DeepSea
W67-0645(95)00101-8
Research II, Vol. 43. No. 2-3. pp. 491-515.1996 Copyright 0 1996 Elsevier Science Ltd
Printed in Great Britain. All rights reserved 0967-0645/96$15.00+0.W
Stocks and dynamics of bacterioplankton in the northwestern Sargasso Sea CRAIG A. CARLSON,*§
HUGH
W. DUCKLOWt
and THOMAS
D. SLEETERS
(Received 4 October 1994; in revisedform 30 May 1995; accepted 12 September 1995)
Abstract-We examined seasonal variations of bacterioplankton stocks and distributions in the upper 250 m in the Sargasso Sea near Hydrostation S and the U.S. JGOFS Bermuda Atlantic Timeseries Study (BATS) site during 1987-1988 and 1991-1994. Mean vertical profiles of bacterial abundance, cell volume, and ‘H-thymidine and ‘H-leucine incorporation rates varied seasonally, and distribution patterns were correlated with physical mixing in the fall and winter. Conversion factors for ‘H-thymidine and ‘H-leucine incorporation were determined empirically to be 1.63 and 0.078 x IO” cells mol-‘, respectively. Integrated bacterial biomass and production within the euphotic zone were low compared to other oceanic sites and ranged between 241-411 mg C m-’ and 1l-36 mg C m-’ day-‘, respectively. Seasonal variation in bacterial biomass and production was observed; however, the range of variation was less than two-fold despite a five-fold range in primary production. Bacterial biomass (BB): phytoplankton biomass (PB) ratios remained high during the summer and fall, with bacterial biomass dominating the chl u-C estimates at times, and BB:PB ratios decreased in the winter and spring due to increased phytoplankton production. Low bacterial production (BP):phytoplankton production (PP) ratios were observed for all seasons. Although BP:PP ratios were low, growth efficiencies observed in this region indicate that carbon flux through seasonal BP could account for 17-> 100% of seasonal PP. The small response of bacterial production during and after a phytoplankton bloom may indicate that the majority of dissolved organic carbon (DOC) that accumulates in post bloom conditions is of semi-labile quality, resulting in slow bacterial oxidation of DOC. Copyright 0 1996 Elsevier Science Ltd
INTRODUCTION Bacterioplankton are a significant component of the planktonic community, responsible for mediating the transformation of dissolved organic matter (DOM) into particulate organic matter (Azam and Hodson, 1977). The majority of work regarding bacterioplankton dynamics has been conducted in coastal, upwelling and inshore waters (Ducklow and Carlson, 1992). In addition several studies have been conducted in high nutrient oceanic systems such as the North Atlantic (Ducklow et al., 1993; Li et al., 1993), Subarctic Pacific (Kirchman et al., 1993), the Equatorial Pacific (Ducklow et al., 1995; Kirchman et al., 1995)
*Horn Point Environmental Laboratory, Box 775, Cambridge, MD 21613, U.S.A. tThe College of William and Mary, Virginia Institute of Marine Sciences, Box 1346, Gloucester Point,VA 23062, U.S.A. SMinistry of the Environment, Government Administration Building, 30 Parliament St., Hamilton HM-12, Bermuda. §Present address: Bermuda Biological Station for Research, Ferry Reach GE 01, Bermuda. 491
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and the Southern Ocean (Karl et al., 1991). Data from oligotrophic systems are few but indicate that bacterial biomass (BB) is equivalent to or can even dominate phytoplankton biomass (PB) at times (Fuhrman et al., 1989; Cho and Azam, 1990; Li et al., 1992; Caron et al., 1995; Roman et al., 1995). However, little is known about growth, production and dynamics of bacterioplankton in these systems. Meteorological forcing of the Sargasso Sea near Bermuda results in winter convective mixing and vernal restratification. As a consequence, this oceanic region is seasonally oligotrophic, exhibiting marked seasonal variability in primary production (PP) and other biogeochemical processes (Menzel and Ryther, 1960; Lohrenz et al., 1992; Michaels et al., 1994). However, to assess the fate of organic matter in these waters, it is essential to understand the microbial dynamics. In a model of the oceanic mixed layer that utilized Menzel and Ryther’s (1960) PP data, Fasham et al. (1990) speculated that bacterioplankton as well as phytoplankton would undergo a bloom sequence. However, they cautioned that annual production of bacterioplankton could not be validated due to a lack of data. Here we present data that address the seasonal variability of bacterial biomass and production over several years in the open ocean near Bermuda. The present study was conducted in the northwestern Sargasso Sea in conjunction with Hydrostation S cruises, U.S. JGOFS Bermuda Atlantic Time-series Study (BATS) cruises and several independent cruises. In 1987-1988, a preliminary study was conducted to establish the annual cycle of bacterial abundance in the surface waters of the Sargasso Sea. In 1991-1994, seasonal visits in the vicinity of Hydrostation S (32”lO’ N, 64”30’ W) and BATS (31”50’ N, 6410’ W) allowed us to perform short time-series studies to inv-zstigate daily variability of bacterial properties within each season. Our objectives were: (i) to estimate an appropriate factor to convert 3H-thymidine and 3H-leucine incorporation into bacterial cell production; (ii) to determine the seasonal variability in stocks and distributions of bacterial abundance, biovolume, and 3H-thymidine and 3H-leucine incorporation; (iii) to examine the cycles of BB and bacterial production (BP) in the context of the annual cycles of PP and dissolved organic carbon (DOC). METHODS The 1987-1988 data were collected during cruises aboard the R.V. Weatherbird to Hydrostation S approximately every 2-3 weeks. The 1991-1994 data were collected during several seasonal cruises aboard the R.V. Cape Hatteras, R.V. Endeavor, and the R.V. Weatherbird II in the vicinity of the U.S. JGOFS BATS station and Hydrostation S. Sample collection
From 1987 to 1988, water column samples were collected for bacterial abundance using 5 1 Niskin bottles attached to a stainless steel hydrowire. From 1991 to 1994, samples for bacterial abundance, cell volume and incorporation rates were collected from the surface 250 m of the water column with a CTD rosette equipped with 10-30 1 Niskin or Go-F10 bottles (both General Oceanics, Miami, FL) on a Kevlar line. The spring mechanism in the Niskin bottles was either an epoxy-coated spring or silicone tubing. In preliminary experiments, incorporation rates conducted with water collected from trace metal-free Go-F10 bottles were similar to water collected with these special Niskin bottles. Samples were drawn directly from the Niskin or Go-F10 bottle spigot to the sample bottle or
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incubation vessel. Polyethylene manipulation.
gloves were worn at all times during
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live sample
Abundance and biovolume measurements
Samples for bacterial abundance and biovolume were preserved with particle-free 25% glutaraldehyde (final concentration of 1.0%) and stored at 4°C until slide preparation, which occurred within 4 days of collection. Three to 10 ml samples were filtered onto 0.2 pm blackened polycarbonate filters. The poiycarbonate filter was supported by a 3 pm mixed ester filter during filtration to help distribute the cells homogeneously. Samples were stained with acridine orange (final concentration 0.005%) according to Hobbie et al. (1977), mounted on slides in Resolve immersion oil and stored frozen until examination. All samples were enumerated by epifluorescence microscopy using an Olympus epifluorescent microscope or a Zeiss Axiophot at 1613 x with a blue BP 450-490 excitation filter and LP-520 barrier filter. Biovolumes were estimated using a PC 486based Zeiss Vidas Videoplan Image Analysis system, which acquired images from a DageMT1 Nuvicon video camera connected to the Axiophot microscope through a Dage Gen-II image intensifier. The system was calibrated with fluorescent spheres of various sizes (Polysciences Corp.). Cell volumes were calculated using the algorithm of Baldwin and Bankston (1988). At least 200 cells per slide were counted, and 200-500 cells per slide were analyzed for bacterial biovolume. 3H-Thymidine and 3H-leucine incorporation
BP was estimated from [3H-methyl]-thymidine (3H-TdR) and [4,5-3H]-leucine (3H-Leu) incorporation. The procedures followed those of Ducklow et al. (1992). Duplicate 30 ml incubations were amended with methyl ‘H-TdR (Amersham sp. act. > 80 Ci mmol-‘; 10 nM final cont.) and incubated for l-4 h in polycarbonate centrifuge tubes at approximate in situ temperature ( f 2.5”C). Preliminary experiments demonstrated linear uptake of 3H-TdR for at least 4 h in the surface water, at 60 m and at 250 m depth (data not shown). The incubations were stopped by pouring the live sample into a second tube containing formalin (final concentration 1% by volume). Fifteen milliliter aliquots of killed sample were filtered through a 0.22 pm cellulose nitrate filter and extracted with four rinses of ice cold 5% trichloroacetic acid (TCA) and three rinses of ice cold 80% ethanol (ETOH). The protocol of Wicks and Robarts (1987) was used to measure incorporation of 3H-thymidine into DNA. The remaining 15 ml of sample were extracted with 0.25 N NaOH (final cont.) then chilled on ice for not longer than 48 h. Samples were then neutralized and the DNA was precipitated with ice-cold 100% TCA (20% final cont.). The sample was then filtered through a cellulose nitrate filter, rinsed three times with Mini-Q water, four times 1:1 phenol-chloroform and finally three times with ice cold 80% ETOH. 3H-Leu incorporation (Kirchman et al., 1985) was estimated in parallel incubations of 15 ml samples amended with 1 nM of 3H-Leu (Amersham sp. act. > 140 Ci mmol-‘) and 20 nM of unlabeled leucine. Incubation and extraction with 5% TCA and 80% ETOH were as described above. Samples killed with 1% formalin prior to isotope addition were used as control blanks. The cellulose nitrate filters were dissolved with 1 ml of ethyl acetate prior to the addition of 6 ml of Ultima Gold scintillation cocktail (Packard). Radioactivity was analyzed by a Packard Liquid Scintillation Counter, and corrected with external standard and quench
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curve. Ultima Gold scintillation cocktail yielded optimal count data among several biodegradable cocktails tested for our combination of filters and reagents. Conversion factors Bacterial carbon values were calculated from bacterial abundance and average cellular biovolume at each depth using a carbon conversion factor of 120 fg C prne3. This volumetric conversion factor falls near midrange 8-220 fg C prnd3 estimated for bacterioplankton in the Sargasso Sea near Bermuda (Gundersen et al., 1994). Conversion factors for converting TdR and Leu incorporation to rates of bacterial cell production were determined empirically. Oligotrophic seawater was collected from several stations located between Bermuda and hydrostation S (32”10’N, 64”30’W) in October 1991, May 1992, July 1992, October 1992, March 1993, and January 1994. All stations were positioned 3-12 miles off Bermuda in waters at least 1000 m deep. Water was collected from a depth of approximately 10 m via 12 1Niskin bottles with epoxy coated springs on a CTD rosette or by Go-F10 bottles on Kevlar line. Upon recovery of collection bottles, seawater was transferred to polycarbonate carboys via non-contaminating Teflon tubing. All carboys, Teflon tubing and filtration devices were washed in 5% HCl and rinsed with copious amounts of Mill&Q water prior to experiment. All seawater cultures were prepared by inoculating filter sterilized seawater (filtered through a 0.22 pm filter) with whole water (January 1994), or a 0.8 pm inoculum at a dilution of O-90% (see Table 1). Preparation of the 0.22 pm filtrate began at sea or
Table 1. Summary of conversion factor experiments for ‘H-thymidine and ‘H-leucine in the northwestern Sargasso Sea 1991-1994. Cultures were preparedfrom 10 m water unless stated otherwise. Culture prep. indicates the per cent dilution of the inoculum by the 0.22 umfilteredseawater. Number of datapoints used in the regression of the cumulative parameters cell abundance and isotope incorporation (n) and standard errors ( f s.e.) are given for each experiment
Conversion Factors Experiment Date
Culture Prep.
Treatment
n
October 1991 May 1992
90% dilution 90% dilution 80% dilution 0.8 filtrate 90% dilution 70% dilution 90% dilution 70% dilution 70% dilution -
Control Control
7 12 12
July 1992
October 1992 March 1993 January 1994
Control NJ-J4 50 m Control Control NJ-J4 PO4
Mean S.E. n
10 10 10 9 12 12 11 8 8 8
TdR (10” cell mol-‘) 1.10 0.40 0.60 5.60 0.80 0.80 1.10 4.10 0.2 3.70
1.oo 0.90 0.90
1.63 0.46 13
s.e.
0.10 0.02 0.02 0.60 0.04 0.04 0.10 0.50 0.03 0.40 0.10 0.10 0.10
Leu (10” cell mol-‘)
se
0.030 0.034
0.001 0.000 0.012 0.001 0.002 0.002 0.008 0.006 0.030 0.006 0.007 0.006
0.100 0.030 0.028 0.048 0.100 0.024 0.300 0.100 0.100 0.047 0.078 0.022 12
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immediately upon arrival at Bermuda Biological Station for Research (within 2 h of collection). To minimize contamination and cell breakage, all filtrates were generated by gentle gravity filtration though 142 mm Nuclepore membra-Fil filters and a plastic filtration rig. The potential organic and inorganic contamination from the membrane filters was minimized by flushing the filters with approximately 1.5-2 1 of Milli-Q water then approximately 2 1 of sample water before filtrate collection. The 10 1collection carboy was rinsed several times with filtrate after the filter had been flushed. Cultures of 5-10 1 were incubated in polycarbonate carboys in the dark and swirled frequently. All cultures except, July 1992 and October 1992 experiments, were incubated in upright incubators (Precision Scientific; Chicago, IL) at in situ temperatures. July and October, 1992 cultures were incubated at room temperature that was +2”C of in situ temperatures. Samples were drawn regularly for 4-5 days via the carboy’s spigot. As in the study by Kirchman (1992) various inorganic compounds were added to examine their effects on bacterial growth (Carlson and Ducklow, 1996) and conversion factors. Samples were amended with a single addition of nutrients at the beginning of the seawater culture. There were no nutrient additions to control treatments. Conversion factors were estimated by the “cumulative approach” (Bjornsen and Kuparinen, 1991) in which a time-weighted ratio of cells produced: isotope incorporated was calculated. The cumulative parameters for 3H-TdR and 3H-Leu were regressed against the accumulation of bacterial cells using a model II regression. The last time point used in these regressions corresponded to the last point of logarithmic growth determined from plots of LN cell abundance vs time.
Primary production and chl a
PP and chlorophyll data were obtained from the U.S. JGOFS BATS database (see Knap et al. (1994) for details on protocol). Phytoplankton biomass was estimated using a C:chl a ratio (pg C:pg chl a). In order to account for changes in C:chl a ratio that occur over depth (Li et al., 1992) we converted chl a to biomass using a C:chl a ratio of 44 for the upper 50 m,
a ratio of 20 for depths between 50 m and 100 m and a ratio of 15 from 100 m to the base of the euphotic zone.
Data
Temperature data were collected and processed by Seabird CTD and software for all seasons except fall 1992, during which a Neil Brown CTD was used. The data presented here are from the CTD casts from which bacterial samples were collected. A more detailed description of the surface hydrography of this region of the Sargasso Sea can be found in Menzel and Ryther (1960) Michaels et al. (1994), and Siegel et al. (1995). Statistical analysis
Statistical analyses, including analysis of variance (ANOVA; model II) and linear regression (model II), were performed using Super ANOVA (Abacus Concepts, Inc., Berkeley, CA, 1989). Parameters are described as significantly different when a significance level of 10.05 was met. A posteriori pair-wise comparisons were evaluated with the Student-
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Newman-Keuls pairwise comparison test. Assumptions graphically by plotting residuals vs fitted Y values.
of ANOVA
were verified
RESULTS
Non-specljk labeling of 3H- TdR
The specific incorporation of 3H-TdR into DNA estimated by the phenol-chloroform method averaged 0.79 + 0.01 of the non-specific incorporation estimated from the cold TCA extraction technique (Fig. 1). This estimate is close to the original ratio of 80% assumed in Fuhrman and Azam (1980), suggesting the validity of the thymidine method for measuring growth rates (i.e. DNA synthesis) in these waters. Thymidine and leucine conversion factors
Conversion factors for 3H-TdR and 3H-Leu were determined by regressing the cumulative cell abundance against cumulative isotope incorporation rates. The slopes of these regressions are the factors for converting 3H-TdR and 3H-Leu incorporation into cell production (Table 1). Grazing was minimized in the bacterial cultures by various combinations of filtration and dilution with particle-free water (Table 1). The inorganic nutrient additions did not affect bacterial growth significantly from the control (Carlson and Ducklow, 1996). In the present study, we chose the cumulative approach of Bjsmsen and Kuparinen (1991) in order to maximize the use of all data from the conversion factor experiments. The mean 3H-TdR conversion factor was 1.63 f0.46 x lOi* cells mol-’ (range 0.2-5.6; n = 13).
pmol
I-‘Y’ (cold TCA)
Fig. 1. Relationship between incorporation of exogenous 3H-thymidine into cold TCA-insoluble cell fractions and the purified DNA fraction according to the protocol of Wicks and Robarts (1987). Data was pooled from all seasons and depths over the surface 250 m. This procedure was performed on .70% of the casts conducted from 1991 to 1994 and included all samples collected in the upper 250 m of the water column. The dashed line represents the 1:1 line. The slope is 0.79 kO.01 with an Rs of 0.96; n = 310.
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The mean Leu conversion factor was 0.078 kO.022 x 10’s cells mol-’ (range 0.028-0.300; II = 12). Bacterial production was estimated from the following formula BP = (TdR or Leu) x ICF x biovolume x CCF where BP is the bacterial production (mg C 1-l h- ‘), TdR or Leu is the ‘H-TdR or 3H-Leu incorporation (PM h-l), ICF is the respective isotope conversion factor (see above), biovolume is as determined for each depth in a given season (see cell volume below), and CCF is the carbon conversion factor of 120 fg C prnw3. In six of the eight seasons, the Leu and TdR carbon production estimates over the surface 250 m differed by only l-30%. In winter and summer of 1993, agreement between the two methods was poor. Overall, slopes were usually < 1, suggesting that our Leu conversion factor values led to lower estimates of BP than TdR (Table 4). A mean of the TdR and Leu based estimates was used to estimate bacterial carbon production. Annual pattern of bacterial abundance A preliminary study was conducted during 1987-1988 to assess the annual pattern of bacterial stocks. Data were collected approximately every 2-3 weeks from Hydrostation S. Over 95% of the bacterial cells were not associated with particles and appeared to be free living. A composite of all the 1987-1988 data in the surface 200 m is presented as single annual cycle in Fig. 2(A). Bacterial stocks were elevated in the surface 100 m and ranged between 3 and 7 x lo8 cells 1-l throughout the year. Bacterial abundance began to increase in late March, and a subsurface bacterial abundance maximum of 6-7 x lo8 cells 1-l was maintained from April through August between 25 and 75 m. This subsurface bacterial abundance maximum was located well above the summer chlorophyll maximum, which resides at approximately 100 m in these waters (Menzel and Ryther, 1960; Michaels ef al., 1994). In 1987, integrated stocks in the surface 100 m showed a high degree of variability, but there was a general pattern of increased bacterial abundance in the early summer and decline in the fall (Fig. 2(B)). There was less than a two-fold increase in bacterial stocks in the surface 100 m in 1987-1988. A comparison was made between the high temporal resolution data set collected in 1987 and the U.S. JGOFS BATS data set for 1991-1993 (see Knap et al., 1993, 1994 and 1995 for details on protocol). The BATS public data set shows similar patterns (Fig. 3) to those observed in 1987-1988, with little seasonal variability in bacterial abundance and the development of a subsurface maximum in spring and maintained through the summer. These similarities indicate a repeatable seasonal cycle in bacterial abundances. Details of the BATS data set are discussed by Gundersen et al. (in prep.). Vertical distribution of bacterial properties The objective of this portion of the study was to evaluate average seasonal profiles of bacterial abundance, 3H-TdR and 3H-Leu incorporation rates in the vicinity of the BATS station and Hydrostation S. As in any oceanic system, the presence of mesoscale eddies may alias a discrete-sample time-series (Malone et al., 1993; Siegel et al., 1995). We attempted to reduce the influence of mesoscale features by making repeated measurements over periods of weeks within a sampling period (except for fall 1991 and winter 1992). This should allow our average seasonal profile to represent an integration of the mesoscale variability within
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100
3
V50 a2oo 250 300
JFMAMJ
JAS
OND
JFM’AMJ
JAS
OND
R
Fig. 2. (A) Composite view of the annual cycle of bacterial abundance at Hydrostation S. Samples were collected between January 1987 and March 1988 and have been contoured as a single year’s data for this figure. Bacterial abundances are reported as 10s cells 1-r. (B) Integrated cell abundance (cells 10” m-a) over the surface 100 m at Hydrostation S, 1987.
Fig. 3. Contour plot of the annual cycle of bacterial abundance at BATS from February 1991 to September 1993. Data was provided by the public U.S. JGOFS BATS data set (Knap et al., 1993, 1994, 1995).
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each season. Internal waves and mesoscale eddies may have affected the shape of the upper thermocline from day to day (Michaels et al., 1994); thus the mean temperature profiles presented in Figs 4-7 represent general seasonal profiles. The number of casts conducted for each parameter and the duration of the sampling period within each season are described in Figs 4-7. Samples were grouped by depth interval and changes in bacterial parameters for each season were compared over depth by model II ANOVA. Because of the wide range of conversion factors used to convert 3H-TdR and 3H-Leu incorporation rates into cell production and bacterial cells into carbon (Ducklow and Carlson, 1992) we decided first to present actual measured parameters. The conversion of these parameters to carbon units will be discussed later. Spring profiles
The mean temperature profile for April 1992 shows that the water column was weakly, but completely, thermally stratified (Fig. 4(A)). In the spring, bacterial abundance, TdR and Leu incorporation profiles demonstrated significantly higher values in the surface 80 m and decreased to uniform values by 250 m (Fig. 4(A), (B) and (C)). Cell abundance was not statistically different over depth in the surface 80 m and averaged ca 4 x lo* cells 1-i. 3HTdR incorporation rates showed high day-to-day variability in the upper 80 m and averaged ca 1 pM h- ‘. In addition to exhibiting the highest mean seasonal 3H-Leu incorporation rates within the upper 80 m, the spring profiles also had the largest degree of day to day variability. This high degree of variability yielded no significant difference in average incorporation rates in the surface 80 m despite a range of 21-34 pM h-i. Summer 1992 and 1993 profiles
In June-July 1992 and July-August 1993, a shallow mixed layer at 5-18 m formed above the seasonal pycnocline (Fig. 5(A)) During the summers of 1992 and 1993, average cell
Temperature ( ‘C) 20 22 24 26 L
30 Td;R (PM h-1) 2
0
Leu(pMb”)
204060
. . -.,. C
A
c:
Fig. 4. Mean vertical profiles of (A) temperature, (B) cell abundance, (C) ‘H-thymidine and (D) ‘Hleucine for spring 1992 (2-26 April). Solid lines represent mean profile for the given season. Number of casts as follows: abundance: 9; TdR incorporation: 8; Leu incorporation: 8.
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Lem(pMY’)
Fig. 5. Mean vertical profiles of (A) temperature, (B) cell abundance, (C) ‘H-thymidine and (D) ‘Hleucine for summer 1992 (29 June-14 July) and summer 1993 (16 July-20 August). Solid lines represent mean profile for the given season. Number of casts as follows: abundance: 1992,7; 1993,15. TdR incorporation: 1992,7; 1993,16. Leu incorporation: 1992, 7; 1993, 16.
abundance was homogeneously distributed within the surface mixed layer. Below this mixed layer, a subsurface maximum of 7.3 and 7.7 x 10’cells 1-i developed between 40 and 60 m, and then decreased to 1.5 x 10’ cells 1-i by 250 m (Fig. 5(B)). In 1992, a significant subsurface incorporation maximum of ca 0.7 pM h- ’developed between 20 and 100 m and then decreased to 0.07 pM h-’ by 250 m. In 1993, mean incorporation rates increased from the surface to a maximum value of ca 2.1 pM h- ’at 60 m and then decreased to background values by 250 m (Fig. 5(C)). There was no pronounced subsurface maximum in 3H-Leu incorporation rates as was observed with cell abundance and 3H-TdR. Instead, high day to day variability produced little difference in average Leu incorporation rates over depth in the surface 100 m (Fig. 5(D)); however, rates were significantly greater in the upper 100 m compared to deeper water. Fall 199 1 and 1992 profiles
In October 199 1 and November 1992 the surface mixed layer deepened to ca 50 and 70 m, respectively (Fig. 6(A)). In both years, a homogeneous distribution of ca 5.0 x 10’cells 1-i was observed in the upper 80 m and then decreased to ca 2 x 10’ cells 1-l by 250 m (Fig. 6(B)). 3H-TdR incorporation rates were homogeneous at ca 0.7 pM h-i in the surface 60 and 80 m, respectively, and then decreased to a background value of ca 0.1 pM h- ’by 150 m (Fig. 6(C)). 3H-Leu incorporation rates exhibited similar depth profiles as 3H-TdR with homogeneous incorporation rates of ca 15 pM h-’ in the surface 60 and 80 m, then decreased to a background value of ca l-3 pM h-’ by 150 m (Fig. 6(D)). Winter 1992, 1993 and 1994
Deep convective mixing was observed in 1992 and 1993 (Fig. 7(A)). The mixed layers extended below 250 m in 1992. In 1993, the mixed layer deepened and shoaled over the
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Tempdure ( ‘C) 20 22 24 26
0
ioecdLrl 5
10
0
TdR (PM b “1 1 2
so-
jy: 150-
200-
II9
-0. Fdl’ll
-b
Fall’91
250-
Fig. 6. Mean vertical profiles of (A) temperature, (B) cell abundance, (C) 3H-thymidine and (D) 3Hleucine for autumn 1991 (7-8 October) and autumn 1992 (4-17 November). Solid lines represent mean profile for the given season. Number of casts as follows: abundance: 1991, 2; 1992, 9. TdR incorporation: 1991, 1; 1992,9. Leu incorporation: 1991, 1; 1992,9.
sampling period between ~200 m and > 250 m. In 1994, the thermal mixed layer was homogeneous to ca 100 m. General trends in abundance show a homogeneous distribution of ca 4 x lo8 cells 1-i within the surface mixed layer in all three years and then a significant decrease below the surface mixed layer (Fig. 7(B)). A single cast in winter 1991 showed a broad 3H-TdR incorporation subsurface maximum of ca 1.5 pM h- ’ from 60 to 150 m. In 1993, 3H-TdR incorporation rates exhibited high day-to-day variability, averaging cu 1.2 pM h-l, and were not significantly different over 150 m. 3H-TdR incorporation rates were
18
Tenpcmlum ( “2) 20 22 24 26
0
Lcu ( phi b-1) 20 40 60
Fig. 7. Mean vertical profiles of (A) temperature, (B) cell abundance, (C) ‘H-thymidine and (D) ‘Hleucine for the winter 1992 (24 March), winter 1993 (25 February-13 March) and winter 1994 (12-18 January). Solid lines represent mean profile for the given season. Number of casts as follows: abundance: 1992, 1; 1993,6; 1994,3. TdRincorporation: 1992, I; 1993,6; 1994,3. Leuincorporation: 1992, 1; 1993,6; 1994,3.
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only measured below 150 m once, in winter 1993. During this cast, the mixed layer depth was ~200 m; thus the apparent rapid decrease observed in Fig. 7(C) may underestimate incorporation rates between 200 and 250 m occurring in the deeper mixed layer. 3H-TdR incorporation rates in winter 1994 were not significantly different over the upper 100 m. Except for winter 1992, which demonstrated a broad subsurface maximum in 3H-Leu incorporation, there was ca 11 pM h- ’ homogeneously distributed in the top 150 m (Fig. 7(D)). Cell volume
In the surface 250 m, the average seasonal depth-dependent bacterial cell volume ranged from 0.033 to 0.060 pm3 (Fig. 8(A), (B), (C) and (D)). In order to minimize the error associated with biovolume estimates we analyzed 200- > 500 cells per slide. The standard error (se.) associated with this measurement was relatively consistent and averaged kO.002 pm3 (range of 0.001-0.005 pm3; number of slides analyzed = 293). The average cell volume in the winter was significantly smaller than in any other season. Day-to-day variability was high within each season resulting in no clear statistical trend in cell volume over depth. Spring and summer samples showed slight increases in cell size to ca 0.057 pm3 in the upper 20-40 m but did not correspond to abundance maximum. Below 100 m, cell volumes ranged between 0.038 and 0.047 pm3. Except for fall 1992 and winter 1992, which showed slight surface enhancement, the fall and winter data sets showed no significant difference in cell volume over depth. The average fall cell volumes ranged between 0.036 m3 and 0.060 pm3, and the average cell volumes for winter 1993 and 1994 were 0.036 pm3 and 0.050 ,um3, respectively. Interannual variability
Mean bacterial abundance, 3H-TdR, and 3H-Leu incorporation rates were integrated over the euphotic zone (ca 140 m) within each given season and compared interannually
Fig. 8. Vertical profiles of mean bacterial biovolumes in each season. Lines represent mean profile for the given season. The number of casts per season are as follows: spring 1992,5; summer 1992,5; 1993,6; fall 1991, 1; 1992, 3; winter 1992, 1; 1993,s; 1994,2.
Stocks and dynamics of bacterioplankton
Fig. 9.
503
Interannual variability of cell abundance (A) ‘H-thymidine (B) and ‘H-leucine (C) in each given season. The error bars are standard error.
(Fig. 9). There was no cast replication for ‘H-TdR and 3H-Leu incorporation in the fall 1991 nor replication of any bacterial properties in the winter 1992, thus interannual comparisons within these seasons cannot be made with statistical confidence. However, general trends in Fig. 9 show that cell abundance exhibited the least amount of interannual variability within a given season. Both 3H-TdR and 3H-Leu incorporation demonstrated a larger degree of interannual variation, with summer yielding the largest variation (Fig. 9(B) and (C)). 3HTdR and 3H-Leu incorporation in summer 1993 were greater than summer 1992 by 130% and 50%, respectively. Fall values showed little interannual variability. The mean winter integrated rates show that TdR incorporation was lowest in the winter 1994 and similar for 1992 and 1993 (Fig. 9(B)). Area1 rates of ‘H-Leu incorporation were largest in 1992 and showed little difference between 1993 and 1994 (Fig. 9(C)).
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Seasonal variability of bacterial biomass andproduction The seasonal variability of BB and BP is presented in the context of phytoplankton variability (Fig. 10(A) and (B)). BB accumulation exhibited a seasonal pattern in 1992 and 1993, with a maximal buildup in the summer followed by a progressive decrease through the winter (Fig. 10(A)). The range of seasonal variability was remarkably low, with less than a two-fold variation in integrated BB over an annual cycle. In contrast, phytoplankton biomass exhibited up to a six-fold range of variation over the same period. 1600
A 1400
1200
bib; ‘A M J J ASOND
1992 Fig. 10. biomass cycle of standard
J FMAMJ
J ASONDJ
It,
1993
Annual cycle of bacterial variability in the context of phytoplankton variability. Bacterial (bars) and phytoplankton biomass (m) are in panel (A). Panel (B) represents the annual bacterial production (bars) in the context of primary production (0). The error bars are error. The width of the bars corresponds to the duration of the sampling period (lines = single casts).
Stocks and dynamics of bacterioplankton
505
BP was estimated from the average of 3H-TdR and 3H-Leu based production. While there was significant variation in 1992 and 1993, seasonal patterns were not as evident as were the patterns of BB (Fig. 10(A) and (B)). In winter-spring 1993, BP did not increase significantly over the previous fall; however, sampling may have occurred too early in the bloom event to have observed a significant bloom response. The highest BP of any season occurred during summer 1993. Low phytoplankton biomass and production, as well as the low resolution of between season sampling, make it difficult to reconcile this large increase. Bacterial growth rates The mean bacterial growth rates within the euphotic zone were derived by dividing integrated production by integrated biomass. Data for all years were grouped into seasons, and mean growth rates and generation times are presented in Table 2. Highest growth rates were observed in the spring after restratification of the water column. Growth rates progressively decreased through fall and began to increase again during bloom events in 2 of the 3 years. The seasonal range of generation time was less than two-fold, 7.5-12.4 days. DISCUSSION Conversion factors One of the most difficult problems in the analysis of bacterial data sets is arriving at accurate estimates of biomass and biomass production. There are no universally accepted conversion factors used to convert bacterial abundance to carbon biomass or 3H-TdR and 3H-Leu incorporation into carbon production (Ducklow and Carlson, 1992; Caron et al., 1995). Equally there is no single conversion factor available to convert chl a to carbon biomass (Li et al., 1992, 1993). The choice of a specific conversion factor can greatly influence the interpretation of a data set. For these reasons we have first presented all data in untransformed units so the reader can compare the raw units with other data sets. When ever possible we have generated our own conversion factors or have picked literature values derived from work conducted in the Northwestern Sargasso Sea. Because significant changes in average bacterial biovolumes were observed from season to season and a positive relationship between cell C and cell volume has been demonstrated in several studies (Bratbak, 1985; Bjomsen, 1986; Nagata and Watanabe, 1990) we felt it was more appropriate to apply a cell-volume based carbon conversion factor to estimate BB Table 2. Mean seasonal bacterial growth rates and generation times in the euphotic zone of the northwestern Sargasso Sea. Datafor each season were pooledfrom 1991 to 1994
Sampling Period
n
Spring Summer Autumn Winter
8 22 10 10
p’ (day-‘)
0.096 0.079 0.057 0.070
s.e.
Generation time+ (days)
s.e.
0.007 0.004 0.002 0.006
7.5 9.6 12.4 10.9
0.56 0.73 0.44 1.18
‘p = euphotic zone integrated ( cz 140 m) BP / BB. +G = In 21~.
506
C. A. Carlson et al.
than to apply a single C cell-’ conversion factor. There is, however, a wide range of conversion factors presented in the literature, ranging from 50 to 560 fg C prnm3. (See Ducklow and Carlson, 1992 and Christian and Karl, 1994.) We have chosen the conversion factor of 120 fg C prnT3, which is relatively conservative compared to estimates of 560 fg C prnm3 (Bratbak, 1985), although it is a midrange value determined for bacterioplankton in the Sargasso Sea near Bermuda (Gundersen et al., 1994). Another vexing problem is the inability to differentiate via epifluorescent microscopy between bacterial cells and a portion of small prochlorophytes cells (Chisholm et al., 1988) due to similar cell size and shape. Cells that were obviously larger than bacteria were excluded from cell counts and biovolume estimates, yet bacterial cell abundance data most likely included small prochlorophytes cells. However, based on integrated seasonal prochlorophyte abundances in the Sargasso Sea (Olson et al., 1990) we estimate that prochlorophytes comprised less than 10% of our integrated bacterial abundances for each season. Because our biomass estimates were determined from cell size and abundance and because cells obviously larger than bacteria were excluded from image analysis, only the inclusion of bacterial sized prochlorophytes in our bacterial cell abundance estimates, not biovolume, would bias our biomass estimates. Thus we suggest that our biomass estimates may have been overestimated by approximately 10% due to the inclusion of prochlorophytes. Li et al. (1992) found that the phytoplankton C:chl a ratio (pg C:pg chl a ) varied with depth in the Sargasso Sea and estimated the C:chl a ratio to be approximately 44 in the surface 50 m and 15 below 100 m. In addition to these conversion factors, we used a C:chl a ratio of 20 between 50 and 100 m to estimate phytoplankton biomass (determined from Fig. 8 in Li et uf., 1992). Li et al. (1992) used flow cytometry to count individual cells to account for the phytoplankton C. Their surface C:chl a ratio of 44 was almost identical to the ratio used by Cho and Azam (1990) for the oligotrophic Pacific which was determined by the 14C--chllabeling technique (Redalje and Laws, 1981), and fell within the range of 10-91 reported by Bidigare et al. (1990) for the surface 50 m of the Sargasso Sea. Malone et al. (1993) also observed a similar decrease in the C:chl a ratio with the i4C:chl a method averaging 50 in the surface to 20 at the 1% light level. The C:chl a values derived by Li et al. (1992) in the Sargasso Sea were similar to those of Christian and Karl (1994) derived from the oligotrophic U.S. JGOFS time series station off of Hawaii, and we felt these conversion factors were appropriate to apply to our data set. While larger C:chl a ratios have been reported for surface waters, cu 80-100 in open ocean systems (Ducklow et al., 1993; Caron et al., 1995; Goericke and Welschmeyer, 1993); we have chosen to apply the relatively conservative carbon conversion factors of Li et al. (1992) to compare estimated phytoplankton C to bacterial C, which was also calculated with a conservative carbon conversion factor. Comparison of thymidine and leucine based incorporation rates
While the 3H-TdR and 3H-Leu incorporation techniques have proven to be sensitive and practical for field application (Fuhrman and Azam, 1980, 1982; Kirchman et al., 1985, 1986) the results are often difficult to interpret because measured uptake rates need to be converted to carbon units for meaningful biogeochemical comparisons. Several problems associated with these methods, including non-specific labeling (Wicks and Robarts, 1987; Hollibaugh, 1988; Brittain and Karl, 1990; Torriton and Bouvy, 1991) and isotope dilution (Pollard and Moriarty, 1984; Chrzanowski, 1988; Simon and Azam, 1989; Riemann and
Stocks and dynamics of bacterioplankton
507
Azam, 1992), make the use of theoretical factors to convert 3H-TdR and 3H-Leu incorporation into respective DNA and protein production dubious. However, the multiplication of measured uptake rates by empirical conversion factors is an approach that corrects for methodological errors assuming the same methods are used in generating conversion factors and in situ measurements (Kirchman et al., 1982). Several different approaches have been used to generate empirical conversion factors (see Ducklow et al., 1992). In the present study, we choose the cumulative approach of Bjornsen and Kuparinen (1991) to maximize the use of all data from the conversion factor experiments. The TdR and Leu conversion factors derived from this study fit well within the range empirically derived from other oceanic sites, i.e. 1-4x lo’* cells moi-’ for TdR and 0.055-0.180 x 10” cells mol- ’for Leu (see Kirchman, 1992 and citations within). TdR and Leu incorporation rates may not give equivalent values of bacterial production due to unbalanced growth of bacterioplankton (Kirchman et al., 1985; Chin-Leo and Kirchman, 1990); however, over longer timescales the two methods yield similar estimates (Chin-Leo and Kirchman, 1990; Kirchman, 1992). As a result of poor agreement between the 3H-TdR and 3H-Leu production estimates in several seasons (Table 4), we arrived at a conservative estimate of bacterial carbon production by taking the mean of TdR and Leu carbon production rates. This approach has been used in several studies of oceanic BP and is employed to remove extreme bias from either method (Ducklow et al., 1995; Kirchman et al., 1994, 1995). Comparison of bacterial stocks and isotope incorporation rates with other oceanic regions To avoid confounding the comparison of measured bacterial properties with the uncertainties of applied conversion factors, we have compared mean euphotic zone values of bacterial abundance, 3H-TdR and 3H-Leu incorporation rates with recalculated values from several other oceanic regions (Table 3). Bacterioplankton in the northwestern Sargasso Sea rank among the lowest in mean euphotic zone abundance and isotope incorporation rates. The low 3H-TdR incorporation rates were only matched by those observed by Kirchman et al. (1993) in the subarctic Pacific and are at least two-fold lower than any other ocean region presented here. Bacterial growth rates (Table 2) are also among the lowest growth rates reported in oceanic regimes. Bacteria-phytoplunkton
relationships
Biomass. The patterns of bacterial and phytoplankton biomass were almost completely out of phase, with BB maxima coinciding with phytoplankton biomass minima and vice versa (Fig. 10(A)). The increase in BB in the summer may be a result of relaxed grazing pressure. Roman et al. (1993) found that smaller zooplankton (< 200 pm) that preyed on small phytoplankton and protozoa were more prevalent in the summer compared to spring. Removal of small protozoa may alleviate grazing pressure on bacterioplankton, resulting in an accumulation of biomass. Accumulation of bacterial cells also was observed over depth profiles, resulting in a repeatable annual feature of a subsurface maximum forming between the spring throughout the summer (Figs 2,3 and 5(B)). A slight salinity maximum near 50 m has been observed in the summer seasons near the BATS station (Siegel et al., 1995); thus the possibility of horizontal advection influencing bacterial abundance profiles and integrated biomass concentrations cannot be ruled out.
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C. A. Carlson et al.
Table 3.
Summary
qfmean euphotie zone bacterial cell abundance, ‘H-thymidine and 3H-leucine incorporation for several open ocean studies.* Means with ranges presented in parenthesis
Depth (m)
Region North Atlantic 47”N 2o”W North Atlantic 40”N 47”W North Atlantic 45”N 41”W Equatorial Pacific
50
100
$22) 9.5
100
12
120
5.6 (3.6-9.7) 7.1 (3.1-11.0) 19.5 9.1-36.8
80
Subarctic Pacific Arabian Sea
35-l 10
Gulf Stream front
SO-120
Gulf Stream ring Sargasso Sea
Cell Abundance (108cel11-‘)
25-50 140
‘H-Thymidine (pmoll-’ day-‘) 121 (74-l 80) 63 99
‘H-Leucine (nmol I-’ day-‘) 1.59 (0.72-2.56) 1.12
Reference Ducklow et al. (1993) Li et al. (1993)
2.75
(2Gl) (8Y8) 168 (S&608)
0.63 (0.30-0.92) -
Kirchman et a/. (1993)
-
Ducklow et al. (1993)
Ducklow et al. (1995)
Borsheim (1990) (3.11116.4) 6.8 (2.6-9.0) 4.5 (3.0-6.2)
(1230)
-
Ducklow (1986)
(237-:40) (7z47)
0.41 (0.21-0.69)
This study
*These values are water column averages determined by dividing euphotic zone standing stocks and rates by depths.
Previous studies have demonstrated that BB can contribute the largest percentage of living particulate carbon present in the water column of oligotrophic oceans (Dortch and Packard, 1989; Fuhrman et al., 1989; Cho and-Azam, 1990; Caron et al., 1995; Roman et al., 1995). These findings appear to be consistent with biomass ratios observed during the summer and fall seasons (Table 5); however, as Li et al. (1992) suggested, this ratio is significantly lower during bloom events (Table 5, Fig. 10(B)). In a situation where bacterioplankton comprise a large percentage of the plankton biomass for an extended period of time, Fuhrman et al. (1989) suggested that bacterial growth was necessarily slower Table 4. Statistics for linear regressions of ‘H-leucine based estimates of bacterial production on ‘H-thymidine based estimates. Slopes of 1 indicate the estimates are equal
Season
n
Slope*
se.
Autumn 1991 Winter 1992 Spring 1992 Summer 1992 Autumn 1992 Winter 1993 Summer 1993 Winter 1994
8 7 80 79 98 64 161 30
1.31 0.74 1.01 ,1.04 0.83 0.25 0.38 0.78
0.12 0.20 0.08 0.07 0.05 0.03 0.03 0.10
*All slopes were significant at the ~~0.05 level.
0.95 0.73 0.67 0.74 0.72 0.44 0.54 0.67
509
Stocks and dynamics of bacterioplankton Table 5.
Summary of euphotic zone biomass and biomass production for bacteria andphytoplankton in the Sargasso Sea near Bermuda
Biomass (mg C m-*)
Season
Bacteria
Phytoplankton*
Autumn 1991 Winter 1992 Spring 1992 Summer 1992 Autumn 1992 Winter 1993 Summer 1993 Winter 1994
335 331 288 411 325 241 393 251
258 474 572 318 429 1367 367 512
Production (mg C m-* day-‘)
Bacteria/ Phytoplankton+ 1.30 0.70 0.50 1.29 0.76 0.18 1.07 0.49
Bacteria
Phytoplankton*
Bacteria/ Phytoplankton+
17 27 27 20 18 19 36 11
247 1136 565 383 301 717 235 144
0.07 0.02 0.05 0.05 0.06 0.02 0.15 0.08
‘Seasonal means of phytoplankton biomass and production were calculated from data collected at the BATS station during the approximate period as bacterial data was sampled. ‘Bacteria:phytoplankton ratios were calculated from seasonal means and does not reflect bacterial growth efficiency.
that of phytoplankton. In oligotrophic environments bacterial production is supported by in situ supply of dissolved organic matter (DOM). DOM is supplied by many processes including direct exudation from phytoplankton (Lancelot, 1979; Goldman et al., 1992), zooplankton excretion and egestion (Lampert, 1978; Nagata and Kirchman, 1992) and cell lysis from viral infection (Proctor and Fuhrman, 1990; Fuhrman, 1992); however, the absolute magnitude of DOC supply in oligotrophic surface waters ultimately depends on the fixation of inorganic C to organic material via photosynthesis. Low phytoplankton biomass could support higher bacterial biomass only if phytoplankton had a faster turnover rate than bacterioplankton. Here we report that mean euphotic zone bacterial growth rates for each season range from 0.057 to 0.096 day-‘, which are less than or equal to rates observed in the upper 20 m by Fuhrman et al. (1989). Oligotrophic phytoplankton have been shown to grow at rates of 0.5-2 day-’ (Laws et al., 1984) which are 5-35 times faster than growth rates of these oligotrophic bacterioplankton.
than
Production
In 1992, BP appeared to respond to the spring bloom production of DOM by increasing in late winter-early spring, followed by decreased production through the fall. However, only a 1.6-fold increase in BP was observed in response to a five-fold increase in PP in 1992. In contrast, (Ducklow et al., 1993) observed a proportional increase in BP in response to a 2.4-fold increase in integrated PP during the North Atlantic Bloom Experiment (NABE). The BP:PP ratio is used as an index to determine how much carbon fixed by phytoplankton is processed by bacterioplankton. The ratios estimated on seasonal time scales are presented in Table 5. Global average of BP:PP has been estimated to be 0.3 1 (Cole et al., 1988). The BP:PP ratios observed in the oligotrophic Sargasso Sea are significantly lower than these estimates and are comparable to ratios observed in the subarctic and equatorial Pacific (Kirchman et al., 1993; Ducklow et al., 1995; Kirchman et al., 1995). Ducklow et al. (1995) suggested that in quasi steady-state conditions low BP:PP ratios may
510
C. A. Carlson et al.
be the norm. The BP:PP in combination with the growth efficiency of bacterioplankton ultimately determines how much fixed carbon passes through bacteria. Several studies have demonstrated that the often cited bacterial growth efficiency of 50% is not universal and actual growth efficiencies are lower and vary temporally and spatially (Kirchman et al., 1991; Coffin et al., 1993; Kroer, 1993; Biddanda et al., 1994; Carlson and Ducklow, 1996). These determinations were based on observations of bacterial growth and utilization of naturally occurring substrates resulting in lower growth efficiencies than experimental work using labile tracers as substrates. The growth efficiency of bacterioplankton in the Sargasso Sea has been estimated to be ca 14% based on experiments which monitored bacterial biomass increase and DOC depletion (Carlson and Ducklow, 1996). This low growth efficiency in combination with field observations, indicates that seasonal BP could account for 17- > 100% of seasonal PP. Thus, although the ratio of BP:PP might seem low, there is nonetheless great carbon flux through bacterioplankton. Bacterial-phytoplankton
relationship and the DOC cycle
As a consequence of deep convective mixing, there is a flux of nutrients into the euphotic zone resulting in increased pigments, phytoplankton biomass, and PP during late winter/ early spring (Menzel and Ryther, 1960; Michaels et al., 1994; Siegel et al., 1995). Increased DOC production from phytoplankton blooms, in combination with restratification of the water column, results in an annual accumulation of DOC in spring followed by a decrease over the course of the year (Carlson et al., 1994). There is an inverse relationship between BP:PP ratios and bulk DOC stocks (Fig. 11), indicating that the small response of BP relative to PP results in an accumulation of DOC in
-0.14
-0.12
0.1 9: -0.08
Q
-0.06
0.04
Fig. 11. The relationship between DOC concentrations and the ratio of bacterial: primary production. The dark line represents the seasonal DOC concentrations integrated over the upper 250 m of the water column. The grey Iine represents the seasonal BP:PP ratio. Note the inverse relationship.
Stocks and dynamics of bacterioplankton
511
the spring. The reason why the BP:PP ratio remains low during a bloom and its decline is unclear, but it may be a consequence of the mechanisms by which DOC is supplied, i.e. trophic interactions, the composition of the phytoplankton community, the quality of the DOC produced or a combination of the three. Ducklow et al. (1993) suggested that differences observed in response to blooms in the Sargasso Sea and NABE may be due to herbivore impact and bacteria-bacteriovore relationships. Li et al. (1993) have shown vast differences in the composition of the spring bloom phytoplankton regimes for two sites in the North Atlantic. They reported BP:PP ratios to be lower at 40”N 47”W, where the bloom was dominated by picoplankton, and higher BP:PP ratios at 45”N 41”W where the bloom was dominated by both picoplankton and microplankton. Studies by Olson et al. (1990) and Li et al. (1992) have shown that prochlorophytes and Synechococcus comprise a significant portion of the phytoplankton community and dominate the picoplankton abundances in the Sargasso Sea. Malone et al. (1993) demonstrated that picoplankton dominated the phytoplankton production and chl in the Sargasso Sea during summer (1989) and spring (1990) cruises. The large response in BP observed in the NABE project (Ducklow et al., 1993) indicates that DOC buildup from PP, phytoplankton-grazer interactions and particle dissolution supplied a relatively labile DOC source upon which bacterioplankton could grow. Kirchman et al. (1991) observed a reduction of 25% of bulk DOC in the NABE project over the course of 2 days. The absolute concentrations of DOC utilized in this experiment are questionable due to methodological problems in DOC analysis (Suzuki, 1993) but the relative changes still suggest that a large labile portion of the bulk pool was removed. While the bacterial populations utilized this material with low efficiency, the Kirchman et al. (1991) study provided evidence of a post bloom accumulation of a large labile pool. In the Sargasso Sea, the DOC accumulation in the spring appears to be semi-labile and oxidized on timescales of weeks to months (Carlson et al., 1994). Carlson and Ducklow (1996) reported that the most optimal DOC reduction observed in seawater cultures was on the order of only 67% of the bulk DOC pool in Sargasso Sea cultures. Pakulski and Benner (1994) found that carbohydrate concentrations were lowest in the Sargasso Sea compared to several other oceanic regions. They concluded that differences in carbohydrate concentrations between geographical locations may reflect differences in the biogeochemical composition of the plankton community or in the processes which produce and consume these compounds. If the mechanisms by which DOC is supplied produce a low quality substrate, this could help explain the low bacterial response to a relatively large bloom. SUMMARY In the northwestern Sargasso Sea we observed relatively low BB and BP as compared to other oceanic environments. However, BB was a significant percentage of the estimated chl a-C in the euphotic zone, ranging from 76 to 130% in the fall and summer seasons, respectively. High bacterial to phytoplankton biomass ratio appears to be consistent with low bacterial growth rates required to offset the supply rate of DOM by phytoplankton production. The BB:PB ratios dropped considerably in the winter and spring due to the uncoupling of bacterial and phytoplankton biomass production. BP:PP was low in the Sargasso Sea compared to other oceanic systems, but low growth efficiencies indicate that a relatively large portion of PP is processed by bacterioplankton. Vertical distribution patterns of bacterial parameters varied seasonally with the
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C. A. Carlson et al.
appearance of biological processes dominating the distribution in the spring and summer and physical processes dictating distribution in the fall and winter. Seasonal variability in stocks and production was surprisingly low, with stwo-fold annual variation relative to a five- and six-fold variation in PP and phytoplankton biomass. The small response of bacterioplankton to the relatively large variation in PP may be due to the production of semi-labile DOM which is not readily utilized by bacteria on short timescales. To evaluate these results properly, more work needs to be done on the identification of specific organic compounds and their concentrations during an annual cycle. In addition, trophic interactions such as herbivore-phytoplankton and bacteriovore-bacteria dynamics need to be assessed in these waters. Acknowledgements-The authors thank the officers and crews of the R.V. Endeavor, R.V. Cape Hatteras, and R.V. Weatherbird I and II for their help during the cruises. The authors are grateful to John Dacey, Tony Knap, Larry
Madin, Tony Michaels, Dave Siegel and Oliver Zafiriou for providing ship-time; the BATS technicians Ann Close, Rachel Dow, Alice Doyle, Kjell Gundersen, Frances Howse, Rod Johnson, Rhonda Kelley, Jens Sorensen and Tye Waterhouse for their generous assistance in logistics, sampling and providing data. Alison Bryant, David Kirchman, Rachel Parsons, Frank Shiah and Helen Quinby provided helpful discussion in the preparation of this manuscript. This research was sponsored by NSF grants OCE 90-l 5888 to H.W. Ducklow and CA. Carlson. This is CEES contribution 2732, BBSR contribution 1423, and JGOFS contribution 216.
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