Centre d'Etudes Biologiques de Chizé, UMR 7372, Centre National de la Recherche Scientifique, 79360 Villiers en Bois, France

4 Biology Department, MS-50, Woods Hole Oceanographic Institution, Woods Hole, MA, USA

5 Scholander Hall, Scripps Institution of Oceanography, 9500 Gilman Drive 0204, La Jolla, CA 92093-0204, USA

6 Département d’Écologie, Physiologie, et Éthologie, Institut Pluridisciplinaire Hubert Curien (IPHC), Centre National de la Recherche

Scientifique, Unite Mixte de Recherche 7178, 23 rue Becquerel, 67087 Strasbourg Cedex 02, France

7 Scientific Centre of Monaco, Polar Biology Department, 8 Quai Antoine 1er, 98000 Monaco

8 H.T. Harvey and Associates Ecological Consultants, Los Gatos, California CA 95032 USA

9 Université de Strasbourg, IPHC, 23 rue Becquerel 67087 Strasbourg, France

10 CNRS, UMR7178, 67087 Strasbourg, France

11 Applied Ocean Physics and Engineering, Woods Hole Oceanographic Institution, Woods Hole, MA, USA

12 Department of Physics, University of Erlangen-Nuremberg, Henkestrasse 91, 91052 Erlangen, Germany

13 School of Biological Sciences, Monash University, VIC 3800 Australia

14 University of Minnesota, Minneapolis and St. Paul, Minnesota MN 55455 USA

15 University of Turku, Turku, FI-20014 Turun Yliopisto, Finland

16 Milner Centre for Evolution, University of Bath, Claverton Down, Bath, BA2 7AY UK

17 Atkinson Center for a Sustainable Future and Cornell Lab of Ornithology, Cornell University, Ithaca, NY 14850, USA

18 Information Services, University of Cambridge, 7 JJ Thomson Avenue, Cambridge CB3 0RB UK

* Author for correspondence (E-mail: [email protected]; Tel.: +44 1223 221602).

SUPPLEMENTARY MATERIAL, PART 1

Given the regional variability of climate change around the Antarctic (e.g. Turner et al., 2017; Rignot et al., 2019), different emperor penguin colonies are likely to be affected in different ways and over different temporal scales. Understanding the vulnerability of different habitat types will therefore help increase confidence when making projections about future scenarios. Individual colony projections are best viewed in the context of the local environment and geography (e.g. Kooyman et al., 2007,

Barber-Meyer et al., 2008, Kooyman & Ponganis, 2016).

To explore the current variation amongst colonies, we classified them according to current observed sea ice, near-surface temperature and wind (both zonal and meridional). We used sea ice concentration data obtained from satellite microwave sensors processed using the Bootstrap v3.1 algorithm (see https://nsidc.org/data/nsidc-0079); for near-surface temperature and winds, we used data from the ERA-Interim reanalysis (see https://www.ecmwf.int/en/forecasts/datasets/archive- datasets/reanalysis-datasets/era-interim). However, it should be noted that this explores variation in large-scale pack ice, and not specifically fast ice. The assumption is therefore made that “so as pack ice goes, so goes fast ice,” with a level of appreciable uncertainty. To some degree extensive pack ice cover does shield fast ice from ocean swells and wind waves, thus inhibiting early break up (Ainley et al., 2015; Kim et al., 2018). On the other hand, however, persistent winds can also retard fast ice formation, or lead to successive early break outs, at the same time contributing to more extensive pack ice (Ainley et al., 2010). Clearly, the situation is complex and data are sparse, stemming from the fact that microwave imagery cannot differentiate between ice-covered land and adjacent fast ice.

For both data sets, we extracted seasonal means for January through March, April through June, July through September and October through December for the years 1979-2017. Data were gridded at 99 km spatial resolution and the values for the cells nearest to each colony extracted; we then used K- means clustering based on a scree plot of the within groups sum of squares to estimate the appropriate number of clusters. Clustering was carried out in R (R version 3.3.1 Copyright © 2016 The

R Foundation for Statistical Computing) using RStudio (Version 1.0.136 – © 2009-2016 RStudio, Inc.) and the library cluster. Four clusters were evident based on the first two principal components (PC1 and PC2); these jointly explained 62.8% of the variance. PC1 showed positive weightings for temperature and negative weightings for both meridional and zonal winds. PC2 showed positive weightings for zonal winds and negative weightings for meridional winds. PC1 also separated sea ice with positive weightings for January through March, and negative weightings for April through June and July through September. Based on these principal components, the area of recent rapid warming in West Antarctic formed a separate group (SM Fig. 1, group 1), whilst the Ross Sea and the Weddell

Sea, i.e. the deepest embayments of the Antarctic continent, formed another group (SM Fig. 1, group

3); the coast line of East Antarctica comprised two groups (SM Fig. 1, groups 2 and 4). A small number of colonies from each group were located away from the majority of sites for that group. Identifying such different broad habitat types around the continent emphasises the range of habitats currently occupied by the species and the complexity of projecting change.

EMPIRICAL OBSERVATIONS AT SELECTED COLONIES

To better understand the factors that affect emperor penguin colonies we consider several as exemplars of differing environmental conditions, and differing levels of knowledge about individual sites. Many of the conditions and responses observed at each site almost certainly have wider relevance to colonies elsewhere, including those distant to national research stations. The colonies we highlight are (i) Halley Bay (SM Fig. 1, group 3), a colony next to an ice shelf demonstrating collapse following stochastic events during years with extreme low atmospheric pressure and strong winds; (ii)

Pointe Géologie (SM Fig. 1, group 4), a colony within an archipelago and that is now stable or recovering after extreme perturbation; (iii) Rothschild Island (SM Fig. 1, group 1), a colony in an area that is warming rapidly and vulnerable to ice shelf basal thinning and collapse; (iv) Taylor Glacier (SM

Fig. 1, group 4), a colony at a fixed location situated on land (v) Ledda Bay (SM Fig. 1, group 1), a colony where intermittent sea ice allows only occasional successful breeding; (vi) Riiser-Larsen

Peninsula/Gunnerus Bank and Umebosi Rock (SM Fig. 1, group 2), colonies where numbers were high but then suddenly decreased; and, (vii) Cape Washington and Cape Crozier (SM Fig. 1, group 3), colonies with adjacent colonies in the southwest Ross Sea that show inter-annual variability, but which are relatively stable.

(i) Halley Bay (75.55°S, 27.42°W)

The emperor penguin breeding site at Halley Bay, Coats Land, Weddell Sea, used to be the second largest of all known colonies (Fretwell et al., 2012). Records are sparse, but various sites in the creeks of the Brunt Ice Shelf have been used regularly by large numbers of breeding pairs (see historical counts in SM Table 1) that congregate at a location generally consistent between years. Since the operational use of remote sensing for population estimation (Barber-Meyer et al., 2007; Fretwell &

Trathan, 2009; Fretwell et al., 2012; Fretwell & Trathan, 2019), the site has been surveyed annually to estimate the colony size (SM Fig. 2). This has revealed fluctuations in numbers, and complete breeding failure between 2016 and 2018 due to the early break out of sea ice (Fretwell & Trathan, 2019).

Variability in population size is a feature of the colony, with several significant decreases; however, complete breeding failure has not been previously recorded. The first year of complete failure immediately followed the strongest El Niño in more than 60 years (Oceanic Niño Index, ONI; data available from https://climatedataguide.ucar.edu/climate-data/nino-sst-indices-nino-12-3-34-4-oni- and-tni), and one of the highest positive values of the Southern Annular Mode (SAM; data available from http://www.nerc-bas.ac.uk/icd/gjma/sam.html) (Fretwell & Trathan, 2019). In 2017, sea ice had blown out by October, and after sea ice reformed in November, only 2,000 adults were recorded but none were breeding. In October 2018, just a few hundred adults were present, but again, by the end of November the sea ice had blown out, suggesting another year of failed breeding. Fretwell & Trathan

(2019) suggested that following 2016, a proportion of the population probably had deferred breeding and had remained at sea in an unobservable state, a proportion was not breeding but had then become observable, while a large proportion, increasing over the three year period, had begun to

4 breed at the nearby Dawson-Lambton colony. This colony is only 55 km from the Halley Bay site, which is unusually close for emperor colony locations (Ancel et al., 2017). It is possible that some birds could also have moved to other colony locations farther away, but due to the natural variability of colony size, smaller changes are more difficult to associate with immigration.

Wind speeds at Halley Bay tend to be highest during August, September and October (Turner et al.,

2009c), sea ice dispersal at this time would be critical for chick survival, which may explain the colony location in a sheltered creek with firm fast ice. In 2016, average monthly atmospheric pressure was the lowest for September in over 30 years, whilst average wind speed was the highest for September over the same time frame; temperatures were also higher than average (Fretwell & Trathan, 2019).

The timing, frequency and duration of strong wind events in relation to key aspects of breeding will almost certainly be important for successful reproduction. Historically the colony has been situated within sheltered creeks at the front of the Brunt Ice Shelf. Following the ice breakout in 2016, ice shelf morphology also changed, plausibly associated with the strong wind events (Fretwell & Trathan,

2019). For those birds previously at Halley Bay, some would have either continued to visit Halley Bay, but were not breeding or had failed to fledge chicks, whilst many would have moved to the existing adjacent colony at Dawson-Lambton. For birds that had left Halley Bay, prospecting for new sites presumably involved complex social and behavioural processes, whilst the attractant forces of existing breeding aggregations would potentially have also remained important. When the Mertz Ice Tongue calved in February 2010, the local colony took two years to resettle, eventually selecting two new previously unused sites 19 km apart (Ancel et al., 2014). Further work on how emperors relocate to other breeding sites would therefore be informative, including for informing future model projections of population.

Determining how environmental correlates impact upon the breeding colony at Halley Bay, or elsewhere, remains a key challenge. Understanding the drivers, the frequency, and the consequences of stochastic events that lead to breeding failure is vital when projecting future population trajectories

5 in a warming environment. The recent observations at Halley Bay highlight that complete breeding failure can occur over consecutive seasons, even for large colonies and at high latitude locations.

Halley Bay represents approximately 8% of the global population. Hence, no breeding over a prolonged period is likely to have important demographic consequences, at least locally.

(ii) Pointe Géologie Archipelago (Dumont d'Urville) (66.70°S, 139.82°E)

At Pointe Géologie, Terre Adélie, emperor penguins congregate between the continent and the larger islands of the archipelago, at a site that has been consistent between years for many decades. Fast ice at this location breaks up late in the summer, though occasionally break out can be incomplete. The colony at Pointe Géologie is the longest continuously observed of all emperor colonies, having been monitored since its discovery in 1952. The number of breeding pairs is estimated annually from ground counts based on a standardised methodology (Barbraud & Weimerskirch, 2001; Barbraud et al., 2011).

When first observed, the colony numbered 5,000-6,300 breeding pairs (SM Fig. 3), but then decreased by around 50% between 1976 and 1982. From 1983 to 2005, the colony was relatively stable, averaging 2,900 breeding pairs, but after 2006 increased to reach 4,500 pairs in 2016. The decrease in the late 1970s and early 1980s has been attributed to an increase in apparent adult mortality, which in turn has been linked to a decrease in sea ice extent in the Dumont d’Urville Sea (Barbraud &

Weimerskirch, 2001; Jenouvrier et al., 2005a; 2009a; 2012). Furthermore, it has been noted that this period corresponded to an abrupt change in the meridional atmospheric circulation in East Antarctica

(Masson-Delmotte et al., 2003) and a shift in Southern Ocean conditions (Weimerskirch et al., 2003;

Ainley et al., 2005; Jenouvrier et al., 2005b). Following this, sea ice extent recovered and adult survival returned to a level adequate for population stability, but breeding success remained relatively low and highly variable until 1997. The latter prevented population recovery (Jenouvrier et al., 2009b).

Low breeding success may have been due to several years with extensive fast ice separating the colony from the foraging grounds, which probably increased foraging trip duration for breeding adults, with consequent chick starvation and chick mortality (Massom et al., 2009; but see Robertson et al. (2014)

6 who reported long distance travel over sea ice at Taylor Glacier). Since 1997, breeding success has remained above 40% (except in 2013 and 2014), and was particularly high (66% to 83%) between 2007 and 2012.

Understanding the decrease in apparent survival after the late 1970s is important. True mortality caused by a decrease in food resources following a major and multiyear decrease in sea ice extent may have played a central role (Barbraud & Weimerskirch, 2001; Jenouvrier et al., 2005a; 2009a; see also Barbraud et al., 2011). Suggestions that changes in the population trajectory were due to emigration of juvenile birds (Cristofari et al., 2016) requires further data, as they are not consistent with population model hindcasts (Jenouvrier et al., 2014); however, determining the historical level of emigration of individuals to the Mertz colony 260 km further east, or to other colonies, is currently not feasible.

In 2013 and 2014 there were massive breeding failures (89% and 97% offspring mortality, respectively); these were linked to extensive fast ice between the colony and foraging grounds

(Barbraud et al., 2015). This extensive fast ice may have resulted from several non-exclusive factors, such as changing wind intensity and direction, freshening of the upper ocean due to enhanced freshwater discharge from melting icebergs and fresh water ice, internal feedbacks within the near- surface-ice-ocean system, or calving of the Mertz Glacier tongue in mid-February 2010 accompanied by decreased polynya formation (Young et al., 2010; Tamura et al., 2012; Lecomte et al., 2016).

Population projections for this colony have been undertaken using modelled sea ice concentration trends in the d’Urville Sea, based on Intergovernmental Panel on Climate Change (IPCC) scenarios

(Ainley et al., 2010; Jenouvrier et al., 2012). However, uncertainties still remain and a detailed understanding about the respective effects of several environmental parameters will improve forecasting population responses to climate change. Major improvements that would enhance forecasts also include understanding the drivers of extreme events, both climatic and biological, such

7 as the massive breeding failures at Pointe Géologie in 2013, 2014 (van de Pol et al., 2017); see also

Fretwell & Trathan (2019).

(iii) Rothschild Island (69.52°S, 72.23°W)

The small emperor penguin colony of approximately 750 pairs at Lazarev Bay, Rothschild Island, near to Alexander Island off the west Antarctic Peninsula, was first reported in 2013 (LaRue et al., 2015); however, it is not known whether the colony existed prior to this time, or whether it was initially formed of birds from Emperor Island, some 225 km to the north, which relocated when conditions for breeding there deteriorated (Trathan et al., 2011).

Whatever the origins of the Rothschild colony, its situation is likely to change in the future, as the eastern end of Lazarev Bay is currently closed by the Wilkins Ice Shelf (SM Fig. 4), which has receded dramatically in recent years (Rankl et al., 2017). The ice shelf connected with Charcot Island until 2008, after which time the ice front receded rapidly. The small rocks and islets to the south of Rothschild

Island may pin remnants of the Wilkins Ice Shelf for some time, but eventually the eastern end of

Lazarev Bay will open and the protected breeding site will probably become less favourable, particularly given that both regional sea ice extent and duration have also reduced dramatically

(Stammerjohn et al., 2008; Hobbs et al., 2016).

Loss of sea ice will also reduce buffering of the Wilkins Ice Shelf (Massom et al., 2018), which is thinning because of warmer surface air temperatures, as well as intrusion of warming waters beneath the ice shelf. Basal melting of thin ice shelves like the Wilkins is very sensitive to upper-ocean and coastal processes that act over shorter time and space scales than those affecting basal melting of thicker

West Antarctic ice shelves, such as George VI and Pine Island Glacier (Padman et al., 2012; see also

Rignot et al., 2019). Glaciers terminating in warm Circumpolar Deep Water have undergone considerable retreat, whereas those further north, terminating in cooler waters, have not (Cook et al.,

2016). Changes in ocean-induced melting are the primary cause of retreat for glaciers in this region

(Cook et al., 2016). Ocean warming over the coming century (Vaughan et al., 2013) therefore presents a potential threat to emperor colonies adjacent to ice shelfs vulnerable to basal melting.

(iv) Taylor Glacier (67.45°S, 60.88°W)

The emperor penguin colony at Taylor Glacier, on the Mawson Coast of Mac.Robertson Land, is the only emperor penguin colony that is entirely located on land. Exposed rock on the eastern side of

Taylor Glacier rises in the southern part towards the plateau but offers a relatively flat area in the centre at 10 to 20 m elevation. The colony was discovered in October 1954 (Willing, 1958) and was monitored intermittently from 1957 to 1975, and then continuously since 1988 (Robertson et al.,

2014).

Since 1988, photographs of the colony have been taken (from an elevated position) shortly after midwinter, when males are still incubating and females have yet to return. In the early years, only ground counts were recorded, and though the methodology differed, the counts are considered accurate (Robertson et al., 2014). Initially, the colony contained about 3,700 breeding pairs compared to 2,900 pairs over the last two decades. The main reduction in the number of birds appears to have taken place during the late 1970s or early 1980s when the colony was not monitored, but congruent with the sharp decrease also recorded at Pointe Géologie.

However, at Taylor Glacier changes in sea ice extent during the breeding season are not thought to be the cause of decrease (Robertson et al., 2014). Along the Mawson Coast, fast ice is influenced by the local bathymetry (Fraser et al., 2012), with a band stretching 60 to 70 km north of and parallel to the coastline, making it less variable than at Terre Adélie. Thus, the current downward trajectory of the population at Taylor Glacier is not related to changes in regional or local sea ice extent. Understanding other drivers, possibly linked to changes in atmospheric circulation, remains a priority.

A population decrease of approximately 20% over the course of 13 years is important, and indicative of the ecological uncertainty for the species. Only a handful of colonies have been subjected to

9 continuous monitoring, yet at Taylor, even with such a record, it remains challenging to ascribe causes for the decrease.

(v) Ledda Bay (74.27°S, 131.24°W)

Ledda Bay, off Grant Island, Marie Byrd Land, is a shallow bay that borders the Getz Ice Shelf in Marie

Byrd Land, West Antarctica. An emperor colony at this location was first reported by Fretwell &

Trathan (2009), based on guano stains seen in satellite images dating from December 1999. In early

October 2010, faecal stains were detected in a small canyon between the island and the ice shelf (SM

Fig. 5), near a tongue of fast ice (~90 km long and 30 km at its widest) extending from the island. On

23 October 2010, a major storm dislodged the ice tongue and set it adrift. The guano-stained area disappeared, leaving open water. It is unknown whether the emperor penguins had been breeding. If they had, it is unlikely that the chicks would have survived, as at age 3.5 months their plumage would not have been water-proof.

This type of event is not unusual in this region. In 12 of the 18 years between 1999 and 2017, the sea ice had broken out before December (i.e. before emperor penguin chicks would have started their moult). Only during four years would the fast ice have lasted long enough for successful fledging to take place. Given these odds, it is highly unlikely that Ledda Bay is a suitable breeding site. The reasons why birds then congregate at Ledda Bay, if successful breeding is such a high-risk strategy, are unknown.

(vi) Gunnerus Bank (68.76°S, 34.38°E); Umebosi Rock (68.05°S, 43.02°E)

Emperor penguins at Riiser-Larsen Peninsula, Queen Maud Land (Kato et al., 2004), also known as

Gunnerus Bank (Fretwell et al., 2012), breed on fast ice at the foot of the ice shelf. The population size at Gunnerus has fluctuated between 4,000 and 9,000 pairs, when counted periodically during

August/September. During the mid-1990s, populations were two to three times greater than during the 1980s, but they suddenly decreased in 2000 back to their former level (Kato et al., 2004). At nearby

Umebosi Rock, population numbers followed a very similar pattern, but with between 200 and 600 pairs over the same time period, followed by a sudden decrease. Kato et al. (2004) reports that like other areas in East Antarctica, inter-annual variability in sea ice extent is considerable, and may affect provisioning rates and colony size.

Like most emperor penguin colonies, Gunnerus and Umebosi have been little studied. Nevertheless, major changes in numbers do occur, highlighting the need for continued monitoring and for further investigation into population dynamics and the causes of high levels of inter-annual variability.

(vii) Cape Washington (74.64°S, 165.38°E); Cape Crozier (77.47°S, 169.33°E)

Of the six emperor penguin colonies in the Ross Sea, only Cape Washington and Cape Crozier are generally accessible (by helicopter travel from national science facilities), though decadal-scale time series are available for most colonies as a result of aerial photography obtained from special flight missions (Kooyman et al., 2007; Barber-Meyer et al., 2008; Kooyman & Ponganis, 2016). The colony at Cape Washington may be one of the most stable of all emperor colonies. For example, there is little evidence of an effect at Cape Washington when in 2001 two major icebergs, C16 and B15A, caused dramatic effects at other nearby colonies; Cape Crozier, Beaufort Island and to some extent, Franklin

Island (Kooyman et al., 2007). B15A collided with the north-west tongue of the Ross Ice Shelf at Cape

Crozier and destroyed penguin breeding habitat such that the colony totally failed in 2001, and in the following years whilst the iceberg was still in place. Reduced reproductive output ranged from 0 to

40%, compared with the number of chicks produced in 2000. At Cape Crozier, incubating adults were either crushed, trapped in ravines, or abandoned the colony and subsequently occupied less suitable habitat (Kooyman et al., 2007). At Beaufort Island, 70 km to the northwest of Crozier, chick production decreased to 6% of the numbers in 2000.

The icebergs separated Beaufort Island from the Ross Sea Polynya, which formerly provided easily accessible feeding areas. Other calving events from the Ross Ice Shelf usually result in icebergs that follow a trajectory offshore from most colonies; however, the Cape Crozier colony forms within the

11 rifts of the Ross Ice Shelf and these change from year to year and consequently affect the reproductive output of the colony. Since 2006, conditions have enabled high reproductive output and there has been remarkable growth in the colony compared with the previous 50 years. Some degree of alternating oscillation in colony size between Beaufort and Crozier is evident, indicating inter-colony exchange of adults. Elsewhere in the Ross Sea, Cape Colbeck has also seen recent rapid growth, doubling between 1993 and 2012 (Kooyman & Ponganis, 2016). The event has also demonstrated a level of fluidity of occupation among closely adjacent colonies.

Such events have probably occurred infrequently since the West Antarctic Ice Sheet began to retreat

12,000 years ago. The event has, however, allowed assessment of recovery rates for one colony decimated by both adult and chick mortality, and the other by adult abandonment and chick mortality.

Kooyman & Ponganis (2016) propose that the apparent instability observed in individual colony population counts in the Ross Sea is a consequence of the natural history of emperors, including events that are catastrophic. Kooyman & Ponganis (2016) reason this is because: first, the species does not invest in a nest site; second, there is no long-term shared investment with a mate from year to year, as inter-annual mate fidelity is the lowest of all penguin species; and third, birds may not breed every year. These factors suggest that assessment of emperor penguin population trends requires counts at all colonies in a region and not simply at individual colonies.

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FIGURES

SM Fig. 1. Clustering of emperor penguin breeding sites based on current sea ice concentration, surface temperature and wind at each site (see text for further details).

SM Fig. 2. Variability in the emperor penguin population breeding at Windy Creek, Halley Bay.

Estimates of the number of breeding pairs (Fretwell & Trathan, 2019) were made from very high resolution satellite imagery following the methods of Fretwell et al., (2012); upper and lower 95% confidence intervals are shown.

SM Fig. 3. Variability in the numbers of emperor penguins breeding at Pointe Géologie, Terre Adélie.

Estimates were obtained from Barbraud & Weimerskirch (2001), Barbraud et al., (2011) and updated following the same method (Barbraud et al., unpublished data).

SM Fig. 4. Location of Rothschild Island and Emperor Island (no longer extant) emperor penguin colonies. The locations of historical ice fronts for the Wilkins Ice Shelf are shown, with the current ice shelf shown in blue.

SM Fig. 5. Satellite images from October 2010, showing the loss of the ice tongue at Ledda Bay, leading to complete breeding failure of the emperor penguin colony.

SM Table 1. Historical estimates for the Halley Bay emperor penguin colony

Range indicates where a range is given in the BAS report and Estimate where a single figure is given; if only a single figure is given in the Range column, it reflects a minimum estimate

BAS Archive Adults Adults Chicks Chicks Year Month Document number (Range) (Estimate) (Range) (Average) AD6/2HB/1956/Q1 1956 NA 21,000 – 27,000 AD6/2HB/1956/Q2 1956 January 6,000 – 8,000 AD6/2HB/1956/Q2 1956 April 8,000 – 14,000 AD6/2HB/1956/Q2 1956 May 8,000 AD6/2HB/1956/Q2 1956 August 7,000 AD6/2HB/1956/Q2 1956 September 20,000 AD6/2HB/1957/Q1 1957 April 10,000 – 15,000 AD6/2HB/1957/Q2 1957 April AD6/2HB/1957/Q3 1957 April 7,000 - >10,000 10,000 AD6/2HB/1957/Q3 1957 July 7,000 AD6/2HB/1957/Q3 1957 August 9,000 AD6/2HB/1957/Q3 1957 October huge AD6/2HB/1958/Q3 1958 January 15 250 AD6/2HB/1958/Q3 1958 February 1 9 AD6/2HB/1958/Q3 1958 March 15 AD6/2HB/1958/Q3 1958 April 16,000 AD6/2HB/1958/Q2 1958 May 20,000 – 25,000 AD6/2HB/1958/Q3 1958 May 20,000 AD6/2HB/1958/Q3 1958 July 15,000 – 20,000 10,000 AD6/2HB/1958/Q3 1958 August 10,000 AD6/2HB/1958/Q2 1958 August 12,000 AD6/2HB/1958/Q3 1958 October 2,000 AD6/2HB/1958/Q3 1958 December 1,000 AD6/2HB/1958/Q3 1959 January 600 5,000 AD6/2Z/1959/Q 1959 January 50 - 60 AD6/2Z/1959/Q 1959 February 0 AD6/2Z/1959/Q 1959 April 2,000 AD6/2Z/1959/Q 1959 May 15,000 – 20,000 AD6/2Z/1960/Q2 1960 April 11,700 AD6/2Z/1960/Q2 1960 May 19,900 – 20,300 20,000 AD6/2Z/1960/Q2 1960 June 11,900 6,000 AD6/2Z/1960/Q2 1960 July 9,000 AD6/2Z/1960/Q2 1960 August 12,000 – 13,000 8,100

BAS Archive Adults Adults Chicks Chicks Year Month Document number (Range) (Estimate) (Range) (Average) AD6/2Z/1960/Q2 1960 September 6,300 AD6/2Z/1960/Q2 1960 October 6,000 AD6/2Z/1960/Q2 1960 November 4,500 AD6/2Z/1960/Q2 1960 December AD6/2Z/1961/N 1961 May 19,000 AD6/2Z/1961/Q3 1961 May 23,500 AD6/2Z/1961/N 1961 July 9,000 8,200 AD6/2Z/1962/N1 1962 August 3,000 – 4,000 AD6/2Z/1963/N2 1963 August 8,000 400 AD6/2Z/1968/N 1968 April 15,000 AD6/2Z/1968/N 1968 August 5,000 AD6/2Z/1968/N 1968 December 12,500 AD6/2Z/1969/N 1969 September 15,000 AD6/2Z/1969/N 1970 January 1,000 3,000 – 4,000 AD6/2Z/1971/N 1971 May 20,000 AD6/2Z/1971/N 1971 July 37,000 AD6/2Z/1971/N 1971 August 15,000 14,000 AD6/2Z/1972/N 1972 October 3,500 – 4,000 7,000 AD6/2Z/1973/N 1973 August 5,000 – 6,000 AD6/2Z/1977/N2 1975 September 20,000 – 25,000 AD6/2Z/1977/N2 1975 September 25,000 – 30,000 AD6/2Z/1977/Q 1977 August 12,000 – 30,000 AD6/2Z/1977/Q 1977 October 15,000 AD6/2Z/1977/Q 1977 October 10,000 6,000 AD6/2Z/1977/Q 1977 December 4,580 14,750 AD6/2Z/1983/N 1983 April 5,000 – 7,000 AD6/2Z/1983/N 1983 May 18,000 – 22,000 AD6/2Z/1983/N 1983 July 7,000 – 10,000 AD6/2Z/1983/N 1983 July 11,000 AD6/2Z/1983/N 1983 August 10,000 – 12,000 AD6/2Z/1983/N 1983 September 25,000 AD6/2Z/1986/N 1986 October 15,700 AD6/2Z/1987/N 1987 November 14,300

SUPPLEMENTARY MATERIAL, PART 2

DEVELOPMENT OF A SPECIES ACTION PLAN FOR THE EMPEROR PENGUIN

Annex 8 to the Protocol on Environmental Protection to the Antarctic Treaty (hereafter the Protocol), emphasises that proposals for new designations, or revision of existing designations, of species as

Antarctic Specially Protected Species (Antarctic SPS), may be submitted by any Party, the CEP or SCAR to the CEP for consideration at its next meeting. Such proposals should include scientific justification and, for new designations, a draft Action Plan, to the extent possible with available data and knowledge.

On receipt of a proposal, the CEP should invite the Scientific Committee on Antarctic Research (SCAR) to assess the status of the species, if SCAR has not already made such an assessment as part of the proposal.

SCAR should use the most up-to-date IUCN criteria (consulting with appropriate experts in IUCN and elsewhere) to assess the risk of extinction of the species. Such assessments should, as a priority, take account of the global status and trends of the species, though the status and trends of the species at regional or local levels may also need to be assessed.

Periodic reports on the emperor penguin as an Antarctic SPS would enable the CEP and the Antarctic

Treaty Parties to assess the success of the Action Plan. Such reports could be prepared by SCAR, potentially in collaboration with the IUCN Species Survival Commission's Penguin Specialist Group,

BirdLife International, or by other groups of interested scientists from within the Treaty Parties.

Within the process outlined, the engagement of SCAR is vital. We therefore suggest that SCAR takes overall responsibility for developing an Action Plan for the emperor penguin. To inform this, we propose initial considerations should include:

OVERALL GOAL

To manage all direct and indirect human interactions with free-living emperor penguins that are potentially harmful, in order to reduce threats at every stage of their life cycle and thereby ensure their continued existence in the wild until such time that risks posed by climate change are mitigated.

SPECIFIC OBJECTIVES

• Liaise with the IUCN Species Survival Commission Penguin Specialist Group, and BirdLife

International to formally evaluate the IUCN Red List threat status of emperor penguins, initially as soon as practicable, and thereafter in keeping with the IUCN’s Red List schedule, or as requested by the Antarctic Treaty Consultative Parties (ATCPs) based on new scientific information.

• Liaise with relevant parts of the UN Framework Convention on Climate Change (UNFCCC), highlighting the scientific evidence relevant to the population status of emperor penguins.

• Establish SCAR’s Expert Group on Birds and Marine Mammals as the group to liaise with all interested and affected parties to provide regular synthetic updates on the status of emperor penguins.

• Convey the outcomes of relevant scientific assessments, with recommendations for concrete management action, to the ATCPs on a regular basis, or as any substantial changes might suggest, via

Working Papers submitted either via the CEP or directly by SCAR in keeping with Article 10.2 of the

Protocol on Environmental Protection to the Antarctic Treaty.

• As part of the five-yearly update of the Action Plan, provide information on the effectiveness of the management actions for emperor penguins and recommendations for changes to management actions if these are required. Doing so should involve best practise decision-science and engage all stakeholders for maximum efficacy, and should be preceded in the year prior to the update by an online forum or meeting to assess the effectiveness of actions.

• Initiate demographic studies to better document the functional relationships between demographic parameters across different life history stages and environmental fluctuations.

• Build on analyses by Ainley et al. (2010), Jenouvrier et al. (2014; 2017) and Abadi et al. (2017) to develop new analyses of how emperor penguins are projected to respond to climate change using

CMIP5 data, and when sufficiently mature, CMIP6 data. Consider the full circumpolar extent of emperor penguins with a special focus on inter-annual variation in breeding propensity (i.e. frequency of occurrence of breeding at colony sites) across different parts of the species range. Highlight the need for regional climate models that provide robust ecological projection capability at scales relevant to the ecology of emperor penguins. Develop modelling capacity beyond the next 100 years.

• Undertake population assessment studies to monitor emperor penguins at the colony scale, the regional scale and the circumpolar scale. Initiate ground counts and aerial counts to ground-truth and improve satellite remote-sensing population estimates. Evaluate population assessments based on satellite remote-sensing, with particular emphasis on short-term colony movement (see e.g.

Richter et al., 2018), repeated observation within the same breeding season, and improved image analysis techniques.

• Collate all available tracking data in order to undertake a gap analysis. Then, undertake new telemetry studies to better document the preferred habitats of emperor penguins at different times of the year and across different life history stages.

• Consider the energetic, physiological and behavioural capacity of emperor penguins to adapt to new breeding conditions and altered food web interactions, including altered prey availability and changed predation risks.

• Identify and collate information on other known threats to emperor penguins, especially those associated with human activities. Quantify all such threats, both spatially and temporally, in order to determine where and how management actions can mitigate the impacts of these threats and improve the survival of emperor penguin breeding populations.

• Engage across the international science community to develop best practice guidelines for specific scientific procedures relevant to emperor penguins. Initiate outreach to science facilities close to emperor penguin colonies, to increase awareness about the risks and threats to emperor penguins and to promote guidelines. Engage with the ATCPs and with the Council of Managers of National

Antarctic Programs to facilitate distribution of guidelines, including translations thereof to the predominant language used at a given facility.

• Liaise with the International Association of Antarctic Tour Operators (IAATO) to help develop species-specific guidelines for visitation to accessible emperor penguin colonies. Provide advice and recommendations about upper limits on tourist activities in order to contribute to the protection of emperor penguins in the long term. Link with such bodies to increase public awareness and need for conservation, including how to offset carbon footprints associated with Antarctic tourism.

• Liaise with relevant Associations of Zoos and Aquaria about living collections and breeding programmes, including the identification of wild-caught specimens of emperor penguins. Link with such bodies to increase public awareness and need for conservation.

• Assess and revise this draft Action Plan every five years.

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