[advances in marine biology] advances in marine biology volume 29 volume 29 || autotrophic and...

Autotrophic and Heterotrophic Picoplankton in the Baltic Sea

J. Kuparinen and H. Kuosa

Finnish Institute of Marine Research, PO Box 33, SF-00931 Helsinki, Finland

Preface . . . . . . . . . . . . . . . . I. Introduction . , . . . . . . . . .. . .

A. The Baltic Sea . . . . . . . . . . . . B. Picoplanktonic algae .. .. . . . . ..

11. Methods . . . . . . . . . . . . . . A. Autotrophic picoplankton . . . . . . .. . .

111. IV.

V l

VII.

V11I. IX. X.

B. Bacterioplankton . . . . . . . . . . . . Phytoplankton Succession in the Baltic Sea . . . . . . Autotrophic Picoplankton in the Baltic Sea . . . . . .

Bacterioplankton in the Baltic Sea . . . . . . . .

B. Distribution of bacterioplankton . . . . . . . . Factors Controlling Autotrophic Picoplankton . . . . A. Nutrients and temperature . . , . . . . . . . B. Grazing . . . . . . . . . . . . . . Factors Controlling Bacterioplankton . . . . . . . .

B. Predation control of bacterioplankton . . . . . . Bacteria in the Pelagic Food Web . . . . . . . . Acknowledgements . . . . . . . . . . . . References . . . . . . . . . . . . . .

A. Areal and vertical distribution . . . . . . . . B. Seasonal variation . . . . . . . . . . . .

A. Annual and seasonal variation of bacterioplankton production

A. Nutrient- and carbon-limited bacterioplankton growth . .

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Preface

The introduction of the concept of a size-structured plankton food web (Williams, 1981; Azam et al . , 1983) greatly stimulated studies of aquatic

ADVANCES IN MARINE BIOLOGY VOLUME 29 ISBN 0-12-026129-4

Copyrighr 0 1993 Acudemic Press Limrted All rightc of reproduction in any form reserved

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74 J . KUPARINEN AND H . KUOSA

microbial ecology in the 1980s, and there was an outburst of publications on the oceans, brackish waters and lakes. In addition, the developing techniques of epifluorescence microscopy and the use of radioactive tracers have provided many new data.

This review summarizes results obtained from various locations in the Baltic Sea, which has been described as one of the most intensively

1 0' 1 4' 18' 22' 26' 30'

64'

62'

60'

58O

56'

54'

FIG. 1 . Map of the Baltic Sea. Study sites from which the majority of the data presented in this paper originate are marked on the map: Station 1 = 63"31'N, 19"48'E; 2 = 63"19'N, ZO"17'E; 3 = 59".50'N, 23"lO'E; 4 = S9"3S'N, 23"18'E; 5 = .59"26'N, 21"30'E; 6 = 59"02'N, 21"OS'E; 7 = S8"4S'N, 17"3S'E; 8 = S7"19'N, 20W2'E; 9 = SYlS'N, lS"S9'E; 10 = 55"00'N, IJOOS'E; I I = 54"36'N, lO"27'E.

BALTIC SEA PICOPLANKTON 75

studied aquatic environments (Jansson, 1980). While Baltic Sea hydrography and plankton in general are well known, the category of “most intensively studied” does not yet apply to Baltic Sea picoplankton, on which few publications are yet available. To make good this deficiency we include in this review a substantial amount of new data.

1. Introduction

A. The Baltic Sea

The Baltic Sea is a large brackish water basin with limited connection to the North Sea from the southwestern end (Fig. 1). It comprises several more or less distinct basins or subareas (Fig. 1) with pronounced density stratification prevailing throughout the year (Kullenberg, 1981; Malkki and Tamsalu, 1985). The differences in density between the surface and more saline deep waters restrict exchange between the two layers. The salinity of the surface water decreases from more than 20%~ in the opening to the North Sea to below 1%0 in the extreme ends of the Bothnian Bay and the Gulf of Finland. In the Baltic Proper, surface water salinities are between 6 and 8700.

The primary halocline is at a depth of 60 to 70m in the Baltic Proper

Flc;. 2. Typical distributions of temperature (T), salinity (S) and density (D) in the Bothnian Sea (a), Gotland Deep (b) and the southern Baltic Proper (c).


and 40 to 50 m in the Bornhom Basin (Fig. 2) (Kullenberg, 1981; Malkki and Tamsalu, 1985), below which salinities between 10 and 13%0 are common. This layer receives new water irregularly from inflows through the Danish sounds (Grasshoff and Voipio, 1981). A weak secondary halocline, which separates the frequently anoxic bottom water from the overlying layers, can be detected at a depth of c . 110 and 150m. The extent of this area with insufficient oxygen for macofauna has fluctuated, but is approximately 70,000 km2, mainly in the deep parts of the central Baltic Sea (Andersin and Sandler, 1988). The bottom waters of the Baltic Sea are renewed only after exceptionally strong inflows of North Sea water from the Kattegat. Such inflows occurred in 1913, 1921, 1951 and 1976. Due to the lack of major inflows during the past 14 years, the salinity and density of the deep water have decreased continuously.

In most parts of the Baltic Sea a thermocline develops at depths between 15 and 20m in summer (Fig. 2). The layer of cold water from the previous winter can thus be found between the thermocline and the halocline. These two water masses of about the same salinity mix during the autumn turnover. The western Baltic Sea differs from most of the Baltic Sea in its stratification; due to the water exchange from the North Sea, it is salinity rather than temperature dependent (Fig. 2), and this has implications for the picoplankton in the area (Jochem, 1989).

Another key factor influencing the Baltic Sea picoplankton is the fact that the Baltic is a northern sea, with Arctic characteristics, especially in its northern parts. The winter conditions emphasize differences between the subareas and their biology. The mean number of ice days varies from 190 in the northern end of the Bothnian Bay (Lepparanta et al., 1988) and more than 140 in the easternmost part of the Gulf of Finland to less than 10 days in the central Baltic Proper and in the Kattegat. The mean maximum annual ice thickness varies from more than 70 cm in the northern Bothnian Bay to less than 10cm in the southern Baltic Proper (Climatological Ice Atlas, 1982). These winter conditions contribute to the large seasonal temperature differences, from -0.3 to about 20°C.

The numerous large rivers that bring fresh water and inorganic and organic compounds into the Gulf of Bothnia and to the Gulf of Finland impart special features to the biota of these areas. In particular the Bothnian Sea receives large quantities of allochthonous organics via the rivers (Fonselius, 1986). Due to the terrestrial origin, allochthonous material is highly refractory. Levels from 3.0 to 4.7g/m3 of dissolved organic carbon (DOC) have been reported from the Baltic Proper (Ehrhardt, 1969). Only a small fraction of this pool is liable for bacterial utilization (Bolter, 1981).


B. Picoplanktonic Algae

1. Definition

Pic0 is an epithet applied to pelagic organisms with a size less than 2 pm (Sieburth et al . , 1978). The lower limit of pico-sized organisms, either bacteria, algae or protozoa, is 0.2pm. According to the thorough discussion by Raven (1986), the non-scalable properties of algae constrain their theoretical minimum size to just above 0.2 pm. It seems that in the pelagic environment only viruses and a small fraction of bacteria appear in the femtoplanktonic (0.02 to 0.2 pm) size fraction.

Thus according to the scheme of Sieburth et al. (1978) picoplanktonic organisms are those with cell size under 2 p m . However, this scheme is not totally straightforward when we consider algae. If algae were more or less spherical and if the cells of one species consistently showed very limited variability in size there would be few problems. However, as we know that the form of algae varies considerably, and that the size range of a given species is usually large, the precise definition of picoplanktonic algae in natural phytoplankton communities is difficult.

The distinction of picoplanktonic algae as a separate group has clear ecological grounds. One of the most powerful is that it corresponds to a size fraction of pelagic organisms which is probably not effectively grazed by metazooplankton (rotifers, cladocerans and copepods) and, correspon- dingly, is effectively grazed by protozooplankton (see Section VI). The fraction of organic material produced by picoplankton is thus possibly an indication of the structure of the carbon transfer from primary producers to the higher predators (microbial loop vs. grazing food chain) as discussed by Azam et al. (1983); Ducklow et a f . (1986) and Sherr and Sherr (1988). If we confine ourselves to this ecologically based interest in picoplanktonic algae, the actual upper cell size becomes more a matter of choice than a strict definition. Eventually, it may be possible to choose the upper size limit according to the grazing structure in a given water body, and according to our knowledge of the particle capture ability of zooplankton species.

Small algal cells also have other characteristics in common, such as Slow sedimentation rate and high nutrient uptake capacity. These characteristics are probably not as strictly correlated with cell size as grazing, but their existence further validates the separation of picoplanktonic algae as a single group.

One reason for defining the fraction of the phytoplankton community to be examined in this review of the Baltic Sea is purely practical. Almost

78 J . KUPARINEN A N D H . KUOSA

all the material from the Baltic Sea used for size-fractionated chlorophyll or production measurements has been gathered using 3 pm polycarbonate filters. The reason for this is not really important in the present context - it may be the availability of filters or pure coincidence. At the moment we lack a definitive knowledge of the grazing properties of Baltic Sea zooplankton. Because of the nature of the existing material, and the fact that all size-limits in a phytoplankton community are only loosely defined due to the variable shapes of algal species, rather variable material is included in this review.

2. Organisms

(a) Eukaryotic nlgae A number of eukaryotic algae belonging to variable algal classes are of picoplanktonic size or very near its upper end. As discussed above, there is no reason to regard 2 p m diameter as a strict limit when discussing picoplanktonic algae. Thus according to Thomsen’s (1986) excellent overview the scope of this introduction is also somewhat wider than would be required by pure picoplankton. The actual upper size limit for the species depicted in the following discussion is about 5 pm (“ultraplankton”). Because of their very small size many of these algae have certainly been overlooked in routine work (see Section 11). Their positive identification is possible only by electron microscopy and the routinely used Utermohl method gives few possibilities to count these very small cells in plankton samples.

From the variety of algal classes and genera surveyed by Thomsen (1986). some with relevance to the Baltic Sea can be depicted. Very small Cryptophyceae have been found in the Baltic Sea. Thomsen (1986) presented a photograph of a very small Hemiselmis sp. (aff. anomala) from the Gulf of Bothnia. Hemiselmis virescens Droop is a very small cryptophycean algae (cell size 4-6pm long and about 3 p m wide), which has been recorded in the Western Baltic Sea (Hill, 1992). Of the large class Chrysophyceae, Pedinella tricostata Rouchijajnen (4-6 pm) has been identified from Baltic Sea material (Edler et al., 1984). It is certain that many other small chrysophytes are also present in the Baltic Sea. Similarly, a number of very small solitary flagellated species of Chloro- phyceae are probably to be found in the low salinity waters of coastal areas.

Some very small centric diatoms (Bacillariophyceae) are found in Baltic Sea samples. The taxonomical work, using electron microscopy, has still to be done. From the genus Thalassiosira at least one very small species, T. pseudonunu. is present in the algal flora of the Baltic Sea (Edler et al.,

BALTIC' SEA PICOPLANKTON 79

1984). A very small, solitary Chaetoceros species was also found in many samples, but was probably overlooked like many other small diatoms (Kuosa, unpublished). However, even small Chaetoceros cells are a borderline case in picoiultraplankton. Although the cell size of Chaetoceros may be within the picoplanktonic size range, the seta will enlarge the effective size of the cells in grazing and in fractionation procedures.

The algal class Eustigmatophyceae shows specific ultrastructure and pigment composition. An algal culture maintained at the Tvarminne Zoological Station has been assigned to the genus Nannochloropsis. This small species (2-3pm) may be common in the waters of the northern Baltic Proper, but as is the case in all other small species. we have very little knowledge of its areal distribution and abundance. Micromotzas pusilla (Loxophyceae) is a species within the same size range as Nunnochloropsis sp., but although it is flagellated, it is impossible to differentiate from Ncnnochloropsis sp. in normally preserved phytoplankton samples. Micromonas pusilla has been identified by electron microscopy in samples taken near Tvarminne (Thomsen, 1979). Micrornonas pusilla (1-3 x 1 pm) has a wide distribution in the oceans (Throndsen, 1976), and it may commonly exceed cell numbers of 10h/l (Thomsen, 1986). Another very small species (1.5-2.5 pm) of the class Loxophyceae reported from the Baltic Sea is Pedinomonas micron (Thomsen, 1986). Of the related class Prasinophyceae some small species have appeared in samples studied by electron microscopy (Hallfors and Niemi, 1986). These are: Mantoniella squamata (3-4 pm), Nephroselmis minuta (<4 pm), Pseudoscourfieldiu marina (<4 pm) and Pyramimotzas virginica (<4 pm). According to Hallfors and Niemi (1986) about 25 species of the genus Chrysochromulina (Prymnesiophyceae) have been found from the northern Baltic Proper. The smallest of them belong to the ultraplankton, as does also Prymnesium parvum (Prymnesiophyceae), which is a member of the Baltic Sea phytoplankton (Hallfors and Niemi, 1986).

In the Baltic Sea, as in many other marine areas. there is an almost total lack of integrated data on taxonomical composition and abundance of ultraplankton. The size of an alga is not the only factor determining its role in the ecosystem. The smallest size-class of phytoplankton may contain algae with very different morphological characteristics (flagellated cells, coccoid cells, diatoms with and without seta and cells with scales) and physiology (photosynthetic pigments and phagotrophy). One specific PhYsiological feature is the production of toxins. In 1988, the toxic bloom In the North Sea coastal waters of Sweden and Norway consisted of a small flagellate, Chrysochromulina polylepis (Rosenberg et al.. 1988), and PrYmnesium parvum is also known to be potentially toxic. Thus in order

80 J . KUPAKINEN AND H . KUOSA

to fully understand the role of the smallest algae in the pelagic ecosystem we need cooperation between algal taxonomists, physiologists and ecologists.

(b) Picoplanktonic cyanobacteria Picoplanktonic cyanobacteria in the Baltic Sea mainly belong to two separate types: an ellipsoid or roundish type and a rod-shaped type. The small, almost round or ellipsoid coccoid cells have been recorded from the coastal and open waters of the whole Baltic Sea (Schmaljohann, 1984; Jochem, 1988; Kuosa, 1988a; Anderson et al., in prep.). The cell size of this type varies from very small (<1 pm) to relatively large (2-3 pm). However, the bulk of single coccoid cyanobacteria in the Baltic Sea belong to the true picoplankton. The cell division appears to be Synechococcus-type and these cells correspond to the existing group of oceanic coccoid cyanobacteria addressed to the genus (e.g. Waterbury et al., 1986). It is not known whether several taxa of small coccoid cyanobacteria exist within this group, or whether the coccoid cells with apparently different photosynthetic pigments belong to another taxon.

Both Schmaljohann (1984) and Kuosa (1988a) observed the tendency of small coccoid cyanobacteria to form small cell groups. These colony- like assemblages contain up to ten cells in irregular order, many times several cells in a cell row. Their formation seems to be most pronounced during summer. These formations may be a consequence of rapid cell division and the subsequent loose attachment of daughter cells, and not true colony formation as in the cyanobacterial genera Merismopedia and Microcystis, which are also present in the area. However, if these cell groups are not easily broken by physical disturbance, they may have consequences for the ecological characteristics of the algae. First, these cell groups will be available to larger grazers. Secondly, in fractionation studies, cell groups may be retained by filters with large pore-size or they may be more or less broken by the filtration. We do not yet know how these cell groups behave, and consequently it is unclear whether our results are biased to some extent.

Other forms of picoplanktonic cyanobacteria reported from the Baltic Sea are rarer. Rod-shaped cyanobacteria have been reported from the Gulf of Bothnia (Anderson et al., in prep.) and the Gulf of Finland (Kuosa, 1988a). In the latter publication an unidentified species with long, twisted cells was also introduced. The systematic position of both taxa is still unclear, although the rod-shaped small cells may well be single cells of a very thin trichomatous cyanobacteria (Pseudanabaena sp.). Some specific characteristics (tendency to form short cell chains and sometimes tapering cell ends) point to this possibility.


I I . Methods

A. Autotrophic Picoplankton

1. Counting

The most widely used method of counting phytoplankton samples is inverted microscopy preceded by sedimentation in Utermohl chambers. Cell counting is usually performed with a 40x objective. This method has many drawbacks when it comes to counting pico- or ultraplankton. Firstly, there seems to be a clear tendency to obtain higher abundances if a small volume is sedimented (Huttunen and Kuparinen, 1986). This may be explained by coverage by other particles if larger volumes are sedimented or simply by the human factor of observing small objects more easily among fewer particles (Huttunen and Kuparinen, 1986). However, the sedimentation of small particles may also be incomplete (Kuosa, 1988b). Secondly, there are seldom possibilities to distinguish between very small colourless and chloroplast-containing cells. Thirdly, the smallest cells, picoplanktonic cyanobacteria, cannot be counted by inverted microscopy using a 40x objective.

Epifluorescence microscopy has been used in counting picoplanktonic algae. Preservation of samples has normally been performed either with unbuffered glutaraldehyde or formaldehyde. However, glutaraldehyde was found to be superior in long-term preservation (Kuuppo-Leinikki and Kuosa, 1989). Picoplanktonic cyanobacteria can be counted from unpre- served samples due to their ability to withstand filtration without cell rupture. However, most eukaryotic cells will burst if filtered without aldehyde fixation. Black membrane filters (e.g. Nuclepore) with a pore size of 0.2 pm are used in epifluorescence counting. Picoplanktonic cells are usually counted with a 1 0 0 ~ oil immersion objective.

Epifluorescence counting is based on the autofluorescence of photosynthetic pigments of picoplanktonic algae. Different excitation wavelengths may be chosen to help the separation of picoalgal groups (Becker, 1985). Under blue excitation eukaryotic algae will fluoresce conspicuously. The cells with a high concentration of phycoerythrin (cyanobacteria) will have orange fluorescence under, for example, a Leitz filter set 12 (Fig. 3 ) . This can be used as a marker of small cyanobacteria. However, with blue excitation light the intensity of fluorescence of picoplanktonic cyanobacteria is relatively weak (Craig, 1987). Further- more, cyanobacterial cells without phycoerythrin will not be observed under blue excitation. Thus blue excitation is most suitable for counting eukaryotic picoplankton only.

82 J . KUPARINEN AND H. KUOSA

U V V B G Y O R

FIG. 3 . A: Chlorophyll a (Chl a) , c-phycocyanin (PC), and c-phycoerythrin (PE) absorbance spectra in vivo. B: Transmission spectra of exciting wavelengths produced by Leitz G, I? and M2 filter blocks (Becker, 1985).

Green excitation (e.g. Leitz filter set M2) may be used in counting picoplanktonic cyanobacteria (Becker, 1985; Craig, 1987). Cyanobacteria containing phycoerythrin will be seen yellow-red and those containing phycocyanin will be red. Chlorophyll a fluorescence is also visible (red), although weak, but cyanobacteria containing phycocyanin are easily separated from eukaryotic chloroplasts by their disappearance under blue excitation. Cryptophycean algae also fluoresce under green excitation due to the phycobilins they contain, but they are usually not erroneously counted as cyanobacteria due to the size and form of the chloroplast.

Cells and flagella of algae may be made visible by using different fluorochromes (e.g. Haas, 1982; Caron, 1983; Sherr and Sherr, 1983). The separation of autotrophic and heterotrophic cells is then also possible. Picoplanktonic cyanobacteria may be counted from the fluorochrome-stained filters using green excitation provided that the fluorochrome used does not mask the autofluorescence. For example, one useful fluorochrome, proflavine, which does not form significant background fluorescence in the northern Baltic Proper samples, somewhat masks chlorophyll autofluorescence (Kuosa, 1988b). A separate count for picoplanktonic eukaryotic algae from an unstained filter is therefore recommended.

Although it is advisable to count the samples as soon as possible, it is


natural that in some cases they have to be kept for some time. Baltic Sea samples of picoplanktonic cyanobacteria may be kept for long periods at -20°C as a water sample without any preservative (Kuuppo-Leinikki and Kuosa, 1989). Other samples can be kept as prepared filters at -20°C (Booth, 1987; Kuuppo-Leinikki and Kuosa, 1989). Glutaraldehyde should then be used as preservative (Kuuppo-Leinikki and Kuosa, 1989).

2. Biomass, chlorophyll and production estimates

Picoplanktonic biomass may be estimated from epifluorescence counts. However, in this case the general problem of estimating biovolumes must be faced. Estimation of the biovolumes of picoplanktonic cells may be carried out using an ocular grid, for example. It is advisable to use several standard mean biovolumes and count size-classes of cyanobacteria and eukaryotic algae, as their cell volume will vary considerably (e.g. Jochem, 1988). There is, of course, a contradiction between the number of size-classes and counting efficiency, which must be resolved in each study. It is not known how different preservatives will affect the biovolume estimates of picoplanktonic algae. If carbon estimates are standardized, conversion factors may be used. In this study, Jochem (1988) assumed a cell density of 1.1 g/ml, dry weight 30% of wet weight and carbon content 50% of the dry weight. The percentage of dry weight from wet weight is probably the main source of error in the calculation. However, this calculation, giving a slightly higher carbon content than Edler (1979), but a considerably lower content than Strathmann (1967) and Eppley et al. (1970), is probably a reasonable estimate of the carbon content. We have no direct measurements of the carbon content of Baltic Sea picoplanktonic algae. In any case, a more critical step in estimating carbon biomass is volume calculation.

Most of the problems in measuring picoplanktonic biomass, chlorophyll and production are met in the fractionation procedure. Both 2 and 3 pm filters have been used for separating the picoplanktonic fraction from the rest of the phytoplankton community (Table 7 ) . The choice of the filter is, as discussed earlier, at the moment rather subjective. Furthermore, relatively large cells will pass both 2 and 3 p m filters (Huttunen and Kuparinen, 1986), and some true picoplanktonic cells will probably be retained by these filters (Li, 1986). Li (1986) presented a good review of the effect of vacuum on the recovery of picoplankton in filtration, and his recommendation was to use a slight vacuum instead of gravity filtration if the intention is to get the bulk of picoplanktonic algae in the filtrate. Both Waterbury et al. (1986) and Kuosa (1990a) found that 1 pm fractionation is useful in separating picoplanktonic cyanobacteria from the rest of the

84 J. KUPARINEN AND H. KUOSA

TABLE 1. AN EXAMPLE OF THE METHODS LJSED I N FRACTIONATED PRODUCTION MEASUREMENTS

Reference PreiPost Filter Part/Total Vacuum Stopping Bacterial uptake

Post 2 p m Part (0.6 pm) Not given No No Post 3 p m Part (GF/F) <25 kPa DCMU No Post 3 p m Part (0.2 pm) Gravity Formalin No Pre 3 p m Total Gravity Formalin - Post 3 p m Part (0.2 pm) Not given No Yes

(1) (2) ( 3 ) (4) ( 5 )

“Pre/Post” indicates pre- or post-incubation fractionation, ”Filter” the filter type used in separating picoplankton, “PartiTotal” the type of production estimate (particulate production o r total production), “Vacuum” the amount of vacuum used in fractionation, “Stopping” how production measurements were stopped and “Bacterial uptake” if bacterial uptake of exudates was taken into account in the estimates of picoplanktonic primary production. (1) Anderson er al. (in prep.); (2) Jochem (1989); (3) Huttunen and Kuparinen (1986); (4) Kuosa (1990~); (5) Larsson and Hagstrom (1982).

algal community. At the same time, unfractionated samples may be counted in order to estimate the amount of picoplanktonic cyanobacteria retained by the 1 p m filter and to correct the <1 pm measurements to total cyanobacterial community.

Filtration as such is probably not very harmful to picoplanktonic cyanobacteria (Waterbury et al., 1986). However, filtration will evidently be harmful to eukaryotic cells (Goldman and Dennett, 1985; Kuosa, 1988b). The problem is present in all fractionated measurements, but is most pronounced in production estimates. According to Waterbury et al. (1986) cell fragments of large algal cells are caught by the filters with very small pore-size (in this case 0.2 p m Nuclepore polycarbonate filters), and they falsely increase the estimates of particulate production of the <1 pm fraction. This will be a problem as yet unsolved also in fractionated chlorophyll measurements.

The choice between pre- and post-incubation fractionation in primary production measurements will affect the results considerably. In post- incubation fractionation, cell fragments will possibly cause an overestima- tion of picoplanktonic production values. Pre-incubation fractionation will similarly cause fracture, but instead of a false size distribution the production of size fractions will be reduced, provided that the cell fragments are not photosynthetically active. One problem in post- incubation fractionation is the uptake of algal exudates by bacteria, which is eventually included in picoplanktonic production. This characteristic was used by Larsson and Hagstrom (1982) when they estimated bacterial


uptake of algal exudates by the difference between post- and pre- incubation fractionated samples.

Another problem present at least in the northern Baltic Proper is the difficulty in measuring particulate production. According to Lignell and Kuosa (1988), filtration with polycarbonate or membrane filters cause! considerable leakage of dissolved organic compounds from algae. Thi! leads to a highly unrealistic fraction of “net algal exudation”. Thu: post-incubation fractionation is of little use in production measurement: as it will give gross underestimates of those fractions susceptible to cel breakage in filtration. A pre-incubation fractionation procedure wil probably give somewhat more realistic (under)estimates of the productior of small size fractions. It will also give the opportunity to measure tota’ net production (particulate + dissolved + bacterial uptake of exudates: from the fractionated samples (Niemi e? al., 1983). Another positive characteristic of the pre-incubation fractionation procedure is the exclu. sion of the bulk of predators from the picoplanktonic size fraction.

Both normal dark incubations and DCMU-treated incubations have been used as blanks in picoplanktonic production measurements. LI (1986) discussed the merits of both. More studies in the Baltic Sea should be carried out before any definite conclusions can be reached. However. Waterbury et al. (1986) used normal dark incubations in their studies.

B. Bucterioplankton

Bacterioplankton cell count, biomass and production estimates were based on the following methodology, if not specified otherwise in the text. This applies to all studies quoted as “this study”, “recalculated from” and “unpublished cruise reports”. In the studies in which values for thymidine incorporation were given in “mole x unit volume x time”. recalculation was performed according to the conversion factor: presented here.

Bucterioplankton cell counts. Bacterioplankton cells were counted under an epifluorescence microscope (Hobbie et al., 1977). Water samples of 20ml were preserved with 1.01111 of 0.2pm filtered neutral formalin (39%). Subsamples of 1-2ml were mixed with 4ml of 0 .2pm tiltered demineralized water and filtered onto black 0.2 pm Nuclepore filters (25 mm diameter). The filters were covered with particle-free acridine orange solution (1 gA). After 5 min of staining, the filters were sucked dry, air dried and stored in the dark. Bacteria were counted under blue light (filter set 12/3) with a Leitz Laborlux D epifluorescence microscope.

86 J . K U P A R l N E N A N D H . KUOSA

[-'HI-thymidine incorporation into cold TCA precipitate (TTI) . Duplicate or triplicate water samples of 10-20ml were incubated with about 10 nmol/l of methyl-['HI-thymidine (Amersham, 1.5-2.2 TBqimmol, 40- 60 Ciimmol) for 3&120 min. Incubation with 10 nmol/l of thymidine is likely to be sufficient to saturate uptake in the open sea area of the Baltic Sea (Heinanen, 1992b, submitted) except in the northern Bothnian Sea, where >20 nmolil concentrations are needed (Anderson et al., in prep). Incubations were terminated by adding 100 p l 39% formalin. A prekilled sample was used as blank. The samples were filtered onto 0.22 pm cellulose acetate or cellulose nitrate filters, rinsed 5-10 times with 1 ml 5% ice-cold trichloroacetic acid (TCA) and radioassayed in an LKB-Wallac 1209 RackBeta liquid scintillation counter, using PCS (Amersham) as scintillator.

Bacferioplankton production. Data on ['HI-thymidine incorporation into macromolecular material was converted into carbon production using the following factors: (1) from incorporation into cell production by an empirical factor of 1.1 x 10'' cellsimol (Riemann et al., 1987); (2) to biovolume production by mean cell volumes of 0.052 pm3 in samples from the Gulf of Bothnia (Heinanen, 1992a), 0.059 pm' from the Baltic Proper during the spring period and 0.032 pm3 during the summer period Heinanen and Kuparinen, 1991); and (3) to carbon net production by assuming a cell carbon content of 0.35pg C/pm3 (Bjcirnsen, 1986). The value of Bj~rnsen (1986) was chosen because it has been used in monitoring studies in the Baltic Sea and is close to the mean value measured in temperate and arctic seas. (Bratbak, 1985; Nagata, 1986; Kuparinen, 1988; Lee and Fuhrman, 1987; Bjornsen and Kuparinen, 1991). Conversions (2) and ( 3 ) were also applied to calculations of bacterial biomass values.

Batch culture experiments. Bacterioplankton batch cultures were prepared for the conversion factor and for the enrichment experiments by diluting natural bacterial assemblages in filtrates (800 ml; 0.8 pm Nuclepore filter) of sea water with filtered (7200ml; 0.2p.m Nuclepore filter) sea water from the same site. The 0.8pm filtration removes the majority of predators. Small flagellates may, however, penetrate through the filter and therefore when bacteria were observed microscopically, flagellate appearance was also recorded to see whether flagellate growth occurred in the batches. The seawater cultures were divided into four 2.5-litre glass or polycarbonate bottles in aliquots of 2 litres. One bottle was kept as a control and the remaining were enriched with nutrients (20pg/l of P as KH2P04 and 80 of pg/l of N as NH,Cl) and/or carbon (200pgC/1 as


C12H2201 The nutrient and carbon enrichments represent levels that bacteria may experience during bloom periods and/or upwelling. The batch cultures were incubated in the dark at in situ temperature (f2"C).

111. Phytoplankton Succession in the Baltic Sea

The Baltic Sea shows remarkable variability in both seasonal and areal physical characteristics of the environment (Section I). This is also reflected in the phytoplankton succession, which varies greatly between sub areas. Fig. 4 shows the general annual cycles of phytoplankton development in four parts of the Baltic Sea.

In spring, phytoplankton development starts after the incoming solar radiation increases to a level at which it can sustain algal growth in deep mixing water. Thus the onset of the vernal bloom tends to be earlier towards the southern Baltic Sea. The vernal phytoplankton community consists mainly of cold-water diatoms and dinoflagellates. After thermal stratification develops, and surface water is physically cut off from the deeper nutrient-rich water layer, the spring bloom declines as a result of the removal of inorganic nutrients from above the thermocline.

The summer stage is characterized by low algal biomasses, moderate productivity and the dominance of small algae. In late summer, a dense cyanobacterial bloom of large trichomatous species may develop, but its intensity and areal distribution varies greatly from year to year. Autum- nal cyanobacterial blooms do not occur in the Bothnian Bay due to the high inorganic N : P ratio (Niemi, 1979), as these species possess heterocytes to fix molecular nitrogen. Phytoplankton development in the Bothnian Bay is also generally limited by the low availability of phosphorus together with the short average growth season. In the southern and western Baltic Sea autumnal diatom maxima are regular. Dinoflagellates also appear in the area which is heavily influenced by oceanic water.

IV. Autotrophic Picoplankton in the Baltic Sea

A. Areal and Vertical Distribution

Although not well documented, there are some indications of an omnipresence of picoplanktonic algae in the Baltic Sea. The first microscopical observations of very small algal cells were from the early 1980s (Larsson and Hagstrom, 1982; Schmaljohann, 1984; Huttunen and


I I I I I I I I I I I

BB I I I I I

I I I I I I I I I I I

J F M A M J J A S O N D

FIG. 4. Generalized annual cycles of phytoplankton development in different parts of the Baltic Sea. Vertical scale arbitrary. BB = Bothnian Bay. NB = northern Baltic Proper, the Gulf of Finland and the Bothnian Sea, SB = southern Baltic Sea, WB = western Baltic Sea (redrawn from Hallfors and Niemi, 1986).


Kuparinen, 1986). Picoplanktonic cyanobacteria were evidently not included in the data of Larsson and Hagstrom (1982) and Huttunen and Kuparinen (1986), as these were obtained by the Utermohl technique. Thus Schmaljohann (1984), who used electron microscopy, was the first to document picoplanktonic cyanobacteria from the Baltic Sea. Recent studies have used epifluorescence microscopy for counting both eukaryotic and prokaryotic algae.

Most of the studies on picoplanktonic algae in the Baltic Sea have been made at coastal stations (Table 2). The data from the Bothnian Sea indicates almost total dominance of cyanobacteria in the picoplanktonic size-class (Anderson et al., in prep.). Eukaryotic picoplankton is abundantly present ( 103-104 cells/ml) in other coastal stations of the Baltic Sea (Tvarminne, Ask0 and Kiel). In a north-south transect through the whole Baltic Sea, eukaryotic picoplankton was present in abundance at all stations in early summer (Tanskanen et al. , in preparation).

Picoplanktonic coccoid cyanobacteria have been reported from all stations studied along the Baltic Sea coast, from the Gulf of Bothnia to the western Baltic Sea (Jochem, 1988; Kuosa, 1988a, 1991; Anderson et

TABLE 2. GENERAL ESTIMATES OF THE NUMBER OF PICOPLANKTONIC CYANO-

STATIONS OF THE BALTIC SEA AND AT ONE TRANSECT IN THE OPEN BALTIC PROPER

BACTERIA ( i d ) AND THEIR GENERATION TIMES (id) AT THREE COASTAL

Area Season Abundance Growth

Umea (1989, 1990)

Tvarminne (1986, 1988)

Kiel (1986)

Baltic Proper (June 1987)

Winter Spring Summer Autumn Winter Spring Summer Autumn Winter Spring Summer Autumn

104 1o4-1oS 1 4 x lo5 1 05-1 o4 104 104-105 104-106 5 x 105-104

104 104-2 x 105 105-104 1 0"

n.d.

148 28

5 4

? (very long) zero-growth-5 days

2 n.d. n.d. n.d. n.d. n.d. n.d.

Data from Anderson ef al. (in prep.), Kuosa (1991), Jochem 1988) and Tanskanen et al. (in Prep.). n.d. = not determined.

90 J . KUPARINEN A N D H. K U O S A

al., in prep.). Similarly, two as yet unpublished cruise studies revealed high numbers of picoplanktonic cyanobacteria in the open sea area of the Baltic Proper (Tanskanen et al., in preparation) and the Gulf of Finland (Kuosa, unpublished). The transect study of the low-salinity waters of an inner archipelago bay, Pojo-bay, also revealed the existence of small cyanobacteria (Kuosa, 1988a). However, single cruise reports provide little information o n the role of picoplankton in the Baltic Sea. The occurrence of cyanobacteria with different fluorescence characteristics (yellow-red/red under green excitation) has not yet been reported. However, according to some data sets from the Gulf of Finland (Kuosa, unpublished), it seems that cyanobacteria containing phycocyanin (red under green excitation) are common only in very diluted low-salinity waters of the inner archipelago and river outlets.

Jochem (1988) and Kuosa (1988a, 1990b) have studied the vertical occurrence of picoplanktonic algae. The absolute maximum was found at the surface in both studies. This is not surprising as in the Baltic Sea the euphotic layer is usually relatively shallow (10 to 20 m), and no real deep maximum can be expected under normal circumstances. However, we still lack systematic studies of the thermocline and pycnocline regions of the Baltic Sea, which may both possess deep chlorophyll maxima apparently due to algal growth at these depths (Jochem, 1989; Kuosa, 1990b). Although the maximum abundance of both eukaryotic and prokaryotic picoplankton is in surface water, they are both also found in relatively high numbers (compared with larger algae) at greater depths (e.g. Kuosa, 1988a). It is still unknown whether this deep population is active, and whether it may function as a seed population after upwelling events, which are common in some areas of the Baltic Sea.

Meromictic lakes, which were earlier connected with the sea, but which are now isolated by rising land level, are specific ecosystems along the coasts of the Baltic Sea. They still possess a deep saltwater layer, which prevents normal circulation in the lake. Craig (1987) found picoplanktonic cyanobacteria in abundance in one of those lakes in Aland. They occurred as a thin layer just under the halocline.

B . Seasonal Variation

1. Abundance

There is limited seasonal variation of eukaryotic picoplankton. These plankton appear to be present in low numbers (10'/ml) during the winter (Kuosa, 1991), and to increase in abundance during early spring. Both


Jochem (1988) and Kuosa (1991) recorded the dominance of eukaryotic picoplankton in cold water. Kahru et al. (1991) reported the growth of “unidentified small-sized ( 1 4 pm) phytoplankton” in early spring. This description fits well with the eukaryotic picoplankton fraction which was studied by both Jochem (1988) and Kuosa (1991). Huttunen and Kuparinen (1986) also reported high abundance of “Nannochloropszs sp.” during spring. Another season of high relative eukaryotic abundance of the picoplanktonic fraction is autumn, at least at the Tvarminne station (Kuosa, 1991).

The abundance of eukaryotic picoplankton during the growth season is about 1-3 x 10‘lml at Tvarminne (Kuosa, 1991). This compares well with the values from oceans, which range up to 3 4 X 104/ml (Joint, 1986).

Picoplanktonic cyanobacteria show wider seasonal variation. All existing material indicates a clear positive correlation between cyanobacterial number and water temperature (Jochem, 1988; Kuosa, 1991; Anders- son et al., in prep.). Temperature has been proposed as a controlling factor of cyanobacterial growth in all these studies. This also fits the general picture arising from the existing literature (Krempin and Sullivan, 1981; El-Hag and Fogg, 1986; Joint, 1986; Waterbury et al., 1986). There is, however, one reference (Shapiro and Haugen, 1988) to a cold-water race of Synechococcus. Strangely, it seems that the Baltic Sea cyanobacteria do not incorporate this characteristic, which would be expected due to the long annual cold season.

The number of picoplanktonic cyanobacteria (Table 2) has been found to be high at all those stations from which we have proper data sets (Jochem, 1988; Kuosa, 1988a, 1991; Andersson et al., in prep.). Generally, Baltic Sea values are of the same order of magnitude as oceanic coastal abundances (Joint, 1986). There seems to be a maximum at the Tvarminne station, in which summer abundances are nearly an order of magnitude higher than at two other stations. Even worldwide data of the cyanobacterial numbers show the northern Baltic Proper station at Tvarminne to be at the higher end of the range (Joint, 1986). The highest values at Tvarminne can only be matched by the values from the tropical Pacific (Li er al., 1983).

2. Biomass and production

Almost all values from spring indicate low contribution of picoplankton to the total algal biomass and production (Jochem, 1989; Kuosa, 1990a; Andersson er al. , in prep.). However, the fraction of picoplanktonic biomass and production has been more intensively measured during summer. The available data indicate the high contribution of picoplank-

92 J . KUPARINEN AND E l . KUOSA

TABLE 3. ESTIMATES OF THE S H A R E OF PICOPLANKTONIC ALGAE TO THE TOTAI. BIOMASSES AND PRODUCTION IN SUMMER, WHICH IS THE ONLY SEASON WITH A

NUMBER OF MEASUREMENTS. DUE TO SEVERAL METHODOLOGICAL DIFFER- ENCES THE VALUES ARE Nor FULLY COMPARABLE

Area Biomass Production

Umei Tvarminne Ask0 Kiel

25% (bm) 3&70% 2(1-50% (chl) 2&50% 10-25% (bm) 20 % 2-20% (chl) 7-38%

Data from Anderson et al. (in prep.), Kuosa (1990a). Larsson and Hagstrom (1982) and Jochem (1989). bm = the share estimated from phytoplankton biomasses and chl = the share estimated from chlorophyll values.

ton in either biomass (or chlorophyll) values or production. Thus, although the methodology varies, it may be concluded that picoplanktonic algae are of considerable importance in the Baltic Sea during the stratified low production period in summer. In one study (Kuosa, 1990a), the fraction of picoplanktonic cyanobacteria of the total algal biomass and production was studied (Table 3). In those samplings in summer from which the estimation could be made, the fraction was 2540% of the chlorophyll and 1.5-50% of the production. The fraction was consistently well over SO% of the total chlorophyll and production in the < 3 p m fraction, and in one sampling it even exceeded the <3 Fm production due to the abundant cyanobacterial cell groups in the sample.

Generally, picoplanktonic cyanobacteria thrive in low-nutrient environments in the Baltic Sea. They are a typical component of the regenerated production period of stratified warm water. There are clear indications of the decreasing importance of the picoplanktonic fraction toward the eutropic end of the oligotrophic gradient. Larsson and Hagstrom (1982) estimated picoplanktonic biomass to account for up to 10% at a eutrophicated station and 2.5% at the control area in Himmerfjarden, and Jochem (1988) found that the relative fraction of picoplankton decreased in the more eutrophic waters near Kiel.

V. Bacterioplankton in the Baltic Sea

A. Annual and Seasonal Variation of Bucterioplunkton Production

Seasonal succession of bacterioplankton production (mg Clm'lday) on the coast of the Gulf of Finland during different years is presented in Fig. 5.

BALTIC SEA PICOPLANKTON

1 a

..._. , , . ..................... -..,.,.!.?

b

C

. . : .. .. :.,

;;.. . .. . . .. . . . .. .. . . . ... . . . . . .. . .. .

-.,, , ; l , j l j J F M A M J J A S O N D

93

FIG. 5 . Bacterioplankton production (mgC/m7/d) on the coast of the Gulf of Finland during 1985(a), 1986(b) and 1988(c). Figure a is redrawn from Kivi et al. (submitted), b from Kuosa and Kivi (1989) and c from Lignell et al. (submitted) and Autio (1992). Temperature IS given as the dotted lines.


Lines were not drawn between the data points (Fig. 6) because only in the study of Kuosa and Kivi (1989) (Fig. 5 ) was the sampling frequency high enough in relation to the time-scales of bacterial growth (doublings in days), and to physical forcing such as water mass movements (in days), for the data actually to describe seasonal features at the study site.

These data from the Gulf of Finland (Fig. 5 ) show some general features of bacterioplankton seasonality. As a response to phytoplankton spring bloom, bacterioplankton cells (Vaatanen, 1976; Virtanen, 1985; Kuparinen, 1988), cell volumes and biomass (Kuparinen et al . , 1984; Virtanen, 1985; Kuparinen, 1988; Lahdes et al., 1988) and production (Kuparinen, 1988; Kuosa and Kivi, 1989; Lignell, 1990a) start to increase, reaching their maximum values about 2 weeks after the phytoplankton peak (Kuparinen ef al., 1984; Kuosa and Kivi, 1989; Lignell et al., submitted). This response of bacterioplankton to the spring bloom has been recorded throughout the Gulf of Finland (Heinanen and Kuparinen, 1991), in a cruise study in which all stations showed elevated production values along the Gulf (Fig. 6) during phytoplankton spring bloom development (Leppanen et al., 1991). Moreover, two of the quasi- synoptic transects through the central line of the Gulf of Finland showed low values in the northern Baltic Proper and elevated values at the entrance to, and in the eastern parts of the Gulf of Finland (Fig. 6), parallel to the trends found in phytoplankton production (Lassig et al., 1978; Leppanen et a[., 1991).

The spring bacterioplankton peak is followed by a decline in early summer. In late summer, with increasing temperature and with the development of cyanobacteria, another peak in bacterioplankton variables is usually observed (Kuparinen et al . , 1984; Virtanen, 1985; Kuosa and Kivi, 1989; Kivi et al., 1992). During years with favourable hydrographic and illumination conditions, a phytoplankton autumn peak may develop, which gives rise to autumnal bacterioplankton production as seen in the data from Kuosa and Kivi (1989) (Fig. 5 ) .

Some general features in the seasonal course of bacterioplankton can also be identified in the northern and in the southern Baltic Sea. In the Bothnian Sea, which is characterized by long winter seasons with ice coverage of about 5 months (December-April), bacterioplankton growth starts after the initiation of phytoplankton spring bloom (Fig. 7), followed by a decline and another rise with the increasing temperature in late summer (Hagstrom, unpublished data). Due to the climatic conditions, the late autumn phytoplankton peak does not occur in the northern Baltic.

The southwestern Baltic Sea is most complex with regard to the features of seasonal bacterioplankton development due to physical


10

7.5

5 -

2.5

0

U -=; 0 cn =L

.

-

-

-

I I I I I 1

12.5 I

20 21 22 23 24 25 26 27 Longitude

FIG. 6 . Bacterioplankton production (pg Cilld) during the spring period in a transect running from the western part of the northern Baltic Proper to the eastern part of the Gulf of Finland in 1990 (a map of the transects is presented in Heinanen and Kuparinen, 1991).

forcing (the inflow of North Sea water, numerous freshwater affluents, etc.) resulting in instability of stratification and its annual development. However, the response to phytoplankton spring development, and the high productivity period during the late summer months (Fig. 7) are similar to other areas in the Baltic Sea (Gocke et af., 1990). The longer summer period in the southern Baltic Sea, with moderately high light levels compared with northern areas, frequently allows an autumn phytoplankton bloom to develop, which in turn gives rise to autumn bacterioplankton development (Rheinheimer, 1981; Kirstein, 1991).

Annual variation, measured with the same methodology and applying similar conversion factors, can be compared with the data of bacterioplankton productivity from the Gulf of Finland (Fig. 5 ) . Similar maximum values in spring were recorded each year, but the summer values differed considerably in different years. In 1986, production remained at a low level throughout the summer compared with 1985 and 1988. In


C

75 -

5 0 -

FIG. 7. Bacterioplankton production (mgC/m3/d) in the Bothnian Bay (a, b) (from different years) and in the Kiel Bight (c) during the late 1980s. Figures a and b are redrawn from Hagstrom (unpublished data) and c from Gocke ef a / . (1990).


1988, high summer values appear to follow temperature changes during the year, but the low values in 1986 cannot be explained by low temperatures (Fig. 5) . Primary production was on an average level in 1986 (Kuosa and Kivi, 1989) compared to long-term series (Gronlund and Leppanen, 1990) and thus cannot alone explain the low bacterial production. However, the spring phytoplankton development, in terms of exudate production into the photic zone and the degree of sedimentation from the photic zone, may contribute to the difference in bacterioplankton production between years. The mobilization of particulate and dissolved material from below the thermocline during the weakly stratified early summer period (Laakkonen et al., 1981), may also markedly contribute to this difference in bacterioplankton production between years.

B. Distribution of Bacterioplankton

1. Vertical distribution

Vertical distribution of bacterioplankton generally follows the distribution of food or energy sources available in the water column, with maximum values found in the photic zone and in the transition zones such as the pycnocline, the halocline and the chemocline. Bacterioplankton cells, heterotrophic activity and bacterioplankton production have been shown to follow the vertical distribution of phytoplankton production and biomass (chlorophyll a), with peak values recorded in the upper photic layer above the thermocline (Virtanen, 1985; Rheinheimer et al., 1988; Autio, 1990; Gocke et al . , 1990; Cruise report 1990, unpublished; Heinanen, 1991). In the eutrophication gradient near Ask0 (Fig. 1) Larsson and Hagstrom (1982) measured some 80% of the annual bacterial production in the 0-20 m trophic layer compared with the 2G35 m atrophic layer. In the more eutrophicated stations, in which the trophic layer was thinner than the atrophic layer, values of 6&70% of the annual production in the trophic layer were recorded.

In regions affected by stratification forces other than temperature, high values of bacterioplankton variables may be obtained from below the photic layer. In the deep parts of the Baltic Sea, where anoxic waters are encountered, Gast and Gocke reported the existence of regions in which the total bacterial number as well as the bacterial activity show well-defined peaks around the oxiclanoxic interface, with significantly higher values than in the oxic water above or anoxic water below (Gast and Gocke, 1988; Gocke et al . , 1990).

98 J . KUPARINEN AND 14. KUOSA

2. Horizontal distribution

As shown in Fig. 7, an order of magnitude difference prevails in the maximum values of surface water bacterioplankton production in the northern (Bothnian Sea) and southern (Kiel Bight) Baltic Sea. In the Gulf of Finland maximum values are higher by a factor of 2 than in the Bothnian Sea. When seasonality in the data is taken into account, differences of more than two orders of magnitude in the production rates (0.1-74mg C/m3/day) have been recorded in the Baltic Sea (Table 4). The highest variability has been recorded at the study sites near the Finnish (Tvarminne, Fig. 1) and Swedish (Asko, Fig. 1) coasts. The southern part of the Baltic Sea is the most productive area. This part of the Baltic has on average the highest surface water temperatures and also the highest phytoplankton productivity (Schulz et al., 1990). High values, up to 30.4mg C/m3/day, have also been recorded from the entrance to the Gulf of Finland. This locality is a biologically active site most probably because of quasi-stationary fronts appearing in the mouth of the Gulf. The formation of fronts is related to the bottom topography and circulation patterns of the Gulf (Kononen and Nommann, 1992). The lowest values in the Baltic Proper were measured in the northern and central Baltic Proper, which are least subject to nutrient and organic loading from land. The exceptionally high values recorded from the Baltic Proper have been related to dense cyanobacterial blooms (Gocke et al., 1990; Heinanen and Kuparinen, 1991).

Total bacterioplankton cell counts vary by two orders of magnitude (0.1-10 x lo9 cellsil) in the surface waters of the Baltic Sea (Table 5). Most of the variation has been measured in the Gulf of Finland, where seasonal cycles have been adequately covered to detect short time fluctuations. In the southern Baltic Sea, the overall variation in total cell counts is low compared with other localities (Table 5 ) . The central Baltic Proper also exhibits little variation, except for the unusually high value of 10 x 10' cells/l associated with the heavy cyanobacterial bloom of 1984 (Gocke et al., 1990) and the low value measured by Autio (1990) in the early summer of 1987.

Bacterioplankton cell volumes vary from 0.015 to 0.125 pm' in the surface waters of the Baltic Sea (Table 6 ) . In general the highest values have been recorded from spring samples throughout the Baltic Proper, except for the high values from the Bothnian Sea (0.114pm') and Kiel Bight (0.1OH. 124 pm3). In epifluorescence microscopy the phytoplankton spring development has a visible effect on bacterioplankton cells, which are well stained and give bright fluorescence (Virtanen, 1985; Kuparinen, 1988) compared with the small and faintly fluorescing cells


TABLE 4. REGIONAI DISTRIBUTION OF SURFACE WATER BACTERIOPLANKTON PRODUCTION (mg C/m3/d) IN THE BALTIC SI-.A

mg C/m3/day Area Season Reference

0 .0M.1 BS Winter Heinanen, 1992a 3.2-6.1 Summer Heinanen, 1991

3.5-17.5 Summer Heinanen, 1992a 0.3-7.5 BS-coast All Hagstrom, unpublished data 1.4-8.4 Tvarminne Spring Lignell, 1990b 0.9-23 Spring Kuparinen, 1988

3 . M . 2 Spring Heinanen and Kuparinen, 1991 0.2-1 3.8 Spring This study 5.0-14.9 Summer Lignell, 1990a 0.2-12.1 Summer This study

6.5 Summer Autio et al. , 1988

5.3 Tvarminne Autumn Autio et al., 1988 10-15" Asko Summer Larsson and Hagstrom, 1982

0.2-1.9 Autumn This study M . 2 " All Virtanen, 1985 0-24" Ask0 All Larsson and Hagstrom, 1982

6.8-10.1 Summer Heinanen and Kuparinen, 1991 2.9-9.3 GOF Spring This study

30.4 Summer Gocke et al., 1990

13.1 Summer Cruise report 1990 (unpublished) 4.0 Summer Heinanen, 1991

2.6 Teili Spring Lahdes et ul., 1988

3.9 Early summer Autio, 1990 2.8 Summer Heinanen, 1991

2 . M . 6 NBP Spring This study

6.2-12.4 Summer Heinanen and Kuparinen, 1991 0.3-2.5 BP Early spring Heinanen and Kuparinen, 1991

1.9 Early summer Autio, 1990

7.4 Summer Cruise report 1990 (unpublished) 3.7 SBP Early summer Autio, 1990

12.9- 19.0 Summer Gocke et al., 1990 2.5 Summer Heinanen, 1991

14.4 Summer Gocke et al., 1990

10.0 Summer Cruise report 1990 (unpublished)

13.9 Kiel Bight Summer Gocke et a/ . , 1990 6-74 All Gocke et al., 1990

6.2-1 2.7 Summer Heinanen and Kuparinen, 1991

BS = Bothnian Sea, GOF = Gulf of Finland, NBP = northern Baltic Proper, BP = Baltic Proper, SBP = southern Baltic Proper. For stations Tv&rminne, Ask0 and Teili see Fig. 1. "FDC technique.


TABLE 5. REGIONAL DISTRIBUTION OF SURFACE WATER BACTERIOPLANKTON (CELLS/~ x 10’) IN THE BALTIC SEA

cellsil x lo9 Area Season Reference

0.5-1.0 BS 1.7-1.8 1.2-3.3

3.3 3.6

3.1-4.7 2.C3.6 0.8-3.4 Tvarminne 1.C5.3

2.3-5.9 4.6-10

1.5-4.5 6.1

1.2-4.8 3.2

0.4-2.8

1.5-5.8

0.8-1.2

1.9-3.5 GOF 0.1-1.8 2.9-7.7

8.2 0.1-2.1

3.5 4 .64 .6 0.1-1.1 Teili 1.0-2.8 NBP

2.2 2.8

3.7-5.4 0.8 BP

3.3-10 5.0

5 .34 .4 4.0

3.1-3.9 0.2-0.7 SBP

0.5 3 . H . 9

2.3 2.G5.1

3.6

Winter Summer Summer Summer Summer Summer Summer Spring Spring Spring Spring Summer Summer Summer Summer Autumn Autumn All Spring Early summer Summer Summer Summer Summer Summer Spring Spring Early summer Summer Summer Early summer Summer Summer Summer Summer Autumn Early spring Early spring Spring Early summer Summer Summer

Heinanen, 1992a Wikner et al., 1986 Wikner et al . , 1990 Gocke et al., 1990 Gocke and Rheinheimer, 1991 Heinanen, 1991 Heinanen, 1992a Virtanen, 1985 Kuparinen, 1988 This study Heinanen and Kuparinen, 1991 This study Virtanen, 1985 Autio et al . , 1988 Kuuppo-Leinikki and Kuosa, 1990 Autio et a/ . , 1988 Virtanen, 1985 Vaatanen, 1976 This study Kiinnis and Saava, 1990 Gocke et a/ . , 1990 Cruise report, 1990 (unpublished) Kiinnis and Saava, 1990 Heinanen, 1991 Heinanen and Kuparinen, 1991 Lahdes et al., 1988 This study Autio, 1990 Heinanen, 1991 Heinanen and Kuparinen, 1991 Autio, 1990 Gocke et al., 1990 Cruise report, 1990 (unpublished) Gast and Gocke, 1988 Gocke and Rheinheimer, 1991 Wikner et a/ . , 1986 Gocke and Hoppe. 1982a Gocke and Hoppe, 1982b Gocke el a[. , 1990 Autio, 1990 Gocke et al.. 1990 Gocke and Rheinheimer. 1991


Table 5 - c o d .

celldl x 10’ Area Season Reference

3.3 Summer Heinanen, 1991 4.2 Summer Cruise report, 1990 (unpublished)

3 .67 .2 Summer Heinanen and Kuparinen, 1991 3.5-7.1 Autumn Gocke et al., 1990

3.6-4 Kiel Bight Summer Gocke et al . , 1990 4.0 Summer Gocke and Rheinheimer, 1991 4.7“ Summer Galv&o, 1990 2.Ob All Galvao, 1990

“Maximum value. hMean of the period September 1987-May 1989.

during the summer period (Virtanen, 1985). This spring bloom effect of producing larger cells was also recorded in the scanning electron micrographs of samples from the northern Baltic Proper (Lahdes et al., 1988).

The biomass estimates of the surface water bacterioplankton in the Baltic Sea show a variation of two orders of magnitude (Table 7). However, different study sites do not follow the same coherence in values as do the cell number and production data. The biomass determinations are based on cell counts, but involve cell volume measurements and carbon conversion factors (Table 7). The variation is partially reduced if carbon conversion factors are unified, but nevertheless it is higher than expected from cell number measurements. This fact indicates the difficulty of accurate cell volume measurement in epifluorescence microscopy. Even when similar procedures, e.g. standard ocular grids, are used in cell measurements, the difference between operators may be significant (unpublished comparisons). New methodology that is less sensitive to personal judgement should be developed in order to obtain more reliable estimates of bacterioplankton biomass.

VI. Factors Controlling Autotrophic Picoplankton

A. Nutrients and Temperature

Theoretically, picoplanktonic algae have the ability to take up nutrients effectively due to their small cell size. In the Baltic Sea, picoplanktonic algae are a principal component of the stratified summer period, which


TABLE 6. REGIONAL DISTRIBUTION OF SURFACE WATER BACTERIOPLANK~ ON

CELL VOLUMES ( p d ) IN THE BALTIC SEA ~

Pm Area Method and Reference season

0.038-0.090 0.0460. 072 0.018-0.080

0.114

0.03Y-0.079 0.032-0.112 0.01 8-0.048 0.0 15-0.033

0.058-0.072 0.088 0.046

0.022-0.026

0,033-0.125 0.047-0.052

0.019 0.029-0.038

0.0940.099 0.094

0.091-0.114

0.017 0.026-0.047

0.134" 0.1 06-0. 124

0.124 0.091'

BS

Tvarminne

GOF

Teili NBP

BP

SBP

Kiel Bight

EFM - winter Heinanen, 1992a EFM - summer Heinanen, 1991 EFM - summer Heinanen, 1992a EFM - summer Gocke et al., 1990

EFM - spring Virtanen, 1985 EFM - spring Kuparinen, 1988 EFM - summer Virtanen, 1985 EFM - autumn Virtanen, 1985

EFM - spring This study EFM - summer Gocke ef al., 1990 EFM - summer Heinanen, 1991 EFM - summer Heinanen and Kuparinen, 1991

SEM - spring EFM - spring This study EFM - summer Heinanen, 1991 EFM - summer Heinanen and Kuparinen. 1991

EFM - spring Gocke et al., 1990 EFM - spring Gocke and Rheinheimer, 1991

EFM - summer Gocke et a/ . , 1990 EFM - summer Gocke and Rheinheimer, 19Y1 EFM - summer Heinanen, 1991 EFM - summer Heinanen and Kuparinen, 1991

EFM - winter Galviio, 1990 EFM - summer Gocke et al., 1990 EFM - summer Gocke and Rheinheimer, 1991 EFM - all Galviio, 1990

Gocke and Rheinheimer, 1991

Lahdes et a/ . , 1988

EFM = epifluorescence microscopy, SEM = scanning electron microscopy. "Maximum value. "Mean of the period September 1987 to May 1989.

relies strongly on regenerated nutrients. Picoplanktonic algae do not appear to be limited by nutrient availability or, at least, they can cope with the nutrient limitation better than larger algae during summer.

In the Baltic Sea, in which surface water temperatures vary greatly, cold water may be an important controller of picoplankton growth. It seems likely that water temperature controls the growth of picoplanktonic


TABLE 7. REGIONAL DISTRIBUTION OF SURFACE WA.I ER BACI ERIOPLANKTON BIOMASS (mg C/m3) IN THE BALTIC S h A

mg C/m3 Area Carbon Reference conversion pg C/pm3

131

77-86 1.6-19.3 4.2-51.7

(5-35 49.8-79.7

88.0 55.0

20. Ck59.2 21.0

3.7-5.7 1.7-19.1 114-132

4 132

0.8-2.3 1.7

117-144

19 26

51-91 11-173

173 45.8" 102b

BS

Tvarminne

Ask0

GOF

NBP

Teili BP

SBP

Kiel Bight

0.35

0.35 0.11 0.12 0.11 0.35 0.35 0.35 0.35 0.35 0.10 0.35 0.35 0.35 0.35

c

c

- -

0.35

0.35 0.35 0.10 0.35 0.35 0.35 0.35

Gocke et a/ . , 1990 Gocke and Rheinheimer, 1991 Heinanen. 1991 Virtanen, 1985 Kuparinen, 1988 Larsson and Hagstrom. 1982 This study Gocke et al., 1990 Heinanen, 1991 This study Autio, 1990 Rheinheimer et al., 1989 Lahdes et al., 1988 Gocke et al., 1990 Autio, 1990 Gocke and Rheinheimer, 1991 Gocke and Hoppe, 1982a Gocke and Hoppe, 1982b Gocke et al., 1990 Gocke and Rheinheimer, 1991 Heinanen, 1991 Autio, 1990 Rheinheimer et a/. , 1989 Gocke et al.. 1990 Gocke and Rheinheimer, 1991 GalvBo, 1990 GalvCo, 1990

"Mean of the period September 1987 to May 1989. hMaximum value. 'Not known.

cyanobacteria. However, there is evidence for the growth of eukaryotic picoplankton in cold water (e.g. Kahru ef at . , 1991). We do not have growth estimates of eukaryotic picoplankton in order to assess the actual growth rate of eukaryotes during the spring bloom. However, the increase of their abundance during the growth season is not comparable


with that of cyanobacteria, which may be a consequence of decreased growth rate or increased loss rate. The reason why eukaryotic picoplankton are not a dominant algal group during the spring bloom and later during the summer is not clear. Their growth, although starting at an early stage, may be slow at least in cold environments, or they may be grazed, or some other factor (growth-inhibiting substances from other algae?) may be responsible for their slow increase. However, we lack completely the requisite knowledge of the physiology of picoplanktonic algae in the Baltic Sea.

The growth rate of picoplanktonic cyanobacteria is quite high in the Baltic Sea. The mean generation time is estimated to be 2 d at Tvarminne and 4 d at Umei. Growth rate may be controlled by the availability of regenerated nutrients, The number of picoplanktonic cyanobacteria is probably tightly grazer-controlled throughout the summer. Protozoan grazers are evidently actively grazing on cyanobacteria. In eutrophic waters, it may be that even at their maximum growth rate, picoplanktonic cyanobacteria consume only a small proportion of the available nutrients due to their low grazing-controlled biomass. This would explain the small relative fraction of picoplanktonic algae in eutrophic areas.

B. Grazing

As discussed earlier, the contribution of picoplanktonic algae to the algal biomass and production is of considerable significance. Sedimentation has been estimated to account for about SO% of spring production in the Kiel Bight (Smetacek et a f . , 1984) and S&70% in Tvarminne (Kuparinen et al., 1984; Lignell el al., submitted). Thus the fraction of picoplanktonic production in the total primary production actually consumed at the surface water layer is of even greater importance.

Grazing is in fact one of the decisive factors in the ecological significance of algal size fractions. Some very large algae (e.g. colonial and trichal cyanobacteria) are not grazed by zooplankton, which leads to intense algal blooms in the Baltic Sea. Similarly, the more intensive is the grazing control of algae and the more rapidly is primary production consumed, the less chance is there for an algal bloom. Carbon cycling through the microbial loop consists of many individual steps before the carbon enters the metazooplankton, and respiration losses are high. Consequently, the more carbon is cycled via the microbial loop the less energy is received by the higher predators. Thus there is great interest in the fraction of primary production incorporated via the microbial loop, either directly or indirectly via bacteria.


Picoplanktonic primary production may enter the microbial loop by protozoan grazing. Either protozoa may compete with metazooplankton for the prey or metazooplankton may be incapable of grazing on small algae. The latter explanation seems to fit picoplanktonic cyanobacteria, which are known to enter the guts of copepods, but which are not harmed by the passage through the gut (Johnson et al., 1982; Caron et al., 1985; Iturriaga and Mitchell, 1986). There are also indications of similar phenomena in the Baltic Sea (Kuosa, 1990~).

Protozoan grazers are known to graze effectively on picoplanktonic algae (Landry et al., 1984; Iturriaga and Mitchell, 1986; Hagstrom et al. , 1988; Nagata, 1988; Rassoulzadegan et a[ . , 1988). However, the only study from the Baltic Sea is that of Kuosa (1991) concerning fractionated incubations. In this study the grazing impact of nanoflagellates on picoplanktonic cyanobacteria was estimated. Nanoflagellates were found to be effective consumers of cyanobacteria, with 1 to 205 cells grazed/ nanoflagellateid. The number of grazed cells was a function of cyanobacterial abundance as flagellate clearance rates varied less (0.4 to 11.4 x 10-6mVflagellate). It was concluded that flagellates grazed on a large fraction of the primary production during summer and autumn (32 and 42%, respectively), but only a considerably smaller fraction during the winter and spring (6 and 396, respectively). Other grazing measurements with independent methods should be obtained before the validity of these figures can be confirmed.

A qualitative study revealed great differences between the particle capture abilities of ciliate species (Kuosa, 1990~). The ability to graze on picoplanktonic cyanobacteria was not a simple function of the predator’s cell size. Some medium-sized ciliates apparently grazed heavily on small particles (e.g. Cothurnia maritima, Strombidium sp., Tintinnopsis lobiancoi and Vurticella sp., Fig. S), but the smallest common ciliate did not ingest cyanobacteria at all. In the same study some chloroplast-containing flagellates were found to graze on particles. However, quantitative estimates of the grazing of picoplanktonic algae either by ciliates or by chloroplast-containing flagellates are not presently available from the Baltic Sea.

VII. Factors Controlling Bacterioplankton

A. Nutrient- and Carbon-limited Bacterioplankton Growth

Batch experiments without the presence of predators were performed to study nutrient and carbon limitation of bacterioplankton growth during

106

A

J . KUPARINEN AND H . KUOSA

FIG. 8. Examples cyanobacteria. A = sp.. 3@40 p m ; c =

B

D

of pelagic ciliates found to graze on picoplanktonic algae and Cothurnia maritirna (on Chaetoceros sp.), 35-45 pm; B = Strombidiurn Vorricella sp., 35-55 km; and D = Tintinnopsis lobiancoi, 50-70 pn.

different seasons. In low temperature water (<lO"C) in early spring, batches were incubated for several days to reach maximum growth in each of the manipulated batches (Fig. 9). At higher temperatures during the summer and autumn periods, incubation of 48 to 60 h was sufficient to determine the maximum growth (Fig. 9). The effects of manipulations were evaluated from the integrated value over the growth period and expressed as a percentage of the control unit (Fig. 10). Experiment 1 was


100 r

"0 1 2 3 4 5 6 7

Days FLG. 9. Thymidine incorporation rate (pmol/l/h) in early spring and summer batch

cultures. Cultures were enriched with 20 pgil of P as KH2PO4 and 80 of pg/l of N as NHdCI and 200pgil of C as Cj2H120,,.

carried out during the phytoplankton spring pre-bloom, experiments 2-5 during the post-bloom period, experiment 6 during late summer and experiments 7-10 during autumn, Experiment 3 (TV-89) was performed about 2 weeks after the phytoplankton chlorophyll-a maximum, when bacterioplankton growth was intensive as indicated by the high integrated value of the control sample in Fig. 10.


0 control EZ nutrients sucrose nutrients+sucrose

500

400

2 300 % 8 200

100

0

6

3 4 E c

2

0

Mav

1 June

Nov.

Oct. I

Oct.

GF-90 TV-87 N-89 TV-87 TV-88 GF-90 TV-87 K-87 K-87

Experiments

FIG. 10. Effects of inorganic nutrient ( N + P) and sucrose-carbon (C) enrichment (96 of the control) on hacterioplankton thymidine incorporation integrated (5-6 samples in 12 h or 24 h interval) over the growth period (upper graph) and integrated thymidine incorporation of control samples in different experiments (lower graph). Enrichments were the same as in Fig. 9. The location and the year of the experiments is given below the bars, G F = Gulf of Finland, TV = Tvarminne and K = Kiel Bight.


In all experiments in which inorganic nutrients were added alone, a moderate increase in production was detected. The single carbon (sucrose) addition markedly stimulated bacterioplankton growth only in the pre-bloom experiment and in the autumn experiment which showed very low bacterioplankton productivity. In other experiments the single carbon addition had only a minor effect or no effect at all (Fig. 10). In all experiments the combined inorganic nutrient and sucrose manipulation had the greatest effect on bacterioplankton productivity, 450% in the pre-bloom and about 300% in autumn experiments (Fig. 10).

These manipulation experiments reflect some general features of the Baltic Sea water and its nutritional status with respect to bacterial growth. During the pre-bloom period in spring, when inorganic nutrient concentrations are high, single inorganic nutrient manipulation has little effect on bacterial growth. In fact the slight stimulation of productivity in the pre-bloom experiment (Fig. 9) was more probably due to preference for the added ammonium nitrogen over the nitrate nitrogen which was present in the water column. Due to low phytoplankton biomass and growth, bacteria need carbon sources for their growth, in which case the single sucrose addition could provoke substantial growth. Similarly, during low phytoplankton activity in autumn, the combined inorganic nutrient and carbon manipulations could substantially stimulate bacterial growth.

During the post-bloom period when the dissolved products from phytoplankton bloom development have accumulated in the water column, bacteria are least affected by the manipulations (experiments 2-5 in Fig. 10). As suggested by the substantial bacterial growth of the control batch in experiment 3 , and the minor effects of sucrose manipulations (Fig. lo), good substrate availability prevails during the post-bloom period. Some rough estimates of the amount of organic substrates produced by phytoplankton during the bloom periods have been presented (Larsson and Hagstrom, 1982; Kuparinen et al., 1984; Lignell, 1990a; Lignell et al., submitted), suggesting that bacterioplankton growth could be sustained for several days at cell densities of 1-2 x 109/1 and at growth rates of 0.254.50/d.

During the late summer period, in experiment 6, sucrose addition had a negative effect on bacterioplankton growth (Fig. 9). However, when nutrients and sucrose were added together, a clear stimulation of growth was observed. This experiment may demonstrate the need for a correct C:N:P ratio in substrates required by bacteria for growth, as suggested by several authors (Goldman et al., 1987; Tezuka, 1990; Goldman and Dennett, 1991). Similar results were obtained in the post-bloom experiment (Fig. 11) in which the individual effects of nitrogen, phosphorus and

110

1.5

0.5

J . KUPARINEN A N D H . KUOSA

Man i pu I ati ons Fic,. 11. Effects of inorganic nutrient (N, P) and sucrose-carbon ( C ) enrichment on

bacterioplankton thymidine incorporation integrated ( 5 samples in 12 h interval) over the growth period. Enrichments were the same as in Fig. 9.

sucrose-carbon were tested. The results from individual manipulations suggested that phosphorus was the limiting factor for bacterioplankton growth during this period. The combined sucrose-carbon and phosphorus resulted in a slightly lower growth than the combined phosphorus and nitrogen. However, when sucrose was supplied together with nitrogen and phosphorus, a substantial stimulation of growth was obtained.

The results of these experiments suggest that during periods other than phytoplankton blooms, when exudates and products from sloppy feeding of micro- and mesozooplankton provide substrates for intensive growth even at low temperatures, Baltic Sea bacterioplankton is predominantly limited by inorganic nutrients in a proper C : N : P ratio. When the size of the labile DOC pool originating from the plankton community is small, bacteria must adapt to the use of the large refractory DOC pool (Ehrhardt. 1969), the utilization of which can be stimulated by inorganic nutrient addition. In the latter process, temperature plays an important role and may explain the large annual variation in the summertime productivity found at the entrance to the Gulf of Finland.


B. Predation Control of Bacterioplankton

Since the introduction of the microbial loop concept by Azam et al. (1983), microbial ecologists have been concerned with the role of bacterioplankton as a food source for higher trophic levels. Heterotrophic nanoflagellates are the main organisms controlling bacterial assemblages by predation in temperate marine (e.g. Fenchel, 1982; Andersen and Fenchel, 1985; McManus and Fuhrman, 1988) and freshwater (Bloem et al., 1989; Sanders et al., 1989) habitats. The close interaction between flagellates and bacteria has been demonstrated by coupled oscillations of the two groups (Andersen and Fenchel, 1985; B j~ rnsen et al., 1988). In the Baltic Sea, the coupled oscillation of bacteria and heterotrophic nanoflagellates has been demonstrated by Wikner and Hagstrom (1988) and Galvlo (1990). Coupled oscillation is also evident between bacterioplankton thymidine incorporation rate and flagellate numbers in 30 m3 plastic enclosures (Fig. 12).

Only a few studies of heterotrophic flagellate predation on bacteria are hitherto available from the Baltic Sea (Table 8). In the western Baltic Sea the mean ingestion rates, 28-38 bacteria/flagellate/h, were similar to maximum values of the whole range of 2-37 bacteriaiflagellateih obtained from Tvarminne, in the Gulf of Finland (Kuuppo-Leinikki and Kuosa, 1990; Kuuppo-Leinikki, 1990). In the Bothnian Sea the values were somewhat higher (Wikner et al., 1990) than those found in the Tviirminne area, although when a similar methodology was applied to both locations a comparable range in the die1 predation rates was obtained (Wikner e f al., 1990).

Areal comparison is difficult because different methods for measuring predation were applied in different localities except in the study of Wikner et al. (1990). In the Tvarminne study (Kuuppo-Leinikki, 1990), ingestion and clearance rates were low compared with values obtained using labelled bacteria as food sources for natural assemblages (Sherr e f al., 1987; Wikner et al., 1986, 1990). However, they were comparable with several other studies in which natural water samples were used (Wright and Coffin, 1984; Coffin and Sharp, 1987; Bjornsen et al . , 1988), suggesting that the fractionation method gives lower values than the method in which labelled bacteria are used as food.

The ingestion rates obtained from diffusion chamber experiments (Galvlo, 1990) were even higher than the rates obtained using fluorescently labelled bacteria and fluorescent particles (Sherr et al., 1987; McManus and Fuhrman, 1988). When a similar diffusion chamber technique was used, comparable ingestion rates were obtained (Landry et a[., 1984). From the above comparisons it is quite evident that several

112 J . KUPARINEN AND 11. KUOSA

4 n

0 Q

5 2

M HNAN

12

I Bag2

8

I

0 7

Bag 3

T -12 25

1 Bag5

0 5 10 15 20

Days

FIG. 12. Bacterioplankton production (cellsimlih x lo4) and number of heterotrophic flagellates (iml x 10’) in 30 mi plastic bags. Bags 1-4 were manipulated with nutrients (NH,-N and PO,-P) and small fish (stickleback fry) in a cross-over experiment. Bag 5 is the control unit. Kuuppo-Leinikki (unpublished).


TABLE 8. Rl-GlONAI DISTRIBUTION C)C SURFACE WATER NANOFI AGL-I I A T t PREDATION ON BACTERIOPLANKTON IN THE BALTIC SEA

Area Ingestion rate Clearance rate Predation rate Reference bact.iflag.1h nllflag.1h bact.lml/h

Bothnian Sea: range" &34 1-20 x 104 (1) medianh 3.0 x lo4 (1)

range" 1-20 x lo4 (1) daily mean 8.0 x 104

range'' 3-22 1-6 (2) ( 3 )

maximum" 6690 (4)

Tvarminne:

Tvarminne:

2-37 1-5 1-7 X lo4

Kiel Bight:

minimum' 13-14 m e a d 28-38

"Die1 study. "Median daily. 'Different calculation methods. "Diffusion chamber experiments in May 1988. 'Diffusion chamber experiments in July 1988. 'Diffusion chamber experiments 1987-1988, without the zero value in January 1958. (1) Wikner et ui., 1990. (2) Kuuppo-Leinikki and Kuosa, 1990. ( 3 ) Kuuppo-Leinikki. 1990. (4) GalvBo, 1990.

methodological calibrations and refinements are needed to obtain better geographical comparability of the ingestion and clearance rates of bacteria by heterotrophic flagellates. Die1 periodicity of bacterioplankton and flagellates has been analysed by Wikner et af. (1990). Bacterial mortality (Pace, 1988) other than predation has been neglected from the estimates since practically no data exist on mortality rates in the Baltic Sea.

In comparison with predation vs. bacterial growth, heterotrophic nanoflagellates were able to remove more than 100% of the bacterial production at maximum ingestion rates (Wikner et al., 1990; Kuuppo- Leinikki, 1990; GalvHo, 1990) in all studies. Wikner et al. (1990) found predation to exceed production in several study sites by a mean factor of 2.6 (s.e. = 0.7). Since no net decrease in bacterial numbers was observed to explain the imbalance, they focused on methodological errors involved in the measurements. They concluded that bacterial production was most probably underestimated by the ?TI method due to the use of a


conservative conversion factor of 1.7 X 10" cells produced per mole of thymidine incorporated.

Conversion of tritiated thymidine incorporation into bacterial cell production is the first step in the TTI method. This conversion, unlike the conversion of biovolume production to carbon production, is well established and has been shown to lie near to the value of 1.1 x 10'' cells/mole as calculated by Riemann et al. (1987) in many marine environments. In freshwater environments and in eutrophic marine environments higher conversion factors have been reported (Smits and Riemann, 1988). The low salinity environment in the northern, coastal stations may give rise to the conversion factor value obtained in the Baltic Sea.

With regard to the Baltic Sea bacterioplankton, the use of a single conversion factor obtained from marine environments may not be justified. Galvgo (1990) found greater disagreement between production and ingestion rates estimated by the TTI method when using a single empirical conversion factor than when using experimentally determined conversion factors in the Baltic Sea. Experimental conversion factors were lower in the unfiltered samples (mean 0.5 x 10" cells/mole) than in the filtered samples (mean 1.7 x 10" celldmole).

Several conversion factor experiments have been made with Gulf of Finland waters in connection with the nutrient and carbon enrichment experiments. The overall mean of the factors was 1.8 ( n = 27) (Fig. 13), with no significant deviation between the values from manipulated and unmanipulated enclosures.

The mean conversion factor is somewhat higher than the mean of 1.1 x 10'' cells/mole reported by Riemann et al. (1987), but still within the range reported by several authors (e.g. Kirchman et al., 1982; Bell, 1990; Riemann and Bell, 1990; Bjornsen and Kuparinen, 1991). Conversion factors from 0.6 to 3.9 x lo1* cells/mole have been reported earlier from the same locality (Bell, 1986; Kuparinen, 1988). Autio (1992) obtained conversion factors well above 2 from the same locality at low temperatures. "Near natural" conversion factor values could be determined in 30 m3 experimental enclosures due to the coupled oscillation of heterotrophic nanoflagellates and bacteria (Fig. 12). During the latter part of the experiment cell numbers and thymidine incorporation rates increased for several days, most probably due to the low number of predators (Kuuppo-Leinikki, 1990). The conversion factor values calculated from two of the five experimental units were 1.6 x 10" cells/mole and 1.4 x 10" cells/mole. These values must be considered as conservative estimates since a minor predation impact was observed during the exponential growth period, decreasing the accumulation of cells in the


0

6) 0 0

0

I I I

0.5 1 1.5 2 Specific growth rate, l/d

FIG. 13. Conversion factors of thymidine incorporation to cell production (10'' cellsimol) in different batch culture experiments. Conversion factors were plotted against specific growth rates. Samples were taken from the Gulf of Finland and from the Tvarminne sea area (see Fig. 1 for the location).

enclosures. These experiments suggest that a higher conversion factor value of, for example, close to 2 x 10" cellshole could be used for Baltic Sea samples.

VIII. Bacteria in the Pelagic Food Web

In many aquatic ecosystems, bacteria have been considered to be the major decomposers of organic matter (Steele, 1974; Fenchel and Black- burn, 1979). Due to the introduction of new techniques to measure growth rates of bacteria (Hagstrom et al., 1979; Fuhrman and Azam, 1980; Moriarty, 1986), many investigators have suggested that production of particulate heterotrophic bacterial biomass provides an important link between dissolved organic matter, detritus and higher trophic levels (e.g. Pomeroy, 1974; Williams, 1981).

The growth of bacterioplankton and the level of their standing stock are controlled by several abiotic and biotic factors such as concentrations of organic substrates and inorganic nutrients and predation. In open ocean ecosystems, where the bulk of organic carbon comes via phytoplankton production, close coupling between phytoplankton and bacterioplankton


production can be expected (Cole et af., 1988). In a cross-system overview Cole et af. (1988) found that 57% of the variance in bacterial production was explained by primary production on a volumetric basis in the photic zone. When bacterioplankton cell numbers were added to the model, 73% of the variance in bacterioplankton production was explained. In the Baltic Sea, considerable loading from land-based organic and inorganic matter reaches the gulf areas, the Gulf of Bothnia, the Gulf of Finland, the Gulf of Riga and the western Baltic Sea. In these areas, as in estuarine systems (Findlay et af., 1991), bacterioplankton production may be based on carbon sources other than those arising from primary production.

Bacterioplankton production values measured in the Baltic Sea are within the range of 0.4 to 153 mg C/m3/d reported by Cole et af. (1988). The majority of the Baltic Sea values fall below the average value of 26.4mgC/m3/d obtained by Cole et af. (1988), but are close to their median value of 11.5 mg C/m3/d (Table 4). The fragmentary primary production data from the Baltic Sea (Lassig ef af., 1978; Schulz et af., 1990) does not allow comparison with the regression line of Cole et af. (1988), but their general trend between bacterioplankton and phytoplankton production is evident in the Baltic Sea data (Fig. 5 , Table 4). The low values recorded in the northern and central Baltic Proper for bacterioplankton (Table 4) also correspond with the primary production of the area (Lassig et af., 1978; Schulz et af., 1990). This trend agrees with the data of Cole et af. (1988) suggesting that phytoplankton production is the primary basis of bacterioplankton growth in the open Baltic Sea.

Cole et af. (1988) concluded that bacterial production averaged 20% (median = 16.5%) of primary production for the pelagic data on a volumetric basis. When they considered the entire water column on an areal basis, bacterial production was even more significant, averaging 30.6% (median = 27.1%) of primary production. In the Baltic Sea, Larsson and Hagstrom (1982) measured bacterial production with the FDC (frequency of the dividing cells) technique in the southern Stock- holm archipelago (Asko, Fig. 1) as 24% of phytoplankton primary production. In a similar study site near the coast of the Gulf of Finland (Tvarminne, Fig. 1) Kuosa and Kivi (1989) measured annual bacterial production with the thymidine technique as 15% of net primary production.

The batch experiments (Fig. 10) support the conclusions of Larsson and Hagstrom (1982) that phytoplankton exudation is the primary basis of bacterioplankton growth in spring. The sucrose additions had little effect on bacterioplankton growth after the peak of the spring bloom, whereas substantial stimulation by carbon sources was observed during the initial


phase. In the northern Baltic Proper, where a substantial part of the phytoplankton spring bloom escapes from the photic layer by sedimentation (Kuparinen et al., 1984; Lignell et al. , submitted), bacterioplankton plays an important role in transferring the energy lost by phytoplankton exudates and sloppy feeding to succeeding microbial communities.

In many areas of the Baltic Sea, where the phytoplankton spring bloom ends with the removal of inorganic macronutrients from the stratified upper water column, the scarcity of labile carbon compounds begins to limit bacterioplankton growth. In the northern Baltic Proper this process occurs simultaneously with the development of heterotrophic nanoflagellate communities, making predation one of the main controllers of bacterioplankton standing stocks (Lignell et af., submitted). Bacterio- plankton and heterotrophic nanoflagellate growth rates reported from different areas of the Baltic Sea (Wikner et af., 1990; Lahdes et af., 1988; Galvlo, 1990; Heinanen and Kuparinen, 1991) are quite similar, or even higher for heterotrophic nanoflagellates. This suggests the possibility of a rapid response from heterotrophic nanoflagellates to changes in bacterioplankton standing stock, as demonstrated by the coupled oscillations in experimental ecosystems (Fig. 13). Moreover, as demonstrated by, for example, Kuosa and Kivi (1989), flagellate carbon demand may exceed the supply from bacterioplankton, making heterotrophic nanoflagellates potentially reactive to increases in bacterioplankton standing stock.

Very few data exist concerning heterotrophic flagellate communities in the open Baltic Sea. However, the results of a few experiments suggest that the control of bacterioplankton by heterotrophic nanoflagellates may explain the low variability found in the late summer stage in the standing stocks of bacteria in the whole Baltic Sea (Autio, 1990; Gocke et af., 1990; Gocke and Rheinheimer, 1991; Heinanen and Kuparinen, 1991). Low variability during summer has also been found in cell volume measurements in the Gulf of Bothnia (Fig. 14). This low variability in cell volume may be explained as selective predation by heterotrophic nanoflagellates (Anderson et al., 1986; Gonzales et af., 1990; Kuuppo- Leinikki, 1990; Monger and Landry, 1991). When the variability in cell volumes in spring, and the large cells found in winter when predation is negligible (Fig. 14), are taken into account, the explanation of predation control is even more attractive. However, the present data do not provide a straightforward answer to this speculation because other factors could explain the same observations of cell volume seasonality. The high surface-to-volume ratio of small cells may be an adaptation to low nutrient concentrations typical in the summer period (van Gemerden and Kuenen, 1984).

Exceptionally high bacterioplankton counts of 8 to 10 X lo9 cells/l


cr)

E a

January 0.12 -

0.08

0. 04

0

0.12

0.08

0.04

0

0.12

0.08

0.04

0

1 ?. February

0 0

June 0

0

& 0

B U 0

August % i .a w * * ** B * ** * a * *

0 0.5 1 7.5 2 2 5 3 3.5

ce//qm/ X I O 6

FIG. 14. Mean hacterioplankton cell volumes (pm3) in samples obtained from the Gulf of Bothnia. Circles are samples below the thermocline and stars samples above the thermocline in the August data (Heininen. 1992a. submitted).

found even in open areas of the Baltic Sea during cyanobacterial blooms in summer may have been a result of a simultaneous lack of predation control and high substrate availability. Ignoring these extreme cases, but assuming cell number of 5 x lo9 celldl as an average for pelagic waters in


the Baltic Sea and using a conservative cell volume estimate of 0.032 (Table 6) and the carbon conversion of 0.35 pg CIpm3, bacterioplankton biomass would be 56 mg C/m3. This is within the range reported from the Baltic Sea (Table 7). In the carbon-limited summer situation indicated by the batch experiments (Fig. 9) and confirmed in many aquatic environments (Nagata, 1986; Kogure and Koike, 1987; Kirchman el al., 1990), the bacterial C : N ratio by atoms would be 4.5 : 1 (Goldman and Dennett, 1991). For an average bacterial biomass of 56 mg C h 3 , this would mean that 1 mmol or 14 mg of nitrogen/m3 is reserved in bacterioplankton biomass.

During warm water periods in summer, bacterioplankton growth rates of 0.5 to lid are common (Galvfio, 1990; Kuparinen and Heinanen, 1992; Wikner et at., 1990). If predation equals (or even exceeds) bacterioplankton production, then more than half of the total nitrogen reserve in bacteria is continuously transferred to higher trophic levels for regeneration. The low ambient nitrogen concentrations found in the stratified upper water column in the Baltic Sea during summer periods (Nehring et uf., 1990) and the low C:N ratio (Goldman and Dennett, 1991) make bacterioplankton effective concentrators of inorganic nitrogen. For phytoplankton production, the close coupling between bacterioplankton and other heterotrophs is thus essential.

IX. Acknowledgements

This study is a contribution to the research project PELAG under which most of the data have been obtained. The Finnish Academy, University of Helsinki, Maj and Tor Nessling Foundation, Walter and Andree de Nottbeck Foundation and the Finnish Institute of Marine Research have provided funding for this study. We are grateful to Tvarminne Zoological Station, to the University of Helsinki and to the Finnish Institute of Marine Research for providing facilities to carry out these studies. We also want to express our gratitude to our colleagues in the project PELAG and in the Finnish Institute of Marine Research for inspiration and feedbacks to continue our efforts in the field. The work of Mr Michael Bailey for checking the language of this article is greatly appreciated.

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