BIBLIOGRAFIA

Polynya determination was based on a sea ice production (SIP; expressed in m.y−1) thresh- old. The estimation of SIP followed Tamura et al. [Tamura and Ohshima, 2011]. First, thin ice thickness was estimated using the Tamura et al. [Tamura et al., 2007] algorithm, us- ing 85 and 37 GHz brightness temperature retrieved from SSM/I. Next, SIP was estimated by heat flux calculation during the freezing period (from March to October) using thin ice thickness and surface atmospheric data. The air-sea ice surface heat flux is obtained by as- suming that the sum of radiative and turbulent fluxes at the ice surface is balanced by the conductive heat flux in the ice. The European Centre for Medium-Range Weather Forecasts Re-Analysis data (ERA-40: 1992–2001, ERA-interim: 1992–2013) and the National Centers for Environmental Prediction/Department of Energy Re-Analysis data (NCEP2: 1992–2013) were used for this calculation. The calculation was performed twice a day over the entire Southern Ocean on the SSM/I Equal Area Scalable Earth-Grid (12.5 km×12.5 km) from 1992 to 2014.

Figure V.1:Schematic representing the different steps for polynya definition and the calculation of SESs use of polynyas.

The determination of polynyas in the study region followed the steps presented in Figure V.1. We first determined the yearly SIP for each year, SIPyear, by summing

monthly SIP during the freezing period (from March to October; step 1, FigureV.1; Panel a, Figure V.2). Then, we defined boxes around known polynya regions based on lit- erature information [Massom et al., 1998, Arrigo and van Dijken, 2003, Arrigo et al., 2015,

Nihashi and Ohshima, 2015], and within these boxes, we draw three polygons to define

polynya regions based on the contour of SIPyear corresponding to 2.5 m.y−1(green con-

tour), 5 m.y−1(yellow contour) and 10 m.y−1(red contour) (step 2a and 2b, FigureV.1; Panel b and c, FigureV.2). For contouring SIPyear, we used the packageraster(from R Develop-

ment Core Team) with the functionrasterToContourand the packagergeoswith the func-

tiongPolygonize. Then, based on daily estimates of thin ice thickness, within the larger

polygon defining the contour of 2.5 m.y−1 of SIPyear, we contoured, for each polynya, a

polygon of thin ice (characterized by a thickness from 0 to 0.2 m, blue contour; step 3, Fig- ureV.1; Panel d, FigureV.2). The three step procedure for defining polynyas is illustrated by two yearly maps of SIP for 2004, where boxes and contours are drawn, and one daily map of thin ice thickness where SIP and thin ice contours are drawn (see FigureV.2). A total of 14 polynyas were identified and named based on Massom et al. [Massom et al., 1998] and Arrigo and van Dijken [Arrigo and van Dijken, 2003]: 1. Lützoh-Holm Bay, 2. Cape Borle, 3. Cape Darnely, 4. Mackenzie, 5. Barrier, 6. West Ice Shelf, 7. Shackleton, 8. Bowman Island, 9. Vincennes Bay, 10. Cape Poinsett, 11. Dalton, 12. Paulding Bay, 13. Dibble, 14. Mertz.

V. COASTAL POLYNYAS:A WINTER OASIS FOR TOP PREDATORS

Figure V.2:Illustration of the polynya definition based on SIP and thin ice thickness. Example of yearly SIP (m.y−1) map obtained from the sum of monthly SIP during the freezing period from March to October in 2004 (a). Same as (a) with boxes superimposed defining some polynya areas based on literature, within which polynya definition polygons were computed based on threshold of SIP of 2.5 m.y−1(green contour), 5 m.y−1 (yellow contour) and 10 m.y−1(red contour) (b). A total of 14 polynyas were identified: 1. Lützoh-Holm Bay, 2. Cape Borle, 3. Cape Darnely, 4. Mackenzie, 5. Barrier, 6. West Ice Shelf, 7. Shackleton, 8. Bowman Island, 9. Vincennes Bay, 10. Cape Poinsett, 11. Dalton, 12. Paulding Bay, 13. Dibble, 14. Mertz. The insert is a zoom of polynyas 9 and 10 to highlight the different contours (c). Examples of map of thin ice thickness data for three days in 2013 where SIP polynya definition (i.e. 2.5 m.y−1(green contour), 5 m.y−1(yellow contour) and 10 m.y−1(red contour)) and bottom topography are superimposed (d). Within the green polygon (i.e. the larger polynya definition based on SIP), polygons of thin ice were daily drawn for thickness comprised between 0 and 0.2 m (blue contour). The red dot corresponds of one the seal position for this given day.

As such, for each of the 14 polynyas, we define a yearly position of the polynya, based on three thresholds corresponding to three yearly-mean "cores" of the polynya, from less to more active: SIPyear equal to 2.5 m.y−1; 5 m.y−1; or 10 m.y−1. In addition, we define the

“daily core” region of the polynya, corresponding to the region with the thinnest thin ice within the yearly polynya core: thin ice thickness less than 0.2 m. By determining the "daily core" of the polynya from the thin ice contours, we characterized the variability of the dis- tribution of thin ice from one day to another inside the polynya region defined with a yearly SIPyear. Note that these "daily core" were derived for each day of the seals’ track, including

periods outside the freezing period. While, a polynya is often defined as an area of open wa- ter or reduced sea ice cover located in waters that would be expected to be ice covered (i.e. is considered as a wintertime phenomena), in this study, we abusively refer to as polynya in spring/summer, as surface waters after the retreat of sea-ice, within a polynya sector, are often more biologically productive than adjacent waters [Arrigo and van Dijken, 2003].

The area of each polygon (expressed in squared meter) was computed using the pack-

agergeoswith the functiongArea(step 4, FigureV.1). The shortest distance between each

seal position and each polygon contour was computed using the packagergeosand the functionspDistsN (step 5, FigureV.1). Finally, we also determined if the seal was inside of each polygon using the packagergeosand the functiongContains(step 6, FigureV.1).