Short- and Long-Term Response of Phytoplankton to ENSO in Prydz Bay,Antarctica:Evidences from Field Measurements,Remote Sensing Data and Stratigraphic Biomarker Records

ZHAO Jun,Hans-Ulrich Peter,ZHANG Haisheng,,HAN Zhengbing,HU Chuanyu,YU Peisong,LU Bing,and Thomas S.Bianchi

1)Second Institute of Oceanography,State Oceanic Administration(SOA),Hangzhou 310012,P. R.China

2) Key Laboratory of Marine Ecosystem and Biogeochemistry, SOA,Hangzhou 310012,P. R.China

3) Institute of Ecology,Friedrich Schiller University, Jena D-07743, Germany

4) Department of Geological Sciences,University of Florida,Gainesville FL 32611-2120, USA

? Ocean University of China,Science Press and Springer-Verlag Berlin Heidelberg 2014

1 Introduction

ENSO(El Ni?o-Southern Oscillation)with warm(El Ni?o)and cold(La Ni?a)phases is rooted in the tropical Pacific,involving large-scale ocean-atmosphere interactions,and is the strongest natural climate variation at interannual scales(Changet al.,2007; McPhadenet al.,2006; Philander and Fedorov,2003; Trenberth and Hoar,1997).The impact of El Ni?o and La Ni?a on marine phytoplankton is evolving as a spotlight with great interests in understanding the causes and consequences of ENSO(Chavezet al.,2011; Doneyet al.,2012).Past work has shown that marine phytoplankton growth rate and community structure change are correlated significantly with global warming and El Ni?o/La Ni?a events(Behrenfeldet al.,2006; Rittenouret al.,2000).More recent studies similarly have corroborated that variation of marine phytoplankton primary production is strongly correlated with(extended)Multivariate ENSO Index(MEI or MEI.ext)(Wolter and Timlin,1983,2011); an annual response to El Ni?o/La Ni?a was especially visible(Hernández-de-la-Torreet al.,2003; Mackeyet al.,2010).

The Southern Ocean is a typical High Nutrient-Low Chlorophyll(HNLC)region with a simple marine food chain and remains one of the least studied of all the oceans.We do know that marine phytoplankton primary production and community structure have an important effect on this important global marine ecosystem and appear to be extremely sensitive to climate change(Arrigoet al.,2008; Smetacek and Nicol,2005).The relationship between ENSO events and annual variation of SST,as well as phytoplankton biomass(chlorophyll-a,Chl-a)around the Antarctic Peninsula region and the Ross Sea,has shown more subtle consequences of ENSO variability on marine ecosystem responses(Arrigo and van Dijken,2004; Loebet al.,2009; Reisset al.,2009).These studies highlight that high latitude oceans are sensitive to global impact of ENSO events.Although there is no unified understanding on the biological responses and feedback mechanisms in low and high latitude regions to ENSO,we do recognize the need for a better understanding in the polar oceans,which have been impacted by changes in both oceanic and atmospheric circulations(Sarmientoet al.,2004).While the Arctic has received considerably more attention in recent years(Stein and Macdonald,2004),there is perhaps greater need to better understand marine ecosystem variability associated with ENSO in the Southern Ocean forcing by examining internally consistent short- and long-term multidisciplinary data.

Diagnostic lipid biomarkers in stratigraphic records have been successfully employed to reconstruct historical changes of phytoplankton relative abundance and community structure(Sicreet al.,2000; Bianchi and Canuel,2011).For example,brassicasterol,dinosterol,and alkenones(C37and C38)are indicators of diatoms,dinoflagellates and haptophytes(mainlyEmiliania huxleyi),respectively(Volkman,2006).Relative proportions of biomarkers can be used to reveal phytoplankton community variation,while their bulk concentrations are indicators of phytoplankton production since diatoms,dinoflagellates and haptophytes are dominant algae in the Antarctic phytoplankton community(Wright and van den Enden,2000; Wrightet al.,2010).

In this study,we present 1)annual field measurements of nutrients,Chl-a,phytoplankton abundance and community in austral summer during 1990 to 2002; 2)monthly remote sensing data of Chl-a,particulate organic carbon(POC)and sea surface temperature(SST)in austral summer during 2007 to 2011; and 3)long-term stratigraphic lipid biomarker records during 1900 to 2005 in Prydz Bay,East Antarctica.Then we compare these data with ENSO variation indicated by MEI or MEI.ext.The primary goal of this work is to explore short- and long-term response of phytoplankton to ENSO variability using algal biomarkers in the sediment record.

2 Materials and Methods

2.1 Site Description

Prydz Bay is the largest embayment and a typical marginal ice zone in the Indian sector of the Southern Ocean,East Antarctic Margin,between approximately 69?E and 80?E,70?S and 67?S(Fig.1).It is bounded to the northeast by the Four Ladies Bank,to the southeast by the Ingrid Christensen Coast-Larsemann Hills Oasis,to the south by the Amery Ice Shelf-Lambert Glacier ice drainage system,to the west by Mac.Robertson Land,to the northwest by the Fram Bank,and to the north by the continental shelf edge(Pu and Dong,2003).Prydz Bay is trenched by the Prydz Channel to the north and the Svenner Channel to the east,and the Four Ladies Bank and Fram Bank form partial barriers to deep-water exchange between the bay and the deep ocean.Usually,the bay is covered by sea ice in winter and spring,but several polynyas occur far earlier than is usual for such high latitudes(Smithet al.,1984).The Chinese Zhongshan Station(69?22′24′S,76?22′40′′E)is located on Prydz Bay,and has been in operation for the past 20 years.

Fig.1 Study area located in Prydz Bay,East Antarctica.Black dot shows where sediment core sample III-12(67.49?S,73.00?E)was collected by an undisturbed multicorer during CHINARE-21,2005.

2.2 Sampling and Data Collection

Sediment core(III-12,67.49?S,73.00?E)was collected using an undisturbed multi-corer onboard theR/V Xuelongfrom Prydz Bay on February 2,2005 during the 21stChinese National Antarctic Research Expedition(CHINARE-21)(Fig.1).The sample was then stored frozen onboard(?20℃)and transferred to a ?20℃ freezer in the laboratory for storage,prior to biomarkers and radionuclides analyses.Annual ship-based field data of sea water temperature,dissolved oxygen(DO),Chl-a,nutrients and information of phytoplankton species in Prydz Bay from 1991 to 2002(during CHINARE-6 to 18)were cited from references.Monthly ocean color remote sensing concentrations of Chl-a,POC and SST were from satellite remote sensing database of MODIS.

2.3 Sediment Chronolo gy

Core III-12 was 28 cm in length.It was subsampled at 0.5 cm intervals on the top 1 cm,at 1 cm from 1 to 10 cm,and at 2 cm below 10 cm.The subsamples were then freeze-dried with a Freezone-6 freeze-dryer(Labconco,USA).The210Pb activities(half life = 22.3 years)were determined by alpha particle spectrometry methods according to Chenet al.(2001),and whole down-core excess210Pb(210Pbxs)vales were utilized for calculating sediment accumulation rates based on the calculation methods of Nittrouer and Sternberg(1981)since no surface mixed-layer was observed.Briefly,a constant initial concentration(CIC)model was employed,and the function is

wheresis the sedimentation rate(cm year?1),λis the ra-dioactive decay constant for210Pb(0.0311 year?1),kis the slope(linear coefficient)between natural logarithms of210Pbxsradioactivity(x-axis)and depth(y-axis).

2.4 Biomarker Extraction and GC Analysis

Sedimentary biomarkers were extracted according to Zhanget al.(2012).Briefly,approximately 10 g homogenized freeze-dried sediment was mixed with methylene chloride/methanol(v/v = 3/1),and 20μL(16.19 mg)r-C30alkane(squalane)and 20μL(16.74 mg)n-C19alcohol as internal standards.The mixtures were then extracted for 48 h by Soxhlet extraction with water?bath temperature ca.62℃ and return velocity 4?5 times h1.The extracts were desulfurized by active copper overnight and concentrated by rotary evaporation.After that,10 mL 1 mol L?1KOH/ methanol(v/v = 5/95)solvent were added to alkaline hydrolyse the extracts and to remove acidic components.Then the extracts were centrifuged and re-extracted with hexane for four times.The supernatant was decanted into a rotary evaporator so as to be concentrated,blown to dryness with nitrogen and re-dissolved with hexane.Silica column chromatography method was employed to separate different components.Sterols and ketenes were separated by methylene chloride/methanol(v/v = 95/5),blown to dryness with nitrogen and re- dissolved by hexane to 1 mL vials.They were then transformed into trimethylsilyl derivative(TMS-ether)by BS-TFA [Bis(trimethyl)-trifluoroa-cetamide] for GC analysis.

Fig.2(A)Structures of sedimentary biomarkers:brassicasterol,dinosterol and alkenones(C37 and C38),and(B)their GC chromatograms.

The extract was injected into an HP5890 GC coupled with an elastic quartz capillary column(DB-5,30 m × 0.25 mm i.d.,0.25μm thickness of membrane).The temperature was 260℃ at sample entrance,and temperature-programming was:80℃ at the very beginning,followed by being ramped to 200℃ with a speed of 25℃min?1,to 250℃ with a speed of 4℃ min?1,then to 300℃with a speed of 1.8℃ min?1,and finally to 310℃ with a speed of 5℃min?1to hold isocratically for 2 min before next injection.Hydrogen was employed as carrier gas,with a flow velocity 1.2 mL min?1.Identification of biomarkers was performed according to the retention time of chromatograms,and their quantifications were based on the integration areas of chromatograms using response factor of internal standards(Volkman,2006).The biomarker structures and sample chromatograms are shown in Fig.2.

2.5 Field Measurements of Chl-a

Chl-awas determined by extraction fluorometric method.Briefly,water sample(100 ? 500 mL)was filtered by GF/F filter.Chl-awas extracted by 90% acetone for 24 h under ?20℃,and then determined using Turner Designs Fluorometer.

3 Results and Discussion

3.1 Annual Field Measured Phytoplankton and Environmental Factors(1990-2002),and Their Relationship with ENSO Events

Annual ship-based field data of water temperature,salinity,dissolved oxygen,nutrients,Chl-a,phytoplankton standing stock and community of 7 years within the period from 1990 to 2002 in Prydz Bay,East Antarctica(Table 1)have been employed to study the responding of marine environment and ecosystem change to El Ni?o and La Ni?a events.The interannual variability of the above parameters was significant in the bay according to the data in Table 1 and references therein.During El Ni?o years(March 1991? June 1992 and March 1993? September 1993),the proportion of bacillariophyta increased(84.8% and 78.6%)relative to normal years(77.9% and 73.0%),while those of other algae(pyrrhophyta,chrysophyta,etc.)decreased;Nitzschia barkleyiandNitzschia cylindrusbloomed rapidly and dominated the phytoplankton community(Ning,1998).During La Ni?a years(December 1998 ? July 2000),the proportion of bacillariophyta decreased(61.1% and 70.5%)relative to normal years,while those of other algae increased,withNitzschia curtaas the dominant phytoplankton species(Caiet al.,2003; Liuet al.,2001).Although bacillariophyta dominated the algal community,its proportion varied significantly during El Ni?o or La Ni?a events.Phytoplankton species decreased during both El Ni?o(78 and 95)and La Ni?a(36 and 65)years,compared with normal years(145 and 122)(Caiet al.,2003; Liuet al.,2001; Ning,1998; Zhuet al.,1994).These results suggest that changes in marine phytoplankton composition are linked to both warm and cold climate anomalies(El Ni?o and La Ni?a events)in the Southern Ocean.

Table 1 Field measurements of environmental factors,phytoplankton community and relative abundance in Prydz Bay,1990-2002,and their relationship with ENSO events

In January and February,2002,the normal year between La Ni?a(December 1998 ? July 2000)and El Ni?o(May 2002 ? March 2003)events,the proportion of bacillariophyta was lower(68.6%)than in other normal years(January ? March 1990 and December 1990 ? February 1991),andFragilariopsis kerguelensiswas the dominant species(Liuet al.,2004).Field measurements of phytoplankton species(86)during this period increased sig-nificantly compared to those in previous La Ni?a events,but were still less than those in other normal years(Caiet al.,2003; Liuet al.,2004; Liuet al.,2001; Ning,1998; Zhuet al.,1994).This indicates that the recovery time from these climate fluctuations for these phytoplankton may be quite long in the Antarctic,based on the connections with El Ni?o during May 2002 and March 2003.These results have significant implications for future impacts of climate on Southern Ocean phytoplankton communities.However,further research is necessary to better understand and document the linkages between physical forcings and biotic response times.

Physicochemical factors,such as nutrients,dissolved oxygen and salinity,were also associated with the changes in phytoplankton composition and varied among different years(normal,El Ni?o and La Ni?a).Although we only had a very limited set of data for these parameters,a distinct seasonal pattern was not apparent(Table 1 and references therein).However,salinity was lower in El Ni?o years due to accelerated melting of Antarctic ice shelves and sea ice than in La Ni?a or normal years.This is similar to the situation in the central and eastern tropical Pacific where salinity decreases due to increased precipitation during El Ni?o years(McPhadenet al.,2006).

3.2 Monthly Remote Sensing Data of Chl-a,POC and SST(2007-2011),and Their Response to ENSO Events

Monthly remote sensing observations of Chl-a,POC and SST during 2007 – 2011(austral summer,November– March)were employed to estimate the relationship between phytoplankton production and ENSO events(MEI index,http://www.esrl.noaa.gov/psd/enso/mei/)in Prydz Bay(72? ? 78?E,67 ? 69?S).Chl-aand the other environmental factors have been shown to be sensitive to climate change in Antarctica(Loebet al.,2009).In our study phytoplankton bloom areas and Chl-aconcentrations were different due to ENSO-related SST variation,sea ice variability,and nutrients supply changes between years.This was particularly obvious in polynya regions,which also supports previous work(Arrigo and van Dijken,2003; Tremblay and Smith,2007).During La Ni?a years(shown in cyan color).Phytoplankton blooms occurred in January(both Chl-aand POC were higher than in December and were similar to those in February),and lagged behind the elevated SST.During the El Ni?o year(shown in light red color),phytoplankton blooms occurred in December(both Chl-aand POC were higher than in January and February)and preceded the elevated SST(Fig.3).These results indicated that the relationships between variability of Chl-a,POC and SST probably arose from changes in temperature,stratification and nutrients(e.g.,Fe)in upper Southern Ocean which were mainly ENSO-driven(Arrigoet al.,2008).The mechanism for this kind of relationships still remains unknown,with further research needed to better explore the relationship between ENSO,marine phytoplankton composition and abundance,and SST.

Fig.3 Relationship between remote sensing monthly average concentrations of Chl-a(mg m?3),POC(mg m?3)as well as SST(℃)and Multivariate ENSO Index(MEI,monthly)(http://www.esrl.noaa.gov/psd/enso/mei/)in Prydz Bay(72?–78?E,67?–69?S)during austral summer(Nov.– Mar.),2007 – 2011.El Ni?o event(Jun.2009 – Apr.2010)is in light red color and La Ni?a events(Sept.2007 – Apr.2008,Oct.2008 – Mar.2009 and Jul.2010 – Apr.2011)are in cyan color.

Both Chl-aand SST in Prydz Bay were significantly higher in austral summer during El Ni?o(shown in light red color)compared to La Ni?a years(shown in cyan color).For example,the highest Chl-aconcentration in an El Ni?o year(that in December)was 1.7 to 2.0 folds higher than that in La Ni?a years(January).However,POC did not vary significantly between El Ni?o and La Ni?a years(Fig.3).It indicated that phytoplankton biomass in Prydz Bay was impacted significantly by different ENSO events,and that the timing of phytoplankton blooms and SST was quite different between warm and cold phases of climate change pattern(Loebet al.,2009; Philander and Fedorov,2003; Yuan,2004).

3.3 Long-Term Marine Lipid Biomarker Stratigraphic Records(1900–2005)of Phytoplankton,and Their Response to ENSO Events

Fig.4 Excess 210Pb concentrations(dpm g?1)in sediment core III-12 from Prydz Bay,East Antarctica,collected in Feb.2005 during CHINARE-21.The sediment accumulation rate is 0.17 cm yr?1(R2 = 0.90).

Based on the down-core distribution of210Pbxsactivity in sediment core III-12(Fig.4),the sediment accumulation rate was 0.17 cm yr?1.Thus,each centimeter of the core represented approximately 5.9 years since there was no surface mixed-layer.Accordingly,the top of core III-12 should represent the year 2005,and a depth of 18 cm the year 1899.We have shown here that the long-term variation of marine phytoplankton community structure,with climate change in Antarctica,can be effectively examined by employing historical trends of total concentration and relative proportion of diagnostic lipid biomarker stratigraphic records of core III-12 and MEI.ext index(Fig.5).Over the past century,marine phytoplankton composition and abundance,as indicated by total concentration of sedimentary brassicasterol(diatoms),dinosterol(dinoflagellates)and C37alkenones(haptophytes),showed increasing trends.The relative proportion of diatoms was the highest,followed by dinoflagellates,and haptophytes being the lowest.Previous work has shown that Antarctic phytoplankton community structure varied due to global climate change(Arrigoet al.,1999).Diatoms(low ratio of C to nutrient drawdown)are sensitive to SST variation,and therefore their overall abundance increased significantly with SST increase and was higher than that ofPhaeocystis antarctica(high ratio of C to nutrient drawdown)(Arrigoet al.,1999).Warm or cold climate changes have been shown to impact the utilization of C and atmosphericpCO2(Marinovet al.,2006).The shift in dominant phytoplankton fromP.antarcticato diatoms inferred that the Antarctic marine ecosystem in this bay is showing a response to climate changes.These changes at the level of primary production will likely have significant impacts at higher trophic levels.In fact,recent research on lipid biomarkers in penguin droppings from the Ardley Island,West Antarctica,showed that ENSO impacted significantly on lower plants and soil microorganism as well as penguin community in the Antarctic terrestrial environment(Zhanget al.,2012).

Fig.5 Bulk biomarker concentrations and relative concentrations of individual biomarker in each layer of core III-12,and their relationship with ENSO(indicated by monthly MEI.ext,Wolter and Timlin(2011)).Strong El Ni?o events(May 1997– May 1998,Sept.1982 – Sept.1983,Jun.1972 – Mar.1973 and Apr.1957 – Aug.1958)are in light red color and strong La Ni?a events(Dec.1998 – Feb.2000,Jun.1988 – Jun.1989,May 1975 – Mar.1976 and Oct.1955 – Jul.1956)are in cyan color.

Variations of brassicasterol,dinosterol percentages,brassicasterol:dinosterol ratio,and MEI.ext index showed that phytoplankton community structure changes(e.g.,percentage of diatoms in phytoplankton)were affected by ENSO.When examining downcore changes in such lipids it is also important to consider the effects of remineralization on biomarkers during early diagenesis(Sicreet al.,2000; Volkman,2006).As shown in Fig.5,the relatively high resolution stratigraphic record of lipid biomarker in the top 10 cm of core III-12 revealed similar trends with MEI.ext index.This supports the notion that these biomarkers were stable throughout this section of the core.Based on these lipids,we see that strong El Ni?o(shown in light red color)and La Ni?a(shown in cyan color) events have been recorded in sediments by these biomarkers by high(86.5%,85.1%,83.1% and 78.1%)and low(70.6%,72.5%,81.2% and 62.0%)percentages of sedimentary brassicasterol,respectively.It is important to note that the sedimentary biomarker concentration in each layer was an integration of ca.6 years.Further corroboration of the veracity of the biomarker data is that the annual field data counts agreed with the percentages of diatoms based on biomarker abundance in sediments(Table 1).This change in diatoms likely resulted from differences in ENSO-driven marine environment variability,e.g.,surface water stratification(SST-derived).For example,surface water stratification was more intensified during El Ni?o than during La Ni?a events,since SST was higher(see Fig.3).As stated earlier,the higher abundance of diatoms during El Ni?o(Arrigoet al.,1999)was confirmed by a higher concentration of brassicasterol in the sediment record(Figs.5B,E).It should be noted that there was clearly a lower resolution of sedimentary records at bottom of the core,making the ecological signals of El Ni?o and La Ni?a indistinguishable.Thus,there is a need for higher-resolution sediment sampling in future studies in this region.In general,our results not only infer that diatoms blooms occur during El Ni?o rather than La Ni?a events,but also show that the blooms had an increasing trend with time during the past century.We can only speculate at this time that these changes have occurred from a combination of ENSO and global climate warming(e.g.,intensified surface ocean stratification)(Arrigoet al.,1999; McPhadenet al.,2006).

4 Conclusions

Field measured and remote sensing data as well as sedimentary biomarker records provided comprehensive evidences of both short- and long-term impacts of ENSO on phytoplankton production and community structure in Prydz Bay,East Antarctica:

1)Annual field measured phytoplankton community showed significant ENSO-related succession during 1990 to 2002.Algae species decreased significantly during El Ni?o/La Ni?a years compared to normal years.

2)Monthly variation of remote sensing Chl-aand SST indicated that ENSO impacted the timing of phytoplankton blooms during 2007 to 2011.Phytoplankton blooms(indicated by Chl-a)preceded increases in SST in El Ni?o years,while they lagged behind increases in SST in La Ni?a years.

3)Long-term stratigraphic lipid biomarker records inferred that the proportion of different algae changed significantly between El Ni?o and La Ni?a events.The relative proportion of diatoms increased with dinoflagellates being decreased during El Ni?o,but the reverse occurred during La Ni?a.

Acknowledgements

The authors wish to thank team members of CHINAREs,captains and the crew ofR/V Xuelongfor helping collect samples.This study was financially supported by the National Natural Science Foundation of China(NSFC)(40876104,41306202,41376193,41076134 and 41006118),the scientific research fund of Second Institute of Oceanography,SOA(JT1208 and JG1218),Chinese Arctic and Antarctic Administration Foundation(20110208),and the special fund for polar environment comprehensive investigation and assessment(CHINARE 2014-04-04,2014-01-04 and 2014-04-01).

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