Limnol.
Oceanogr.. 38(3), 1993, 532-546
Sociely of Limnology
0 1993, by the American
and Oceanography,
Inc.
Limnetic macroscopic organic aggregates (1a:kesnow):
Occurrence, characteristics, and microbial
dynamics in Lake Constance
Grossart and Meinhard Simon
Hans-Peter
Limnological
Institute,
University
of Constance, P.O. Box 5560, D-7750 Konstanz,
Germany
Abstract
We have studied macroscopic aggregates sampled in situ by SCUBA diving in Lake Constance. Such
aggregates are well known from marine environments as marine snow but have not been studied extensively
in lakes. In contrast to marine snow, formation of lake snow aggregates is mostly dependent on windinduced turbulences. Our results show that abundance, chemical composition, settling velocity, microbial
colonization,
and bacterial production of lake snow are fairly similar when compared to marine snow.
The component particle composition
reflects the composition of the plankton community in the bulk
water. The mean size of our lake snow aggregates was fairly small (5 mm) although the aggregates were
densely colonized by bacteria. The bacterial abundance on aggregates on a per volume basis was m lo8
ml- I, which is 100 x higher than in the bulk water. The turnover of lake snow aggregates on the basis of
bacterial protein production and particulate combined amino acids on aggregates usually was between 3
and 30 d. Soluble reactive phosphorus (SRP) concentrations in the matrix water of aggregates were > 1,000
times higher than in the surrounding water when its SRP concentrations were close to the detection limit
(0.05 PM). These results indicate that lake snow aggregates are important sites for nutrient regeneration
with enhanced microbial activity. On the basis of abundance and dry weight, we estimated that lake snow
aggregates comprised 2040% of the detrital particulate organic C. This finding indicates that lake snow
is important for the cycling and flux of elements and energy in lakes and needs to be included in the
conceptual framework of lacustrine ecosystem studies.
Many investigations have shown that particulate organic matter (POM) is of great importance for the transformation
and cycling of
elements in pelagic marine and limnetic ecosystems (e.g. see Fowler and Knauer 1986;
Alldredge and Silver 1988; Bloesch et al. 1977;
Stabel 1987; Weilenmann et al. 1989). Most
of the phytoplankton primary production originates and is transferred further in the food
web in particulate form. Eucaryotic heterotrophic organisms ingest their food mainly in particulate form but the growth of heterotrophjz
bacteria is also dependent on POM, although
they take up only dissolved organic matter.
Phytoplankton and small detrital particles can
aggregate into larger particles (Alldredge and
Gotschalk 19 8 9; Alldredge and McGillivary
Acknowledgments
This work was part of the Deutsche Forschungsgemeinschaft-sponsored Special Collaborative
Program “Cycling
of Matter in Lake Constance” (SFB-248).
We would like to thank our colleagues for their support,
in particular B. Rosenstock for technical help in the lab,
D. Springmann for help with SEM, and M. M. Tilzer, who
made the whole program possible. We also appreciate
helpful comments on this paper by A. L. Alldredge and
two anonymous reviewers.
532
1991) and may sink out of the euphotic zone
as d.ead and living POM, thus providing energy
to heterotrophic organisms in aphotic waters
and1 sediments. Besides organic matter most
particles, even in pelagic ecosystems, contain
large amounts of inorganic matter (Alldredge
1979; Stabel 1987; Weilenmann et al. 1989)
which are important for adsorption and desoqption of dissolved compounds and may have
a significant impact on the chemical and bio1og:ical properties of the water (Honeyman et
al. 1988; Santschi et al. 1988).
Macroscopic
organic aggregates (marine
snow) are an important component of particulate matter in the ocean and contribute substantially to the transformation
and flux of organic matter (Fowler and Knauer
1986;
Alldredge and Silver 1988). Although the existence of detrital particles in lakes has been
shown by filtration and microscopic examination (e.g. Paerl 1974; Pedrbs-Alio and Brock
1983) or sediment trap studies (Bloesch et al.
19’77; Stabel 1987; Weilenmann et al. 1989),
the existence of macroscopic organic aggregates analogous to marine snow has not, to our
knowledge, been documented. Most marine
snow aggregates are very fragile and can be
Lake snow in Lake Constance
collected in situ only by SCUBA diving (Alldredge 1979; Silver et al. 1978). This technique
has not yet been applied to study macroscopic
organic aggregates in lakes. It is important to
elucidate the role of lake snow to better understand interactions between the particulate
and dissolved phase and the cycling and flux
of organic matter in lakes.
In this study we report the occurrence and
significance of lake snow aggregates. We have
studied the abundance, chemical composition,
and microbial processes of lake snow in Lake
Constance (Bodensee). Our results indicate that
the significance of macroscopic aggregates is
very similar in lakes and the ocean.
Materials and methods
Study site, abundance, and field collections
of aggregates - The study was performed in
the Uberlinger See, the northwestern arm of
Lake Constance at a station with a maximum
depth of 60 m. Lake Constance is a large, prealpine, mesotrophic lake in which the nutrient
load has been substantially decreased during
the last 10 yr (Tilzer et al. 199 1). The phytoplankton, zooplankton, bacteria, and sedimentation have been studied extensively (Sommer
1984; Simon 1987; Stabel 1987; Geller 1990;
Tilzer et al. 199 1). Individual macroscopic aggregates 3 mm or larger were studied during
80 SCUBA dives from April to November
1990 between the surface and 25-m depth.
The abundance of aggregates >3 mm was
estimated in two ways. If the abundance was
low (< 5 agg. liter- I), aggregates were counted
visually in situ in a glass bottle with a lo-cmwide opening carefully filled with 500 ml of
water at a given depth in five replicates. At
higher abundances aggregates were counted on
five photographs per depth taken with an underwater camera system according to Landmann (1988) and modified after Honjo et al.
(1984). Abundance usually was determined at
5-, 15-, and 25-m depths, but if distinct layers
occurred at other depths they were recorded
as well.
Aggregates were collected with 6-ml openended plastic syringes closed with a stopper as
described in detail by Gotschalk and Alldredge
(1989). To better identify the individual
aggregates, we used a magnifying lens (10 x ) and
an underwater spotlight for collection. Only
aggregates >3 mm were collected, usually at
533
the same depths in which the abundance was
measured. The aggregates remained in the syringes in a cooling box until further processing
in the lab, usually within 1 h. At each depth,
bulk water was collected in a 500-ml glass bottle from which subsamples for all measurements of parameters of the surrounding water
were taken (see below).
Several aggregates were always examined
microscopically
and categorized in terms of
their morphology and particle composition. On
most sampling dates several aggregates were
prepared for scanning electron microscopy
(SEM) according to Paerl(1974) and examined
with a Zeiss SEM (DSM 950).
Sinking rate-The
sinking rate of aggregates
was determined in a 2-liter graduated cylinder
filled with lake water from the depth of sampling. It was measured visually as the time of
an aggregate travelling through a distance of
20 cm and calculated as the mean of 10 individual measurements. For better visibility,
some aggregates initially
were stained with
methylene blue. Thereafter, the unstained aggregates were used for dry weight determination (see below).
Chemical characterization -Total C and the
C : N ratio were determined by CHN analysis
with a Carlo Erba instrument. Dry weight and
ash-free dry weight (AFDW) were determined
on precombusted
(5 50°C) and preweighed
glass-fiber filters (Schleicher & Schuell). Five
to ten aggregates on one filter were first dried
at 100°C for 1 h, weighed, and then combusted
at 550°C for 2 h. We assumed particulate organic C (POC) as 50% of the AFDW. Particulate combined amino acids (PCAA) were
measured after acid hydrolysis as dissolved free
amino acids (DFAA) by high-performance
liquid chromatography
(HPLC; see below).
Phosphorus in the matrix water of aggregates-Soluble
reactive phosphorus (SRP) was
determined in the matrix water of aggregates
as follows. Ten aggregates were pooled in 15
ml of HPLC-grade water and gently disrupted
in a tissue grinder. SRP was analyzed by standard techniques with an autoanalyzer.
Amino acid analysis- We examined DFAA
in the surrounding water by HPLC after precolumn derivatization
with o-phthaldialdehyde as modified by Simon and Rosenstock
(1992). To determine dissolved combined
amino acids (DCAA) in the surrounding water,
534
Grossart and Simon
we hydrolyzed the samples in double-distilled
Leucine incorporation
rates (LeLli,,) were
6 N HCl for 20 h at 110°C. To prevent amino
converted to bacterial protein production (BBP)
acid oxidation due to high nitrate concentraaccording to Simon and Azam ( 19 89):
tions, we added 20 ~1 of ascorbic acid (2 mg
BPP = Leuinc X 1,797 X Fl X ID
ml- I) to the sample before hydrolysis. Samples
for determinations of DFAA and DCAA were where Fl is the fraction of Leuinc in the hot
prefiltered through 0.2~pm filters with low proTCA-insoluble
material as percent of the icetein-binding
capacity (Gelman Acrodisc) imcold TCA precipitate (0.85) and ID the intramediately after return to the lab. For analysis
cellular isotope dilution of Leu. We used ID
of PCAA, 3-5 pooled aggregates were hydro= 2: which was determined as an annual mean
lyzed as DCAA samples. After hydrolysis both
in Lake Constance (Simon and Rosenstock
1992).
DCAA and PCAA samples were analyzed with
HPLC as DFAA.
Thymidine
incorporation
rates were conBacterial numbers and biomass-Bacterial
vertcd to the bacterial cell multiplication
rate
numbers were counted by epifluorescence mi(BCM) by the factor 2.0 x lOI* cells (mol
croscopy after DAPI staining. Free-living bac- TdR- I. This factor was calculated from the
ID determinations
with leucine (Simon and
teria were filtered onto prestained 0.2~pm Nuclepore filters. To count bacteria on aggregates Rosenstock 1992).
we disrupted the aggregates by ultrasonic treatResults
ment in 2 mM Na-pyrophosphate
before stainThe study began in late April during the phying (Velji and Albright 1986). Bacterial biomass was calculated from cell numbers and an toplankton spring bloom when Stephanodiscus
assumed cell volume of 0.053 pm3 for free- hantzschii and Rhodomonas ssp. were dominant. The clear-water phase followed the spring
living and 0.153 pm3 for aggregate-associated
bacteria. These numbers are annual means for bloom in late May and lasted until mid-June.
Thereafter, large diatoms such as Asterionella
Lake Constance as determined
by Simon
formosa,
Fragilaria
crotonensis,
Diatoma
( 1987). Cell volume was converted to protein
elongata, and Melosira granulata started to
according to Simon and Azam ( 1989) yielding
leading to the
19 fg of protein per free-living and 53 fg of dominate the phytoplankton,
phytoplankton maximum in July. Only in July
protein per aggregate-associated cell.
a fairly stable thermal stratification was estabBacterial production-Bacterial
production
lished with surface temperatures of 18-23°C.
was measured by incorporation of [3H]thymidine (TdR; Fuhrman and Azam 1980) and SRP in the epilimnion was co.05 PM during
this period when the phytoplankton below the
[ 14C]leucine (Leu; Simon and Azam 1989) into
surface was composed of various green algae.
the ice-cold trichloroacetic
acid (TCA) fracStratification lasted until late September when
tion. A dual-label approach was applied (Simon
the mixing depth increased again. From midet al. 1990). Briefly, TdR (75 Ci mmol-‘;
cyanoAmersham)
and Leu (3 12 mCi mmol-’ ; July until November colony-forming
Amersham) were added to triplicate samples bacteria such as Anabaena circinalis and Microcystis aeruginosa became abundant in the
and a killed control, both at a final concentration of 30 nM. The protocol of Simon and surface layer.
A bundance, size, and composition -AggreRosenstock (1992) was applied for free-living
bacteria. For attached bacteria, 5-10 aggre- gate abundance varied between < 1 and 50 ligates were pooled in 5 ml of surrounding lake ter - * (Fig. 1). Highest numbers occurred between the surface and 5 m in July and from
water. TdR and Leu were both added at a final
late
August until early October when aggreconcentration
of 60 nM. Pre-experiments
of coloshowed that 60 nM additions of TdR and Leu gates were composed predominantly
yielded nearly maximum incorporation
rates. ny-#forming cyanobacteria. Except when the
Incubation was at in situ temperature in the latter occurred, abundance usually increased
dark. It was stopped after 1 h with 2% For- with depth. Fairly often very few (< 2 liter- ‘)
aggregates > 3 mm were recorded between the
malin (final concn). The sample was filtered
onto a 0.45~pm cellulose nitrate filter and ra- surface and 5 m (Fig. 1). From July until September, we observed a relative accumulation
dioassayed thereafter.
535
Lake snow in Lake Constance
50
”
3
s
r. q
40
II
I
5m
W
15m
- E
25m
I
I
I
I
I
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I
I
I
II
1
I
I
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I
30
8
g 20
a
Fi
2 10
0
28 3
Jun
Fig.
1.
Abundance
5 11 16 16 18 28 5
I
9 10 16 22 24 27 31 5 10
Jul
Aw
of aggregates >3 mm. No bar indicates that ~2 aggrcgatcs liter-’
of aggregates at two thermoclines in 6 and 15
m. Except for cyanobacteria-dominated
aggregates, lake snow formed or increased in abundance after a day with fairly strong wind. We
repeatedly observed this, but it was most pronounced at the end of the diatom bloom in
July when the largest aggregates were recorded
(2 cm). Such large aggregates rarely occurred,
but larger ones generally were more abundant
in greater depths. After wind-induced
formation, aggregates obviously settled out of the
depth of formation rather quickly because usually after 2 d these depths were cleared (see
above). Cyanobacteria-dominated
aggregates,
however, occurred independently of wind; in
contrast, they prevailed near the surface during
calm periods. The mean size of aggregates was
-5 mm in diameter which translates into a
volume of 65 mm3 agg.- l, assuming spherical
shape. We did not have enough data to detect
systematic differences in the mean size and
volume with depth and time, and with different types of aggregates.
In situ observations revealed various shapes
of aggregates such as comets, compact spheres,
and more transparent and fairly fragile aggregates, comparable in shape to those found in
oceanic environments
(Alldredge and Silver
1988). Four major types of aggregates could
be identified microscopically:
those composed
3 23 20
SeP
Ott Nov
were recorded.
of different algal cells or debris depending on
the composition of the phytoplankton present;
those of molts or dead bodies of various zooplankton, mainly of Daphnia ssp. the dominating cladocerans in Lake Constance during
the growing season after the spring bloom; those
composed of colony-forming
cyanobacteria;
and those composed of miscellaneous particles
such as phytodetritus,
zooplankton,
and unidentifiable organic and inorganic debris. The
composition of aggregates usually reflected the
composition of the plankton community except when colony-forming
cyanobacteria dominated on aggregates. In July and August, aggregates were enriched
in autotrophic
picoplankton relative to the surrounding water. Phytodetrital
aggregates were more compact (fresh phytodetritus) or more fragile structures containing algal debris and transparent,
mucuslike material, depending on the type and
physiological state of algae. Aggregates of zooplankton origin, either alone or associated with
phytodctritus, were always found but were most
abundant during the clear-water phase. Their
distribution
was always rather patchy. Aggregates of phytoplankton and zooplankton origin
collected in May and July were often covered
with calcite crystals as shown by SEM. With
SEM we also detected weblike structures similar to those reported by Pearl (1974) and Pe-
l
5m
8
42I
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l- 1s
1.
Irr.,
1
c)
n
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4
un
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1
8
6
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DFAA
DCAA
PCAA
-III
31
24
May Jun
3
13
Jul
18
23
27
3
.
ili_ALL
I LI -
15
Aw
22
27
5
17
SeP
25
3
23
Ott
20
Nov
537
Lake snow in Lake Constance
Table 1. Sinking rates of various lake snow aggregates
determined in a graduated cylinder as the mean of 10
individual measurements, mean f SD.
Type of aggregate
Daphnia molts
Copepod carcass
Phytodetritus
Diatoms
Green algae
Cyanobacteria
Miscellaneous
N
Size
(mm)
37.1t-1.8
57.0
8
3
1
3
130.0+57.8
5.0
0.0
25.0+ 1.O
8
2
5
8
5-20
5-8
5-10
6-12
Sinking rate
(m d-l)
dros-Alio and Brock (1982), gluing together
the components on aggregates. All aggregates
were densely colonized by bacteria (see below)
and also colonized by flagellates and ciliates.
Sinking rate-The
sinking rate was highly
variable depending more on type than on size
of aggregates. Highest rates (> 100 m d- ‘) were
measured with diatom floes (Table 1). Zooplankton molts and carcasses exhibited sinking
rates between 36 and 57 m d-l, whereas phytodetrital aggregates not comprising diatoms
had much lower sinking rates (Table 1). Nearsurface cyanobacterial
aggregates often remained buoyant and did not sink at all.
Chemical characterization -The dry weight
of aggregates varied between 3 and 100 pg
agg.- l. Aggregates of zooplankton origin exhibited the highest dry weight, whereas those
of individual
molts were in the range of other
aggregates including phytodetritus
(Table 2).
The C : N ratio of aggregates varied between
5.1 and 8.9 with mean values between 5.8 and
7.1 for different types (Table 2). Aggregates of
Daphnia molts exhibited a POC content of
16.3 pg C agg. - l (Table 2). If we assume POC
to be 15% of the total dry weight (Alldredge
1979), then the POC of individual
Daphnia
molts and miscellaneous aggregates was 1.6
and 2.5 pg C agg. - l, respectively.
PCAA varied between 0.12 and 2.45 nmol
agg.- l, equivalent to 15.5 and 2 11 ng agg?
when an average formula weight of amino acids of 120 is assumed. Daphnia molts and miscellaneous aggregates on average comprised
162 and 8 5 ng PCAA agg. - l (Table 2). On the
basis of the POC calculation (see above) and
assuming C as 50% of the formula weight of
amino acids, PCAA comprised between 0.7
and 15% of POC on aggregates with an average
of 14 and 7% on Daphnia molts and miscellaneous aggregates, respectively. PCAA on aggregates per liter (PCAA agg. - Ltimes aggregate
abundance) usually was in the range of 0.2-2
PM and intermediate
between DFAA and
DCAA concentrations (Fig. 2).
Concentrations of SRP in the matrix water
of aggregates were significantly higher than in
the surrounding
water during stratification.
Whereas in the surrounding water SRP was
near or below the detection limit (0.05 PM) in
August, it was enriched 1,447-2,650-fold
in
the matrix water of aggregates (Table 3).
Bacterial abundance and biomass-Aggregates were densely colonized by bacteria. Total
numbers ranged from 1.2 to 22.6 x 1O6agg. - I,
equivalent to 0.2-3.4 x lo8 cells ml-l of aggregate volume (65 mm3). Numbers per aggregate in deeper layers were higher than near
the surface (Fig. 3). Because the abundance of
aggregates increased with depth the number of
aggregate-associated bacteria was enhanced
with depth even more except when cyanobac-
Table 2. Type, dry weight, C: N ratio, particulate organic carbon (POC), and particulate
(PCAA) of aggregates. N-Number
of samples; nd-not
determined.
TYPC
(rg)
N
C:N
N
Single Daphnia molts
Aggregates of Daphnia molts
Phytodetritus
Miscellaneous
1 l.Ok4.3
75.0+ 19.1
7.7+ 1.3
9.2k8.6
13
4
2
10
7.1k1.4
nd
5.8kO.l
7.0f1.9
10
2
10
POC
(Pep)
nd
16.31L2.5
nd
nd
combined
N
4
amino acids
PCAA
W
162+98
nd
nd
85*40
N
5
3
t
Fig. 2. Concentrations
of dissolved free (DFAA) and combined amino acids (DCAA) in the surrounding water,
and particulate combined amino acids (PCAA) on aggregates. PCAA was calculated from the PCAA per aggregate
times aggregate abundance. No bar indicates no measurement.
Grossart and Simon
538
Table 3. SRP (PM) in the surrounding
matrix water of lake snow aggregates.
10 Aug
16 Aug
* IIclow detection
limit
Depth
(ml
Water
15
25
15
25
0.1
0.1
bd*
bd
water and in the
Lake snow
145
318
72
116
(0.05 FM).
terial aggregates were abundant near the surface. Fresh phytodetritus and molts were colonized mainly by cocci and rods x0.6 pm, but
more degraded phytodetritus and molts were
inhabited by larger rods <4 pm long. The biomass of bacteria on aggregates ranged between
64 and 1,197 ng protein agg.- 1which is higher
than PCAA agg. - 1(see above). When the range
of error in the measurements of PCAA and
bacterial abundance on aggregates (see discussion) is considered, these numbers indicate that
bacteria are a major protein component on
aggregates.
Abundance of aggregate-associated bacteria
per liter was always a minor fraction of total
planktonic bacteria and accounted for 2-7% of
total bacterial numbers near the surface and
for 5-l 2% at 25 m. From late August until
November
numbers of free-living
bacteria
ranged between 0.74 and 2.9 x lo9 liter-’ with
r
05 m
28 3
5 11 16
Jun
hig:hest values near the surface. On the basis
of an equivalent volume, however, bacterial
numbers on aggregates were 100 x higher than
in the surrounding water (see above).
Bacterial production on aggregates- BPP on
aggregates ranged from 0.1 to 1.8 ng protein
agg.-’ h-l (Fig. 4). There were no pronounced
seasonal and vertical patterns. If we take the
aggregate abundance into account, however,
BPP on aggregates liter- 1 was highest at 5 m
when cyanobacterial aggregates occurred. Rates
per liter in 15 and 25 m were lower and fairly
similar. Protein production
of aggregate-associated bacteria usually accounted for 2-l 0%
of total BPP but higher values of 20-30% occurred sometimes at 5 m at the end of algal
blooms. Total BPP ranged between 0.02 and
1.1 pg protein liter- I h-l with highest values
nea.r the surface (Fig. 4). On the basis of an
equivalent volume, BPP on aggregates was 2030 times higher than in the surrounding water.
The BCM rate on aggregates ranged between
0.2 and 6 x lo4 cells agg.-1 h- * (Fig. 5). Values
in ,4ugust when cyanobacterial aggregates occurred were lowest. There was no pronounced
vertical difference. The bacterial cell multiplication rate on aggregates always accounted for
~6% of total BCM which ranged between 0.3
and 4 x 1O7 cells liter- 1 h-l (Fig. 5). On the
basis of an equivalent volume, BCM on ag-
1115 m
El25 m
6 22 24 27 31 6 10 26 3 23 20
Jul
Fig. 3.
Bacterial abundance per aggregate. No bar indicates no measurement.
Nov
Lake snow in Lake Constance
surrounding
539
water
1.5,"""""""""""'
I q l5m
n
l5m
l325m
on LAKE SNOW
2.0,""""""""""
11,
ll5m n
1
15mB25m
1.5
1.0
0.5
0.0
---
28 3
Jun
6
11 16 16 19 29 6
0
Jul
JJLL
11 26
SeP
Fig. 4. Bacterial protein production (BPP) in the surrounding
scales. No bar indicates no measurement.
gregates was lo-20 times higher than in the
surrounding water.
’
Protein per new cell (BPP : BCM), a parameter to compare Leu- with TdR-based production rates (Simon et al. 1990) ranged from
5.5 to 338 (mean: 55+62; N = 61) fg protein
cell-’ for free-living bacteria and from 5 to
10 16 22 24 27 31 6
3 23 20
act
Nov
water and on lake snow aggregates. Note the different
2,314 (mean: 151+314; N = 69) fg protein
cell * for aggregate-associated bacteria. On
some dates this ratio was similar for free-living
and aggregate-associated bacteria, but on others it was much higher for the latter. Although
wide variations occurred, this ratio indicates
that, on average, aggregate-associated bacteria
Grossart and Simon
surrounding
W15m
m
s
El5
n
v-l
I~
water
on LAKE SNOW
I
III
I
I
l
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l
Flsrn
6.0
I
l
l
H25m
I
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1115m
l
l
l
l
l
l
l
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w
l
p
4.5
4
8
3.0
0
4
1.5
E
0.0
r2l
263
Jun
6
11
16 16
18 28 6
Jul
Fig. 5.
8
10 16 22 24 27 31 5
Awz
As Fig. 4, but of bacterial
produced more biomass per cell than free-living bacteria.
Growth rates of aggregate-associated bacteria calculated from BCM and bacterial abun-
0 26
SeP
cell multiplication
3 23
act
Nov
(BCM).
dance, and assuming exponential
growth,
ranged between <O.O 1 and 0.72 d-l but most
values were CO.2 d-l (Fig. 6). In June and July
rates at 15 and 25 m were often at least as high
+
Fig. 6. Growth rates of aggregate-associated bacteria as calcu’lated from bacterial abundance and BCM and bacterial
protein and BPP, assuming exponential growth. No bar indicates no measurement.
542
Grossart and Simon
cl 5m
50
W15m
ti25m
Q)
.+E
b
5f
z
40
30
20
10
0 _
J
3
Jul
Fig. 7.
Turnover
13
10
27
3
15
Aw
22
27
5
17
SeP
25
3
act
23
20
Nov
times of aggregates on the basis of PCAA and BPP on aggregates. No bar indicates no measurement.
as in 5 m, but later rates at 15 and 25 m tended
to be lower. Growth rates estimated from bacterial protein and protein production on aggregates were in the same range as that based
on BCM, although absolute values exhibited
wide variations (Fig. 6). Growth rates of aggregate-associated bacteria were in the same
range as that of free-living bacteria. At 15 and
25 m, however, growth rates of free-living bacteria were usually higher than that of aggregateassociated bacteria.
Turnover of PCAA on aggregates calculated
on the basis of BPP varied between 1 and 54
d with a mean of 13.4 * 14.9 d; 80% of the
data were between 3 and 30 d (Fig. 7). Although variations were wide within single layers, there was a tendency toward longer turnover times with increasing depth.
Discussion
This study documents for the first time the
existence of macroscopic organic aggregates in
a lake and indicates that lake snow aggregates
have the same significance for the turnover and
flux of organic matter in a lake as marine snow
aggregates in the ocean. Our results show scvera1 important features of lake snow such as
its dynamic occurrence, fairly high abundance,
fragile structure. dense bacterial colonization,
high PCAA turnover, and very high SRP concentrations as compared to the surrounding
water. These findings have not been described
in lakes before because they could not be assessed with conventional sampling techniques
suc!h as sediment traps (Bloesch et al. 1977;
Stabel 1987; Weilenmann et al. 1989) or filtration (Pedros-Alio and Brock 1983; Kirchman 1983; Simon 1987) which destroy the
structure of organic aggregates. Our findings
wit:h respect to abundance, size, sinking rate,
chemical composition, inorganic nutrient concentrations,
and bacterial colonization
are
comparable, though, to similar studies of macroscopic organic aggregates in the ocean
(Shanks and Trent 1979; Alldredge and Silver
1988; Alldredge and Gotschalk 1989, 1990;
Simon et al. 1990) where their significance for
the transformation
and flux of organic matter
is well known (Fowler and Knauer 1986). Due
to differences in the pelagic community in lakes
and the ocean, the composition of aggregates
in both environments also differs. Most pronounced is the absence in lakes of mucus filter
feeders such as larvaceans, doliolids,
and
pteropods. Larvacean houses, doliolid fecal
pellets, and pteropod feeding webs are often
the major components of marine snow (Alldredge and Silver 1988). Also, we rarely found
fecal pellets on lake snow because the zoo-
Lake snow in Lake Constance
plankton in Lake Constance during the growing season is dominated by cladocerans (Gellcr
1990) which do not produce well-defined fecal
pellets.
Our in situ observations indicated that aggregate formation was triggered by wind-incuced turbulence and shear, which seems contrary to observations
in marine waters.
Alldredge and Gotschalk (1989) and Riebesell
(199 1) have reported that in marine environments aggregates during phytoplankton blooms
formed predominantly
without wind activity.
The near-surface layer in a lake, however, even
in a large one such as Lake Constance, exhibits
only weak turbulent movements during calm
periods as compared to that in the ocean, prcsumably causing much weaker shear. Turbulent mixing is assumed to be important (in
addition to differential setting and sticking efficiency) for aggregate formation (Shanks and
Edmondson 19 8 9; Alldredge and McGillivary
199 1). In marine near-surface waters, however, water motion always appears to be sufficient to yield shear high enough for aggregate
formation. The formation of aggregates composed predominantly
of colony-forming
cyanobacteria with heterocysts which prevail near
the surface for certain periods is a different
process and more comparable to the occurrence or Trichodesmium aggregates in the ocean
(Paerl 1990).
The size range and sinking rate of lake snow
aggregates that we found were similar to marine snow aggregates (Alldredge and Silver
1988; Alldredge and Gotschalk 1989, 1990),
although our largest aggregates were much
smaller than those in marine waters. As in marine waters, the sinking rate of diatom floes
was highest and is consistent with the rapid
sedimentation of diatom blooms in Lake Constance (Stabel 1987). Our sinking rates determined experimentally,
however, are much
faster than annual mean settling velocities of
POM and various algal species as determined
from sediment trap measurements in the lake
(Sommer 1984; Stabel 1987). At thermoclines
we found a relative accumulation
of aggregates. Comparable observations have been reported from discontinuity
layers in the marine
environment (Alldredge and Youngbluth 1985;
Herndl and Malacic 1987).
The range of dry weight, POC, C : N, and
PCAA of lake snow aggregates that we found
543
were similar to marine snow aggregates (Alldredge 1979; Alldredge and Gotschalk 1990)
and demonstrate that lake snow aggregates are
also a detritus-dominated
system. Based on
the POC content and abundance, we estimate
that lake snow aggregates comprise lo-20% of
the total POC in Lake Constance which is in
the range of 0. l-l .5 mg C liter- l (Tilzer and
Beese 1988). Since algal and bacterial biomass
together account, on average, for - 30% of the
POC (Simon and Tilzer 1987) and zooplankton for - 12% (Geller et al. 199 l), our results
indicate that lake snow aggregates >3 mm
comprise 20-40% of the detrital POC in the
lake. For the POC downward flux, lake snow
aggregates are presumably even more important because the sinking rate is a function of
size and hence they settle preferentially
to
smaller particles (Weilenmann et al. 1989).
A problem inherent with studies of macroscopic organic aggregates is the high error involved in most measurements, and this is true
for our study as well. The abundance of aggregates usually is rather patchy, and to collect
a representative number of aggregates is problematic, in particular when aggregates are small
and scarce. Because of the fairly small size of
aggregates we could not split them for various
measurements (Alldredge and Gotschalk 1990)
but rather had to pool them and perform different measurements on different aggregates
(e.g. for measurements of the chemical composition and bacterial production). Therefore,
measurements often yielded coefficients of
variation (SE/mean) of 0.50 to > 1.O. Similar
high variation has also been reported by others
(e.g. Alldredge et al. 1986; Alldredge and Gotschalk 1989, 1990; Simon ct al. 1990). It could
be the reason our estimates of bacterial protein
on aggregates exceeded the PCAA content of
aggregates. In addition, we assumed a mean
biomass of aggregate-associated bacteria of 53
fg protein cell-‘, corresponding to a cell volume of 0.153 pm3. Probably the size of aggregate-associated bacteria was variable and may
be smaller during certain periods, although the
size is comparable to bacteria inhabiting marine snow (Alldredge et al. 1986; Simon et al.
1990). Nevertheless, we think that our results
and conclusions in general are not affected by
this high variation because they compare well
with marine studies and are consistent with
comparable results from Lake Constance based
544
Grossart and Simon
on other methods (Simon 1987, 1988; St&e1
1987).
Lake snow aggregates are only the largest
fraction of organic and inorganic particles
present in the water column. Therefore, bacterial biomass and production on lake snow
underestimates the total bacterial biomass and
production
on particles. Simon ( 1987) estimated that particle-associated bacteria in Lake
Constance comprised - 15% of the total bacterial biomass and 15-20% of the total bacterial production. At the breakdown of algal
blooms, however, particle-associated bacteria
could account for as much as 50% of the total
bacterial production.
Our results indicate that lake snow aggregates are important for specific processes relevant also to the bulk water, which is consistent with comparable studies of marine snow
(Alldredge et al. 1986; Simon et al. 1990; Smith
et al. 1992) as well as with studies of particleassociated bacteria on the basis of filter fractionation (Kirchman
198 3; Pedros-Alio and
Brock 1983; Simon 1987). When comparing
the abundance and production of aggregateassociated bacteria on a per volume basis with
free-living bacteria, our data show that bacterial abundance on aggregates is 100 x and
production 20-30 x higher than in an equivalent volume of surrounding water. The growth
rates of aggregate-associated bacteria, however, were not higher than those of free-living
bacteria. Comparable observations have been
made on marine snow (Alldredge and Youngbluth 1985; Simon et al. 1990) and with particle-associated bacteria (Simon 19 8 8).
Bacteria on aggregates on average produced
more protein per new cell (15 1 fg) than freeliving bacteria (5 5 fg), although wide variations occurred and the difference is not statistically significant. Still, this comparison is
interesting because the relative difference between the two numbers is similar to the difference between the amount of protein cell-’
we used to estimate the biomass of aggregateassociated (53 fg) and free-living bacteria (19
fg). These numbers are annual mean values
determined for Lake Constance (Simon 1987).
The numbers of protein per new cell, however,
are 3 x higher. As outlined by Simon et al.
(1990), this ratio is sensitive to errors in calculating bacterial production from Leu as well
as TdR incorporation
and may indicate that
we used inappropriate conversion factors. The
factor we used to translate Leu incorporation
into BPP is 2 x the theoretical one (ID of Leu
= 2; Simon and Azam 1989). Due to high Leu
concentrations in the matrix water of aggregates it is conceivable that ID is close to 1 but
not substantially >2 (Simon and Rosenstock
19912). Unfortunately,
ID cannot be determined directly with aggregate-associated bacteria. The TdR conversion factor we used is
in the range of values often used (Cho and
Azam 1988). Based on the conversion of Leu
incorporation,
we could reduce the ratio of
protein per new cell by 100% (ID = 1) but it
would still be 50% higher than the cell volumebased numbers. In freshwaters, empirical TdR
conversion factors often are higher than 2.0 x
10‘” cells (mol TdR)-’ (Cho and Azam 1988).
Therefore, we suggest that we underestimated
the TdR conversion factor also because ID for
Leu incorporation
by free-living bacteria under nonmanipulated
in situ conditions is always > 1.5 in Lake Constance (Simon and Rosenstock 1992).
Bacteria were the major component of PCAA
on aggregates, which seems surprising since
algae were also found on aggregates, in particular during the breakdown of algal blooms.
Our estimates of BCAA were affected by a fairly h.igh error (limited number of comparisons;
comparison of bacteria and PCAA from different aggregates). Nevertheless, they suggest
that bacteria were a substantial protein component on aggregates. This suggestion is consistent with the notion that in the bulk water
of the lake biomasses of bacteria and algae on
average are also similar, and bacterial biomass
exceeds algal biomass during the clear-water
phase and in winter (Simon and Tilzer 1987).
The turnover of aggregates on the basis of
BPP and PCAA varied between 3 and 54 d,
but most values were <30 d and the mean
13.1 d, which indicates that the turnover of
bacterial biomass contributes significantly to
PCAA turnover. Our turnover times are shorter than those calculated by Simon (1987) for
POlM in Lake Constance retained on glass-fiber filters and on the basis of bacterial production (40 d). They-are in the range of the
residence times of POM in the epilimnion
of
the: lake, 3-20 d, as calculated from POM concentrations and sedimentation
rates (Stabel
19iB7). The actual turnover of aggregates is pre-
Lake snow in Lake Constance
sumably even faster because, besides bacterial
production, respiration and microbial hydrolytic activities also contribute significantly to
the turnover of organic particles and aggregates. Smith et al. (1992) found that hydrolysis
and release of PCAA-DCAA
from marine snow
exceeded the carbon demand of marine snowassociated bacteria by - 9 5 -fold.
Concentrations
of SRP were substantially
enhanced in the matrix water of aggregates
during stratification
when they were near or
below the detection limit in the surrounding
water, suggesting that aggregates were significant sites of P recycling under these conditions. Bacteria are the major sink for particulate P in Lake Constance (Jiirgens and Glide
1990) and outcompete algae for uptake of inorganic phosphorus (Pi) under low concentrations (co.1 PM; Rothhaupt and Glide 1992).
Rothhaupt and Gi.ide (1992) have shown that
at higher and inhomogeneous concentrations,
however, algae take up an increasing fraction
of Pi. Therefore, the microenvironment
of aggregates in the surrounding water in which nutrients presumably are leaking out is a highly
favorable site for uptake of Pi by algae, enabling them to grow even when the Pi concentrations in the bulk water favor bacterial uptake.
In conclusion, our results demonstrate that
lake snow aggregates are comparable to marine
snow aggregates with respect to abundance, dynamic occurrence, and chemical and microbial
composition, although some differences occur
due to the different composition of marine and
limnetic plankton communities. The bacterial
activity on lake snow aggregates is also comparable to that on marine snow. Lake snow
aggregates have not yet been included into the
conceptual framework of fluxes and cycling of
elements in pelagic limnetic environments. Our
results indicate that their consideration adds
new insights into the understanding of iacustrine ecosystems such as the dynamic POM
turnover and flux and microscale nutrient recycling.
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Accepted: 6 August 1992
Revised: 27 January 1993