Phytoplankton dynamics within 37 Antarctic coastal polynya systems

Transcription

1 JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 108, NO. C8, 3271, doi: /2002jc001739, 2003 Phytoplankton dynamics within 37 Antarctic coastal polynya systems Kevin R. Arrigo and Gert L. van Dijken Department of Geophysics, Stanford University, Stanford, California, USA Received 6 December 2002; revised 16 April 2003; accepted 8 May 2003; published 22 August [1] Antarctic coastal polynyas are areas of reduced sea ice cover within the ice pack and their associated surface waters are noted for sustaining enhanced levels of biological production during the spring and summer. Here we present satellite-based estimates of interannual changes in the areal extent, phytoplankton abundance, and primary productivity within 37 Antarctic coastal polynya systems over five annual cycles (1997 to 2002). The largest polynya studied was located in the Ross Sea (396,500 km 2 ) while the smallest was located in the West Lazarev Sea (1040 km 2 ). Most polynyas attained maximum areal extents in February of less than 20,000 km 2. Mean polynya chlorophyll a from 1 September to 31 March ranged from 0.16 to 2.2 mg m 3, averaging 0.69 mg m 3. Daily production averaged 0.09 to 0.76 g C m 2 d 1. Mean annual primary production ranged from 18 to 161 g C m 2 yr 1, with most coastal polynyas exhibiting annual rates of production between 20 and 80 g C m 2. Total production (the product of the open water area and the spatial mean daily primary production rate) varied by 2 orders of magnitude, from 0.03 to 48 Tg C yr 1. Taken together, the Ross Sea, Ronne Ice Shelf, Prydz Bay, and Amundsen Sea polynyas are responsible for >75% of total polynya production. In eastern Antarctica, where 91% of all Adélie penguin colonies are associated with a coastal polynya, the magnitude of annual production in polynyas explained 65% of the variance in penguin colony size. INDEX TERMS: 4815 Oceanography: Biological and Chemical: Ecosystems, structure and dynamics; 4275 Oceanography: General: Remote sensing and electromagnetic processes (0689); 4842 Oceanography: Biological and Chemical: Modeling; 4805 Oceanography: Biological and Chemical: Biogeochemical cycles (1615); KEYWORDS: Antarctica, polynya, primary production, phytoplankton Citation: Arrigo, K. R., and G. L. van Dijken, Phytoplankton dynamics within 37 Antarctic coastal polynya systems, J. Geophys. Res., 108(C8), 3271, doi: /2002jc001739, Introduction [2] Polar marine waters, and their associated annually forming sea ice cover, are widely recognized for the role they play in globally important processes such as the carbon cycle [Arrigo and McClain, 1994; Arrigo et al., 2000; Smith, 1995; Smith et al., 1997; Becquevort and Smith, 2001], air-sea gas exchange [Sweeney et al., 2000], surface heat budget [Budillon et al., 2000; Roberts et al., 2001], and oceanic thermohaline circulation [Grigg and Holbrook, 2001; Stossel et al., 2002; Buffoni et al., 2002]. In recent years, attention has focused on processes associated with structural features unique to these ice-covered high-latitude waters, the coastal polynyas. By its strictest definition, a polynya is an area of open water or reduced sea ice cover located in waters that would be expected to be ice covered. As such, polynyas are usually considered to be wintertime phenomena. However, surface waters associated with polynyas are often biologically productive because they are the first polar marine systems to be exposed to the increasing springtime solar radiation, either because they lack ice cover altogether or because their weak ice cover is Copyright 2003 by the American Geophysical Union /03/2002JC more susceptible to early breakout in the spring [Mundy and Barber, 2001]. While technically no longer polynyas, these springtime features are important biologically and biogeochemically, and owing to their close relationship to winter polynyas, they will be referred to here as post-polynyas. [3] Coastal polynyas, such as the Mertz Glacier polynya [Bindoff et al., 2001] and the Ross Sea polynya [Fichefet and Goosse, 1999] in the Antarctic, and the NorthEast Water (NEW) polynya and NOrth Water (NOW) polynya in the Arctic [Melling et al., 2001; Mundy and Barber, 2001], are generally wind-driven latent heat polynyas, whose dynamics are controlled largely by synoptic scale winds [Zwally et al., 1985]. They may have a sensible heat component due to the movement of warm waters into the surface layer, either via upwelling [Davis and McNider, 1997] or tidal forcing [Polyakov and Martin, 2000], but this is often relatively small. In some regions, their dynamics may also be governed by strong katabatic winds that drive extremely high rates of sea ice production, as older sea ice is continually blown offshore and replaced by newly formed frazil ice. Notable examples are the Antarctic polynyas in Commonwealth Bay [Wendler et al., 1997], Terra Nova Bay in the western Ross Sea [Bromwich and Kurtz, 1984; Bromwich et al., 1992; Van Woert et al., 2001], and Dumont d Urville [Adolphs and Wendler, 1995]. Coastal polynyas, 27-1

2 27-2 ARRIGO AND VAN DIJKEN: PHYTOPLANKTON DYNAMICS IN ANTARCTIC POLYNYAS such as the Mertz Glacier and Terra Nova Bay polynyas, can also result from the presence of glacial ice which deflects sea ice away from the coast, resulting in open water along their downstream margins [Massom et al., 1998, 2001]. On longer timescales, the size of coastal polynyas has been shown to be controlled by climate state, although this relationship is not spatially coherent. For example, a 25-year sea ice record shows that the extent of the Ross Sea polynya was at its historical minimum during the El Niño [Arrigo and Van Dijken, 2003], the same year that the Ronne Polynya in the Weddell Sea attained its historical maximum size [Ackley et al., 2001]. [4] Although they are relatively small in area, coastal polynyas play a disproportionately important role in a variety of physical and biological processes. As areas of appreciable sea ice production and salt flux, coastal polynyas are important to the formation of high-salinity shelf water (HSSW) [Bindoff et al., 2001; Buffoni et al., 2002] and Antarctic bottom water [Vaz and Lennon, 1996; Stossel et al., 2002]. Recent model results demonstrate that including brine rejection from polynyas produces a more stable modeled thermohaline circulation and that the presence of open water within modeled sea ice contributes significantly to the sensitivity of the climate response [Grigg and Holbrook, 2001]. In addition, air-sea heat fluxes in polynyas can be very high because of the large air-sea temperature differences in winter [Dare and Atkinson, 2000; Roberts et al., 2001]. In the Ross Sea, measured loss of heat to the atmosphere was greatest during May, averaging 217 W m 2 between 1994 and 1997 [Budillon et al., 2000]. Short-term measurements of heat flux to the atmosphere in the Mertz Glacier polynya were even greater (575 W m 2 under windy conditions and 250 W m 2 during calmer conditions). [5] Coastal polynyas are also regions of enhanced oceanic primary and secondary production as well as other biogeochemical processes. The growth and accumulation of phytoplankton biomass, including diatoms [Gradinger and Baumann, 1991; Von Quillfeldt, 1997; Arrigo et al., 2000], dinoflagellates [Dennett et al., 2001], and prymnesiophytes [Kopczynska et al., 1995; Arrigo et al., 2000; Rey at al., 2000; Becquevort and Smith, 2001; Dennett et al., 2001; Gowing et al., 2001] are much greater within polynyas than in adjacent waters. Rates of primary production by these phytoplankton often exceed 1 g C m 2 d 1 [Arrigo et al., 2000], and the proportion of new to regenerated production is generally high, with f ratios ranging from 0.6 to 0.8 [Smith, 1995; Smith et al., 1997; Cochlan et al., 2002]. As a result of their enhanced productivity, polynyas are frequently the site of high rates of particle flux [Cooper et al., 2002], due to both increased rates of fecal pellet production [Gowing et al., 2001] and the formation of aggregates late in the bloom [Becquevort and Smith, 2001]. Surface nutrients are often depleted almost to exhaustion [Kattner and Budeus, 1997], even when initial concentrations are extremely high [Gibson and Trull, 1999]. Interestingly, although the data are somewhat scarce, bacterial abundance in some polynyas appears to be unusually low, considering the high rates of primary production measured there [Billen and Becquevort, 1991; Ducklow et al., 2000]. [6] Polynyas are also critical habitats for a wide variety of higher trophic level organisms. The dominant zooplankton grazers found in these ecosystems include microzooplankton [Li et al., 2001], copepods [Hosie and Cochran, 1994; Li et al., 2001], krill [Hosie and Cochran, 1994; Pakhomov et al., 2002], and salps [Li et al., 2001; Pakhomov et al., 2002]. These pelagic grazers in turn fuel the growth of larger predatory organisms such as seabirds [Woehler, 1997; Gilchrist and Robertson, 2000], seals [McMahon et al., 2002], and whales [Gill and Thiele, 1997]. Benthic organisms such as sponges, echinoderms, crustaceans, and cnidarians also rely on this concentrated phytoplanktonbased food source for a large fraction of their nutrition [Ambrose and Renaud, 1995]. [7] While the importance of polynyas as a site of concentrated biological activity is now widely accepted, our understanding of these ecosystems is still based on relatively few, well-studied examples (NEW, NOW, Ross Sea, Prydz Bay, etc.). To date, there has been no comprehensive investigation of polynyas in either the Arctic or the Antarctic that would allow for the quantification of their relative importance to either local or regional rates of productivity. The Antarctic alone has dozens of coastal polynyas, most of which have never been studied in any detail. Here we present an analysis of satellite data that identifies 37 different coastal polynya systems surrounding the Antarctic continent and derive a 5-year time series of polynya dynamics and phytoplankton abundance and productivity associated with each. This information is used to compute the amount of biological productivity associated with each of these polynyas and to characterize how this productivity varies both interannually and as a function of the physical environment. Finally, we use estimates of individual polynya productivity to help understand the distribution and size of Adélie penguin colonies around the Antarctic continental margin. 2. Methods 2.1. Sea Ice [8] Daily sea ice distributions between June 1997 and May 2002 were computed from SSM/I data obtained from the EOS Distributed Active Archive Center (DAAC) at the National Snow and Ice Data Center, University of Colorado, Boulder, Colorado. SSM/I brightness temperatures were used as input to the enhanced resolution PSSM algorithm of Markus and Burns [1995]. Rather than producing maps of sea ice concentration at the usual 25-km resolution, this algorithm determines whether or not a given SSM/I subpixel (6.25 km) contains sea ice. If the ice cover is calculated to be greater than approximately 10%, then the sub-pixel is defined as being ice covered. If there is less than 10% ice cover, then a given sub-pixel is identified as open water Polynya Masks [9] The daily images of sea ice distribution produced in the manner described above were used to construct a spatial map of the number of days during the months of June through October over the 5-year study period that each pixel location was ice-free (Figure 1a). This map was used to identify the location of coastal polynyas based on the understanding that polynyas experience the greatest number of ice-free days. Using a threshold of 50% ice-free winter days to qualify as a polynya, 52 polynyas were detected

3 ARRIGO AND VAN DIJKEN: PHYTOPLANKTON DYNAMICS IN ANTARCTIC POLYNYAS 27-3 phytoplankton blooms associated with each post-polynya is larger than the wintertime polynya area and was estimated using ocean color information obtained by the Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Spatial overlays (Figure 1b) were produced from SSM/I sea ice distributions and the SeaWiFS-derived phytoplankton bloom areas and used as a guide to assign pixels from all SeaWiFS imagery either to one of the 37 post-polynyas or to the non-polynya continental shelf (approximately 54% of the Antarctic continental shelf). In this way, the annual cycles of chlorophyll a (Chl a) and primary production were derived independently for each post-polynya and for the Antarctic continental shelf (depth < 1000 m) Chlorophyll a [10] SeaWiFS data were obtained from the Goddard Earth Sciences Data and Information Services Center, DAAC, for the time period of September 1997 through April Chl a concentrations (mg m 3 ) were derived from SeaWiFS 8-day Level 3 binned files (fourth reprocessing), which utilizes the OC4v4 algorithm [O Reilly et al., 1998]. The spatial resolution of these images is constant with latitude (9.8 km) but variable with longitude, ranging from 4.3 km at a latitude of 63 S to 2.0 km at 78 S. Most of the Antarctic continent (particularly east Antarctica) lies between the latitudes of 65 S and 70 S where SeaWiFS pixels are at a longitudinal resolution of km. Figure 1. Map of the Antarctic showing locations of the 37 post-polynyas investigated during this study (names can be found in Table 1). (a) Colored region indicates the percentage of days between 1 June and 31 October between 1997 and 2001 that a particular pixel location was ice-free. Coastal areas with low winter sea ice cover were identified as polynyas. (b) Variable colored areas are masks used to associate a given pixel location with a particular polynya and extend at most as far north as the continental shelf (depth < 1000 m). Continental shelf area not associated with a polynya is shown in white. during (Figures 1a and 2). Because in some cases adjacent polynyas coalesce between winter and spring, these were treated as a single post-polynya. A good example is found in Prydz Bay where three distinct winter polynyas (polynya 25 in Figure 2) fuse to form a single large post-polynya in early spring. The original 52 polynyas were reduced to a final total of 37 post-polynyas in this way (Figure 1b, Table 1). The maximum horizontal extent of 2.4. Primary Production [11] The radiative transfer model of Gregg and Carder [1990] was used to compute clear sky downwelling irradiance each hour, which was subsequently corrected for fractional cloud cover, derived from monthly climatologies, according to the equation of Dobson and Smith [1988]. Phytoplankton primary production (mg C m 3 hr 1 ) was calculated as a function of diurnal changes in spectral downwelling irradiance, water temperature ( C), and Chl a concentration as described by Arrigo et al. [1998] assuming a carbon:chl a ratio of 90. It was assumed that the Chl a concentration and the carbon:chl a ratio were both uniform with depth within the euphotic zone. This assumption is justified in well-mixed waters, and introduces only a small error in stratified waters because the exponential decline in irradiance results in primary productivity being concentrated within near surface waters. Lower Chl a concentration and higher carbon:chl a ratios in deeper waters contribute relatively little to depth integrated production, minimizing the impact of our assumption of uniformity with depth. Productivity at each SeaWiFS pixel location was integrated over depth (at 0.1 m vertical resolution near the surface, increasing gradually to <5 m at the 1% light depth) and time (hourly for 24 hours) to determine daily primary production (mg C m 2 d 1 ). 3. Post-Polynya Sizes [12] In many respects, the method used here to estimate the size of coastal polynyas is preferable to most other methods of polynya detection that are also based upon SSM/I sea ice concentrations. The PSSM algorithm we employed yields maps of open water area at a resolution 16 times greater than that obtained using the standard SSM/I

4 27-4 ARRIGO AND VAN DIJKEN: PHYTOPLANKTON DYNAMICS IN ANTARCTIC POLYNYAS Figure 2. Expanded view of Figure 1a showing in greater detail the size and distribution of Antarctic coastal polynyas. At one extreme, areas in red are those that never became ice-free during the winter months. At the other extreme, black areas remained ice free all winter. product (39 km 2 versus 625 km 2 ). This means that the PSSM algorithm can identify areas of open water that are much smaller than those detectable in the standard SSM/I sea ice product. Standard SSM/I algorithms record small coastal polynyas as areas of reduced sea ice concentration but are unable to accurately characterize the amount of open water associated with them. This is because even where open water is present, the large SSM/I pixel size will often overlap an adjacent region that contains land or sea ice, resulting in an underestimate of the open water area in the ice-free zone and an overestimate of open water in the icecovered zone. As a result, when the standard SSM/I sea ice product is employed to study polynyas, particularly small coastal ones, the sea ice threshold used to characterize a polynya must be set higher than is desirable. The 39 km 2 pixel size of the PSSM algorithm is sufficiently small to allow visualization of even small coastal polynyas in excellent detail (Figure 2). The PSSM algorithm is particularly useful in areas where the band of sea ice around the Antarctic continent is narrow (e.g., off Adélie Land), and it is difficult to distinguish coastal polynyas from the marginal ice zone to the north, where sea ice concentrations also are reduced (Figure 1b). [13] As a result of the different approach used in this study, the winter polynya areas reported here differ markedly from those reported previously by Massom et al. [1998] for 27 east Antarctica coastal polynyas. Our polynya areas are based on a 10% sea ice threshold employed by the PSSM algorithm using daily SSM/I images, while those of Massom et al. [1998] use a 75% sea ice threshold in monthly SSM/I images. In other words, a monthly SSM/I pixel (625 km 2 ) with 75% or less sea ice cover is treated as a polynya pixel by Massom et al. [1998] whereas we require a daily sea ice concentration of 10% (within a 39 km 2 pixel). Because the calculation of polynya area is very sensitive to the sea ice concentration threshold used (see analysis by Massom et al. [1998]), and because Massom et al. [1998] ignored months when the polynya did not develop when calculating mean wintertime polynya area (i.e., zero areas are not used to calculate means), in some cases, polynya areas calculated by Massom et al. [1998] are an order of magnitude or more greater than those presented here. It should be remembered, however, that these are largely operational differences between the two studies based upon how a polynya is defined in terms of sea ice cover and that the polynya locations determined by the two

5 ARRIGO AND VAN DIJKEN: PHYTOPLANKTON DYNAMICS IN ANTARCTIC POLYNYAS 27-5 Table 1. Physical Characteristics of 37 Antarctic Polynyas a Polynya Name Latitude, S Longitude Winter Area, 10 3 km 2 Summer Area, 10 3 km 2 Summer: Winter Ratio Shelf Width, km Number of Days >50% Maximum Size Peak Area Month 1 Ross Sea E Feb 5 2 Sulzberger Bay W Oct 5 3 Hull Bay W Feb 5 4 Wrigley Gulf W Feb 5 5 Amundsen Sea W Jan 5 6 Pine Island Bay W Jan 5 7 Eltanin Bay W Feb 5 8 Latady Island W Mar 5 9 Marguerite Bay W Apr 5 10 Larsen Ice Shelf W Jan 3 11 Ronne Ice Shelf W Feb 2 12 Halley Bay W Feb 4 13 Lyddan Island W Feb 4 14 Maudheim W Feb 5 15 Jelbart Ice Shelf W Mar 5 16 W. Lazarev Sea E Mar 4 17 E. Lazarev Sea E Feb 5 18 Breid Bay E Mar 5 19 Lützoh-Holm Bay E Apr 1 20 Amundsen Bay E Mar 5 21 Cape Borle E Feb 5 22 Utstikkar Bay E Feb 5 23 Cape Darnley E Jan 5 24 Mackenzie Bay E Feb 5 25 Prydz Bay E Feb 5 26 West Ice Shelf E Feb 3 27 Davis Sea E Mar 5 28 Shackleton Ice Shelf E Feb 4 29 Vincennes Bay E Feb 5 30 Cape Poinsett E Feb 5 31 Henry Bay E Feb 5 32 Paulding Bay E Feb 5 33 Porpoise Bay E Mar 2 34 Davis Bay E Jan 5 35 Dumont d Urville E Feb 5 36 Mertz Polynya E Dec 5 37 Ninnis Glacier E Feb 5 a Data are based on 5-year averages. Locations are shown in Figure 1. Number Years Formed studies agree very well. In our study, a polynya is virtually ice free; in the study by Massom et al. [1998], it is a region with ice cover below 75%. [14] The 37 Antarctic coastal post-polynyas identified in this study range widely in their physical attributes, including their minimum and maximum size, seasonal change in open water area, length of time each post-polynya remains expanded in the spring and summer, month that peak open water area is reached, and recurrence rate. The amount of open water within this group of 37 post-polynyas varies by more than 2 orders of magnitude both during the winter and the summer. The Ross Sea polynya, by far the largest of the Antarctic polynyas, has a mean open water area of 20,230 km 2 in winter and a post-polynya area of 396,500 km 2 in summer (Figure 3, polynya 1, Table 1). In contrast, the smallest Antarctic polynya identified here, located in the West Lazarev Sea (polynya 16), averages only 130 km 2 in size in the winter and 1040 km 2 as a postpolynya in the summer. A size frequency distribution shows that 25 of the 37 post-polynyas (68%) had a maximum size over the 5-year study of 20,000 km 2 or less (Figure 4a) and another 10 post-polynyas (27%) had maximum sizes between 20,000 km 2 and 80,000 km 2. Although there were no post-polynyas between 80,000 km 2 and 300,000 km 2, two (5%) extremely large post-polynyas exhibited maximum sizes larger than 300,000 km 2 (the Ronne Ice Shelf and Ross Sea post-polynyas). [15] The mean summer (February) post-polynya size exhibited a frequency distribution (Figure 4b) that was generally similar to the 5-year maximum (Figure 4a), with most of the post-polynyas being among the smaller size classes. Approximately one third of the post-polynyas attained 5-year mean open water areas during the summer of 5000 km 2 or less and 34 of the 37 post-polynyas (92%) were less than 40,000 km 2 in area. Log-transformation of the summer post-polynya areas shows a distinct lognormal size frequency distribution (Figure 4c). An analysis of postpolynya size versus location indicates that there was no significant relationship between these two variables; small post-polynyas were as likely to be found in the eastern Antarctic as they were in the west and as likely to be found in the South Pacific, South Atlantic, and South Indian Ocean sectors of the Antarctic continental shelf. [16] Polynya size during the winter (September, Figure 4d) was also lognormally distributed (Figure 4e), with 36 of the 37 polynyas attaining sizes below 10,000 km 2 and 29 of these (78%) exhibiting mean winter areas below 3000 km 2. The small wintertime size of most Antarctic polynyas is in stark contrast to the Ross Sea polynya, which averages 20,230 km 2 during winter (Table 1), a value that is greater

6 27-6 ARRIGO AND VAN DIJKEN: PHYTOPLANKTON DYNAMICS IN ANTARCTIC POLYNYAS

7 ARRIGO AND VAN DIJKEN: PHYTOPLANKTON DYNAMICS IN ANTARCTIC POLYNYAS 27-7 Figure 4. Frequency histogram for the 37 polynyas investigated during this study of (a) maximum polynya size, (b) mean polynya size during the month of February, (c) log mean polynya size during the month of February, (d) mean polynya size during the month of September, (e) log mean polynya size during the month of September, (f ) the ratio of the February:September polynya size, (g) the number of days that polynya size exceeded 50% of its seasonal maximum value, (h) the month when polynya size reached its annual maximum, and (i) the number of years each polynya exhibited a summer expansion in area. than the mean peak summer area of 25 of the 36 other Antarctic polynyas. [17] In addition to their wide range in size, Antarctic postpolynyas also exhibit marked differences in the magnitude of seasonal changes in open water area. The smallest change in size in transitioning from a winter polynya to a summer postpolynya was a factor of 2 associated with the Sulzberger Bay polynya (Table 1). On average, Antarctic post-polynya area increased ninefold between winter and summer (Figure 4f ), with some post-polynyas increasing in size by as much as a factor of >20 (e.g., Ronne Ice Shelf, Amundsen Bay, and Utstikkar Bay). Most (73%), exhibited winter-summer increases ranging from a factor of There was no significant relationship (p = 0.39) between the magnitude of the seasonal change in polynya size and either the mean polynya size (i.e., the big polynyas did not necessarily undergo larger proportional changes in area between winter and summer) or polynya location. Figure 3. (opposite) Annual cycle of the minimum, maximum, and 5-year mean post-polynya area for the 37 polynyas investigated during this study (names can be found in Table 1). Y axis is scaled to the area of the post-polynya mask (Figure 1b).

8 27-8 ARRIGO AND VAN DIJKEN: PHYTOPLANKTON DYNAMICS IN ANTARCTIC POLYNYAS [18] All Antarctic post-polynyas reached their peak open water area between the months of October and April, exhibiting a normal frequency distribution within this 7-month timeframe (Figure 4h). Most Antarctic postpolynyas (21 of 37) reached their mean peak size during the month of February, with 33 of 37 (89%) post-polynyas peaking in size between January and March. The Sulzberger Bay post-polynya is the earliest to peak (October) on average, but also exhibits a highly variable seasonal cycle in open water area (polynya 2, Figure 3). In years when the Sulzberger Bay post-polynya is relatively large, it attains peak size in October, but during heavy ice years, the peak can be delayed until February. For post-polynyas in the Bellingshausen- Amundsen Sea, one of the few regions of the Antarctic where the coast is oriented in a north-south direction, there appears to be a temporal progression in the time that peak postpolynya size is attained, with post-polynyas to the south peaking earlier than those in the north (Table 1). For example, moving south to north, the Pine Island Bay post-polynya peaked in January while the adjacent post-polynya in Eltanin Bay peaked one month later (February). Then in March, the Latady Island post-polynya reached its maximum size, and in April, so did the Marguerite Bay post-polynya. This latitudinal progression is likely to be the consequence of the later refreezing of sea ice associated with the warmer, more northerly positioned post-polynyas. [19] As an indicator of how long post-polynyas were in their expanded state during the spring and summer, the number of days that each post-polynya exceeded 50% of its maximum summertime area was calculated from the mean area for each post-polynya (Figure 4g). As can be seen from Figure 3, most post-polynyas undergo rapid increases in size in spring and subsequent decreases in late summer when light is plentiful, and therefore, the 50% threshold provides a good estimate of the amount of the time available for phytoplankton blooms. On average, Antarctic post-polynyas remained in their expanded state for 115 ± 24 days, with a range of 74 to 173 days. The two largest post-polynyas (Ross Sea and Ronne Ice Shelf) remained open for only 100 and 88 days, respectively. The longest surviving spring/ summer post-polynyas were in Marguerite Bay (173 days) and the Larsen Ice Shelf (162 days), two relatively small post-polynyas (Table 1). The two shortest lived (74 days) spring/summer post-polynyas were even smaller (Porpoise Bay and Lützoh-Holm Bay), but again, there was no significant relationship between the amount of time a postpolynya remained open and either its size (p = 0.40) or its location (p = 0.50). [20] The other late (April) peaking post-polynya, located in Lützoh-Holm Bay, only expanded from its winter area once between 1997 and 2002 making it difficult to determine a likely cause for its late development during its lone year of expansion. This is unusual because the majority of the Antarctic coastal post-polynyas identified in this study formed every year (28 of 37) or four or more out of the 5 years (32 of 37) (Figure 4i). The more sporadically forming spring/summer post-polynyas cannot be easily categorized on the basis of their size or any other simple physical characteristic. Although many of these post-polynyas were rather small (Porpoise Bay, West Ice Shelf, Lützoh-Holm Bay), the list also includes the Ronne Ice Shelf post-polynya, one of the largest Antarctic post-polynyas. These post-polynyas are widely distributed over the Antarctic continental shelf, often adjacent to the more regularly forming post-polynyas. The main generalization that can be made is that the Weddell Sea contains a disproportionate number of sporadic postpolynyas, including the Larsen Ice Shelf post-polynya (3 of 5 years), the Ronne Ice Shelf post-polynya (2 of 5 years), The Halley Bay post-polynya (4 of 5 years) and the Lyddan Island post-polynya (4 of 5 years). 4. Phytoplankton Blooms 4.1. Phytoplankton Biomass [21] As expected from their varying sea ice dynamics, the coastal post-polynyas surrounding Antarctica exhibited highly variable phytoplankton dynamics as well. In broad terms, the temporal progression of phytoplankton blooms in all of the post-polynyas was similar, with concentrations of Chl a beginning at very low levels in September (Figure 5), but slowly increasing in the early austral spring (October) in response to increased solar insolation. Phytoplankton Chl a consistently reached a peak during summer, and then began to decline, usually reaching pre-bloom levels by March or April. Although this general pattern applies to all 37 Antarctic coastal post-polynyas, there were marked interpost-polynya differences in the timing, size, and intensity (with respect both to standing crop and primary production) of these phytoplankton blooms. For example, the Chl a time series of many post-polynyas exhibited temporally broad peaks (e.g., post-polynyas 1, 9, 22, 25, 27, 36), indicating that phytoplankton blooms in these waters persisted for 3 months or more. Others expressed a more irregular pattern, with one or more relatively short-lived (weeks) spikes in Chl a (e.g., post-polynya 23, 24, 31, 33), suggesting more transient bloom conditions. Still others showed a bi-modal pattern (e.g., post-polynya 19, 20, 32, 33, 36, 37), whereby an initial bloom in December-January was followed shortly thereafter by a second bloom in February March. [22] The specific pattern of increase and subsequent decline of the phytoplankton blooms varied dramatically between post-polynyas (Figure 5), with most (46%) exhibiting a slow, steady increase in Chl a followed by a similarly steady decline (e.g., post-polynyas 3, 8, 10, 15 19, 21, 26 30, 32, 34, 35). Although post-polynyas exhibiting these bloom dynamics are located in most Antarctic sectors, they are mostly restricted to waters adjacent to the area between Queen Maud Land and Wilkes Land (see Figure 1b, Table 2). The next most common phytoplankton bloom dynamic (29.7%) consists of a similarly steady increase in Chl a but followed by a very abrupt decline (e.g., post-polynyas 2, 7, 11, 12, 14, 20, 22 24, 36). Postpolynyas of this bloom type are distributed all around the Antarctic continent (Figure 1b), exhibiting no discernable spatial pattern. This is also true of those post-polynyas exhibiting a rapid increase in Chl a followed by a steady decline, although these were relatively rare, accounting for only 11% of all Antarctic post-polynyas (e.g., postpolynyas 5, 6, 13, 37). Post-polynyas exhibiting a rapid increase in Chl a followed by an equally rapid decline (e.g., post-polynyas 1, 4, 9, 25, 33) were also uncommon (13.5%), but include some of the most productive of all Antarctic post-polynyas, including the Ross Sea and Prydz Bay post-polynyas (see below).

9 ARRIGO AND VAN DIJKEN: PHYTOPLANKTON DYNAMICS IN ANTARCTIC POLYNYAS 27-9 Figure 5. Annual cycle of the minimum, maximum, and 5-year mean Chl a for the 37 polynyas investigated during this study (names can be found in Table 1).

10 27-10 ARRIGO AND VAN DIJKEN: PHYTOPLANKTON DYNAMICS IN ANTARCTIC POLYNYAS Table 2. Phytoplankton Blooms of 37 Antarctic Polynyas a Polynya Name Chl a Bloom, mg m 3 Chl a January, mg m 3 PP Bloom, gcm 2 d 1 PP January, gcm 2 d 1 PP Annual, gcm 2 PP Total, Tg C yr 1 Bloom Time Series 1 Ross Sea 1.51 ± ± ± ± ± ± Sulzberger Bay 0.69 ± ± ± ± ± ± Hull Bay 0.75 ± ± ± ± ± ± Wrigley Gulf 1.34 ± ± ± ± ± ± Amundsen Sea 2.18 ± ± ± ± ± ± Pine Island Bay 1.42 ± ± ± ± ± ± Eltanin Bay 0.80 ± ± ± ± ± ± Latady Island 1.37 ± ± ± ± ± ± Marguerite Bay 1.44 ± ± ± ± ± ± Larsen Ice Shelf 0.47 ± ± ± ± ± ± Ronne Ice Shelf 1.17 ± ± ± ± ± ± Halley Bay 0.68 ± ± ± ± ± ± Lyddan Island 0.39 ± ± ± ± ± ± Maudheim 0.55 ± ± ± ± ± ± Jelbart Ice Shelf 0.30 ± ± ± ± ± ± W. Lazarev Sea 0.28 ± ± ± ± ± ± E. Lazarev Sea 0.38 ± ± ± ± ± ± Breid Bay 0.26 ± ± ± ± ± ± Lützoh-Holm Bay 0.17 ± ± ± ± ± ± Amundsen Bay 0.25 ± ± ± ± ± ± Cape Borle 0.35 ± ± ± ± ± ± Utstikkar Bay 0.34 ± ± ± ± ± ± Cape Darnley 0.80 ± ± ± ± ± ± Mackenzie Bay 0.98 ± ± ± ± ± ± Prydz Bay 1.22 ± ± ± ± ± ± West Ice Shelf 0.16 ± ± ± ± ± ± Davis Sea 0.73 ± ± ± ± ± ± Shackleton Ice Shelf 0.34 ± ± ± ± ± ± Vincennes Bay 0.49 ± ± ± ± ± ± Cape Poinsett 0.48 ± ± ± ± ± ± Henry Bay 0.31 ± ± ± ± ± ± Paulding Bay 0.17 ± ± ± ± ± ± Porpoise Bay 0.35 ± ± ± ± ± ± Davis Bay 0.51 ± ± ± ± ± ± Dumont d Urville 0.49 ± ± ± ± ± ± Mertz Polynya 0.59 ± ± ± ± ± ± Ninnis Glacier 0.82 ± ± ± ± ± ± a Data are based on 5 year averages. Locations are shown in Figure 1. For the bloom time series, + + indicates a rapid increase in chlorophyll a followed by a rapid decline, + indicates a rapid increase followed by a steady decline, + indicates a steady increase followed by a rapid decline, and indicates a steady increase and a steady decline. [23] Time- and space-averaged Chl a concentration in icefree surface waters over the course of the phytoplankton bloom (1 September through 31 March) varies by over an order of magnitude between Antarctic coastal post-polynyas, from 0.16 mg m 3 in the West Ice Shelf post-polynya to 2.2 mg m 3 in the Amundsen Sea post-polynya (Table 2), averaging 0.69 mg m 3 for all post-polynyas. Eight postpolynyas had mean bloom Chl a concentrations exceeding 1mgm 3, including those in the Ross Sea, Wrigley Gulf, Amundsen Sea, Pine Island Bay, Latady Island, Marguerite Bay, Ronne Ice Shelf, and Prydz Bay (Table 2). With the exception of the Prydz Bay post-polynya, all of these post-polynyas are restricted to the region bounded by the Ross Sea, Amundsen Sea, and the Antarctic Peninsula. The frequency distribution for mean Chl a across all postpolynyas is lognormal, with approximately half of the postpolynyas (18 of 37) exhibiting a mean Chl a concentration between 0.2 mg m 3 and 0.6 mg m 3 (Figure 6a). [24] Statistical analyses showed that the mean level of Chl a in Antarctic post-polynyas during the spring phytoplankton bloom was not related to either the relative change in postpolynya size from winter to summer (r 2 = 0.05, p = 0.19), the number of days a particular post-polynya was open (r 2 = 0.005, p = 0.692), or the month when peak Chl a was attained (r 2 = 0.02, p = 0.4). There was a significant, albeit weak relationship with seasonal peak post-polynya size (r 2 = 0.18, p = 0.009), which was able to explain 18% of the inter-post-polynya variation in mean Chl a concentration during the bloom. The physical variable most strongly related to mean bloom Chl a was the width of the section of continental shelf where the post-polynya was located (r 2 = 0.30, p = ), with post-polynyas over a wider shelf exhibiting higher mean Chl a concentrations. This positive correlation between continental shelf width and mean Chl a during the bloom probably explains why mean Chl a is higher in post-polynyas of the west Antarctic, where the continental shelves are wider (Figure 1b). As further evidence of this relationship, the only post-polynyas in the east Antarctic where mean Chl a exceeded 1 mg m 3 were associated with Prydz Bay, where the continental shelf is also relatively wide for that region. Multiple linear regression analysis using all five of the above variables was able to explain 34% of the inter-post-polynya variation in mean Chl a concentration during the bloom. This represents only a minor improvement over the single variable, continental shelf width, which was able to explain 30% of the variation.

11 ARRIGO AND VAN DIJKEN: PHYTOPLANKTON DYNAMICS IN ANTARCTIC POLYNYAS average 2.6-fold higher than the mean value calculated for the entire bloom period (Figure 6c). The peak bloom Chl a concentration in the Amundsen Sea post-polynya, which ranked highest among all Antarctic post-polynyas, was over 50% greater than in any other post-polynya. The Ross Sea post-polynya, which had the second highest mean bloom Chl a concentration, exhibited only the sixth greatest peak bloom Chl a concentration, with the Wrigley Gulf, Pine Island Bay, Latady Island, and Prydz Bay post-polynyas exhibiting higher concentrations. Of the 37 Antarctic postpolynyas, 16 had Chl a concentrations that were below 1mgm 3 during the peak of their phytoplankton bloom (Figure 6c). These included all the post-polynyas from Queen Maud Land to MacRobertson Land (Figure 1b) and half of those between MacRobertson Land and Victoria Land (Table 2). [26] The relationship between peak bloom Chl a concentration and characteristics of the physical environment for each post-polynya were weaker than they were for the mean bloom Chl a concentration. A multiple regression analysis of peak bloom Chl a against the same five variables used above explained only 12% of the variance in peak bloom Chl a concentration, only slightly higher than was explained by continental shelf width alone (r 2 = 0.11, p = 0.04). There was no significant relationship between peak bloom Chl a and either the post-polynya size (r 2 = 0.06, p = 0.14), the number of days the post-polynya remained expanded (r 2 = , p = 0.947), the month that the peak Chl a was attained (r 2 = 0.04, p = 0.22), or the amplitude of the seasonal change in post-polynya size (r 2 = 0.03, p = 0.32). Figure 6. Frequency histogram for the 37 polynyas investigated during this study of (a) mean Chl a during the phytoplankton bloom (1 September to 31 March), (b) the month when Chl a reached its annual maximum, (c) mean Chl a during the month of January, (d) the month when primary production reached its annual maximum, (e) mean primary production during the phytoplankton bloom (1 September to 31 March), (f ) mean primary production during the month of January, (g) mean annual primary production, and (h) log mean primary production. [25] Most Antarctic post-polynyas (89%) attain their maximum levels of phytoplankton biomass between December and February, with over half exhibiting a January peak (Figure 6b). Chl a values during the peak of the phytoplankton bloom ranged from 0.24 to 7.0 mg m 3, with most post-polynyas exhibiting a peak that was on 4.2. Primary Production [27] The annual cycle of primary production was similar to that of Chl a, but with substantially less high frequency variation (Figure 7). This is because primary production is calculated as a function of both Chl a and downwelling irradiance, and therefore, the effect of large and rapid changes in Chl a on primary production is diminished, particularly near the beginning and the end of the growing season when light is reduced (e.g., compare Polynyas 8 or 23 in Figures 5 and 7). All 37 post-polynyas exhibited peaks in primary production between December and February (Figure 6d), with most (51%) peaking in January and the rest with peaks equally distributed between the months of December (9 of 37) and February (9 of 37). [28] Daily primary production averaged over the course of the phytoplankton bloom exhibited less inter-post-polynya variation than did Chl a, ranging from 0.09 g C m 2 d 1 in Lützoh-Holm Bay to 0.76 g C m 2 d 1 in the Amundsen Sea post-polynya (Table 2). Most post-polynyas (54%) had mean daily production rates below 0.3 g C m 2 d 1 (Figure 6e) during the phytoplankton bloom period of 1 September through 31 March. The three most productive post-polynyas on a daily basis over the course of the phytoplankton bloom (Ross Sea, Pine Island Bay, and Amundsen Sea postpolynyas) were about 50% more productive than any of the 34 other post-polynyas (Table 2). During the month of January, the time of maximum or near-maximum production rates in all Antarctic post-polynyas (Figure 6d), mean primary production varied from 0.18 g C m 2 d 1 in the Paulding Bay post-polynya to 2.1 g C m 2 d 1 in the Amundsen Sea post-polynya (Table 2), or 2 3 times the

12 27-12 ARRIGO AND VAN DIJKEN: PHYTOPLANKTON DYNAMICS IN ANTARCTIC POLYNYAS Figure 7. Annual cycle of the minimum, maximum, and 5-year mean daily primary production for the 37 polynyas investigated during this study (names can be found in Table 1). mean rate for the entire bloom period. Twelve of the 37 Antarctic post-polynyas (32%) exhibited maximum production rates between 0.4 and 0.6 g C m 2 d 1 (Figure 6f ) and 43% ranged from 0 to 1.0 g C m 2 d 1. [29] Mean annual primary production between 1997 and 2002 associated with coastal post-polynyas ranged from 18 g C m 2 yr 1 (Lützoh-Holm Bay post-polynya) to 161 g Cm 2 yr 1 (Amundsen Sea post-polynya). There is a weak,

13 ARRIGO AND VAN DIJKEN: PHYTOPLANKTON DYNAMICS IN ANTARCTIC POLYNYAS albeit significant, relationship between winter polynya size and the magnitude of annual production (r 2 = 0.30, p < 0.004), with larger polynyas tending to be more productive. The Ross Sea and the Pine Island Bay postpolynyas were nearly as productive as the Amundsen Sea, both exhibiting annual rates of 151 g C m 2. The majority of coastal post-polynyas (76%) exhibited annual rates of production between 20 and 80 g C m 2 (Figure 6g). As was the case for mean daily primary production during the phytoplankton bloom, production in the three most productive post-polynyas was approximately 50% greater than all other post-polynyas studied (Figure 6g, Table 2). The most productive post-polynyas were located in the Ross, Amundsen, and Bellingshausen seas while annual production in the post-polynyas of East Antarctica was generally low, with only the phytoplankton bloom in the Prydz Bay post-polynya exceeding an annual production rate of 100 g C m 2 yr 1. [30] Annual production within waters encompassed by all of the 37 Antarctic post-polynyas averaged 118 g C m 2 yr 1 between 1997 and It must be noted, however, that this value is heavily weighted by the large and highly productive Ross Sea post-polynya. When mean post-polynya production is recalculated without regard to post-polynya size (i.e., the simple mean of all 37 polynyas is calculated without weighting each post-polynya by its size), this mean annual production rate drops to 66 g C m 2 yr 1 due to the impact of the less productive, but numerous, small post-polynyas. To put these annual estimates in context, primary productivity in all waters south of 50 S, including the permanently open ocean zone, the sea ice zone, and the continental shelf, averages approximately 100 g C m 2 yr 1 [Arrigo et al., 1998]. In aggregate, then, while Antarctic coastal polynyas are more productive per unit area than offshore waters of the Southern Ocean, many individual polynyas are actually less productive on an annual basis. [31] Considering that polynyas are among the most productive of all polar waters, this result may at first seem counterintuitive. However, unlike the open Southern Ocean, post-polynyas are transient features that exist for at most half of the year (Table 1). During that time, production per unit area is often much higher than that of the offshore Southern Ocean. For example, peak production in January Figure 9. Comparison of seasonal changes in postpolynya area with seasonal changes in daily primary production showing the early decline in production relative to refreezing of the sea ice in the most productive Antarctic coastal polynyas. Figure 8. Comparison of the annual cycle of mean primary production for all Southern Ocean waters south of 50 S with (a) the annual cycle of primary production averaged over all coastal polynya waters and with (b) the annual cycle of primary production in each Antarctic coastal polynya. averaged over all post-polynya waters is more than threefold higher than the average for the entire offshore Southern Ocean (Figure 8a). Furthermore, rates of primary production between December and February exceeded those of the offshore Southern Ocean in 80% of the post-polynyas studied (Figure 8b). However, because large areas of the offshore Southern Ocean remain ice free, primary production begins earlier (note lag between peak polynya production and Southern Ocean production in Figures 8a and 8b) and takes place year-round, resulting in an annual produc-

14 27-14 ARRIGO AND VAN DIJKEN: PHYTOPLANKTON DYNAMICS IN ANTARCTIC POLYNYAS tion rate (100 g C m 2 yr 1 ) that is higher than that measured in many coastal polynyas (Table 2). Interestingly, despite the fact that the longer growing season in the open Southern Ocean results in a higher mean rate of production than the average coastal polynya, within the coastal polynya system there was no significant relationship between annual primary production for a given post-polynya and the number of days that that post-polynya remained >50% of its maximum size (r 2 = , p = 0.93). [32] In most polynyas, rates of primary production drop before the post-polynya begins to refreeze in late austral summer (i.e., in most polynyas primary production peaks in January, Figure 6d, while open water area peaks in February, Figure 4h). This decrease in productivity is mirrored in a decline in phytoplankton biomass (Figure 5), which suggests that the change is due either to decreased solar radiation, depleted nutrient concentrations, increased mixed layer depth, or increased grazing pressure during the summer. Because solar radiation is still high through January, this variable is not likely to be a factor in declining rates of production. In most post-polynyas, nutrient exhaustion is also unlikely to limit production because the upper 50 m of the water column contains enough nitrate and phosphate at the start of the growing season to support primary production in excess 100 g C m 2 yr 1. Even if no additional nutrients were made available during the phytoplankton bloom via vertical mixing or recycling (which they certainly are), initial nutrient concentrations are sufficient to support the annual rate of production in 81% of the coastal postpolynyas. Therefore, grazing or increasing mixed layer depth, which are not well understood for most postpolynyas, are likely to be important factors limiting primary production in these less productive post-polynyas. [33] In those few post-polynyas where production exceeds 150 g C m 2 yr 1, nutrient depletion is likely to play an important role in precipitating the phytoplankton bloom decline. Blooms in these post-polynyas often peak and then begin to decline earlier (December) than in the less productive post-polynyas (January), often 2 3 months prior to refreezing in the late summer (Figure 9). In the case of the Ross Sea post-polynya, the decline of the bloom has been linked to nutrient depletion, most likely iron, in early summer [Arrigo et al., 2003]. The similar dynamics of the other productive post-polynyas suggest that nutrient limitation may play a similarly important role there as well. [34] Total production within a given post-polynya, a product of the open water area and the spatial mean rate of daily primary production, varied by more than 2 orders of magnitude between polynyas, ranging from 0.03 Tg C yr 1 in the West Lazarev Sea post-polynya to 48 Tg C yr 1 in the Ross Sea post-polynya (Table 2). Most post-polynyas (86%), however, exhibited total production rates of only 2 TgCyr 1. The annual cycle of total production was much more variable between years (Figure 10) than it had been for areal averaged production (Figure 7) because interannual differences in production are amplified by interannual differences in open water area. This is particularly evident in the 5-year minimum annual cycle of production estimated for each post-polynya. For example, the 5-year minimum rate of daily production on 1 January off the Ronne Ice Shelf (polynya 11) was 0.8 g C m 2 (Figure 7). That same year, however, total production (corrected for open water area) on 1 January was close to zero (Figure 10) because of heavy sea ice cover. This pattern was also observed in the Halley Bay, Breid Bay, Cape Borle, Davis Sea, Vincennes Bay, and Henry Bay post-polynyas. [35] In terms of total area-weighted production, it is clear that a few post-polynyas are responsible for a large fraction of total post-polynya production on the Antarctic continental shelf (Table 2). The dominant post-polynya in this respect is in the Ross Sea, where the production of 48 Tg C annually accounts for half of the total post-polynya production on the entire Antarctic continental shelf (96 Tg C yr 1 ). The high fraction of total production attributable to the Ross Sea post-polynya is due both to its high rate of production per unit area (Table 2) and its large size and recurrence rate (Table 1). Adding to this the production in the Ronne Ice Shelf post-polynya (mean of 14 Tg C yr 1, but annual value can be as high as 45 Tg C yr 1 ), Prydz Bay post-polynya (6.0 Tg C yr 1 ), and the Amundsen Sea post-polynya (5.5 Tg C yr 1 ) means that 4 of the 37 post-polynyas on the Antarctic continental shelf are responsible for >75% of total post-polynya production. We estimate that total production on the Antarctic continental shelf, including post-polynya and non-postpolynya waters, is 148 Tg C yr 1, suggesting that coastal post-polynyas are responsible for 65% of total shelf primary production. Approximately half of all non-post-polynya production on the continental shelf (43 Tg C yr 1 ) is associated with the Antarctic Peninsula (22 Tg C yr 1 ), where sea ice extent is generally low, even in winter, and a large fraction of the Antarctic continental shelf area is located (Figure 1b). 5. Impact on Upper Trophic Levels [36] Polynyas have long been observed to be sites of enhanced productivity at all trophic levels. Until now, however, it has been difficult to quantitatively assess the extent to which population sizes of upper trophic level organisms actually depend on the magnitude of productivity within polynyas. With the estimates of polynya-specific rates of production presented here, it is now possible to relate productivity of specific polynyas to the distribution patterns of the larger organisms believed to rely on them. Although comprehensive circum-antarctic distribution and population data are scarce for most Antarctic wildlife, Ainley [2002] presents valuable data on Adélie penguin distributions that has allowed us to investigate the relationship between the size of the Adélie penguin population at a given rookery and the productivity of any polynya associated with that rookery. [37] Our results show that whether or not an Adélie penguin rookery is associated with a coastal post-polynya depends upon where that rookery is located. In western Antarctica, only 26% of the Adélie penguin rookeries are associated with a recurring coastal post-polynya. Many colonies in this area are located along the Antarctic Peninsula and nearby offshore islands where there is access to large expanses of open water, independent of the formation of coastal post-polynyas. Because of this, sustenance of the breeding colony does not depend solely on phytoplankton production within coastal post-polynyas. In contrast, along the eastern side of Antarctica between Enderby Land and