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Stimulated bioluminescence as an early indicator of bloom development of the
toxic dinoflagellate Alexandrium ostenfeldii
Anniina H. Le Tortorec, Päivi Hakanen, Anke Kremp, John Olsson, Sanna Suikkanen and Stefan
G.H. Simis
Finnish Environment Institute (SYKE), Marine Research Centre, P.O. Box 140, FI-00251 Helsinki,
Finland.
Corresponding author: [email protected]
ABSTRACT
Daily patterns of stimulated bioluminescence were recorded throughout an Alexandrium ostenfeldii
bloom at a remote shallow site in the Finnish Archipelago Sea. Transect measurements showed highly
localized bioluminescence prior to the bloom peak. High bioluminescence, corresponding to peak
dinoflagellate biomass, lasted 15 days in mid-August. Large day-to-day variation of bioluminescence
intensity was observed throughout the bloom. Bioluminescence intensified after sunset, peaked
around midnight and continued during the early morning. Night-time chlorophyll-a (Chl-a)
fluorescence was significantly correlated with bioluminescence intensity during the bloom. The
relation between Chl-a fluorescence and bioluminescence was indicative of the presence of A.
ostenfeldii, confirmed by infrequent cell counts. Low concentrations of cellular paralytic shellfish
poisoning (PSP) toxins were detected throughout the sampling period while higher toxin
concentrations were limited to the period where bioluminescence intensities were high and
bioluminescence could be easily detected by eye. These results suggest that, under special conditions
as described here, autonomous optical measurements may be useful to predict the onset of toxic
dinoflagellate bloom, although the highly localized distribution may require advance knowledge of
potential bloom locations.
Key words: Alexandrium ostenfeldii, bioluminescence, harmful algal blooms, optical detection,
paralytic shellfish poisoning toxins
2
INTRODUCTION
Harmful phytoplankton blooms increasingly threaten ecosystem health in estuaries and coastal waters
worldwide (Hallegraeff, 2010; Anderson et al., 2012). The main groups forming harmful blooms
include cyanobacteria, diatoms, haptophytes, raphidophytes and dinoflagellates (Hallegraeff et al.,
2003). Dinoflagellates account for an estimated 75% of the species that form harmful algal blooms
(Smayda, 1997). A wide range of dinoflagellate species produce toxic substances that can affect
higher trophic levels (e.g. fish and waterfowl) and accumulate in benthic and littoral food webs
(Hallegraeff, 2010; Anderson et al., 2012). Blooms of dinoflagellates in coastal waters can cause
paralytic and diarrheic shellfish poisoning (PSP, DSP) with associated losses to aquacultures and the
environmental and recreational value of affected areas (Hallegraeff et al., 2003; Hallegraeff, 2010;
Anderson et al., 2012).
Bioluminescence is a night-time optical phenomenon where cells emit flashes of light induced by
pressure on the cell wall (Van den Hoek et al., 1995). A large number of harmful dinoflagellate taxa
luminesce (Van den Hoek et al., 1995), and virtually all bioluminescence in surface waters of marine
environments originates from dinoflagellates (Swift et al., 1995; Marcinko et al., 2013a).
Dinoflagellate bioluminescence is considered a defence mechanism against grazing, possibly alerting
the predator's predators (e.g. Abrahams & Townsend, 1993), thus suggesting the potential to alter the
marine food web in favour of dinoflagellate presence. Bioluminescence has been mainly studied in
the open ocean (e.g. Marra, 1995) and in the coastal zone (Herren et al., 2005; Moline et al., 2007;
Moline et al., 2009), whereas few studies have focused on bioluminescent blooms in near-shore
waters (Kim et al., 2006) where animal and human populations are particularly vulnerable.
While many bioluminescent dinoflagellate species occur in the Kattegat-Skagerrak area of the Baltic
Sea, only few species are known to occur in the central and northern parts of the Baltic Sea (Hällfors,
2004). Protoceratium reticulatum (Claparède & Lachmann) Bütschli is generally found in low
abundances throughout the open Baltic Sea (Hällfors, 2004; Mertens et al., 2012). Lingulodinium
polyedrum (Stein) Dodge is encountered in the Southern Baltic Sea (Hällfors, 2004). In recent years,
Alexandrium ostenfeldii (Paulsen) Balech and Tangen has been increasingly observed in shallow
waters and bays of the Baltic Sea up to the Archipelago Sea, with reports from Åland, the Gulf of
Gdansk, Gotland and Kalmar (Larsson et al., 1998; Hajdu et al., 2006; Kremp et al., 2009; Hakanen
et al., 2012). Sampling in recent years in the Åland archipelago (located between Finland and Sweden,
3
Fig. 1) suggests that A. ostenfeldii is the only bioluminescent dinoflagellate species found in this area
(Kremp et al., 2009; Hakanen et al., 2012).
A. ostenfeldii is found in temperate waters worldwide (e.g Moestrup and Hansen, 1988; Mackenzie
et al., 1996; John et al., 2003; Gribble et al., 2005). In oceans it normally occurs at low densities
(Moestrup and Hansen, 1988; John et al., 2003; Gribble et al., 2005) but in the coastal areas of the
Baltic Sea recurrent dense blooms are observed (Larsson et al., 1998; Hajdu et al., 2006; Kremp et
al., 2009; Hakanen et al., 2012). Summer blooms with densities up to 106 cells L-1 have formed in
the Åland archipelago at least in the last decade (Kremp et al., 2009; Hakanen et al., 2012). These
blooms pose a potential threat to the ecosystem due to the observed production of PSP toxins (Kremp
et al., 2009; Hakanen et al., 2012). PSP effects on humans have thus far not been considered, probably
because a commercial shellfish industry is absent in the Baltic Sea. Laboratory studies have, however,
shown that A. ostenfeldii toxins affect zooplankton grazing behaviour (Sopanen et al., 2011), and
shellfish and small fish collected from the bloom area contained concentrations of PSP toxins that
exceed the European Commission safety limits of 80 µg 100g-1 (O. Setälä, Helsinki, personal
communication).
A clear need for an early warning of dinoflagellate presence exists in the coastal areas of the Baltic
Sea in summer. Due to the complex coastline with many isolated and remote bays, this demand cannot
be met using traditional sampling and analysis of water samples. The recurrent dense toxic blooms
of A. ostenfeldii in the Åland archipelago provide a case to develop an autonomous monitoring and
early warning strategy based on bioluminescence. The environmental monitoring potential of
bioluminescence as an early indicator of the presence of toxic dinoflagellate bloom has thus far
received little attention. Relations between dinoflagellate toxicity and bioluminescence dynamics are
also not known. In this study, we investigate spatiotemporal patterns of bioluminescence produced
during different stages of an A. ostenfeldii bloom, in an area that due to its high latitude (60° N)
experiences short nights in summer, which may limit the light-suppressed production of
bioluminescence. The high-resolution in situ dynamics of bioluminescence and the biomass threshold
at which bioluminescence and toxicity are evident are addressed in this study, in order to define an
optimal monitoring strategy.
4
METHOD
Study area
The study site is situated in a remote area in the Åland archipelago between Finland and Sweden (Fig.
1A). Salinity ranges from 6 to 7 psu, and surface water temperature may reach up to 24 °C in isolated
bays. Summer day length at this latitude (60° N) reaches up to 19 hours. In the middle of July the sun
typically rises around 04:40 and sets at 22:45, and in the beginning of September the sun rises around
06:35 and sets at 20:45. A recurrent A. ostenfeldii bloom site is located in a sound in the northern part
of the Föglö archipelago (60° 5' 35" N, 20° 32' 12" E, Fig. 1C). The 3-km long sound is shallow
(water depth < 3 m) and sheltered with limited water exchange. A detailed description of the study
area is given in Kremp et al. (Kremp et al., 2009).
Semi-continuous measurements
A sensitive submersible light sensor (GlowTracka, Chelsea Technologies Group, West Molesey,
UK), a temperature logger (HOBO U22 Water Temp Pro v2), and a chlorophyll a (Chl-a) fluoroprobe
(SCUFA, Turner Designs, Sunnyvale, CA, USA) were mounted on a submerged frame and installed
on-site on 14 July 2011. After minor changes to resolve light contamination, daily patterns of
bioluminescence and Chl-a fluorescence were recorded continuously from 27 July to 7 September
2011, covering the start, peak, and decline of an A. ostenfeldii bloom. The sensor frame was moored
approximately 10 meters from the shore at 0.5 - 1.0 m depth (station A, Fig. 1) where water depth
was approximately 1.5 m. Water was pumped through the sensor chamber of the GlowTracka at 6 L
min-1 using a submersible pump (SBE 5P, Sea-bird Electronics, Bellevue, WA, USA) mounted
directly in front of the sensor chamber. A 1-mm mesh was positioned before the water intake, using
a funnel to widen the intake area. The mesh was required to keep macrophytes away from the sensor
chamber, and the wide area over the funnel kept the water flow through the mesh sufficiently low to
prevent stimulation of bioluminescence before it reached the pump. Black tubing and masking tape
were used to shield the sensor from ambient light. The sensors were connected to a data logger (DI-
710, DATAQ, Akron, OH, USA) on the shore and powered from a solar panel. A microcontroller
(Arduino Uno) was used to power the system for one minute at 10-min intervals. The data logger
recorded the light sensor signal at 15 Hz. This combination of sensor and data recording frequency
was not sufficient to analyse flash patterns from individual cells, but allowed in situ data storage over
a long observation period. The noise floor of the instrument was 0.05 ± 0.006 nW cm-2. Because of
5
the low noise floor of the instrument, no threshold was used to define the presence of a
bioluminescence signal. The raw bioluminescence and fluorescence data were averaged over each
recorded 1-min period to generate the results shown in this paper. Chl-a fluorescence values were
converted to pigment concentrations using a laboratory calibration. The factory calibration of the light
meter was used to convert the response of the photodiode to corresponding light intensity at 560 nm.
The sensor surfaces were cleaned weekly to avoid biofouling.
Spatial distribution of bioluminescence
The time-series of bioluminescence measurements at station A was interrupted for two nights to
assess the spatial distribution of bioluminescence in the study area, from 8 to 11 August 2011. A 7-
km transect (Fig. 1) was covered with a motorboat four times each night: between 21:00 - 23:00 h,
01:00 - 03:00 h, 05:00 - 07:00 h, and 09:00 - 11:00 h. The sensor frame was lowered to a depth of 0.5
- 1.0 m, every 100 m to record for approximately 2 minutes. Water samples for phytoplankton counts
were collected at a depth of 0.5 m at 10 points along the same transect line on the day following the
last bioluminescence measurements.
Sample preparation and analysis
Toxin samples were collected every second week between mid-July and the end of September, by
sequentially filtering 10 L of seawater from 0.5 m depth through 75-µm and 25-µm sieves. The 25 -
75 µm fraction was retained and washed into a 50 mL Falcon tube. The concentrated sample was
filtered onto a Whatman GF/F glass fiber filter (Ø 25 mm), transported in liquid nitrogen, and stored
at -80 °C until further analysis. The samples were freeze-dried before extraction. The extraction
procedure and the protocol for high-performance liquid chromatography with fluorescence detection
(HPLC-FD) used to quantify PSP toxin concentrations are described in detail in Hakanen et al.
(Hakanen et al., 2012).
Samples for phytoplankton analyses were fixed with Lugol's solution and counted following the
Utermöhl inverted microscope method (HELCOM, 2008). Depending on cell density, sample
volumes of 3 - 50 mL were left to settle in phytoplankton counting chambers for 3 - 24 h.
Phytoplankton enumerations were performed at 200× and 400× magnifications using a Leica
DM13000B inverted microscope. At least 500 cells were counted. The identity of A. ostenfeldii cells
against other thecate dinoflagellates was confirmed with epifluorescence microscopy. Cells were
6
stained with 1 mg mL-1 solution of Fluorescent Brightener 28 (Sigma-Aldrich) to see thecal plate
tabulation and confirm identity (Friz and Tiemer, 1985).
Statistical analyses
Linear least-squares regression analysis was used to assess the relations between A. ostenfeldii cell
density, bioluminescence intensity, and toxicity, and between Chl-a concentration and
bioluminescence intensity in the semi-continuous monitoring study. The same method was used to
relate cell density to bioluminescence intensity in the transect study. Results were considered
statistically significant if the p-value was below 0.05.
RESULTS
Semi-continuous measurements
Stimulated bioluminescence was first detected during the night of 30 July, then again from 6 August
lasting until the end of the measuring period on 7 September. Intense (> 2 nW cm-2) bioluminescence
was recorded from mid-August and lasted approximately 15 days, with a maximum intensity (1–min
average) of 14.46 nW cm-2 on 26 August. Fig. 2 describes the recorded bioluminescence at 10-minute
intervals for the whole study period. The bioluminescence intensity was used to arbitrarily divide the
data set into four time periods. The first period (27 July - 6 August) was characterized by very low
bioluminescence (mean ± standard deviation (std): 0.07 ± 0.04 nW cm-2). The second period (7 - 16
August) was associated with intermediate bioluminescence levels (0.54 ± 0.46 nW cm-2), which were
clearly visible to the naked eye. The strongest bioluminescence (2.09 ± 2.05 nW cm-2) was observed
in period 3 (17 August – 1 September). During the last period (2 - 7 September) bioluminescence
returned to low intensities, although the signal intensity exceeded the pre-bloom situation up until the
end of the observation period (0.10 ± 0.03 nW cm-2).
Large variations in the day-to-night intensity of bioluminescence were observed throughout the study
period (Fig. 2). Most noticeable is that during the peak of the bloom (period 3), bioluminescence did
not completely disappear during the day. The ratio of night-to-day bioluminescence was highly
variable with mean ± standard deviation of 3.27 ± 2.53 for period 1, 19.69 ± 11.63 for period 2, 32.90
7
± 22.20 for period 3, and 1.73 ± 0.68 for period 4. Here, night-time bioluminescence was calculated
from sunset to sunrise. Day-time bioluminescence (sunrise to sunset) was close to the instrument
noise level only during the first period.
Daily rhythms of bioluminescence are visualized in Fig. 3 following standardization of the signal in
24-h periods, by first subtracting the 24-h minimum value and subsequently normalizing to the 24-h
peak value. The four periods are presented separately and each plot is centered on sunset. A sinusoid
rhythm, rising shortly after sunset and decreasing from morning to late afternoon was already visible
in the first period, despite the weak amplitude of the signal (Fig. 3A). The fluctuations between day
and night-time bioluminescence became more pronounced during some nights in the second period
(Fig. 3B), indicating the transition to the bloom. In period 3, the period of highest bioluminescence,
a clear pattern was observed, with bioluminescence rising sharply after sunset, peaking around
midnight, and declining in the morning (Fig. 3C). In period 4 the weak sinusoid pattern of the first
period was again seen during some nights, whereas isolated peaks (some during the day) during other
24-h periods, associated with low nightly mean bioluminescence, suggest that the population of
bioluminescent cells was too sparse to discern any remaining rhythm (Fig. 3D).
To assess whether night-time stimulated bioluminescence corresponded to A. ostenfeldii abundance,
toxicity, and the abiotic environment, the results recorded with the autonomous in situ instruments
and laboratory analyses (cell counts and PSP toxin concentrations) are plotted on the same time scale
in Fig. 4. Despite the small number of water samples that could be brought to the lab from the remote
site, night-time bioluminescence (Fig. 4A) and cell density (Fig. 4D) show comparable temporal
trends for which statistical analysis is given below. Chl-a concentration fluctuated throughout the
study period with a mean and standard deviation of 10.66 ± 3.12 mg m-3. The night-time Chl-a
concentrations (Fig. 4B) were highest in periods 2 and 3 concurrently with the highest night-time
bioluminescence intensities (Fig. 4A) and A. ostenfeldii cell densities (Fig 4D).
Mean daily water temperatures were > 22 °C from 19 July until the start of period 2 and > 19 °C in
period 3, the height of the bloom. Decreasing water temperatures to < 19 °C coincided with a decrease
in the intensity of bioluminescence (Fig. 4C). Changes in water temperature corresponded closely to
the visual separation of bioluminescence intensities between periods 1-4. These high-resolution
observations support the idea that high temperatures promote A. ostenfeldii blooms (Larsson et al.,
1998; Hajdu et al., 2006; Kremp et al., 2009; Hakanen et al. 2012).
8
A. ostenfeldii cells were present in the water column throughout the study period but high abundances
were only reached in late August, with a maximum of 3.08 × 105 cells L-1 on 22 August (Fig. 4D).
Despite the low number of concurrent samples (n = 7), there was a significant positive relation
between night-time bioluminescence and the number of A. ostenfeldii cells (BL = 1.63×10-5 cells +
0.52, R2 = 0.66, n = 7, p = 0.03). The distribution of corresponding bioluminescence and cell number
data did not allow accurate determination of a cell density threshold for bioluminescence detection.
Low concentrations of cellular PSP toxins were detected throughout the sampling period while higher
toxin concentrations (> 0.28 mg m-3) were limited to the period when measured bioluminescence was
> 1 nW cm-2 at night (Fig. 4E), and could be easily detected by eye. PSP toxins gonyautoxins 2 and
3 (GTX2/GTX3) and saxitoxin (STX) were found. The highest total cellular PSP toxin concentrations
were 0.31 and 0.28 mg m-3 on 10 and 26 August, respectively. With only four concurrent samples no
relation between toxicity and night-time bioluminescence could be established. Six concurrent
samples were available to relate toxicity and A. ostenfeldii cell number. This relation was positive
and significant (toxins = 5.43×10-6cells + 0.02, R2 = 0.89, n = 6, p = 0.005).
The results for regression analysis between all night-time (sunset+1h - sunrise-1h) observations of
bioluminescence and Chl-a fluorescence are summarized in Table I, as well as the correlation between
nightly mean bioluminescence and nightly mean Chl-a fluorescence. Nightly mean values gave
stronger regression results when analysed over the whole study period, and during period 3,
suggesting that short-term variability between the sensor signals (measured from slightly different
positions in the sensor frame) was significant. Regression results obtained during periods 2 and 4
were only significant when all night-time observations were considered. The correlation between
night-time bioluminescence intensity and Chl-a concentration varied markedly between the four
designated periods (Table I, Fig. 5). No meaningful correlation was defined during period 1 when
bioluminescence did not significantly depart from the noise level. In period 2 a weak negative trend
was observed (Fig. 5B), possibly suggesting a succession from higher biomass non-bioluminescent
cells to low abundances of A. ostenfeldii. The mean bioluminescence intensity (0.54 nW cm-2) rose
nearly 7-fold compared to period 1, suggesting that infrequent flashes or bioluminescent glow were
present. In period 3, regression statistics show a significant positive relation between bioluminescence
and Chl-a (Fig. 5C). If we assume the bloom to be dominated by A. ostenfeldii during this period,
extrapolation of this trend implies a minimum biomass threshold for bioluminescence detection at
5.52 mg Chl-a m-3. In period 4, bioluminescence returned to weak intensities, although regression
9
analysis indicates a stronger relation to Chl-a fluorescence (Fig. 5D), suggesting that bioluminescent
cells were predominant even though biomass was declining. The minimum biomass threshold to
detect bioluminescence in this period can be extrapolated from the regression analysis to 1.50 mg
Chl-a m-3.
Spatial distribution
Transect measurements taken along the sound during two nights in the second period showed highly
localized bioluminescence prior to the bloom peak. Fig. 6 describes the mean bioluminescence values
recorded during two-minute intervals at each site. Bioluminescence was concentrated around the
permanent mooring (station A) in the inner areas of the sound and sharply decreased towards the open
sea until it was indistinguishable from instrument noise. The brightest bioluminescence was 1.89 nW
cm-2, easily visible to the naked eye. The horizontal distribution of bioluminescence and A. ostenfeldii
cells was similar (Fig. 6) with a positive correlation between bioluminescence intensity and the A.
ostenfeldii abundance in the geographically closest water sample taken on the next day (BL =
8.41×10-6 + 0.08, R2 = 0.76, n = 10, p = 0.001). On 26 August, during the bloom peak, visible
bioluminescence was observed to extend until the open sea on the west side of the sound. Transect
measurements are however not available for that time.
DISCUSSION
The aim of this study was to assess the environmental monitoring potential of bioluminescence as an
early indicator of the presence of a toxic dinoflagellate bloom. Our results show that bioluminescence
is already detectable when A. ostenfeldii is present at low cell concentrations in the water column.
Two simultaneous patterns explained most of the variation in the recorded bioluminescence. The
widely observed circadian rhythm of bioluminescence was the primary source of variation in the
recorded signal. The second source of variability in the bioluminescence signal was the seasonal
change in the intensity of bioluminescence driven by phytoplankton succession and fluctuations in
phytoplankton biomass. The transect study showed that bioluminescence remained highly localized
until mere days before the bloom peak. High toxin concentrations occurred only at intermediate and
high bioluminescence intensities, although these observations were sparse. Various aspects of bloom
10
dynamics, acting on different time and spatial scales, must therefore be considered before a
monitoring strategy can be implemented.
The diurnal variation in bioluminescence in periods 2 and 3 (Fig. 3B-C) has been repeatedly observed
in nature (e.g. Utyushev et al., 1999; Geistdoerfer and Cussatlegras, 2001; Marcinko et al., 2013b)
and in cultured cells of single species (e.g. Fritz et al., 1990; Knaust et al., 1998). Bioluminescence
increased sharply after sunset and peaked around midnight. Bioluminescence continued into the early
morning and decreased thereafter, supporting the idea that the production of substrate for the
bioluminescent reaction is limited by light. The ratio between night and day intensity observed in this
study (max 32.90 ± 22.20 during the period of high bioluminescence) is similar to that found in other
natural populations, e.g. a maximum ratio of 23 in Marcinko et al. (Marcinko et al., 2013b), but lower
than reported in the literature for cultured dinoflagellates with ratios of 200 for Pyrodinium
bahamense and Gonyaulax polyedra and up to 950 for Pyrocystis lunula (Biggley et al., 1969).
However, results obtained from cultured strains are difficult to compare to results from the field,
where changes in the light field are gradual and illumination conditions (cloud cover) can be variable.
The seasonal change in the intensity of bioluminescence was likely governed by fluctuations in the
biomass of A. ostenfeldii at the study site. Biomass fluctuations are typically caused by currents,
population growth and decline as well as life cycle transformations (Smayda, 1997; Wyatt and
Jenkinson, 1997). Natural currents and currents produced by ships passing either side of the sound
might influence local A. ostenfeldii biomass fluctuations. The most likely reason for the seasonal
change in the intensity of bioluminescence is the natural population dynamics: A. ostenfeldii has in
the years prior to this study repeatedly peaked after mid-July and declined at the end of August. Peaks
were always short-lived, and outside the peak period the species persisted in the water column at
modest or low numbers (Hakanen et al., 2012). Worldwide blooms of Alexandrium are generally
described as short-lived (Wyatt and Jenkinson, 1997). It has been suggested that in the Baltic Sea
warm water temperatures (around 20 °C) could be the most important single environmental factor
determining whether A. ostenfeldii blooms or not (Larsson et al., 1998; Hajdu et al., 2006; Kremp et
al., 2009; Hakanen et al., 2012). In this study the mean daily water temperatures remained over 19
°C until the end of August, when the period of high bioluminescence ended. Subsequently,
temperature and bioluminescence both decreased steadily. This supports the idea that warm water
promotes persistence of the bloom. Like many seasonal Alexandrium species, A. ostenfeldii produces
resting cysts during its life cycle, which serve as survival stages through periods of unfavourable
11
conditions (Hakanen et al., 2012). The drop in temperature during early autumn could induce cyst
formation, thereby accelerating population decline.
A. ostenfeldii cell density and night-time bioluminescence intensity were positively related,
supporting the hypothesis that bioluminescence could be used to follow bloom development. In turn,
the number of A. ostenfeldii cells was positively related with toxicity, in line with Hakanen et al.
(Hakanen et al., 2012) who reported that PSP toxin dynamics corresponded to A. ostenfeldii
abundance. Thus, while simultaneous toxin and bioluminescence data were too scarce to develop a
predictive model, bioluminescence and toxicity were indirectly related in our data set.
The relationship between night-time bioluminescence intensity and Chl-a concentration was strong
during the bloom period in the middle of August. Extrapolation of this relationship yields a lower
limit of bioluminescence detection at 5.52 mg Chl-a m-3 while the bloom reached biomass in the order
of 10 - 20 mg Chl-a m-3. 60% of the variability in mean nightly bioluminescence could be attributed
to changes in mean nightly Chl-a (dominated by A. ostenfeldii biomass). A significant but slightly
weaker relationship was found over the whole study period explaining 48% of variability in mean
nightly data. The weak negative trends between night-time bioluminescence intensity and Chl-a
concentration until the middle of August were likely due to other species than A. ostenfeldii
dominating the phytoplankton community and contributing to Chl-a fluorescence. Hakanen et al.
(Hakanen et al., 2012) have shown that in the Föglö study area A. ostenfeldii does not form
monospecific blooms but is part of a diverse phytoplankton community. During the abundance peaks
in 2009, A. ostenfeldii contributed > 60% of the phytoplankton biomass in July and around 30% in
August (Hakanen et al., 2012). At the start of the period 1 in the current study, filamentous
cyanobacteria were visibly dominant but later disappeared. Kim et al. (Kim et al., 2006) noted similar
trends in Chl-a concentration and bioluminescence intensity, related to increased dinoflagellate
abundance. The positive, albeit weak, relation between night-time bioluminescence intensity and Chl-
a in September, when bioluminescence levels were decreasing, may be explained by a decrease of
the total phytoplankton biomass towards autumn. Bioluminescent cells may nevertheless have been
relatively more abundant, judging from the lower detection threshold of bioluminescence
corresponding to Chl-a concentrations of 1.50 mg Chl-a m-3. The weak correlations in periods 2 and
4 are not seen to be significant within the mean nightly data, likely due to low sample size. In
summary, these results suggest that the combined use of Chl-a fluorescence and bioluminescence can
help to determine the development of dinoflagellates in the phytoplankton community.
12
The transect measurements revealed that bioluminescence was highly localized prior to the bloom
peak. It was strongest in the inner areas of the sound and decreased towards the open sea. This aspect
is interesting as it suggests that the bloom spread out from a single location, supporting earlier
findings that the distribution of A. ostenfeldii is highly localized in the Baltic Sea (Larsson et al.,
1998; Hajdu et al., 2006; Hakanen et al., 2012). On 26 August bioluminescence was visible up to the
open sea in the west end of the sound and the total area where the signal was visible spanned
approximately three kilometres. It is not well known what factors determine the distribution of A.
ostenfeldii but benthic resting cysts could play an important role in population establishment, as it
has been shown that cyst beds are a key feature of many Alexandrium blooms (McGillicuddy et al.,
2003, 2005; Stock et al., 2005).
In support of bioluminescence measurements to monitor the development of dinoflagellate blooms in
shallow, near-coastal systems, it is safe to state that the measurement system used in this study was
sufficiently sensitive for early detection of dinoflagellate blooms, since bioluminescence could be
measured in periods where dinoflagellates were not yet common. However, the diurnal rhythm of
bioluminescence and localization of blooms in their early stages of establishment should be taken
into account when planning environmental monitoring of this phenomenon. We were able to measure
bioluminescence during the whole summer night (between 7.5 - 9.5 hours in periods 2 and 3) and low
levels of bioluminescence could also be detected during some parts of the day. Because the bloom
area was strongly localised at first, monitoring sites should be carefully selected. We therefore
recommend targeted monitoring in areas where blooms are frequently observed or where risks are
high, e.g. close to human settlements or fish farms. Biofouling did not pose a problem. The system in
this study was cleaned weekly as a precaution, but there was no evidence of significant build-up of
materials in the sensor chamber. This may be attributed to the absence of sunlight in the chamber,
and the use of a pump with a mesh.
In conclusion, this study shows that it is possible to relate bioluminescence to the succession of
phytoplankton community towards a dinoflagellate bloom using automated measurements. Further,
the dynamics of in situ bioluminescence correspond to cell numbers of A. ostenfeldii. Toxicity was
positively related to abundance of A. ostenfeldii, as shown in more detail in previous studies. Future
work should improve the estimates of toxicity predictions from bioluminescence and Chl-a
fluorescence. This could be done by further concurrent field measurements with increased sampling
for toxicity, or alternatively through laboratory experiments. Sampling blooms at remote locations
13
remains a major challenge, and the autonomous optical measurements may be used to direct sampling
efforts.
ACKNOWLEDGEMENTS
The authors wish to thank Johan and Helene Franzén for their help and hospitality during field work,
Hanna Kauko and Mira Stenman for helping with data collection, and Johanna Oja for assistance in
the lab. The constructive comments provided by two anonymous reviewers are gratefully
acknowledged.
FUNDING
This work was supported by the Academy of Finland [grant number 128833 to A.K. and S.S., 132409
to A.H.L. and S.G.H.S.]; EC/IAPP project WaterS [grant number 251527 to J.O.] and the Finnish
Cultural Foundation [grant to P.H.].
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18
TABLES
Table I. Regression results for night-time bioluminescence and night-time Chl-a. In the first columns,
all night-time samples for the specified period are included. The last columns include only nightly
mean values in the analysis. Results for period 1 are not shown because the bioluminescence signal
did not significantly depart from the noise level of the instrument during that period. (r.c. = regression
coefficient, i = model intercept).
Period All night-time samples Nightly mean values r.c. i R2 n p-value r.c. i R2 n p-value
All 0.45 -3.48 0.37 1581 < 0.0001 0.52 -4.40 0.48 40 < 0.0001 2 -0.02 0.76 0.03 276 0.007 -0.03 0.96 0.21 8 0.25 3 0.31 -1.71 0.22 2145 < 0.0001 0.74 -6.37 0.60 16 0.0004 4 0.02 -0.03 0.21 280 < 0.0001 0.02 -0.07 0.37 5 0.27
Statistically significant results (p < 0.05) are shown in bold.
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FIGURES
Fig. 1. (A) The Finnish Archipelago Sea in the northern Baltic Sea showing the location of the Åland
islands (black box). (B) The Föglö islands and the area surrounding the study site (black box). (C)
Detail of the islands around the study site showing the sampled transect (drawn line) and the location
of station A (black marker) where semi-continuous measurements took place during the study period.
The transect corresponds to a distance of approximately 7 km.
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Fig. 2. Intensity of bioluminescence, measured at 10-min intervals.
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Fig. 3. Daily rhythm of standardized bioluminescence (lowest intensity subtracted, followed by
normalization to peak intensity) per 24-h period. Each plot is centered on sunset. Thick drawn lines
are the average dynamics observed over the whole period (all curves in graph). The dark period is
indicated (hatched) at the top of each figure. The hatched pattern is divided into two parts, the first
part indicating the length of the shortest night and the second part indicating the length of the longest
night during the period in question. (A) Period 1 (27 Jul - 6 Aug), (B) period 2 (7 - 16 Aug), (C)
period 3 (17 Aug – 1 Sep) and (D) period 4 (2 - 7 Sep).
22
Fig. 4. Dynamics of (A) night-time bioluminescence (nightly mean, standard deviation as error bars),
(B) night-time chlorophyll a (nightly mean, standard deviation as error bars), (C) water temperature,
(D) A. ostenfeldii cell abundance (one replicate per sampling) and (E) total cellular PSP toxin
concentration (mean of two replicates) (* = traces of GTX toxins found on 29 September) at station
A from 11 July to 29 September.
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Fig. 5. Correlation between night-time (one hour after sunset until one hour before sunrise)
bioluminescence and night-time chlorophyll a concentration for (A) the whole data set, (B) period 2
(7 - 16 Aug), (C) period 3 (17 Aug – 1 Sep) and (D) period 4 (2 - 7 Sep). Correlation for period 1 is
not shown because the bioluminescence signal did not significantly depart from the noise level of the
instrument during this period.
24
Fig. 6. Horizontal distribution of bioluminescence (circles) and A. ostenfeldii cell abundance (line
with squares) measured along the transect line. 0 m represents station A.