Sea ice algae play a key role in Arctic marine ecosystems. They not only contribute a significant amount to the primary production in early spring, but they can also influence the ice-edge phytoplankton blooms that occur during ice retreat. For the highly productive Bering Sea, some evidence supports the seeding of ice-edge phytoplankton blooms by ice algae, but no quantitative data exists on the relative contribution of different algal species to the spring bloom. In this project I will establish the abundance, biomass, and diversity of ice algal and phytoplankton communities in the Bering Sea across two spring sea ice conditions: ice growth and ice melt. Based on a combination of ice, water, and sediment trap samples, I will be able to estimate the significance of sea ice algae to the ice-edge bloom under these two conditions. Species identification is key to this project and will be accomplished using both traditional light microscopy and scanning electron microscopy (SEM). The results of this study will provide the first ever full assessment of ice algal and phytoplankton diversity in the Bering Sea, and yield crucial information for predicting the impacts of a changing sea ice regime on the Bering Sea system.
Introduction
In this project I will determine the composition and fate of ice algae in the southeastern Bering Sea throughout spring from March to May. Ice algae are a vital component of primary production in Arctic seas, particularly during the early spring when they are the first primary producers to emerge (Alexander and Chapman 1981; Michel et al. 2007). While seeding of ice algae into ice-edge phytoplankton blooms is suggested to play a large role in the Bering Sea and other seasonally ice covered regions (Michel et al. 1993; Lomas et al. 2012), much of the evidence for this has been equivocal (Alexander and Chapman 1981; Jin et al. 2007; Riebesell et al. 1991). Understanding these processes is highly relevant, as ice-edge zones in seasonally ice covered areas are very productive, and often serve as focal points for groups of seabirds and marine mammals (Stirling 1997). The influence of ice algae in these areas is of great importance as the extent and timing of ice melt has tremendous relevance for the Bering Sea ecosystem (Mueter et al. 2009; Hunt et al. 2011). Moreover, shifts in sympagic species diversity could further alter ecosystem processes as suggested previously for Bering Sea zooplankton (Brodeur et al. 2008) and high Arctic phytoplankton (Li et al. 2009).
Ice algae occupy a unique niche in Arctic regions. Comprised primarily of diatoms (Poulin et al. 2011), ice algal assemblages live in the extreme environment within the brine channels of sea ice (Horner 1985). They concentrate within the lowermost decimeters of the ice pack where the nutrient input from the water is highest and brine salinities, which can exceed 100 (Kiko et al. 2008), are relatively low. Ice algae are highly adapted to both the high salinity and low light conditions at the bottom of the ice pack (Manes and Gradinger 2009). They are capable of withstanding over five months in total darkness, allowing them to remain at low abundances within the ice during the winter months, and reinitiate photosynthesis when sufficient light returns (Zhang et al. 1998).
The timing of the ice algal bloom in the spring is crucial. The current results from our Bering Sea study (group led by Gradinger, Bluhm, Iken; UAF) show that Bering Sea ice algae bloom as early as late February, with concentrations three orders of magnitude above phytoplankton values. Ice algae continue to provide the highest food availability throughout the spring while production in the water column remains low (Horner 1985). Our Bering Sea data support the general idea that ice algae contribute 4 to 26% of the total primary production in seasonally ice covered areas (Legendre et al. 1992). Although small, it is essential for the early spring development of many Arctic organisms both in terms of timing and food quality (Sun et al. 2009).
The ultimate fate of ice algae is strongly influenced by the condition of the ice. Spring in the Bering Sea can be divided into two main periods: ice growth, which continues until mid- April (roughly day 100 of the year), and ice melt, which occurs from mid-April until the ice completely retreats midsummer (Gradinger et al., unpubl). Our data demonstrate that similar to other regions (Riedel et al. 2006; Brown and Belt 2012a, 2012b), ice algae may support not only sympagic organisms, but also benthic and pelagic communities in various extent over the season.
During ice growth, the flux of ice algae into the water column is low (Horner 1985; own data). Ice algae are grazed on by a variety of small proto- and metazoans within the ice, including ciliates, dinoflagellates, rotifers, and the larvae of both benthic and pelagic organisms (eg. molluscs, polychaetes) as well as under-ice amphipods (Alexander and Chapman 1981; Werner 2000) and-unique to the Bering Sea-euphausiids (Gradinger et al., unpubl). When the ice begins to melt, ice algae are released into the water column, where they are consumed by pelagic herbivores (Brown and Belt 2012b) or sink directly to the sea floor where they provide a pulse of nutrition that enriches benthic communities (Sun et al. 2009; Brown and Belt 2012a). This spike in algal release from the ice during periods of ice melt is reflected in the isotopic signatures of Bering Sea sediment trap samples, which show an increase in the heavier δ13C associated with ice material over time (Gradinger et al. unpubl). I therefore hypothesize that vertical flux under the Bering Sea ice is dominated by the fecal pellets of pelagic and sympagic grazers up to day 100, followed by direct sinking of ice algae towards the sea floor.
However, released sea ice algae can remain viable in the water column and seed the spring phytoplankton bloom. Ice-edge phytoplankton blooms are common in the spring as the ice melt increases salinity-driven stratification, stabilizing the surface water and maintaining cells above the mixed layer depth (Niebauer et al. 1995). Although these spring blooms are short-lived
(Perrette et al. 2010), they constitute the first major development of primary production in the water column, and are thought to account for 50-65% of the annual primary production in the Barents Sea and on the Bering Sea shelf (Sakshaug 2004). Through seeding, ice algae are capable of influencing the magnitude, duration, species composition, and particularly the timing
of the phytoplankton blooms as they are inoculated into the pelagic community (Alexander and Chapman 1981; Jin et al. 2007; Tedesco et al. 2012). Seeding obsures a portion of the total contribution of ice algae to primary production; when seeding is taken into account, this contribution may be substantially higher than previously estimated. If seeding occurs, phytoplankton composition within the bloom should match the sea ice algal diversity at least in the initial stages of the bloom formation (Guillard and Kilham 1977).
There is considerable evidence for ice algal seeding in the Bering Sea. Model forecasts in the southeastern Bering Sea were far more predictive when seeding was incorporated than when there was no growth of ice algae in the water column (Jin et al. 2007). Several species of ice algae present in the Bering Sea are capable of growing under salinity and light conditions of the surface water environment (Grant and Horner 1976; Alexander and Chapman 1981, respectively). The timing of the ice-edge bloom matches that of the receding ice, and the sporadic information on qualitative inventories of algae in the ice and water column showed significant overlap (Alexander and Chapman 1981). However it is difficult to distinguish whether ice algae found in the water column are viable and actively growing, or are simply present post-melt in the process of sinking.
This project will attempt to make that distinction, and to establish how this fate might differ between species. By quantifying the species composition within ice, water, and sediment trap samples, I will be able to determine the relative proportion of ice algal taxa observed within each strata, and compare these to the proportions predicted by various sinking/seeding scenarios. I will establish which species appear only transiently in the water column versus those that may become inoculated more permanently into the phytoplankton and initiate the spring bloom. During the period of ice growth I expect to find minimal ice algae in the water and sediment trap samples (Figure 1a), and high dissimilarity between phytoplankton and sea ice composition. Ice algae will likely be grazed upon directly by sub-ice fauna like euphausiids and copepods (Iken et al., unpubl.), and will therefore appear primarily in the resulting fecal pellets collected by the sediment traps. During ice melt I predict that ice algae will appear in higher abundances in the water column as they are released from the ice (Figure 1b), and a subset of ice algal species will have a preferentially higher sinking rate compared to other ice algae and phytoplankton species (Brzezinski and Nelson 1988). If there is a corresponding increase in the number of diatom- containing fecal pellets collected, then these missing species were likely subject to preferential grazing by zooplankton. However if the fraction absent from the sediment traps appears at high abundance in the water column, then this assemblage is likely contributing to seeding the phytoplankton.
ICE GROWTH ICE MELT
Figure 1. The fate of ice algae as assessed by sediment trap collection under two different ice conditions. A) Grazing by under-ice fauna during ice formation. B) Sinking, seeding, and grazing during ice melt.
The selective dissolution of the ice algae's silicate frustules in the water column can also result in a change in the apparent species composition, favoring more heavily silicated species when collected at depth. Calculated rates of silicate dissolution range from 18 to 68% in the upper 100 m of the water column (Nelson and Gordon 1982, Southern Ocean; Kohley 1998,
Greenland Sea), however even at the highest dissolution rates the main decrease in lightly silicated diatoms occurred between 500 and 1000 m (Kohley 1998). At 5 m depth, where collection for this project took place, the effects of silicate dissolution are likely to be negligible. I therefore emphasize the significance of biological processes in controlling the biogeochemical processes in the Bering Sea ice edge zone as observed for other Arctic regions (Michel et al. 2002).
Because the accurate identification of algal species is so fundamental for understanding the roles that they play in both ice and phytoplankton communities, both traditional light microscopy and scanning electron microscopy (SEM) will be used to identify cells. Species identification in ice algae has been limited primarily to light microscopy due to the expense and expertise required for SEM analysis, but many species are impossible to distinguish with light microscopy alone (Morales et al 2001). Misidentification can overlook potentially significant variation in species distribution. SEM will also be used to examine the contents of the fecal pellets collected in the sediment traps, and ideally identify those taxa which are being preferentially grazed upon (Schrader 1971). The results will provide clear evidence on the species level whether ice algae are available to the pelagic food web at certain times, and determine their contribution to growth of phytoplankton as well as their fate through mortality and direct sinking.
Justification
Global models of CO2 effects show the greatest temperature increases occurring in Arctic regions (Lemke 2012) associated with cascade of environmental changes including the loss of summer sea ice, earlier spring melt, and an increase in freshwater from both rivers and ice melt (Bluhm and Gradinger 2008). These changes have huge impacts on sympagic systems. Comparative studies in the Chukchi/Beaufort Seas showed a dramatic shift in the species composition in ice algal communities from the 1970s to 2002, linked to increasing temperatures and changing salinity (Melnikov et al. 2002). For the central Arctic, warming temperatures and fresher water drive the dominance of small-celled algal species, which alters the efficiency of energy transfer throughout food webs (Li et al 2009, Tremblay et al. 2012). Rising temperatures also dramatically alter the timing of ice formation and melt. As the succession of ice algal species changes throughout the spring (Horner 1985), earlier melt could release a much different population into the water column both in terms of total biomass as well as diversity. Determining the relative contribution of different ice algal species to the seeding of ice-edge phytoplankton blooms is necessary for understanding how these many changes may alter not only sympagic but also pelagic communities. Understanding species composition of sea ice algae and phytoplankton is also relevant for determining feeding rates of important Bering Sea zooplankton (eg. Euphausiids), as current research indicates preferential feeding of Bering Sea zooplankton on released sea ice algae (Campbell et al. unpubl). Zooplankton are essential prey for everything from fish larvae to bowhead whales (Bluhm and Gradinger 2008), and play a pivitol role in Bering Sea food webs.
The research I propose clearly contributes to the CIFAR's overarching goal of understanding ecosystem functioning in order to gain sufficient knowledge of Alaskan marine ecosystems to forecast their response to both natural and anthropogenic changes. Only by understanding the current role of ice algae in influencing, and possibly initiating, the ice-edge blooms in the Bering Sea will we be able to predict the effects that changing sea ice will have on total spring productivity. The vulnerability of the sea ice regime in the Bering Sea clearly ties this study to the theme of climate change. It further follows the Department of Interior (DOI) Alaska Climate Science Center's first premise for research: Natural variability in the physical environment influences ecosystem structure and services. Differences in ice condition may have substantial impacts on the coupling between ice algal and phytoplankton communities, and in a rapidly changing sea ice environment the repercussions of this could extend even after the spring ice has vanished.
This research also adds an essential component to the collective work of the NSF Bering Ecosystem Study (BEST) and the NPRB Bering Sea Integrated Ecosystem Research Program (BSIERP), which together provided samples for this study. The BEST-BSIERP Bering Sea Project aims to synthsize key aspects of the Bering Sea ecosystem, from the climate and ocean conditions that influence lower trophic levels to the fish, seabirds, marine mammals, and people sustained by the Bering Sea. This study will fill a large gap in the current understanding of coupling between sympagic and pelagic systems using microbiology to explore the ecological question of how ice algae influence Bering Sea phytoplankton blooms. Results of this study will add a key piece to our understanding of the Bering Sea ecosystem as a whole.
Objectives and Approach
This study seeks to fill substantial gaps in our current understanding of ice algal communities in the Bering Sea. The objectives of this study are to:
Determine the diversity of sea ice, phytoplankton communities.
Establish the fate of sea ice algae in the Bering Sea from early spring ice growth until ice melt
Estimate the contribution of ice algal species to seeding the spring ice-edge phytoplankton bloom
The following hypotheses will be tested:
H1:During the period of ice growth, ice algae will primarily be grazed upon directly from the ice, while during ice melt ice algae will be released into the water column.
H2:Sea ice and water column algal diversity is significantly different during the ice growth period, but will be similar during the melt regime.
H3:A subset of ice algal species will remain viable in the water column and contribute to the ice-edge phytoplankton bloom, as evidenced by their absence in sediment trap collections. Other species will be preferentially vertically exported and occur in high concentrations in sediment trap samples.
BEST-BSIERP sample collection - Ice, water, and sediment trap samples were collected for algal analysis from the Bering Sea shelf as part of the BEST-BSIERP Bering Sea synthesis project. Sampling was conducted over three spring periods between March 10 and May 4, 2008- 2010. Sites extended across the Bering Sea pack ice from St. Lawrence Island to the shelf break (58.21-63.48° N; 167.75-178.90° E). I selected five sampling sites from each year, covering a range of ice conditions from ice formation through ice melt. From each site ice cores were obtained using a 10 cm KOVACS ice auger and sectioned into 1-10 cm segments. I will focus my analysis on the bottom 5 cm of the cores, as the highest ice algal accumulations are concentrated there (Horner 1985). Core segments were melted in filtered sea water to prevent osmotic stress during the melt process (Garrison and Buck 1986). Samples were fixed in a 1% final concentration of buffered formaldehyde-sea water solution. Phytoplankton samples were collected using a Kemmerer water sampler from 5 m water depth beneath the ice at each site and were fixed by the same method. Sediment traps 10 cm in diameter with a 1:10 aspect ratio were filled with filtered seawater and deployed beneath the ice at a depth of 5 m for 4-6 hours. Data on the physical environment were also collected at each sampling site including the temperature and salinity of the ice and sub-ice surface water, ice cover, ice thickness, snow depth, and under-ice PAR.
Light Microscopy - All samples will be concentrated using the Utermöhl method (Utermöhl 1958) and analyzed under an inverted Zeiss microscope with phase contrast. Taxonomy will be determined using morphological traits, and will extend to the species level whenever possible (Sournia 1978). I will rely primarily on Lebour's Planktonic Diatoms of the Northern Seas (1930) and Tomas's Identifying Marine Phytoplankton (1997) for taxonomic keys; all names will be verified with the most recent entries in the World Register of Marine Species (WoRMS). Abundance data will be based on the enumeration of representative subsamples, according to the sampling procedures outlined in the UNESCO Phytoplankton Manual (Sourina 1978) with a minimum of 500 cells counted per sample to obtain statistically robust results. I will calculate biomass directly using abundance values and a volumetric correction, applying the equations of Menden-Deuer and Lessard (2000).
Scanning Electron Microscopy - After examination under the light microscope, I will take an ice, water, and sediment sample from each site and verify the species composition using SEM, for a total of 45 samples. I will oxidize the organic material from the diatom frustules by adding potassium persulphate to rinsed samples and heating them from 6-8 hours at 350K (Ma 1978). Cleaned silicate frustules allow for better resolution of the fine features that are essential for identification. I will filter the cleaned diatoms onto a 2.5 µm Millipore® filter and place the sample in a dessicator containing silica gel for 24 hours to ensure that it is completely dehydrated (Ma 1978). I will then fix the filter to an aluminum microscope stub with carbon tape and sputter coat it with gold palladium to increase the conductivity. Cells will be measured, photographed and analyzed under the SEM, and the species identified will be compared to those identified with light microscopy. Any discrepancies will be matched using size classes to determine the species composition. The fecal pellets collected will be dried, fixed and coated, as outlined in Wexels et al. (2003) and their contents will be examined to determine grazing preference based on the identification of intact diatom frustules.
Statistical analysis - I will use PRIMER software with PERMANOVA to analyze the species data. I currently suggest to use a group-average linkage cluster analysis to determine similarities between stations and time periods. Differences between groups of stations and time periods will be assessed using an Analysis of Similarities. To perform the above analyses I will first need to attend a PRIMER workshop to become familiar with the software and capable of applying it effectively to my specific project. Without this instruction, my analysis will be severely limited.
Budget Justification and Other Support
Stipend
No stipend is requested. Tuition and a stipend for the spring of 2013, as well as a stipend for full-time work on sample analysis during the summer of 2013, will be provided through the NSF grant of Dr. Rolf Gradinger. A stipend for the 2013-2014 academic year is requested through a teaching assistant position at UAF in the Department of Marine Science and Limnology.
Travel
Travel costs including per diem are requested for the student PI to attend a PRIMER workshop
in Orlando, FL in August of 2013 (exact date TBD). This workshop will be invaluable to gain the necessary knowledge and skills to make use of the PRIMER 6 software for statistical analysis. Airfare and lodging are based on current estimates. Expenses associated with the workshop including software and registration are based on the costs for the last domestic PRIMER workshop in October 2012.
Services
Funding is requested for the use of UAF's Scanning Electron Microscope in order to process 45 prepared samples from ice, water, and sediment traps. The cost of the SEM is $33 per hour, and it is estimated that each sample will take one hour to set up and photograph for later analysis. The student PI is trained in electron microscopy so funding for a lab technician will not be necessary.
Supplies
Funding is requested to cover the cost of basic supplies necessary for the preparation of samples for the SEM. This includes potassium persulphate for cleaning diatoms, slides and filters for mounting samples, and gold palladium for sputter-coating samples for the SEM. Additional supplies include test tubes, pipettes, cover slips, and labels.
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