domain: sde sdv

text:
Magali Lucia
email: m.lucia33@laposte.net

Hallvard Strøm

Paco Bustamante

Dorte Herzke

Geir W Gabrielsen

Contamination of four ivory gull (Pagophila eburnea) colonies in Svalbard in link with their trophic behaviour

Keywords: Ivory gull, Perfluorinated alkyl substances, Persistent organic pollutants, Arctic, Isotopes

The ivory gull (Pagophila eburnea) is a high-Arctic species considered endangered in most parts of its breeding range. Ivory gulls must cope with not only the reduction in sea ice cover triggered by climate change but also increasing contaminant loads due to changes in global contaminant pathways and the release of previously stored pollutants from melting snow and ice. This top predator may be affected by biomagnification processes of a variety of compounds with concentrations dramatically increasing from water to higher trophic levels.

The objective of this study was therefore to assess the contaminant bioaccumulation of this species in four colonies located on Barentsøya, Svalbard, in link with its trophic behaviour. To that end, contaminants, including organochlorines (OCs), brominated flame retardants (BFRs), and perfluorinated alkyl substances (PFASs), were determined in the blood (plasma and whole blood) of ivory gulls sampled over several years. Carbon-and nitrogen-stable isotopes were also determined in different tissues (feathers, plasma and red blood cells, or whole blood) to infer the trophic level (δ 15 N) and feeding habitat (δ 13 C) during both the breeding and moulting periods. The most quantitatively abundant contaminants found in the ivory gull were p,p'-DDE (dichlorodiphenyldichloroethylene), RPCB (polychlorobiphenyl), and PFOS (perfluorooctane sulphonate). Several compounds including most of the PFASs, trans-nonachlor, cis-nonachlor, and BDE-28 were correlated with nitrogen values. This study highlighted variability in trophic behaviour among individuals during the breeding and the moulting periods. Overall, similar feeding habitats and strategies were used between breeding sites which was echoed by similar contaminant levels.

Introduction

The Arctic region is currently undergoing dramatic environmental changes, with temperature increasing twice as fast as the global average and sea ice extent reaching a record minimum in 2012 with a reduction of 45 % compared with the 1979-2010 climatology (Lei et al. 2015). It is predicted that climate change will result in profound modifications of the Arctic marine food web and contaminant pathways in this region. The main reasons involved are temperature increase, more low-pressure activity, increased river discharges and run-off from glaciers, and accelerated rate of sea ice melting (ACIA 2004;[START_REF] Hoegh-Guldberg | The impact of climate change on the world's marine ecosystems[END_REF]. These climate-related variables may therefore influence the transport and thus the bioavailability of contaminants to Arctic biota [START_REF] Macdonald | Recent climate change in the Arctic and its impact on contaminant pathways and interpretation of temporal trend data[END_REF].

The Arctic acts as a sink for contaminants produced in industrialized parts of the word and transported northward by air, sea, and water masses (de [START_REF] De Wit | AMAP Assessment 2002: Persistent Organic Pollutants in the Arctic[END_REF]). Amongst contaminants, persistent organic pollutants of anthropogenic origin have especially been found in Arctic biota for decades [START_REF] Bourne | Polychlorinated biphenyls in North Atlantic seabirds[END_REF][START_REF] Gabrielsen | Chlorinated hydrocarbons in glaucous gulls (Larus hyperboreus) in the southern part of Svalbard[END_REF]. Recently, perfluorinated alkyl substances (PFASs) and brominated flame retardants (BFRs) also became widespread in the Arctic environment [START_REF] Butt | Levels and trends of poly-and perfluorinated compounds in the arctic environment[END_REF][START_REF] De Wit | Brominated flame retardants in the Arctic environment-Trends and new candidates[END_REF]. In particular, polybrominated diphenyl ethers (PBDE) constitute one of the main classes of brominated compounds used as flame-retardant additives that can be found in ecosystems and taxa [START_REF] Renner | What fate for bromimated fire retardants?[END_REF][START_REF] Covaci | Novel brominated flame retardants: A review of their analysis, environmental fate and behavior[END_REF]). Due to their propensity for persistence and bioaccumulation in wildlife, PFASs and BFRs have become of global environmental concern in addition to legacy organochlorine (OC) compounds.

Among wild populations, seabirds are particularly vulnerable to contaminants because they are relatively long-lived species that bioaccumulate contaminants throughout their life. Moreover, most seabirds are predators that feed at the top of the food web [START_REF] Hobson | A stable isotope (δ 13 C, δ 15 N) model for the North Water food web: implications for evaluating trophodynamics and the flow of energy and contaminants[END_REF]. They are thus affected by biomagnification processes of a variety of compounds (e.g. PFAS, polychlorinated biphenyl 'PCB') with concentrations dramatically increasing from water to higher trophic levels. Strong sub-lethal and/or lethal concentrations and adverse effects were observed at the individual [START_REF] Dawson | Mechanisms of endocrine disruption with particular reference to occurrence in avian wildlife: A review[END_REF] and population (Goutte et al. 2014a, b) levels. These adverse effects include endocrine disruption, impairment of the immune system, oxidative stress, or bone metabolism impairments [START_REF] Verreault | Effects of organochlorine contaminants on thyroid hormone levels in Arctic breeding glaucous gulls, Larus hyperboreus[END_REF]Bourgeon et al. 2012;Pellerin Plourde et al. 2013).

In aquatic systems, food constitutes the major exposure route of seabirds to contaminants. One of the main goals in ecotoxicology is therefore to investigate more precisely the trophic ecology of species to better understand exposure pathways and explain contaminant concentrations in animal populations (Roscales et al. 2010;Leat et al. 2013). Stable isotopes of carbon and nitrogen are useful tools to examine trophic relationships and/or origins of prey to elucidate broad-scale, inter-and intraspecific dietary patterns, and so to determine whether differences in foraging strategies explain variations in contaminant uptake [START_REF] Jardine | Applications, considerations, and sources of uncertainty when using stable isotope analysis in ecotoxicology[END_REF]). The basic isotopic concept is that an animal's chemical composition is directly influenced by what it consumes. Consumers are enriched in 15 N relative to their food and consequently, stable nitrogen isotope measurements (δ 15 N) serve as indicators of a consumer trophic position. By contrast, stable carbon ratios (δ 13 C) vary little along the food chain, and in the marine environment, δ 13 C values are mainly used to indicate the foraging habitats of predators (e.g. benthic versus pelagic habitats, inshore versus offshore; Hobson 1995).

The ivory gull (Pagophila eburnea) is a high-Arctic species that frequents ice-filled waters throughout the year. The main wintering grounds identified for northeast Atlantic populations (north Greenland, Svalbard and Franz Josef Land) of this long-distant migrant species are in south-east Greenland, along the Labrador sea ice edge and in the Bering Strait region [START_REF] Gilg | Postbreeding movements of northeast Atlantic ivory gull Pagophila eburnea populations[END_REF]Spencer et al. 2014). Adults have only a single moult per cycle, a strategy unique among gulls [START_REF] Howell | Molt of the Ivory Gull[END_REF]. Their prebasic moult starts in March and April and is mostly completed before the pre-laying to hatching period (mid-June to early August). The primary moult is then suspended at this time, and the moult of outermost primaries is concluded in late August or September. Consequently, moulting and breeding greatly overlap in the ivory gull, presumably an adaptation to the constraints of its high-latitude winter range and the brief Arctic summer [START_REF] Howell | Molt of the Ivory Gull[END_REF]. The ivory gull is considered endangered in most parts of its breeding range, especially in Canada, where studies documented an 80 % decline in numbers since the 1980s [START_REF] Gilchrist | Declines in abundance and distribution of the ivory gull (Pagophila eburnea) in Arctic Canada[END_REF]. Nevertheless, it is one of the world's most poorly known seabird species even though its high position in the marine food web makes it particularly sensitive to contaminant exposure [START_REF] Karnovsky | Distribution and diet of ivory gulls (Pagophila eburnea) in the North Water Polynya[END_REF]. Previous studies demonstrated that this free-ranging Arctic species is exposed to high contaminant concentrations along its distribution range in the Canadian, Norwegian, and Russian Arctic [START_REF] Braune | Levels and trends of organochlorines and brominated flame retardants in Ivory Gull eggs from the Canadian Arctic, 1976 to 2004[END_REF][START_REF] Miljeteig | High levels of contaminants in ivory gull Pagophila eburnea eggs from the Russian and Norwegian Arctic[END_REF][START_REF] Lucia | Circumpolar contamination in eggs of the high-arctic ivory gull Pagophila eburnea[END_REF]. It is thought that some ivory gulls specialize on scavenging remains of polar bear kills, whereas others feed mainly on polar cod (Boreogadus saida) and crustaceans associated with the ice edge [START_REF] Divoky | The pelagic feeding habits of ivory and Ross' gulls[END_REF][START_REF] Mehlum | Seabird distribution in the northern Barents Sea marginal ice-zone during late summer[END_REF][START_REF] Mehlum | The diet of High-Arctic seabirds in coastal and ice-covered, pelagic areas near the Svalbard archipelago[END_REF][START_REF] Karnovsky | Distribution and diet of ivory gulls (Pagophila eburnea) in the North Water Polynya[END_REF]. Overall, climate-related perturbations (e.g. reduction in sea ice cover, modification of the Arctic marine food web, modification of pollutant bioavailability) are expected to profoundly impact the trophic behaviour of the ivory gull and potentially increase its contaminant exposure.

Consequently, the aim of this study was to better understand the contaminant exposure and foraging strategies of the ivory gull considering the lack of data for this vulnerable seabird. Our objective was to describe contaminant exposure and trophic behaviour of four ivory gull colonies located on Barentsøya, Svalbard, to finally investigate their relationship.

Contaminants, encompassing a number of OCs, BFRs, and PFASs, were determined in the blood (plasma and whole blood) of ivory gulls sampled over 4 years. Carbon-and nitrogenstable isotopes were also determined in different tissues, including feathers and blood (plasma and red blood cells, or whole blood depending on the year) to investigate the foraging ecology during both the breeding and the moulting periods. The stable isotope method is based on timeintegrated assimilated food. Hence, the isotopic value of blood and feathers is representative of the isotopic niche of seabirds during the weeks preceding sampling and the moulting period, respectively.

Materials and methods

Sample collection and preparation

Ivory gulls were sampled for blood and ventral feathers between 2011 and 2014 in four breeding colonies (Auga, Freemanbreen, Hübnerbreen, Sigden, Fig. 1) on Barentsøya, Svalbard, and along the ice edge in Spring (April). When possible, both tissues were sampled on each bird (53 % of the samples). Moreover, different individuals were sampled among years. Birds were caught by the use of a single-catch closing net trap (spring trap) baited with a small piece of seal blubber. When it was possible, age and sex were determined, as well as morphometric measurements (e.g. mass, bill length, bill height, head-bill, wing length). Overall, whole blood was sampled for isotope analyses in 2011 (n = 6), 2012 (n = 5) and 2013 (n = 9), whereas plasma and red blood cells (erythrocytes) were obtained after centrifugation in the field (4000 rpm, 10 min) in 2013 (n = 38) and 2014 (n = 38). Ventral feathers were sampled in 2011 (n = 19), 2012 (n = 40), 2013 (n = 46), and 2014 (n = 34). Over the years, plasma and red blood cells were sampled in four colonies: Auga (n = 5), Freemanbreen (n = 27), Hübnerbreen (n = 19), and Sigden (n = 25), whereas whole blood was sampled in three colonies: Auga (n = 1), Freemanbreen (n = 8), and Hübnerbreen (n = 5), and the ice edge (n = 6), and feathers, in four colonies, Auga (n = 5), Freemanbreen (n = 71), Hübnerbreen (n = 30), Sigden (n = 25), and the ice edge (n = 8).

Of those samples, blood volumes were sufficient to analyse contaminants such as PFASs in plasma samples in 2013 (n = 38) and 2014 (n = 21), and whole blood in 2011 (n = 4), 2012 (n = 5) and 2013 (n = 1). Organochlorines and BFRs were analysed on fewer samples due to the higher volume required for the extraction protocol. Therefore, plasma samples were available in 2013 (n = 30) and 2014 (n = 9), and whole blood in 2011 (n = 4) and 2012 (n = 2). Over the years, PFASs were analysed in plasma samples from Auga (n = 5), Freemanbreen (n = 26), Hübnerbreen (n = 18), and Sigden (n = 10), and in whole blood samples from Auga (n = 1), Freemanbreen (n = 5), and on the ice edge (n = 4).

Organochlorines and BFRs were analysed in plasma samples from Auga (n = 2), Freemanbreen (n = 17), Hübnerbreen (n = 13), and Sigden (n = 7), and in whole blood samples from Freemanbreen (n = 2) and along the ice edge (n = 4). This difference in sampling method (whole blood versus plasma) is explained by the late capacity to centrifuge blood on a remote fieldwork on Barentsøya. Both tissues are useful for studying different contaminants. The use of whole blood has been recommended when analysing OCs and BFRs to avoid loss of contaminants present in the cellular fraction (Volz et al. 2001;Leslie et al. 2007). Serum or plasma can be used for analysis of many contaminants but it is notable that concentrations of some poly-and perfluoroalkyl substances (PFASs) in whole blood are approximately half those in serum or plasma because of the volume displacement of cellular components, which do not appear to function as a sorbent for these substances (Ehresman et al. 2007). All the blood samples, including plasmas and red blood cells, were kept frozen at -20 °C until further analyses. Ventral feathers were washed to remove oil and dirt in a chloroform-methanol solution (2:1) in an ultrasonic bath for 2 min. Afterward, they were rinsed in two consecutive pure methanol baths for a few seconds and dried at 40 °C for 48 h.

Nitrogen and carbon stable isotope analysis

Depending on birds and years, stable isotopes were determined in ventral feathers and either on the whole blood or on the plasma and red blood cells (see above). Analyses were performed at the UMR 7266 CNRS-Université de La Rochelle in France. Cleaned feathers of ivory gulls were chopped using surgical stainless-steel scissors and accurately weighed (±0.001 mg) to a range between 0.1 and 0.4 mg. Blood samples were freeze-dried, grounded, and then weighed with the same accuracy and in the same range of masses. All samples were placed in tin capsules for carbon-and nitrogen-stable isotope analysis and analysed using an elemental analyser (Flash EA 1112 fitted with a ''Zero Blank'' option, Thermo Scientific, Milan, Italy) coupled to an isotope ratio mass spectrometer (Delta V Advantage, Conflo IV interface, Smart EA option, Thermo Scientific, Bremen, Germany). The results are reported in δ unit notation (expressed in per mil relative to standards: Vienna Pee Dee Belemnite for δ 13 C and N2 in air for δ 15 N). Withinrun replicates of internal standards (acetanilide) were run, and values were on average -27 ± 0.03 ‰ and 1 ± 0.05 ‰ for δ 13 C and δ 15 N, respectively.

Determination of OCs and BFRs

OCs and BFRs were analysed from the plasma of 32 birds in 2013 and 9 birds in 2014. The whole blood of 4 birds in 2011 and 2 birds in 2012 was also analysed. Analyses were performed at the Norwegian Institute for Air Research (NILU) in Tromsø. Organochlorine pesticides (o,p' DDT,p,p' DDT,o,p' DDE,p,p' DDE,o,p' DDD,p,p' DDD,HCB,oxychlordane, were searched for. BFRs encompassed 8 PBDE congeners Isotope Laboratories: Woburn, MA, USA) were added to a blood sample of 0.7-1.5 ml. The sample was extracted twice with 6 ml of n-hexane, after denaturation with ethanol and a saturated solution of ammonium sulphate in water. Matrix removal on florisil columns, separation on an Agilent Technology 7890 GC (gas chromatography) and detection on an Agilent Technology 5975C MSD (mass spectrometry) were performed as described by [START_REF] Herzke | Perfluorinated and other persistent halogenated organic compounds in European shag (Phalacrocorax aristotelis) and common eider (Somateria mollissima) from Norway: a suburban to remote pollutant gradient[END_REF]. The limit of detection (LoD) was threefold the signal-to-noise ratio for the analysed BFRs and OCs and ranged between 0.6 and 14,596 pg g -1 wet weight (wet wt) for HCB and TBPA, respectively. For validation of the results, blanks (clean and empty glass tubes treated like a sample) were run for every 10 samples, while standard reference material (1589a human serum from NIST) was also run for every 10 samples. Blank samples were below the detection limit for most reported analytes, and results from samples were deemed acceptable. Prior to analysis, samples were extracted and prepared as described previously [START_REF] Powley | Matrix effect-free analytical methods for determination of perfluorinated carboxylic acids in environmental matrixes[END_REF]. A sample volume of 0.2 mL of plasma or whole blood was spiked with 20 µL of the internal standard, a 13 C perfluorinated compound mix, and subsequently extracted with 1 mL methanol in three consecutive 10 min ultrasonic treatments.

Determination of PFASs

After centrifugation, 0.8 mL of the supernatant solution was added to 25 mg ENVI-Carb and 50 µL glacial acetic acid and vortexed thoroughly. After additional centrifugation at 10,000 rpm for 10 min, 0.5 mL of the solution was transferred to a vial and 2040 pg of 3,7-br-PFDA as a recovery standard was added. Prior to measurement, 50 µL of a 2 mM aqueous ammonium acetate solution was added to the same volume of samples.

All standards were purchased as crystalline substances from Wellington with purities greater than 95 %. Instrumental measurement was carried out according to Hanssen et al. (2013).

Recoveries of the mass-labelled internal standards were 89 ± 12 % for 13 C PFHxS, 87 ± 14 % for 13 C PFOS, 96 ± 11 % for 13 C PFOA, 113 ± 31 % for 13 C PFNA, 104 ± 14 % for 13 C PFDA, 108 ± 14 % for 13 C PFUnDA, 126 ± 22 % for 13 C PFDoDA, and 136 ± 29 % for 13 C PFTeA.

Data treatment and statistical analyses

Several compounds that were detected or analysed in less than 60% of the samples were

Results

Isotopic values depending on the colony, year, and sex of birds

Trophic positions and foraging habitats, assessed respectively through the determination of δ 15 N and δ 13 C, of the ivory gull were investigated in the feathers, whole blood, plasma and red blood cells (Fig. 2). Figure 2 shows the mean isotopic values of the tissues studied. Individual variability was observed for each tissue. Stable carbon isotope values of feathers were especially variable, ranging between -20.8 and -17.5 ‰. Stable nitrogen isotope values in the plasma also ranged widely, varying between 13.0 and 16.3 ‰.

Stable isotope values were compared between colonies to identify any diverging trends in trophic behaviour between birds breeding on Barentsøya. Birds from the Sigden colony showed significant differences in their stable isotope values compared to birds coming from other colonies. Figure 3 Freemanbreen: -21.7 ± 0.1 ‰; p = 0.038). Similarly, sex could be considered as a confounding factor that may be responsible for differences observed between colonies. Unfortunately, it was not possible to sex all individuals used to study differences between colonies, especially in 2014. All the birds from Sigden were sampled that year, and only 7 individuals were sexed (F = 4, M = 3). However, when available, the number of males and females was balanced between colonies. For example, in 2013, numbers between males and females, if not equal, were in the same range (Freemanbreen: M = 12, F = 5; Auga: M = 1, F = 2; Hübnerbreen: M = 10, F = 6).

Consequently, the sex of birds was most likely not responsible for differences observed between colonies. For whole blood, differences appeared between birds sampled on the ice edge and those from Freemanbreen. Ivory gulls from the ice edge had significantly lower δ 15 N values (14.2 ± 0.3 %) than those from Freemanbreen (14.9 ± 0.2 %), Kruskal-Wallis test, p = 0.045).

However, birds from the ice edge and Freemanbreen were sampled on different years, 2011 and 2012-2013, respectively. It is therefore difficult to know whether this discrepancy is rather due to the year instead of the sampling location. In addition, feather values were similar between colonies for δ 15 N and δ 13 C.

The difference in stable isotope values between sampling years was investigated in feathers, plasma and red blood cells. The influence of year was not studied in whole blood because of the few available samples for this tissue. Overall, no differences were observed for feathers and plasma. Conversely, δ 13 C values in red blood cells were significantly higher in 2013 (-20.6 ± 0.1 ‰) compared to 2014 (-21.0 ± 0.1 ‰; p<0.0001, Mann-Whitney U test).

Finally, the influence of sex on stable isotope values was investigated. The only significant difference was between δ 13 C values of male (-20.6 ± 0.04 ‰, n = 29) and females (-20.8 ± 0.07 ‰, n = 16) in red blood cells (p = 0.044, Mann-Whitney U test).

Influence of the time, location, and sex on contaminant concentrations

Mean concentrations of PFASs, OCs and BFRs in plasma and whole blood of ivory gulls are presented in Tables 1 and2 for each sampling year. Firstly, the influence of time, therefore year, was investigated independently of colonies for each tissue. For PFASs, no significant differences were observed between sampling years for both tissues (Table 1). Plasma concentrations of BDE-100 and BDE-154 were, however, significantly higher in 2013 compared to 2014 (BDE-100: p = 0.002, BDE-154: p = 0.044), whereas whole blood concentrations were similar between years.

The influence of sampling location (colony) was consequently investigated, independently of the year and the sex of individuals. In plasma, discrepancies appeared for PFASs. Gulls captured at Auga displayed significantly lower PFOS, PFUnDA and PFDoDA concentrations than birds from Freemanbreen (PFOS: 14.9 ± 1.2 and 35.8 ± 4.0, PFUnDA: 7.2 ± 0.9 and 14.4 ± 1.3, PFDoDA: 1.33 ± 0.16 and 2.66 ± 0.24 ng g -1 wet wt for Auga and Freemanbreen, respectively; p<0.05, Kruskal-Wallis test). To exclude sex as confounding factor, PFAS concentrations were compared on females only. Similar differences occurred between Auga and Freemanbreen for PFOS, PFUnDA, and PFDoDA (p<0.05). Unfortunately, not enough samples were available in Auga to test for year as confounding factor. Organochlorine and BFR concentrations were not different between colonies for all the tissues studied.

Because of the potential maternal transfer of contaminants to eggs, sex-dependent differences in contaminant concentrations were also examined. The influence of this parameter appeared important for PFAS accumulation. Plasmatic concentrations of males (n = 28) were higher for all PFASs than females (n = 15), with the exception of PFNA and PFHxS (p<0.05, Mann-Whitney U test). In contrast, males (n = 22) displayed lower HCB concentrations in the plasma than females (n = 11; 7.19 ± 0.75 vs 9.62 ± 0.39 ng g -1 wet wt; p = 0.012, Mann-Whitney U test).

The relationship between contaminants and body mass of birds was investigated. Plasma concentrations of PFASs were positively correlated with the body mass of birds (r ranged between 0.27 for PFHxS and 0.51 for PFDA). Simultaneously, HCB, PCB-118, and BDE-99 plasma concentrations were negatively correlated with the body mass of ivory gulls (r = -0.42, -0.32 and -0.48, respectively; Spearman test, p<0.05).

Relationship between trophic position, feeding habitat and contaminant bioaccumulation

All colonies and years combined, PFAS concentrations were significantly correlated with d15N values in the plasma (r comprised between 0.37 for PFOS and 0.52 for PFTeA; p<0.05, Spearman test). Only PFHxS and PFNA concentrations were not significantly correlated with stable nitrogen isotope values. In contrast, δ 13 C values were not correlated with PFAS concentrations. The same trend was observed in whole blood. No correlations were observed between PFAS concentrations and δ 13 C values, whereas δ 15 N values were significantly correlated with most of the PFASs, with the exception of PFHxS and PFNA (r comprised between 0.66 for PFUnDA and 0.80 for PFTriA; p<0.05, Spearman test).

For OCs and BFRs, δ 15 N values in plasma samples were positively correlated with transnonachlor (r = 0.41), cisnonachlor (r = 0.32), and BDE-28 (r = 0.78), whereas δ 13 C values were only correlated with trans-nonachlor (r = 0.35; Fig. 4).

Discussion

We investigated the contaminant bioaccumulation in one of the most poorly researched seabirds in the Northern hemisphere, the ivory gull, and the relationship with its trophic habits. The trophic diet of this species has been previously described in Svalbard [START_REF] Mehlum | The diet of High-Arctic seabirds in coastal and ice-covered, pelagic areas near the Svalbard archipelago[END_REF] and other Arctic areas such as the Barents Sea [START_REF] Mehlum | Seabird distribution in the northern Barents Sea marginal ice-zone during late summer[END_REF]), the Chukchi Sea [START_REF] Divoky | The pelagic feeding habits of ivory and Ross' gulls[END_REF], and in northern Baffin Bay [START_REF] Karnovsky | Distribution and diet of ivory gulls (Pagophila eburnea) in the North Water Polynya[END_REF]). However, the large sample size of two non-invasive measures of long-term diet (e.g. blood and feathers) in our study provides an excellent opportunity to examine the relationship between contaminants and trophic ecology of ivory gulls, over several years and sampling locations on Barentsøya, Svalbard.

Contaminant bioaccumulation in the ivory gull

Results in this study are similar to previously reported results in ivory gull eggs where high concentrations were reached for OCs, especially p,p'-DDE and PCBs [START_REF] Braune | Levels and trends of organochlorines and brominated flame retardants in Ivory Gull eggs from the Canadian Arctic, 1976 to 2004[END_REF][START_REF] Miljeteig | High levels of contaminants in ivory gull Pagophila eburnea eggs from the Russian and Norwegian Arctic[END_REF][START_REF] Lucia | Circumpolar contamination in eggs of the high-arctic ivory gull Pagophila eburnea[END_REF]. Previous experimental studies in birds have demonstrated that exposure to various OCs, such as PCB, DDE and mirex, affect parental behaviour. This has often been attributed to endocrine disruption or neurological disorders [START_REF] Mcarthur | Ecological significance of behavioral and hormonal abnormalities in breeding ring doves fed an organochlorine chemical mixture[END_REF][START_REF] Peakall | Behavioral responses of birds to pesticides and other contaminants[END_REF][START_REF] Keith | Effects of DDE and food stress on reproduction and body condition of ringed turtle doves[END_REF]. [START_REF] Bustnes | Patterns of incubation and nest-site attentiveness in relation to organochlorine (PCB) contamination in glaucous gulls[END_REF] demonstrated that plasma PCB concentrations in glaucous gulls (Larus hyperboreus) nesting on Bjørnøya, Svalbard, were positively correlated with the proportion of time birds were absent from the nest with concentrations ranging from 52 to 1079 ng g -1 wet wt. This study included eight PCB congeners. With 11 congeners in the present study, concentrations ranged between 134 and 1597 ng g -1 wet wt, which could imply potential reproductive disruptions for the ivory gull.

Perfluorinated organic compounds have been reported in tissues of Arctic biota [START_REF] Butt | Levels and trends of poly-and perfluorinated compounds in the arctic environment[END_REF]. The most predominant PFAS in this study was PFOS. This result was similar to previous reports for Canadian [START_REF] Martin | Identification of long-chain perfluorinated acids in biota from the Canadian Arctic[END_REF][START_REF] Tomy | Fluorinated organic compounds in an eastern Arctic marine foood web[END_REF]) and Norwegian Arctic avian wildlife [START_REF] Verreault | Perfluorinated alkyl substances in plasma, liver, brain, and eggs of glaucous gulls (Larus hyperboreus) from the Norwegian Arctic[END_REF][START_REF] Lucia | Circumpolar contamination in eggs of the high-arctic ivory gull Pagophila eburnea[END_REF]. Levels observed in plasma samples of ivory gulls were below or of the same order of magnitude than those reported for the glaucous gull, an apex scavenger-predator seabird breeding in the Norwegian Arctic [START_REF] Verreault | Perfluorinated alkyl substances in plasma, liver, brain, and eggs of glaucous gulls (Larus hyperboreus) from the Norwegian Arctic[END_REF].

Perfluorooctane sulphonate levels for the glaucous gull ranged between 48 and 349 ng g -1 wet wt, whereas concentrations in this study ranged between 4 and 90 ng g -1 wet wt. Conversely, PFNA concentrations were of the same order of magnitude for both species, with glaucous gull concentrations ranging between below the detection limit (<2.33) and 6.33 ng g -1 wet wt and ivory gull concentrations ranging between 0.15 and 5.94 ng g -1 wet wt. Potential detrimental effects of PFOS include a competitive interaction with thyroid hormone thyroxin (T4) for binding sites on albumin and changes in hormone homeostasis [START_REF] Jones | Binding of perfluorinated fatty acids to serum proteins[END_REF][START_REF] Thibodeaux | Exposure to perfluorooctane sulfonate during pregnancy in rat and mouse. I: Maternal and prenatal evaluations[END_REF]. However, predominant, it seems unlikely that PFOS alone would contribute to measurable adverse effects in the ivory gull. Nevertheless, the cocktail of accumulated PFASs may trigger potential additive and synergetic impacts detrimental to this species.

Simultaneously in this study, PFAS concentrations in the plasma were positively correlated with the body mass of birds. This observation may be partially linked to the structural similarity between PFASs and fatty acids [START_REF] Heuvel | Differential activation of nuclear receptors by perfluorinated fatty acid analogs and natural fatty acids: A comparison of human, mouse, and rat peroxisome proliferator-activated receptor-α, -β, and -γ, liver X receptor-β, and retinoid X receptor-α[END_REF]). However, since blood concentrations only show a snapshot of the recent exposure of the investigated organisms, the causality might be more complex. This relationship between PFAS concentrations and the body mass could have several origins. For example, individuals with higher body mass may be more efficient in catching certain prey with a higher PFAS load and/or more food in general, or alternatively, be characterized by a slower metabolism and therefore a slower distribution of PFAS to the other compartments of the body. At the same time, sex-related differences appeared between males and females, the latter displaying lower concentrations for most of the PFASs.

A previous study on mallards (Anas platyrhynchos) exposed chronically to a PFOS contaminated feed demonstrated sex-dependent differences in serum PFOS concentrations where males had approximately 5 to 6 times the concentrations observed in females (Newsted et al. 2007). This study clearly demonstrated the maternal transfer of this compound to eggs.

Moreover, similar to PFOS, long-chain PFAS (PFTriA, PFTeA, and PFPeDA) also showed a tendency towards high accumulation in eggs of common guillemots (Uria aalge) from the Baltic Sea (Holmström and Berger 2008). Lower PFAS concentrations in ivory gull females consequently draw attention to the potential importance of PFAS maternal transfer to the eggs at the time of their formation as a mechanism of elimination.

Polybrominated diphenyl ethers concentrations were relatively low in the ivory gull ranging between 0.67 and 7.56 ng g -1 wet wt in the plasma. As a comparison, sum PBDE concentrations of the glaucous gull in the Norwegian Arctic ranged from 2.49 to 54.5 ng g -1 wet wt in the plasma [START_REF] Verreault | Brominated flame retardants in glaucous gulls form the Norwegian Arctic: More than just an issue of polybrominated diphenyl ethers[END_REF]). However, this previous study included 38 congeners which could imply that similar levels may be reached in the ivory gull if more congeners were taken into account. Apart from BDEs, HBB was the only other BFR that was detected in the present study.

Historically, HBB was widely used in Japan as an additive to paper, plastic, and electronic goods. However, the use of this substance has been reduced by Japan (350 tons in 2001; [START_REF] Watanabe | Environmental release and behavior of brominated flame retardants[END_REF], and this compound is not currently produced in Europe. The low levels observed could suggest a very low background in the food web of the ivory gull and the Arctic region in general. Overall, it is difficult to draw conclusions on the potential effects of contaminants in this study. Some compounds appeared to be linked to lower body masses of the birds (e.g. HCB, , but this result may also be linked to the bird's reproductive status at the time of the sampling.

The present study covered 4 years of observations which provided very valuable information for a number of chemical compounds. However, there were few differences between sampling years and no clear patterns were observed. For example, PFAS levels did not differ significantly between 2011 and 2013, even if this lapse of time is relatively small. Contaminant concentrations seem rather to follow episodic events of contamination in Svalbard.

Nevertheless, the sampling period still remains short in this study. It appears therefore fundamental to sustain the sampling effort over several years and tissues to properly evaluate the possible contamination patterns resulting from global change in the Arctic.

Relationship between trophic position, feeding habitat and contaminant bioaccumulation

In this study, the trophic level and feeding habitats of birds, measured through δ 15 N and δ 13 C values, were lower compared to a study using feather data from museum specimens from the Canadian Arctic and western Greenland over a 130 year period (Bond et al. 2015). Isotope values in the present study were variable, both in blood and feathers. Assuming that birds from different colonies or origins forage in food webs with similar isotopic baseline, this result indicates individual differences in trophic behaviour during the breeding (blood) and moulting (feathers) periods, respectively. The importance of polar cod to the diet of ivory gulls has been previously documented [START_REF] Divoky | The pelagic feeding habits of ivory and Ross' gulls[END_REF][START_REF] Mehlum | Seabird distribution in the northern Barents Sea marginal ice-zone during late summer[END_REF][START_REF] Mehlum | The diet of High-Arctic seabirds in coastal and ice-covered, pelagic areas near the Svalbard archipelago[END_REF][START_REF] Karnovsky | Distribution and diet of ivory gulls (Pagophila eburnea) in the North Water Polynya[END_REF]). Nevertheless, individuals also feed on other fish species such as Atlantic cod (Gadus morhua) and coalfish (Pollachius virens), and amphipods [START_REF] Mehlum | The diet of High-Arctic seabirds in coastal and ice-covered, pelagic areas near the Svalbard archipelago[END_REF]. Some ivory gulls are also known to specialize on scavenging remains of predator kills (e.g. polar bears). Ivory gulls may therefore feed on prey situated at different trophic levels (Wassmann et al. 2006). This overall variability in stable isotope values among birds can also be explained by differences in foraging strategies between breeding and nonbreeding birds. Birds were often captured at the edge of the colonies to avoid any disturbances at the nest. Consequently, some sampled individuals could have been failed breeders which may result in differences in e.g. diet, fasting status, body mass, and overall biology and ecology. This overall variability in stable isotope values among birds is accompanied by an overlap in stable isotope values among colonies. Ivory gulls from different breeding sites demonstrated similar feeding habitats and strategies. Only birds from one colony, Sigden, displayed lower δ 15 N and δ 13 C values in their red blood cells compared to the rest of the colonies. This result suggests a diet in this colony originating from a more offshore and lower trophic level in the month prior to the blood sampling (Hobson et al. 1994). Diet-switching experiments on birds have indeed demonstrated that the half-life of stable isotopes in red blood cells was approximately 1 month (half-life = 29.8 days), versus 2-3 days in the plasma fraction (half-life = 2.9 days; [START_REF] Hobson | Turnover of d 13 C and plasma fractionations in blood: implications for non-destructive sampling in avian dietary studies[END_REF]. Nevertheless, this observation was not echoed in plasma samples where isotopic values were not significantly different between colonies. It appears rather unlikely that birds from Sigden had an entirely different trophic behaviour compared to birds from other colonies. This divergence in isotopic values for this colony could reflect a possible shift in trophic behaviour during a special event (e.g. climatic event triggering poor sea ice conditions) or a specific food source only exploited by these birds at a certain period in time. The same overlap between colonies was observed for feathers thus demonstrating similar trophic behaviour during the moulting period.

The homogeneity in feeding behaviours between different colonies is reflected by the absence of differences in contaminant concentrations. Only the Auga colony displayed lower plasma PFAS concentrations (e.g. PFOS, PFUnDA, and PFDoDA) than birds from Freemanbreen. This discrepancy could be related to several factors including the fewer number of individuals sampled in Auga compared to Freemanbreen (n = 5 and 27, respectively). It is, however, difficult to draw exact conclusions about the origin of this difference since isotopic values in the plasma were not different between those colonies. This discrepancy may be the result of several factors including contaminant exposure of birds on their wintering and breeding grounds, the local diet, and the remobilization of contaminants from internal tissues (e.g. liver)

in association with the reproductive status of individuals. Despite being amphiphilic, PFASs demonstrate bioaccumulation tendencies due to their ability to bind to proteins. Perfluorinated alkyl substances accumulated in the liver can for example be transferred to the forming egg as a protein-PFOS complex (Holmström and Berger 2008). During fasting, PFAS associated with proteins may also easily be remobilized in the blood system of birds. As specified above, birds sampled could have been failed breeders, influencing therefore their overall biology, ecology, and contaminant exposure. The rate of failed breeders may have been especially higher at Auga where predation on eggs is often high (personal observation).

Stable isotope analysis has become a powerful tool to study dietary exposure and biomagnification of contaminants in free-ranging animal populations [START_REF] Jardine | Applications, considerations, and sources of uncertainty when using stable isotope analysis in ecotoxicology[END_REF]. In this study, nitrogen values in the blood of birds were positively correlated to most of the PFASs.

This result is in line with previous findings about the biomagnification potential of these compounds in the Barents Sea food web (Haukas et al. 2007). Organochlorines and BFRs are also known to biomagnify along the food chain making species at high trophic levels such as the ivory gull, more vulnerable to contaminant exposure through their diet [START_REF] Hop | Food web magnification of persistent organic pollutants in poikilotherms and homeotherms from the Barents Sea[END_REF]Borga et al. 2004;[START_REF] Braune | Levels and trends of organochlorines and brominated flame retardants in Ivory Gull eggs from the Canadian Arctic, 1976 to 2004[END_REF]. In this study, trans-nonachlor, cis-nonachlor, and BDE-28 were linked to nitrogen values which denote the increase of those contaminants along the Arctic food web. Alternatively, transnonachlor was the only compound clearly correlated with carbon values in birds, demonstrating therefore that ivory gulls with the most enriched δ 13 C values probably feeding on more inshore prey have a higher tendency to bioaccumulated this persistent pollutant.

Conclusion

The most quantitatively abundant contaminants found in the ivory gull were p,p′-DDE, ΣPCB and PFOS. Overall, OC, BFR and PFAS did not suggest direct lethal risk to these compounds.

Nevertheless, their potential synergetic or additive effects warrant monitoring. This study also highlighted a possible individual variability in trophic behaviour during the breeding and moulting periods, respectively. Overall, ivory gulls from different breeding sites used similar feeding habitats and strategies which were echoed by similar contaminant levels. Results for several compounds, including most of the PFASs, trans-nonachlor, cis-nonachlor, and BDE-28, are in line with previous reports about their biomagnification potential. Finally, several factors (time, colony, sex) can influence the contaminant bioaccumulation and the trophic behaviour of ivory gulls. However, this study does not allow for a full quantification of their impact due to the lack of data available on this remote species. Further research is therefore needed to better understand the contaminant pressure and foraging strategies of the ivory gull through, for example, investigation of movement patterns.

  standard solutions ( 13 C-labelled compounds from Cambridge

  presents red blood cell mean values for all colonies, all years consolidated. Birds sampled at Sigden displayed significantly lower δ 13 C values than birds from Freemanbreen and Hübnerbreen colonies, as well as lower δ 15 N values than individuals from Hübnerbreen (δ 13 C: Sigden vs Freemanbreen p = 0.005, Sigden vs Hübnerbreen p<0.0001; δ 15 N: Sigden vs Hübnerbreen p = 0.043). However, birds coming from Sigden were only sampled in 2014. To exclude year as confounding factor, stable isotope values were compared between colonies sampled in 2014 only. However, only Freemanbreen and Sigden could be compared because of low number of birds sampled in other colonies. The same trend was consequently observed that year. Sigden birds displayed lower stable isotope values than birds from Freemanbreen (δ 13 C: p = 0.024; δ 15 N: p = 0.031). Furthermore, plasma δ 13 C values were also significantly different between both colonies in 2014 (Sigden: -21.3 ± 0.1 ‰,

  Goutte et al. (2014c) demonstrated differences in foraging strategies between breeders and nonbreeding birds in an Arctic population of black-legged kittiwakes (Rissa tridactyla). Nonbreeders were potentially less constrained by energetic costs and time, and therefore displayed a higher foraging range than breeders. The same tendency was demonstrated for earlier breeders which tended to forage at farther distances than kittiwakes breeding later in the season. The same patterns could apply to the ivory gull.

Figure 1 .

 1 Figure 1. Locations of the four ivory gull (Pagophila eburnea) colonies sampled on Barentsøya (78°25'N, 21°27'E), Svalbard, Norway.

Figure 2 .

 2 Figure 2. Carbon (δ 13 C) and nitrogen (δ 15 N) isotopic values (mean % ± SD) in a) plasma (n = 76), b) red blood cells (n = 76), c) whole blood (n = 20) and d) ventral feathers (n = 139) of ivory gulls from Svalbard.

Figure 3 .

 3 Figure 3. Carbon (δ 13 C) and nitrogen (δ 15 N) isotopic values (mean % ± SD) in red blood cells of ivory gulls sampled from four colonies on Barentsøya, Svalbard: Hübnerbreen (H; n = 19), Freemanbreen (F; n = 27), Auga (A; n = 5) and Sigden (S; n = 25).

Figure 4 .

 4 Figure 4. δ 15 N values versus trans-nonachlor, BDE-28 and cis-nonachlor concentrations (ng g - 1 wet wt) and δ 13 C values versus trans-nonachlor concentrations (ng g -1 wet wt) in plasma of ivory gulls. Equations of the trend curves were indicated for each graphs.

Table 1 .

 1 Mean concentrations (ng g -1 wet wt ± standard deviation) and ranges (min-max) of perfluorinated alkyl substances in the plasma in 2013 (n = 38) and 2014 (n = 21), and the whole blood in 2011 (n = 4), 2012 (n = 5) and 2013 (n = 1) of ivory gulls (Pagophila eburnea) from Svalbard.Table2. Mean concentrations (ng g -1 wet wt ± standard deviation) and ranges (min-max) of organochlorines and brominated flame retardants in the plasma in 2013 (n = 30) and 2014 (n = 9), and the whole blood in 2011 (n = 4) and 2012 (n = 2) of ivory gulls from Svalbard

  As normality and homogeneity of variance were not achieved despite log10(x+1) transformation (Cochran C test), non-parametric analysis of variance (Kruskal-Wallis and Mann-Whitney Utest) was applied to assess differences in contaminant concentrations and stable isotope signatures for each parameters (colony, year, sex). Moreover, the Spearman test was applied to study correlations between parameters (contaminant concentrations and stable isotope values).

	DDD, cis-chlordane, PCB-152, BDE-138, BATE, TBPA, PBT, PBEB, DPTE, BTBPE,
	BEHTBP, EHTeBB, 6:2 FTS, 8:2 FTS, PFBS, PFHpS, PFDcS, PFOSA, PFBA, PFPeA,
	PFHxA, PFHpA, PFOA, PFHxDA. Values below the quantification limit were taken into

excluded from statistical analyses including o,p'

DDT, p,p' DDT, o,p' DDE, o,p' DDD, p,p'

account in calculation of the means by assigning them values one-half of the detection limit for the given contaminant (e.g. a value < 0.02 was reported as 0.01 ng g -1 wet wt). Contaminant concentrations are expressed in ng g -1 wet wt.

Acknowledgments. The authors wish to thank the European Commission for its financial support through a Marie Curie fellowship to M. Lucia, as well as Gael Guillou from the ''plateforme analyses isotopiques'' (UMR LIENSs) for technical support during stable isotope analyses. We thank Linda Hanssen and Arntraut Götsch (NILU) for their assistance with the

chemical analyses. We also thank Birgit Braune for her help with English. The fieldwork was supported by the Norwegian Polar Institute's centre for Ice, Climate and Ecosystems (ICE) and the SEAPOP program (seapop.no). Thanks to Vidar Bakken, Audun Igesund, Cecilie Miljeteig, Knut Olsen, Maria Gavrilo, Olivier Gilg and Odd Kindberg for help in the field.


Goluck Konuko

Giuseppe Valenzise

Stéphane Lathuilière

ULTRA-LOW BITRATE VIDEO CONFERENCING USING DEEP IMAGE ANIMATION

Keywords: Video compression, Video conferencing, Model-based compression, Deep learning

In this work we propose a novel deep learning approach for ultra-low bitrate video compression for video conferencing applications. To address the shortcomings of current video compression paradigms when the available bandwidth is extremely limited, we adopt a model-based approach that employs deep neural networks to encode motion information as keypoint displacement and reconstruct the video signal at the decoder side. The overall system is trained in an end-to-end fashion minimizing a reconstruction error on the encoder output. Objective and subjective quality evaluation experiments demonstrate that the proposed approach provides an average bitrate reduction for the same visual quality of more than 60% compared to HEVC.

INTRODUCTION

Video conferencing applications represent a substantial share of Internet video traffic, which has significantly increased in the past months due to the global pandemic. Video conferencing relies heavily of the availability of efficient video compression standards, such as H.264, HEVC [START_REF] Sullivan | Overview of the high efficiency video coding (hevc) standard[END_REF], and, in the next future, VVC [START_REF] Bross | Jvet-m1001: Versatile video coding (draft 5)[END_REF]. Although these video codecs have been optimized and tuned for over 30 years, they are still unable to provide acceptable performance at very low bitrates. In fact, when bandwidth is extremely limited, e.g., due to a congested network or to poor radio coverage, the resulting video quality becomes unacceptable, degrading the video conferencing experience significantly.

A major limitation of the current video compression paradigm comes from employing elementary models of pixel dependencies in order to increase coding efficiency. For instance, the commonly used discrete cosine transform implicitly assumes that pixels are generated by a Gaussian stationary process [START_REF] Pad | On the optimality of operator-like wavelets for sparse AR (1) processes[END_REF]. Similarly, spatial and temporal prediction exploit low-level pixel dependencies such as spatial directional smoothness and simple translational motion across time. Furthermore, these tools are often optimized with pixel-based fidelity metrics such as the Mean Squared Error (MSE), which is known to correlate poorly with human perception [START_REF] Wang | Image quality assessment: from error visibility to structural similarity[END_REF].

In this paper, we consider a very different, model-based compression approach for video conferencing that goes beyond simple pixel-based techniques. Specifically, we interpret video frames as points of a low-dimensional manifold living in the higher-dimensional pixel space. We leverage recent advances in image generation and deep generative networks [START_REF] Goodfellow | Generative adversarial nets[END_REF], which have made possible to automatically synthesize images or videos of faces with unprecedented quality and realism [START_REF] Karras | A style-based generator architecture for generative adversarial networks[END_REF][START_REF] Zakharov | Few-shot adversarial learning of realistic neural talking head models[END_REF][START_REF] Siarohin | Animating arbitrary objects via deep motion transfer[END_REF][START_REF] Siarohin | First order motion model for image animation[END_REF]. These tools have recently reached a great deal of popularity in computer vision and computer graphics applications, such as motion transfer [START_REF] Chan | Everybody dance now[END_REF], creation of video portraits [START_REF] Kim | Deep video portraits[END_REF], deep fakes [START_REF] Yang | Exposing deep fakes using inconsistent head poses[END_REF], image to image translation [START_REF] Nguyen | Multidomain image-to-image translation with adaptive inference graph[END_REF] etc. However, their potential as a video compression tool is still unexplored. In this work, we describe, for the first time, a video coding pipeline that employs a recently proposed image animation framework [START_REF] Siarohin | Animating arbitrary objects via deep motion transfer[END_REF][START_REF] Siarohin | First order motion model for image animation[END_REF] to achieve long-term video frame prediction. Our scheme is open loop: we encode the first frame of the video using conventional Intra coding, and transmit keypoints extracted by subsequent frames in the bitstream. At the decoder side, the received keypoints are used to warp the Intra reference frame to reconstruct the video. We also propose and analyze an adaptive Intra frame selection scheme that, in conjunction with varying the quantization of Intra frames, enable to attain different rate-distortion operating points. Our experiments, validated with several video quality metrics and a subjective test campaign, show average bitrate savings compared to HEVC of over 60%, demonstrating the potential of this approach for ultra-low bitrate video conferencing. The source code and additional results are available at https://goluck-konuko.github.io/.

RELATED WORK

Model-based compression paradigms are not new in data compression. A prominent example comes from speech coding standards, where vocoders [START_REF] Spanias | Speech coding: A tutorial review[END_REF] are a broadly used kind of generative models. Unfortunately, generative image and video models turn out to be significantly more complex than in the audio case. Previous work aimed at using generative models for talking heads has failed to provide realistic and appealing video compression performance. The most notable example was the MPEG-4 Visual Objects standard, which enables embedding of synthetic objects such as faces or bodies and animate them using a sequence of animation parameters [START_REF] Preda | Critic review on MPEG-4 face and body animation[END_REF]. Although the concept of visual object was an innovative idea and inspired follow-up work (even recently, e.g., [START_REF] Wijnants | Talking video heads: Saving streaming bitrate by adaptively applying object-based video principles to interview-like footage[END_REF]), the quality of the resulting animated faces was quite unrealistic. As a result, this part of the standard has been rarely used in practice. In this work, we use a recently proposed image animation model which can instead produce highly realistic faces [START_REF] Siarohin | First order motion model for image animation[END_REF].

Recently, deep neural networks have been successfully applied to image and video compression [START_REF] Ma | Image and video compression with neural networks: A review[END_REF]. Learning-based image compression has been generally cast as the problem of learning deep representations, typically by means of deep auto-encoders, which are optimized in an end-to-end fashion by maximizing a rate-distortion criterion [START_REF] Ballé | Variational image compression with a scale hyperprior[END_REF][START_REF] Rippel | Real-time adaptive image compression[END_REF]. Learningbased image codecs can compress pictures in a more natural way than conventional codecs [START_REF] Valenzise | Quality assessment of deep-learning-based image compression[END_REF]. Similar ideas have been employed later for the case of video. There, deep learning tools have been mainly used to replace and optimize single stages of the video coding pipeline [START_REF] Rippel | Learned video compression[END_REF][START_REF] Wang | Enhancing hevc spatial prediction by context-based learning[END_REF]. In this work, we consider instead a generative modeling perspective, and propose a coding architecture which departs substantially from that of a conventional hybrid video codec.

Deep generative models have also been recently employed in image/video compression schemes [START_REF] Agustsson | Generative adversarial networks for extreme learned image compression[END_REF][START_REF] Kaplanyan | Deepfovea: Neural reconstruction for foveated rendering and video compression using learned statistics of natural videos[END_REF], to reduce bitrate by hallucinating parts of the video that are outside the region of interest (ROI). In this work, instead, we use deep generative models to synthesize face images, which constitute the main ROI in video communication. ROI-based coding has been previously used for video conferencing [START_REF] Meddeb | Region-of-interest-based rate control scheme for highefficiency video coding[END_REF]. There, coding gains are obtained by varying the bitrate allocation between the ROI/non-ROI regions. We use instead a very different warping tool to animate the ROI with a very low bitrate.

PROPOSED CODING METHOD

Coding scheme based on image animation

The overall pipeline of the proposed codec is illustrated in Fig. 1. It consists of an Intra frame compression module (which could be any state-of-the-art image codec); a sparse keypoint extractor to code Inter frames; a reconstruction (warping) module to motion compensate and reconstruct the Inter frames; and a binarizer and entropy coder to produce a compressed binary bitstream. In the following, we provide a walk-through of the main coding steps of our system: Intra-frame coding. We first encode the initial frame F 0 using the BPG image codec, which essentially implements HEVC Intra coding, using a given QP 0 . The coded frame is sent to the decoder. On the decoder side, the initial frame is decoded using the BPG decoding procedure. This decoded initial frame is referred to as F0 . Keypoint prediction. Following the recent work of Siarohin et al. [START_REF] Siarohin | First order motion model for image animation[END_REF], we encode motion information via a set of 2D keypoints learned in a self-supervised fashion. The keypoints are predicted by a U-Net architecture [START_REF] Ronneberger | U-net: Convolutional networks for biomedical image segmentation[END_REF] network that, from its input frame, estimates M heatmaps (one for each keypoint). Each heatmap is then interpreted as detection confidence map and used to compute the expected keypoint locations. In addition, following [START_REF] Siarohin | First order motion model for image animation[END_REF], we compute a (symmetric) 2 × 2 Jacobian matrix for each keypoint, which encodes the orientation of the face region associated to that keypoint. Each keypoint is then represented by a 5-dimensional vector (2 spatial coordinates, plus the 3 elements to represent the Jacobian matrix). Entropy coding. Keypoints are represented as floating point values with 16 bits precision. We compress these values using an off-the-shelf LZW encoder (gzip). Notice that any other entropy coding solution, e.g., a binary arithmetic codec with contexts, could be equally used. The coded motion information, together with the BPG compressed Intra frames, form the bitstream that is sent to the decoder. Motion compensation and inter-frame reconstruction At the decoder side, we reconstruct the frame F t at time t from the decoded initial frame F0 and the displacement of a set of M keypoints, K 0 ∈ R 5×M and K t ∈ R 5×M , extracted from frames F0 and F t , respectively. These keypoints are detected for each frame at the encoder side and transmitted in the bitstream, as explained above. We then employ the reconstruction network introduced in [START_REF] Siarohin | First order motion model for image animation[END_REF] to reconstruct Ft from F0 and the keypoints K 0 and K t . This reconstruction network is composed of two sub-networks. The first sub-network predicts the optical flow between the frames at times 0 and t from F0 , K 0 and K t . This optical flow is then used by the second sub-network to predict Ft from F0 . Please refer to [START_REF] Siarohin | First order motion model for image animation[END_REF] for the details of the reconstruction network architecture.

The overall system is trained in an end-to-end fashion on a large training set of videos depicting talking faces. We minimize a reconstruction loss between the input and the decoded frames. In this way, we force the keypoint detector network to predict 2D keypoints that describe motion in such a way that the reconstruction network can correctly reconstruct each frame. The reconstruction loss is based on the perceptual loss of Johnson et al. [START_REF] Johnson | Perceptual losses for real-time style transfer and super-resolution[END_REF] using a VGG-19 network pre-trained on ImageNet. This loss is completed with a GAN loss [START_REF] Mao | Least squares generative adversarial networks[END_REF] and an equivariance loss that enforces that network to be equivariant to random geometric transformations [START_REF] Siarohin | First order motion model for image animation[END_REF]. Notice that Intra frame coding with BPG, as well as gzip, are not differentiable, and as a consequence, cannot be included in the training process. While differentiable approaches to estimate entropy have been proposed [START_REF] Ballé | Variational image compression with a scale hyperprior[END_REF], in this work we opt for the simpler solution to ignore this step during training.

Adaptive Intra frame selection

The coding scheme described in the previous section adopts an open GOP structure, i.e., only the first frame is coded as Intra. While this leads to a very high video compression rate, Fig. 1: Basic scheme of our proposed baseline codec. The encoder (in red) encodes the first frame as Intra (IF) using a BPG codec. The following frames (t > 1) are encoded as keypoints predicted by a neural network. Keypoints are entropy coded (EC) and transmitted in the bitstream. The decoder (in blue) includes a neural network that combines the reconstructed initial frame F0 and its keypoints K 0 , with the keypoints K t at the current time t, to reconstruct Ft . The overall system is trained in an end-to-end manner via reconstruction loss minimization. the reconstruction quality might rapidly degrade due to the loss of temporal correlation as frames get farther away from the initial one. This is particularly evident in case of occlusions/disocclusions caused by a person's pose change.

To overcome this issue, we introduce in the following an adaptive Intra-Refresh scheme using multiple source frames. The procedure is described in Algorithm 1. The proposed multi-source Intra frame selection is parametrized by a threshold parameter τ that allows quality (and, implicitly, bitrate) adjustment. We employ a buffer B containing the key frames that are required to reconstruct the input video, together with the corresponding keypoints. At every time step, this buffer is synchronized between the encoder and the decoder. To this end, every frame added to B by the encoder is sent to the decoder that, in turn, adds the frame to its buffer.

The buffer is initialized with the first frame F0 and the keypoints K 0 , as described in Section 3.1. Note that the keypoints K 0 need not be sent to the decoder since K 0 can be re-estimated at the decoder side from F0 . Then, for every frame F t , we apply the following procedure: We estimate the keypoints K t . Then, we identify the best frame in the buffer that can be used to reconstruct the current frame. To this aim, we reconstruct Ft using all the frames Fb and their keypoints K b . We select the buffer frame index b * that leads to the lowest PSNR. We use PSNR here, rather than perceptual loss, because of its lower computational cost. At this point, two cases can happen: i) if the best source frame yields a PSNR higher than the threshold τ , we use the frame F b * as source frame to reconstruct F t . Therefore, the index b * and the keypoints K t are sent to the decoder; ii) the PSNR is lower than threshold τ . In this case, none of the frames in the buffer is suitable to reconstruct the current frame and F t needs to be added to the buffer as a new Intra frame and sent to the decoder. To this end, we encode the current frame F t with QP 0 used for the first frame. Input : Frames: F 0 , . . . , F T , Threshold: If the resulting PSNR is still above τ , we reduce the QP by one unit, and repeat the procedure till the quality constraint is satisfied. This provides a set of operating ratedistortion curves for the codec. By taking the convex hull of these curves, we can effectively attain different rate-distortion trade-offs. We leave the study of efficient rate-distortion optimization strategies for adaptive Intra frame selection to future work. Signaling the best source frame index is a good tradeoff between compression rate and computational cost. We implement B as a first-in, first-out buffer. When a new source frame is added, the oldest source is popped assuming that reconstruction error increases with time. In all our experiments, we use a buffer of size 5. In our preliminary experiments, we observed that a larger buffer size does not bring significant gain but increases memory requirements. Additionally, the source frame keypoints, K B b can be signalled directly in the bitstream to eliminate the need for a keypoint detector at the decoder.

τ > 0 K 0 = Keypoint( F0 ) // Estimate keypoints B = {( F0 , K 0 )} // Initialize the buffer Send(F 0 ) for t ∈ {1, ..., T } : // For every frame Kt = Keypoint(Ft) // Estimate keypoints F B t = {Reconstruct( Fb , K b , Kt); ∀( Fb , K b ) ∈ B} b * = argmin F b t ∈ F B t PSNR( F b t , Ft) // Best frame in B if PSNR( F b * t , Ft) > τ : Send(b * , Kt) //

EXPERIMENTS AND RESULTS

Datasets. We employ two datasets suited for a video conferencing scenario:

• Voxceleb is a large audio-visual dataset of human speech of 22,496 videos, extracted from YouTube videos. We follow the pre-processing of [START_REF] Siarohin | First order motion model for image animation[END_REF] and filter out sequences that have resolution lower than 256×256 and resize the remaining videos to 256×256 preserving the aspect ratio. This dataset is split into 12,331 training and 444 test videos. For evaluation, in order to obtain high quality videos, we select the 90 test videos with the highest resolution before resizing.

• Xiph.org is a collection of videos we downloaded from Xiph.org 1 . This repository includes video sequences widely used in video processing ("News", "Akiyo", "Salesman", etc.). We select 16 sequences of talking heads that correspond to the targeted video conferencing scenario. The full list of videos used in the experiments is available on the GitHub page of the paper. The region of interest is cropped with a resolution of 256×256 with speakers' faces comprising 75% of the frame. Notice that we use this dataset for testing only, while the system is trained on the Voxceleb training set.

Comparison with HEVC. We compare our approach with the standard HM 16 (HEVC) low delay configuration (IPPP GOP structure) 2 by performing a subjective test on 11 videos (9 from Voxceleb and 2 from Xiph.org) using Amazon Mechanical Turk (AMT). Each sequence is encoded using 6 bitrate levels (6 with HEVC, 6 with our proposed method) rang- ing from 5Kbps to 30Kbps. The different points in the curve are obtained by changing QP 0 in BPG, as well as τ . We implement a simple pair comparison test interface in AMT.

Users are invited to follow a brief training on a sequence not used for test. The lowest quality level ("5kbps") is used to check the reliability of voters since 100% preference for our framework is invariably expected. We collected 30 subjective evaluations per stimulus. After collecting data from all the participants, we detected and eliminated 62 outliers. Based on these preliminary results, we proceed with an extensive performance evaluation of the proposed method using these quality metrics. In Table 2, we report the average Bjontengaard-Delta performance for VoxCeleb test and Xiph.org images.

The gains are significant (over 60% BD-rate savings) on the two datasets. Finally, we provide a qualitative comparison in Fig. 3 on a sequence from Xiph.org. In this example, we observe that at a similar bitrate, our approach produces much fewer artifacts. The difference is clearly visible in the eye region. Even at a much lower bitrate (5 Kbps) -one lower than the minimum rate achievable by HEVC -our approach generates better quality images.

CONCLUSIONS

In this paper, we propose the first video conferencing codec that employs a deep generative frame animation scheme and drastically improve coding performance at ultra-low bitrate. We encode the initial frame using a state-of-the-art image codec. Motion information is then encoded via moving keypoints predicted by a deep network. We propose an adaptive Intra frame selection mechanism to improve reconstruction quality over long sequences. Our experiments show that our approach outperforms HEVC with a large margin. As future work, we plan to handle high-resolution videos and more complex scenarios with multiple speakers in the same video.

Algorithm 1 :

 1 Adaptive Intra frame selection (encoder side)

Fig. 2 :

 2 Fig. 2: RD curve for 90 test videos sampled from VoxCeleb test set encoded by our framework.

Fig. 3 :

 3 Fig. 3: Qualitative evaluation against HEVC on Deadline (Frame 40) sequence in a low bitrate setting.

Table 1 :

 1 User preference score vs HEVC

	Bitrate (kbps) No. of votes (Ours/HEVC)	PREFERENCE (%)
	5	268 / 0	100.00
	10	229 / 31	88.08
	15	218 / 40	84.50
	20	193 / 59	76.59
	25	160 / 92	63.49
	30	164 / 98	62.60

Table 2 :

 2 Bjontengaard-Delta Performance over HEVC

		VoxCeleb	Xiph.org
		BD quality / BD rate BD quality / BD rate
	PSNR	1.66 / -62.18	2.23 / -76.86
	SSIM	0.06/ -56.34	0.1/ -67.43
	MS-SSIM	0.04 / -52.33	0.06 / -51.73
	VIF	0.02 / -41.46	0.05 / -49.99
	Original	HEVC: 20 Kbps Ours: 20Kbps	Ours: 5Kbps