Biological activity and calcium carbonate dynamics in Greenland sea ice – Implication for the inorganic carbon cycle. Technical Report No. 92

BIOLOGICAL ACTIVITY AND CALCIUM CARBONATE DYNAMICS IN GREENLAND SEA ICE – IMPLICATION FOR THE INORGANIC CARBON CYCLE Dorte H. Søgaard PhD thesis 2014 BIOLOGICAL ACTIVITY AND CALCIUM CARBONATE DYNAMICS IN GREENLAND SEA ICE – IMPLICATION FOR THE INORGANIC CARBON CYCLE ISBN: 87-91214-68-8 Dorte_omslag_Oktober.indd 1 24-10-2014 07:30:13 BIOLOGICAL ACTIVITY AND CALCIUM CARBONATE DYNAMICS IN GREENLAND SEA ICE – IMPLICATION FOR THE INORGANIC CARBON CYCLE PhD thesis 2014 Dorte H. Søgaard Title: Biological activity and calcium carbonate dynamics in Greenland sea ice – Implication for the inorganic carbon cycle Subtitle: PhD thesis Author: Dorte H. Søgaard Affi litations: Greenland Climate Research Centre (c/o Greenland Institute of Natural Resources), Kivioq 2, Box 570, 3900 Nuuk, Greenland University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark Publisher: Greenland Institute of Natural Resources, Nuuk Greenland Year of publication: 2014 PhD supervisors Internal: Professor Ronnie N Glud University of Southern Denmark Campusvej 55 5230 Odense M, Denmark External: Professor Søren Rysgaard Arctic Research Centre, Department of Bioscience Ny Munkegade 116, building 1540 8000 Aarhus C, Denmark Please cite as: Søgaard D.H. (2014) Biological activity and calcium carbonate dynamics in Greenland sea ice – Implication for the inorganic carbon cycle. PhD thesis. Greenland Climate Research Centre and Department of Biology, University of Southern Denmark. Greenland Institute of Natural Resources, 148 pp. Keywords: Subarctic sea ice • High Arctic sea ice • Air-sea CO2 exchange • Greenland • Spatial variability • Calcium carbonate • Net autotrophic activity • Net heterotrophic activity Reproduction permitted provided the source is explicitly acknowledged Layout: Tinna Christensen Cover photo: Jakob Sievers Number of pages: 148 Printed by: Rosendahls – Schultz Grafi sk a/s ISBN: 87-91214-68-8 EAN: 9788791214684 Circulation: 160 Electronic version: www.natur.gl Data sheet Contents List of publications 5 Preface 6 Acknowledgements 7 Abstract 8 Dansk abstrakt (abstract in Danish) 9 Eqikkaaneq (abstract in Greenlandic) 10 CHAPTER 1 – INTRODUCTION 11 1.1 Setting the scene 12 1.1.1 General oceanography of the study areas 13 1.2 Phase I: Transition from open water to ice-covered oceans 14 1.2.1 Sea ice formation – abiotic processes 15 1.2.2 Microorganisms in newly formed sea ice 18 1.2.3 Frost fl owers and brine skim formation – abiotic processes 19 1.3 Phase II: Growing winter sea ice 20 1.3.1 Abiotic processes in growing winter ice 21 1.3.2 Growth limitation of microorganisms in winter sea ice 22 1.4 Phase III: Transition from ice-covered ocean to open waters 23 1.4.1 Abiotic processes in melting sea ice 23 1.4.2 Biotic processes in spring/summer sea ice 24 1.4.3 The open water period 28 1.5 Ocean and sea ice in the context of global change 29 1.6 Conclusions and perspectives 30 1.7 Glossary 31 1.8 Literature cited 34 CHAPTER 2 – PUBLICATIONS 41 Paper I The relative contributions of biological and abiotic 43 processes to carbon dynamics in subarctic sea ice Paper II Ikaite crystal distribution in winter sea ice and 61 implications for CO2 system dynamics Paper III Frost fl owers on young Arctic sea ice: The climatic, chemical 75 and microbial signifi cance of an emerging ice type Paper IV Autotrophic and heterotrophic activity in Arctic fi rst-year 95 sea ice: seasonal study from Malene Bight, SW Greenland Paper V Growth limitation of three Arctic sea ice algal species: 111 eff ects of salinity, pH, and inorganic carbon availability Paper VI Short-term variability in bacterial abundance, cell properties, 121 and incorporation of leucine and thymidine in subarctic sea ice Paper VII High air-sea CO2 uptake rates in nearshore and shelf areas 139 of Southern Greenland: Temporal and spatial variability 5 PhD thesis by Dorte Haubjerg Søgaard List of publications Part of the dissertation Paper I: Søgaard DH, Thomas DN, Rysgaard S, Glud RN, Norman L, Kaartokallio H, Juul-Pedersen T, Geilfus N-X (2013) The relative contributions of biological and abiotic processes to carbon dynamics in subarctic sea ice. Polar Biol 36:1761 – 1777, doi:10.1007/s003-013-1396-6 Paper II: Rysgaard S, Søgaard DH, Cooper M, Pucko M, Lennert K, Papakyriakou TN, Wang F, Geilfus NX, Glud RN, Ehn J, McGinnis DF, Attard K, Sievers J, Deming JW, Barber D (2013) Ikaite crystal distribution in winter sea ice and implications for CO2 system dynamics. TC 7:707 – 718, doi:10.5194/tc7-707-2013 Paper III: Barber DG, Ehn JK, Pucko M, Rysgaard S, Papakyriakou T, Deming J, Galley R, Søgaard DH (2014) Frost fl owers on young Arctic sea ice: The climatic, chemical and microbial signifi cance of an emerging ice type. J Geophys Res-Atmos, doi:10.1002/2014JD021736 Paper IV: Søgaard DH, Kristensen M, Rysgaard S, Glud RN, Hansen PJ, Hilligsøe KM (2010) Autotrophic and heterotrophic activity in Arctic fi rst-year sea ice: seasonal study from Malene Bight, SW Greenland. Mar Ecol Prog Ser 419:31 – 45, doi:10.3354/meps08845* Paper V: Søgaard DH, Hansen PJ, Rysgaard S, Glud RN (2011) Growth limitation of three Arctic sea ice algal species: eff ects of salinity, pH, and inorganic carbon availability. Polar Biol 34:1157 – 1165, doi:10.1007/s00300-011-0976-3** Paper VI: Kaartokallio H, Søgaard DH, Norman L, Rysgaard S, Tison JL, Delille B, Thomas DN (2013) Short-term variability in bacterial abundance, cell properties, and incorporation of leucine and thymidine in subarctic sea ice. Aquat Microb Ecol 71:57 – 73, doi:10.3354/ame01667 Paper VII: Rysgaard S, Mortensen J, Juul-Pedersen T, Sørensen LL, Lennert K, Søgaard DH, Arendt KE, Blicher ME, Sejr MK, Bendtsen J (2012) High air-sea CO2 uptake rates in nearshore and shelf areas of Southern Greenland: Temporal and spatial variability. Mar Chem 128-129:26 – 33, doi:10.1016/j.marchem.2011.11.002 Related work not included in the dissertation Long MH, Koopmans D, Berg P, Rysgaard S, Glud RN, Søgaard DH (2012) Oxygen exchange and ice melt measured at the ice-water interface by eddy correlation. BG 9:1957 – 1967, doi:10.5194/bg-9-1-2012 Geilfus N-X, Galley RJ, Cooper M, Halden N, Hare A, Wang F, Søgaard DH, Rysgaard S (2013b) Gypsum crystals observed in experimental and natural sea ice. Geophys Res Let 40: 1 – 6, doi:10.1002/2013GL058479 Sørensen LL, Jensen B, Glud RN, McGinnis DF, Sejr MK, Sievers J, Søgaard DH, Tison JL, Rysgaard S (2014) Parameterization of atmospheric-surface exchange of CO2 over sea ice. TC 8:853 – 866, doi:10.5194/tc-8-853-2014 Juul-Pedersen, Arendt KE, Mortensen J, Blicher M, Søgaard DH, Rysgaard S (submitted) Seasonal and interannual phytoplankton production in a sub-arctic fj ord (Godthåbsfj ord) connected to the Greeland Ice Sheet. Mar Ecol Prog Ser Søgaard DH, Glud RN, Rysgaard S, Jody Deming (in prep) A comparative study of bioticand abiotic-induced oxygen and inorganic carbon dynamics in meter thick winter and young thin polynya ice. Prepared for Mar Ecol Prog Ser Meire L, Søgaard DH, Juul-Pedersen T, Blicher M, Rysgaard S, Glud RN, Sejr M, Arendt K, Lennert K, Mortensen J (in prep) Infl uence of glacier runoff and biology on the CO2 uptake in a Subarctic Greenlandic fj ord (Godthåbsfj ord, SW Greenland). Prepared for Mar Chem *) The data material was a part of my master´s thesis, but the data processing, writing the paper and the review process was done during my Ph.D. study. **) A small part of the data material was a part of a model project, but the rest of the data, the data processing, writing the paper and the review process was done during my Ph.D. study. Photo: Jakob Sievers.. 6PhD thesis by Dorte Haubjerg Søgaard Preface This dissertation is the result of a 3-year Ph.D. project conducted at the Greenland Climate Research Center (GCRC) and the Greenland Institute of Natural Resources (GINR). The project was funded by the Commission for Scientifi c Research in Greenland (KVUG). Much of the work has been conducted with logistical support by GCRC, GINR, the Department for Education, Church, Culture and Equality (IIKNN), the Marine Basis Monitoring Programmes of Greenland Ecosystem Monitoring (GEM; www.g-e-m.dk), the Canada Excellence Research Chair (CERC) program and the Danish Agency for Science, Technology and Innovation. One of the fi rst descriptions of the transport of CO2 across the sea ice-ocean interface (i.e., the sea ice CO2 pump) was made by E.P. Jones and A.R. Coote (1981) in the year I was born. Now 33 years later the understanding of the seasonal events controlling the inorganic carbon dynamics in icecovered seas is still a challenging subject. A very important factor in climate change is the global carbon budget; and, in order to refi ne it, we need detailed measurements of the seasonal inorganic carbon dynamics in ice-covered seas. My dissertation consists of two chapters: Chapter 1 is structured as a review with a detailed discussion of the processes driving the inorganic carbon cycle in high latitude waters during all phases of the sea ice growth and decay cycle (sections 1.2 – 1.4). In addition, there is a discussion of the Arctic Ocean and sea ice coverage in the context of global change (section 1.5) and, fi nally an outline and discussion of future studies needed to improve our understanding of the seasonal events controlling the dynamics of inorganic carbon in high latitude oceans (section 1.6); Chapter 2 consists of seven published peer-reviewed papers. The fi ndings in this thesis provide strong evidence for the idea of a sea-ice-driven carbon pump in Subarctic and High Arctic sea ice, improve the state of knowledge on the relative contribution of biotic and abiotic processes to carbon dynamics within sea ice, and present a compilation of the current knowledge of the seasonal inorganic carbon dynamics in ice-covered seas during sea ice growth and decay. Furthermore, it provides new knowledge of the infl uence of biological processes and glacier runoff on the pCO2 fl ux in Arctic coastal waters. Photo: Jakob Sievers. 7 PhD thesis by Dorte Haubjerg Søgaard Acknowledgements I owe tremendous thanks to my supervisors Søren Rysgaard (Aarhus University) and Ronnie N. Glud (University of Southern Denmark) for excellent supervision and support, for making this project possible in the fi rst place as well as introducing me to the fi eld work in Malene Bight, SW Greenland and Young Sound, NE Greenland and for many quality hours spend in the Arctic winter. Thanks to John Mortensen and Lorenz Meire for a fruitful cooperation on the subject of the infl uence of glacier runoff and biology on the CO2 uptake in a Subarctic Greenlandic fj ord. Nicolas-Xavier Geilfus (ARC) is thanked for constructive ideas and discussions during our study of ikaite in sea ice. Thanks to the warm welcome from GINR when I arrived in Greenland in 2007. Special thanks to director Klaus Nygaard (GINR) for supporting me fi nancially and logistically. Thanks to my colleagues at GINR for an inspiring and pleasant working environment – especially Martin E. Blicher, Kristine E. Arendt, Thomas Juul Pedersen, John Mortensen, Katrine Raundrup and Rasmus Hedeholm for scientifi c advice and for correction of my manuscripts. This project could not have been completed without help in the fi eld: Thomas Krogh, Michael S. Schrøder, Thomas JuulPedersen, Paul Batty, Kristine E. Arendt, Martin E. Blicher, Morten Kristensen, Lorentz Meire, Kunuk Lennert, Ivali Lennert and Egon Frandsen. Thanks to all my co-authors for comments on manuscripts but especially for broadening my scientifi c horizon by challenging my work. A special thanks to my best friend Charlotte F. Michelsen for helping me whenever needed and for proof reading my thesis. I am grateful for the support of my family: my parents Bent and Hanne Søgaard, my sister Susanne Søgaard, my grandparents Margit and Børge Sørensen and my in-laws Ulla and Peter Schrøder for always encouraging me to explore new horizons and for providing unwavering support. Deep felt thanks to Michael S. Schrøder, my wonderful husband, who has participated right from the beginning – in the fi eld with statistical support, for having patience with me at busy times, for engaging in interesting discussions, for providing a profound sense of stability and for giving me my two daughters Sif and Naja. You followed me to Greenland and made this project possible. I will forever be grateful for this. Ilaquttakka asasakka uannut pingaarnerpaavusi! Nuuk, August 2014 Dorte H. Søgaard for correction of my manuscripts . Dorte H Søgaard 14 PhD thesis by Dorte Haubjerg Søgaard fects the water mass properties and contribute to diff erences in the marine systems as well as in sea ice production and distribution in Greenland coastal areas and fj ords. With respect to the Young Sound Area in NE Greenland (Fig. 2; Rysgaard et al. (II), Barber et al. (III)), the East Greenland Current (i.e., a continuation of the Transpolar Current) has an important infl uence on the water mass properties in this area – especially due to the large amounts of sea ice it carries along with it. Another oceanographic feature in this area is the large seasonal input of freshwater from the Greenland Ice Sheet, terrestrial runoff and melt water from both sea ice and calved glacial ice (Rysgaard and Glud 2007). Furthermore, the area outside Young Sound is a polynya site, where new sea ice is produced and frequently blown away, thereby allowing new ice to form again and again (Pedersen et al. 2010). The marine system in the Godthåbsfj ord area in SW Greenland (Fig. 2; Søgaard et al. (I), Søgaard et al. (IV), Kaartokallio et al. (VI), Rysgaard et al. (VII)) is aff ected by three principal water masses, atmospheric heat exchange and melt/freeze processes (Mortensen et al. 2011, 2013). Two of the three principal water masses are found outside the fj ord – sub-polar mode water and coastal water; whereas the third, freshwater, comes from meltwater runoff from the Greenland Ice Sheet, terrestrial runoff , meltwater from sea ice and calved glacial ice (Mortensen et al. 2011, 2013). The freshwater input in this area from the Greenland Ice Sheet induces a seasonal stratifi - cation of the upper part of the water column and is a source of large amounts of bioavailable nutrient (Arendt 2011, Calbet 2011, Lydersen et al. 2014). 1.2 Phase I: Transition from open water to ice-covered oceans In this section, the mechanisms behind sea ice formation, phase I, are described as well as the microorganisms in newly formed sea ice and their contribution to the CO2 dynamics in this phase (sections 1.2.1 and 1.2.2). In addition, the mechanisms behind brine skim and frost fl ower formation are briefl y described (1.2.3). The processes driving CO2 exchange in the transition period from open water to icecovered seas are discussed and whether phase I acts as net sink or source of CO2 to the atmosphere. Grease ice: thin layer of frazil ice Pancake ice: consolidation of frazil into larger units Frazil crystals: 3 to 4 mm in diameter New ice: recently frozen sea water Nilas: designates a sea ice crust up to 10 cm in thickness Young ice: from 10 to 30 cm First-year ice: melts away during the spring and summer months Multi-year ice 2) Calm conditions1) Agitated conditions G r e a s e i c e : t hin la y er o f f razil ice Pan cak e i ce : c onsolidation of f razil into lar ger un its Frazi l cr y sta l s: 3 to 4 mm in di ame ter N ew i c e: r ecentl y frozen sea water N il a s : d esi g nates a sea ice crust up to 10 cm in thickn ess Firsty ear ice : m elts awa y duri ng t he spring and summer months 2) Ca l m con d itions1) Agitate d con d itions Figure 3. Sea ice development stages 1) agitated conditions with ice growth in wave-fi eld and 2) calm conditions with ice growth through quiescent bottom freezing. 15 PhD thesis by Dorte Haubjerg Søgaard 1.2.1 Sea ice formation – abiotic processes In autumn and winter, when the ocean surface layer is cooled down to temperatures close to –1.86° C (freezing point of seawater with a salinity of 34), ice crystal start to grow on the surface (Weeks 2010) and form a soupy suspension known as frazil ice crystals (i.e., 3 to 4 mm in diameter; Fig. 3). Under calm conditions, the ice crystals freeze together to form a sheet of new ice called Nilas, which designates a sea ice crust up to 10 cm in thickness with randomly-oriented ice crystals (i.e., granular ice texture; Timco and Weeks 2010; Fig. 3 and Fig. 4). It is at this point that frost fl owers are sometimes formed from the brine skim on the ice surface (described in more detail in section 1.2.4). As the sheet ice thickens through congelation at the ice-water interface, the transitional granular/columnar ice layer forms (Eicken and Lange 1989). This layer is a few centimetres thick transition zone that is mainly characterised by elongated grains (Fig. 4). Below the transitional granular/columnar layer, the sea ice consists of columnar ice, characterised by verticallyelongated ice crystals (Fig. 4 and Fig. 5). The sea ice is classifi ed as young ice when the ice sheet becomes thicker than 10 cm and fi rst-year sea ice when the ice sheet becomes thicker than 30 cm (Fig. 3; Weeks 2010). If the fi rst-year ice survives at least one melting season (i.e., one summer), it is called multi-year ice (Fig. 3). Under more agitated conditions with ice growth in wavefi elds, frazil crystals consolidate into grease. The grease ice layer consolidates into ice discs known as pancakes (Fig. 3). As they grow from a few centimetres to a few meters across, they solidify and thicken mechanically by rafting on top of each other. Pancakes freeze together to form cakes and fl oes, which contain a large amount of ice with a granular texture (Fig. 4). With ongoing freezing, the pancakes adhere into a continuous ice sheet by bottom freezing at the icewater interface. Stratigraphy classification Growth conditions Snow deposition Flooding Turbulent mixing Quiscent (growth rate, current shear) Genetic Snow ice Frazil ice Transition zone Congelation ice Ice water interface Textural Granular Mixed columnar/ granular Columnar Skeletal layer Figure 4. Schematic summarizing the main ice texture and growth conditions for fi rst-year sea ice. The fi gure is adapted from Eicken (2003). The horizontal thin-section photographs is of fi rst-year sea ice from Young Sound in NE Greenland for detailed description see Rysgaard et al. (II) (photo courtesy of M. Pucko). 16 PhD thesis by Dorte Haubjerg Søgaard The frazil – congelation sea ice growth process described above is the process that occurs most frequently, but other sea ice types exists, e.g., snow ice and superimposed ice. Snow ice is formed through sea water fl ooding due to negative freeboard and thick snow cover (Fristsen et al. 1998), and it is quite porous (Eicken 2003, Rysgaard et al. (II), Søgaard et al. (IV)). Superimposed ice occurs during spring and summer when the snow melts internally and melt water refreezes either in the snow or at the snow-ice interface, when the temperature gradients within snow and ice are negative (Hass et al. 2001, Nicolaus et al. 2009). As soon as sea water solidifi es, some of the salts and gases present in the seawater are rejected, whereas the rest are trapped within the brine pockets, channels and tubes (Fig. 5; Weeks and Ackley 1982, Petrich and Eicken 2010). A reduction in sea ice temperature decreases the brine volume and, concurrently, increases the brine salinity and brine pCO2 through a decrease in brine CO2 solubility (Cox and Weeks 1983, Papadimitriou et al. 2004). Thus, at this point, the pCO2 in the sea ice brine is higher than that in the air above the sea ice; and, therefore, the sea ice brine has the potential to release CO2 to the atmosphere. However, when the sea ice temperature reaches –5˚ C, the brine volume decreases; a brine volume of 5 % is generally considered the threshold at which the sea ice matrix becomes impermeable, thus preventing air-sea ice gas exchange (Golden et al. 1998, Zhou et al. 2013). This percolation threshold varies with changes in the ice crystal structures – e.g., granular ice shows a higher percolation threshold than columnar ice (Fig. 4; Weeks 2010). In addition, as temperature decreases and solute concentration increases, calcium carbonate precipitates (Marion et al. 2001). On the basis of thermodynamic equilibrium calculation, calcium carbonate precipitation was predicted to occur during natural sea ice formation (Assur 1958), which was later confi rmed fi rst in freezing sea water by Richardson (1976), then in artifi cial sea ice (Tison et al. 2002) and, fi nally, in Antarctic and Arctic sea ice as ikaite (Dieckmann et al. 2008; 2010, Rysgaard et al. 2011; 2012, Fischer et al. 2013, Geilfus et al. 2013a, Nomura et al. 2013b, Rysgaard (II)). At present, it is still not clear whether ikaite is the only calcium carbonate phase formed in sea ice (Dieckmann et al. 2010). The calcium carbonate formation increases the amount of CO2 in the brine beyond that attributed solely to the solubility eff ect. The calcium carbonate crystals are trapped within the interstices between the ice crystals (Rysgaard (II)), whereas the CO2 released through calcium carbonate production within the brine can be lost from the sea ice. Therefore, as sea ice grows, brine drainage leads to an export of gases from the sea ice, leaving sea ice depleted in CO2 compared to ambient seawater (Rysgaard et al. 2007, Crabeck et al. 2014, Søgaard et al. (I)). Brine drainage from sea ice causes the formation of highly saline dense cold 1 cm 65 to 75 cm section 2 mm Figure 5. Thin section of fi rst year sea ice showing ice platelets and the brine pockets along the grain boundaries. For detailed description see Rysgaard et al. (II) (Photo courtesy of M. Pucko). g m -2 FF FYYS POLY FYKB SC70 NI-MY GIS BS SC17 SC7 FIFS FIAN 0 10 20 30 40 Figure 6. Calcium carbonate concentration in diff erent ice types in the Arctic and Antarctic: FYKB= First-year sea ice in Kapisigdlit Bight, SW Greenland (Søgaard et al. (I)), FYYS=First-year sea ice in Yound Sound, NE Greenland and POLY=newly formed polynya ice in Young Sound, NE Greenland (Rysgaard et al. (II)), FF= frost fl owers and BS=brine skim in Young Sound, NE Greenland (Barber et al. (III)), NI-MY=Nilas to multi-year ice in the Antarctic from Dieckmann et al. (2008), FIAN=Fast ice in Antarctic from Fischer et al. (2013), FIFS=Fast ice in Fram Strait from Rysgaard et al. (2012), GIS=Sea ice near the Greenland Ice Sheet (unpublished data D.H. Søgaard), SC70=70 cm thick snow cover and SC17=17 cm thick snow cover in Young Sound, NE Greenland (unpublished data D.H. Søgaard) and SC7=7 cm thick snow cover in Kapisigdlit Bight, SW Greenland (Søgaard et al. (I)). 17 PhD thesis by Dorte Haubjerg Søgaard water that sinks to deeper layers and contributes to the global ocean circulation. Furthermore, observations in the Arctic suggest that TCO2 can be transported below the pycnocline and, subsequently, be incorporated into intermediate and deep-water masses (Rysgaard et al. 2007; Rysgaard et al. 2011). Knowledge on precipitation of calcium carbonate in newly formed sea ice and its eff ect on inorganic carbon dynamics are still not well described. This issue is addressed in two of our papers (Søgaard et al. (I), Rysgaard et al. (II)), where we report measurements of calcium carbonate concentration of 1 g m-2 in a 2 weeks old Subarctic sea ice in Kapisigdlit Bight in SW Greenland (Fig. 2 and Fig. 6) and 10 g m-2 in a less than one-week-old High Arctic sea ice in Young Sound, NE Greenland (Fig. 2 and Fig. 6). The amount of calcium carbonate in the newly formed High Arctic sea ice (Rysgaard et al. (II)) was 2 to 5 times higher than those measured in other sea ice types in both Arctic and Antarctic waters and also 10 times higher than concentrations measured in newly formed Subarctic sea ice in Kapisigdlit Bight in SW Greenland (Fig. 2 and Fig. 6; Søgaard et al. (I)). However, the calcium carbonate concentration in the newly formed High Arctic sea ice was lower than concentrations observed in fi rst-year sea ice and in 70 cm-thick snow cover at the same sampling location in NE Greenland (Fig. 2 and Fig. 6; Rysgaard et al. (II)) as well as in land-fast ice in Fram Strait (Fig. 6.; Rysgaard et al. 2012). These results indicate very dynamic conditions of calcium carbonate formation even on short timescales but also indicate considerable spatial distribution of calcium carbonate (Søgaard et al. (I)). The potential infl uence of melting the entire newly formed ice cover in Kapisigdlit Bight in SW Greenland (Fig. 2; Søgaard et al. (I)) and Young Sound in NE Greenland (Fig. 2; Rysgaard et al. (II)) into a 20 m thick mixed layer (typical for summer conditions in these location) on the CO2 fl ux can be determined using the measured ice carbon chemistry (Table 1) and the initial mixed layer characteristics (Table 2) from the two diff erent regions. Assuming that melt occurs over one month, the resultant air-sea CO2 fl ux to return to premelt conditions would be – 3.4 mmol C m-2 d-1 in Kapisigdlit Bight in SW Greenland (Fig. 2) and – 2.3 mmol C m-2 d-1 in Young Sound in NE Greenland (Fig. 2). The potential air-sea CO2 fl ux vary by a factor of 0.7 with the highest potential air-sea CO2 fl ux estimated in Subarctic sea ice (Søgaard et al. (I), Rysgaard et al. (II)). The reason for this diff erence is unclear but indicates that the age of the sea ice plays an important role for this potential fl ux. In addition, this fi nding suggests that TA and TCO2 feature high variability between ice locations and clearly emphasizes the importance of studies covering the spatial variability in these parameters in order to make reliable carbon budgets. In these calculations, we assume that sea ice formation occurs only once. However, in polynya areas, sea ice with low bulk concentrations of CO2 and high alkalinities is produced (Rysgaard et al. (II)) and frequently blown away from the area, which thereby allows new ice to form again and again. The function of a polynya and the infl uence on CO2 exchange are not well understood, but the production of new sea ice in these areas may contribute to a signifi cant CO2 release to the atmosphere, which is balanced by the dissolution of calcium Area and Site Date Type TCO 2 (μmol kg -1 ) TA (μmol kg -1 ) TA:TCO 2 Bulk salinity Reference Greenland Kapisigdlit Bight 17 February 2010 Newly formed sea ice 281 359 1.28 4.6 Søgaard et al. (I) Kapisigdlit Bight 11 to 15 March 2010 Winter sea ice 233 280 1.20 5.6 Søgaard et al. (I) Kapsigdlit Bight 8 April to 1 May 2010 Spring/summer sea ice 282 356 1.26 2.8 Søgaard et al. (I) Young Sound 17 March 2012 Winter sea ice 406 516 1.27 6.5 Rysgaard et al. (II) Young Sound 20 March 2012 Newly formed polynya sea ice 502 605 1.21 7.8 Rysgaard et al. (II) Greenland/Svalbard Fram Strait 25 to 29 June 2010 Spring/summer sea ice 221 420 1.90 3.9 Rysgaard et al. (2012) Table 1. Sea ice bulk conditions of TCO2, TA and salinity during diff erent fi eld campaigns. Area and Site Date TCO 2 (μmol kg -1 ) TA (μmol kg -1 ) TA:TCO 2 Bulk salinity Reference Greenland Kapisigdlit Bight 17 February 2010 2110 2180 1.03 33 Søgaard et al. (I) Kapisigdlit Bight 11 to 15 March 2010 2095 2230 1.06 32.7 Søgaard et al. (I) Kapsigdlit Bight 8 April to 1 May 2010 2015 2138 1.06 32.7 Søgaard et al. (I) Young Sound 17 March 2012 2101 2276 1.08 31.7 Rysgaard et al. (II) Young Sound 20 March 2012 2070 2205 1.07 31.7 Rysgaard et al. (II) Greenland/Svalbard Fram Strait 25 to 29 June 2010 1987 2203 1.11 32.6 Rysgaard et al. (2012) Table 2. Surface water conditions below sea ice of TCO2, TA and salinity during diff erent fi eld campaigns. 18 PhD thesis by Dorte Haubjerg Søgaard carbonate when the sea ice melts. On the other hand, it is possible that polynya areas act as a downward vertical transport mechanism to remove CO2 rejected from sea ice away from the surface layer and, therefore, ensure a net CO2 fl ux into the ocean over the entire year (Rysgaard et al. 2011). Our fi ndings of high calcium carbonate concentrations in newly formed polynya ice suggest that polynya formation increases the potential for seawater uptake of CO2 (Rysgaard et al. (II)). Another scenario is that the formation of calcium carbonate and the concentration of solutes in newly formed polynya sea ice lead to CO2 de-gassing. If all CO2 produced during the precipitation of calcium carbonate (1) were released to the atmosphere, then the consumption of CO2 during dissolution of the calcium carbonate mineral in the melting phase would balance the effl ux during precipitation (Rysgaard et al. 2011; 2012). Thus, calcium carbonate would not contribute to the polar carbon cycle. However, as soon as an excess of CO2 is rejected together with brine to the underlying water column and transported away from the sea ice formation region, then the mineral may potentially have an important role in the polar carbon cycle as proposed by Rysgaard et al. (2007; 2011 and 2012). However, it is still critical that the surface sea water layer is exposed for a suffi cient time so that the mixed layer has time to equilibrate with the atmosphere, which may not be the case in High Arctic areas with short open water periods (Fransson et al. 2009). In the newly formed sea ice in Young Sound in NE Greenland, we observed high concentrations of calcium carbonate, and at this early stage, the sea ice was still permeable with a brine volume over 5 % (Søgaard et al. (I), Rysgaard et al. (II)). As mentioned earlier, precipitation of calcium carbonate increases the amount of CO2 in the brine beyond that attributed solely to the solubility (1). As a consequence, CO2 may diff use to the atmosphere (Fig. 1; Papadimitriou et al 2004, Nomura et al. 2006; 2010a; 2010b, Loose et al. 2011a, Rysgaard et al. 2011). Since high ice permeability is usually encountered in newly formed sea ice, we would expect some ice-atmosphere fl uxes during sea ice formation. Indeed, we measured a CO2 effl ux of 3.67 ± 1.99 mmol m-2 d-1 above newly formed sea ice in Young Sound in NE Greenland (Fig. 2), using chamber fl ux measurements (Barber et al. (III)), which is consistent with laboratory experiments by Nomura et al. (2006; 2010) and to fi ndings by Geilfus et al. (2013), who estimated a CO2 release from young growing sea ice of 4.2 – 9.9 mmol m-2 d-1. This suggested a release of CO2 from newly formed sea ice. However, recent studies have shown that the largest fl ux of TCO2 and CO2 is driven by brine drainage to the underlying water column and subsequently incorporation into deep-water masses (Rysgaard et al. 2007, Sejr et al. 2011). 1.2.2 Microorganisms in newly formed sea ice Microorganisms in sea ice have been reported for more than 160 years (Horner 1985 and references herein); but, to our best knowledge, the biological processes during the initial stages of sea ice formation have not been well described. The initial stages of sea ice formation generally begin when there are still substantial microbial populations left in the water column (described in section 1.4.3). As a result, particles such as viruses, bacteria and heterotrophic (e.g., fl agellates and ciliates) and autotrophic (e.g., diatoms) protists are often scavenged from the water column as the newly formed frazil ice rise to the surface (Fig. 3; Garrison et al. 1990, Reimnitz et al. 1992, Grossmann and Gleitz 1993, Gradinger and Ikävalko 1998, Kaartokallio et al. 2006). It is also possible that fl oating ice algal aggregates can be refrozen into the sea ice during autumn and, therefore, act as a seeding stock (Assmy et al. 2013 and reference herein). Organisms larger than 10 μm are selectively scavenged from the water column into the sea ice and can accumulate at concentrations higher than that in the underlying sea water (Gradinger and Ikävalko 1998, Riedel et al. 2007, Mikkelsen et al. 2008, Rózanska et al. 2008). Bacteria seem to become entrained in the sea ice along with micro-algae (e.g., Riedel et al. 2007). The bacterial cells may attach to the outer surface of the algae (e.g., epiphytic attachment), or to particles in the water column, which can subsequently transport them into the sea ice. The sea ice bacterial community closely resembles the sea water bacterial community in oligotrophic systems; thus, selection processes during sea ice formation seem to play a minor role (Collins et al. 2010). By contrast, in more productive regions, selection processes due to viral lysis of the heterotrophic bacterial community is possible (Collins et al. 2011). Once incorporated into the sea ice, the microorganisms are challenged with changes in space, light availability, salinity, nutrients, TCO2 and O2 concentrations, temperature and pH (Gradinger and Ikävalko 1998, Søgaard et al. (I), Søgaard et al. (IV – V), Kaartokallio et al. (VI)). These micro-environmental diff erences can lead to dramatic diff erences in the composition and magnitude of the microbial community living there. Sea ice environments are dominated by psychrotolerant and/or psychrophilic organisms (Cameotra and Makkar 1998), and adaptation to low temperatures in all cellular components is of great importance for algae and bacteria living in cold environments. For some sea ice algae and protozoans, one reproductive strategy is the formation of robust stress resistant cysts, which can lie dormant until suitable conditions for growth are present. Sea ice algae that are stressed by extreme ice salinities are likely to exhibit increased halo tolerance and some studies show that sea ice diatoms remain physiologically active at salinities above 100 (Stoecker et al. 1997). A recent study 19 PhD thesis by Dorte Haubjerg Søgaard showed that diatoms are the most successful colonisers of newly formed sea ice (Gradinger and Ikävalko 1998). In addition, we have shown that diatoms are less aff ected by increasing salinities, which might explain the high abundance of diatoms in sea ice (Søgaard et al. (V)). The diff erences in tolerance between sea ice algal species have been ascribed to various abilities for osmotic acclimations, e.g., production of osmolytes (such as dimethylsulphoniopropionate; DMSP), which balances the ionic pressure during changes in salinity (Gleitz and Thomas 1992, Arrigo et al. 2010). In addition to high salinities, sea ice algae must also adapt to the low light conditions in the sea ice, where facultative heterotrophy is an important survival strategy (Horner and Alexander 1972). Sea ice algae are known to be adapted to low ambient light levels and are able to grow beneath several meters of ice and snow only receiving < 1 % of the solar irradiance (Horner & Schrader 1982, Gosselin et al. 1990, Gradinger and Ikävalko 1998, Mock and Gradinger 1999, Lazzara et al. 2007). Cold adaptation by sea ice bacteria include maintaining membrane fl uidity (Gounot & Russell 1999), modifi cation of amino acid composition of the proteome (Deming 2010), i.e., conferring fl exibility to proteins for their enzymatic functions, and storage of intercellular reserves in the form of large polymers or polyhydroxyalkanoates (PHA; Deming 2010, Kaartokallio et al. (VI)). Sea ice bacteria also release antifreeze proteins, cold-active enzymes and exopolymeric substances (EPS; Feller and Gerday 2003, Marx et al. 2009, Deming 2010). In addition to low temperatures, the sea ice bacteria also need to adapt to extremely high salinities and to protect themselves against osmotic shock. These adaptation processes include the production or accumulation of intracellular, compatible solutes (typically sugars and amino acids), changes in membrane fatty acid composition and by the production of salt-tolerant enzymes (Thomas and Dieckmann 2002, Bowman 2008). High concentrations of EPS have been measured in Arctic sea ice throughout the sea ice season, and EPS is released both by bacteria and algae in sea ice. The role of EPS in sea ice is to protect the algal and bacterial cells against the harsh environmental conditions, assist in cell locomotion, serve as a carbon-rich substrate, provide a defence against grazing and create a microhabitat in which bacterial attachment is favoured thereby increasing bacteria-mediated processes (Deming 2010). The productivity of the microorganisms inhabiting sea ice during the fi rst stages of ice formation and development is not well described. However, in Søgaard et al. (I) and Søgaard et al. (IV), we showed that the ice-associated biological community in newly formed sea ice was net heterotrophic with a bacterial carbon demand of 0.50 mg C m-2 d-1 in Kapisigdlit Bight in SW Greenland (Fig. 2) and 0.20 mg C m-2 d-1 in Malene Bight in SW Greenland (Fig. 2). An obvious question is whether the biological processes aff ect the TCO2 concentration within the sea ice in this phase. The relative eff ects of the biological activity and precipitation of calcium carbonate on the air-sea exchange of CO2 can be estimated. At both locations in the newly formed ice (i.e., Kapisigdlit Bight and Malene Bight; Fig. 2) the ice-associated biological communities were net heterotrophic with a CO2 production rate of 4.10 to 2.10 mg m-2 which were very low compared to the integrated calcium carbonate concentration of 1,000 mg m-2 (Søgaard et al. (I)). In our studies the highest bacterial production was observed at the base of the newly formed sea ice (Søgaard et al. (I), Søgaard et al. (IV)). Consequently, this indicates that although the relative contribution of the biological processes to the carbon dynamics is low, it is still possible that the observed CO2 effl ux above newly formed sea ice in some areas (see description in section 1.2.1) is driven, in part, by the respiration of the heterotrophic community at the base of the sea ice. 1.2.3 Frost fl owers and brine skim formation – abiotic processes During the initial hours of sea ice formation, a highly saline layer of brine skim is often observed on the surface of the new and young ice (Drinkwater and Crocker 1988, Perovich and Richter-Menge 1994, Isleifson et al. 2014). The skim layer is typically 1 – 2 mm thick and is highly saline, yielding salinities in the order of 30 to 120 (Douglas et al. 2012, Geilfus et al. 2013a, Barber et al. (III)). It is suggested that this skim layer is formed by brine transport as the brine channels constrict during sea ice growth (Martin et al. 1995). In calm wind conditions (< 5 m s-1), frost fl owers may form on top of the newly formed ice and brine skim as distinct nodules and, then, expand from their nucleation sites radially outwards in all directions (Style and Worster 2009, Barber et al. (III)). In the literature, there is still an ongoing debate whether frost fl owers form due to sublimation or evaporation from the sea ice surface rather than from deposition from the atmosphere (Domine et al. 2005). In the meantime, our measurements show that the initial δ18O values in the frost fl owers are close to 0 ‰, which is similar to the signature of the surface slush layer (Barber et al. (III)), suggesting that newly formed frost fl owers are composed primarily of brine. This is also supported by previous work showing that brine can be wicked into frost fl owers from brine skim (Perovich and Richter-Menge 1994, Martin et al. 1995, Roscoe et al. 2011, Isleifson et al. 2012). Frost fl owers are modifi ed signifi cantly within a few days, since they are extremely eff ective collectors of blowing snow, which suggests a temporal increase in the atmospheric fraction in the frost fl owers (Barber et al. (III)). As a consequence, they are integrated into the snow layer on top of the sea ice (Perovich and Richter-Menge 1994). 20 PhD thesis by Dorte Haubjerg Søgaard Although the mechanisms behind frost fl ower formation are relatively well described, the biological components in frost fl owers are not well-known (Bowman and Deming 2010, Bowman et al. 2013, Eronen-Rasimus et al. 2014). In Barber et al. (III), we showed that the bacterial concentrations generally increase with salinity in frost fl owers. It also confi rms that the bacterial community in frost fl owers is signifi cantly diff erent from that in the underlying sea water. In our study, we found high calcium carbonate concentrations of 2.00 – 2.12 g m-2 (Fig. 6; Barber et al. (III)) in these newly formed saline layers (< 1 h old), which is similar to calcium carbonate concentrations found in frost fl owers and brine skim in an outdoor pool of the Sea-Ice Environmental Research Facility (SERF; Rysgaard et al. 2014), but they are several times higher than concentrations reported from Barrow, Alaska (Geilfus et al. 2013a). If we compare the amount of calcium carbonate in the frost fl owers and brine skim (Fig. 6; Barber et al. (III)) with the total amount of calcium carbonate in the entire sea ice column in Young Sound in NE Greenland (Fig. 2 and Fig. 6; Rysgaard et al. (II)), it accounted for approximately 8 %. This is in general agreement with other studies in which frost fl owers and brine skim in newly formed sea ice fully covered by frost fl owers accounted for 1-5 % of the total calcium carbonate (Domine 2005, Rysgaard et al. 2014). An explanation for the occurrence of calcium carbonate in the frost fl owers and brine skim could be the upward migration of brine with calcium carbonate from the underlying sea ice (Geilfus et al. 2013a) and, subsequently, the incorporation of this brine into frost fl owers and brine skim on the ice surface. The observation of high calcium carbonate concentrations in the newly formed sea ice within the same season and at the same sampling station supports this idea (Fig. 6; Rysgaard et al. (II)). Furthermore, we observed that the newly formed frost fl owers were composed primarily of brine from the underlying sea ice (Barber et al. (III)). However, it is possible that precipitation of calcium carbonate continued after the brine skim and frost fl owers were formed due to low air temperature at the sampling station, allowing the precipitation of salts to occur within these structures (Barber et al. (III)). The upward migration of brine from the ice column to the frost fl owers and brine skim (Barber et al. (III)) facilitates salt transport to the atmosphere and increases the specifi c surface area of the ice, which may potentially promote CO2 exchange between the ice and the atmosphere (Rankin et al. 2000; 2002, Alvarez-Aviles et al. 2008, Bowman and Deming 2010, Geilfus et al. 2013a, Barber et al. (III)). Our results indicate an effl ux of CO2 at the brine wetted newly formed sea ice surface (3.35 ± 0.86 mmol m-2 d-1, n = 8), but there were no striking diff erences in the CO2 fl ux if frost fl owers were inside the chamber footprint (3.02 ± 0.76 mmol m-2 d-1, n = 4) or outside the footprint (3.67 ± 1.99 mmol m-2 d-1, n = 4), suggesting that the formation of frost fl owers only promotes minor CO2 de-gassing (Barber et al. (III)). However, another study showed that frost fl ower formation releases high amounts of CO2, produced during the precipitation of calcium carbonate (Geilfus et al. 2013a). Nevertheless, when the precipitated calcium carbonate from frost fl ower formation is dissolved later during summer thaw, this leads to a similar CO2 uptake from the atmosphere; and, therefore, this will, most likely, not have a net eff ect on the CO2 exchange between the atmosphere and ocean (Fig. 1; phase II). We found high amounts of calcium carbonate (9 – 20 g m-2; Fig. 6) in the snow cover above the sea ice in Young Sound, NE Greenland (Fig. 2), which has also been shown for snow on top of sea ice in other Arctic locations (Søgaard et al. (IV)). If the precipitated calcium carbonate is incorporated into the snow cover together with the CO2 released through calcium carbonate production (1), then it is possible that the CO2 is lost from the snow cover to the atmosphere under conditions with high wind speed (Fig. 1; wind-drift). The overall outcome is that the dissolution of calcium carbonate during the summer thaw, most likely, will have no net eff ect on the CO2 exchange between the atmosphere and ocean. As a result of the way frost fl owers are formed and their later integration into the snow cover, frost fl owers present a unique way for the ocean and sea ice to interact with the atmosphere. The events controlling the dynamics of inorganic carbon in the transition from open water to an ice-covered ocean in autumn and winter have been outlined in the sections above (Fig. 1; phase I). Altogether, my results from this phase I indicate that CO2 is released to the atmosphere while, at the same time, TCO2 is rejected together with brine to the underlying sea water (Fig. 1). Formation of new ice may lead to a de-gassing of CO2 in part, because of the increase in concentration of solutes but also because of the formation of calcium carbonate. However, it may also be a result of respiration by the net heterotrophic community at the ice base in newly formed sea ice. High concentrations of calcium carbonate occur both in frost fl owers and brine skim, accounting for approximately 5 % of the total calcium carbonate in the entire sea ice column. However, the fate of the precipitated calcium carbonate still remains unclear. 1.3 Phase II: Growing winter sea ice In this section, the processes driving CO2 exchange in the growing winter sea ice are discussed (1.3.1) and whether this phase acts as a net sink or source of CO2 to the atmosphere. A short description of the microorganisms in winter sea ice and their contribution to the CO2 dynamics during phase II is also provided (1.3.2). 21 PhD thesis by Dorte Haubjerg Søgaard 1.3.1 Abiotic processes in growing winter ice During winter (Fig. 1; phase II), the largest fl ux of TCO2 and CO2 is driven by brine drainage to the underlying water column, leaving sea ice depleted in CO2 compared to ambient seawater (Fig. 1). This is supported by results in Søgaard et al. (I) indicating that the TCO2 depletion in sea ice in Kapisigdlit Bight in SW Greenland (Fig. 2) was mainly controlled by brine drainage to the underlying water. There are three types of desalination mechanisms: 1) brine expulsion, 2) gravity drainage and 3) brine pocket migration. The fi rst two desalination mechanisms are the only ones of quantitative importance (Eicken 2003). Brine expulsion is the migration of brine driven by the cooling of the sea ice, which results in pressure buildup in the brine pocket. This allows the brine to escape from the brine pocket and migrate toward the warmer end of the ice sheet (Weeks 2010). Gravity drainage includes all processes in which the brine, under the infl uence of gravity, drains out of the sea ice into the underlying water column (Cox and Weeks 1974). These two desalination mechanisms result in the rejection of large amounts of TCO2 and CO2 to the underlying water column along with the expelled brine during sea ice growth (Killawee et al. 1998, Anderson et al. 2004, Rysgaard et al. 2007), which subsequently increases the pCO2 concentration below the sea ice (Fig. 1; Gibson and Trull 1999, Semiletov et al. 2004; 2007, Delille 2006; 2010). TCO2 is assumed to be removed from the surface oceanic mixed layer to deeper water masses via the sinking of the expelled dense brine (Nansen 1906, Rysgaard et al. 2011). However, the fate of the rejected TCO2 in the water column is still poorly understood. During winter calcium carbonate precipitation continues in sea ice (Søgaard et al. (I), Rysgaard et al. (II)). Our measurement from growing Subarctic winter sea ice in Kapisigdlit Bight (Fig. 2) showed high calcium carbonate concentrations (i.e., 9 g m-2; Søgaard et al. (I)), which was 4 times higher than the average seasonal calcium carbonate concentration in sea ice measured in this area (i.e., 2.13 g m-2; Søgaard et al. (I)). In addition, in winter ice in the High Arctic in Young Sound, NE Greenland (Fig. 2), we observed the highest calcium carbonate concentrations ever measured to our knowledge in natural sea ice (i.e., 25 g m-2; Rysgaard et al. (II)), suggesting that winter (Fig. 1; phase II) is extremely important for the annual calcium carbonate precipitation (Fig. 6). Furthermore, it indicates that the calcium carbonate concentration in the brine increases with decreasing temperatures as the highest calcium carbonate concentrations are observed in cold winter High Arctic sea ice (Rysgaard et al. (II)). Calcium carbonate is mainly found as ikaite in the natural sea ice environment, and we confi rmed that the calcium carbonate found in the winter sea ice in the Young Sound area in NE Greenland (Fig. 2) was, indeed, ikaite (Rysgaard et al. (II)). Precipitation of ikaite requires near-freezing temperatures and conditions of high alkalinity (Bischoff et al. 1993, Buchardt et al. 2001, Selleck et al. 2007, Hu et al. 2014). Previously, it was also postulated that elevated phosphate concentrations were critical for ikaite precipitation (Bischoff et al. 1993); however, this has been shown not to be the case (Hu et al. 2014). In the winter sea ice in Young Sound, NE Greenland and in Kapisigdlit Bight, SW Greenland (Fig. 2), we did observe low sea ice temperatures and conditions of high alkalinity with the pH following a C-shaped pH profi le, i.e., high pH (> 9) in the surface and bottom sea ice layers and slightly lower pH conditions (8.5) in the internal sea ice layers (Søgaard et al. (I), Rysgaard et al. (II)). The C-shaped pH profi le in the sea ice is created when the brine inclusions in the upper ice layers are closed due to low ice permeability. This will restrict further CO2 expulsion from the interior ice, which then results in CO2 depletion relative to sea water and, thus, higher pH levels in the upper ice layers (Hare et al. 2013). The interior ice layer continues to receive CO2 from calcium carbonate precipitation and CO2 transport due to brine movement, which explains the low pH values encountered here. The bottom ice layer has open brine channels that continuously export brine to the underlying water resulting in CO2-depletion and high pH in this layer (Hare et al. 2013). The calcium carbonate concentrations measured at two different locations followed the C-shaped pH profi le with high calcium carbonate concentrations in the surface and bottom sea ice layers (Fig. 7; Søgaard et al. (I)). This suggests that the calcium carbonate precipitation in natural sea ice is also controlled by pH, as suggested in a laboratory study by Hu et al. (2014). This contradicts previous studies in which calcium carbonate is primarily found in the uppermost layers of sea ice (e.g., Fischer et al. 2013, Nomura et al. 2013b, Rysgaard et al. 2014). Calcium carbonate concentration (μmol l-1) Ice depth (cm) 1 2 3 400 800 1200 1600 0 20 40 60 80 100 120 Figure 7. Vertical distribution of the calcium carbonate concentration in fi rst-year winter sea ice in Kapisigdlit, SW Greenland (black line; Søgaard et al. (I)) and in fi rst-year winter sea ice in Young Sound, NE Greenland (dashed black line; unpublished data D. H. Søgaard). 22 PhD thesis by Dorte Haubjerg Søgaard The potential infl uence of melting the entire winter ice cover in Kapisigdlit Bight in SW Greenland (Fig. 2; Søgaard et al. (I)) and Young Sound in NE Greenland (Fig. 2; Rysgaard et al. (II)) into a 20 m thick mixed layer (typical for summer conditions in these location) on the CO2 fl ux can be determined using the measured ice carbon chemistry (Table 1) and the initial mixed layer characteristics (Table 2) from the two diff erent regions. Assuming that melt occurs over one month, the resultant air-sea CO2 fl ux to return to pre-melt conditions would be – 4.8 mmol C m-2 d-1 in Kapisigdlit Bight in SW Greenland and – 5.9 mmol C m-2 d-1 in Young Sound in NE Greenland (Fig. 2). The potential air-sea CO2 fl ux vary by a factor of 0.8 with the highest potential air-sea CO2 fl ux estimated in High Arctic sea ice (Søgaard et al. (II), Søgaard et al. (IV)). Our observations of calcium carbonate concentrations in sea ice vary by several orders of magnitude depending on the sea ice type and the locality (Fig. 6; Søgaard et al. (I), Rysgaard et al. (II)), suggesting that TA, TCO2 and calcium carbonate concentrations feature high horizontal variability. This issue is addressed in one of my papers (Søgaard et al. (I)) in which we found high spatial variability on the scale of metres to hundreds of metres for calcium carbonate concentration and other sea ice biogeochemical properties. Another important fi nding in these studies is that the presence of calcium carbonate in sea ice almost doubles the air-sea CO2 fl ux as compared to melting of calcium carbonate-free sea ice, which emphasizes that the precipitation and dissolution of calcium carbonate is critical to the effi ciency of the sea ice-driven carbon pump in these areas (Søgaard et al. (I), Rysgaard et al. (II)). Although the rejection of TCO2 from growing sea ice to the underlying water column during winter is the dominant process in this phase, the sea ice-atmosphere fl uxes should also be taken into account when describing the sea ice carbon budget. As mentioned above, our data showed that calcium carbonate concentration follows a C-shaped profi le (Fig. 6; Søgaard et al. (I)). Since most of the calcium carbonate is found in the upper and lower sea ice layers, it suggests that the CO2 produced during precipitation of calcium carbonate is both in close contact with the atmosphere and the underlying water column. The amount of CO2 released to the atmosphere depends on the ice permeability, while CO2 in the lower ice layers is rejected together with the brine to the underlying water column when there is an excess of CO2 due to high permeability in this ice layer. The low temperatures during winter result in lower brine volumes and, subsequently, a decrease in permeability, which impedes the ice-atmosphere gas exchange (Loose et al. 2011a, Rysgaard et al. 2011) and results in insignifi cant fl uxes above cold sea ice (Heinesch et al. 2010, Miller et al. 2011b, Geilfus et al. 2012b, Sørensen et al. 2014). However, small fl uxes of CO2 have been observed above cold winter sea ice under conditions with high wind speed (Heinesch et al. 2010, Miller et al. 2011a, Papakyriakou and Miller 2011, Else et al. 2011), indicating that CO2 de-gassing might occur occasionally above winter sea ice (Fig. 1; snow-drift). The CO2 de-gassing above winter sea ice is mainly due to the loss of stored CO2 from the snow pack (Rysgaard et al. 2014). This is supported by a recent study showing low pH values in the snow cover above winter sea ice, indicating high CO2 concentrations (Hare et al. 2013). In addition, we also found high amounts of calcium carbonate (0.12 – 20 g m-2; Fig. 6) in the snow cover above the sea ice in Young Sound, NE Greenland and in Kapisigdlit Bight in SW Greenland (Fig. 6; Søgaard et al. (IV)). If the precipitated calcium carbonate is incorporated into the snow cover together with the CO2 released through calcium carbonate production (1), this process may be responsible for the observed snow-driven CO2 degassing under conditions with high wind speeds above winter sea ice (Fig. 1; phase II). The snow cover also has an insulating eff ect (Sturm and Massom 2010, Fischer et al. 2013), maintaining sea ice temperatures high enough to allow a small CO2 effl ux from the ice column into the snow cover (Golden et al. 2007; Nomura et al. 2010a; 2010b, Hare et al. 2013). In addition, new snowfall or a redistribution of snow due to high winds to the same site may warm sea ice cover locally during winter, which may dissolve calcium carbonate (Rysgaard et al. 2014). This indicates dynamic conditions of calcium carbonate precipitation/dissolution, CO2 and pH during winter. 1.3.2 Growth limitation of microorganisms in winter sea ice In winter (Fig. 1; phase II), light availability in the sea ice is very low and the sympagic community remains net heterotrophic, counteracting the atmospheric CO2 drawdown as respiration releases CO2 (Søgaard et al. (I), Søgaard et al. (IV)). Our studies show that, although both biotic and abiotic processes can infl uence air-sea CO2 exchange, the relative eff ects of biotic processes throughout the examined winter sea ice are very low (Søgaard et al. (I)). In addition, our studies revealed that the ice-associated biological community was net heterotrophic in this winter phase with high bacterial carbon demands (i.e., varies between 19.40 mg C m-2 – 40.50 mg C m-2) compared to estimated primary production values (i.e., varies between 12.20 – 20.70 mg C m-2; Søgaard et al. (I), Søgaard et al. (IV)). The bacterial carbon demand in winter sea ice varies between locations with recorded values of 0.80 – 26 mg C m-2 d-1 in Greenland sea ice (Long et al. 2012, Søgaard et al. (I), Søgaard et al. (IV)), 0.02 – 1.5 mg C m-2 d-1 in the Baltic Sea (Kaartokallio 2004) and 5.96 mg C m-2 d-1 in sea ice in Resolute (Smith and Clement 1990). Regardless of location and bacterial carbon demand, minima in bacterial abundance have been observed during winter (Collins et al. 2008, Deming 2010 and references herein). The low bacterial abundance in sea ice during winter might be due to virally-mediated cell death (Collins et al. 2008), 23 PhD thesis by Dorte Haubjerg Søgaard grazing by bacterivorous protists (Rózanska et al. 2008), a reduction in habitable space or the formation of intracellular ice crystals and cell-puncturing by ice crystals (Collins and Deming 2011). Our studies indicate that high ice salinity is a key parameter infl uencing the constitution and activity of the bacterial community in winter sea ice (Kaartokallio al. (VI)). Our fi ndings also suggest that the sea ice is acting as a biofi lm-like system rather than being analogous to open-water systems, which may be a survival strategy for the heterotrophic community in this hostile environment (Kaartokallio al. (VI)). As mentioned in section 1.3.1, the pH in winter sea ice follows a C-shape profi le i.e., high pH (> 9) in the surface and bottom sea ice layers and slightly lower pH conditions (8.5) in the internal sea ice layers. This may have an eff ect on the growth of the microorganisms within the sea ice. Limited knowledge exists on how high pH aff ects growth rates of sea ice algae and bacteria. However, previous studies indicate that high extracellular pH may cause gross alterations in membrane transport processes and metabolic functions involved in internal pH regulation (Raven 1980) or cause alterations of cellular content of amino acids and their composition, which might aff ect cellular growth (e.g., Taraldsvik & Myklestad 2000). Changes of pH infl uence the interspeciation of inorganic carbon (CO2 (aq), HCO3-, CO32-). At pH 8 in sea water (TCO2 approximately 2mM in marine waters), approximately 1 % of TCO2 is present as CO2 while, at pH 9, only 0.1 % of TCO2 is present in this form (Hinga 2002). Potentially, the limitation of the CO2 supply due to elevated pH may restrict photosynthesis and growth of phytoplankton (Hansen 2002). However, some phytoplankton species have active transport systems by which they utilize HCO3in order to avoid TCO2 limitation at elevated pH (Korb et al. 1997, Huertas et al. 2000, Hansen 2002). We have shown that the growth rates of the sea ice diatom species (i.e., Fragilariosis nana and Fragilariopsis sp.) were signifi cantly reduced at pH > 9.0; and, at pH=9.5, they stopped growing irrespective of TCO2, indicating that pH had a direct eff ect on algal growth (Søgaard et al. (V)). In addition, our experiments revealed that a chlorophyte species commonly encountered in sea ice (i.e., Chlamydomonas sp.) had an extreme pH-tolerance since only a small reduction in its growth rate was observed above pH=9.5, but it was sensitive to low TCO2 concentrations (Søgaard et al. (V)). Furthermore, the chlorophytes species out-grew two species of sea ice diatoms in a succession experiment, suggesting that an elevated pH played a potential role in the succession of Arctic sea ice algae in winter sea ice (Søgaard et al. (V)). Sea ice algae are known to be adapted to low light levels and are able to grow at light intensities down to 0.36 – 20 μmol photon m-2 s-1 (Horner and Schrader 1982, Gosselin et al. 1990, Gradinger and Ikävalko 1998, Mock and Gradinger 1999). However, much lower light intensities are observed in the winter sea ice covered with heavy snow (Søgaard et al. (IV)). In our study, light was identifi ed as the major limiting factor for algal productivity – with snow cover depth largely controlling light transmission in Subarctic sea ice in Malene Bight in SW Greenland during winter (Fig. 2; Søgaard et al. (IV)). This suggests that the low algal biomass and productivity in the winter sea ice in Malene Bight in SW Greenland is caused by poor light conditions (Søgaard et al. (IV)). In the sections above, the sequence of events controlling the dynamics of inorganic carbon in growing winter sea ice (Fig. 1; phase II) is outlined. Very high amounts of calcium carbonate were observed in winter the High Arctic sea ice in Young Sound in NE Greenland (Fig. 2), and the concentration followed a C-shaped profi le, suggesting that the CO2 produced in this phase is both in close contact with the atmosphere and the underlying water column. In addition, the sea ice permeability was very low, suggesting that brine drainage were the dominant processes leading to TCO2 depletion in the ice column during the winter months. Therefore, CO2 de-gassing plays only a role in areas with high ice permeability, high wind speeds and/or heavy snow cover where ice temperatures are maintained high enough to allow for CO2 effl ux. Altogether, my results indicate that the role of biology in modulating inorganic carbon dynamics in this phase is minor, and is apparently delayed until spring and summer. 1.4 Phase III: Transition from icecovered ocean to open waters In this section, the abiotic processes driving CO2 exchange in melting sea ice are discussed (1.4.1) and whether this phase acts as a net sink or source of CO2 to the atmosphere. In addition, the microorganisms in melting sea ice and their contribution to the CO2 dynamics in this phase are described (1.4.2) with a focus on the processes determining the magnitude of the primary production in Greenland sea ice and the considerable geographic diff erences in primary production. Finally, a short discussion of the balance of CO2 sinks and sources in the open water period in section 1.4.3 is provided. 1.4.1 Abiotic processes in melting sea ice The warming of sea ice is accompanied by a reduction in ice salinity, approaching zero salinity, because of internal ice melt and brine fl ushing due to the draining of meltwater from surface melt ponds (Untersteiner 1968, Cox and Weeks 1974, Fetterer and Untersteiner 1998). Brine inclusions and channels enlarge upon warming and form new pathways for brine and melt water. These new pathways form longer and bigger channels than the primary pathways in 30 PhD thesis by Dorte Haubjerg Søgaard In addition, melt ponds are a widespread and increasing surface feature of Arctic sea ice during spring and summer (Rösel and Kaleschke 2012), and their impact on inorganic carbon transport through sea ice might, therefore, increase in the future (see description in section 1.4.1). The more transparent sea ice cover and earlier ice melt will also result in an increasing potential for pelagic primary production both below the thinner sea ice cover and in the open waters (Arrigo et al. 2012, Nicolaus et al. 2012, Mundy et al. 2013, Barber et al. (III)). Recent studies also indicate that the current sea ice thinning may enhance ice-algal export due to algal aggregation (Boetius et al. 2013). As a consequence, the biological drawdown of CO2 is expected to increase as sea ice cover is reduced, which will lead to increased net oceanic uptake of CO2 (Bates et al. 2006, Arrigo et al. 2008, Bates and Mathis 2009, MacGilchrist et al. 2014). However, recent studies show that the uptake capacity of the Arctic Ocean for atmospheric CO2 is limited as a result of surface warming and increased stratifi cation (Fransson et al. 2009, Cai et al. 2010, Brent et al. 2013, Else et al. 2013) and that these changes will also stimulate bacterial production and, consequently, limit the sink function of the Arctic Ocean when the sea ice cover is reduced (Xie et al. 2009). Furthermore, observation has shown that the Arctic river runoff has increased, which would lead to an even stronger stratifi cation in the Arctic Ocean (Fransson et al. 2009). This will most likely result in a decrease in the annual biological production in these areas and, consequently, also limit the sink function of the Arctic Ocean in summer (Fransson et al. 2009). The melt from the Greenland Ice Sheet has also increased as a response to global warming, adding more freshwater to the surface water in the coastal areas and fj ords in Greenland (Inall et al. 2014 and references herein, Khan et al. 2014). What is the eff ect of glacial runoff on the air-sea CO2 exchange in coastal areas and fj ords in Greenland? Our studies revealed that the Godthåbsfj ord system in SW Greenland was, indeed, a sink of CO2 (Rysgaard et al. (VII)) and that the CO2 dynamics were controlled by both the biological processes and mixing between glacial meltwater and coastal waters (Rysgaard et al. (VII)). The strength of the sink was particularly strong near the Greenland Ice Sheet, indicating spatial variations in air-sea CO2 uptake. High amounts of CO2 are taken up in the Godthåbsfj ord (annual fl ux of – 83 to – 108 g C m-2 yr-1; Rysgaard et al. (VII)). This estimate is higher than fl ux estimates from other sites in the Greenland Sea (i.e., – 52 g C m-2 yr-1; Nakaoka et al. 2006), in Young Sound in NE Greenland (– 32 g C m-2 yr-1; Sejr et al. 2011; Fig. 2) and data from other Arctic shelf systems (Bates and Mathis 2009), underlining the importance of this Subarctic fj ord system acting as a strong sink for CO2 (Rysgaard et al. (VII)). If this uptake is typical for similar Subarctic fj ord systems in Greenland, then the coastal areas of Greenland constitute a larger sink than anticipated. Furthermore, a recent study from the Godthåbsfj ord indicates that the glacial freshwater runoff is likely to be important for the stimulation eff ect on primary production (total annual production of 84.6 – 139.1 g C m-2 yr-1). This suggests that the timing, duration and magnitude of the glacial freshwater runoff are likely to be important for the CO2 uptake in this Subarctic fj ord system (Rysgaard et al. (VII), Juul-Pedersen et al. submitted). Therefore, an increased ablation of the Greenland Ice Sheet due to future warming could result in an increase in the annual biological production, which could potentially increase the air-sea CO2 fl ux in these areas. 1.6 Conclusions and perspectives So, what have we learned since the sea ice CO2 pump was fi rst suggested by Jones and Coote (1981) 33 years ago and later confi rmed in natural sea ice by, e.g., Rysgaard et al. 2007? The studies of sea ice carbon dynamics over a complete seasonal cycle of sea ice formation and decay as presented in this thesis have, indeed, improved our understanding of the drivers of the sea ice CO2 pump. Collectively, the results in this thesis showed that the formation of sea ice results in transport of TCO2 out of the ice column and, therefore, strengthens the idea of an effective sea-ice-driven carbon pump in both Subarctic and High Arctic sea ice in Greenland (Fig. 1). However, the extent to which TCO2 is transported to the underlying water column and, subsequently, enters the intermediate and deep water masses has yet to be determined. The highest concentrations of calcium carbonate ever reported in natural sea ice was measured in approximately 5-month-old High Arctic land-fast sea ice, followed by high concentrations in newly formed High Arctic polynya sea ice; whereas the lowest concentrations observed during our studies were in Subarctic land-fast sea ice. Variations in sea ice properties such as temperature, salinity, pH, ice texture and freshwater input are likely responsible for some of the diff erences found in calcium carbonate concentrations between sites. It seems that the direction and magnitude of the air-ice fl ux appear to be determined by the stage of ice development, the properties of the sea ice carbonate system (i.e., TA, TCO2, pCO2) as well as sea ice geophysical (i.e., salinity and permeability) and thermodynamic (i.e., temperature) properties. The contribution of primary production to the TCO2 depletion was minor compared to the contribution of calcium carbonate precipitation/dissolution in my study areas; however, in areas of high primary production the contribution to the TCO2 depletion might be signifi cantly higher. As a result, the evaluation of the sea ice sink described in this thesis is not representative of the Arctic as a whole since the uptake of CO2 by biological activity seems to be much lower in Greenland sea ice compared to other regions. 31 PhD thesis by Dorte Haubjerg Søgaard These results revealed large variation in calcium carbonate concentration and other biogeochemical properties at different temporal and spatial scales in sea ice, emphasising the importance of full-season studies covering the hundred-meter spatial scale in order to make reliable regional and eventually global carbon budgets. Many questions still remain unanswered within this fi eld of research, some of which I would like to address in the future. The fi rst step would be to perform full-season studies of the inorganic carbon dynamics in diff erent sea ice types and in diff erent ice locations. It is important to perform continuous measurements of all components involved in the seaice-driven carbon cycle during a complete seasonal cycle, in diff erent sea ice types and from diff erent geographic areas. Furthermore, seasonal measurements of the resulting CO2 fl uxes across the atmosphere-ice-ocean boundary layer are needed. In addition to measuring these parameters with already established techniques, it is also important to develop new methods for measurements including in situ measurements in the microenvironment of brine channels and pockets. This fi rst step require in itself a focused eff ort and still other basic questions will undoubtedly present themselves: 1) Will the future changes in sea ice cover aff ect the capacity of the Arctic Ocean to take up atmospheric CO2? 2) What is the fate of the rejected TCO2 in the water column at diff erent Arctic areas, and is it transported below the pycnocline? 3) What is the fate of the calcium carbonate and CO2 in frost fl owers and brine skim? 4) What is the importance of polynya areas to the air-sea CO2 fl ux? 5) How important is the sea ice carbon pump compared to the solubility pump and biological pump? Here, I outline what are to me the most interesting unanswered questions to advance our knowledge of the events controlling the inorganic carbon dynamics in high latitude oceans. The temporal and spatial variations in the air-sea CO2 fl ux were discussed for the coastal seawater in Godthåbsfj ord, SW Greenland (Fig. 2). This area is determined to be a strong sink of CO2, which was highly regulated both by the biological processes and by mixing between glacial meltwater and coastal waters. The strength of this sink is particularly strong near the Greenland Ice sheet. The next step will be to put these results into a global context to understand how important the role of Greenland coastal waters is in relation to the global carbon budget. Three basic questions present themselves: 1) What is the inter-annual pattern of the CO2 sink and biological processes in Greenland in the Subarctic and High Arctic fj ords? 2) What is the spatial pattern of the CO2 sink and biological processes in Greenland? 3) Will these patterns change as a consequence of ongoing global warming, which is more pronounced at these high latitudes? It is a nontrivial task to answer these questions as the coastal CO2 fl ux and biological processes show high spatial and temporal heterogeneity. However, Greenland presents a unique opportunity to study changes in coastal biological and physical characteristics along a climate gradient from the Subarctic to the High Arctic. Therefore, there are still a lot of important future research questions in terms of understanding the infl uence of the sea-ice-driven CO2 pump and the role of Greenland coastal waters in relation to the global carbon cycle, and it is needed urgently since climate change threatens to take these frozen high latitude environments from us. 1.7 Glossary Aggregates: are attached or free-fl oating mats or aggregates of, e.g., the centric diatom Melosira arctica beneath the sea ice, in melt ponds, frozen into the sea ice or sunk to the bottom of the deep-sea fl oor. Air-sea CO2 exchange: is primarily controlled by the air-sea diff erence in gas concentrations and the exchange coeffi - cient. It takes about one year to equilibrate CO2 in the surface ocean with atmospheric CO2. Therefore, in some areas large air-sea diff erences in CO2 concentrations can be observed. In my PhD thesis negative fl ux indicates sea ice or sea water uptake of CO2. Algae: general term for eukaryotic organisms ranging from unicellular genera, e.g., diatoms to multicellular forms, such as giant kelp, of which most are autotrophic and non-vascular organisms that live almost exclusively in aquatic environments. Autotrophic: ability to convert energy from light (photoautotrophic) or from oxidation of inorganic compounds (chemoautotrophic) to organic material by utilising inorganic carbon (usually CO2). Bacteria: constitute a large domain of prokaryotic microorganisms, most of which are heterotrophic and, typically, a few micrometres in length. Biological pump, the: is driven by the sinking of particulate material -either organic carbon (i.e., dead algal cell) or particulate inorganic carbon (i.e., calcium carbonate from calcifying organisms such as coccolithophores, foraminiferans or pteropods). Brine skim: a highly saline skim of brine that is formed on the surface of newly formed sea ice. 32 PhD thesis by Dorte Haubjerg Søgaard Calcium carbonate: Exists in six phases, namely, amorphous calcium carbonate, calcium carbonate monohydrate, calcium carbonate hexahydrate (ikaite) and three anhydrous phases: vaterite, aragonite and calcite. In both Arctic and Antarctic sea ice, precipitation of calcium carbonate in the form of ikaite has been observed. At present, it is not clear whether ikaite is the only calcium carbonate phase formed in sea ice. However, precipitation of ikaite in sea ice is an important process as it catalyses chemical processes such as boundary layer ozone depletion events (ODEs) and the formation and subsequent draw-down of CO2 via brine drainage. Carbon cycle: is the biogeochemical cycle by which carbon is exchanged among the atmosphere, hydrosphere, lithosphere, cryosphere and pedosphere of the earth. Carbon dioxide (CO2): next to water vapour CO2 is the most abundant greenhouse gas on earth. Most global CO2 is dissolved in water, and CO2 reacts with water and forms bicarbonate (HCO3-) and carbonate ions (CO32-). The concentration of the diff erent ions depends on thermodynamic equilibriums that are related to temperature, pH, salinity and pressure. However, at typical sea water conditions, HCO3is dominant (86.5 %), whereas CO2 (0.5 %) and CO32- (13 %) are only present in small concentrations. Cells: are the smallest unit of life that can replicate independently. Cell membrane: is a biological membrane that separates the interior of all cells from the outside environment (called cell wall). It is made of a lipid bilayer interspersed with proteins, which makes it selectively permeable to ions and organic molecules. Chlorophyll: a group of green pigments in photosynthetic organisms that traps the energy of sunlight for photosynthesis and exists in several forms of which the most abundant is chlorophyll a. Chlorophyll a: a type of chlorophyll that is common and predominant in all oxygen-evolving photosynthetic organisms. It is abbreviated Chl a. Chlorophyta: is a division of green algae. Ciliates: are a group of protozoans characterized by the presence of hair-like organelles called cilia. Deep-water masses: water located below the intermediate waters. It generally has low temperatures (2° C) and high salinity (34.9) and, therefore, a high density. Diatoms: are a major group of algae and are among the most common types of phytoplankton of which most are unicellular. They can exist as colonies and with a cell wall of amorphous silica. Dimethylsulphoniopropionate (DMSP): is a widely used osmolyte used by microalgae to acclimate to changes in salinity. DMSP is a precursor of dimethylsulphide (DMS), which is a climate-active gas. Dissolved organic carbon (DOC): are organic molecules of varied origin and composition within aquatic systems. DOC in marine systems is generally a result of decomposition processes from dead organic matter such as plants. DOC is a food supplement supporting the growth of microorganisms and plays an important role in the global carbon cycle through the microbial loop. Dissolved organic nitrogen (DON): is a mixture of compounds ranging from simple amino acids to complex humic substances. Exponential growth: Growth of microorganisms whereby the cell number doubles within a fi xed time period. Extracellular polymeric substances (EPS): are high-molecular weight compounds secreted by microorganisms into their environment. EPS can function as cryoprotection, as external reserves of hydrolysable organic compounds, to depress the freezing point and to provide a physical buff er against encroaching ice crystals. First-year sea ice: is sea ice of not more than one winter´s growth. It develops from young ice and have a thickness > 30 cm. Flagellate: is an organism with one or more organelles called fl agella. Flagella-bearing species are common in all algal classes except Cyanophyceas, Rhodophyceae, Phaeophyceae and Bacillariophyceae. Frost fl owers: clusters of saline ice crystals that have a dendritic and branched structure. Frost fl owers form at the interface between a warm ice surface and a cold atmosphere at conditions with low surface wind conditions. Global carbon budget: is the sum of all exchanges (infl ows and outfl ows) of carbon compounds between the earth´s carbon reservoirs of the carbon cycle. Halotolerant: the ability to withstand large changes in salinity. Heterotrophic: ability to obtain carbon for organic synthesis by metabolising organic material. Ikaite (CaCO3 · 6H2O): is an unstable hexahydrate polymorph of CaCO3, which begins to precipitate at -2.2˚ C and dissolves at temperatures above 4˚ C. Precipitation of ikaite has been confi rmed in sea ice from both hemispheres. In situ: means on site. Intracellular: occurs or functions within a cell. 33 PhD thesis by Dorte Haubjerg Søgaard Lipid bilayer: is a fl at and thin polar membrane that consists of two layers of lipid molecules. This sheet forms a continuous barrier around all cells. Melt ponds: result from an accumulation of meltwater on sea ice – mainly, due to the melting of snow, but the underlying sea ice cover also contributes to the melt pond formation. Melt ponds absorb solar radiation rather than refl ecting it as ice does and, thereby, have a signifi cant infl uence on the earth’s radiation balance. Membrane fl uidity: is the viscosity of the lipid bilayer of a cell membrane that can aff ect the rotation and diff usion of proteins and, therefore, also aff ects the function of these molecules. The lipid bilayer has proteins embedded in them, and lipid packing can infl uence the fl uidity of the cell membrane. Multi-year ice: ice of more than one year´s growth. Osmolytes: are dissolved ion or organic solutes within a cell that prevent osmotic shock by maintaining osmotic pressure within the cell to avoid cell lysis (too much internal pressure) or shrinkage (too little internal pressure). Osmotic shock: is a sudden change in the solute concentration around a cell that causes a change in the movement of water across its cell membrane. In environments with high concentrations of salts, water is drawn out of the cells. This is avoided by the incorporation of osmolytes. pCO2: the partial pressure of CO2. Pelagic: describes organisms that swim or drift in a sea. Pelagic organisms: are plankton and nekton. pH: pH of seawater plays an important role in the ocean’s carbon cycle. pH measurement in sea water is complicated by its chemical properties, and several distinct pH scales exist, i.e., total scale, sea water scale and free scale. Photosynthesis: the process by which green plants and some unicellular organisms convert incoming sunlight into organic material from CO2 and water. Photosynthetically active radiation (PAR): is the spectral range (wave band) of solar radiation from 400 to 700 nanometres in which photosynthetic organisms are able to use for photosynthesis. PAR is normally quantifi ed asμmol photonsm-2 s-1. Polyhydroxyalkanoates (PHA): produced in nature by bacteria to store carbon and energy. Polynya: is an area of open water surrounded by sea ice. In this area, new sea ice is produced and frequently blown away, thereby allowing new ice to form again and again Precipitation: formation of a solid from solution by chemical or physical processes. Proteome: is the entire complement of proteins that are or can be expressed by a cell, tissue or organism. Psychrophilic organisms: are organisms that have optimal growth rates at temperatures usually below 15° C and cannot grow above 20° C. Psychrotolerant organisms: are organisms that have optical growth rates at temperatures above 20° C but are able to tolerate and, for bacteria, grow under cold conditions. Pycnocline: is a boundary in oceanography separating two water layers of diff erent densities. The formation of a pycnocline may result from changes in salinity or temperature. Because the pycnocline layer is extremely stable, it acts as a barrier for surface processes; and, therefore the changes in salinity and temperature are very small below the pycnocline but are seasonal in surface water. Respiration: bacteria perform two major functions in the transformation of organic material: 1) they produce new bacterial biomass (bacterial production), and 2) they respire organic carbon to inorganic carbon (bacterial respiration). Salinity: the total grams of salts in 1 kg of sea water. Solubility pump, the: is driven by two processes in the ocean: 1) CO2 solubility strongly related to sea water temperature where CO2 is more soluble in cold waters, and 2) thermohaline circulation, driven by the formation of cold, dense water masses at high latitudes Stratifi cation: occurs when water masses with diff erent properties – e.g., of salinity (halocline), density (pycnocline) and temperature (thermocline) – form layers that act as barriers to water mixing and, therefore, create barriers to nutrient-mixing between layers. Sympagic: describes organisms that live where water exists mostly as a solid, i.e., sea ice. TA: total alkalinity is related to the charge balance in sea water and in natural sea water at pH > 8 in μmol kg-1 of seawater. TCO2: in sea water, CO2 exists in three inorganic forms: CO2 (aq), HCO3and CO3-2. The sum of the concentration of these forms is called total dissolved inorganic carbon, abbreviated TCO2, in μmol kg-1 of seawater. 34 PhD thesis by Dorte Haubjerg Søgaard 1.8 Literature cited Alou-Font E, Mundy J-C, Roy S, Gosselin M, Agusti S (2013) Snow cover aff ects ice algal pigment composition in the coastal Arctic Ocean during spring. Mar Ecol Prog Ser 474:89 – 104 Alvarez-Aviles L, Simpson WR, Douglas TA, Sturm M, Perovich D, Domine F (2008) Frost fl ower chemical composition during growth and its implications for aerosol production and bromine activation. J Geophys Res-Atmos 113:D21304, doi:10.1029/2008JD010277 Anderson LG, Falck E, Jones EP, Jutterström S, Swift JH (2004) Enhanced uptake of atmospheric CO2 during freezing of seawater: a fi eld study in Storfj ord, Svalbard. J Geophys Res 109:C06004, doi:10.1029/2003JC002120 Arendt KE, Nielsen TG, Rysgaard S, Tönnesson K (2010) Diff erences in plankton community structure along the Godthåbsfj ord, from the Greenland Ice Sheet to off shore waters. Mar Ecol Prog Ser 401:49 – 162 Arendt K, Dutz J, Jónasdóttir SH, Jung-Madsen S, Mortensen J, Møller EF, Nielsen TG (2011) Eff ects of suspended sediments on copepods feeding in a glacial infl uenced sub-Arctic fj ord. Jour Plankt Res 33:1526 – 11537 Arrigo KR, Dijken GL, Pabi S (2008) Impact of a shrinking Arctic ice cover on marine primary production. Geophys Res Lett 35:L19603, doi:10.1029/2008GL035028 Arrigo KR, Mock T, Lizotte MP (2010) Primary production and sea ice. In: Thomas DN, Dieckmann GS (eds) Sea ice, 2nd Edition. WileyBlackwell Publishing Oxford, pp 283 – 1326 Arrigo KR, Perovich DK, Pickart RS, Brown ZW, van Dijken GL, Lowry KE, Mills MM, Palmer MA, Balch WM, Bahr F, Bates NR, BenitezNelson C, Bowler B, Brownlee E, Ehn JK, Frey KE, Garley R, Laney SR, Lubelczyk L, Mathis J, Matsuoka A, Mitchell BG, Moore GWK, OrtegaRetuerta E, Pal S, Polashenski CM, Reynolds RA, Schieber B, Sosik HM, Stephens M, Swift JH (2012) Massive Phytoplankton Blooms Under Arctic Sea Ice. Science 336:1408 – 11408 Assmy P, Ehn JK, Fernández-Mendez M, Hop H, Katlein C, Sundfj ord A, Bluhm K, Daase M, Engel A, Fransson A, Granskog MA, Hudson SR, Kristiansen S, Nicolaus M, Peeken I, Renner AHH, Spreen G, Tatarek A, Wiktor J (2013) Floating ice-algal aggregates below melting Arcric sea ice. PLOS 8:1 – 113 Assur A (1958) Composition of sea ice and its tensile strength, in Arctic Sea ice Conference Proceesings, pp. 106-138, NAS-NRC Publ. 598, Nat. Academy of Sci., Washington D.C Assur A (1960) Composition of sea ice and its tensile strength, Res. Rep. 44:49 pp. U.S. Army Snow Ice and Permafrost Res. Establ., Wilmette, III Bates NR (2006) Air-sea CO2 fl uxes and the continental shelf pump of carbon in the Chukchi Sea adjacent to the Arctic Ocean. J Geophys Res 111:C10013, doi:10.1029/2005JC003083 Bates NR, Mathis JT (2009) The Arctic Ocean marine carbon cycle: evaluation of air-sea CO2 exchanges, ocean acidifi cation impacts and potential feedbacks. Biogeosciences 6:2433 – 12459 Bischoff JL, Fitzpatrick JA, Rosenbauer RJ (1993) The solubility and stabilization of ikaite (CaCO3 · H2O) from 0° to 25°C: Environmental and paleaclimatic implications for thinolite tufa. J Geol 101:21 – 133 Boetius A, Albrecht S, Bakker K, Bienhold C, Felden J, FernandezMendez M, Hendricks A, Katlein C, Lalande C, Krumpen T, Nicolaus M, Peeken I, Rabe B, Rogacheva A, Rybakova E, Somavilla R, Wenzhöfer F (2013) Export of algal biomass from the melting Arctic sea ice. Science 339:1430 – 11432 Bowman JP (2008) Genomic analysis of psyscrophillic prokaryotes. In: Psychrophiles: from Biodiversity to Biotechnology (Eds. R.Margesin, F. Schinner, J-C. Marx and C. Gerday) Springer-Verlag, Berlin, pp. 265 – 1284 Bowman JS, Deming JW (2010) Elevated bacterial abundance and exopolymers in saline frost fl owers and implications for atmospheric chemistry and microbial dispersal. Geophys Res Let 37:L13501, doi:10.1029/2010GL043020 Bowman JS, Larosa C, Vogel TM, Deming JW (2013) Selective occurrence of Rhizobiales in frost fl owers on the surface of young sea ice near Barrow, Alaska and distribution in the polar marine rare biosphere. Environ Microbiol Rep 5: 575 – 1582 Brent G, Else T ,Galley RJ ,Lansard B ,Barber DG ,Brown K ,Miller LA ,Mucci A,Papakyriakou TN,Tremblay J-E,Rysgaard S (2013) Further observations of a decreasing atmospheric CO2 uptake capacity in the Canada Basin (Arctic Ocean) due to sea ice loss. Geophys Res Lett 40:1132 – 11137, doi:10.1002/grl.50268 Buchardt B, Israelson C, Seaman P, Stockmann G (2001) Ikaite tufa towers in Ikka Fjord, southwest Greenland: Their formation by mixing of seawater and alkaline spring water. J Sediment Res 71:176 – 1189 Buck KR, Nielsen TG, Hansen BW, Gastrup-Hansen D, Thomsen HA (1998) Infi ltration phytoand protozooplankton assemblages in the annual sea ice of Disko Island, West Greenland, spring 1996. Polar Biol 20:377 – 1381 Cai W-J, Chen L, Chen B, Gao Z, Lee SH, Chen J, Pierrot D, Sullivan K, Wang Y, Hu X, Huang W-J, Zhang Y, Xu S, Murata A, Grebmeier JM, Jones EP, Zhang H (2010) Decrease in the CO2 uptake capacity in an ice-free Arctic Ocean Basin. Science 329:556 – 1559 Calbet A, Riisgaard K, Saiz E, Stedmon C, Nielsen TG (2011) Phytoplankton growth and microzooplankton grazing along a sub-Arctic fj ord (Godthåbsfj ord, West Greenland) Mar Ecol Prog Ser 442:11 – 122, doi:10.3354/meps09343 Cameotra SS, Makkar RS (1998) Synthesis of biosurfactants in extreme conditions. Appl Microbiol Biotechnol 50: 520 – 1529 Cavalieri DJ, Parkinson CL (2012) Arctic sea ice variability and trends, 1979 – 2010. TC 6: 881-889, doi: 10.5194/tc-6-881 – 12012 Collins RE, Carpenter SD, Deming JW (2008) Spatial heterogeneity and temporal dynamics of particles and pEPS in Arctic winter sea ice. J Mar Syst 74:902 – 1917 Collins RE, Rocap G, Deming JW (2010) Persistence of bacterial and archaeal communities in sea ice through an Arctic winter. Environ Microbiol 12:1828 – 11841 35 PhD thesis by Dorte Haubjerg Søgaard Collins RE, Deming JW (2011) Abundant dissolved genetic material in Arctic sea ice, Part II: Virus dynamics during autumn freezeup. Polar Biol 34:1831- – 11841 Comiso JC (2003) Large-scale characteristics and variability of the global sea ice cover. In: Thomas DN, Dieckmann GS (eds), 1st Edition. Sea ice: an introduction to its physics, chemistry, biology and geology. Blackwell Science, Oxford, pp 112 – 1142 Comiso JC, Parkinson CL, Gersten R, Stock L (2008) Accelerated decline in the Arctic sea ice cover. Geophys Res Lett 35:L01703, doi:10.1029/2007GL031972 Comiso JC (2012) Large Decadal Decline of the Arctic Multiyear Ice Cover. J Climate 25:1176 – 11193 Cota GF, Horne EPW (1989) Physical control of arctic ice algal production. Mar Ecol Prog Ser 52:111 – 1121 Cota GF, Anning JL, Harris LR, Harrison WG, Smith REH (1990) The impact of ice algae on inorganic nutrients in seawater and sea ice in Barrow Strait, NWT, Canada during spring. Can J Fish Aquat Sci 47:1402 – 11415 Cox GFN, Weeks WF (1974) Salinity variations in sea ice. J Glaciol 13:109 – 1120 Cox GFN, Weeks WF (1983) Equations for determining the gas and brine volumes in sea-ice samples. J Glaciol 29:306 – 1316 Crabeck O, Delille B, Thomas DN, Geilfus NX, Rysgaard S, Tison JL (2014) CO2 and CH4 in sea ice from a subarctic fj ord. Biogeosciences Discuss 11:4047 – 14088, doi:10.5194/bgd-11-4047-2014 Delille B (2006) Inorganic carbon dynamics and air-ice-sea CO2 fl uxes in the open and coastal waters of the Southern Ocean, PhD thesis, 296 pp. Univ. de Liège, Liège, France. Delille B, Jourdain B, Borges AV, Tison J-L, Delille D (2007) Biogas CO2, O2, dimethylsulfi de dynamics in spring Antarctic fast ice. Limnol Oceanogr 52:1367 – 11379 Deming J (2010) Sea ice bacteria and viruses. In: Thomas DN, Dieckmann GS (eds) Sea ice, 2nd Edition. Wiley-Blackwell Publishing Oxford, pp 247 – 1282 Dieckmann GS, Nehrke G, Papadimitriou S, Göttlicher J, Steininger R, Kennedy H, Wolf-Gladrow D, Thomas DN (2008) Calcium carbonate as ikaite crystals in Antarctic sea ice. Geophys Res Lett 35:L08501, doi:10.1029/2008GL033540 Dieckmann GS, Nehrke G, Uhlig C, Göttlicher J, Gerland S, Granskog MA, Thomas DN (2010) Brief communication: ikaite CaCO3· 6H2O discovered in Arctic sea ice. TC 4:227 – 1230, doi:10.5194/ tc-4-227-2010 Domine F, Taillandier AS, Simpson WR, Severin K (2005) Specifi c surface area, density and microstructure of frost fl owers. Geophys Res Lett 32: L13502, doi: 10.1029/2005GL023245 Douglas TA, Domine F, Barret M, Anastasio C, Beine HJ, Bottenheim J, Grannas A, Houdier S, Netcheva S, Rowland G, Staebler R, Steff en A (2012) Frost fl owers growing in the Arctic ocean-atmospheresea ice-snow interface: 1. Chemical composition. J Geophys Res 117:D00R09, doi: 10.1029/2011JD016460 Drinkwater MR, Crocker GB (1988) Modelling changes in the dielectric and scattering properties of young snow-covered sea ice at GHz frequencies. J Glaciol 34:274 – 1282 Eicken H, Lange MA (1989) Development and properties of sea ice in the coastal regime of the Southeastern Weddel Sea. J Geophys Res-Ocean 94:8193 – 18206, doi:10.1029/JC094iC06p08193 Eicken H (2003) From the microscopic to the macroscopic to the regional scale, growth, microstructure and properties of sea ice. In: Thomas DN, Dieckmann GS (eds), 1st Edition. Sea ice: an introduction to its physics, chemistry, biology and geology. Wiley-Blackwell Publishing Oxford, pp 22 – 181 Eicken H, Grefell TC, PErovich DK, Richter-Menge JA, Frey K (2004) Hydraulic controls of summer Arctic pack ice albedo. J Geophys Res-Oceans 109:C08007, doi:10.1029/2003JC001989 Eicken H, Dmitrenko I, Tyshko K, Darovskikh A, Dierking W, Blahak U, Groves J, Kassens H (2005) Zonation of the Laptev Sea landfast ice cover and its importance in a frozen estuary. Global Planet Change 48: 55 – 183, doi:10.1016/j.gloplacha.2004.12.005 Else BGT, Papkyriakou T, Asplin M, Barber D, Galley R, Miller L, Mucci A (2013a) Annual cycle of air-sea CO2 exchange in an Arctic polynya region. Glob Biogeochem Cycles 27, doi:10.1002/gbc.20016 Else BGT, Galley RJ, Lansard B, Barber DG, Brown K, Miller LA, Mucci A, Papkyriakou TN, Temblay JE, Rysgaad S (2013b) Further observations of a decreasing atmospheric CO2 uptake capacity in the Canada Basin (Arctic Ocean) due to sea ice loss. Geophys Res Lett 40:1132 – 11137, doi:10.1002/grl.50268 Else BGT, Papkyriakou TN, Galley RJ, Drennan WM, Miller LA, Mucci A, Thomas H (2011) Wintertime CO2 fl uxes in an Arctic polynya using eddy covariance: evidence of enhanced air-sea gas transfer during ice formation. J Geophys Res 116:C00G03, doi: 10.1029/2010JC006760 Eronen-Rasimus W, Kaartokallio H, Lyra C, Autio C, Autio R, Kuosa H, Dieckmann GS, Thomas DN (2014) Bacterial community dynamics and activity in relation to dissolved organic matter availability during sea ice formation in a mesocosm experiment. Microbiol 3:139 – 1156 Feller G, Gerday C (2003) Psychrophillic enzymes: hot topics in cold adaptation. Nat Rev Microbiol 1: 200 – 1208 Fetterer F, Untersteiner N (1998) Observations of melt ponds on Arctic sea ice. J Geophys Res-Oceans 103:24821 – 124835 Fischer M (2013) Sea ice and the air-sea exchange of CO2. PhD thesis, University Bremen FischerM, ThomasDN, KrellA, NehrkeG, GöttlicherJ, NormanL, Meiners KM, Riaux-GobinC, DieckmannGS (2013) Quantifi cation of ikaite in Antarctic sea ice. Ant Sci 25:421 – 1432 Fransson A, Chierici M, Nojiri Y (2006) Increased net CO2 outgassing in the upwelling region of the southern Bering Sea in a period of variable marine climate between 1995 and 2001. J Geophys Res 111: C08008, 10.1029/2004JC002759 Fransson A, Chierici M, Nojiri Y (2009) New insights into the spatial variability of the surface water carbon dioxide in varying sea ice conditions in the Arctic Ocean. Continent shelf Res 29:1317 – 11328 36 PhD thesis by Dorte Haubjerg Søgaard Fransson A, Chierici M, Yager PL, Smidt Jr. Wo (2011) Antarctic sea ice carbon dioxide system and controls. J Geophys Res 116:C12035. doi:10.1029/2010JC006844 Fritsen CH, Ackley SF, Kremer JN, Sullivan CW (1998) Flood-freeze and microalgal dynamics in Antarctic pack ice, in Antarctic sea ice: Biological processes, interactions and variability. Antarct Res Ser 73:1 – 122 Garrison DL, Buck KR (1986) Organisms losses during melting: A serious bias in sea ice community studies. Polar Biol 6:237 – 239 Garrison DL, Close AR, Reimnitz E (1990) Microorganisms concentrated by frazil ice: evidence from laboratory experiments and fi eld measurements. In Sea Ice Properties and Processes (eds) SF Ackley and WF Weeks, U.S. Army Corps of Engineers, Cold of Engineers, Cold Regions Research and Engineering Laboratory, Monograph 90-1, Pp. 92 – 196 Geilfus N-X, Garnat G, Papakyriakou T, Tison JL, Else B, Thomas H, Shadwick E, Delille B (2012b) Dynamics of pCO2 and related air-ice CO2 fl uxes in the Arctic coastal zone (Amundsen Gulf, Beaufort Sea). J Geophys Res 117:C00G10, doi:10.1029/2011JC007118 Geilfus NX, Carnat G, Dieckmann GS, Halden N, Nehrke G, Papakyriakou T, Tison JL, Delille B (2013a) First estimates of the contribution of CaCO3 precipitation to the release of CO2 to the atmosphere during young sea ice growth. J Geophys Res 188:244 – 1255, doi:10.1029/2012JC007980 Geilfus NX, Galley RJ, Crabeck O, Papkyriakou T, Landy J, Tison JL, Rysgaard S (2014) Inorganic carbon dynamics of melt pondcovered fi rst year sea ice in the Canadian Arctic. Biogeosciences Discuss 11:7485 – 17519, doi: 10.5194/bgd-11-7485-2014 Gibson J, Trull T (1999) Annual cycle of fCO2 under sea-ice and in open water in Prydz Bay, East Antarctica. Mar Chem 66:187 – 1200 Gleitz M, Thomas DN (1992) Physiological responses of a small Antarctic diatom (Chaetocerros sp.) to simulated environmental constraints associated with sea ice formation. Mar Ecol Prog Ser 88:271 – 1278 Gleitz G, Rutgers VD, Thomas DN, Dieckmann GS, Millero FJ (1995) Comparison of summer and winter inorganic carbon, oxygen and nutrient concentrations in Antarctic sea ice brine. Mar Chem 51:81 – 191 Glud RN, Rysgaard S, Kühl M, Hansen JW (2007) The sea ice in Young Sound: Implications for C cycling. In: Carbon cycling in Arctic marine Ecosystems: Case study Young Sound. Chapter 4 p: 62 – 185. Rysgaard S & Glud RN (Eds), Carbon cycling in Arctic marine Ecosystem: Case study Young Sound. Meddelser om Grønland, Bioscience Vol 58. Copenhagen the Commission for Scientifi c Research in Greenland 2007 Glud RN, Rysgaard S, Turner G, McGinnis DF, Leakey RJG (2014) Biological and physical-induced oxygen dynamics in melting sea ice of the Fram Strait. Limnol Oceanogr 59:1097 – 1111 Golden K, Ackley SF, Lytle V (1998) The Percolation Phase Transition in Sea Ice. Science 282:2238 – 12241, doi:10.1126/ science.282.5397.2238 Golden KM, Eicken H, Heaton L, Miner J, Pringle D, Zhu J (2007) Thermal evolution of permeability and microstructure in sea ice. Geophys Res Lett 34:L16501, doi:10.1029/2007GL030447 Gosselin M, Legendre L, Therriault J-C, Demers S, Rochet M (1986) Physical control of the horizontal patchiness of sea-ice microalgae. Mar Ecol Prog Ser 29:289 – 1298 Gosselin M, Legendre L, Therriault J-C, Demers S (1990) Light and nutrient limitation of sea ice microalgae (Hudson Bay, Canadian Arctic). J Phycol 26:220 – 1232 Gounot, A.M., Russell, N.J., 1999. Physiology of cold-adapted microorganisms. In: Margesin, R., Schinner, F. (Eds.), Cold-adapted Organisms. Ecology, Physiology, Enzymology and Molecular Biology. Springer, Berlin, pp. 33 – 155 Gowing MM, Garrison DL, Gibson AH, Krupp JM, Jeff ries MO, Fritsen CH (2004) Bacterial and viral abundance in Ross Sea summer pack ice communities. Mar Ecol Prog Ser 279:3 – 112 Gradinger R, Ikävalko J (1998) Organism incorporation into newly forming Arctic sea ice in the Greenland Sea. J Plankton Res 20:871 – 1886 Gradinger R, Friedrich C, Spindler M (1999) Abundance, biomass and composition of the sea ice biota of the Greenland Sea packice. Deep-Sea Res Part Li Top Stud Oceanogr 46:1457 – 11472 Gradinger R (2009) Sea ice algae: Major contributors to primary production and algal biomass in the Chukchi and Beaufort Seas during May/June 2002. Deep-Sea Res PT II 17: 1201 – 11212, doi:10.1016/j.dsr2.2008.10.016 Grossmann S, Gleitz M (1993) Microbial responses to experimental sea-ice formation: implications for the establishment of Antarctic sea-ice communities. J Exp Mar Biol Ecol 173:273 – 1289 Haas C, Hendricks S, Eicken H, Herber A (2010) Synoptic airborne thickness surveys reveal state of Arctic sea ice cover. Geophys Res Let 37:L09501, doi:10.1029/2010GL042652 Hansen PJ (2002) The eff ect of high pH on the growth and survival of marine phytoplankton: implications for species succession. Aquat Microb Ecol 28:279 – 1288 Hare AA, Wang F, Barber D, Geilfus N-X, Galley R, Rysgaard S (2013) pH evolution in sea ice grown at an outdoor experimental facility. Mar Chem 154:46 – 164, doi:10.1016/j.marchem.2013.04.007 Heinesch B, Tison JL, Carnat G, Eicken H, Geilfus N-X, Goosens T, Papakyriakou T, Yernaux M, Delille B (2010) Micrometeorological survey of air-sea ice CO2 fl uxes in arctic coastal waters. In EGU Genral Assembly, 2 – 17 May, 2010, Vienna, Austria Hinga KR (2002) Eff ect of pH on coastal marine phytoplankton. Mar Ecol Prog Ser 238:281 – 1300 Horner R, Alexander V (1972) Algal populations in arctic sea ice: an investigation of heterotrophy. Limnol Oceanogr 17:454 – 1458 Horner R, Schrader GC (1982) Relative contributions of ice algae, phytoplankton, and benthic microalgae to primary production in nearshore regions of the Beaufort Sea. Arctic 35:485 – 1503 Horner RA (1985) Ecology of sea ice microalgae. In: Horner RA (Ed.), Sea Ice Biota. CRC Press, Boca Raton, FL, pp. 83 – 1103 Hu Y-B, Wolf-Gladrow DA, Dieckmann GS, Völker C, Nehrke G (2014) A laboratory study of ikaite (CaCO3 · 6H2O) precipitation as a function of pH, salinity, temperature and phosphate concentration. Mar Chem 162:10 – 118 37 PhD thesis by Dorte Haubjerg Søgaard Huertas IE, Colman B, Espie GS; Lubian LM (2000) Active transport of CO2 by the three species of marine microalgae. J Phycol 36:314 – 1320 Inall ME, Murray T, Cottier FR, Scharrer K, Boyd TJ, Heyword KJ, Bevan SL (2014) Oceanic heat delivery via Kangerdlugssuaq Fjord to the south-east Greenland ice sheet. J Geophys Res-Ocean 119:1 – 115, doi:10.1002/2013JC009295 Isleifson D, Galley RJ, Barber DG, Landy JC, Komarov AS, Shafai L (2013) A study on the C-band polarimetric scattering and physical characteristics of frost fl owers on experimental sea ice. IEEE Trans Geosci Remote Sensing 52:1787 – 11798 Jakobsson, M Grantz A, Kristoff ersen Y, Macnab R (2004) Bathymetry and physiography of the Arctic Ocean and its constituent seas. In Stein R & MacDonald RW (eds) The organic carbon cycle in the Arctic Ocean. Springer Verlag Berlin Heidelberg New York, pp. 1 – 16 Jones EP, Coote AR (1981) Oceanic CO2 produced by the precipitation of CaCO3 from brines in sea ice. J Geophys Res 86: 11041 – 111043, doi:10.1029/JC086iC11p11041 Juul-Pedersen, Arendt KE, Mortensen J, Blicher M, Søgaard DH, Rysgaard S (submitted) Seasonal and interannual phytoplankton production in a sub-arctic fj ord (Godthåbsfj ord) connected to the Greeland Ice Sheet. Mar Ecol Prog Ser Kaartokallio H (2004) Food web components, and physical and chemical properties of Baltic Sea ice. Mar Ecol Prog Ser 273:49 – 163 Kaartokallio H, Kuosa H, Thomas DN, Granskog MA, Kivi K (2006) Biomass, composition and activity of organism assemblages along a salinity gradient in sea ice subjected to river discharge in the Baltic Sea. Polar Biol 30:183 – 1197 Khan SA, Kjær KH, Bevis M, Bamber JL, Wahr J, Kjeldsen KK, Bjørk AA, Korsgaard NJ, Stearns LA, Broeke MR, Liu L, Larsen NK, Muresan LS (2014) Sustained mass loss of the northeast Greenland ice sheet triggered by regional warming. Nature Climate Change 4:292 – 1299, doi:10.1038/NCLIMATE2161 Killawee JA, Fairchild IJ, Tison JL, Janssens L, Lorrain R (1998) Segregation of solutes and gases in experimental freezing of dilute solutions: Implications for natural glacial systems. Geochim Cosmochim Acta 62:3637 – 13655 Korb RE, Saville PJ, Johnston AM, Raven J (1997) Sources of inorganic carbon for photosyntesis by three species of marine diatoms. J Phycol 33:433 – 1440 Krell A, Funck D, Plettner I John U, Dieckmann G (2007) Regulation of proline metabolism under salt stress in the psychrophillic diatom Fragilariopsis cylindrus (Bacillariophyceas). J Phycol 43: 753 – 1762 Kuosa H, Borrman B, Kivi K, Brandini F (1992) Eff ects of Antarctic sea ice biota on seeding as studied in aquarium experiments. Polar Biol 12:333 – 1339 Kühl M, Glud RN, Borum J, Roberts R, Rygaard S (2001) Photosynthetic performance of surface-associated algae below sea ice as measured with a pulse-amplitude-modulated (PAM) fl uorometer and O2 microsensors. Mar Ecol Prog Ser 223:1 – 114 Lannuzel D, Schoermann V, Jong JD, Tison J-L, Chou L (2007) Distribution and biogeochemical behaviour of iron in the East Antarctic sea ice. Mar Chem 106:18 – 132 Lavoie D, Denman K, Michel C (2005) Modeling ice algal growth and decline in a seasonally ice-covered region of the Arctic (Resolute Passage, Canadian Archipelago). J Geophys Res-Ocean 110: C11009, doi:10.1029/2005JC002922 Lazzara L, Nardello I, Ermanni C, Mangoni O, Saggiomo V (2007) Light environment and seasonal dynamics of microalgae in the annual sea ice at Terra Nova Bay, Ross Sea, Antarctica. Antarct Sci 19: 83 – 192 Lee SH, Stockwell DA, Joo H-M, Son YB, Kang C-K, Whitledge TE (2012) Phytoplankton production from melting ponds on Arctic sea ice. J Geophys Res 117:C04030, doi:10.1029/2011JC007717 Legendre L, Ackley SF, Dieckmann GS, Gulliksen B, Horner R, Hoshiai T, Melnikov IA, Reeburgh WS, Spindler M, Sullivan CW (1992) Ecology of sea ice biota. Polar Biol 12:429 – 1444 Leu E, Wiktor J, Søreide JE, Berge J, Falk-Petersen S (2010) Increased irradiance reduced food quality of sea ice algae. Mar Ecol Prog Ser 411:49 – 160 Leu E, Søreide JE, Hessen DO, Falk-Pedersen S, Berge J (2011) Consequences of chaning sea ice cover for primary production and secondary producers in the European Arctic Shelf seas: Timing, quantity and quality. Prog Oceanography 90:18 – 132 Leu E, Mundy CJ, Assmy P, Campbell K, Gabrielsen TM, Gosselin M, Juul-Pedersen T, Gradinger R (submitted) Arctic spring awakening – steering principles behind the phenology of vernal ice algae blooms Long MH, Koopmans D, Berg P, Rysgaard S, Glud RN, Søgaard DH (2012) Oxygen exchange and ice melt measured at the ice-water interface by eddy correlation. BG 9:1957 – 11967, doi:10.5194/ bg-9-1-2012 Loose B, Miller LA, Elliott S, Papakyriakou T (2011a) Sea Ice Biogeochemistry and Material Transport Across the Frozen Interface. Ocean 24:203 – 1218 Loose B, Schlosser P, Perovich DK, Ringelberg D, Ho D, Takahashi T, Richter-Menge JA, Reynolds C, Mcgillis W, Tison JL (2011b) Gas diff usion through columnar laboratory sea ice: implications for mixed-layer ventilation of CO2 in the seasonal ice zone. Tellus 63B:23 – 139, doi:10.1111/j.1600-0889.2010.00506.x Lüthje M, Feltham Taylor PD, Worster MG (2006) Modeling the summertime evolution of sea ice melt ponds. J Geophys Res 111:C02001, doi:10.1029/2004JC002818 Lydersen C, Assmy P, Falk-Petersen S, Kohler J, Kovacs KM, Reigstad M, Steen H, Strøm H, Sundfj ord A, Varpe Ø, Walczowski W, Weslawski JM, Zajaczkowski M (2014) The importance of tidewater glaciers for marine mammals and seabirds in Svalbard, Norway. J Mar Syst 129:452 – 1471 MacGilchrist GA, Garabato CAN, Tsubouchi T, Bacon S, TorresValdés S, Azetsu-Scott K (2014) The Arctic Ocean carbon sink. Deep-Sea Res I 86:39 – 155 Marion GM (2001) Carbonate mineral solubility at low temperatures in the Na-K-Mg-Ca-H-Cl-SO4-OH-HCO3-CO3-CO2-H2O system. Geochim Cosmochimica Act 65:1883 – 11896 Martin S, Drucker R, Fort M (1995) A laboratory study of frost fl ower growth on the surface of young sea ice. J Geophys Res 100:7027 – 17036, doi:10.1029/94JC03243 38 PhD thesis by Dorte Haubjerg Søgaard Marx JG, Carpenter SD, Deming JW (2009) Production of cryoprotectant extracellular polysaccharide substances (EPS) by the marine psychrophilic bacteriumColwellia psychrerythraeastrain 34H under extreme conditions. Can J Microbiol 55: 63 – 172, doi: 10.1139/W08-130 Miller L, Garnat G, Else B, Sutherland N, Papakyriakou T (2011a) Carbonate system evolution at the Arctic Ocean surface during autumn freeze-up. J Geophys Res 116:C00G04, doi:10.1029/2011JC007143 Miller LA, Papakyriakou TN, Collinsn RE, Deming JW, Ehn JK, Macdonald RW, Mucci A, Owens O, Raudsepp M, Sutherland N (2011b) Carbon dynamics in sea ice: A winter fl ux time series. J Geophys Res 116:C02028, doi:10.1029/2009JC006058 Millero FJ (1995) Thermodynamic of the carbon dioxide system in the ocean. Geochim Cosmochim Acta 59:661 – 1677 Mikkelsen DM, Rysgaard S, Glud RN (2008) Microalgal composition and primary production in Arctic sea ice: a seasonal study from Kobbefj ord (Kangerluarsunnguaq), West Greenland. Mar Ecol Prog Ser 368:65 – 174 Mikkelsen DM, Witkowski A (2010) Melting sea ice for taxonomic analysis: a comparison of four melting procedures. Polar Res, doi:10.1111/j.1751-8369.2010.00162.x Mock T, Gradinger R (1999) Determination of Arctic ice algal production with a new in situ incubation technique. Mar Ecol Prog Ser 177:15 – 126 Mortensen J, Lennert K, Bendtsen J, Rysgaard S (2011) Heat sources for glacial melt in a sub-Arctic fj ord (Godthåbsfj ord) in contact with the Greenland Ice Sheet. J Geophys Res 116, C01013, doi:10.1029/2010JC006528 Mortensen J, Bendtsen J, Motyka RJ, Lennert K, Truff er M, Fahnestock M, Rysgaard S (2013) On the seasonal freshwater stratifi cation in the proximity of fast-fl owing tidewater outlet glaciers in a sub-Arctic sill fj ord. J Geophys Res-Oceans 118:1382 – 11395, doi:10.1002/jgrc.20134 Mundy CJ, Gosselin M, Ehn J, Gratton Y, Rossnagel A, Barber DG, Martin J, Tremblay J-E, Palmer M, Arrigo KR, Darnis G, Fortier L, Else B, Papakyriakou T (2009) Contribution of under-ice primary production to an ice-edge upwelling phytoplankton bloom in the Canadian Beaufort Sea. Geophys Res Lett 36:L17601, doi:10.1029/2009GL038837 Mundy CJ, Gosselin M, Gratton Y, Brown K, Galindo V, Campbell K, Levasseur M, Barber D, Papakyriakou T, Bélanger S (2013) Role of environmental factors on phytoplankton bloom initiation under landfast sea ice in Resolute Passage, Canada. Mar Ecol Prog Ser 497:39 – 149 Munro DR, Dunbar RB, Mucciarone DA, Arrigo KR, Long MC (2010) Stable isotope composition of dissolved inorganic carbon and particulate organic carbon in sea ice from the Ross Sea, Antarctica. J Geophys Res-Ocean 115:C09005, doi:10.1029/2009JC005661 Nansen F (1906) Northern Waters: Captain Roald Amundsen’s oceanographic observations in the Arctic Seas in 1901. In commission by Jacob Dybvad, Christiania. Nakaoka S-I, Aoki S, Nakazawa T, Hashida G, Morimoto S, Yamanouchi T, Yoshikawa-Inoue H (2006) Temporal and spatial variations of oceanic pCO2 and air-sea CO2 fl ux in the Greenland Sea and the Barents Sea. Tellus 58B:148 – 1161 Nedashkovsky A, Khvedynich S, Petrovsky T (2009). Alkalinity of sea ice in the High-Latitudinal Arctic according to the surveys performed at North Pole Drifting Station 34 and characterization of the role of the Arctic ice in the CO2 exchange. Mar Chem 49:61 – 169 Nicolaus M, Haas C, Willmes S (2009) Evolution of fi rst-year and second-year snow properties on sea ice in the Weddell Sea during spring-summer transition. J Geophys Res-Atmos 114:1 – 117, doi:10.1029/2008JD011227 Nicolaus M, Katlein C, Maslanik J, Hendricks S (2012) Changes in Arctic sea ice result in increasing light transmittance and absorption. Geophys Res Let 39:L24501, doi:10.1029/2012GL053738 Nomura DH, Yoshikawa-Inoue, Toyota T (2006) The eff ect of sea-ice growth on a air-sea CO2 fl ux in a tank experiment. Tellus B Chem Phys Meteol 58:418 – 1426 Nomura D, Eicken H, Gradinger R, Shirasawa K (2010a) Rapid physically driven inversion of the air-sea ice CO2 fl ux in the seasonal land fast ice off Barrow, Alaska after onset of surface melt. Continent Shelf Res 30:1998 – 12004, doi:10.1016/j.csr.2010.09.014 Nomura D, Yoshikawa-Inoue H, Toyota T, Shirasawa K (2010b) Eff ects of snow, snowmelting and refreezing processes on air-seaice CO2 fl ux. J Glaciol 56:262 – 1270 Nomura D, Granskog MA, Assemy P, Simizu D, Hashida G (2013a) Arctic and Antarctic sea ice acts as a sink for atmospheric CO2 during periods of snowmelt and surface fl ooding. J Geophys ResOcean 118:6511 – 16524, doi:10.1002/2013JC009048 Nomura D, Assmy P, Nehrke G, Granskog MA, Fischer M, Dieckmann GS, Fransson A, Hu Yubin, Schnetger B (2013b) Characterization of ikaite (CaCO3· 6H2O) crystals in fi rst-year Arctic sea ice north of Svalbard. Annals Glaciology 62:125 – 1131, doi:10.3189/ 2013AoG62A034 Parkinson CL (2000) Variability of Arctic sea ice: The view from space and 18-year record. Arctic 53:341 – 1358 Papadimitriou S, Kennedy H, Kattner G, Dieckmann GS, Thomas DN (2004) Experimental evidence for carbonate precipitation and CO2 degassing during sea ice formation. Geochim Cosmochim Acta 68:1749 – 11761 Papadimitriou S, Thomas DN, Kennedy H, Haas C, Kuosa H, Krell A, Dieckmann GS (2007) Biogeochemical composition of natural sea ice brines from the Weddell Sea during early austral summer. Limnol Oceanograp 52:1809 – 11823 Papadimitriou S, Thomas D, Kennedy H, Kuosa H, Dieckmann GS (2009) Inorganic carbon removal and isotopic enrichment in Antarctic sea ice gap layers during early austral summer. Mar Ecol Prog Ser 386:15 – 127 Papadimitriou S, Kennedy H, Norman L, Kennedy DP, Dieckmann GS, Thomas DN (2012) The eff ect of biological activity, CaCO3 mineral dynamics and CO2 degassing in the inorganic carbon cycle in sea ice in late winter-early spring in the Weddell Sea, Antarctica. J Geophys Res 117:C08011, doi:10.1029/2012JC008058 39 PhD thesis by Dorte Haubjerg Søgaard Papakyriakou T, Miller L (2011) Springtime CO2 exchange over seasonal sea ice in the Canadian Arctic Archipelago. Annals Glaciol 52:215 – 1224 Pedersen JTP, Kaufmann LH, Kroon A, Jakobsen BH (2010) The northeast Greenland Sirius Water Polynya dynamics and variability inferred from satellite imagery. Geografi sk Tidskrift 110:131 – 1142 Perovich DK, Richter-Menge JA (1994) Surface characteristics of lead ice. J Geophys Res Lett 99:16341 – 116350, doi:10.1029/94JC01194 Perovich DK (1996) The optical properties of sea ice, CRREL Monograph, 96 – 11, 25 pp Perovich DK, Jones KF, Light B, Eicken H, Markus T, Stroeve J, Lindsay R (2011) Solar partitioning in a changing Arctic sea-ice cover. Ann Glaciol 52:192 – 1196, doi:10.3189/172756411795931543 Petrich C, Eicken H (2010) Growth, Structure and Properties of sea ice. In: Thomas DN, Dieckmann GS (eds) sea ice, 2nd Edition. WileyBlackwell Publishing Oxford, pp 23 – 178 Polashenski C, Perovich D, Courville Z (2012) The mechanisms of sea ice melt pond formation and evolution. J Geophys Res-Oceans 117:C01001, doi:10.1029/2011JC007231 Ralph PJ, Ryan KG, Martin A, Fenton G (2007) Melting out of sea ice causes greater photosynthetic stress than freezing in. J Phycol 43: 948 – 1956 Ramaswamy V, Chanin M-L, Angell J, Barnett J, Gaff en D, Gelman M, Keckhut P, Koshelkov Y, Labitzke K, Lin J-JR, O`Neill A, Nash J, Randel W, Rood R, Shine K, Shiotani M, Swinbank R (2001) Stratospheric temperature trends: Observation and model simulations. Review Geophys 39:71 – 1122, doi:10.1029/199RG000065 Rankin AM, Auld V, Wolff EW (2000) Frost fl owers as a source of fractionated sea salt aerosol in the polar regions. Geophys Res Let 27:3469 – 13472 Rankin AM, Wolff EW, Martin S (2002) Frost fl owers: Implications for tropospheric chemistry and ice core interpretation. J Geophys Res-Atmos 107:D23, doi:10.1029/2002JD002492 Raven J (1980) Limits on growth rate. Nature 361:209 – 1210 Reimnitz E, Marincovich L Jr, McCormick M, Briggs WM (1992) Suspension freezing of bottom sediment and biota in the Northwest Passage and implications for Arctic Ocean sedimentation. Can J Earth Sci 29:693 – 1703 Richardson C (1976) Phase relationships in sea ice as a function of temperature. J Glaciol 17:507 – 519 Riedel A, Michel C, Gosselin M, LeBlanc B (2007) Enrichment of nutrients, exopolymeric substances and microorganisms in newly formed sea ice on the Mackenzie Shelf. Mar Ecol Prog Ser 342:55 – 67 Roscoe HK, Brooks B, Jackson AV, Smith MH, Walker SJ, Obbard RW, Wolff EW (2011) Frostfl owers in the laboratory: Growth, characteristics, aerosol and the underlying sea ice. J Geophys Res 116: D12301, doi:10.1029/20010JD 015144 Rösel A, Kaleschke L (2012) Exceptional melt pond occurrence in the years 2007 and 2011 on the Arctic sea ice revealed from MODIS satellite data. J Geophys Res-Oceans 117: C05018, doi:10.1029/2011JC007869 Ròzanska M, Poulin M, Gosselin M (2008) Protist entrapment in newly formed sea ice in the coastal Arctic Ocean. J Mar Sys 74:887 – 1901 Ròzanska M, Gosselin M, Poulin M, Wiktor MP, Michel C (2009) Infl uence of environemental factors on the development of bottom ice protist communities during the winter-spring transition. Mar Ecol Prog Ser 386: 43 – 159 Ryan KG, Ralph PJ, McMinn A (2004) Acclimation of Antarctic bottom-ice algal communities to lowered salinities during melting. Polar Biol 27:679 – 186 Rysgaard S, Kühl M, Glud RN, Hansen JW (2001) Biomass, production and horizontal patchiness of sea ice algae in a high-Arctic fj ord (Young Sound, NE Greenland). Mar Ecol Prog Ser 223:15 – 26 Rysgaard S, Glud R (Eds.) (2007) Carbon cyclin in Arctic marine ecosystem: Case study Young Sound. Meddr Grønland, Bioscience 58. Copenhagen, the Commision of Scientifi c Research in Greenland, 214 pp Rysgaard S, Glud RN, Sejr MK, Bendtsen J, Christensen PB (2007) Inorganic carbon transport during sea-ice growth and decay: A carbon pump in polar seas. J Geophys Res 112:C03016, doi:10.1029/2006JC003572 Rysgaard S, Arendt K, Frederiksen M. et al. (2008) Nuuk Basic: The Marine Basic Program 2005-2006. In Klitgaard AB, Rasch M and Caning K (eds.), Nuuk Ecological Research Operations, 1st Annual Report 2008. Danish Polar Center, Copenhagen Rysgaard S, Bendtsen J, Petersen LT, Ramløv J, Glud RN (2009) Increased CO2 uptake due to sea ice growth and decay in the Nordic Seas. J Geophys Res 114:C09011, doi:10.1029/2008JC005088 Rysgaard S, Bendtsen J, Delille B, Dieckmann GS, Glud RN, Kennedy H, Mortensen J, Papadimitriou S, Thomas DN, Tison JL (2011) Sea ice contribution to the air-sea CO2 exchange in the Arctic and Southern Oceans. Tellus B 63:823 – 830, doi:10.1111/ J.1600-0889-2011.005471.x Rysgaard S, Glud RN, Lennert K, Cooper M, Halden N, Leaky R, Hawthorne FC, Barber D (2012) Ikaite crystals in melting sea ice – implications for pCO2 and pH levels in Arctic surface waters. TC 6:1015 – 11035, doi:10.51947tcd-6-015-2012 Rysgaard S, Wang F, Galley RJ, Grimm R, Notz D, Lemes M, Geilfus NX, Chaulk A, Hare AA, Crabeck O, Else BGT, Campbell K, Sørensen LL, Sievers J, Papakyriakou T (2014) Temporal dynamics of ikaite in experimental sea ice. TC 8:1469 – 11478, doi:10.5194/tc-8-1469-2014 Sabine CL, Feely RA, Gruber N, Key RM, Lee K, Bullister JL, Wanninkhof R, Wong CS, Wallace DWR, Tilbrook B, Millero FJ, Peng T-H, Kozyr A, Ono T, Rios AF (2004) The oceanic sink for anthropogenic CO2. Science 305: 367 – 1371, doi:10.1126/science.1097403 Sakshaug E (2004) Primary and secondary production in the Arctic seas. In: Stein R, Macdonald RW (eds) The organic carbon cycle in the Arctic Ocean, 2nd Edition. Springer-Verlag Berlin Heidelberg. Pp: 57 – 181 Sejr MK, Krause-Jensen D, Rysgaard S, Sørensen LL, Christensen PB, Glud RN (2011) Air-sea fl ux of CO2 in arctic coastal waters infl uenced by glacial melt water and sea ice. Tellus B 63:815 – 1822, doi:10.1111/j.1600-0889.2011.00540.x 46 PhD thesis by Dorte Haubjerg Søgaard in March. The water column in the Kapisigdlit Bight was fully mixed and the salinity under the sea ice varied between 33 and 33.5. The water depth under the sea ice was 30–40 meter. More details on the oceanographic conditions in the Godtha ˚bsfjord are provided by Mortensen et al. (2011). Two sampling designs were used: 1. Spatial variability was investigated over a perpendicular x–ytransect covering 0.07 km 2 that was investigated on March 11 and April 8, 2010 (See Fig. 1for location of these). The parameters sampled in this part of the work were CaCO 3 , dissolved organic carbon and nitrogen (DOC, DON), inorganic nutrients (PO 43- , Si(OH) 4 ,NO 2 - ,NO 3 - , and NH 4 ? ), temperature, salinity, and snow and sea ice thickness. 2. The temporal development of CaCO 3 , TCO 2 , TA, inorganic nutrients, DOC, DON, primary production, bacteria production, bulk salinity, snow and sea ice thickness, and temperature was also investigated at a single location in the study area (Fig. 1) every 2–3 weeks from February to May 2010 (i.e. 17 February, 10, 11, 12 and 15 March, 8 April and 1 May). Spatial variability In both of the transect surveys (i.e., March 11 and April 8, 2010), 25 sea ice cores were taken along a 266-m-long perpendicular x–ytransect. The cores were collected at distances of 0, 0.2, 0.4, 0.6, 0.8, 1, 3, 9, 20, 42, 64, 128, and 266 m in both x and y directions. At each sampling point, a sea ice core was collected using a MARK II coring system (Kovacs Enterprises Ltd) and an overlying snow sample was collected using a small shovel. The air temperature was measured 2 m above the snow, and vertical profiles of temperatures within the ice were measured using a calibrated thermometer (Testo Ò ). Sea ice temperature measurements were complemented by a custom-built string of thermistors that were frozen into the sea ice from 11 March until 8 April. The thermistor string data were recorded every 6 h at a spatial resolution of 4 cm. The retrieved ice cores were cut into 12 cm sections with a stainless steel saw and placed in plastic containers and transported back to the laboratory in dark thermoinsulated boxes. Sea ice and snow samples were slowly melted in the dark at 3 ±1°C, which took between 2 and 3 days. We measured all the parameters in all sea ice sections. However, we only report data from the top and bottom section as they are the most important. To determine the amount of CaCO 3 within the ice and snow, between 300 and 500 ml of melted ice or snow was divided into three subsamples and filtered (3 ±1°C) through pre-combusted (450 °C, 6 h) Whatman Ò GF/F filters. The exact volume of the filtered meltwater was measured. The filters were transferred to tubes (12 ml Exetainer Ò ) containing 20 ll HgCl 2 (5 % w/v, saturated solution) to avoid microbial activity during storage and 12 ml deionized water with a known TCO 2 concentration. The tubes were then spiked with 300 ll of 8.5 % Fig. 1 Map showing the sea ice area in Kapisigdlit in SW Greenland and the temporal development and spatial variability sampling stations Polar Biol (2013) 36:1761–1777 1763 123 47 PhD thesis by Dorte Haubjerg Søgaard phosphoric acid to convert CaCO 3 on the filters to CO 2 , and after coulometric analysis (Johnson et al. 1993)ofCO 2 the CaCO 3 concentration was calculated. At each sampling occasion, samples from different ice depth horizons were inspected under the microscope to check for the presence of microorganisms with calcium carbonate external structures such as coccolithophores and foraminifers. These inspections showed that no microorganisms with calcium carbonate external structures were present in any of the samples. The remaining meltwater was filtered through 25-mm Whatman Ò GD/X disposable syringe filters (pore size 0.45 lm). A subsample of the filtrate was transferred to precombusted glass vials; 100 ll of 85 % phosphoric acid was added; and the vials were frozen for later analyses of DOC. The remaining filtrate was transferred to pre-combusted (450 °C, 6 h) and alkali-washed glass vials and frozen for later analysis of DON, PO 43- ,NO 3 - ,NO 2 - , Si(OH) 4 , and NH 4 ? . The DOC, DON, and nutrient samples were frozen at -19 °C until analysis. DOC was measured by high-temperature catalytic oxidation, using a MQ 1001 TOC Analyzer (Qian and Mopper 1996). The concentrations of NO 3 ,NO 2 - , PO 43- , and Si(OH) 4 were determined by standard colorimetric methods (Grasshoff et al. 1983) as adapted for flow injection analysis (FIA) on a LACHAT Instruments QuickChem 8000 autoanalyzer (Hales et al. 2004). The PO 43samples from the first sampling was contaminated, and therefore we did not include them. The concentration of NH 4 ? was determined with the fluorometric method of Holmes et al. (1999) using a HITACHI F2000 fluorescence spectrophotometer. The concentration of DON was determined by subtraction of the concentration of DIN (DIN =[NO 3 - ]?[NO 2 - ]?[NH 4 ? ]) from that of the total dissolved nitrogen determined by FIA on the LACHAT autoanalyzer, using online peroxodisulphate oxidation coupled with UV radiation at pH 9.0 and 100 °C (Kroon 1993). The conductivity of the melted sea ice sections was measured (Thermo Orion 3-star with an Orion 013610MD conductivity cell), and values were converted to bulk salinity (Grasshoff et al. 1983). The brine volumes of the original sea ice samples were calculated from the measured bulk salinity and temperature and a fixed density of 0.917 g cm -3 according to Leppa ¨ranta and Manninen (1988) for temperatures[-2°C and according to Cox and Weeks (1983) for temperatures \-2°C. Spatial autocorrelation (Legendre and Legendre 1998) was used to analyze the correlation of the horizontal and vertical distribution of CaCO 3 concentration, DOC, DON, inorganic nutrients, temperature, and salinity as well as the snow and sea ice thickness. Autocorrelation was estimated by Moran’s I coefficients (Moran 1950; Legendre and Legendre 1998). This coefficient was calculated for each of the following intervals along the transect (classes of distance): 0–0.25, 0.25–0.50, 0.50–1.5, 1.5–2.5, 2.5–5.0, 5.0–10, 10–50, 100–150, 150–200, 200–250, and [250 m. The autocorrelation coefficients estimated by the Moran’s I coefficient were tested for significance according to the method described in Legendre and Legendre (1998). A 2-tailed test of significance was used. Positive (?) indicates positive autocorrelation (correlation) and negative (-) indicates negative autocorrelation. A zero (0) value indicates a random spatial pattern. We applied a significance level of P\0.05. Pearson’s correlation was used to find the correlation between the parameters. Furthermore, a full factorial generalized linear model (GLM) including time, depth, and position as explanatory variables, which was reduced based on Akaike’s Information Criterion (AIC), was applied. The same model was applied for several dependent variables: position (horizontal), depth (vertical), and time on CaCO 3 concentration, bulk salinity, DOC, and DON. Temporal development On each of the 7 sampling occasions for the temporal study, triplicate ice cores and environmental parameters were collected from a defined area (5 m 2 ), and samples were processed as described above. Primary production was measured (Søgaard et al. 2010) on 4 occasions (i.e.17 February, 11 March, 8 April, and 1 May). In short, primary production was determined on melted sea ice samples (melted within 48 h in the dark at 3±1°C). The potential primary production in the sea ice at different sea ice depths (i.e. 12 cm sections) was measured in the laboratory cold room at 3 irradiances (72, 50,14 lmol photons m -2 s -1 ) and corrected with one dark incubation, using the H 14 CO 3 - incubation technique (incubation time was 5 h). The potential primary production measured in the laboratory at different sea ice depths was plotted against the three laboratory light intensities 42, 21, and 9 lmol photon m -2 s -1 and fitted to the following function described by Platt et al. (1980) PPðlgCl 1h1Þ¼Pm1exp aEPAR Pm  ð1Þ where PP is the primary production, P m (lgCl -1 h -1 )is the maximum photosynthetic rate at light saturation, a (lgCm 2 slmol photons -1 l -1 h -1 ) is the initial slope of the light curve, and E PAR (lmol photons m -2 s -1 ) is the laboratory irradiance. The photoadaptation index, E k (lmol photons m -2 s -1 ), was calculated as P m /a. In situ down-welling irradiance was measured at ground level (Kipp & Zonen pyrometer, CM21, spectrum range of 305–2,800 nm) once every 5 min, and hourly averages were provided by Asiaq (Greenland Survey). Hourly downwelling irradiance was converted into hourly 1764 Polar Biol (2013) 36:1761–1777 123 48 PhD thesis by Dorte Haubjerg Søgaard photosynthetically active radiation (PAR; light spectrum 300–700 nm) after intercalibration (R 2 =0.99, P\0.001, n=133) with a Li-Cor quantum 2 pi sensor connected to a LI-1400 data logger (Li-Cor Biosciences Ò ). The in situ hourly PAR irradiance was calculated at different depths, depending on sea ice and snow thickness, using the attenuation coefficients measured during the sea ice season. In situ primary production was calculated for each hour at different sea ice depths using hourly in situ PAR irradiance (Eq. 1). Total daily (24 h) in situ primary production was calculated as the sum of hourly in situ primary production for each depth. The depth-integrated net primary production was calculated using trapezoid integration. Light attenuation of the sea ice samples was measured with a Li-Cor quantum 2 pi sensor connected to a LI-1400 data logger (Li-Cor Biosciences Ò ) in a dark, temperatureregulated room (at in situ temperatures to avoid brine loss) using a fiber lamp with a spectrum close to natural sunlight (15 V, 150 W, fiber-optic tungsten–halogen bulb). The sensor was placed under the sea ice section and the fiber lamp was placed above. Light attenuation was measured in this way for each sea ice section. We assume depth-independent attenuation in the sea ice. To measure light attenuation of the snow cover, we gently removed the snow and placed the sensor on the ice surface and then we placed the snow on top of the sensor. Thus, down-welling irradiance was measured directly above and below the snow (Søgaard et al. 2010). The bacterial production procedures employed (i.e., 17 February, 11 March, 8 April, and 1 May) have been described by Søgaard et al. (2010), except those between 13 and 16 March, when the measurements were made using an ice-crushing method described by Kaartokallio (2004) and Kaartokallio et al. (2007). The two methods used for bacterial production measurements yield comparable results (the mean values from March using the ice-crushing method were 2.4 lgCl -1 day -1 and the mean values from April using the melting sea ice approach were 2.5 lgCl -1 day -1 ). Bacterial production in melted sea ice samples was determined by measuring the incorporation of [ 3 H] thymidine into DNA. Triplicate samples (volume =0.01 L) were incubated in darkness at 3 ±1°C with 10 nmol l -1 of labeled [ 3 H] thymidine (New England Nuclear Ò , specific activity 10.1 Ci mmol -1 ). Trichloroacetic acid (TCA)- treated controls were made to measure the abiotic adsorption. At the end of incubation period (T=6 h), 1 ml of 50 % cold TCA was added to all the samples. The samples were filtered and counted using a liquid scintillation analyzer (TricCarb 2800, PerkinElmer Ò ). For the ice-crushing method, samples were prepared by crushing each intact 5 to 10 cm ice core section, first using a spike tool, and then grinding ice chunks in an electrical ice cube crusher. Approximately 10 ml of crushed ice was placed in a scintillation vial and weighed. To ensure even distribution of labeled substrate, 2–4 ml of sterile-filtered (0.2 lm minisart filters, Sartorius Ò ) seawater was added to the scintillation vials. All ice-processing work was done in a cold on-deck laboratory at near-zero temperature. Two aliquots and a formaldehyde-killed absorption blank were amended with [methyl-3H] thymidine (New England Nuclear Ò ; specific activity 20 Ci mmol -1 ). Concentrations of 20 nmol l -1 for thymidine were used for all samples. Samples were incubated in the dark at -0.2 °C in a seawater/ice-crush bath for 17–18 h and incubation stopped with the addition of 200 ll of 37 % sterile-filtered formaldehyde. Samples were processed using standard coldTCA extraction and filtration procedure (using Advantec Ò MFS 0.2 lm MCE filters). A Wallac Win-Spectral 1414 counter (PerkinElmer Ò ) and InstaGel (PerkinElmer Ò ) cocktail were used for scintillation counting. For both methods, the bacterial carbon production was calculated, using the conversion factors presented in Smith and Clement (1990). Bacterial carbon demand (BCD) for growth was calculated as: BCDðlgCl 1h1Þ¼ BP BGE ð2Þ where BP is the bacteria production and BGE is a bacterial growth efficiency estimate of 0.5 measured in polar oceans (Rivkin and Legendre 2001). To investigate the temporal distribution of TCO 2 and TA, an additional sea ice core was collected on each sampling occasion. The core was cut into 12-cm sections and placed in laminated transparent NEN/PE plastic bags (Hansen et al. 2000) fitted with a gas-tight Tygon tube and a valve for sampling. These sections were brought back to the laboratory cold room (3 ±1°C). Cold (1 °C) deionized water of known weight and TA and TCO 2 concentration was added (10–30 ml) to each NEN/PE bag (Hansen et al. 2000). The bags were closed, and excess air quickly extracted through the valve. Then, the ice was melted (\48 h) in the dark. Gas bubbles released from the melting sea ice were transferred to tubes (12 ml Exetainer Ò ). Sea ice meltwater was likewise transferred to similar tubes containing 20 ll HgCl 2 (5 % w/v saturated solution; Rysgaard and Glud 2004). Standard methods of analysis were used: TCO 2 concentrations were measured on a coulometer, TA by potentiometric titration (Haraldsson et al. 1997), and gaseous O 2 ,CO 2 ,N 2 by gas chromatography (SRI 8610C; FID/TCD detector; Lee et al. 2005). A Wilcoxon rank sum test was used to test whether CaCO 3 concentration was significantly differently distributed within the sea ice. We applied a significance level of 95 %. Polar Biol (2013) 36:1761–1777 1765 123 49 PhD thesis by Dorte Haubjerg Søgaard Following the bulk determination of TCO 2 and TA, the bulk pCO 2 and pH (on the total scale) were computed using the temperature and salinity conditions in the field and a standard set of carbonate system equations (See Rysgaard et al. 2013), excluding nutrients, with the CO2SYS program of Lewis and Wallace (2012). We used the equilibrium constants of Mehrbach et al. (1973), refitted by Dickson and Millero (1987,1989). We assumed a conservative behavior of CO 2 dissociation constants at subzero temperatures since Marion (2001) and Delille et al. (2007) suggested that a thermodynamic constant relevant for the carbonate system can be assumed to be valid at subzero temperatures. Results Figure 1shows a map of the investigated sea ice area with the different sampling stations in Kapisigdlit, SW Greenland (Fig. 1). The air temperature during the study period ranged from -17 °C in February to ?16 °C in May just before the sea ice break-up (Fig. 2). Temperatures within the snow and sea ice varied from -6.0 ±0.1 to 0 ±0.02 °C, with minimum temperatures measured in February and March, followed by a gradual increase to maximum values in late April (Fig. 3a). The bulk salinity of the sea ice samples varied from 1.7 to 6 (Fig. 3b). The brine volume varied from 5 to 32 % at the top of the sea ice and from 12 to 40 % at the bottom of the sea ice (Fig. 3c), an indication that the ice was permeable for most of the study (Golden et al. 1998). In April, when air temperatures varied between -2 and ?16 °C, the ice began to melt, which resulted in high relative brine volumes and low bulk salinities (Fig. 3b, c). Spatial variability Moran’s I (Table 1) was used to estimate the spatial autocorrelation within the datasets collected for the two transect samplings in March and April. All parameters had a random spatial distribution pattern with no apparent patches, indicating that the distribution of the parameters investigated was highly heterogeneous on the scale of meters to hundreds of meters (Table 1). Despite this heterogeneity, there was evidence of a correlation between several parameters: CaCO 3 had significant correlation with PO 43- , bulk salinity, Si(OH) 4 and NO 3 - . CaCO 3 and DON were significantly correlated (negative) only during the second sampling. There was no -20 -15 -10 -5 0 5 10 15 20 17/02 03/03 17/03 31/03 14/04 28/04 12/05 Air temperature ( o C) Air temperature Fig. 2 Meteorological data on air temperature (°C) at the Asiaq meteorological station in Kapisigdlit (a) Sea ice and snow temperature [ºC] -20 0 20 -40 -60 -80 Sea ice and snow depth [cm] (c) Relative brine volume [%] -20 0 20 -40 -60 -80 -20 0 20 -40 -60 -80 Feb March A p ril Ma y 30 30 30 40 20 20 20 10 10 5 -1.2 -0.8 -3 -4 -2.8 -2.8 -2.0 -2.0 -7.0 -5.0 -5.0 -1.2 -4 -2.0 -6.0 -6.0 (b) Bulk salinity 5 4 6 4 3 3 Fig. 3 Temporal development in (a) sea ice and snow temperature [°C] N.B. The temperature data collected from retrieved ice cores are supplemented by thermistor string data from 11 March until 8 April, (b) bulk salinity, (c) relative brine volume fraction [%]. The black dots represent triplicate measurements 1766 Polar Biol (2013) 36:1761–1777 123 50 PhD thesis by Dorte Haubjerg Søgaard correlation between CaCO 3 and DOC, NH 4 ? ,NO 2 - , and temperature (Table 2). A GLM where depth (vertical), time, and position (horizontal) as explanatory variables is used to test whether there was a significant effect on several dependent variables: CaCO 3 , bulk salinity, DOC, and DON. The GLM test was applied on the datasets collected for the two transect samplings in March and April. There was a significant effect of depth for all the parameters. The significant effect of depth was largely dependent on the time of sampling for CaCO 3 (F 5,261 =15.9784, P\0.001), bulk salinity (F 5,248 =5.6322 P\0.001), and DON (F 5,239 = 3.6861 P\0.001) (data not shown). Furthermore, when the two studies in March and April were compared, a significant effect of time was found for bulk salinity, DOC, and DON (Table 3). No significant effect of position (horizontal) was found for CaCO 3 , bulk salinity, and DON (Table 3). Temporal distribution In the temporal survey, there were no vertical differences in TCO 2 and TA (Fig. 4), although the concentrations of TCO 2 and TA decreased with time (Fig. 4). The highest TCO 2 and TA concentrations were measured in February (293 ±6.1 and 410 ±40 lmol kg -1 in melted sea ice), which decreased to 181 ±1.3 and 190 ±1.2 lmol kg -1 in melted sea ice in the beginning of May, respectively (Fig. 4). However, high concentrations of TA and TCO 2 were also measured in April (Fig. 4). No small-scale variability was observed for TCO 2 and TA concentrations. Table 1 Moran’s I as a function of distance class (m) between sites for CaCO 3 , bulk salinity, DOC, DON, NH 4 ? ,NO 2 - ,NO 3 - , Si(OH) 4 and PO 43in snow (S), top sea ice (T) and bottom sea ice (B). First sampling period was on March 11 and second sampling period was on April 8, 2010. Positive (?) indicates positive autocorrelation (correlation) or negative (-) negative autocorrelation (dispersion). A zero value indicates a random spatial pattern First sampling Distance class (m) CaCO 3 Bulk salinity DOC DON NH 4 ? NO 2 - NO 3 - Si(OH) 4 S TBS T B STBS T BS TBS T BS T BS T B 0.25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.5 0 0 0 0 -0 000000000000000000 1.0 0 0 0 0 --0000 -00000000---00 2.5 0 0 0 -00000??0-00-????00-0 5.0 0 0 0 0 -00000-0000000000-00 10 0 0 0 -0 0 000000000000000000 50 0000 0 0 000000-000 -0000000 100 0 0 0 0 0 0 0 0 0 -0-000000000000 200 0 0 0 0 0 0 0 0 0 -000000000000-0 250 -000 ?0000-00?000 0 0 -00000 [250 -000 0 0 000000000000000000 Second sampling Distance class (m) CaCO 3 Bulk salinity DOC DON NH 4 ?NO 2 - NO 3 - Si(OH) 4 PO 43STBS T B STBSTBSTBSTBSTBSTBSTB 0.25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -000000000 0.5 0000 0 0 0-00-0000000000000000 1.0 0000 -0 0000000000--00-000000 2.5 ?-0???0?0-00-0?00 0 ?00000000 5.0 0000 0 0 00000000000--00-00?00 10 0000 0 0 0000000000?0000000000 50 0000 0 0 0000000000-0000000000 100 0000 0 0 0-00000-00000000000-0 200 0000 0 0 000000000000000000000 250 0 0 -0000?000000000?0--000000 [250 0000 0 0 000000000000000000000 Polar Biol (2013) 36:1761–1777 1767 123 51 PhD thesis by Dorte Haubjerg Søgaard In the water column, the highest TCO 2 concentration, of 2,101 ±7.7 lmol kg -1 , was measured in February, which decreased to 2,085 ±27 lmol kg -1 in May (Fig. 4). The highest TA concentration of 2,253 ±2.5 lmol kg -1 was measured in May and the lowest of 2,220 ±2.2 lmol kg -1 in March (Fig. 4). The average TA:TCO 2 ratio within the sea ice was [1 during February (average 1.25) and March (average 1.20), and higher than that in the water column (Fig. 4). The highest TA:TCO 2 ratio (1.75) was calculated for the uppermost horizons of the sea ice in April. In April, the average ratio was 1.32, while the value in the beginning of May was 1.1. The CaCO 3 concentrations varied vertically within the ice cores: in February the highest concentration of 2.4 ±0.4 lmol CaCO 3 l -1 was measured in the upper most layer of the sea ice (Wilcoxon rank sum test; P\0.05; Fig. 5). Conversely, just before ice break-up in early May, the highest CaCO 3 concentration of 4.4 ±0.1 lmol CaCO 3 l -1 was measured in the lowermost ice horizon (Wilcoxon rank sum test; P\0.05; Fig. 5). In March and April, CaCO 3 was evenly distributed within the sea ice with an average concentration of 1.8 ±0.40 lmol CaCO 3 l -1 in March and 2.0 ±0.30 lmol CaCO 3 l -1 in April (Wilcoxon rank sum test; P[0.05). No small-scale variability was observed for CaCO 3 concentration in the sea ice (Fig. 5). CaCO 3 concentrations in the snow decreased throughout the sea ice season: from 5.2 ±1.5 lmol CaCO 3 l -1 in February to 3.0 ±1.5 lmol CaCO 3 l -1 in April (Fig. 5). Sediment traps were deployed under the sea ice during the study period but no CaCO 3 crystals were found (data not shown). The DOC concentrations increased over time with a maximum concentration of 160 lmol l -1 being measured in May in the bottommost layer of the ice (Fig. 6). DON concentrations did not vary vertically within the sea ice during winter. However, in April and May, when the sea ice began to melt, the DON concentrations increased, and maximum DON values of 15 lmol l -1 were measured in the bottommost part of the sea ice (Fig. 6). The DOC:DON ratios ranged from 5 to 20 (average 12). The highest volume-specific primary production (bulk) of 25 lgCl -1 day -1 was measured in March in the bottom of the sea ice (Fig. 6). Bacterial carbon demand varied vertically within the sea ice, with maximum values measured in the top and bottom section of the sea ice in March and May (Fig. 6). In February and April, the maximum BCD was measured in the internal sea ice layers. The highest BCD of 5.8 lgCl -1 day -1 was estimated in the bottommost sections of the sea ice in March. Bulk nutrient concentrations for each sampling date were plotted as a function of bulk salinity and compared with the expected dilution line (Clarke and Ackley 1984). To calculate the dilution line, we used the average nutrient concentration and salinity measured at 17 February, 11 Table 2 Pairwise comparison of CaCO 3 , bulk salinity, temperature, DOC, DON, NH 4 ? ,NO 2 - ,NO 3 - , Si(OH) 4 and PO 43- .(-) indicates significantly negative (-) and (?) indicates significantly positive (?) correlated variables (Pearsons) at a 5 % significance level. First sampling period was in March and second sampling period in April 2010 12 bulk salinity 12 temperature 12 DOC 12 DON 12 NH 4+ 12 NO 212 NO 312 Si(OH) 4 12 PO 43CaCO 3 bulk salinity - - temperature · · · · DOC · · · · · · DON · - · - · · · · ·· · - · · ·-·· ·· · · + · · ····+ ++ - - + · · - · -++·+ -- · + · · · · ·+--··- - -- · · · · · · · --+··-+· · NH 4+ NO 2NO 3Si(OH) 4 PO 43CaCO 3 Table 3 Results from a GLM model where depth, time, and position as explanatory variables were used to test whether there was a significant effect on several dependent variables: CaCO 3 , bulk salinity, DOC, and DON Variable Position Time Depth CaCO 3 F 24,261 =1.2685 P=0.19 F 1,261 =2.6087 P=0.11 F 5,261 =53.7673 P\0.001 Bulk salinity F 24,248 =0.8054 P=0.73 F 1,248 =18.4728 P\0.001 F 5,248 =14.2994 P\0.001 DOC F 24,217 =2.13 P\0.001 F 1,217 =224.6497 P\0.001 F 5,217 =3.1986 P\0.001 DON F 24,239 =0.5919 P=0.94 F 1,239 =162.4025 P\0.001 F 5,239 =6.6925 P\0.001 1768 Polar Biol (2013) 36:1761–1777 123 52 PhD thesis by Dorte Haubjerg Søgaard March, 8 April, and 1 May in the water column (i.e. 0–10 m; PO 43- =0.94 lmol l -1 , Si(OH) 4 =7.0 lmol l -1 ,NO 2 - ?NO 3 - =8.6 lmol l -1 ,NH 4 ? =0.28 lmol l -1 , DOC =62.6 lmol l -1 , DON =1.2 lmol l -1 and a average salinity of 33). If values are below the line, depletion of nutrients has taken place, and if above the dilution line production, or net-deposition, of the solute has occurred. Plots of salinity versus PO 43- , Si(OH) 4 ,NO 2 - ? NO 3 - ,NH 4 ? , DOC, and DON in sea ice were generally all above the dilution line implying accumulation of nutrients and organic matter within the ice (Fig. 7a–f). However, depletion of PO 43was observed in February and March. Furthermore, NO 2 - ?NO 3 - was depleted in April and May. There was a negative correlation between PO 43and CaCO 3 and Si(OH) 4 and CaCO 3 , while a positive correlation was observed between NO 3 - and CaCO 3 (Table 2). 0 500 1000 1500 2000 2500 1,0 1,2 1,4 1,6 1,8 0 500 1000 1500 2000 2500 1,0 1,2 1,4 1,6 1,8 TCO 2 and TA (μmol kg -1 ) 0 20 40 60 Water February March Ta:TCO 2 ratio Ta:TCO 2 ratio April Ta:TCO 2 ratio Ta:TCO 2 ratio May TCO 2 and TA (μmol kg -1 ) 0 500 1000 1500 2000 2500 1,0 1,2 1,4 1,6 1,8 Sea ice and water depth (cm) 0 500 1000 1500 2000 2500 0,8 1,0 1,2 1,4 1,6 1,8 0 20 40 60 Water 0,8 0 20 40 60 Water 0,8 0 20 40 60 Water 0,8 Sea ice and water depth (cm) Fig. 4 Temporal development of the vertical concentration profiles of TCO 2 (black bars) and TA (gray bars) and the TA:TCO 2 ratio (circles) in bulk melted sea ice during the 2010 sea ice season. Note that TCO 2 and TA below 60 cm are water column values. Horizontal dotted line represents the sea ice–water column interface. Data points represent treatment mean ±SE (n=3) μmol CaCO3 l-1 0246810 Snow and sea ice depth (cm) 0 -20 -40 -60 February March April May Snow Fig. 5 Temporal development of the CaCO 3 concentration [lmol CaCO 3 l -1 ] in bulk sea ice and snow in February, March, April, and May 2010 Polar Biol (2013) 36:1761–1777 1769 123 53 PhD thesis by Dorte Haubjerg Søgaard Figure 8shows nTA and nTCO 2 (TA and TCO 2 value being normalized to a salinity of 33 to remove correlation to salinity) relationships in seawater samples and bulk ice samples. The different lines represent the theoretical effects of precipitation–dissolution of CaCO 3 ,CO 2 release–uptake and photosynthesis–respiration on the ratio nTCO 2 :nTA. The precipitation of CaCO 3 decreases both TCO 2 and TA in a ratio of 2:1. An exchange of CO 2 has no impact on TA, while TCO 2 will be affected. Biological activity has an almost negligible effect on TA, with a ratio TA:TCO 2 =-0.16 (Zeebe and Wolf-Gladrow 2001). Considering that sea ice was formed from seawater with a known TA:TCO 2 ratio (Fig. 4), we are able to decipher which process took place in the ice: in February and March, the sea ice samples were aligned on the theoretical line for CaCO 3 precipitation (Fig. 8). In April and May, the ice samples were well aligned (slope 0.75; R 2 =0.86) between the theoretical trend for CaCO 3 precipitation/dissolution and the one for CO 2 release/uptake (Fig. 8). In April two sea ice samples were aligned on the theoretical line for CaCO 3 dissolution. This implies that both CaCO 3 precipitation/dissolution and CO 2 release/uptake had occurred in the ice. Discussion Biological activity A maximum BCD of 5.8 lgCl -1 day -1 (Fig. 6) was estimated, which is low compared with maximum rates of 27 lgCl -1 day -1 estimated in the neighboring fjord Malene Bight in April 2008 (60 km to the SW from the present study site; Søgaard et al. 2010). Pairwise correlations between primary production and BCD revealed significant positive relationships. Furthermore, accumulation of DOC was observed (Fig. 6e–f) as well as DOC/DON ratios ranging from 5 to 20 indicating a probable production of carbon-rich extracellular polymeric substances (EPS) by the sea ice algae and bacteria (Underwood et al. 2010; Krembs et al. 2011; Juhl et al. 2011). Correlation between primary production and BCD, high DOC/DON ratio and accumulation of DOC points to there being a low-quality substrate resulting in a low bacteria production. Previous studies have shown that EPS is a low-quality substrate for heterotrophic bacteria (Pomeroy and William 2001), which might explain the low BCD and the observed DOC accumulation (Fig. 6). However, several DON (μmol l-1) Bacterial carbon demand (μg C l-1 d-1 ) Primary production (μg C l-1 d-1 ) 0 10 20 30 40 50 60 0 10 20 30 40 50 60 DOC (μmol l-1) Sea ice deptn (cm) Sea ice deptn (cm) 0 10 20 30 40 50 60 810121416 20 40 60 80 100 120 140 160 180 0246 0123456 0 5 10 15 20 25 30 0 10 20 30 40 50 60 February March April May February March April May March April May March April May Fig. 6 Vertical profiles of DOC, DON, primary production, and bacterial carbon demand in bulk sea ice in February to May. N.B. there were no data available on the vertical profiles of DOC and DON in February 1770 Polar Biol (2013) 36:1761–1777 123 54 PhD thesis by Dorte Haubjerg Søgaard studies suggest the opposite that EPS serve as high-quality substrate for bacteria (e.g. Junge et al. 2004; Meiners et al. 2008). Another explanation for the low BCD might be the value for bacterial growth efficiency used. We used a bacterial growth efficiency of 0.50 (Rivkin and Legendre 2001). However, growth efficiency is an inverse function of temperature, and small changes in temperature would influence growth efficiency (*2.5 % decrease in growth efficiency per 1 °C increase) and thereby the BCD (Rivkin and Legendre 2001). Using a lower growth efficiency (\0.15; e.g. Middelboe et al. 2012), the seasonal net autotrophic sea ice would change to a net heterotrophic sea ice, which compares to result found by Long et al. (2011) in Kapisigdlit Bight in March 2010. Thereby the biological activity would not contribute to the atmospheric CO 2 uptake at all. However, we believe the use of a growth efficiency of 0.50 to be most valid since it also agrees with the growth efficiency of 0.41 measured by Kuparinen et al. (2011) and Del Giorgio and Cole (1998). The highest estimates of primary production (Fig. 6) were measured in the bottom ice horizons in March. Average rates of sea ice algal primary production during March (4.03 mg C m -2 day -1 ) are at the lower end of the llomμ(noitartnecnoctneirtuN -1 ) 0 2 4 6 8 10 0 1 2 3 4 0 20 40 60 80 100 120 140 llomμ(noitartnecnoctneirtuN -1 ) (a) PO43llomμ(noitartnecnoctneirtuN -1 ) (b) Si(OH)4 0 2 4 6 8(c) NO2- + NO30,0 0,5 1,0 1,5 2,0 2,5 3,0 (d) NH4+ (e) DOC 0246810 0246810 0246810 02468100246810 0246810 0 2 4 6 8 10 12 14 16 Bulk salinity Bulk salinity (f) DON February March April May February March April May February March April May February March April May February March April May February March April May Fig. 7 Temporal development of (a) PO 43- ,(b) Si(OH) 4 ,(c) NO 2 - ?NO 3 - ,(d)NH 4 ? ,e) DOC, and f) DON concentrations versus bulk salinity in sea ice from February to May. The solid line indicates the expected dilution line predicted from salinity and nutrient concentrations in seawater (0–10 m, average salinity of 33 under the sea ice) Polar Biol (2013) 36:1761–1777 1771 123 55 PhD thesis by Dorte Haubjerg Søgaard scale for values reported from the Arctic (0.2–463 mg C m -2 day -1 ; Arrigo et al. 2010 and references therein). A decrease in TCO 2 was measured in the bottommost ice at the time of the algae growth, suggesting that primary production was responsible for the decrease in TCO 2 (Figs. 4,6). However, the average net biological production in the bottom of the sea ice in March was only 1.6 lmol C day -1 (Fig. 6) and the average TCO 2 loss in the bottom of the sea ice in March was 6.4 lmol day -1 , indicating that processes other than primary production influence the inorganic carbon dynamics in the sea ice. TCO 2 in sea ice is controlled by primary production and respiration by both autotrophic and heterotrophic organisms, CaCO 3 precipitation/dissolution, and CO 2 release/ uptake. The magnitude of the primary production and thus the potential role of the production in controlling the sea ice inorganic carbon cycle depend primarily on light availability and the size of the inorganic nutrient pool (Papadimitriou et al. 2012). The highest light attenuation coefficient of 12 m -1 was measured in March in the snow, corresponding to coefficients reported in snow cover in both the Arctic and Antarctic (Thomas 1963; Weller and Schwerdtfeger 1967; Søgaard et al. 2010). High snow reflection causes low light conditions in the sea ice. However, the highest primary production was found in the bottom of the sea ice in March (Fig. 6), where the light availability was low compared to spring, indicating that light was not the main factor controlling the primary production. However, the low primary production in the bottom of the sea ice after March suggests that the sea ice algae were nutrient-limited late in the sea ice season. Assuming that nutrient uptake by the ice algae follows the Redfield-Brzezinski ratio of 106C:16N:15Si:1P (from Redfield et al. 1963; Brzezinski 1985), then the nitrogen (N:P ratio \2) and silicate (Si:P ratio \6) appear to have limited the sea ice algal primary production in April and May, while phosphate was found at relatively higher concentrations. This is supported by the nutrient-salinity plot for NO 2 - ?NO 3 - in Fig. 7, which indicates depletion of NO 2 - ?NO 3 - at the end of the sea ice season. A further factor known to influence the sea ice algal communities is grazing (Gradinger et al. 1999; Bluhm et al. 2010); however, grazing was not measured during the present study. CaCO 3 precipitation The observed CaCO 3 formation was expected (Anderson and Jones 1985; Marion 2001; Papadimitriou et al. 2004) and is consistent with the elevated TA:TCO 2 ratios (Fig. 4). We measured much lower TCO 2 and TA concentrations within the sea ice compared to concentrations found in the underlying seawater (average TA:TCO 2 ratio =1.06 in seawater; Fig. 4). Likewise, we found elevated TA:TCO 2 ratios in the sea ice with a maximum of 1.75, as compared to the underlying seawater (Fig. 4). However, the TA:TCO 2 ratios found in the sea ice in the present study are low compared to values found in other sea ice studies (Rysgaard et al. 2007,2012; Papadimitriou et al. 2012; Geilfus et al. 2012; Rysgaard et al. 2013). Ikaite precipitation is favored by near-freezing temperature, alkaline condition, and elevated phosphate concentrations ([5lmol l -1 ; Bischoff et al. 1993; Buchardt et al. 2001; Selleck et al. 2007). In this study, bulk phosphate concentrations between 0.2 and 3.1 lmol l -1 were measured in the sea ice, and therefore, the brine phosphate concentrations were occasionally above 5 lmol l -1 . Furthermore, the phosphate concentrations observed in present study were 5–20 times higher than concentrations found in previous studies in the Arctic (e.g. Krembs et al. 2002; Mikkelsen et al. 2008; Søgaard et al. 2010). Sea ice temperatures during our study ranged from -6to0°C, which is the temperature where ikaite will form. Alkalinity condition was also satisfied as a C-shaped pH profile with high pH ([9) in surface, and bottom sea ice layers, and slightly lower pH conditions (8.5) in the internal sea ice layers were calculated for February, using temperature and bulk salinity (Fig. 3), TA and TCO 2 concentrations (see ‘‘Materials and methods’’ section; Fig. 4). A C-shaped pH profile was also observed in a recent study on experimental sea ice (Hare et al. 2013). In the early part of the study, we measured the highest CaCO 3 concentrations in the surface of the sea ice, and the concentrations decreased with depth (Fig. 5). This is similar to that described by Geilfus et al. (2013) and Rysgaard et al. (2013). nTCO2 0 1000 2000 3000 4000 5000 6000 7000 0 2000 4000 6000 CaCO3 precipitation CaCO3 dissolution CO2 invasion CO2 release Respiration Photosynthesis nTA Sea ice - Feb. Sea ice - Mar. Sea ice - Ap. Sea ice - May Seawater Fig. 8 nTA:nTCO 2 (values normalized to a salinity of 33) relationship in seawater samples and bulk ice samples from February to May. The different lines represent the theoretical evolution of TCO 2 :TA following precipitation/dissolution of calcium carbonate (dashed line), a release or uptake of CO 2 (g) (dotted line) and impact of biology (solid line) 1772 Polar Biol (2013) 36:1761–1777 123 62 PhD thesis by Dorte Haubjerg Søgaard The Cryosphere, 7, 707–718, 2013 www.the-cryosphere.net/7/707/2013/ doi:10.5194/tc-7-707-2013 © Author(s) 2013. CC Attribution 3.0 License. The Cryosphere Open Access Ikaite crystal distribution in winter sea ice and implications for CO2 system dynamics S. Rysgaard1,2,3,4, D. H. Søgaard3,6,M.Cooper 2,M.Pu´ cko1, K. Lennert3, T. N. Papakyriakou1,F.Wang 1,5, N. X. Geilfus1,R.N.Glud 3,6,7,J.Ehn 1,D.F.McGinnis 6, K. Attard3,6,J.Sievers 4,J.W.Deming 8, and D. Barber1 1Centre for Earth Observation Science, Department of Environment and Geography, University of Manitoba, Winnipeg, MB R3T 2N2, Canada 2Department of Geological Sciences, University of Manitoba, Winnipeg, MB R3T 2N2, Canada 3Greenland Climate Research Centre, Greenland Institute of Natural Resources, 3900 Nuuk, Greenland 4Arctic Research Centre, Aarhus University, 8000 Aarhus, Denmark 5Department of Chemistry, University of Manitoba, Winnipeg, MB R3T 2N2, Canada 6University of Southern Denmark and NordCEE, Odense M, Denmark 7Scottish Association for Marine Science, Oban, UK 8University of Washington, School of Oceanography, Seattle, WA, USA Correspondence to: S. Rysgaard ([email protected]) Received: 18 November 2012 – Published in The Cryosphere Discuss.: 6 December 2012 Revised: 30 March 2013 – Accepted: 2 April 2013 – Published: 23 April 2013 Abstract. The precipitation of ikaite (CaCO3·6H2O) in polar sea ice is critical to the efficiency of the sea ice-driven carbon pump and potentially important to the global carbon cycle, yet the spatial and temporal occurrence of ikaite within the ice is poorly known. We report unique observations of ikaite in unmelted ice and vertical profiles of ikaite abundance and concentration in sea ice for the crucial season of winter. Ice was examined from two locations: a 1m thick land-fast ice site and a 0.3m thick polynya site, both in the Young Sound area (74◦N, 20◦W) of NE Greenland. Ikaite crystals, ranging in size from a fewμm to 700μm, were observed to concentrate in the interstices between the ice platelets in both granular and columnar sea ice. In vertical sea ice profiles from both locations, ikaite concentration determined from image analysis, decreased with depth from surface-ice values of 700–900μmolkg−1ice (∼25×106crystalskg−1)to values of 100–200μmolkg−1ice (1–7×106crystalskg−1)near the sea ice–water interface, all of which are much higher (4– 10 times) than those reported in the few previous studies. Direct measurements of total alkalinity (TA) in surface layers fell within the same range as ikaite concentration, whereas TA concentrations in the lower half of the sea ice were twice as high. This depth-related discrepancy suggests interior ice processes where ikaite crystals form in surface sea ice layers and partly dissolve in layers below. Melting of sea ice and dissolution of observed concentrations of ikaite would result in meltwater with a pCO2of <15μatm. This value is far below atmospheric values of 390μatm and surface water concentrations of 315μatm. Hence, the meltwater increases the potential for seawater uptake of CO2. 1Introduction As sea ice forms from seawater, dissolved salts are trapped in interstitial liquid brine inclusions. Because phase equilibrium must be maintained between these inclusions and the surrounding ice, the brine becomes increasingly concentrated as temperatures decrease. Solid salts begin to precipitate out of solution, starting with ikaite (CaCO3·6H2O) at −2.2◦C, mirabilite (NaSO4·10H2O) at −8.2◦C and hydrohalite (NaCl·2H2O) at −23◦C (Assur, 1960). The mineral ikaite was recently discovered in springtime sea ice in both hemispheres (Dieckmann et al., 2008, 2010). Ikaite crystals appeared to be present throughout the sea ice, but with larger crystals and higher abundance in surface layers (Dieckmann et al., 2010; Rysgaard et al., 2012; Geilfus et al., 2013). Ikaite crystals of various sizes and morphologies have been isolated Published by Copernicus Publications on behalf of the European Geosciences Union. 63 PhD thesis by Dorte Haubjerg Søgaard 708 S. Rysgaard et al.: Ikaite crystal distribution in winter sea ice from sea ice. They range in size from a few μm to large mmsize crystals; all are highly transparent with rounded rhombic morphology and show uniform extinction under crossed polarized light, suggesting simple, single well-crystalline crystals. The specific conditions promoting ikaite precipitation in sea ice are poorly understood, but if precipitation occurs during the ice-growing season in the porous lower sea ice layer, where the brine volume is greater than 5% (Weeks and Ackley, 1986; Golden et al., 1998, 2007; Ehn et al., 2007), then the resulting CO2-enriched brine will exchange with seawater via gravity drainage (Notz and Worster, 2009). Earlier work has led to the suggestion that ikaite crystals may remain trapped within the skeletal layer where they act as a store of TA, becoming a source of excess TA to the ocean water upon subsequent mineral dissolution during summer melt (Nedashkovsky et al., 2009; Rysgaard et al., 2011). This excess would lower the partial pressure of CO2(pCO2)of surface waters affected by melting sea ice and cause an increase in the air–sea CO2flux. At this point, the spatial and temporal occurrence of ikaite precipitates within sea ice is poorly constrained. There is urgency for increasing the knowledge base, given that the precipitation of CaCO3is implicated in many processes of global significance, including the sea ice-driven carbon pump and global carbon cycle (Delille et al., 2007; Rysgaard et al., 2007, 2011; Papadimitriou et al., 2012) and pH conditions (acidification) in surface waters (Rysgaard et al., 2012; Hare et al., 2013). Quantification of CaCO3crystals in sea ice in the few previous studies has been made on melted samples assuming that ikaite will not dissolve if temperature is maintained below 4◦C. In principle, however, dissolution may also be related to the reaction of ikaite with CO2in the meltwater or with the atmosphere during the melting procedure, which can last for days at low temperature allowing the possibility of changing pH in the surroundings of the ikaite crystal and underestimation of ikaite concentration. Examining ikaite in such melted samples also makes it impossible to evaluate spatial distribution within the sea ice matrix on the micrometer to millimeter scale and determine whether or not the mineral is entrapped in the ice crystal lattice and thus separated from the solution. Precipitation of ikaite in standard seawater conditions is described by Ca2++2HCO− 3+5H2O↔CaCO3·6H2O+CO2.(1) Brine drainage from sea ice is expected to result in a removal of dissolved CO2along with salts. If precipitated ikaite crystals become trapped within sea ice interstices, then the reaction in Eq. (1) is pushed to the right in brine, providing further potential for CaCO3growth. Over time, the concentration of trapped ikaite crystals could increase. Here we provide novel tests of these ideas during crucial winter conditions by examining ikaite in intact (unmelted) natural sea ice and determining detailed vertical ikaite distributions in the sea ice from two locations in Young Sound (northeast Greenland). Combined with other measurements and model calculations, the results allow us to relate sea ice formation and melt to the observed pCO2conditions in surface waters, and hence, the air–sea CO2flux. 2 Methods 2.1 Study site and sampling Sampling was performed at two locations in the Young Sound area (74◦N, 20◦W: Rysgaard and Glud, 2007), NE Greenland, in March 2012 (Fig. 1). The land-fast ice station, ICE I (74◦18.5764N, 20◦18.2749W), was in the fjord with 110–115cm thick sea ice covered by 70cm of snow. Freeboard at ICE I was negative, e.g. when a hole was drilled through the ice, the ice surface flooded. However, at sites without drilled holes, we did not observe flooding during our experiment and there was a distinct snow–ice interface. On top of the ice of ICE I, about 8cm of slush snow at the snow– ice interface was observed. The new-ice station, POLY I (74◦13.905N, 20◦07.701W), was situated in a polynya region about 3km off the sharp land-fast ice edge, where sea ice regularly breaks up in winter. At the time of sampling, POLY I was 15–30cm thick and covered by 17cm of snow. At POLY I there was negative freeboard too – with about 2cm of slush snow at the snow–ice interface. At POLY I the snow was denser up to ∼8cm from the ice interface, then a bit lighter (newer snow) above. Air temperature during sampling ranged from −20 to −25◦C. The polynya site is representative of thin Arctic sea ice, whereas the ICE I location is representative of fjord ice in the Arctic where there is a large source of winter precipitation (snow). Snow was very dry and very cold (unlike Antarctic ice). There was also no surface flooding. ICE I is typical of sea ice in fjords or where large moisture sources are available to the Arctic winter climate system. Sea ice cores were extracted using a MARK II coring system (Kovacs Enterprises). Vertical temperature profiles were measured with a thermometer (Testo Orion 3-star with an Orion 013610MD conductivity cell) in the center of the cores immediately after coring. Sea ice was then cut into 5–10cm sections, kept cold and brought to the field laboratory within 1h for processing. In the 20◦C laboratory, sea ice sections were melted for measurement of bulk salinity with a conductivity probe (Thermo Orion 3-star with an Orion 013610MD conductivity cell, UK) calibrated against a 15N KCLsolutionat20◦C. Brine volume in sea ice was calculated according to Cox and Weeks (1983) and Lepp¨ aranta and Manninen (1988). Brine salinity was calculated from the measured sea ice temperatures and freezing point of seawater (Unesco, 1978). Although there was a lot of snow on the thick fast ice in the fjord there was not natural flooding of the surface. When we installed ocean instruments (drilling through the ice) we The Cryosphere, 7, 707–718, 2013 www.the-cryosphere.net/7/707/2013/ 64 PhD thesis by Dorte Haubjerg Søgaard S. Rysgaard et al.: Ikaite crystal distribution in winter sea ice 709 Godhavn Thule Godthåb Angmagssalik Scoresby Sund Greenland Canada ABWollaston Forland Clavering island Fig. 1. Study site. (A) Greenland showing the study area (box) and (B) the Young Sound fjord between Wollaston Forland and Clavering Island. Sea ice coring sites for the land-fast ice location (ICE I) is shown as a red star and the polynya coring site (POLY I) as a yellow star. The satellite image showing land-fast ice in the fjord and thin ice–open water conditions in the polynya outside the fjord is from early March 2012. created some artificial flooding. A widely distributed snowice interface survey, however, showed that flooding was limited to only the area immediately surrounding the installed instruments. The same was the case for the Polynya site. 2.2 Analysis In the cold laboratory (−20 to −25◦C), corresponding sea ice cores were cut into vertical thick sections (10cm×6cm×1cm) and horizontal thick sections (6cm×6cm×1cm), then mounted onto slightly warmed glass plates and thinned to 1–3mm thickness using a microtome (Leica SM 2010R). Each section was then photographed (Nikon D70) using polarized filters to document ice texture. Subsequently, each thin section was inspected under a stereomicroscope (Leica M125 equipped with a Leica DFC 295 camera and Leica Application Suite ver. 4.0.0. software) to document the vertical and horizontal position of ikaite crystals in sea ice. To document the abundance and concentrations of ikaite crystals in sea ice, 20–90mg of sea ice were cut off, using a stainless steel knife, at three random places within each 5– 10cm sea ice section. These subsamples were weighed and placed onto a glass slide that rested on a chilled aluminum block with a 1cm central viewing hole, then brought into the 20◦C laboratory. There they were inspected intact under a microscope (Leica DMiL LED) under 100–400 magnification as they were also allowed to melt. A few seconds after the sea ice had melted the first image was taken (same camera and software as described above). This image was used to document the amount and concentration of ikaite crystals (further details given below). After 2–5min the second image was taken and compared with the first one. If crystals were dissolving, they were assumed to be ikaite. Three random samples, each covering 1.07mm2of the counting area, were imaged in this fashion. The area of the melted sea ice sample was determined after thawing to calculate the counted area to total area ratio. Ikaite crystals and other precipitates were observed to settle to the glass slide rapidly after ice crystal melt due to their high density. In total, three 20–90mg sea ice sub-samples were processed from each sea ice section in triplicates, resulting in 9 replicate images for each 5–10cm vertical sea ice section. The abundance and concentrations of crystals were calculated from the images using the software ImageJ (1.45s). Individual images were brightness/contrast adjusted prior to binary file conversion. A “close-function” routine then ensured that crystals were closed before “filling-holes” with black. An “analyze” routine was then applied to count the crystals and analyze their area relative to counting area. This ratio was multiplied by the area of the melted ice subsample. For concentration estimates of ikaite a cubic form was assumed for the mineral. Ikaite concentration in sea ice was calculated from its volume, density (1.78gcm−3), molar weight (208.18gmol−1), and weight of subsample and converted into μmolkg−1melted sea ice units. A sea ice core (entire core) from each site was kept at −20◦C for three weeks and brought to the x-ray laboratory at the Department of Geological Sciences at the University of Manitoba, Canada. There, 20–90mg subsamples of sea ice were cut randomly from each sea ice section (5– 10cm vertical sections) and mounted onto a cold glass slide resting on a chilled aluminum block containing a 1cm central viewing hole. The crystals were first examined with a polarized light microscope to assess their optical properties and then mounted for x-ray study using a stereo binocular microscope. Ikaite crystals were selected from each 10cm section of the sea ice cores from both ICE I and POLY I, dragged across the cold glass slide using a metal probe and immersed into a drop of special purpose sampling oil that restricted sublimation. Each crystal was then scooped up with a low x-ray scattering micro-loop and instantly transferred to the nitrogen cold stream (−10◦C) on the x-ray diffraction instrument with a magnetic coupling goniometer head. The www.the-cryosphere.net/7/707/2013/ The Cryosphere, 7, 707–718, 2013 65 PhD thesis by Dorte Haubjerg Søgaard 710 S. Rysgaard et al.: Ikaite crystal distribution in winter sea ice x-ray diffraction instrument consisted of a Bruker D8 threecircle diffractometer equipped with a rotating anode generator (MoKαX-radiation), multi-layer optics, APEX-II CCD detector, and an Oxford 700 Series liquid-N Cryostream. The intensities of more than 100 reflections were harvested from six frame series (each spanning 15◦in either ωor ϕ) collected to 60◦2θusing 0.6s per 1◦frame with a crystalto-detector distance of 5cm. In total, 12 crystals (one from all ice layers investigated from both ICE I and POLY I) were identified through successful indexing of observed xray diffraction maxima onto known characteristic unit cells. To determine TA and total dissolved inorganic carbon (TCO2)concentrations in sea ice, three sea ice cores were cut into 5–10cm sections and brought to the field laboratory. Here, the ice segment was placed immediately in a gas-tight laminated (Nylon, ethylene vinyl alcohol, and polyethylene) plastic bag (Hansen et al., 2000) fitted with a 50cm gastight Tygon tube and a valve for sampling. The weight of the bag containing the sea ice sample was recorded. Cold (1◦C) deionized water (25–50mL) of known weight and TA and TCO2concentration was added. The plastic bag was closed immediately and excess air and deionized water quickly removed through the valve and weighed. The weight of the deionized water accounted for <5% of the sea ice weight. This processed sea ice was subsequently melted, and the meltwater mixture transferred to a gas-tight vial (12ml Exetainer, Labco High Wycombe, UK). Any CaCO3crystals present in these ice core sections are expected to have dissolved during sample processing and, thus, be included in the measured TA and TCO2concentrations. Standard methods of analysis were used: TCO2concentrations were measured on a coulometer (Johnson et al., 1987), TA by potentiometric titration (Haraldsson et al., 1997), and gaseous CO2 by gas chromatography. Routine analysis of Certified Reference Materials (provided by A. G. Dickson, Scripps Institution of Oceanography) verified that TCO2and TA concentrations (n=3) could be analyzed within ±1μmolkg−1and ±4μmolkg−1, respectively. Bulk concentrations of TA and TCO2in the sea ice (Ci)were calculated as Ci=([CmWm− CaWa]/Wi), where Cmis the TA or TCO2concentration in the meltwater mixture, Wmis the weight of the meltwater mixture, Cais the TA or TCO2concentration in the deionized water, Wais the weight of the deionized water, and Wi is the weight of the sea ice (Rysgaard et al., 2008). Following the bulk determination of TCO2and TA, the bulk pCO2and pH (on the total scale) were computed using the temperature and salinity conditions in the field and a standard set of carbonate system equations, excluding nutrients, with the CO2SYS program of Lewis and Wallace (2012). We used the equilibrium constants of Mehrbach et al. (1973) refitted by Dickson and Millero (1987, 1989). In summary, triplicate cores were collected 18, 20 and 24 March for snow and ice thickness determination, ice temperatures and bulk ice salt concentrations. Measurements were performed on the same cores. Triplicate separate cores were sampled for determination of TCO2and TA concentrations. Ice texture, density and photo documentation of ikaite location in intact ice corers were performed on triplicate separate cores (ICE I, 17 March: POLY I, 20 March). Ikaite image analysis for concentration determination was done on three separate cores collected 18, 20 and 24 March. X-ray diffraction analyses were performed on a separate core collected 24 March. Samples for bulk salt, TA, TCO2, ikaite crystal abundance and concentration were processed immediately in the field laboratory. Crystals for ikaite determination on x-ray were kept frozen (−20◦C) until analysis a month later. Photo documentation showed that ikaite crystal morphology did not change due to storage. Thus, prolonged freezing period prior analysis should not affect the results obtained. However, it is important that preservation of TA, TCO2and quantification of ikaite is done in the field. These samplesshould notbe stored atlowtemperatures beforeanalysis as CaCO3could be produced during the storage. 2.3 FREZCHEM modeling The production of ikaite in the sea ice cores was modeled by FREZCHEM (version 10), an equilibrium chemical thermodynamic model parameterized for concentrated solutions (up to 20molkg−1(H2O)) and sub-zero temperatures (to −70◦C) (Marion et al., 2010). The model uses the Pitzer approach correcting for activity coefficients of solutes in concentrated solutions. Our calculation was done by following the freezing process of seawater with the same chemical composition as the local seawater under the local pCO2values; the thermodynamic constants used were the default values provided with the model. It should be noted that FREZCHEM modeling is based on the assumption that chemical species in the sea ice environment (ice, brine, and air) have reached thermodynamic equilibrium, and that most of the thermodynamic constants used in the model were extrapolated to low temperatures rather than being directly determined experimentally. Nevertheless, the model has shown promising applications in exploring cold geochemical processes associated with seawater freezing among many others (Marion et al., 1999, 2010). 3 Results Sea ice covered the fjord on our arrival, but there was a polynya outside the fjord with a distinct ice edge running across the fjord between Wollaston Forland and Clavering Island (Fig. 1). Several freezing and opening incidents were observed in this area from satellite images prior to our arrival; however, due to low temperatures of −20◦Cto−36◦C and calm conditions, the polynya began to re-freeze prior to our sampling. Due to the insulating effect of the thick (70cm) snow cover at ICE I, our land-fast station in the fjord, sea ice surface temperature was relatively warm, −10◦C, The Cryosphere, 7, 707–718, 2013 www.the-cryosphere.net/7/707/2013/ 66 PhD thesis by Dorte Haubjerg Søgaard S. Rysgaard et al.: Ikaite crystal distribution in winter sea ice 711 -100 -80 -60 -40 -20 0 Sea ice, cm -12 -8 -4 0 Temperature, ºC 1210864 Bulk salinity -100 -80 -60 -40 -20 0 Sea ice, cm -12 -8 -4 0 Temperature, ºC 1210864 Bulk salinity AB CD -100 -80 -60 -40 -20 0 0.300.250.200.150.100.050.00 Brine volume (v/v) 2001601208040 Brine salinity -100 -80 -60 -40 -20 0 0.300.250.200.150.100.050.00 Brine volume (v/v) 2001601208040 Brine salinity Fig. 2. Vertical profiles of sea ice features. (A) Temperature (-o-) and bulk salinity (-•-) and (B) brine volume (-o-) and brine salinity (-•-) at ICE I. (C) Temperature (-o-) and bulk salinity (-•-) and (D) brine volume (-o-) and brine salinity (-•-) at POLY I. Vertical dotted line represents the brine volume where sea ice becomes permeable. with a gradient to −2◦C towards the sea ice–water interface (Fig. 2a). Bulk salinities ranged from 10–12 in the top layers to 4 at the bottom. Calculated brine volumes ranged from less that 5% in surface layers to 12% near the bottom (Fig. 2b); brine salinities, from 150 in the surface sea ice to 33 near the water column. At POLY I, our new-ice station in the polynya where snow cover was thinner (17cm), surface sea ice temperature was only −5◦C (Fig. 2c) due to the rapid freezing with concurrent heat release and proximity to the water column (thin ice of 15–30cm). Bulk salinities ranged from 10 in surface ice layers to 7 in the lower ice layers (Fig. 2c). Given high bulk salinities and temperatures, brine volumes ranged from 10% in the top layers to 20% in the lower ice layers; brine salinities were lower at ICE I, ranging from 78 at the surface to 33 near the water column (Fig. 2d). The upper 35cm of sea ice at ICE I was composed of polygonal granular ice, formed through perculation and refreezing of brine and seawater into snow, i.e. snow ice (Fig. 3a). The snow ice formation was likely promoted by negative freeboard. The fact that we do not observe flooding is probably due to low temperatures (brine or seawater quickly refreezes in the cold snow). Daily images with automatic camera systems (MarinBasis Program, c/o Greenland Institute of Natural Resources) show that sea ice started to form locally outside the fjord in early October, and that those ice floes drifted into the fjord and consolidated with local ice to form a uniform ice cover that persisted through our study. Thus, the top layers of ice at ICE I may have been produced outside the fjord. The ice layer from 35–112cm consisted of columnar sea ice (Fig. 3d). Microscopic examination of different vertical and horizontal ice thin sections showed the presence of ikaite crystals throughout the ice column (Fig. 3b, c and e, f). Ikaite crystals were located in the interstices between the ice platelets. The sea ice at POLY I was less than one week old when first sampled. The upper 5cm of the ice consisted of orbicular granular ice crystals, followed by transitional granular/columnar texture from 5 to 12cm (Fig. 4a). This uppermost layer closely resembles the disc-like granular ice observed in nilas (Ehn et al., 2007) and may be related to freezing of brine expulsed to the sea ice surface. The transition into mainly columnar-like sea ice occurred at around 10– 12cm from the surface and continued to the sea ice–water interface (29cm); however, the disorderly structure implies intrusion of frazil ice and platelet ice forms, and thus supercooling at the ice–ocean interface was a significant factor in determining the ice structure. Similarly to ICE I, microscopic examination of thin ice sections from POLY I revealed the presence of ikaite crystals throughout the ice column (Fig. 4b, c and e, f). Ikaite crystals were again observed primarily in the interstices between the ice platelets. Ikaite crystals become easily visible when the sea ice melts. As an example from POLY 1, 19 crystals were observed a few seconds after melting 50mg of randomly subsampled sea ice (10–20cm section; Fig. 5a and b). Allowing the crystals to dissolve for a few minutes before taking another image allowed us to identify ikaite crystals (as the ones that had dissolved; Fig. 5c). In this case, the crystal area covered 0.48% of the counting area. At ICE I, the number of ikaite crystal per kg of melted ice ranged from ∼25×106kg−1in the upper layers to ∼1×106kg−1near the ice–water interface (Fig. 6a). At POLY I, similar ikaite abundances were observed in upper ice layers, whereas abundances near the water column reached ∼7×106kg−1(Fig. 6b). The molar concentration of ikaite perkg melted ice at ICE I decreased with depth from surface values of 900μmolkg−1to 100μmolkg−1near the ice–water interface. At POLY I, the highest concentrations (700μmolkg−1)were observed at 5–10cm from the ice surface, decreasing to ∼200μmolkg−1near the water column. The crystals (a few μm to 700μm in size) observed in the sea ice were highly transparent with a rhombic morphology and showed uniform extinction under cross-polarized www.the-cryosphere.net/7/707/2013/ The Cryosphere, 7, 707–718, 2013 67 PhD thesis by Dorte Haubjerg Søgaard 712 S. Rysgaard et al.: Ikaite crystal distribution in winter sea ice 1 cm 10-20 cm section 250 μm 250 μm1 cm 49-59 cm section A B D E 100 μm 100 μm C F Fig. 3. Images of sea ice with ikaite crystals, from ICE I. (A, D) Sea ice texture (polarized light); (B, E) microscopic images of sea ice. Yellow arrows point to ice crystal borders, blue arrows to brine pockets, green arrows to air bubbles and red arrows to ikaite crystals. (C, F) Ikaite crystals at higher magnification. (A),(B) and (C) from 10–20cm section; (D),(E) and (F) from 49–59cm section. light, suggesting that they were simple single crystals. All x-ray reflections fitted well to a monoclinic C-centered cell with refined cell parameters shown in Table 1. From the general shape, optical properties and unit-cell determination, the crystals examined were ikaite (Hesse and K¨ uppers, 1983). The crystals identified as ikaite had a very distinct 250 μm 100 μm 250 μm 100 μm 1 cm 10-20 cm section 1 cm 0-10 cm section A B C D E F Fig. 4. Images of sea ice with ikaite crystals, from POLY I. (A, D) Sea ice texture (polarized light); (B, E) microscopic image of sea ice. Yellow arrows point to ice crystal boarders, blue arrows to brine pockets, and red arrows to ikaite crystals. (C, F) Ikaite crystals at higher magnification. (A),(B)and (C) from 0–10cm section; (D), (E) and (F) from 10–20cm section. morphology, and were easily recognized with two significant variations: the more common thicker rhombs (Fig. 7a) and rather rare thinner plates (Fig. 7b). Whereas ikaite crystals in intact sea ice sometimes were assembled in aggregates such as the ones illustrated in Fig. 4e and f, they consisted mostly of isolated rhombic forms and thin plates as observed under The Cryosphere, 7, 707–718, 2013 www.the-cryosphere.net/7/707/2013/ 68 PhD thesis by Dorte Haubjerg Søgaard S. Rysgaard et al.: Ikaite crystal distribution in winter sea ice 713 100 μm 100 μm A 100 μm B C Fig. 5. Microscopic images of ikaite crystals (A) a few seconds after melting 50mg sea ice (10–20cm section) from POLY I. Image represents a very small fraction (2μg) of the sample. (B) Software (ImageJ 1.45s) processing of image A to find the number (19) and area (0.48% of counting area) of the crystals. (C) Image taken after 2min showing that crystals are dissolving. the microscope immediately after ice platelets had melted (Fig. 5). Surface TA concentrations of 600–800μmolkg−1melted sea ice were measured at ICE I, with decreasing concentrations to 380μmolkg−1melted sea ice in ice layers close to the water column (Fig. 8a). TCO2values at ICE I had similar vertical distribution with lower concentrations. At POLY I site, TA values were measured at ∼800μmolkg−1melted sea ice near the surface, and decreased to ∼500μmolkg−1 melted sea ice near the water column. As at ICE I, the vertical TCO2concentrations at POLY I were similar to TA, but with lower values. 40x106 3020100 Ikaite crystal numbers/kg -100 -80 -60 -40 -20 0 Sea ice, cm 160012008004000 Ikaite crystal conc., μmol/kg 40x106 3020100 Ikaite crystal numbers/kg -100 -80 -60 -40 -20 0 160012008004000 Ikaite crystal conc., μmol/kg AB Fig. 6. Vertical distribution of ikaite crystals determined from image analysis. Abundance of crystals (-o-) and concentration of ikaite (- -•--)atICEI(A) and POLY I (B). 4 Discussion 4.1 Spatial and temporal variability of ikaite occurrence and concentration Ikaite concentrations from this study are higher than those reported previously: 10 times higher than those measured in spring sea ice from Antarctica (Dieckmann et al., 2008), and 4 times higher than in surface summer ice from Fram Strait (160–240μmolkg−1melted sea ice; Rysgaard et al., 2012). The differences may be explained in part by differences in quantification procedure, as our study is unique in employing immediate analysis in the field without prolonged melting. The higher values we report may also reflect real differences between sites and seasons, as we present results for winter sea ice, while other studies were conducted in spring and summer with melt already apparent. As a result, a fraction of ikaite crystals in the previous studies may already have been dissolved due to ice warming and melting or lost via brine drainage. In addition, ikaite crystals were observed in the week-old POLY I sea ice and even within 1 hour in frost flowers and thin ice in an artificially opened lead (data to be presented elsewhere). This observation indicates dynamic conditions of ikaite formation even on short timescales. Understanding the dynamics of those processes is an important objective for future studies. Here, we note that higher concentrations of ikaite in surface sea ice are predicted by the FREZCHEM model (Marion et al., 2010). Assuming that a standard seawater (S=35, [Na+]=0.4861, [K+]=0.01058, [Ca2+]=0.01065, [Mg2+]=0.05475, [Cl−]=0.56664, [SO2− 4]=0.02927, [HCO− 3]=0.0023; ions concentration unit: molekg−1water) freezes in an open system with pCO2=320μatm, the FREZCHEM model predicts an ikaite concentration of up to 620μmolkg−1sea ice in the cold surface layer of ICE I, decreasing exponentially downwards (Fig. 9). Both the concentration range www.the-cryosphere.net/7/707/2013/ The Cryosphere, 7, 707–718, 2013 69 PhD thesis by Dorte Haubjerg Søgaard 714 S. Rysgaard et al.: Ikaite crystal distribution in winter sea ice Table 1. X-ray diffraction data. Refined unit-cell parameters for ikaite crystals identified by x-ray diffraction analysis. ( )=Standard deviation, R=rhombs, TP=thin plate. ICE I Section cm a( ˚ A) b( ˚ A) c( ˚ A) β(◦)V( ˚ A3) 0–10 R 8.808(2) 8.313(2) 11.031(2) 110.59(1) 756.1(8) 10–20 R 8.820(2) 8.330(2) 11.050(3) 110.57(2) 761.7(4) 20–30 TP 8.823(3) 8.326(3) 11.049(4) 110.64(2) 759.6(7) 30–40 R 8.813(2) 8.312(2) 11.034(3) 110.60(1) 756.7(4) 40–50 R 8.817(3) 8.312(2) 11.027(3) 110.58(2) 756.6(5) 50–60 R 8.812(2) 8.311(1) 11.040(2) 110.58(1) 756.9(6) 60–70 R 8.831(3) 8.320(2) 11.047(3) 110.55(2) 760.1(6) 70–80 R 8.812(2) 8.318(2) 11.031(3) 110.56(2) 757.0(8) 80–90 R 8.819(2) 8.315(2) 11.025(3) 110.57(2) 758.3(5) 90–100 TP 8.820(2) 8.323(2) 11.049(2) 110.64(1) 759.2(5) POLY I Section cm a( ˚ A) b( ˚ A) c( ˚ A) β(◦)V( ˚ A3) 0–10 TP 8.816(3) 8.333(2) 11.043(3) 110.68(2) 759.1(6) 10–20 TP 8.810(1) 8.320(1) 11.033(1) 110.58(1) 757.1(2) and distribution pattern agreed well with the empirical data at ICE I. Although the FREZCHEM modeling assumes that the system reaches thermodynamic equilibrium and is always open to a constant pCO2, assumptions that are not fulfilled under natural conditions, the modeling results nevertheless support the observation that ikaite concentration increases with decreasing temperature. Seasonally variable ikaite concentration, with highest values in winter, is thus expected. It is a key point as to exactly where the crystals are located. If they are in the brine channels then they can potentially move with the circulation of brine as the temperatures change internally in the ice. If they are isolated from larger brine networks and are located at the interstices then they may remain trapped in the ice as convection occurs. This will make a big difference on the exchange through winter and well into spring. Our images document that ikaite crystals are located between the interstices of the sea ice matrix between the pure ice platelets. As they are particles they can be trapped between the small interstitial pore spaces and therefore retained in the ice. In contrast, solutes and gases (CO2), as well as organic particles including microorganisms (Junge et al., 2001; Krembs et al., 2011), can be transported within the brine system. It was possible to see brine motion in the microscope as small particles and air bubbles moved between the interstices of ice platelets. Increasing the temperature by a few degrees significantly accelerated the transport velocity. The TA: bulk salinity ratio in sea ice was 84±4 (ICE I) and 78±0.8 (POLYI)as comparedwith the watercolumn 67±3 (ICE I) and 61±0.2 (POLY I). Thus, the higher TA-S ratio in sea ice than in seawater shows that CaCO3release adds a 20 μm 20 μm A B Fig. 7. Two most common forms of ikaite in freezing sea ice. (A) rhombs, (B) thin plates. -100 -80 -60 -40 -20 0 10008006004002000 TA & TCO2 μmol/kg -100 -80 -60 -40 -20 0 Sea ice, cm 10008006004002000 TA & TCO2 μmol/kg AB Fig. 8. Vertical profiles of concentration of total alkalinity (- -o- -) and dissolved inorganic carbon (-•-) in (A) at ICE I and (B) at POLY I. further alkalinity contribution to the simple melt of ice. These observations confirm previous hypotheses (Rysgaard et al., 2007, 2009, 2011) that ikaite crystals are trapped within the sea ice matrix, whereas CO2released through ikaite production (Eq. 1) and dissolved within the brine can be lost from the sea ice. As a result, CaCO3stores twice as much TA as TCO2, hence TA of the meltwater increases relative to TCO2 in sea ice. When ikaite crystals dissolve during sea ice melt, surface water pCO2will decrease. This is important as low The Cryosphere, 7, 707–718, 2013 www.the-cryosphere.net/7/707/2013/ 70 PhD thesis by Dorte Haubjerg Søgaard S. Rysgaard et al.: Ikaite crystal distribution in winter sea ice 715 -100 -80 -60 -40 -20 0 Sea ice, cm 160012008004000 Ikaite concentration μmol/kg Fig. 9. Vertical profiles of ikaite concentration. Measured (-•-) and FREZCHEM calculated (-o-) at ICE I. pCO2values in surface waters will lead to a large CO2flux from the atmosphere into the ocean. Bulk TA concentrations in surface ice layers (including ikaite crystals) were within the same range as ikaite concentrations, implying that most of TA is present in the crystal form of ikaite and, thus, trapped within the surface sea ice matrix. In contrast, bulk TA concentrations were higher than ikaite crystal concentrations in the internal and bottom layer of the sea ice at both stations, implying that not all TA in the lower ice layers originate from ikaite crystals. One explanation for this finding invokes dissolution or reduced growth rate of ikaite in interior ice layers due to exposure to excess CO2originating from cold upper ice layers, where elevated brine concentrations of Ca2+and HCO− 3are higher due to lower brine volumes. The CO2released in upper ice could be transported to interior ice layers by downward brine drainage. Low pH conditions in interior ice layers have recently been reported for experimental sea ice (Hare et al., 2013). Here, vertical pH profiles for bulk ice, as measured at near-freezing temperatures, revealed a consistent C-shaped pattern during columnar ice growth, with the highest pH values (>9) in both the exterior (top and bottom) ice sections and lowest pH (∼7) in the interior ice sections (Hare et al., 2013). Calculating the verticalpH profile at ICE I, using temperature and bulk salinity (Fig. 2) and TA and TCO2conditions (Fig. 8) from our winter ice study, yielded a similar C-shaped pH profile with high pH (>9) in surface and bottom ice layers, and lower pH (∼8) in interior layers. At POLY I, a C-shaped pH profile was also estimated, although the pH values in exterior layers were slightly lower (∼8.5). The sum of these findings suggests that downward transport of pH equivalents could be responsible for dissolving ikaite in the interior ice layers. Another mechanism that could affect the dissolution/precipitation dynamics of trapped ikaite crystals involves convective solutes (Worster and Wettlaufer, 1997) ensuring contact between the interior brine system and the underlying water column. CO2-enriched brine can exchange with seawater via gravity drainage (Notz and Worster, 2009) if the brine volume is above 5% to allow vertical ice permeability (Cox and Weeks, 1975; Notz and Worster, 2009). In this study, brine volume fractions were above 5% in the lower 50cm of sea ice at ICE I, and throughout the ice column at POLY I. Thus, the increase in pH in the sea ice layers close to the water column could be caused by replenishment of brine with surface seawater (pH 8.1–8.3). 4.2 Role of ikaite in seawater CO2system and gas exchange The observation that ikaite crystals are trapped within the sea ice matrix, while CO2dissolved in the brine through ikaite production (Eq. 1) can be mobile (lost from the ice with brine), means that ikaite crystal formation increases the amount of CO2available for export beyond that attributed solely to the solubility effect. The implication is that, in an open system, TA is preferentially stored in the sea ice as ikaite, raising the buffering capacity of sea ice (and surface water) upon melting and subsequent crystal dissolution. With trapped ikaite crystals, ice melt will therefore lead to both lower surface water salinity and pCO2. As the low pCO2 meltwater remains at the ocean surface due to density stratification gradient, CO2flux from the atmosphere to the surface will be enhanced (Rysgaard et al., 2012). Based on data from this study, the melting of sea ice (salinity from Fig. 2, TA and TCO2from Fig. 8) at 0◦C and dissolution of observed concentrations of ikaite (Fig. 6) would result in meltwater with a pCO2of <15μatm at both sites. This value is far below atmospheric values of 390μatm and surface water concentrations of 315μatm measured in this study. Hence, the meltwater can increase the air–sea CO2uptake. During ice growth, pCO2in the brine system will increase and reduce pH in interior ice layers. In the surface ice layer, released CO2may escape to the atmosphere or be transported to deeper ice layers by downward brine drainage. Few measurements of air–sea CO2fluxes have been reported for winter conditions. Geilfus et al. (2012) detected no CO2release for ice surface temperatures below −10◦C, instead observing a small negative flux (into the sea ice) of 0.23mmolm−2d−1over sea ice in the Amundsen Gulf, Beaufort Sea. Miller et al. (2011) measured fluctuating CO2 fluxes over sea ice with strong downward fluxes in February in the Southern Beaufort Sea. Sejr et al. (2011) observed that 99% of TCO2in newly forming ice over drilled holes www.the-cryosphere.net/7/707/2013/ The Cryosphere, 7, 707–718, 2013 71 PhD thesis by Dorte Haubjerg Søgaard 716 S. Rysgaard et al.: Ikaite crystal distribution in winter sea ice in meter thick sea ice was rejected to the underlying seawater in Young Sound, Greenland. The suggestion that most of the CO2released through ikaite crystal formation will sink towards the seawater in dense brine is consistent with these several findings. The fate of CO 2expelled from the sea ice to seawater remains unclear. Dense brine production in the polynya region (Anderson et al., 2004) may provide a mechanism to deliver CO2below the mixed layer, making ikaite production in sea ice a “carbon pump” that removes CO2from the surface ocean to deeper water layers (Rysgaard et al., 2009, 2011). Low-density ice meltwater remaining at the surface will facilitate atmospheric CO2deposition as a result of ikaite dissolution. An air–sea CO2flux of −10.6mmolm−2d−1has been reported during spring and summer for the region previously (Rysgaard et al., 2012). Geilfus et al. (2012) calculated, based on the carbon chemistry in the sea ice brine in equilibrium partitioning with the atmosphere, that melting of a 1.3m thick sea ice cover within one month in the Beaufort Sea could lead to CO2fluxes ranging from −1.2 to −3.1mmolm−2d−1, which are comparable to CO2fluxes measured over melt ponds. At ICE I, we calculated the potential influence of melting the entire ice cover into a 20m thick mixed layer (typical for summer conditions at this location) on the CO2flux in the region, using the measured ice carbon chemistry (salinity of 6.5, TA of 516μmolkg−1,TCO2of 406μmolkg−1,andaverage temperature of 0◦C) and the initial mixed layer characteristics (average temperature of 0◦C, salinity of 31.7, TA of 2276μmolkg−1,andTCO2of 2101μmolkg−1). The resultant conditions in a 20m mixed layer (temperature of 0◦C, salinity of 30.4, TA of 2184μmolkg−1,andTCO2of 2013μmolkg−1)would cause a 14μatm decrease in pCO2. Assuming the melt occurs over one month, the resultant air–sea CO2flux to return to pre-melt conditions would be −5.9mmolm−2d−1, which falls within the range reported previously. This calculation is based on a single melt event and does not account for the numerous cycles of sea ice growth and melt characteristic of polynya systems (Tamura and Ohshima, 2011; Drucker et al., 2011). The polynya formation at POLY I is predominantly governed by mechanical forcing caused by northerly gales; it has been classified as a winddriven shelf water system (Pedersen et al., 2010), where sea ice formation is continuous and rejection of CO2to deeper water layer with dense brine occurs (Anderson et al., 2004). Ikaite crystals trapped in the forming sea ice will be exported with the ice to melt elsewhere. Such polynya systems are thus likely to export CO2to depth effectively. Based on results presented here, enhanced ice production in winter polynyas would add considerable amounts of TA to the surface waters in the form of ikaite crystals from sea ice, lowering surface water pCO2upon ice melt and crystal dissolution, and increasing the potential for seawater uptake of CO2. An interesting observation in the polynya region we have studied (Sejr et al., 2011; Papakyriakou et al., 2013) is that the pCO2levels in the water column are very low, gradually increasing with depth from surface values of 315μatm to 360μatm at 80m. During the present study, the average pCO2concentration of the upper 20m water column was 335μatm compared to 390μatm in the atmosphere. As melting 1m of sea ice will reduce pCO2levels by 14μatm in a 20m water column according to the calculations above, ∼4m of sea ice would need to melt locally to explain the low pCO2concentrations in the water column. In polynya areas the sea ice production is usually much greater than indicated by the annual sea ice thickness due to the continued production of ice (McLaren, 2006). The local ice production at POLY I is thus likely responsible for much more larger ice growth than the April–May ice thickness of 1.4– 1.6m usually observed at ICE I (Rysgaard and Glud, 2007). Furthermore, the study site is located on the NE Greenland Sea shelf where large amounts of sea ice exported from the Arctic Ocean through Fram Strait subsequently melt during southward transport toward the Denmark Strait (Vinje, 2001). Sea ice containing ikaite crystals as observed in the present study may well explain a large part of the low pCO2 levels in the upper part of the water column due to melting of sea ice from previous summer/autumn in the area. Biological CO2fixation will also contribute to the atmospheric drawdown, but constraining this factor is beyond the scope of the present study. The current work nevertheless supports previous model calculations from the area estimating that melting of sea ice exported from the Arctic Ocean into the East Greenland current and the Nordic Seas greatly increases the seasonaland regionalCO2uptakein the area (Rysgaard etal., 2009). More work is required to determine how applicable our results are to other regions of the Arctic (or Antarctic), given the variable nature of CaCO3among the few available ikaite studies (above references) and the seasonal nature of pCO2in ice-free Arctic systems (Mucci et al., 2010; Cai et al., 2010). 5 Conclusions We report unique observations of ikaite in unmelted ice and vertical profiles of ikaite abundance and concentration in sea ice for the crucial season of winter. Ikaite crystals, ranging in size from a few μm to 700μm, were observed to concentrate in the interstices between the ice platelets in both granular and columnar sea ice. Their concentration decreased with depth from surface-ice values of 700–900μmolkg−1ice (∼25×106crystalskg−1)to values of 100–200μmolkg−1ice (1–7×106crystalskg−1)near the ice–water interface, all of which are much higher (4–10 times) than those reported in the few previous studies. Direct measurements of TA in surface layers fell within the same range as ikaite concentration, whereas TA concentrations in The Cryosphere, 7, 707–718, 2013 www.the-cryosphere.net/7/707/2013/ 78 PhD thesis by Dorte Haubjerg Søgaard Our objectives are to investigate the physical, radiative and thermal environment of frost fl owers on new sea ice grown in a winter polynya off the NE coast of Greenland. We seek to understand the climate forcing on the formation of these fl owers and in particular to examine the processes that create and drive their growth and deterioration. We then examine the potential role of frost fl owers in geochemical exchange across the OSA interface and as a microbial habitat. More specifi - cally we address the following interrelated research questions: 1. What are the climatic and geophysical forcing conditions associated with frost fl ower formation and development? (Climate Forcing) 2. How did the above conditions affect vapor diffusion processes and temperatures across the young ice surface and can we determine if atmospheric deposition or sea ice sublimation/evaporation or brine wicking dominated frost fl ower formation? (Frost Flower Formation) 3. How does the concentration of salt in the ice surface and frost fl owers affect the carbonate chemistry of the sea ice and the exchange of CO2 across the OSA interface? (Gas Exchange) 4. Can bacterial measurements across the OSA interface over time help to inform the frost fl ower formation process and the suitability of these unique physical and biogeochemical environments as habitats for microbes? (Microbial Habitat) Methods A multinational, multidisciplinary fi eld program was coordinated through the University of Manitoba’s Canada Excellence Research Chair (CERC) at the Danish/Greenlandic fi eld station, Daneborg. The station is located in the Young Sound fjord on the NE coast of Greenland (Figure 1). General description of the Daneborg fi eld site and the winter carbonate chemistry cycle in the fjord are found elsewhere [Rysgaard and Glud, 2007; Rysgaard et al., 2013]. The thin-ice station, POLY I (74°13.905’N 20°07.701’W, 2930 cm thick on 22 March, snow-covered with varying thickness), was situated in a recurrent winter polynya region about 3 km off the landfast ice edge. An area of ~5 × 7 m was opened near POLY I at 16:00 GMT on 22 March to expose the ocean to the atmosphere (hereinafter referred to as the ‘pond’ site). The opening of the pond was done using a hand-held ice saw by cutting smaller segments that then were pushed to the side underneath the ice cover. A time-lapse camera was installed at the pond site to document the development of frost fl owers as the ice formed in situ. Half of the pond was reopened on 24 March at 15:00 GMT; i.e., after about 47 h of the initial pond opening. At this time, the initial ice was ~12 cm thick. The recurrent polynya at this location will occur as open water (as evidenced by satellite imagery just prior to our arrival) or with a young ice cover (like we experienced); frost fl owers are known to occur regularly on this polynya ice (Rysgaard and Glud, 2007). Components of the surface energy balance were acquired using purpose-built meteorological stations located in proximity to the pond site over the period spanning this experiment. Wind speed and direction were measured at the heights of 3.8 m and 3.1 m using sonic anemometers (Gill® Windmaster Pro and Metek®, model uSonic-3). Incoming and refl ected shortwave, and incoming and emitted longwave radiation were measured at the station (over a snow surface) using a four component net radiometer (Kipp & Zonen®, model CNR4) at a height of 1.5 m. Air temperature and relative humidity were measured using a HMP45C probe (Vaisala®) installed in radiation shields at a height of 1.6 m. Figure 1. Daneborg fi eld station at the NE Greenland coast (A) showing the location of the Young Sound fjord (B) and the newly formed ice in the polynya at the mouth of the fjord where the frost fl ower ‘pond’ was constructed (C). 79 PhD thesis by Dorte Haubjerg Søgaard Downwelling incident scalar irradiance and transmitted scalar irradiance over 400–700 nm wavelength range was measured at 1-min intervals at the pond site using MDS-L photosynthetically available radiation (PAR) sensors (Alec Electronics Co. Ltd). The surface reference PAR sensor was shielded from the upwelling component of the radiation and installed next to the pond. Two other PAR sensors were installed at the airwater interface and at 30-cm depth in the pond by attaching them to a string hanging from a horizontal aluminum pole that extended across the northern pond corner (Figure 1C). To fi ll gaps between measured ice thicknesses (H) and surface temperatures (Tsurface), we used the hourly averaged air temperatures (Tair) from the meteorological station as input in an analytical ice growth model [Maykut 1986]: –ρice L = kice dH dt Tsurface–Tsw H+ Fw , (1) where ρice = 920 kg m–3 is the assumed density of sea ice which was kept constant, L = 333.5 J g–1 the latent heat of fusion, kice = 1.8465 J m–1 s–1 K–1 thermal conductivity of sea ice with a salinity of 8 and temperature of –5°C, Tsw = –1.7°C the temperature of the underlying seawater, Fw = 0 W m–2 is ocean heat fl ux, and Tsurface =kice Tsw + ct Tair H kice + ct H (2) The calculation of Tsurface relied on a surface-to-air heat transfer coeffi cient Ct, which was found by matching to observed ice thicknesses and surface temperatures. The best match to observations were obtained by keeping Ct at 140 J cm–1 day–1 K–1 for the fi rst 7 cm of ice growth and then reducing it to 110 J cm–1 day–1 K–1 for the remainder. These values are notably smaller than the Ct = 209 J cm–1 day–1 K–1 derived by Maykut [1986], refl ecting the large temperature difference between the warm ice surface and the atmosphere in this thin ice environment. The upwelling longwave radiation LWu was not measured above the pond ice but calculated from Tsurface (for a bare frost fl ower free surface) using the Stefan-Boltzmann law with an emissivity of 0.985. Surface and interior brine salinities were then estimated assuming a linear temperature profi le from Tsurface to Tsw and using the equation for the freezing point of seawater following Fofonoff and Millard [UNESCO 1983]. Data on the Infrared Temperature (IR) of the ice and frost fl ower surfaces were collected with a FLIR systems SC660 thermal camera (Wilsonville, OR, USA). The IR camera uses an uncooled microbolometer over the spectral range of 7.5 to 13.0 μm. Thermal images were stored as calibrated 32-bit fl oating point data over a 640 by 480 image plane. Calibration of the FLIR was conducted with an external black body and using an internal camera calibration system. System specifi cations were verifi ed through a series of calibration tests conducted daily. The system was capable of an average ±0.1°C precision over the range of thermal conditions encountered; absolute calibration was not tested but FLIR indicates it to be < 1%. Additional measurements of the bare ice surface temperature were taken with a handheld digital thermometer (Traceable, model 4000, Control Company, USA). Throughout this manuscript we discuss the effects of the brine skim but sampled the ‘surface slush layer’, which contains the brine and the uppermost ice grains of the young ice, or the lowermost grains of the frost fl ower base, or potentially some snow that might have settled on top of the brine skim. Brine skim is a liquid with both its salinity and temperature controlled by the fact that it has to remain above its freezing point to exist as a liquid, while the surface slush additionally contains (salt-free) ice crystals and possibly precipitated salts. Our results show a signifi cant difference between the salinity of the surface brine skim (calculated) versus the bulk salinity of the slush layer. Frost fl ower and surface slush layer samples for salinity and δ18O analysis were collected with a sharp metal spatula, put into plastic bags, and melted at room temperature prior to analysis. Samples of sea ice brine for salinity and δ18O were collected from the top part of the ice by scraping an approximate 2-cm deep hole in the surface after the removal of frost fl owers and the surface slush layer, allowing the interior sea ice brine to accumulate for a few minutes, then collecting it with a plastic syringe. Sea ice was sampled with a 9-cm diameter ice corer (Mark II coring system, Kovacs Enterprises, Lebanon, USA). After extraction, ice cores were imaged thermally using the aforementioned FLIR camera, cut into layers, placed in tightly closed containers, and returned to the laboratory to melt at room temperature. The salinity of the melted frost fl owers, surface slush layer, sea ice, and brine samples was calculated from conductivity and temperature using a HACH SENSION5 portable conductivity meter (Hach, Loveland, US A (± 0.01)) calibrated against a 15N KCl solution at 20°C. Samples for oxygen isotope composition were transferred into glass vials tightly capped with polyseal closures and parafi lm. Analysis was performed on a Picarro Isotopic Water Analyzer, L2120-I (Picarro, Sunnyvale, USA) equipped with a PAL autosampler (Leap Technologies, Carrboro, USA). Details of the method can be found elsewhere [e.g., Versteegh et al., 2012]. Results are expressed in standard δ18O notation with the V-SMOW standard as a reference value. Agreement between triple consecutive injections of the same sample was within ± 0.1 ‰. The δ18O signal of frost fl owers of atmospheric origin was assumed to be that of freshly fallen snow; the δ18O signature of frost fl owers of brine origin was calculated from δ18O measured in brine using a fractionation value of +2.6 [Macdonald et al., 1995]. In the cold laboratory (–25 to –20°C), corresponding sea ice cores were cut into vertical sections (10 × 6 × 1 cm) and horizontal sections (6 × 6 × 1 cm), which then were mounted onto slightly warmed glass plates, cooled until frozen onto the plates, and thinned to 1–2 mm thickness using a microtome (Leica® SM 2010R) and a wood plane [e.g., Ehn et al., 2007]. Each of these, so called thin sections, was then photographed 80 PhD thesis by Dorte Haubjerg Søgaard (Nikon® D70) between cross-polarized fi lters to document ice texture. Subsequently, each thin section was inspected (in the fi eld) under a stereomicroscope (Leica® M125 equipped with a Leica® DFC 295 camera and Leica® Application Suite ver. 4.0.0. software) to document the vertical and horizontal position of ikaite crystals in sea ice. Samples of ikaite from the pond site were kept at –20°C for three weeks and brought to the x-ray laboratory at the Department of Geological Sciences at the University of Manitoba, Canada. There, subsamples of sea ice and frost fl owers were mounted onto a cold glass slide resting on a chilled aluminum block containing a 1-cm central viewing hole. The crystals were fi rst examined with a polarized light microscope to assess their optical properties and then mounted for x-ray study using a stereo binocular microscope. The x-ray diffraction instrument consisted of a Bruker D8 three-circle diffractometer equipped with a rotating anode generator (MoKα X-radiation), multi-layer optics, APEX-II CCD detector, and an Oxford 700 Series liquid-N Cryostream. The intensities of more than 100 refl ections were harvested from six frame series (each spanning 15° in either ω or φ) collected to 60° 2θ using 0.6s per 1° frame with a crystalto-detector distance of 5 cm. Further details on the ikaite sampling are provided elsewhere [Rysgaard et al., 2013]. The surface diffusive fl ux of CO2 associated with the re-freezing pond was sampled both in the presence and absence of frost fl owers using an automated chamber fl ux system (LICOR®, model LI-8100) equipped with a 20-cm (diameter) survey chamber. As part of the post-processing procedure, the CO2 concentration time series associated with each sample was screened, after which the fl uxes were calculated using the LI-8100A data analysis software. Frost fl owers for microbial analyses were removed from the pond site into sterile 1-L plastic bags using an ethanol-rinsed spatula. A second scraping over the same surface area yielded the corresponding, operationally defi ned brine skim; i.e., the surface slush layer. Samples of sea ice were also collected, as described above, along with samples of seawater and snow from the surrounding area. Samples of frost fl owers, the underlying surface slush layer, and snow were melted directly over the shortest period possible (always < 12 h, with sample temperature remaining at ≤ 0°C), while sea ice samples were melted into sterile 0.2-μm fi ltered brine according to the isohaline approach described by Ewert et al. [2013]. Immediately upon melting, samples were fi xed with 0.2 μm-fi ltered formaldehyde to a fi nal concentration of 2% and stored in the cold and dark until total bacterial (total prokaryotic) abundance was determined using epifl uorescence microscopy, as in Bowman and Deming [2010]; virus-like particles (VLP) were enumerated on a subset of samples, according to Wells and Deming [2006]. Particulate and dissolved extracellular polysaccharide substances (pEPS and dEPS) were quantifi ed using the phenol sulfuric acid assay, as in Krembs et al. [2011] and Ewert et al. [2013]. Salinities of samples used for these bacterial and EPS analyses were determined by refractometer. To determine the dominant members of the bacterial community, DNA was extracted from the different sample types for amplifi cation and sequencing of the 16S rRNA gene using the phenol-chloroform method (as in Bowman et al. [2013]); one patch of frost fl owers was sampled to obtain the upper centimeter portions separately from the basal portions. The V3-V5 region of the 16S rRNA gene was amplifi ed using primers 357F and 926R for 30 cycles. An aliquot of the amplifi ed material, along with positive and negative controls, was visualized on a gel to insure proper fragment length. Amplicons were purifi ed using the GeneJet Purifi cation Kit (Fermentas) and submitted to the Tufts University Sequencing Center, where amplicons underwent a second round amplifi cation for 10 cycles using barcoded primers 517F and 967R. Second round amplicons were gel-purifi ed prior to library construction. Sequencing was conducted on the 454 FLX platform (Roche) using Titanium chemistry. Read processing and classifi cation using Mothur [Schloss et al., 2009] followed Bowman et al. [2012] except that the Greengenes reference taxonomy was used for classifi cation (available at the Mothur website, http://www.mothur.org/wiki/ Greengenes-formatted_databases); sequence data are available under NCBI accession number SRP038953). Brine and Milli-Q blanks were processed along with the environmental samples. Operational taxonomic units (OTUs, defi ned at the level of 97 % similarity) found in the blanks were removed from the environmental samples prior to downstream analysis. OTUs that classifi ed as chloroplasts were also removed, assuming these reads to be derived primarily from chloroplasts [although see Diez et al., 2001; Waleron et al., 2007; Cottrell and Kirchman, 2009; and Bowman et al., 2012]. Similarity in community composition between samples was assessed by randomly sampling to the depth of the shallowest sample (1,367 reads), calculating the relative abundance of the 25 most abundant OTUs, and applying hierarchal clustering to samples using the complete linkage method through the vegdist and hclust functions as implemented by the heatmap function in R [Oksanen et al., 2013]. Results and Discussion Climate Forcing The climate at the Daneborg site was typical of conditions experienced in mid-winter in the Young Sound region of NE Greenland [Rysgaard and Glud, 2007]. Air masses are infl uenced by the proximal Greenland ice sheet. Storms are generated through the interface of warm, moist air masses, associated with the open water areas of the marginal ice zones surrounding Greenland, interacting with the cold dry air masses associated with the ice cap. 81 PhD thesis by Dorte Haubjerg Søgaard Figure 2 summarizes the salient data from the ‘pond’ met station. After a brief period of >10 m s–1 winds prior to the opening of the frost fl ower pool on 22 March, wind speeds remained between 1 and 3 m s–1 during the fi rst 2 days of the ice-growth experiment. This period was followed by 3 days of variable winds generally between 1 m s–1 and 5 m s–1, reaching about 8 m s–1 briefl y around noon on 27 March (Figure 2A). These initial low wind speeds are thought necessary for frost fl ower formation as turbulence during higher wind speeds (>5 m s–1) destroys the near-surface supersaturated layer [Style and Worster, 2009]. To allow a direct comparison with results from Style and Worster [2009] the measured relative humidity reported here is with respect to water surfaces (as output from sensor) with no correction for ice surfaces [see Andreas et al., 2002]. During the growth experiment, relative humidity remained between 70 and 85% (Figure 2B). We note three rapid drops in the relative humidity on March 20, 21 and 26 below a smaller running mean largely dominated by diurnal fl uctuations due to changing air temperature. Air temperature at the start of the experiment was around –26°C and dropped to –32°C, the lowest during the experiment, in the early hours of 23 March (Figure 2C). Air temperatures showed an increasing trend during the experiment, reaching as high as –10°C on 27 March, and underwent diurnal cycling which was interrupted for the night between 25 and 26 March due to the presence of cloud cover (note period of increased downwelling longwave radiation during 26 March in Figure 2D). The corresponding ice surface temperature, calculated using Eq. (2), rapidly decreased to –10°C about 8 hours after the initial opening of the pond (Tsurface1 in Figure 2C) in response to the cold air temperature and ice thickness growth to 4 cm thickness (Hsurface1). The decrease to –10°C took 17 hours for the pond portion reopened around 15:00 on 24 March (Tsurface2 in Figure 2C), refl ecting the effect of prevailing warmer air temperatures and ice thickness growth to 5 cm (Hsurface2). After the initial decreases, the surface temperatures remained between –15 and –6°C for both surfaces until the end of the experiment when (calculated) ice thicknesses had reached 20 cm for Hsurface1 and 13 cm for Hsurface2 (Figure 2C). Scalar irradiance over PAR wavelengths was measured on the side of the pond that was reopened (Figure 1C; Figure 2E). Thus, PAR was measured initially in ice that grew rapidly to about 12 cm and, for the latter part of the experiment, in ice that grew more slowly to 13 cm (Figure 2C). For both ice-growth phases, scalar PAR at about 30 cm below surface followed closely the values recorded by the cosine-corrected downwelling PAR at the meteorological tower. The near interface PAR, however, differed between the two cases due both to how the surfaces evolved (full frost fl ower coverage vs. patchy coverage) and to differences in where the sensor was located relative to the ice surface (top of sensor located about 5 mm below ice surface vs. top of sensor at surface). These differences resulted in notably higher interface PAR values during the second growth phase and illustrate the importance of near-surface properties and frost fl owers on light transmission through thin ice. The observed PAR levels that reached values > 500 μmol quanta s–1 m–2 are more than suffi cient to support primary production [e.g., Kühl et al., 2001]. This result may have ecosystem implications, considering the much larger spatial expanse of young, frost fl ower-covered sea ice in March in the Arctic (e.g., thousands of square kilometers in the Southern Beaufort Sea in February–April of 2013; http://www.youtube.com/watch?v=KXjb6MRj_5U). 0 500 1000 1500 2000 2500 PAR (ƫmol quanta s m ) -2-1 E (incident) d E (incident) 0d E (-0 cm) 0 E (-30 cm) 0 3/19 3/20 3/21 3/22 3/23 3/24 3/25 3/26 3/27 0 50 150 250 350 Radiative flux (W m ) -2 -50 SWĻ SWĹ LWĻ LWĹQ * snow snow snow LWĹ LWĹ surface2 surface1 65 75 85 Relative humidity (%) -10 0 10 20 Wind (m/s) A B C D E -35 -30 -25 -20 -15 -10 -5 0 Temperature (°C) T air T surface1 T surface2 H surface1 H surface2 H observation 20 15 10 5 0 25 Ice thickness (cm) Figure 2. Surface energy balance conditions during the frost fl ower growing experiment at the pond site: (A) wind (the length of arrows corresponds to wind speed; angle of the arrows corresponds to wind direction with northward wind pointing upward); (B) relative humidity; (C) air temperature (Tair) measured at the meteorological station, ice thickness observations (Hobservation), and calculated ice thicknesses (Hsurface) and surface ice temperatures (Tsurface) where subscripts with 1 and 2 denote values for the initially opened and reopened portions of the pond, respectively; (D) shortwave (SW), longwave (LW) and net (Q*) radiative fl ux where the subscripts denote the surface type (1, 2, or snow), arrows either downwelling or upwelling; and (E) PAR (E) where subscript 0 is for scalar irradiance and d is for downwelling. 82 PhD thesis by Dorte Haubjerg Søgaard A patch of mature frost fl owers was imaged with a FLIR camera to ascertain the thermal fi eld conditions of the frost fl owercovered and bare ice surface (Figure 3A and B, respectively). A patch of frost fl owers radiated out from the initial node of frost fl ower formation (Figure 3A. The patch consisted of mature frost fl owers extending > 1 cm (vertically) into the boundary layer. Top portions of the frost fl owers were at a temperature of ~ –7°C, ice surface temperature was ~ –4.5°C, and air           Temperature (°C) Relative pixel location along the profiles in images A and B. Figure 3. Thermal IR temperature of young ice showing the temperatures for a cluster of frost fl owers (A) and after this cluster was removed (B). Profi les in the color FLIR images are plotted from left to right according to the profi le line location at A and B (23 March 2013). Larger and more mature fl owers in the cluster have a lower surface temperature. Ice surface temperatures dropped by about 0.25°C due to the removal of the frost fl owers. Figure 4. Thermal IR temperature of young ice showing the temperatures of the ice surface relative to that of three frost fl owers. Profi les in the color FLIR images are plotted from left to right according to the profi le line location at A (23 March, 19:15 GMT, ~27 hours from freeze-up) and B (23 March, 20:15 GMT, ~28 hours from freezeup). The different lines illustrate the change in ice surface temperature that occurred during 1 hour relative to the change in the size and temperature of three frost fl owers.              Temperature (°C) Relative pixel location along the profiles in images A and B. 83 PhD thesis by Dorte Haubjerg Søgaard temperature was ~ –27°C. After frost fl ower removal, the ice surface temperature decreased by ~ 0.25°C due to direct contact with the cold air just above the growing ice (Figure 3B). On average we found a difference between fl ower tops and brine skim of about 5°C with a range of ± 1°C based on data shown in Figures 3 and 4 and data not shown. The temperature fi elds associated with the growth of individual frost fl owers were recorded with the FLIR camera by cutting and removing a small section of the ice, then allowing the ice to re-freeze. A one-hour time lapse between images of three growing frost fl owers (compare Figure 4A and B) shows the thermal effect of the frost fl ower formation on the surface ice fi eld and the effect of thickening sea ice on the surface fi eld temperature (Figure 4C). The average relative difference in the profi le lines in Figure 4A and B illustrates the difference in ice surface temperature (A-B) of about 2.5°C created by ice growth alone. The three fl owers in the thermal IR image frame grew 0.5 cm over 1 hour, which resulted in a temperature difference of ~ 2.5°C (absolute difference in temperature between 19:15 and 20:15 GMT on 23 March). The greatest temperature differences correspond to the large frost fl owers projecting the furthest into the atmospheric boundary layer. The lower surface temperatures of the frost fl owers dampen longwave radiation loss by between ~ 10 Wm–2 (~ 3.6%) and ~ 20 Wm–2 (~ 8%) relative to background sea ice and brine skim (observed ΔTsurface = –25 and –5°C, respectively). To place the effect in context, the change in longwave emission associated with frost fl ower formation relative to background brine-wetted sea ice is between 50% and 60% of reported wintertime sensible heat loss from newly formed grease ice (Table 1 in Else et al. [2011]), and hence a signifi cant proportion of the heat budget of the youngest forms of sea ice. Frost fl ower formation The fi rst frost fl owers were recorded at 16:15 GMT on 22 March (very small white nodules, Figure 5A), after only 15 minutes from when the pond was initially opened. Initial frost fl owers formed as distinct nodules in the very young ice, and then expanded from their initial nucleation sites radially outwards in all directions. Frost fl owers grew signifi cantly overnight; by the next morning they exhibited a patchy distribution with 9/10 of the pond surface covered. Frost fl owers were well formed by about 12 hours into the experiment and exhibited a typical branched structure at maximum growth (Figure 5C). δ18O ± SD [‰] S ± SD T [ºC] υb [%] Brine –4.9 ± 0.7 88.8 Fresh snow –24.6 ± 0.4 0.0 Ice 19h 0.0-2.5 cm –1.6 ± 0.1 10.4 –8.7 8.0 2.5-5.0 cm –1.9 ± 0.5 11.2 –5.4 14.1 5.0-8.0 cm –1.2 ± 0.3 8.7 –2.1 23.9 Ice 26h 0.0-2.0 cm 2.0-5.0 cm 7.6 –5.3 6.6 5.0-8.0 cm 8.6 –2.2 17.7 8.0-11.0 cm 9.2 –1.8 23.6 11.0-14.0 cm 6.6 –1.8 16.8 14.0-17.0 cm 9.5 –1.7 25.9 Frost fl owers 19h –0.8 ± 0.3 125.1 –12.7 43.8 26h –1.6 ± 0.3 94.9 ± 13.8 –7.8 56.6 46h –2.1 ± 0.3 90.9 ± 10.1 –7.1 58.9 46h (tops) –4.0 ± 0.2 92.2 ± 16.5 46h (bottoms) –0.1 ± 0.4 89.6 ± 3.8 –7.1 58.9 70h –4.4 ± 1.2 87.0 ± 9.7 90h –4.4 ± 0.3 64.4 90h (tops) –7.7 50.2 90h (middles) –4.6 ± 0.4 78.8 90h (bottoms) –0.9 ± 0.3 64.1 114h –4.3 ± 0.1 77.4 Surface slush layer 19h –0.1 ± 0.5 48.2 –10.3 22.7 26h –0.9 ± 0.4 66.2 ± 7.6 46h 2.1 ± 0.9 77.4 ± 19.1 –8.7 41.7 70h –0.4 ± 0.5 72.7 ± 11.0 90h –0.4 ± 0.0 52.9 114h –1.3 ± 0.5 72.3 Table 1. Measurements of δ18O, S, T, and υb in samples of sea ice, brine, fresh snow, frost fl ower and the surface slush layer throughout the duration of the frost fl ower growth experiment. 84 PhD thesis by Dorte Haubjerg Søgaard Over the course of the second night, the initially patchy coverage evolved into a relatively homogeneous cover (lower part of Figure 5B). A brine skim formed very early in the growth cycle of the new ice. This brine skim is often seen on young growing ice and is the result of brine being ejected upwards during ice growth. When the frost fl owers form, this brine skim can provide both a vapor source (for frost fl ower growth) and brine for salt migration into the frost fl owers. Work on chemical composition of frost fl owers corroborates this basic process of microstructure development [Alvarez-Aviles et al., 2008]. In what follows we discuss the effects of the brine skim, recognizing along the way that what we sampled was the ‘surface slush layer’, as defi ned above. The environmental conditions of frost fl ower formation during the experiment were placed in the context of the six regimes hypothesized in the SW model based on relative humidity of the atmosphere and temperature difference between the atmosphere and the ice surface (Figure 6; the numbering I-VI follows that of Style and Worster [2009]). Evaporation into vs. condensation from a supersaturated atmosphere (relative humidity > 100%) is characterized by regimes I and II, respectively. Regimes III to VI are for exchanges with an undersaturated atmosphere. Condensation from the air occurs at the surface in III-IV, while evaporation from the surface occurs in V-VI. Regimes V and VI distinguish between undersaturated vs. supersaturated water vapor conditions in the near-surface layer, as determined by the Clausius–Clapeyron equation. In both V and VI, the source of water vapor in the layer directly above the sea ice comes from evaporation or sublimation from the sea ice surface rather than from deposition from the cold atmosphere. For most of the experiment, pond surface conditions remained within regime VI with a brief transition into regime V after about 84 hours of the initial pond opening (Figure 6). Style and Worster [2009] observed that larger values of supersaturation, depicted by conditions to the left of the dash-dotted curve in Figure 6, were required for frost fl ower formation to occur. Our observations closely corroborate this fi nding.   Figure 5. Examples of frost fl owers grown at the pond. (A) The fi rst evidence of frost fl ower formation (see small white dots within the black rectangle) at ~ 3 hours into the experiment (ice < 1 cm thick; 22 March 19:00 GMT); (B) a patchy frost fl ower coverage on the reopened pond half after ~ 24 hours of growth (ice < 10 cm thick). Foreground shows the mature frost fl ower fi eld on the initially grown ice (~ 17 cm thick); and (C) a close-up image of a typical frost fl ower structure at ~ 48 hours into the experiment. Figure 6. The relative differences in humidity and temperature during the pond experiment set in the context of environmental conditions under which different condensation, evaporation and sublimation processes occur, following Style and Worster [2009]. Red (fi rst opening) and blue (second opening) colored numbers indicate the time (hours) elapsed in 4-hour intervals from the start of freeze-up (i.e., from 22 March at 16:00 GMT and 24 March at 15:00 GMT, respectively); their locations show the prevailing conditions at the time. Roman numerals I through VI are the categorical conditions under which various vapor-temperature differentials create various features: frost fl ower, rime, fog, dew, etc. The dashed and dash-dotted lines are redrawn from Style and Worster [2009, Figures 3-4], while the adjacent solid lines are obtained using the same equations but the temperatures observed during the pond experiment. 85 PhD thesis by Dorte Haubjerg Søgaard In the literature, there is still a debate as to whether frost fl owers form due to deposition of atmospheric water vapor onto the ice surface or sublimation or evaporation of the warm ice surface into the atmospheric boundary layer. Measured δ18O values of frost fl owers from 19 to 114 hours after freeze-up suggest that the frost fl owers were composed primarily of brine (Figure 7A). Fresh (19-h) unsectioned frost fl owers had a δ18O value of –0.8 ± 0.3‰ which was similar to the signature of the surface slush layer (–0.1 ± 0.5‰) and decreased gradually with time to –4.3 ± 0.1‰ after 114 hours from freeze-up (Table 1), pointing to the infl uence of secondary atmospheric deposition either from vapor or from blowing snow (δ18O value of –24.6 ± 0.4‰) during later stages of the experiment. Infl uence of that secondary atmospheric deposition is particularly pronounced in the top sections of frost fl owers, while bottom sections remained composed almost exclusively of brine (Figure 7A). Results presented here are generally in agreement with similar studies on Arctic leads [Douglas et al., 2005] and over large open water expanse formations of young frost fl ower covered sea ice [Douglas et al., 2012]. Initial salinities of frost fl owers were much higher than those measured in the surface slush layer (Figure 7B), strongly supporting the brine origin of frost fl owers revealed by the δ18O signature analysis (and further corroborated by the bacterial results; see below). The low temperatures of the frost fl owers (Figure 3) and, perhaps more importantly, the direct contact of brine with the atmosphere allowing for high evaporation rates, suggest that precipitated salts must be present [Assur, 1960], possibly explaining the high salinities of melted frost fl owers. Only after 46 hours of the experiment, when a δ18O atmospheric signature began to appear in the frost fl owers and the collected brine skim had a higher salinity, did the frost fl ower salinities approach those measured for the brine skim. Previous work has shown that brine can be wicked up into frost fl owers from a high-density brine skim, both in situ [Perovich and Richter-Menge, 1994] and in laboratory experiments [Martin et al., 1995; Roscoe et al., 2011] and sea ice mesocosm experiments [Isleifson et al., 2012]. Lack of data prior to 19 hours after freeze-up in our experiment prevents a defi nitive determination of initial ice-surface origin, but formation of nucleating nodules from frozen brine and/or precipitated salts seems plausible as: 1) atmospheric temperatures were below the temperature of freezing for brine with the maximum modeled salinity of ~ 200 (~ –10 ºC; Figure 7B), potentially allowing for the precipitation of salts to occur after cooling of brine to < –5ºC [Light et al., 2003]; and 2) initial salinities of frost fl owers were much higher than those measured in the surface slush layer within the range of modeled salinities of the liquid brine in the top 5 cm of ice (Figure 8). Brine skim temperatures (Figure 2C) calculated using Eq. (2) agreed well with measured surface slush layer temperatures (Table 1). The salinity of the brine in the surface slush layer could then be estimated using seawater freezing-point relationships [Fofonff and Millard, 1983]. The differences in salinity among the samples then allowed estimates of the brine volume within the surface slush layer, calculated as: 31, 49, 54, 41, 37, and 59% at 19, 26, 46, 70, 90 and 114 hours, respectively, into the ice-growth experiment. Furthermore, assuming that the brine from the brine skim wicks into the frost fl ower and forms part of its structure, we estimated the rela-         í í í í í í í í í í í í   !" !"#&!& !"#&!#  !"#&! !"#&!" !! #" !! #" !! ! ! #" !% !!## ! "$! !"$! !"$! $# $#  į  )                       #' !!($ $!" Figure 7. Temporal evolution of δ18O (A) and salinity (B) in frost fl owers and surface slush layer over the duration of the frost fl ower growing experiment that started 16:00 GMT on 22 March. 86 PhD thesis by Dorte Haubjerg Søgaard tive proportions of the sampled frost fl owers that were formed through brine wicking versus vapor deposition: for the above six sampling occasions, wicked brine composed about 81, 70, 64, 49, 45, and 63%, respectively, of the mass of the frost fl owers. This exercise illustrates the important role of brine wicking, not only in transferring salt (and organic matter, including bacteria), but also in bringing water to the frost fl owers. Over the course of the ice-growth experiment there was a general decrease in the brine-wicked fraction and consequent increase in deposition from vapor, a pattern entirely consistent with the δ18O signature analysis that also suggested a temporal increase in the atmospheric fraction (see above). Despite internal consistency, this approach to estimating the composition of frost fl owers could not account for possible changes in brine salinities over the course of the frost fl ower formation process, for example due to evaporation or sublimation. Gas Exchange The climate forcing and resulting frost fl ower formation concentrate brine in the upper layer of the ice and within the frost fl owers. This brine concentration affects the carbonate chemistry of the sea ice and thus gas exchanges across the OSA interface, specifi cally through the infl uence of ikaite formation. Ikaite crystal concentrations in frost fl owers and brine skim were characterized and quantifi ed by sampling at different times and distances (centimeter-scale) in the newly frozen pond (Figure 9A). Within 1 hour ikaite crystals were observed to form in both the thin ice and the frost fl owers, indicating the short-term dynamic conditions of ikaite formation. Ikaite crystals become easily visible when sea ice is melted. For example, 39 crystals were observed in a 3 μg subsample a few seconds after melt-      C) Relative pixel location  Figure 8. Temperature, salinity, brine volume fraction (υb) and δ18O profi les in sea ice during the frost fl ower growing experiment after 19 (A) and 26 (B) hours from freeze-up. Thermal IR image of small scale temperature of a sea ice core extract from the pond site at 26 hours into the experiment (coincident with temperature probe measurements in B). Figure 9. Frost fl owers at the pond during sampling of ikaite crystals for characterization and quantifi cation. (A) Frost fl ower fi eld with marks after sampling at different centimeter distances in the lower part of the image above the ruler. (B) Example of ikaite crystals just after ice crystals in the sample had melted. (C) Ikaite concentrations in frost fl owers (fi lled circles) and surface slush layer (empty circles). 87 PhD thesis by Dorte Haubjerg Søgaard ing 58 mg of new frost fl owers (Figure 9B). This image represents a very small fraction (3 μg) of the sample. In this case, the crystals covered 1.5% of the counting area, corresponding to an ikaite concentration of 2150 μmol kg–1. The crystals observed in the sea ice ranged in size (maximum dimension) from a few micrometers to 200 μm, were highly transparent with a rhombic morphology, and showed uniform extinction under crosspolarized light, suggesting that they were simple single crystals. All x-ray refl ections fi t well to a monoclinic C-centered cell with a(Å) = 8.816(3), b(Å) = 8.333(2), c(Å) = 11.043(3), β(°) = 110.68(2), and V(Å3) = 759.1(6). From the general shape, optical properties and unit-cell determination, the crystals examined were ikaite [Hesse and Küppers, 1983]. Average ikaite concentrations in the frost fl owers were 1013 μmol kg–1 (± 632, standard deviation) and in the surface slush layer, 1061 μmol kg–1 (± 736, standard deviation) (Figure 9C). The highest concentration of ikaite was observed in the sea ice column [Rysgaard et al., 2013]. The surface slush layer and frost fl owers represented a thin low-density layer on top of the ice with a strikingly high abundance of ikaite crystals (e.g., compared to Geilfus et al. [2013]), yet accounted for only 5% of the total ikaite in the ice column [Rysgaard et al., 2013]. Formation of ikaite in surface ice layers, however, can lead to a CO2 fl ux from the ice into the atmosphere. Due to logistical constraints we were only able to sample the surface CO2 fl ux at the pond on March 23 and 24. Sampling was performed on ice thickness of approximately 10 and 13 cm, respectively (Figure 2C), with ice surface temperatures between –10 and –13°C. Air temperature ranged between –21.5 and –19°C during sampling. Chamber fl ux measurements confi rmed an expected effl ux of CO2 at the brine-wetted sea ice surface (3.35 ± 0.86 mmol m–2 day–1, n = 8), but there was no discernible difference in this effl ux if frost fl owers were within the chamber footprint (3.02 ± 0.76 mmol m–2 day–1, n = 4) or not (3.67 ± 1.99 mmol m–2 day–1, n = 4). These results may not be unexpected given the small difference in ikaite concentration between the frost fl owers and surrounding brine skim. Few studies exist against which to compare our results. Fluxes are consistent in sign, but generally smaller than chamber fl ux measurements reported by Geilfus et al. [2013] over young, landfast sea ice near Barrow, AK. They observed an average effl ux of 6.7 mmol m–2 day–1 (4.2 to 9.6 mmol m–2 day–1) based on four measurements over ice that was thicker (20 cm), covered with older frost fl owers, and marginally colder (ice surface temperature of –14.2 °C) relative to the newer ice in our pond experiment. Ignoring possible differences in sea ice organic carbon composition between sites, the larger effl ux of CO2 at the Barrow site is possibly the result of colder near-surface temperature. On cooling, pCO2 in the brine system of sea ice tends to increase, given the likelihood of ikaite production, and because gases are generally less soluble in stronger electrolyte solutions (e.g., Thomas et al., 2010). Given that the brine volume was > 5% throughout their sea ice profi le, outgassing could occur along a brine-to-air pCO2 gradient. Microbial Habitat In general, the higher the salinity of the frost fl ower (or brine skim) sample, the greater its bacterial content according to Bowman and Deming [2010], whose data support the view that bacteria in sea ice brine are transported upwards as the brine wicks into frost fl owers. In our pond experiment, the highest concentrations of bacteria were again observed in the saltiest features (in rank order, on a melt-volume basis): 1.56–4.46 × 105 cells ml–1 (n = 32) in frost fl owers and the surface slush layer, compared to 1.10–2.11 × 105 ml–1 (n = 7) in seawater, 6.58–7.85 × 104 ml–1 (n = 2) in young sea ice, and only 133–353 ml–1 (n = 2) in freshly deposited snow (which had no detectable salinity by refractometer). An atmospheric source of bacteria (represented by fresh snow samples) to the frost fl owers and brine skim at the pond was thus negligible, including even for aging frost fl owers showing signs by ∂18O analysis of atmospheric ice-crystal deposition (Figure 7). The contribution of vapor-derived ice to frost fl owers, however, represents an unavoidable dilution (upon sample melting) of the true bacterial density in the habitable brine volume fraction of these structures. Although estimates of this dilution factor could be made in a few cases, comparing bacterial abundance across the data set required scaling numbers to melted sample volume. Earlier short-term laboratory and mesocosm experiments to evaluate bacterial content as a function of frost fl ower age have not been defi nitive [Bowman and Deming, 2010; Aslam et al., 2012], but this fi eld experiment clearly revealed highest concentrations of bacteria early in the growth phase of these briny ice structures (Figure 10) when salinity was also highest. Frost Figure 10. Bacterial abundance in frost fl owers (blue squares) and surface slush layer (red circles) over time since opening the experimental pond, with abundance in seawater (green diamonds) representing time zero. The fi rst three values for frost fl owers derive from the second opening of the pond. Second-order polynomials were fi t to the data primarily to help visualize the different apparent time-course trajectories for frost fl owers (R2 = 0.609) and surface slush layer (R = 0.237). 95 PhD thesis by Dorte Haubjerg Søgaard PAPER IV Marine Ecology Progress Series 419:31 – 45, doi: 10.3354/meps08845 D.H. Søgaard • M. Kristensen • S. Rysgaard • R.N. Glud • P.J. Hansen • K.M Hilligsøe Autotrophic and heterotrophic activity in Arctic fi rst-year sea ice: seasonal study from Malene Bight, SW Greenland Photo: Michael S. Schrøder. 96 PhD thesis by Dorte Haubjerg Søgaard 3 Vol. 419: 31–45, 2010 doi: 10.3354/meps08845 MARINE ECOLOGY PROGRESS SERIES Mar Ecol Prog Ser Published November 30 Autotrophic and heterotrophic activity in Arctic first-year sea ice: seasonal study from Malene Bight, SW Greenland Dorte Haubjerg Søgaard 1, 2, *, Morten Kristensen 1, 2 , Søren Rysgaard 1 , Ronnie Nøhr Glud 1, 4 , Per Juel Hansen 2 , Karen Marie Hilligsøe 3 1 Greenland Climate Research Centre (c/o Greenland Institute of Natural Resources), Kivioq 2, Box 570, 3900 Nuuk, Greenland 2 University of Copenhagen, Marine Biological Laboratory, Strandpromenaden 5, 3000 Helsingør, Denmark 3 Aarhus University, Department of Biological Sciences, Ny Munkegade 114-116, 8000 Århus C, Denmark 4 Presentaddress: The Scottish Association for Marine Science, Oban, Argyll PA37 1QA, Scotland, UK ABSTRACT: We present a study of autotrophic and heterotrophic activities of Arctic sea ice (Malene Bight, SW Greenland) as measured by 2 different approaches: (1) standard incubation techniques (H14CO – and [3H]thymidine incubation) on sea ice cores brought to the laboratory and (2) cores incubated in situ in plastic bags with subsequent melting and measurements of changes in total O2 concentrations. The standard incubations showed that the annual succession followed a distinctive pattern, with a low, almost balancing heterotrophic and autotrophic activity during February and March. This period was followed by an algal bloom in late March and April, leading to a net autotrophic community. During February and March, the oxygen level in the bag incubations remained constant, validating the low balanced heterotrophic and autotrophic activity. As the autotrophic activity exceeded the heterotrophic activity in late March and April, it resulted in a significant net oxygen accumulation in the bag incubations. Integrated over the entire season, the sea ice of Malene Bight was net autotrophic with an annual net carbon fixation of 220 mg C m–2, reflecting the net result of a sea ice-related gross primary production of 350 mg C m–2 and concurrent bacterial carbon demand of 130 mg C m–2. Converting the O2 net exchange of the bag incubations into carbon turnover estimated an annual net carbon fixation of 1700 ± 760 mg C m–2 (mean ± SD), which was higher than the annual net carbon fixation quantified in the standard incubations. KEY WORDS: Sea ice · Primary production · Bacterial carbon demand · Net autotrophic activity · Net heterotrophic activity · Attenuation coefficients Resale or republication not permitted without written consent of the publisher INTRODUCTION Sea ice provides a low-temperature habitat for diverse communities of microorganisms including viruses, bacteria and heterotrophic (e.g. flagellates and ciliates) and autotrophic protists (e.g. diatoms) (Kaartokallio et al. 2006). During sea ice formation, microorganisms, inorganic solutes and solids can be incorporated into the ice and accumulate to concentrations higher than that in the underlying seawater (Reimnitz et al. 1992, Grossmann & Gleitz 1993, Gradinger & Ikävalko 1998). Organisms incorporated into sea ice are challenged with *Email: [email protected]l changes in space, light availability, salinity, nutrients, dissolved inorganic carbon (DIC) and O2 concentration, temperature and pH (Gradinger & Ikävalko 1998). Especially, light availability within the sea ice has a major influence on the sea ice algal biomass and production (Cota & Horne 1989, Rysgaard et al. 2001). Sea ice algae constitute an important component of sympagic communities and have been extensively studied in Arctic sea ice (e.g. Horner & Schrader 1982, Gosselin et al. 1997, Glud et al. 2007, Mikkelsen et al. 2008). The sea ice algae represent an important food source for metazoan grazers, and photosynthetic prod- © Inter-Research 2010 · www.int-res.com O PENN ACCCEESSSS 97 PhD thesis by Dorte Haubjerg Søgaard 32 Mar Ecol Pro g Ser 419: 31–45, 2010  3 ucts or entrained organic material can lead to elevated bacteria abundance and production within the sea ice (Smith et al. 1989, Krembs et al. 2002, Meiners et al. 2003, Riedel et al. 2007). Several previous studies have shown that heterotrophic bacteria are active and abundant in Arctic sea ice (Bunch & Harland 1990, Smith & Clement 1990, Brinkmeyer et al. 2003, Lizotte 2003, Kaartokallio 2004), but studies on spatial and seasonal variations are few (Smith et al. 1989, Gradinger and Zhang 1997). Sea ice represents a partially interconnected network of brine-filled channels comprising 1 to 30% of the sea ice volume (e.g. Weeks & Ackley 1986). The degree of interconnection of the brine enclosures is generally enhanced with increasing temperature, and the potential accumulation of sea ice algae therefore increases towards the polar spring. The significance of heterotrophic processes typically increases during late bloom and postbloom situations close to spring thaw (Vézina et al. 1997, Kaartokallio 2004). In addition to biologically mediated dynamics, thaw and freezing processes induce extensive dynamics in solute and gas distribution (Glud et al. 2002). Consequently, the sea ice matrix is highly heterogeneous and dynamic, and quantification of in situ algae and bacterial productivity represent a true challenge. The overall objective of this investigation was to describe the dynamics of autotrophic and heterotrophic activity in first-year sea ice. We measured autotrophic and heterotrophic activity of intact sea ice cores under in situ conditions in bag incubations, and measurements were compared with primary production and bacterial carbon demand as measured in the concentrations, sea ice algal productivity and bacterial carbon demand during each sampling campaign, the latter 2 being referred to as ‘standard incubations’. On 15 February and 19 March, 10 sea ice cores were collected using a MARK II coring system (Kovacs Enterprises). Cores were cut into 2 sections of equal length (ca. 22 cm), i.e. top half and bottom half, which were brought back to the laboratory in black plastic bags within 1 h of sampling. In a laboratory cold room (3 ± 1°C), core sections were placed in laminated transparent NEN/PE plastic bags (Hansen et al. 2000) fitted with a gas-tight Tygon tube and a valve for sampling. Artificial seawater (salinity of 33) with a known O2 concentration was added (10 to 30 ml) to the NEN/PE bags (Hansen et al. 2000). The bags were closed, and excess air quickly extracted through the valve. The top and bottom halves of a single ice core (i.e. the contents of one pair of bags) were melted within 48 h in darkness (3 ± 1°C). Gas bubbles released from the melting sea ice were subsequently transferred to 12 ml Exetainer tubes (Labco) containing 20 Ǎl HgCl2 (5% w/v, saturated solution). The gas bubbles were analysed for gaseous O2 by gas chromatography in a flame ionization detector and thermal conductivity detector (FID/TCD, SRI model 8610C). The melted water was also transferred to Exetainer tubes for O2 measurements. Dissolved O2 in the melted sea ice was measured by Winkler titration (Grasshoff et al. 1983). The remaining 9 sea ice cores in plastic bags were transferred to the drilled holes at the sea ice sampling site within 2 h, and the in situ snow cover above the cores was re-established. The sea ice cores, i.e. top and bottom halves, were sampled at 1 to 2 wk intervals to laboratory by standard H14CO – and [3H]thymidine determine the O2 bulk concentration of the sea ice. incubations under well-defined conditions. MATERIALS AND METHODS Measurements were conducted on first-year landfast sea ice in Malene Bight in the vicinity of Nuuk, SW Greenland (64° 82’ N, 51° 42’ W). Sampling was performed at 1 to 2 wk intervals from 1 February to 14 April 2008. During that period, sea ice thickness varied between 0 and 62 cm, while snow cover ranged between 0 and 28 cm. The net aerobic activity of an enclosed sea ice community was followed in situ by determining the O2 concentrations in sea ice cores sealed in plastic bags and placed under natural snow cover, hereafter referred to as ‘bag incubations’. These measurements were supplemented with standard measurements of temperature, salinity, irradiance attenuation in snow and ice, nutrient concentrations (phosphate, Permeability of the NEN/PE bags was quantified by adding artificial seawater (salinity of 33) to 9 plastic bags containing a gas-tight valve for sampling (Hansen et al. 2000). The bags were spiked with HgCl2 (200 Ǎl of a 5% solution per liter seawater) to prevent biological activity during the incubation. The water was then flushed with N2 gas until the O2 concentration in the bags reached 50% of atmospheric saturation. The valves in the bags were then closed ensuring that no gas phase was left inside the 1 l bag. Three bags were incubated at –20°C, 3 bags at 3°C and 3 bags at 20°C for 7 d. Initially the O2 concentration was measured in all bags. After the incubation, O2 samples were collected and measured as described previously. Ice formation in the bags (–20°C experiment) led to bubble formation and the O2 concentration was therefore calculated as the sum of O2 in gas and water. The maximum O2 flux across the plastic bags was calculated from the O2 concentration change between initial 3– – – –1 –1 PO 4 ; nitrate and nitrite, NO3 + + NO2 ; silicic acid, and final readings to 0.48 ± 0.20 Ǎmol O2 l d (mean Si(OH)4; and ammonium, NH4 ), chlorophyll a (chl a) ± SD). This put a lower limit on the activity that can be 98 PhD thesis by Dorte Haubjerg Søgaard Søgaard et al.: Autotrophic and heterotrophic activit y in Arctic sea ice 33  4 + – – resolved by this procedure and may compromise over- (Turner Designs). The remaining filtered sea ice was 3– – – all net activity at low biomass. In reality the permeabilfrozen (–18°C) for later analysis of PO4 + , NO3 – + NO2 , – ity at the incubation temperature (–5 to 0°C) was significantly less than our maximum value. O2 bulk concentration in the sea ice (Ci) was calculated as: C W C W Si(OH)4 and NH4 . Concentrations of NO3 + NO2 were measured by vanadium chloride reduction (Braman & Hendrix 1989). Concentrations of Si(OH)4 and PO 3– were determined by spectrophotometric analysis (Strickland & Parsons 1972, Grasshoff et al. 1983). Con- + C i m m a a (1) centrations of NH4 were determined by a fluorometric W i where Cm is the O2 concentration in the melted sea ice method (Holmes et al. 1999). The lower detection limit for the nutrient measurements were 0.002 Ǎmol l–1 for 3– –1 – – –1 (gas bubble + melted sea ice), Wm, is the weight of the PO 4 , 0.5 Ǎmol l for NO3 + NO2 , 0.002 Ǎmol l for melted sea ice, Ca, is the O2 concentration in the artificial Si(OH)4 and 0.10 Ǎmol l–1 for NH4 (lower detection sea water, Wa is the weight of the artificial sea water, and Wi is the weight of the sea ice (Rysgaard & Glud 2004). The season was divided into Series 1 and Series 2. Series 1 consisted of 10 cores, which were incubated on 15 February and were individually collected for analysis from 15 February to 25 March. Series 2 consisted of another 10 cores incubated on 19 March and were individually collected for analysis from 19 March to 11 April. Linear regression was performed on each of the 4 series (i.e. top half and bottom half of cores in Series 1 and Series 2). The slope of the regression line was tested in all 4 series by means of Student’s t-test. On each of the 7 sampling occasions, triplicate ice cores were collected using a MARK II coring system. The 3 sea ice cores were cut into sections using a stainless steel handsaw, and vertical temperature profiles limit is calculated using the t-value of 2.99 corresponding to a 99% confidence interval with df = 7). Conductivity of the melted sea ice sections was measured using a conductivity cell (Thermo Orion 3-star with an Orion 013610MD conductivity cell) and converted to bulk salinity (Grasshoff et al. 1983). Sea ice brine salinity was calculated as a function of temperature (Cox & Weeks 1983) and the brine volume as a function of bulk salinity, density and temperature. Brine volume was calculated according to Leppäranta & Manninen (1988) for temperatures greater than –2°C and according to Cox & Weeks (1983) for temperatures less than –2°C. Primary production was determined in melted (melted within 48 h in dark conditions at 3 ± 1°C) sea ice water at 3 light intensities (42, 21 and 9 Ǎmol photons m–2 s–1) and corrected with one dark incubation uswere measured in drilled holes to the centre of each ing the H14CO3 incubation technique (Steemansection using a thermometer (Testo thermometer). Downwelling irradiance was measured directly above and below the snow with a data logger (LI-1400, Li-Cor Biosciences). In addition, air temperature was meaNielsen 1952). The sea ice samples were melted and subsequently acclimatised at 20 Ǎmol photons m–2 s–1 for a few hours (> 2 h). Then the sea ice samples were poured into 120 ml gastight glass bottles and 4 ǍCi of sured 2 m above the snow, and snow and sea ice thickH14CO3 were added to each bottle. The bottles were nesses were determined using a measuring stick. The sea ice sections were placed in plastic containers in a dark insulated transport box (Thermobox) and brought back to the laboratory. Light attenuation of the sea ice samples was measured with a LI-1400 data logger in a dark thermally regulated room using a fibre lamp with a spectrum close to natural sunlight (15 V, 150 W, fibreoptic tungsten–halogen bulb). The LI-1400 data logger was placed under the sea ice section and the fibre lamp was placed above. Light attenuation was measured this way for each sea ice section. All sea ice samples were melted within 48 h for analysis of nutrients, salinity, chl a, primary production and bacterial carbon demand analysis at 3 ± 1°C in darkness. The melted sea ice was filtered onto 25 mm GF/F filters (Whatman) for chl a analysis. The filters were extracted for 18 h in 96% ethanol (Jespersen & Christoffersen 1987) and analysed fluorometrically (Turner TD700 fluorometer, Turner Designs) before and after incubated on a plankton wheel at 1 rpm for 5 h at 3 ± 1°C at the different light intensities. Illumination was provided by cool white fluorescent lamps with a spectrum close to natural sunlight (Master TL-D 36W/840, Phillips) and irradiance was measured using a LI-1400 data logger. Incubations were terminated by adding 200 Ǎl of 5% ZnCl2 and subsequently filtered onto 25 mm GF/F filters (Whatman). The filters were placed in scintillation vials containing 200 Ǎl 1 M HCl to remove labelled, unfixed inorganic carbon, and then extracted in scintillation liquid (PerkinElmer Ultima Gold) for 22 h and counted using a liquid scintillation analyser (TricCarb 2800 TR, PerkinElmer). Dissolved inorganic carbon (DIC) concentrations in melted sea ice were measured on a CO2 coulometer as described by Rysgaard & Glud (2004). After liquid scintillation counting, counts were converted to potential primary production (under photoinhibition) (PPi, Ǎg C l–1 h–1) as: addition of 200 Ǎl of a 1 M HCl solution. The fluorometer was calibrated against a pure chl a standard PPi DPMactivity DICsea ice Fdiscr Mc DPMadded tinc (2) 99 PhD thesis by Dorte Haubjerg Søgaard 34 Mar Ecol Pro g Ser 419: 31–45, 2010  where DPMactivity is the 14C assimilated carbon corrected for assimilated carbon in the dark (disintegrations per minute [dpm] on filter), DICsea ice is dissolved inorganic carbon in melted sea ice (~450 Ǎmol l–1), Fdiscr = 1.05 is the discrimination factor of algae assimilation of 12CO2 and 14CO2, Mc is the molar mass of carbon (12.01 g mol–1), DPMadded is the specific activity of the 14C labelled medium (dpm ml–1) in which cells were labelled, and tinc is the incubation time (5 h). The potential primary production (under no photointrated through 25 mm mixed cellulose ester filters (pore size 0.2 Ǎm, Advantec MSF) and the filters were placed in scintillation vials. Scintillation vials were rinsed with 5 ml of 5% cold TCA. Subsequently, filters were rinsed 7 times with 1 ml of cold 5% TCA and then extracted in scintillation liquid (Ultima Gold, PerkinElmer) for 22 h and counted using a liquid scintillation analyser (TricCarb 2800, PerkinElmer). Bacteria production (BP, Ǎg C l–1 h–1) was calculated as: hibition) (PP, Ǎg C l–1 h–1) measured in the laboratory DPM N N M sample cells c c at different sea ice depths was plotted against the 3 laboratory light intensities, 42, 21 and 9 Ǎmol photons BP SA t inc Vfilt (4) m–2 s–1, and fitted to the following function described by Platt et al. (1980): where DPMsample is the average dpm for the live treatment subtracted from the average dpm for the TCAPP Pm 1 exp E PAR (3) killed controls, Ncells is the conversion factor (2.09 1018 cells mol–1 3H, according to Smith & Clement P m 1990), tinc is the incubation period (tinc = 6 h), Vfilt is the where Pm (Ǎg C l–1 h–1) is the maximum photosynthetic rate at light saturation, (Ǎg C m2 s Ǎmol photons–1 l–1 h–1) is the initial slope of the light curve and EPAR (Ǎmol photons m–2 s–1) is the laboratory irradiance. The photoadaptation index, Ek (Ǎmol photons m–2 s–1) was calvolume of the subsamples (Vfilt = 0.01 l), Mc is the molecular mass of carbon and SA is the specific activity of the thymidine solution (2.24 1016 dpm mol–1). Nc = 5.7 10–8 Ǎg C cell–1 is calculated as: culated as P m / . In situ downwelling irradiance was measured at N c Cellsize Cfactor 1000000 (5) ground level with a pyrometer (Kipp & Zonen, model CM21, spectrum range of 305 to 2800 nm) once every 5 min, and hourly averages were provided by Asiaq (Greenland Survey). Hourly downwelling irradiance was converted into hourly photosynthetically active radiation (PAR) (light spectrum, 300 to 700 nm) after intercalibration (r2 = 0.99, p < 0.001, n = 133) with a LIwhere Cellsize is the average bacteria cell size (0.473 Ǎm3) (Smith & Clement 1990), and Cfactor is the factor used to convert cell volume to carbon (0.12 pg C Ǎm–3) according to Smith & Clement (1990). Bacterial carbon demand (BCD, Ǎg C l–1 h–1) was calculated as: 1400 data logger (Li-Cor). The in situ hourly PAR irradiance was calculated at different depths, depending BCD BP BGE (6) on sea ice and snow thickness, using the attenuation coefficients measured during the sea ice season. In situ primary production was calculated for each hour at different sea ice depths using hourly in situ PAR irradiance (see Eq. 3). Total daily (24 h) in situ primary production was calculated as the sum of hourly in situ primary production for each depth. The depthintegrated net primary production was calculated using trapezoid integration. Bacteria production in melted sea ice samples was determined by measuring the incorporation of [3H]thymidine into DNA. Triplicate subsamples (volume, Vfilt = 0.01 l) were incubated in darkness at 3 ± 1°C with 10 nM of labelled [3H]thymidine (New England Nuclear, specific activity, 10.1 Ci mmol–1). Trichloroacetic acid (TCA)-killed controls were made to measure the abiotic adsorption. At the end of the incubation period (tinc = 6 h), 1 ml of 50% cold TCA was added to all the subsamples (Fuhrman & Azam 1982). Subsamples of [3H]thymidine were stored at 3 ± 1°C in scintillations vials until filtration. Subsamples were filwhere BP is the bacteria production and BGE is the bacterial growth efficiency of 0.5 according to Rivkin & Legendre (2001). To extrapolate bacterial carbon demand to daily in situ carbon demand we assumed that the respiration was light-independent (multiply by 24). The depth-integrated bacterial carbon demand was calculated using trapezoid integration. On 23 February, 10 sea ice cores were collected along a 10 m long section to investigate the spatial (horizontal and vertical) variability of the biotic conditions (chl a, primary production and bacterial carbon demand) and the abiotic conditions (sea ice temperature, bulk salinity and brine volume) in the sea ice. The 10 sea ice cores were collected close to the plastic bag incubations at 1 m intervals. The cores were cut into 2 sections, i.e. top and bottom halves, and brought back to the laboratory in a dark Thermobox for further analysis as described. To extend the evaluation of spatial variability, a large-scale investigation of horizontal variability was conducted on 29 February. Fifty-two sea ice cores were collected along a 367 m long transect to investigate the 100 PhD thesis by Dorte Haubjerg Søgaard Søgaard et al.: Autotrophic and heterotrophic activit y in Arctic sea ice 35  heterogeneity of chl a, sea ice temperature, brine salinity and brine volume in the bottom of the sea ice. The snow and sea ice thickness was measured as described previously. Four sea ice cores were sampled at 20 cm intervals at position 1 m. The first core was cut vertically into 2 pieces at every sampling position. Sea ice cores were collected at distances of 1, 3, 5, 7, 9, 20, 31, 42, 53, 64, 165, 266 and ca. 367 m. All the ice cores were brought back to the laboratory in a dark Thermo box for determination of brine salinity, volume and chl a concentration as described. Spatial autocorrelation (Legendre & Legendre 1998) was used to analyse the horizontal distribution of chl a, sea ice temperature, bulk salinity, snow thickness and sea ice thickness. We assume that the variability along one line is the same as along a perpendicular line. The autocorrelation was estimated by Moran’s I coefficients (Moran 1950, Legendre & Legendre 1998). This coefficient was calculated for each of the following intervals along the transect (distance classes): 0 to 0.50 m, 0.50 to 1.5 m, 1.5 to 2.5 m, 2.5 to 5.5 m, 5.5 to 10.5 m, 10.5 to 20.5 m, 20.5 to 50.5 m, 50.5 to 100.5 m and >100.5 m. The autocorrelation coefficients estimated by Moran’s I coefficient were tested for significance according to the method described in Legendre & Legendre (1998). A 2-tailed test of significance was used. The null hypothesis of random spatial distribution was rejected at the specified level of significance when an individual autocorrelation coefficient exceeded a critical value (positive or negative). A significance level of p < 0.05 was used. RESULTS Abiotic parameters Temperatures within the snow cover varied from –13 to 0°C and the sea ice temperature from –5 to 0°C (Fig. 1a). Minimum temperatures of the sea ice were a) Sea ice and snow temperature (°C) 40 –13 25 –10 0 d) Bulk salinity 40 25 0 9 –3 –20 –35 –50 –65 –6 –5 –1 –4 –2 –20 –35 –50 –65 7 8 1 5 1 40 25 0 –20 –35 –50 –65 b) Light attenuation coefficient (m –1 ) 20 32 13 10 8 6 c) Irradiance (mol photons m –2 s –1 ) 40 25 0 –20 –35 –50 –65 e) Relative brine volume (%) 0 –20 –35 –50 –65 7 7 76 60 40 7 500 250 0 Fig. 1. Sea ice development in Malene Bight, NW Greenland, during the 2008 season: (a) sea ice and snow temperature (°C), (b) light attenuation coefficient (m–1), (c) average daily photon irradiance in sea ice and at surface (PAR, Ǎmol photons m–2 s–1), (d) bulk salinity, (e) relative brine volume fraction (%). The sea ice in late March from 0 to 16 cm is a layer of granular snow–ice. The black dots represent triplicate measurements Feb Mar Apr 80 10 10 60 20 Feb Mar A pr Sea ice and snow depth (cm) Sea ice and snow depth (cm) Sea ice and snow depth (cm) P AR (ȝ mol photons m –2 s –1 ) 101 PhD thesis by Dorte Haubjerg Søgaard 36 Mar Ecol Pro g Ser 419: 31–45, 2010  32 4 – – observed in February, after which the temperature gradually increased to maximum values just before sea ice break-up in mid-April. The high light reflectance and scatter from the snow cover caused strong light attenuation throughout the sea ice season, with average attenuation coefficients of K snow = 23 m–1 and Kice = 8 m–1 (Fig. 1b). Early in the sea ice season, irradiance at the bottom of the sea ice was low (0.03 to 0.15 Ǎmol photons m–2 s–1) (Fig. 1c). Light availability increased the sea ice (Fig. 1e). In late March melting from the top of the sea ice was initiated, which resulted in high relative brine volumes and low bulk salinities in the uppermost part of the sea ice. During this period air temperatures varied between 0 and 7°C. Nutrient parameters 3– along with increasing day length and declining snow Bulk PO4 concentration was initially 0.05 to cover, reaching a maximum downwelling irradiance of 76 Ǎmol photons m–2 s–1 in the uppermost sea ice section and 7 Ǎmol photons m–2 s–1 in the bottom on April 4. The bulk salinity decreased over time with a maximum salinity of 9 in early March and a minimum salinity of 1 from late March and onward (Fig. 1d). Bulk salinity varied vertically within sea ice cores during 0.20 Ǎmol l–1 (Fig. 2a), and increased to a maximum of 0.70 Ǎmol l–1 in March but subsequently decreased to 0.05 Ǎmol l–1 in April. Bulk Si(OH)4 concentration remained constant between 1.8 and 2.3 Ǎmol l–1 in the sea ice from February to late March with lowest values encountered at the bottom of the sea ice. In late March, Si(OH)4 concentration decreased rapidly to below 1.4 Ǎmol l–1 (Fig. 2b). The initial bulk concentration of winter, with lower values encountered in the bottom NO – + NO – was 3.2 Ǎmol l–1 at the top and 2.0 Ǎmol l–1 sea ice from mid-February until late March. From 25 March to 4 April, bulk salinity was lowest in the uppermost part of the sea ice. The relative brine volat the bottom of the sea ice (Fig. 2c) and decreased throughout the season, reaching a minimum of 1.5 Ǎmol l–1 in April. The initial bulk concentration of ume increased throughout the sea ice season, with a NH + was 4.0 Ǎmol l–1 at the top and bottom of the sea + maximum in late March in the uppermost section of ice. During the sea ice season the NH4 concentration Fig. 2. Nutrient concentration (Ǎmol l–1) in bulk sea ice: (a) phosphate, (b) silicic acid, (c) NO3 + NO2 , (d) ammonium. LOD is lower limit of detection, which is calculated using the t-value of 2.99 corresponding to a 99% confidence interval with df = 7. The black dots represent triplicate measurements 102 PhD thesis by Dorte Haubjerg Søgaard Søgaard et al.: Autotrophic and heterotrophic activit y in Arctic sea ice 37  15 Feb 3 Mar 10 Mar 19 Mar 25 Mar 4 Apr c) NO – + NO – 3 2 a) Phosphate b) Silicic acid 8 8 6 6 4 4 2 2 0 0 d) Ammonium 8 8 6 6 4 4 2 2 0 0 2 4 6 8 0 10 0 2 4 6 8 10 Bulk salinity – – Fig. 3. Concentrations of (a) phosphate, (b) silicic acid, (c) NO3 + NO2 and (d) ammonium versus bulk salinity in sea ice. The solid line indicates the expected dilution line predicted from salinity and nutrient concentrations in seawater (0 to 10 m depth, salinity of 33). See ‘Results: Nutrient parameters’ for explanation increased, reaching values of 6 to 12 Ǎmol l–1 at the bottom of the sea ice and 5.0 to 6.0 Ǎmol l–1 at the top of the sea ice (Fig. 2d). Bulk nutrient concentrations for each sampling date were plotted as a function of bulk salinity and compared with the expected dilution line (according to Clarke & Ackley 1984). If values were below the line, depletion of nutrients occurred in the sea ice. If values were above the dilution line, production or net deposition of the solute took place. Plots of salinity– tion (bulk) of 40 Ǎg C l–1 d–1 was encountered in the middle part of the sea ice profile in April. The highest sea ice bacterial carbon demand of 27 Ǎg C l–1 d–1 was encountered in the central ice at the onset of the melting period (Fig. 4c). However, a single peak of 9.00 Ǎg C l–1 d–1 was observed on 10 March in the upper 10 cm section of the sea ice. Depth integration of the activity reflected low autotrophic and heterotrophic productivity during winter, followed by a slightly net heterotrophic period 3– – – PO 4 , salinity–Si(OH)4, salinity–NO3 + + NO2 and in late February and March. Finally, a net autotrophic salinity–NH 4 in sea ice were generally all above the + period was observed from late March until the end of dilution line (Fig. 3), but most explicitly for NH4 , which clearly accumulated within the sea ice (Fig. 3d). Biotic parameters Sea ice profiles of the algal biomass, expressed as chl a, showed that the highest bulk concentration in the lower 15 cm of the sea ice cores was 2.80 Ǎg l–1 on 25 March (Fig. 4a). Subsequently, the algal biomass in the lower 15 cm of the sea ice cores decreased rapidly reaching a value of 1.50 Ǎg l–1 in April. Sea ice primary production integrated for the sea ice profile increased throughout winter from 0.09 mg C m–2 d–1 (15 February) to 12.60 mg C m–2 d–1 (4 April) (Fig. 4b). The highest volume-specific primary producthe study period (Fig. 5). Integrated over the entire measuring season (i.e. from 15 February to 14 April) the sea ice of Malene Bight was net autotrophic. An annual net carbon fixation of 220 mg C m–2 was calculated by subtracting the net result of a sea ice-related gross primary production of 350 mg C m–2 from the bacterial carbon demand of 130 mg C m–2. Bag incubations Oxygen levels during February and March indicated a low net oxygen accumulation in the top sea ice cores of 0.50 ± 3.00 Ǎmol O2 l–1 d–1 (mean ± SD) and in the bottom sea ice cores of 1.30 ± 5.00 Ǎmol O2 l–1 d–1. However, none of these values were significantly different from Nutrient concentration (mol l –1 ) 103 PhD thesis by Dorte Haubjerg Søgaard 38 Mar Ecol Pro g Ser 419: 31–45, 2010  40 25 0 –20 –35 –50 –65 40 25 a) Chlorophyll (g l–1 melted sea ice) b) Primary production (g C l–1 melted sea ice d–1) 14 12 10 8 6 4 2 0 Fig. 5. Primary production (PP, mg C m–2 d–1) and bacterial carbon demand (BCD, mg C m–2 d–1) in bulk sea ice 0 –20 –35 –50 –65 c) Bacterial carbon demand (g C l–1 melted sea ice d–1) 40 25 350 300 250 200 150 100 50 a) Top sea ice cores Series 1 Series 2 PP BCD 100 80 60 40 20 0 0 –20 –35 –50 –65 5 9 2 27 2 13 350 300 250 200 b) Bottom sea ice cores 100 80 60 40 Feb Mar Apr Fig. 4. (a) Chl a concentrations (Ǎg chl a l–1) in bulk sea ice. (b) Primary production (Ǎg C l–1 melted sea ice d–1). (c) Bacterial carbon demand (Ǎg C l–1 melted sea ice d–1) calculated according to Rivkin & Legendre (2001). The black dots represent triplicate measurements 150 100 50 20 0 Feb Mar Apr zero (p > 0.05) (Fig. 6). Autotrophic activity exceeded heterotrophic activity in late March and April, resulting in a significantly high net oxygen accumulation in the bottom sea ice cores of 6.30 ± 2.30 Ǎmol O2 l–1 d–1 (p < 0.01) whereas no significant oxygen accumulation (0.80 ± 3.50 Ǎmol O2 l–1 d–1) was observed in the top sea ice cores. Assuming a photosynthetic quotient of 1.00 CO2 evolved per O2 consumed, a net annual carbon fixation of 1700 ± 760 g C m–2 was calculated for the bag incubations. Fig. 6. Measurements of O 2 concentration ( d , z : Ǎmol O 2 l –1 melted sea ice), primary production (PP) ( j : Ǎg C l –1 melted sea ice d –1 ) and bacterial carbon demand (BCD) ( h j : Ǎg C l –1 melted sea ice d –1 ) in (a) top half and (b) bottom half of sea ice cores. Dashed lines represent regression lines Heterogeneity On 23 February the abiotic and biotic conditions, i.e. bulk salinity, brine volume, temperature, chl a, primary production and bacterial carbon demand, were measured in top and bottom sections of the sea ice cores (n = 10) along a 10 m transect (Table 1). There 0.2 0.5 1 0.3 1.5 2 22..88 2 7 4 23 7 4 3 3355 4 4400 22 277 PP BCD Feb Ma r Apr Sea ice and snow depth (cm) O 2 conc. (ȝ mol O 2 l –1 melted sea ice) PP , BCD (mg C m –2 d –1 ) PP, BCD (ȝ g C l –1 d –1 ) 110 PhD thesis by Dorte Haubjerg Søgaard Søgaard et al.: Autotrophic and heterotrophic activit y in Arctic sea ice 45  ߨ Thomas DN, Lara RJ, Eicken H, Kattner G, Skoog A (1995) Dissolved organic matter in Arctic multi-year sea ice during winter: major components and relationships to ice characteristics. Polar Biol 15:477–483 Trodahl HJ, Buckley RG (1990) Enhanced ultraviolet transmission of Antarctic sea ice during the austral spring. J Geophys Res 17:2177–2179 ߨ Vézina AF, Demers S, Laurion I, Sime-Ngando T, Juniper SK, Devine L (1997) Carbon flows through the microbial food web of first-year ice in Resolute Passage (Canadian High Arctic). J Mar Syst 11:173–189 Weeks WF, Ackley SF (1986) The growth, structure and properties of sea ice. In: Untersteiner N (ed) The geophysics of sea ice. NATO ASI Series Ser B Physics. Plenum Press, New York, NY, p 9–164 Weller G, Schwerdtfeger P (1967) Radiation penetration in Antarctic plateau and sea ice. In: Polar meteorology. World Meteorol Org Tech Note 87:120–141 Editorial responsibility: Graham Savidge, Portaferry, UK Submitted: January 8, 2010; Accepted: September 27, 2010 Proofs received from author(s): November 26, 2010 111 PhD thesis by Dorte Haubjerg Søgaard PAPER V Polar Biology 34:1157 – 1165, doi: 10.1007/s00300-011-0976-3 D.H Søgaard • P.J. Hansen • S. Rysgaard • R.N. Glud Growth limitation of three Arctic sea ice algal species: eff ects of salinity, pH, and inorganic carbon availability Sea ice diatom (Fragilariopsis sp.) Photo: Diana W. Krawczyk. 112 PhD thesis by Dorte Haubjerg Søgaard ORIGINAL PAPER Growth limitation of three Arctic sea ice algal species: effects of salinity, pH, and inorganic carbon availability Dorte Haubjerg Søgaard •Per Juel Hansen • Søren Rysgaard •Ronnie Nøhr Glud Received: 14 October 2010 / Revised: 18 January 2011 / Accepted: 19 January 2011 / Published online: 3 March 2011 ÓSpringer-Verlag 2011 Abstract The effect of salinity, pH, and dissolved inorganic carbon (TCO 2 ) on growth and survival of three Arctic sea ice algal species, two diatoms (Fragilariopsis nana and Fragilariopsis sp.), and one species of chlorophyte (Chlamydomonas sp.) was assessed in controlled laboratory experiments. Our results suggest that the chlorophyte and the two diatoms have different tolerance to fluctuations in salinity and pH. The two species of diatoms exhibited maximum growth rates at a salinity of 33, and growth rates at a salinity of 100 were reduced by 50% compared to at a salinity of 33. Growth ceased at a salinity of 150. The chlorophyte species was more sensitive to high salinities than the two diatom species. Growth rate of the chlorophyte was greatly reduced already at a salinity of 50 and it could not grow at salinities above 100. At salinity 33 and constant TCO 2 concentration, all species exhibited maximal growth rate at pH 8.0 and/or 8.5. The two diatom species stopped growing at pH [9.5, while the chlorophyte species still was able to grow at a rate which was 1/3 of its maximum growth rate at pH 10. Thus, Chlamydomonas sp. was able to grow at high pH levels in the succession experiment and therefore outcompeted the two diatom species. Complementary experiments indicated that growth was mainly limited by pH, while inorganic carbon limitation only played an important role at very high pH levels and low TCO 2 concentrations. Keywords Arctic Sea ice algae Salinity pH TCO 2  In situ succession patterns Introduction Sea ice is permeated with pores and brine channels, which host a unique microbial community. The total brine channel volume of sea ice typically ranges between 1 and 30% depending on salinity, temperature, and ionic composition of the brine fluid (Weeks and Ackley 1986). When the temperature decreases, the thermodynamic phase equilibrium drives the sea ice toward a lower brine volume with higher salinities (Cox and Weeks 1983). Thus, the temperature and brine of sea ice are interrelated. At brine temperature between -1.9 and -6.7°C, the brine salinity may range from 34 to 108 (Gleitz et al. 1995). However, when sea ice is exposed to temperatures below -20°C, the brine salinity can be well above 200 (Cox and Weeks 1983). In the summer when sea ice melts, the salinity of the brine can be as low as one-third of normal sea water, e.g., salinity \10 (Ryan et al. 2004). Brine salinity also fluctuates vertically within the sea ice, with the lowest salinities usually encountered in the bottom sea ice layers (Gradinger 1999; Lizotte 2003; Ryan et al. 2004). Thus, sea ice algae must cope with severe physicochemical stress factors caused by natural variations in salinity. Only a few studies D. H. Søgaard (&)S. Rysgaard R. N. Glud Greenland Climate Research Centre (C/O Greenland Institute of Natural Resources), Kivioq 2, Box 570, 3900 Nuuk, Greenland e-mail: [email protected] P. J. Hansen Marine Biological Laboratory, University of Copenhagen, Strandpromenaden 5, 3000 Helsingør, Denmark D. H. Søgaard R. N. Glud University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark R. N. Glud Dumstaffnage Marine Laboratory, Scottish Association for Marine Science, PA37 1QA Dunbeg, Scotland, UK 123 Polar Biol (2011) 34:1157–1165 DOI 10.1007/s00300-011-0976-3 113 PhD thesis by Dorte Haubjerg Søgaard include investigations into the effect of salinity stress on growth rates of sea ice algae (Grant and Horner 1976; Arrigo and Sullivan 1992; Thiel et al. 1996; Ryan et al. 2004). A study on the sea ice diatoms (Amphiprora kufferathii, Nitzschia, and Thalassiosira Antarctica) isolated from ice cores from Weddell Sea revealed growth at salinities up to 90 at -5.5°C, and the diatoms were found to survive for 20 days at salinities up to 145 (Thiel et al. 1996). Other studies have shown that the growth of different sea ice diatoms from the Weddell Sea ceased at salinities above 50 (Grant and Horner 1976). Furthermore, studies have shown that most flagellate species of algae e.g., chlorophytes, dinoflagellates, and chrysophytes have been reported in the sea ice (Arrigo et al. 2010). These flagellate species is especially found in the top sea ice layer, where the highest salinity and lowest temperatures is encountered. The differences in tolerance between sea ice algal species have been ascribed to various abilities for osmotic acclimations, e.g., production of osmolytes (such as proline), which balances the ionic pressure during changes in salinity (Gleitz and Thomas 1992). Moreover, changes in sea ice salinity and associate factors may be the key drivers for microbial succession in sea ice communities (Mikkelsen et al. 2008). The sea ice algal species that are capable to cope with a broad range of salinity may have an advantage and become dominant in the sea ice community. An understanding of the effect of fluctuating salinities in sea ice brine indicates which factors drive the distribution and succession of sea ice algae and might give important information that can be used to modeling sea ice species succession and carbon dynamics within the brine. Variation in seawater pH levels can also have a marked effect on the growth and survival of sea ice algae. In sea ice, a number of biological and physical processes influence pH. Studies of sea ice have shown that in regions characterized by high primary production, the sea ice brine has considerably reduced concentrations of dissolved inorganic carbon (TCO 2 ) and elevated pH levels as high as 10.0 (Gleitz et al. 1995; Thomas et al. 2001). Furthermore, changes in carbon chemistry alone can result in significant changes in pH of the sea ice brine. One mechanism behind this is CaCO 3 precipitation that can occur at low temperatures (Rysgaard et al. 2007; Dieckmann et al. 2008). Carbonate precipitation will initially lead to a buildup of CO 2 in the brine system leading to a decrease in pH. With time, CO 2 can be transported to the water column through brine drainage. This net export of CO 2 out of the sea ice brine will lead to increased pH in the brine, especially when sea ice starts to melt. In sea water, changes in pH influence the equilibrium of the carbonate system and therefore the inter-speciation of TCO 2 , i.e., CO 2 (aq), HCO 3 - ,CO 3 -2 , which may influence microalgae species succession and distribution (Hansen 2002; Rost et al. 2003; Trimborn et al. 2008). Limitation in the supply of CO 2 due to elevated pH levels may restrict photosynthesis and growth of some algal species (Hansen 2002; Rost et al. 2003; Hansen et al. 2007) and favor species that utilize HCO 3 - as an inorganic carbon source (Korb et al. 1997; Huertas et al. 2000; Hansen 2002). Diatoms have been found to actively take up HCO 3 - and convert it into intracellular CO 2 by extracellular enzymes (e.g., Korb et al. 1997; Tortell et al. 1997). Additionally, diatoms can utilize HCO 3 - directly for carbon fixation through C 4 photosynthesis (Tortell et al. 1997; Reinfelder et al. 2000). However, a previous study has shown that the ability to tolerate high pH is not related to particulate algal groups, but rather is species specific (Hansen 2002). In this study, we investigated the upper limit for growth with respect to salinity, pH, and TCO 2 for three common Arctic sea ice algal species; the diatoms Fragilariopsis nana,Fragilariopsis sp. and the chlorophyte Chlamydomonas sp. The physiological response toward these stress factors are evaluated and discussed in relation to in situ succession patterns. This study is important to understand the factors controlling the growth, survival, composition, and distribution of the sea ice algal communities within the brine and can be used to accurately model the species succession and the productivity of this complex system. Materials and methods Algae species and maintenance of sea ice algae cultures Three sea ice algae were selected for the study (Arrigo et al. 2010). The diatom Fragilariopsis sp. (CCMP2297) and the chlorophyte Chlamydomonas sp. (CCMP2294) originated from sea ice from Baffin Bay and were provided by Guillard National Center for Culture of Marine Phytoplankton (CCMP), and the diatom Fragilariopsis nana (SCCAP K-0637) was isolated from the Labrador Sea and provided by the Scandinavian Culture Collection of Algae and Protozoa, Department of Phycology, University of Copenhagen. The two species of diatoms were selected as representatives for pennate diatoms, which are very common in sea ice (Arrigo et al. 2010). We deliberately chose Fragilariopsis nana because it is a relatively small species (length 8.0–9.4 lm; width 1.9–2.0 lm) and Fragilariopsis sp. because it is somewhat larger diatom species (length 12–16 lm; width 6–10 lm). The chlorophyte Chlamydomonas sp. (length 8–10 lm; width 4.0–6.0 lm) was selected because chlorophytes are common in sea ice as well (Arrigo et al. 2010). 1158 Polar Biol (2011) 34:1157–1165 123 114 PhD thesis by Dorte Haubjerg Søgaard Algal cultures were grown in L1 growth medium (Guillard and Hargraves 1993) based on autoclaved seawater with a salinity of 33. The stock cultures were maintained at 3 ±1°C and 50 lEm -2 s -1 following a light:dark cycle of 16:8 h. Illumination was provided by cool fluorescent lamps, and irradiance was measured using a LiCor 1400 (Li-Cor, NE, USA). Experimental conditions All experiments were carried out at 3 ±1°C and at an irradiance of 50 lEm -2 s -1 following a light:dark cycle of 16:8 h. Only cells from exponentially growing cultures were used for inoculation of the experiments. However, the first 6–10 days were considered as an acclimation period; therefore, cell counts from these samplings were not included in the calculations of growth rates. All experiments were carried out in 62-ml polystylene bottles, except for the pH-drift experiments that were carried out in gas-tight laminated NEN/PE plastic bag (Hansen et al. 2000) fitted with a gas-tight Tygon tube and valve for sampling. All experiments were carried out in triplicates, i.e., each experiment was carried out in three separate bottles. Cultures were kept suspended through the use of a plankton wheel, and an external cooling system was used to prevent heating associated with radiation absorption. The L1 growth medium was selected to make sure that algal cultures were not nutrient limited at anytime during the experiment. Enumeration of cells was carried out using subsamples fixed in acidic Lugol’s iodine (2.5% final concentration), and cells were counted in a Sedgewick-Rafter chamber. Each count was based on at least 400 cells. Growth rates (l) were measured as increase in cell number and were calculated assuming exponential growth: lðd1Þ¼ðln N1ln N0Þ ðt1t0Þð1Þ where N 0 and N 1 are number of cells at time t 0 and t 1 , and t is the difference in time (d) between t 0 and t 1 samples (Hansen 2002). We determined the exponential phase of growth (straight line). Two points, N 0 and N 1 , at the extremes of this linear phase was taken and substituted into the equation (same approach was used for determining the two points, t 0 and t 1 ). All experiments were carried out in triplicates; thus, this was done for each replicate and the mean of the three maximum growth rates was determined. The calculations of the growth rates were corrected for any dilutions. pH values were measured using a Sentron Ò 2001 pH-meter equipped with a Red Line electrode, which is an ISFET Ò sensor (Semiconductor Ion Field Effect Transistor) with detection limit of 0.01. The pH sensor was calibrated (2 point) using Sentron buffers of pH 7.0 and 10.0. The concentration of dissolved inorganic carbon (TCO 2 ) was measured in the growth medium by transferring samples (12 ml) to Exetainer tubes (12 ml Exetainer Ò , Labco High Wycombe, UK) spiked with 20 ll HgCl 2 (saturated solution, 5% w/v) and was measured using a CO 2 analyzer (CM5012 CO 2 Coulometer). Experimental setup Growthrateofsea ice algae atdifferentsalinities In the first set of experiments, growth rates of the three sea ice algae Fragilariopsis nana, Fragilariopsis sp, and Chlamydomonas sp. were measured at different salinities ranging from 5 to 150 (i.e., salinity of 5, 20, 33, 50, 75, 100, and 150). The salinity was adjusted from a salinity of 33 by addition of artificial seawater based on Red Sea salt with known TCO 2 concentrations to the L1 medium. The pH value was kept constant at 8.0 throughout the experiment. If the pH differed by more than 0.03 from the set point, it was adjusted by the aliquot addition of 0.1 M NaOH or HCl. The experiment was initiated with an inoculation of 1,000 cells ml -1 and was allowed to run for minimum 18 d and maximum 20 d. Every second day, pH was measured, and subsamples (1 ml) were taken for enumeration of algae cells. After subsampling, the bottles were refilled to capacity with L1 growth medium (1 ml). The L1 growth medium was at each event adjusted to the correct salinity to prevent salinity in the experimental bottles to drift. Salinity and TCO 2 concentrations were measured initially and at the termination of the experiment. To test the effect of lowered salinity on the growth of the three species of sea ice algae, a second set of experiments was conducted. The algal cultures were grown in L1 growth medium (Guillard and Hargraves 1993) based on autoclaved seawater with a salinity of 75 and a known TCO 2 concentration for a month. The salinity was adjusted from a salinity of 75 to different salinities of 5, 20, and 33 to mimic the transition from cold to melting sea ice. The pH value was kept constant at 8.0 throughout the experiment. If the pH differed by more than 0.03 from the set point, it was adjusted by the aliquot addition of 0.1 M NaOH or HCl. The experiment was initiated with an inoculation of 1,000 cells ml -1 and was allowed to run for a minimum of 18 d and a maximum of 20 d. Growthrateofthe sea ice algae atdifferentpHand TCO 2 In the first set of pH experiments, growth rates of the three species of sea ice algae: Fragilariopsis nana, Polar Biol (2011) 34:1157–1165 1159 123 115 PhD thesis by Dorte Haubjerg Søgaard Fragilariopsis sp., and Chlamydomonas sp. were measured at different pH values ranging from 8.0 to 10.0 (i.e., pH 8.0, 8.5, 9.0, 9.5, and 10.0). The salinity was 33 throughout the experiment. The pH was adjusted by addition of 0.1 M HCl or NaOH to the medium. The experiment was initiated by inoculating 1,000 cells ml -1 and was allowed to run for 20 d. The TCO 2 concentration was, in all instances, 2.4 mM. Every second day, pH of the culture media was measured, and subsamples (1 ml) were taken for enumeration of algae cells. After subsampling, the bottles were refilled to capacity with pH adjusted-L1 growth medium (i.e., pH 8.0, 8.5, 9.0, 9.5, 10.0), and the bottles were remounted on the plankton wheel. If the pH differed by more than 0.03 from the set point, it was adjusted by addition of aliquots of 0.1 M HCl or NaOH. In the pH-drift experiment, Fragilariopsis sp. and Chlamydomonas sp. were inoculated (1,000 cells ml -1 )in media with a pH of 8.0 and initial TCO 2 concentrations of c. 1.2 or 2.4 mM and were allowed to grow into stationary growth phase (up to 26 d). The 1.2 mM TCO 2 concentration medium was obtained by mixing the 2.4 mM L1 growth medium with a very low TCO 2 concentration medium (\0.5 mM). The very low TCO 2 medium was prepared by acidifying the growth medium (to pH \3), followed by heating to 110°C for 30 min and aerating the medium. The pH was then adjusted to 8.0 by the addition of 0.1 or 1.0 M NaOH or HCl (Hansen et al. 2007). The experiment was carried out in gas-tight laminated NEN/PE plastic bags (Hansen et al. 2000). Every second day, the pH of the culture medium was measured, and subsamples were withdrawn for enumeration of algae cell concentration (3 ml) and for measurements of the TCO 2 concentration (36 ml). The NEN/PE plastic bags were not refilled after each sampling. The [CO 2 ?HCO 3 - ] concentrations were calculated from measurements of TCO 2 , temperature, salinity, and pH (Lewis and Wallace 1998). Succession experiment The three sea ice algal species were inoculated in a mixed culture (i.e., 1,000 cells ml -1 ) at a pH of 8.0 and a salinity of 33 and an initial TCO 2 concentration of 2.4 mM. The three sea ice algal species were allowed to grow well into stationary growth phase (up to 22 d). Every second day, pH of the culture media was measured, and subsamples (1 ml) were taken for enumeration of the mixed algae cells. After subsampling, the bottles were refilled to capacity with pH adjusted-L1 growth medium and the bottles were remounted on the plankton wheel. TCO 2 concentration was measured at the initiation and the termination of the experiment to ensure that the concentration was sufficient for algae growth during the experiments. Results Effect of salinity on the growth rates of three Arctic sea ice algae The two sea ice diatoms exhibited similar growth rates as a function of salinity, and no significant differences were observed between acclimation salinities (33 or 75) used in the salinity experiments (Student’s t-test, P[0.05). Maximum growth rates were obtained at a salinity of 33 (Fig. 1a). At salinities above 33, growth rates gradually decreased with salinity. However, growth rates at a salinity of 100 were reduced by 50%, and none of the diatoms could grow at a salinity of 150. At salinities below 33, growth rates of the two diatoms decreased only slightly and they were still quite high at a salinity of 5 (Fig. 1a, b). The two diatom species showed significantly more reduced growth rates at high salinities than at low salinities (Fragilariopsis nana OLS, P=0.005, one-sided and -0.4 -0.2 0.0 0.2 0.4 0.6 52033 50 75 100 150 150 10075 5033205 0.6 0.4 0.2 0.0 -0.2 -0.4 Fragilariopsis nana Fragilariopsis sp. Chlamydomonas sp. Salinity growth rates (d-1) growth rates (d-1) Fragilariopsis nana Fragilariopsis sp. Chlamydomonas sp. A B Fig. 1 Fragilariopsis nana, Fragilariopsis sp., and Chlamydomonas sp. Growth rates of the three sea ice algae as a function of salinity. aSalinity adjusted from 33 to the experimental salinity. bSalinity adjusted from 75 to the experimental salinity. Data points represent treatment means SE ±(n=3) 1160 Polar Biol (2011) 34:1157–1165 123 116 PhD thesis by Dorte Haubjerg Søgaard Fragilariopsis sp., P=0.005). The growth response of the chlorophyte as a function of salinity was similar to that of the two diatoms showing more reduced growth rates at high salinities (Chlamydomonas sp. OLS, P=0.009, onesided) (Fig. 1a). Growth rates of the chlorophyte was greatly reduced already at a salinity of 50 and it could not grow at salinities above 100 (Fig. 1a, b). EffectofpHand TCO 2 limitation on the growthrateofthe three sea ice algae. A very profound effect of the pH was observed on the growth rates of all three species (Fig. 2). All species exhibited maximum growth rates at a pH of 8.0–8.5 (Fig. 2). Above a pH of 8.5, a negative effect of increasing pH was observed on the growth rate of all species. However, all species were still able to grow at half the maximum growth rate at pH 9.5. The diatom species could not grow at pH 10, while the chlorophyte species demonstrated a growth rate of one-third its maximum. The growth rates of the two diatoms were significantly reduced at pH [9.0 (Student’s t-test Fragilariopsis nana, P =0.0066; Fragilariopsis sp., P=0.0061). In the pH-drift experiments of Fragilariopsis sp., the pH reached a maximum of 9.5 and 9.7 in the experiments initiated at a TCO 2 concentration of 1.4 and 2.4 mM, respectively (Fig. 3). Final TCO 2 concentrations in these experiments were 1.0 and 1.5 mM, respectively. For the pH-tolerant species, Chlamydomonas sp., the pH reached 9.8, when grown at initially high and low TCO 2 concentrations (Fig. 3). The final TCO 2 concentration was 1.0 mM in the experiments initiated at a high TCO 2 concentration, whereas the concentrations decreased from 1.4 to 1.0 mM for this species in experiments initiated at a low TCO 2 concentration (Fig. 3). Succession experiment The importance of pH in succession of sea ice algae species was studied using mixed cultures of three sea ice algal species (Fragilariopsis nana,Fragilariopsis sp., and Chlamydomonas sp.) with an initial pH of 8.0 (Fig. 4). All three species grew until pH reached 9.4 to 9.5 on Day 18. At Day 20, the pH had increased to above 9.6, and the two diatoms stopped growing, while the chlorophyte species maintained a positive growth rate. Discussion Growth of sea ice algae at different salinities The ability of sea ice algae to grow within the physiochemical gradient found in the sea ice suggests that the algae are well adapted to cope with fluctuations in light, temperature, salinity, pH, and TCO 2 concentrations. However, salinity has a pronounced effect on growth, photosynthetic efficiency, and metabolism (Misra et al. 2001). Some microalgae are considered euryhaline, since they can adapt to varying external salinities (Hellebust 1985). However, the salinity range over which active growth takes place differs greatly among species, and the physiochemical conditions in the sea ice will provide a selection pressure that influences the final community composition (Ryan et al. 2004). A previous study has indicated that most sea ice algae are more tolerant to reduced, rather than elevated salinities (Bates and Cota 1986). The present study supports the results of Bates and Cota (1986), as the three sea ice algae showed more reduced growth rates at high salinity levels than at low salinity levels. The experiments suggest that the two diatoms have a competitive advantage in sea ice, where brine salinity is greater than 50. These salinity conditions are typically encountered where the sea ice temperature is between -1.9 and -6.7°C (Gleitz et al. 1995). When sea ice melts, the algae are exposed to altered salinities and subsequently the algal growth may be influenced. A previous study showed that diatom species are only slightly affected by decreasing salinities, whereas decreasing salinities may result in substantial losses of ciliates and flagellate species (Garrison and Buck 1986; Ryan et al. 2004; Mikkelsen and Witkowski 2010). In the present study, the three sea ice algal species were exposed to changes in salinity conditions with different initial salinities of 33 or 75 to test the effect of rapid shifts in salinity from high to low on the growth rates. The salinity stress had the smallest effect on the growth rate of the two diatoms compared to the effect on the chlorophyte. This suggests that sea ice diatoms are less affected by -0.4 -0.2 0.0 0.2 0.4 0.6 8.0 8.5 9.0 9.5 10.0 Fragilariopsis nana Fragilariopsis sp. Chlamydomonas sp. pH growth rates (d -1 ) Fig. 2 Fragilariopsis nana, Fragilariopsis sp., and Chlamydomonas sp. Growth rates of the three sea ice algae as a function of different fixed pH levels. Dissolved inorganic carbon (TCO 2 ) concentration was initially between 2.2 and 2.4 mM in the experiment flasks. Data points represent treatment means SE ±(n=3) Polar Biol (2011) 34:1157–1165 1161 123 117 PhD thesis by Dorte Haubjerg Søgaard decreasing salinities and thus may have a competitive advantage during summer and spring thaw when sea ice salinity becomes low. This result compares with previous studies showing that sea ice diatoms dominates during sea ice summer and spring thaw (Palmisano and Garrison 1993; Ika ¨valko and Thomsen 1997; Mikkelsen et al. 2008). Furthermore, the present study shows that some sea ice algal species are better adapted to changes in salinity than other algal species, and thus, the changes in sea ice salinity may drive species succession of sea ice algae. All the experiments were conducted at higher temperatures (3 ±1°C) than the in situ temperatures observed in sea ice (Søgaard et al. 2010). Previous studies have shown that photosynthetic rates in sea ice algae are influenced by temperature (Palmisano et al. 1987; Ralph et al. 2005). This suggests that the growth rates of the three sea ice algae might be overestimated compared to growth rates at in situ temperatures. However, it is a nontrivial task to incubate samples at low bulk salinity at 0 or sub-zero temperature without introducing freezing and thaw artifacts. Tolerance of sea ice algae to elevated pH The effect of high pH on the growth rates of marine planktonic algae is well established. Some species are very sensitive to elevated pH and cannot grow when pH exceeds 8.8, while others still grow at pH above 10 (e.g., Hansen 2002; Lundholm et al. 2004). Several studies have also shown that the tolerance to high pH is species specific, and large differences exist within important marine algal groups, such as diatoms and dinoflagellates (Hansen 2002; Lundholm et al. 2004; Søderberg and Hansen 2007). The knowledge of the effect of high pH on growth rates of sea ice algae is however, very limited. High pH is observed in sea ice with high primary production (Gleitz et al. 1995; Thomas et al. 2001) and thus prevails during spring when irradiance increase (Cota and Horne 1989; Ku ¨hl et al. 2001). In the present study, influence of high pH levels on the growth rate of the three species of sea ice algae was studied at pH levels ranging from pH 8.0 to 10.0 in nutrient-rich growth media. We did not measure the nutrient concentrations in the nutrient rich media during all the experiments, but the amount of nutrients left at the termination of the experiments assuming Redfield stoichiometry documents that nutrients were not limiting at any point during the experiments (see Table 1). In the present study, our results clearly demonstrate that all species were restricted by high pH even at a high initial TCO 2 concentration. Growth rates were significantly reduced for both diatom species at pH [9.0 (Fig. 2). Above pH 9.5, the two sea ice diatoms stopped growing irrespective of TCO 2 , showing that pH had a direct effect on algal growth. Only a limited number of diatoms have been studied with respect to effect of pH on growth; however, among those studied the effect of pH on growth varied (Lundholm et al. 2004). Lundholm et al. (2004) found that smaller diatoms have a higher upper pH limit for growth than larger diatom. In present study, we 0 1 2 3 4 pH 7.5 8.0 8.5 9.0 9.5 10.0 pH TCO2[mM] and CO2+HCO3-[mM] 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 7.5 8.0 8.5 9.0 9.5 10.0 0 1 2 3 4B 02468101214161820222426 0 1 2 3 4D 7.5 8.0 8.5 9.0 9.5 10.0 pH pH TCO2[mM] and CO2+HCO3-[mM] 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 Fragilariopsis sp. Chlamydomonas sp. Cell concentration in 105 [cells ml-1] 7.5 8.0 8.5 9.0 9.5 10.0 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 Time(d) Time(d) 0 1 2 3 4 A 0 2 4 6 8 10121416182022 C Cell concentration pH TCO2 [CO2+HCO3-] Cell concentration pH TCO2 [CO2+HCO3-] Cell concentration pH TCO2 [CO2+HCO3-] Cell concentration pH TCO2 [CO2+HCO3-] Fig. 3 Fragilariopsis sp. and Chlamydomonas sp. Cell concentration in 10 5 , pH, dissolved inorganic carbon (TCO 2 ) and available inorganic carbon [CO 2 ?HCO 3 - ] as a function of time for pH-drift experiments at initial TCO 2 concentration for the two sea ice algae. Initial TCO 2 :(a,b) 2.4 mM and (c–d) 1.4 mM. Data points represent treatment means ±(n=3) 1162 Polar Biol (2011) 34:1157–1165 123 118 PhD thesis by Dorte Haubjerg Søgaard deliberately chose Fragilariopsis nana because it is a relatively small diatom species and Fragilariopsis sp. because it is somewhat larger diatom species. Despite the difference in cell volume, the two diatom species showed the same upper pH limit. The sea ice chlorophyte showed an extreme pH tolerance as only a small reduction in growth rate was observed above this pH level. The results suggest that these sea ice algal species are not limited by inorganic carbon at pH 8.0–9.0 (Fig. 3), a pH level close to that found in sea ice brine (Papadimitriou et al. 2007). However, pH increases in colonized sea ice because of a decline in TCO 2 as a result of photosynthetic carbon assimilation (Thomas et al. 2010). This may affect species such as Fragilariopsis nana and Fragilariopsis sp (Figs. 2,3and 4). Other species such as Chlamydomonas sp. can tolerate much higher pH levels and thus will have a competitive advantage in sea ice with high pH levels (Figs. 2,3and 4). However, this species was limited by low TCO 2 concentrations and thus may be outcompeted by algal species in the sea ice, which are able to grow at high pH levels and very low TCO 2 concentrations. Algae can only utilize CO 2 and HCO 3 - for photosynthesis (e.g., Stumm and Morgan 1996; Korb et al. 1997), and it is well known that the speciation of inorganic carbon species depends upon pH. For instance, at pH 9.3, only half of the TCO 2 is available in the form of [CO 2 and HCO 3 - ]. In the pH-drift experiments initiated at a low TCO 2 , the algae were able to deplete the available inorganic carbon [CO 2 and HCO 3 - ] to a lower limit of 0.45 mM for Fragilariopsis sp. and 0.25 mM for Chlamydomonas sp., assuming equilibrium in the carbonate system (Fig. 3). At those low concentrations of [CO 2 and HCO 3 - ], growth rates of the algal species may have become restricted by carbon, as has been shown previously for dinoflagellates (Hansen et al. 2007). For plankton communities, pH changes have been shown to drive species succession, because many planktonic algae appear to be quite sensitive to high pH (Hansen 2002; Pedersen and Hansen 2003). However, possible role of elevated pH in the succession of Arctic sea ice algae has received little attention. The succession experiment carried out in the present study suggested that elevated pH may well drive species succession, as the pH-tolerant species (Chlamydomonas sp.) out-grew the two sea ice diatoms (Fig. 4). However, how can we be sure that the observed succession pattern in the study is due to pH changes and not due to for instance production of toxic substances (allelochemicals) that affect the growth of the two diatoms? Well, we cannot completely out rule that the chlorophyte exudes allelochemicals, as we did not test this specifically. However, no marine chlorophytes have yet been 0 2 4 6 8 10121416182022 0 0.5 1.5 2.0 2.5 3.0 3.5 1.0 Time(d) Cell concentration in 105 [cells ml-1] pH 0 2 4 6 8 10 12 14 16 18 20 22 7.5 8.0 8.5 9.0 9.5 10.0 B A Fragilariopsis nana Fragilariopsis sp. Chlamydomonas sp. Fig. 4 Succession experiment. aChange in cell concentration in 10 5 of the three sea ice algae species. Fragilariopsis nana, Fragilariopsis sp., and Chlamydomonas sp. as a function of time (d) from inoculation at pH 8.0. bpH as a function of time from inoculation. Data points represent treatment means SE ±(n=3) Table 1 Estimated update of C, N, and P in pH-drift experiments at dissolved inorganic carbon concentration (TCO 2 ) of 2.4 and 1.4 mM in Fragilariopsis nana,Fragilariopsis sp., and Chlamydomonas sp. cultures that have reached maximum cell concentration in L1 medium Algae species Maximum cell concentration (cell ml -1 ) TCO 2 initial 2.4 mM C uptake (lm) N uptake (lm) P uptake (lm) C uptake (lm) N uptake (lm) P uptake (lm) Fragilariopsis nana 4.1 910 5 919 139 8.7 329 50 3.1 Fragilariopsis sp. 2.4 910 5 887 139 8.4 405 61 3.8 Chlamydomonas sp. 4.0 910 5 1,384 209 13.0 398 60 3.8 Addition of N and P to the seawater in L1 medium was 1,111 and 47 lm, respectively. Estimation was based on a Redfield ratio of 106C:16N:1P Polar Biol (2011) 34:1157–1165 1163 123 119 PhD thesis by Dorte Haubjerg Søgaard convincingly shown to produce allelochemicals (see review by Grane ´li and Hansen 2006). Secondly, the growth of the two diatom species in the mixed culture experiment can be explained by pH changes alone, and there are no indications in our data set which suggest that allelochemicals were produced. Our study has only dealt with a few species of ice algae. Thus, much more attention is required in this topic. It would be particularly interesting to study how elevated pH and therefore decreasing TCO 2 affects in situ succession pattern and the growth rates of the algal species in the sea ice. Conclusions Our results suggest that the three sea ice algal species have different tolerance to fluctuations in salinity and pH. The results suggest that the three sea ice algal species were mainly limited by pH, whereas TCO 2 concentrations only played a role at high pH levels and low TCO 2 concentrations. The salinity stress had the smallest effect on the growth rate of the two diatoms compared to the effect on the chlorophyte. This suggests that sea ice diatoms are less affected by salinities changes and thus may have a competitive advantage compared to the chlorophyte in sea ice with rapid fluctuations in salinity. Finally, the fluctuations in pH levels may drive species succession of sea ice algae. The chlorophyte was able to tolerate much higher pH levels than the two diatom species. Thus, Chlamydomonas sp. was able to grow even at high pH levels in the succession experiment and therefore outcompeted the two diatom species. Consequently, sea ice algal species, which are able to grow at fluctuating pH and salinity conditions, may have an advantage in surviving in the harsh environment of forming and melting sea ice. Acknowledgments We thank Anna Haxen and Michael R. Schrøder for assistance in field and laboratory and Thomas Juul-Pedersen, Kristine Arendt and Paul Batty for valuable comments. Furthermore, we want to thank Nina Lundholm from the Scandinavian Culture Collection of Algae and Protozoa, Department of phycology, University of Copenhagen for providing the diatom Fragilariopsis nana. The study received financial support from the Danish Agency for Science, Technology and Innovation, KVUK Commission for Scientific Research in Greenland and is a part of the Greenland Climate Research Centre (GCRC 6507) and a contribution to the Nuuk Basic and Zackenberg Basic programmes. References Arrigo KR, Sullivan CW (1992) The influence of salinity and temperature covariation on the photophysiological characteristics of Antarctic sea ice microalgae. J Phycol 28:746–756 Arrigo KR, Mock T, Lizotte MP (2010) Primary producers and sea ice. In: Thomas DN, Dieckmann GS (eds) Sea ice, 2nd edn. Blackwell Science, Oxford, pp 283–325 Bates SS, Cota GF (1986) Flurorescence induction and photosynthetic responses of arctic ice algae to sample treatment and salinity. J Phycol 22:421–429 Cota GF, Horne EPW (1989) Physical control of arctic ice algal production. Mar Ecol Prog Ser 52:111–121 Cox GFN, Weeks WF (1983) Equations for determining the gas and brine volume in sea ice samples. J Glaciol 29:306–316 Dieckmann GS. Nehrke G, Papadimitriou S, Go ¨ttlicher J, Steininger R, Kennedy H, Wolf-Gladrow D, Thomas DN (2008) Calcium carbonate as ikaite crystals in Antarctic sea ice. Geophys Res Lett 35:L08501. doi:10.1029/2008GL033540 Garrison DL, Buck KR (1986) Organisms losses during melting: a serious bias in sea ice community studies. Polar Biol 6:237–239 Gleitz M, Thomas DN (1992) Physiological responses of a small Antarctic diatom (Chaetocerros sp.) to simulated environmental constraints associated with sea ice formation. Mar Ecol Prog Ser 88:271–278 Gleitz G, Rutgers VD, Thomas DN, Dieckmann GS, Millero FJ (1995) Comparison of summer and winter inorganic carbon, oxygen and nutrient concentrations in Antarctic sea ice brine. Mar Chem 51:81–91 Gradinger R (1999) Vertical fine structure of the biomass and composition of algal communities in Arctic pack ice. Mar Biol 133:745–754 Grane ´li E, Hansen PJ (2006) Allelopathy in harmful algae: a mechanism to compete for resources? In: Grane ´li E, Turner JT (eds) Ecology of Harmful Algae, Ecological Studies series of Springer-Verlag, vol 189. Springer, Chap 15 pp 189–201 Grant WS, Horner RA (1976) Growth responses to salinity variation in four Arctic ice diatoms. J Phycol 12:180–185 Guillard RRL, Hargraves PE (1993) Stichochrysis immobilis is a diatom, not a chrysophyte. Phycologia 32:234–236 Hansen PJ (2002) The effect of high pH on the growth and survival of marine phytoplankton: implications for species succession. Aquat Microb Ecol 28:279–288 Hansen JW, Thamdrup B, Jørgensen BB (2000) Anoxic incubation of sediment in gas-tight plastic bags: a method for biogeochemical process studies. Mar Ecol Prog Ser 208:273–282 Hansen PJ, Lundholm N, Rost B (2007) Growth limitation in marine red-tide dinoflagellates: effects of pH versus inorganic carbon availability. Mar Ecol Prog Ser 334:63–71 Hellebust JA (1985) Mechanisms of response to salinity in halotolerant microalgae. Plant Soil 89:69–81 Huertas IE, Colman B, Espie GS, Lubian LM (2000) Active transport of CO 2 by the three species of marine microalgae. J Phycol 36:314–320 Ika ¨valko J, Thomsen HA (1997) The Baltic Sea ice biota (March 1994): a study of the protistan community. Eur J Protistol 33:229–243 Korb RE, Saville PJ, Johnston AM, Raven J (1997) Sources of inorganic carbon for photosynthesis by three species of marine diatoms. J Phycol 33:433–440 Ku ¨hl M, Glud RN, Borum J, Roberts R, Rygaard S (2001) Photosynthetic performance of surface-associated algae below sea ice as measured with a pulse-amplitude-modulated (PAM) fluorometer and O 2 microsensors. Mar Ecol Prog Ser 223:1–14 Lewis E, Wallace D (1998) Program developed for CO2 system calculations. Environmental Science Division. No. 4735 Lizotte MP (2003) The microbiology of sea ice. In: Thomas DN, Dieckmann GS (eds) Sea ice an introduction to its physics, chemistry, biology and geology. Blackwell Science, Oxford, pp 184–210 1164 Polar Biol (2011) 34:1157–1165 123 126 PhD thesis by Dorte Haubjerg Søgaard Kaartokallio et al.: Bacterial production and cell p r ope r ties in sub-A r tic sea ice 61  ï 3 Ice depth (cm) and 50 nmol lï1 TdR for all sample types, 200, 700, 1500, 2000 and 2500 nmol lï1 Leu for ice and brine samples, and 100, 350, 750, 1000 and 1250 nmol lï1 Leu for water samples. Experimental data were fitted with the single kinetic Michaelis-Menten equation V= Vmax × S/[(Kt + Sn)+S], (where V= incorporation rate, Vmax = maximum incorporation rate, Kt + Sn = apparent halfsaturation constant, i.e. half-saturation constant + natural leucine/thymidine concentration), S= added leucine/thymidine concentration), using SigmaPlot 10 software (SPSS). Saturating concentrations were defined as substrate concentrations where 90% of Vmax was reached and calculated as Vmax90 = 9 × Kt + Sn (Ayo et al. 2001). Isotope dilution was assessed as a ratio of Vmax and Vmeasured at the saturating concentration (van Looij & Riemann 1993, Buesing & Gessner 2003). Incorporation kinetics experiments were conducted with a 16 h incubation at 4 h intervals for all 3 sample types on Day 3 using water from immediately under the ice, and brine and bottom ice samples from Day 3 sampling. Statistical analyses Statistical analyses were done using base, Psych, most 24 cm of ice), ‘bottom ice’, the lowermost 4 cm ice section at ice-water interface, and ‘middle ice’, the ice sections between the other 2 classes. Brine samples from both brine sampling horizons as well as water samples from 2 sampling depths were pooled to form sample classes ‘brine’ and ‘water’, respectively. Physical and chemical parameters Ice temperature, salinity and brine volumes are presented in Fig. 1 and Table 1. Differences in the 3 parameters between sampling days were not statistically significant as verified by the KW tests. The ice temperature varied from ï3.8 to ï0.8°C, displaying typical near-linear profiles increasing with ice depth (Fig. 1). Ice bulk salinity was significantly higher in bottom ice compared to upper and middle ice (KW 2 = 17.64, p < 0.001, Wp-h both p < 0.008). Calculated brine volumes were generally below 10% except in the bottom ice. The underlying water had median salinity of 33.1 with small temporal variability. Inorganic and organic nutrient concentrations are presented in Table 1. Both DOC and DON concentrations were higher in bottom ice compared to middle and upper ice (KW, DOC: 2 = 8.39, p = 0.015, DON: Vegan and MASS packages of R software (R Devel2 = 11.89, p < 0.003). NO3 concentrations were sigopment Core Team 2011). Differences between more nificantly higher in bottom ice compared to middle than 2 sample types were verified using the Kruskalice (NO ï : 2 = 10.61, p < 0.005) but not upper ice ï Wallis rank (KW) sum test with the pairwise (Wp-h for DOC, DON and NO 3 all p < 0.05). SurprisWilcoxon rank sum post hoc test (Wp-h) and Bonferroni adjustment or, when comparing 2 sample types using Wilcoxon rank sum tests (W). For non-metric multidimensional scaling (NMDS), Spearman’s rank-order correlations 0 between bacterial and environmental parameters were calculated. NMDS was performed on a Bray-Curtis dissimilarity matrix of bacterial parame20 ters with metaMDS wrapper routine included in the Vegan package (Oksanen et al. 2012). Environmental 40 parameters were fitted on the NMDS plot using the function, ef, included in the Vegan package. 60 RESULTS ingly, apart from silicate, brine and ice concentrations of dissolved inorganic nutrients were similar, despite the salinity contrast between bulk ice and T Upper ice Middle ice Bottom ice –4 –3 –2 –1 0 0 2 4 6 8 10 0 10 20 30 40 For analyses, ice core sections were Temperature (°C) Salinity Brine volume (%) divided into 3 classes: ‘upper ice’, the 2 uppermost ice sections (upperFig. 1. Temperature (T), salinity (S) and brine volume (Vb) profiles in ice on Days 2, 4 and 6. The 3 ice layers used are indicated by different shading V b S Da y 2 Day 4 Day 6 [Document text truncated for crawler view.]