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Paper 1.Pdf (1014.Kb) Polar Biol (2011) 34:731–749 DOI 10.1007/s00300-010-0929-2 ORIGINAL PAPER Seasonal microbial processes in a high-latitude fjord (Kongsfjorden, Svalbard): I. Heterotrophic bacteria, picoplankton and nanoXagellates Kriss Rokkan Iversen · Lena Seuthe Received: 23 November 2009 / Revised: 4 November 2010 / Accepted: 8 November 2010 / Published online: 2 December 2010 © The Author(s) 2010. This article is published with open access at Springerlink.com Abstract Temporal dynamics of the microbial food web mode represented a trophic link for organic carbon in time in the Barents Sea and adjacent water masses in the Euro- and space. The microbial food web’s ability to Wll diVerent pean Arctic are to a large extent unknown. Seasonal varia- functional roles in periods dominated by new and regener- tion in stocks and production rates of heterotrophic bacteria ated production may enhance the ecological Xexibility of and phototrophic and heterotrophic picoplankton and nano- pelagic ecosystems in the present era of climate change. Xagellates was investigated in the upper 50 m of the high- latitude Kongsfjorden, Svalbard, during six Weld campaigns Keywords Microbial food web · Seasonal · Arctic · between March and December 2006. Heterotrophic bacte- Bacteria · Picoplankton · NanoXagellates ria, picoplankton and nanoXagellates contributed to ecosys- tem structure and function in all seasons. Activity within the microbial food web peaked during spring bloom in Introduction April, parallel to low abundances of mesozooplankton. In the nutrient-limited post-bloom scenario, an eYcient micro- Arctic water masses are currently subjected to climate- bial loop, fuelled by dissolved organic carbon from abun- induced alterations likely to inXuence marine ecosystems dant mesozooplankton feeding on phytoplankton and and biogeochemical pathways (e.g. Arctic Climate Impact protozooplankton, facilitated maximum integrated primary Assessment 2004). Basic knowledge on structure and func- production rates. A tight microbial food web consisting of tion of arctic ecosystems is thus crucial for predicting heterotrophic bacteria and phototrophic and heterotrophic future changes. Seasonal variations in physical and chemi- picoplankton and nanoXagellates was found in the stratiWed cal properties of arctic water masses are likely to aVect and water masses encountered in July and September. Micro- alter the marine ecosystem and its ecological impact in the bial stocks and rates were low but persistent under winter same location over a year. In addition, the heterogeneous conditions. Seasonal comparisons of microbial biomass and nature of high-latitude seas (Carmack and Wassmann 2008) production revealed that structure and function of the implies that structure and function of marine ecosystems microbial food web were fundamentally diVerent during may diVer between geographical areas throughout the pan- the spring bloom when compared with other seasons. While Arctic region. the microbial food web was in a regenerative mode most The Barents Sea and adjacent water masses in the Euro- of the time, during the spring bloom, a microbial transfer pean Arctic represent a complex combination of Atlantic and Arctic water masses (e.g. Loeng et al. 1997) under an Arctic light regime. Even though this productive and dynamic shelf-sea (e.g. Falk-Petersen et al. 2000; Wassmann 2002) is well-studied, the ecological signiWcance of the K. Rokkan Iversen (&) · L. Seuthe microbial food web in the European Arctic in general is still Department of Arctic and Marine Biology, relatively unknown. However, the literature available Faculty of Biosciences, Fisheries and Economics, University of Tromsø, Breivika, 9037 Tromsø, Norway suggests that the microbial food web is as important in spe- e-mail: [email protected] ciWc ecological events, such as the vernal bloom and the 123 732 Polar Biol (2011) 34:731–749 post-bloom situation, in the Arctic as reported for temperate seas (e.g. Hansen et al. 1996; Verity et al. 1999; Rat’kova and Wassmann 2002; Not et al. 2005; Hodal and Kristiansen 2008; Sturluson et al. 2008). Datasets covering several physical, chemical and biological parameters over an Arctic year in the European Arctic have, however, not earlier been generated. The high-latitude Kongsfjorden (79°N), situated at the west coast of the Svalbard Archipelago, represents a unique site for seasonal studies of the marine ecosystem in the European Arctic. This is due to the combination of infrastructure, accessibility, arctic climate and association with the Barents Sea. The marine ecosystem in Kongsfjor- den is well known with regard to hydrography, mesozoo- plankton and higher trophic levels, while knowledge on the microbial food web is still insuYcient (Hop et al. 2002). While additional investigations of microbial organisms and processes have been conducted recently (e.g. Jankowska et al. 2005; Wiktor and Wojciechowska 2005; Thingstad et al. 2008; Piwosz et al. 2009; Wang et al. 2009), comprehensive knowledge on seasonal dynamics is still missing. Fig. 1 Schematic overview over the main current system around the The overall objective of this study was to conduct an Svalbard Archipelago, with the West Spitsbergen Current (WSC) transporting warm Atlantic water along the west coast of Svalbard. The annual sequence of studies of the microbial food web in the present study was conducted in Kongsfjorden (station KB3, 78°57ЈN, high-latitude Kongsfjorden, situated in the European Arctic. 11°56ЈE) at the west coast of Spitsbergen In order to cover both the polar night and midnight sun period, basic elements of the microbial food web and its physical and chemical environment were investigated in Hydrography, nutrients, and carbon compounds Kongsfjorden from March to December 2006. More spe- ciWcally, we investigated (i) the signiWcance of the micro- Water samples from six discrete depths were collected with bial food web for ecosystem structure and function in 10-l Niskin bottles (1, 5, 10, 15, 25 and 50 m). Vertical pro- Kongsfjorden during diVerent seasons and (ii) how sea- Wles of salinity and temperature (°C) were measured with a sonal variations in the physical and chemical environment CTD (SBE 19+). Subsamples for nutrient analyses (nitrate, inXuenced the microbial food web with regard to diVerent nitrite, phosphate and silicate) were frozen and later ana- microbial organism groups and their role in carbon cycling. lysed by standard seawater methods applying a Flow In this paper, we focus on heterotrophic bacteria, pico- Solution IV analyzer (OI Analytical, US), calibrated with plankton and nanoXagellates, while dinoXagellates, ciliates reference seawater (Ocean ScientiWc International Ltd., and mesozooplankton are presented elsewhere (Seuthe UK). Due to the small amounts of nitrite, nitrate and nitrite et al. accepted). combined are in the following called nitrate for simplicity. For analysis of particulate organic carbon (POC), tripli- cate subsamples (100–1,500 ml) were Wltered on pre- Method combusted Whatman GF/F glass-Wbre Wlters (450°C for 5 h), dried at 60°C for 24 h and analysed on-shore with a Study site and sampling programme Leeman Lab CEC 440 CHN analyzer after removal of car- bonate by fuming with concentrated HCl for 24 h. Kongsfjorden is a glacial fjord situated at the west coast of Duplicated water samples for analyses of dissolved Svalbard (79°N, 12°E; Fig. 1). This study was conducted at organic carbon (DOC) were Wltered on burned Whatman station KB3, located close to the settlement of Ny-Ålesund GF/F glass-Wbre Wlters (0.7-m pore size) and frozen in Kongsfjorden (depth 300 m; Fig. 1). The station was (¡20°C) in 15-ml acid-washed Nalgene vials in all months, sampled during six Weld campaigns in 2006 (March 18, except March. In March, samples of unWltered proWle water April 25, May 30, July 4, September 16 and December 2) were frozen (¡20°C), and consequently, total organic car- covering both spring, summer, autumn and winter condi- bon (TOC) was measured for this month. DOC concentra- tions. tions for March were thus estimated from the TOC and 123 Polar Biol (2011) 34:731–749 733 POC concentrations. All samples were measured three functional group into the following size classes of Xagel- times in a SHIMADZU TOC-VCPH/CPN analysator. lates: (a) 2–5 m, (b) 5–10 m and (c) 10–20 m. The latter deviation was done to increase the resolution in the estima- Chlorophyll a and primary production tion of biomass and related estimates. Quantitative analyses of other phytoplankton groups and Triplicated subsamples of proWle water were Wltered onto taxonomic analyses of all phytoplankton groups were per- Whatman GF/F glass-Wbre Wlters and Whatman membrane formed on Primulin-stained samples according to methods Wlters (pore size 10 m) to measure total and size-fraction- described in Rat’kova and Wassmann (2002). Many algae ated (10 m) chlorophyll a (chl a), respectively. Filters could be identiWed to genus or to higher taxa only. were immediately frozen for 5–7 days (¡20°C). Prior to The biovolume of algae and protozoan cells was calcu- Xuorometrical analysis (Parsons et al. 1984), samples were lated from the volumes of appropriate stereometrical bodies extracted in 5 ml methanol for 12 h at room temperature in (Smayda 1978). The carbon content of phytoplankton and the dark without grinding. The Xuorescence of the extract dinoXagellate cells was estimated according to Menden- was measured with a Turner Design Fluorometer (Model Deuer and Lessard (2000). For aloricate and loricate ciliates, 10-AU), calibrated with pure chl a (Sigma). the biomass was estimated using a volume to carbon conver- Primary production (PP) was measured in situ using the sion factor of 0.19 pg C m¡3 (Putt and Stoecker 1989) and 14C method (Parsons et al. 1984). Aliquots of proWle water 0.053 pg C m¡3 (Verity and Langdon 1984), respectively. were collected in polycarbonate bottles (320 ml) and For picoplankton (0.2–2 m) and the three size classes of labelled with 4 Ci (Wnal concentration 0.0125 Ci ml¡1) nanoXagellates, the median in each size spectrum was 14C-bicarbonate, before incubation at respective depths for applied when estimating bulk carbon biomass.
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