Introduction
The spring bloom is a key annual event in the phenology of pelagic
ecosystems, where a rapid increase in phytoplankton biomass has a significant
influence on upper ocean biogeochemistry and food availability for higher
trophic levels (Townsend et al., 1994; Behrenfeld and Boss, 2014). Spring
blooms are particularly prevalent in coastal and high-latitude waters. The
high levels of phytoplankton biomass and primary production that occur during
these blooms, and its subsequent export out of the surface ocean, result in a
significant contribution to the biological carbon pump (Townsend et al.,
1994; Sanders et al., 2014). The North Atlantic spring bloom is one of the
largest blooms on Earth, making a major contribution to the annual export of
∼ 1.3 Gt C yr-1 from the North Atlantic (Sanders et al., 2014).
The timing and magnitude of the spring bloom can have a significant
biogeochemical impact (Henson et al., 2009); hence it is important to
understand both the controls on, and the variability in, bloom timing,
magnitude, and community structure. Despite its importance, there remains
little consensus as to the environmental and ecological conditions required
to initiate high-latitude spring blooms (Townsend et al., 1994; Behrenfeld,
2010; Taylor and Ferrari, 2011b; Smyth et al., 2014).
Phytoplankton blooms occur when growth rates exceed loss rates (i.e. a
sustained period of net growth); phytoplankton growth rate constraints
include irradiance, nutrient supply, and temperature, while losses can occur
through predation, advection, mixing out of the euphotic zone, sinking, and
viral attack (Miller, 2003). Therefore, the rapid increase in (net) growth
rates during the spring bloom must be due to either an alleviation of those
factors constraining growth, a reduction in factors determining losses, or
(more likely) some combination of both.
The critical depth hypothesis (Sverdrup, 1953), the seminal theory of spring
bloom initiation, proposes that there exists a critical depth such that when
stratification shoals above this depth, phytoplankton growth will exceed
mortality and a bloom will occur. However, this hypothesis has been more
recently brought into question as bloom formation has been observed to start
earlier than expected (Mahadevan et al., 2012) and in the absence of
stratification (Townsend et al., 1992; Eilertsen, 1993). Several new
theories have now been developed to explain these occurrences (reviewed in
Behrenfeld and Boss, 2014; Fischer et al., 2014; Lindemann and St. John,
2014).
Eddies and oceanic fronts have both been identified as sources of
stratification prior to the wider onset of seasonal stratification (Taylor
and Ferrari, 2011a; Mahadevan et al., 2012). However, they do not explain
blooms in the complete absence of stratification, which can instead be
explained by the critical turbulence hypothesis (Huisman et al., 1999; Taylor
and Ferrari, 2011b; Brody and Lozier, 2014; Smyth et al., 2014). These
theories distinguish between a convectively driven actively mixed layer and a
density-defined mixed layer such that if convective mixing reduces
sufficiently, blooms can occur in the actively mixing layer although the
density-defined mixing layer remains deep. Therefore, blooms are able to form
in the apparent absence of stratification, as defined by the presence of a
thermocline. An alternative to the hypotheses concerning physical controls on
bloom formation is the disturbance–recovery hypothesis proposed by
Behrenfeld (2010), which suggests that the decoupling of phytoplankton and
microzooplankton contact rates in deep winter mixed layers results in
phytoplankton net growth from winter onwards due to reduced mortality (via
grazing). It is also possible that there are multiple biological and physical
controls, acting on different spatial and temporal scales, that drive the
heterogeneous bloom distributions observed via remote sensing (e.g. Lindemann
and St. John, 2014).
Significant interannual and decadal variability in the structure and timing
of spring blooms in the North Atlantic has been documented (Henson et al.,
2009). Such variability in bloom timing has been attributed to the variation
in the winter mixed layer depth (WMLD); a deeper WMLD results in a delayed
bloom in the subarctic North Atlantic (Henson et al., 2009). A strong
latitudinal trend exists in the North Atlantic where the spring bloom
propagates north due to seasonal relief from light limitation at high
latitudes (Siegel et al., 2002; Henson et al., 2009). Both the role of the
WMLD in interannual variability in bloom timing and the northwards
progression of bloom start dates highlight how physical processes have a
clear and significant impact on bloom formation. The controls on the
variability in bloom magnitude are less certain, although it appears to be a
combination of WMLD variability influencing the start date as well as
biological factors such as phytoplankton composition and grazing (Henson et
al., 2009).
Despite considerable discussion on the various factors that may or may not
influence bloom initiation, timing, magnitude and phenology, few studies
have actually examined the in situ phytoplankton community. Instead, because
of the need for temporally resolved data, satellite-derived products and
models have been used in much of the previous work on spring blooms.
However, such methods cannot address the potential influence of the complex
plankton community structure on the development of a spring bloom.
The traditional textbook view of a phytoplankton spring bloom is that the
pre-bloom pico-phytoplankton-dominated (cells < 2 µm) community
is directly succeeded by a diatom-dominated community (Margalef, 1978; Barber
and Hiscock, 2006); as conditions become more favourable for growth, a diatom
bloom develops, “suppressing” the growth of other phytoplankton groups. Through
either increased predation, nutrient stress, or a changing physical
environment (Margalef, 1978), diatoms decline and are then replaced by other
phytoplankton such as dinoflagellates and coccolithophores (Lochte et al.,
1993; Leblanc et al., 2009). In this way, a series of phytoplankton
functional type successions occur as the spring bloom develops. That diatoms
often dominate intense spring blooms is well accepted (Lochte et al., 1993;
Rees et al., 1999); however, the dynamics of the interplay between diatoms and
the rest of the community have been questioned (Barber and Hiscock, 2006).
The rapid proliferation of diatoms in a spring bloom does not necessarily
suppress other phytoplankton (Lochte et al., 1993; Barber and Hiscock, 2006),
and the “rising tide” hypothesis states that instead of succession, the
favourable conditions for diatoms also favour other phytoplankton groups, and
therefore all phytoplankton will respond positively and grow (Barber and
Hiscock, 2006). The apparent suppression of the phytoplankton community by
diatoms is due to the relatively high intrinsic growth rates of diatoms
resulting in concentrations dwarfing the rest of the community. The rising
tide hypothesis is a contrasting theory to succession; however, it may be
that the phytoplankton community response will not be universal, with some
taxa-specific succession due to competition or increased grazing (Brown et
al., 2008). Furthermore, succession may appear to occur if phytoplankton loss
rates are taxonomically specific, such that while many phytoplankton groups
concurrently grow, successive loss of specific groups occurs.
The overall goal of our study was to determine the phytoplankton community
structure, and its evolution during the spring bloom in the North Atlantic,
linking the community structure to the physical environment and examining
whether succession to a diatom-dominated environment would occur early in the
growth season (March–April). Sampling for this study was carried out as part
of the multidisciplinary EuroBASIN “Deep Convection Cruise”. The timing and
location of this cruise (19 March–2 May 2012) was chosen to try to observe
the transition from deep winter convection to spring stratification, and
examine the physical controls on the dynamics of phytoplankton, carbon
export,
and trophic interactions. A recent study has previously suggested that winter
convection in the North Atlantic and Norwegian Sea sustains an overwintering
phytoplankton population, thus providing an inoculum for the spring bloom
(Backhaus et al., 2003), although this transition has not been explicitly
examined before.
Sampling locations in the Iceland Basin
(ICB) and the Norwegian Basin (NWB), superimposed on a composite of MODIS sea
surface temperature for 25 March–29 April 2012.
Methods
Sampling
The Deep Convection Cruise repeatedly sampled two pelagic locations in the
North Atlantic (Fig. 1), situated in the Iceland (ICB, 61.50∘ N,
11.00∘ W) and Norwegian (NWB, 62.83∘ N, 2.50∘ W)
basins, onboard the R/V Meteor. The ICB was visited four times, and
the NWB visited three times during the course of the cruise. Samples were
collected from multiple casts of a conductivity–temperature–depth (CTD)
Niskin rosette, equipped with a fluorometer, at each station. Water samples
for rates of primary production (PP), community structure, and ancillary
parameters (chlorophyll a (Chl a), calcite (PIC), particulate silicate
(bSiO2), and macronutrient concentrations) were collected from predawn
(02:30–05:00 GMT) casts from six light depths (55, 20, 14, 7, 5, and 1 %
of incidental PAR). The depth of 1 % incident irradiance was assumed to
equate to the depth of the euphotic zone (e.g. Poulton et al., 2010). Optical
depths were determined from a daytime CTD cast on preceding days at each
site. Additional samples for coccolithophore community structure and
ancillary parameters were collected from a second CTD cast, while samples for
detailed size-fractionated Chl a were collected from a third cast.
Primary production
Carbon fixation rates were determined using the 13C stable isotope
method (Legendre and Gosseline, 1996). Water samples (1.2 L) collected from
the six irradiance depths were inoculated with
45–46 µmol L-1 13C labelled sodium bicarbonate,
representing 1.7–1.8 % of the ambient dissolved inorganic carbon pool.
Samples were incubated in an on-deck incubator, chilled with sea surface
water, and light depths were replicated using optical filters (misty-blue and
grey, LEE™). Incubations were terminated after
24 h by filtration onto pre-ashed (> 400 ∘C, > 4 h) Whatman
GF/F filters. Acid-labile particulate inorganic carbon (PIC) was removed by adding 1–2 drops of
1 % HCl to the filter followed by extensive rinsing with freshly filtered
(Fisherbrand MF300, ∼ 0.7 µm pore size) unlabelled seawater.
Filters were oven dried (40 ∘C, 8–12 h) and stored in Millipore
PetriSlides™. A parallel 55 % bottle for
size-fractionated primary production (< 10 µm) was incubated
alongside the other samples, with the incubation terminated by pre-filtration
through 10 µm polycarbonate
(Nuclepore™) filters and the filtrate was
filtered and processed as above.
The isotopic analysis was performed on an automated nitrogen and carbon
analysis preparation system with a 20–20 stable isotope analyser (PDZ Europa
Scientific Instruments). The 13C-carbon fixation rate was calculated
using the equations described in Legendre and Gosseline (1996). The
> 10 µm PP fraction was calculated as the difference between
total PP and < 10 µm PP.
Community structure
Water samples for diatom and microzooplankton counts, collected from predawn
cast surface samples (5–15 m) were preserved with acidic Lugol's solution
(2 % final solution) in 100 mL amber glass bottles. Cells were counted in
50 mL Hydro-Bios chambers using a Brunel SP-95-I inverted microscope (X200;
Brunel Microscopes Ltd). Samples for flow cytometry were fixed with
glutaraldehyde (0.5 % final solution) and stored at -80 ∘C
before being analysed using a FACSCalibur (Beckton Dickinson) flow cytometer
(Zubkov et al., 2007).
Water samples (0.5–1 L) for coccolithophore cell numbers and species
identification were collected from surface samples (5–15 m) onto cellulose
nitrate filters (0.8 µm pore size, Whatman), oven dried, and
stored in Millipore PetriSlides™. Permanent
slides of filter halves were prepared and analysed using polarising light
microscopy following Poulton et al. (2010). Coccolithophores were analysed at
the species level following Frada et al. (2010). For confirmation of species
identification, a subset of filter halves were analysed by scanning electron
microscope (SEM) following Daniels et al. (2012). Coccolithophore species
were identified according to Young et al. (2003).
Chlorophyll a
Water samples (250 mL) for total Chl a analysis were filtered onto
Fisherbrand MF300 filters. Parallel samples were filtered onto polycarbonate
filters (10 µm) for > 10 µm Chl a. Samples for
detailed size-fractionated Chl a, collected in duplicate from a single
depth in the upper water column (12–35 m), were filtered in parallel onto
polycarbonate filters of various pore size (2, 10, 20 µm) and
MF300 filters (effective pore size 0.7 µm). Filters were extracted
in 8 mL of 90 % acetone (Sigma) for 20–24 h (dark, 4 ∘C).
Measurements of Chl a fluorescence were analysed on a Turner Designs
Trilogy Fluorometer, calibrated using a solid standard and a Chl a
extract.
Ancillary parameters
Particulate inorganic carbon (PIC) measurements were made on water samples
(500 mL) filtered onto polycarbonate filters (0.8 µm pore-size,
Whatman), rinsed with trace ammonium solution (pH ∼ 10) and oven dried
(6–8 h, 30–40 ∘C). The analysis was carried out following Daniels
et al. (2012) except that extractions were carried out in 5.0 mL of
0.4 mol L-1 nitric acid, erroneously reported as 0.5 mL in Daniels et
al. (2012). Particulate silicate (bSiO2) samples were collected onto
polycarbonate filters (0.8 µm pore-size, Whatman), rinsed with
trace ammonium solution (pH ∼ 10) and oven dried (6–8 h,
30–40 ∘C). Digestion of bSiO2 was carried out in polypropylene
tubes using 0.2 mol L-1 sodium hydroxide, before being neutralised
with 0.2 mol L-1 hydrochloric acid (Ragueneau and Tréguer, 1994;
Brown et al., 2003). The solutions were analysed using a SEAL QuAAtro
autoanalyser, and no corrections were made for lithogenic silica.
Macronutrients (nitrate, phosphate, silicic acid) concentrations were
determined following Sanders et al. (2007) on a Skalar autoanalyser.
Samples for total dissolved inorganic carbon (CT) were drawn into
500 mL borosilicate bottles. No filtering of samples occurred prior to
analysis. Samples were stored in the dark and analysed within 12 h of
sampling, and thus no poisoning was required. CT was determined using
coulometric titration (Johnson et al., 1987) with a precision of ≤ 2 µmol kg-1. Measurements were calibrated against
certified reference material (CRM, Dickson, 2010). Seawater pHT
was measured using the automated marine pH sensor (AMpS) system as described
in Bellerby et al. (2002) modified for discrete mode. This system is an
automated spectrophotometric pH sensor that makes dual measurements of thymol
blue. The pHT data used in this study were computed using the
total hydrogen ion concentration scale and have a precision of 0.0002
pHT and an estimated accuracy of better than 0.0025
pHT units against CRM standards. The measured CT and
pHT, with associated temperatures and salinity, were input to
CO2SYS (Lewis and Wallace, 1998) to calculate saturation state of CaCO3
using the dissociation constants for carbonic acid of Dickson and
Millero (1987), boric acid from Dickson (1990b), sulfuric acid following
Dickson (1990a) and the CO2 solubility coefficients from Weiss (1974).
Upper water column profiles for the ICB (a, b, c) and the NWB
(d, e, f), of density (a, d), CTD fluorescence (b, e), and CTD fluorescence
normalised to peak CTD fluorescence for each profile (c, f).
Seasonal variation in (a) satellite sea surface temperature
(SST), (b) satellite daily incidental PAR, and day length and satellite
Chl a for (c) the ICB and (d) the NWB for 2012. The grey region indicates the period of the cruise. The
vertical dotted lines in plots (c) and (d) indicate bloom initiation, calculated
following Henson et al. (2009). The insets in (c) and (d) show the variation in
satellite chlorophyll during the period of the cruise.
Satellite data on Chl a, photosynthetically available radiation (PAR), and
sea surface temperature (SST) were obtained from the Aqua Moderate Resolution
Image Spectroradiometer (MODIS) as 4 km resolution, 8-day composites. Data
were extracted as averaged 3 × 3 pixel grids, centred on the
sampling locations. Day length was calculated according to Kirk (1994). The
R/V Meteor was not fitted with a PAR sensor, and thus satellite
measurements were the only available source of PAR data.
Data availability
Data included in the paper are available from the data repository PANGAEA via
Daniels and Poulton (2013) for the measurements of primary production,
Chl a, particulate inorganic carbon, particulate silicate, cell
counts of coccolithophores, diatoms, and microzooplankton; Esposito and
Martin (2013) for measurements of nutrients; Paulsen et al. (2014) for
measurements of picoplankton and nanoplankton; and Bellerby (2014) for
measurements of the carbonate chemistry.
Physicochemical features of the Iceland Basin and Norwegian Basin
stations: Sta., station; SST, sea surface temperature; SSS, sea surface salinity;
CT, dissolved inorganic carbon; ΩC, calcite
saturation state; NO3, nitrate; PO4, phosphate; dSi, silicic
acid.
Carbonate chemistry
Surface macro-
nutrients (mmolm-3)
Location
Sta.
Date
Day of year
SST (∘C)
SSS
CT (µmolm-3)
pHT
ΩC
NO3
PO4
dSi
Iceland Basin
1
25 Mar
85
8.7
35.3
2149
8.0
3.1
12.3
0.79
4.7
1
26 Mar
86
8.7
35.3
2148
8.0
3.1
12.6
0.81
4.7
2
7 Apr
98
8.7
35.3
2140
8.0
3.1
12.4
0.81
4.5
2
10 Apr
101
8.7
35.3
2139
8.1
3.2
11.5
0.75
4.3
3
18 Apr
109
8.8
35.3
2144
8.1
3.2
11.6
0.79
4.3
3
19 Apr
110
8.7
35.3
2150
8.1
3.2
11.9
0.76
4.1
4
27 Apr
118
8.9
35.3
2135
8.1
3.2
10.7
0.70
3.1
4
29 Apr
120
8.6
35.3
2148
–
–
12.0
0.80
4.2
Norwegian Basin
1
30 Mar
90
7.0
35.2
2142
8.1
3.0
12.1
0.67
5.3
1
31 Mar
91
7.1
35.2
2161
8.1
3.0
12.5
0.81
5.4
2
12 Apr
103
7.2
35.2
2153
8.1
3.0
13.4
0.84
5.6
2
14 Apr
105
6.9
35.2
2152
8.1
3.0
13.5
0.82
5.6
3
22 Apr
113
6.5
35.1
2150
8.1
3.0
12.2
0.79
5.7
3
25 Apr
116
6.8
35.2
2143
8.1
3.0
12.5
0.82
5.7
Results
General oceanography
The two sites were characterised by very different water column profiles
throughout the study period. In the NWB, a pycnocline persisted over the
upper 400 m with a variable mixed layer (20–100 m, Fig. 2d). In contrast,
the ICB appeared well mixed over the upper 400 m when considered over the
equivalent density range (Fig. 2a). However, weak unstable stratification was
observed in the upper 100 m when examined over a much narrower range in
density (Fig. 2a inset).
Surface (5–15 m) measurements of (a) particulate silicate
(bSiO2) and (b) diatom species abundance in the Iceland Basin. Black
symbols indicate where diatoms were counted from Lugol's samples, while open
symbols indicate SEM counts.
Sea surface temperature showed little variation at both sites
(Table 1), while the ICB (8.6–8.9 ∘C) was consistently warmer than
the NWB (6.5–7.2 ∘C). Satellite estimates of SST were colder than
in situ measurements and exhibited greater variability (Fig. 3a). However,
the general pattern of the ICB being warmer than the NWB was observed from
both in situ measurements and satellite-derived ones. Sea-surface salinity
(SSS), pHT, and ΩCa were relatively stable
throughout the study with total ranges of 35.1–35.3, 8.0–8.1, and 3.0–3.2,
respectively (Table 1).
Biological features of the Iceland Basin and Norwegian Basin
stations: Sta., station; Chl a; PP, primary production; bSiO2,
particulate silicate; PIC.
Surface size fractions
Euphotic zone integrals
Location
Sta.
Date
Day of
Surface
Surface PP
>10 µm
>10 µm
Euphotic
Chl a
bSiO2
PIC
PP
year
Chl a
(mmolCm-3d-1)
Chl a (%)
PP (%)
zone
(mgm-2)
(mmolSim-2)
(mmolCm-2)
(mmolCm-2d-1)
(mgm-3)
depth
(m)
Iceland Basin
1
25 Mar
85
0.27
28
115
22.3
8.3
7.7
1
26 Mar
86
0.31
0.41
24
35
115
26.5
2.5
4.5
22.2
2
7 Apr
98
1.13
80
72
61.4
8.7
8.7
2
10 Apr
101
2.18
4.89
84
61
72
146.4
19.6
6.9
221.9
3
18 Apr
109
1.01
56
50
49.2
13.4
6.5
3
19 Apr
110
1.15
2.11
67
40
50
55.6
15.4
5.8
58.0
4
27 Apr
118
1.18
–
86
75.7
37.1
11.0
4
29 Apr
120
0.62
1.19
94
61
86
55.3
27.6
8.1
61.5
Norwegian Basin
1
30 Mar
90
0.58
6
80
34.6
5.5
7.7
1
31 Mar
91
0.59
0.67
7
5
80
39.2
7.0
7.1
27.3
2
12 Apr
103
0.54
9
65
32.3
4.4
5.9
2
14 Apr
105
0.69
0.90
13
5
65
37.2
4.4
6.4
38.2
3
22 Apr
113
0.93
10
56
46.7
5.0
9.7
3
25 Apr
116
0.84
1.11
21
20
56
40.5
6.4
10.5
39.8
Initial surface water concentrations of nitrate (NO3) and phosphate
(PO4) were ∼ 12 mmol N m-3 and
∼ 0.7–0.8 mmol P m-3 at both sites (Table 1). Silicic acid
(dSi) was high throughout the study period (mostly > 4 mmol
Si m-3), with slightly higher concentrations in the NWB (5.3–5.7 mmol
Si m-3) than the ICB (< 5 mmol Si m-3). Drawdown of
1 mmol m-3 of NO3 and dSi occurred in the ICB between 19 and
27 April, but then returned to previous levels by 29 April. Nutrient
drawdown did not occur in the NWB during the cruise period.
Both sites showed a similar trend of increasing daily PAR during the study
(Fig. 3b): a twofold increase in the NWB (from 12.3 to 28.4 mol
quanta m-2 d-1) and a slightly smaller increase in the ICB (from
13.5 to 24.3 mol quanta m-2 d-1). Daily irradiance continued to
increase after the cruise finished, peaking around 40–45 days later at
values in excess of 40 mol quanta m-2 d-1 (Fig. 3b). The general
trend of increasing PAR was also reflected in the day length (Fig. 3b). At
both sites, the euphotic depth shoaled as the study progressed, from 115 to
50 m in the ICB and from 80 m to 56 m in the NWB (Table 2). However, the
euphotic depth again deepened by 36 m between the third and fourth visits to the
ICB.
Size-fractionated Chl a for (a, c) the
Iceland Basin, and (b, d) the Norwegian Basin. Plots (a) and (b) show the
< 10 and > 10 µm fractions, (c) and (d) show the
< 2, 2–10, 10–20 and
> 20 µm fractions.
For the duration of the cruise until 27 April (day 118), surface and
euphotic zone integrated particulate silicate (bSiO2) increased in the
ICB, peaking at 0.66 and 37.1 mmol Si m-2, respectively (Fig. 4a,
Table 2), with a significant decline in bSiO2 after this date. Lower
values of bSiO2, with little temporal variation, were found in the NWB,
although a small increase in surface bSiO2 was observed between 14
and 22 April (from 0.05 to 0.08 mmol Si m-3, Fig. 4a). Standing stocks
of PIC were less variable than bSiO2. The highest surface values were
observed during the last visit to the NWB (0.20 mmol C m-3), while
integrated calcite peaked at 11 mmol C m-2 on 27 April in the ICB
(Table 2).
Chlorophyll a
Profiles of CTD fluorescence in the NWB had a relatively consistent structure
with high fluorescence in the stratified upper water column (Fig. 2e and f).
Intra-site variation can be seen in the relative fluorescence values in
surface waters, but a consistent increase over time was not observed.
Fluorescence profiles in the ICB were more variable (Fig. 2b and c), ranging
from profiles with high surface fluorescence (10 April, day 101) to profiles
with elevated fluorescence throughout the upper 300 m.
Acetone extracted measurements of Chl a ranged from 0.1
to 2.3 mg m-3 with the highest values generally in surface waters
(5–15 m). Surface Chl a was variable in the ICB, with the lowest surface
values (0.27–0.31 mg m-3) measured during the first visit (Table 2).
Peak Chl a values in the ICB occurred on 10 April (2.2 mg m-3),
after which Chl a declined, reaching a low of 0.62 mg m-3 by the end
of the study (but remaining above initial Chl a values). Initial surface
Chl a values were higher in the NWB (0.58 mg m-3) than the ICB, and
generally increased throughout the cruise. However, the magnitude of this
increase was significantly smaller than in the ICB, peaking at only
0.93 mg m-3. Euphotic zone integrated Chl a showed a similar pattern
to surface Chl a across both stations, with the highest values on 10 April
(ICB, 146.4 mg m-2).
Satellite estimates of Chl a also showed an increase in Chl a at both
sites during the cruise (Fig. 3c and d), although these values
(< 0.4 mg m-3) were much lower than measured in situ Chl a
(Table 2). The large increase in Chl a associated with North Atlantic
spring blooms occurred between 20 and 30 days after the cruise (Fig. 3c and
d). Both sites were characterised by two peaks in Chl a throughout the
year: one in late spring (mid-June) and another in late summer (mid-August).
The largest satellite-derived Chl a values occurred in the ICB in late
spring (1.7 mg m-3, Fig. 3c), while in the NWB, peak Chl a occurred
during the late summer bloom (1.6 mg m-3, Fig. 3d).
Size-fractionated Chl a revealed very different communities at the two
sites (Table 2 and Fig. 5). Initially in the ICB, approximately a quarter of
the Chl a biomass was derived from the > 10 µm fraction
(24–28 %; Table 2, Fig. 5a). On subsequent visits, this increased
significantly to 56–94 % (Table 2, Fig. 5a). A general trend of an
increasing contribution from the > 10 µm fraction was also
observed in those samples collected for more detailed size fractionation
(Fig. 5c). The detailed size fractionation showed that excluding the first
ICB visit where samples were not collected, the > 10 µm fraction
was completely dominated by the > 20 µm fraction in the ICB
(Fig. 5c). Conversely, the > 10 µm fraction formed only a minor
component (< 21 %) of the Chl a biomass in the NWB, although the
> 10 µm contribution did increase throughout the cruise
(Table 2, Fig. 5b). Detailed size fractionation in the NWB showed that the
biggest increase in contribution came from the 2–10 µm fraction,
increasing from 14 to 32 % (Fig. 5d), which was due to an increase in the
absolute value of 2–10 µm Chl a (from 0.09 to 0.31 mg m-3).
Phytoplankton abundance at the Iceland Basin and Norwegian Basin
stations, measured by flow cytometry (Synechococcus, picoeukaryotes,
and nanoplankton), inverted microscopy (diatoms and microzooplankton), and
polarising light microscopy (coccolithophores). Sta. stands for station.
Phytoplankton abundance (cellsmL-1)
Location
Sta.
Date
Day of
Depth
Synechococcus
Picoeukaryotes
Nanoplankton
Diatoms
Micro-
Coccolithophores
year
(m)
(<10 µm)
(>10 µm)
zooplankton
E. huxleyi
C. pelagicus
A. robusta
Others
Iceland Basin
1
25 Mar
85
5
–
–
–
–
–
7.5
0.15
1.2
1
26 Mar
86
15
675
2347
1116
1.3
2.5
4.4
0.22
0.5
2
7 Apr
98
2
400
3375
215
–
–
5.2
0.19
4.1
2
10 Apr
101
10
480
6715
813
249.2
4.0
6.8
0.15
0.7
3
18 Apr
109
5
–
–
–
–
–
16.9
0.22
25.6
3
19 Apr
110
7
2112
6962
712
151.3
2.8
21.9
0.69
22.3
4
27 Apr
118
8
1299
1486
298
–
–
26.7
0.81
7.9
4
29 Apr
120
11
782
1215
313
87.8
4.7
13.2
0.84
7.5
Norwegian Basin
1
30 Mar
90
8
–
–
–
–
–
6.1
0.09
4.8
2.9
1
31 Mar
90
10
2617
18 016
484
0.2
10.8
7.2
0.28
3.8
1.0
2
12 Apr
103
8
–
–
–
–
–
11.8
0.41
2.7
0.3
2
14 Apr
105
10
3372
10 433
858
0.1
17.6
16.0
0.38
3.7
5.1
3
22 Apr
113
7
–
–
–
–
–
27.9
2.66
12.7
11.7
3
25 Apr
116
7
5483
8456
1384
0.5
14.0
28.1
2.79
7.8
8.6
Primary production
Primary production (PP) in surface waters (5–15 m) ranged from 0.41 to
4.89 mmol C m-3 d-1 in this study (Table 2), with PP generally
decreasing with depth. Surface PP correlated well with euphotic zone
integrated PP (r=0.98, p < 0.001, n=7). The largest change in
PP occurred in the ICB between 26 March and 10 April, when peak PP
rates were observed in both the surface waters (4.89 mmol
C m-3 d-1) and integrated over the euphotic zone (221.9 mmol
C m-2 d-1, Table 2). Following this peak, PP in the ICB declined,
although it generally remained higher than pre-peak PP rates. The
> 10 µm PP fraction contributed between 35 and 61 % of the
total PP in the ICB. In contrast, the range and maximum rate of PP in the NWB
was much lower than the ICB (0.67–1.11 mmol C m-3 d-1, Table 2)
with the > 10 µm PP making up a much smaller fraction
(< 20 %). However, a clear increase in the > 10 µm PP
fraction was observed between 14 April (5 %) and 25 April
(20 %). The general trend in total and size-fractionated PP at both sites
reflected that observed in the Chl a measurements.
Community structure
Community structure – picoplankton and nanoplankton
Flow cytometry identified Synechococcus, autotrophic picoeukaryotes,
and autotrophic nanoplankton (< 10 µm) in relatively high
abundance in all samples (Table 3). In general, Synechococcus and
picoeukaryotes were more abundant in the NWB than the ICB. In the NWB, a
contrasting pattern between Synechococcus, nanoplankton, and
picoeukaryotes was observed; while Synechococcus and the
nanoplankton increased significantly from 2617 to 5483 and 484 to
1384 cells mL-1 respectively, a large decrease in picoeukaryotes was
also observed, from 18 016 to 8456 cells mL-1. A less coherent
pattern was observed in the ICB, where peak concentrations of both
Synechococcus (2112 cells mL-1) and picoeukaryotes
(6982 cells mL-1) occurred on 19 April, with a general decline
after this date.
Community structure – coccolithophores
The coccolithophore species identified by polarised light microscopy were
Emiliania huxleyi, Coccolithus pelagicus,
Calcidiscus leptoporus, Coronosphaera mediterranea, and
Syracosphaera pulchra. More detailed SEM observations found a number
of other species at low cell densities not clearly identified by the light
microscope: Algirosphaera robusta, Acanthoica quattrospina,
Calciopappus caudatus, Gephyrocapsa muellerae, Syracosphaera corolla, S. marginaporata,
S. molischii, S. nodosa, S. ossa, and unidentified
Syracosphaera spp. Many of these coccolithophore species have cell
diameters between 10 and 20 µm, with the notable exceptions of
E. huxleyi, G. muellerae, and the smaller
Syracosphaera spp. (Young et al., 2003). Two morphotypes of
E. huxleyi were observed in all samples (A and B) with morphotype A
consistently dominant (71–100 % of total E. huxleyi numbers).
The coccolithophore compositions at both sites were similar, with E. huxleyi generally the most abundant species (4.4–28.1 cells mL-1,
Table 3) at both sites, while C. was present in
all samples at relatively low cell densities (0.15–2.79 cells mL-1).
The NWB was also characterised by the presence of A. robusta
(2.7–12.7 cells mL-1), while S. marginaporata
(0–21.3 cells mL-1) was only present in the ICB.
A general increase in coccolithophore abundance was observed in the ICB, with
a large increase between 10 and 18 April (7.7–42.8 cells mL-1).
Emiliania huxleyi abundance decreased between 27 and 29 April
(26.7–13.2 cells mL-1), but C. pelagicus remained relatively
constant (0.81–0.84 cells mL-1). In the NWB, coccolithophores
generally followed the trend of increasing Chl a with increases in
abundance over time (Table 3). Within the coccolithophore communities, the
largest relative increase in species abundance was by C. pelagicus
with a sevenfold increase (0.38–2.66 cells mL-1) between 14 and
22 April in the NWB.
Community structure – diatoms and microzooplankton
The diatom taxa identified by light microscopy were Chaetoceros,
Cylindrotheca, Dactyliosolen, Guinardia,
Leptocylindrus, Navicula, Pseudo-nitzschia,
Rhizosolenia, Thalassionema, and Thalassiosira.
Whilst samples for diatom counts were collected only once per visit to each
station, particulate silicate (bSiO2) samples were collected from two
CTD casts per visit. As the major source of bSiO2, the significant
variability observed in bSiO2 between the two CTD casts at each visit
(Fig. 4a) suggested a temporal variability in the diatom cell abundance not
captured in the Lugol's counts. Therefore, diatom abundance counts were
supplemented using SEM-image-based diatom counts from samples collected from
those CTDs where Lugol's samples were not collected (Fig. 4b). However, due
to the relatively smaller volumes examined by SEM (∼ 4.2 mL vs.
50 mL), there is a greater inherent error in the counts and as such Lugol's
counts were used wherever possible.
The diatom community was highly variable in the ICB (Fig. 4). Initially
present only in very low abundances (1.3 cells mL-1, Table 3), a peak
concentration of 249 cells mL-1 was reached 15 days later on 10
April (day 101). The population then decreased over the rest of the study,
down to 88 cells mL-1, but remained above initial levels. A shift in
composition was observed after the population peaked, from a
Chaetoceros-dominated community (67–71 %) on 7 to 10 April
(days 98 to 101) to one dominated by Pseudo-nitzschia (65–73 %,
Fig. 4b) on 27 to 29 April (days 118 to 120). Diatoms were virtually
absent from light microscope measurements of the NWB, reaching a maximum of
only 0.5 cells mL-1 (Table 3).
The main microzooplankton groups present were planktonic ciliates and small
(∼ 5–10 µm) naked dinoflagellates (e.g. Gyrodinium
and Gymnodinium). Microzooplankton concentrations were ∼ 4
times higher in the NWB (10.8–17.6 cells mL-1, Table 3) than in the
ICB (2.5–4.7 cells mL-1, Table 3). Dinoflagellates initially dominated
in the NWB (8.5 cells mL-1), but were succeeded by ciliates
(11.9–12.9 cells mL-1). Both dinoflagellates and ciliates were
present in similar concentrations in the ICB, except for the final visit,
when dinoflagellates dominated (4.2 cells mL-1).
Discussion
Time series or mixing?
The dynamic nature of the ocean causes inherent difficulties in interpreting
data collected from fixed-point, Eulerian time series, such as those in this
study. The distribution of phytoplankton in the ocean exhibits significant
heterogeneity, which can be driven by mesoscale physical processes (Martin,
2005). Therefore, Eulerian time series are vulnerable to advection such that
instead of repeatedly sampling the same phytoplankton community, each sample
is potentially from a different population, possibly with a different
composition. Before examining the development of the phytoplankton community,
it is therefore necessary to consider the physicochemical environment. Eddies
and other mesoscale features could potentially cause significant variations
in measured SST, SSS, nutrients, and carbonate chemistry. With the possible
exception of the nutrient concentrations, which are also affected by the
biology present, the measured physicochemical parameters were stable
throughout the study period (Table 1). Therefore, although we cannot rule out
the influence of mesoscale features and advection during the study, the
relative consistency of the sampled physicochemical environment suggests that
the community structure is representative of the location, rather than from
multiple eddies, and thus we can examine how the community developed during
the cruise and compare between two geographically separated sites.
Drivers of the phytoplankton bloom
Density profiles in the ICB were seemingly indicative of a
well-mixed water column (Fig. 2a), yet elevated fluorescence in the upper
100 m of the water column suggested that phytoplankton cells were not being
evenly mixed throughout the water column (Fig. 2b). A detailed examination of
the upper 100 m found small changes in the density profiles (Fig. 2a inset),
corresponding to the elevated fluorescence, however the change in density
with respective to depth was smaller (Δσt < 0.025 over
1 m) than most metrics used to identify mixed layers (e.g. Kara et al.,
2000). Elevated fluorescence with only minimal stratification is consistent
with the critical turbulence hypothesis (Huisman et al., 1999); here it is
likely that active mixing had ceased, allowing phytoplankton net growth,
while the response of the physical environment was slower than the biological
response, and stratification was only just beginning to develop.
Although ICB upper water column fluorescence was elevated throughout the
study, there was significant variation in the magnitude and structure of the
fluorescence profiles (Figs. 3b and c), as well as a peak and decline in
surface Chl a and primary production (PP). The general
theory of bloom formation is that once conditions are favourable for bloom
formation, the pre-bloom winter ecosystem will transition into a blooming
ecosystem, identifiable by increasing Chl a biomass and PP. However, we did
not observe this smooth transition. Instead, we observed periods of stability,
characterised by increased stratification, Chl a, and PP, followed by
periods of instability where increased mixing weakened the developing
stratification. Increased mixing detrains phytoplankton out of the surface
waters, reducing both Chl a biomass and PP, and exporting them to depth
(Giering et al., 2015). One such mixing event occurred between 27 and 29
April (days 118 and 120), where minor stratification (Δσt = 0.019) disappeared (Δσt < 0.001) over the upper
25 m, surface Chl a halved from 1.18 to 0.62 mg m-3, and the
fluorescence profile became well-mixed (Fig. 2c). Furthermore, surface
nutrients were replenished (Table 1). All of the above are indicative of a mixing
event.
The transition period from winter to spring was also observed in satellite
data from the ICB. Bloom metrics (Siegel et al., 2002; Henson et al., 2009)
of satellite Chl a estimate that the main spring bloom did not begin until
∼ 20 days after our study period (dashed line in Fig. 3c). However,
there was a significant increase (r= 0.99, p < 0.015, n=4) in
Chl a during the study period (Fig. 3c inset), consistent with our in situ
observations, that suggests that while the environment was not yet stable
enough for sustained and rapid phytoplankton growth, intermittent net
phytoplankton growth did occur. Therefore, we suggest that the early stages
of a spring bloom are characterised by periods of instability and net growth,
and that rather than a single smooth transition into a bloom, for a period of
weeks prior to the main spring bloom event, phytoplankton form temporary
mini-blooms during transient periods of stability. The export flux from these
pre-bloom communities is a potentially significant food source to the
mesopelagic (Giering et al., 2015).
In contrast to the instability of the ICB, the NWB was
relatively stable with a strong and persistent pycnocline (Fig. 2d), as well
as elevated fluorescence in the upper mixed layer (Fig. 2e). However, a
variable mixed layer that did not consistently shallow in the NWB (Fig. 2d)
suggests variability in the strength of the physical forcing that may
explain why although Chl a and PP increased throughout the cruise, they
remained below that observed in the ICB during the study period (Table 2).
Furthermore, the net community growth rate (Chl a
derived, μChl) was relatively low (0.02 d-1),
suggesting that, as was the case for the ICB, the main spring bloom had yet to
start. This was also confirmed from the satellite Chl a, which showed a
very similar pattern to the ICB: although Chl a increased during our study
period (Fig. 3d inset), the main bloom did not start until ∼ 20 days
later (Fig. 3d). Therefore, despite very different physical environments, the
two sites both represented early stages in the development of spring blooms.
Unlike the ICB, the factors limiting bloom formation in the NWB cannot easily
be attributed to the physicochemical environment. A switch from negative to
positive net heat flux has been linked to spring bloom formation (Taylor and
Ferrari, 2011b; Smyth et al., 2014), but here the net heat flux was negative
for the majority of the study at both sites (C. Lindemann, personal communication,
2014;
Giering et al., 2015). Irradiance is a key driver of phytoplankton growth and
bloom formation; the main spring bloom did not occur until daily PAR reached
its seasonal maximum of 45 mol photons m-2 d-1 (Fig. 3b, c, and
d). The general increase in daily PAR over our study period was coupled with
an increase in Chl a and PP in the NWB, suggesting that despite a
stratified environment, irradiance was an important driving factor. Although
the magnitude of the daily flux of PAR at both sites was similar, Chl a and
PP were higher in the less stable ICB than the NWB, suggesting that
irradiance was not the only driver of the NWB phytoplankton community.
Irradiance levels can also have a secondary influence on the requirements for
phytoplankton growth. While macronutrients were replete at both sites, we did
not measure micronutrients such as iron (Fe). The cellular Fe demand
increases in low-light conditions (Moore et al., 2006), and as such, Fe may be
limiting at this early stage of bloom formation in the Norwegian Basin.
However, without measurements of Fe (or phytoplankton photophysiology), we
cannot directly test this hypothesis. Although temperature limits
phytoplankton gross growth rates (Eppley, 1972), the relatively small
difference in temperature between the NWB and the ICB
(∼ 1.5–2.5 ∘C) is unlikely to have a significant impact on
gross growth rates (Eppley, 1972).
Besides physicochemical drivers of bloom formation, the plankton community
itself can play a large role in the development and formation of a bloom.
Physiological parameters such as net growth rates (μChl) and
“assimilation efficiency” (i.e. PP normalised to biomass, in this case
Chl a) can provide an insight into the state of the phytoplankton
community. The NWB community had noticeably lower assimilation efficiency
(13.5–15.8 g C [g Chl a]-1 d-1) than that in the ICB
(15.7–27.0 g C [g Chl a]-1 d-1); thus, the relative increase
in biomass in the NWB was slower, as reflected in the growth rates where the
maximum estimated (net) growth rate in the NWB (μChl=0.05 d-1) was much lower than in the ICB (μChl=0.22 d-1). Assimilation efficiency varies with both environmental
conditions and species composition, and therefore the composition of the
phytoplankton community is likely to be another key driver behind the
contrasting phytoplankton dynamics observed in the ICB and NWB.
Overall community composition
The contrasting structures of Chl a and PP size fractions observed at the
two sites (Fig. 5, Table 2) were reflected in the contrasting composition of
the phytoplankton communities (Table 3). In the ICB, a change in dominance in
both Chl a and PP, from < 10 to > 10 µm fraction,
occurred as the diatom abundance increased between 26 March and 7 April. An increase in the abundance of the < 10 µm community
was also observed during this period, composed mainly of < 2 µm
Synechococcus and picoeukaryotes (Table 3, Fig. 5c). However, with
most of the diatom population having cells > 20 µm (Fig. 5c),
their relatively large size allowed the diatoms to dominate both the Chl a
and PP while remaining numerically inferior. The decline in total Chl a and
PP later in our study was reflected by a decreasing abundance of most of the
phytoplankton community (Table 3). However, the relative decrease of
pico-phytoplankton (Synechococcus and picoeukaryotes) was greater
than that of the diatoms, such that the > 10 µm fraction
increased its dominance for both Chl a (94 %) and PP (61 %).
Therefore, although surface Chl a and PP declined after the “mini-bloom”
event which peaked around 10 April, the community structure did not
return to a pre-bloom composition, but instead remained dominated by diatoms.
Interestingly, the phytoplankton response to the increased diatom abundance
was not uniform, with the nanoplankton abundance decreasing and
Synechococcus increasing only after the peak in diatom abundance.
Thus, we observed that the phytoplankton community response during the spring
bloom was not universal across functional types as has been previously
observed elsewhere (Brown et al., 2008).
In contrast to the ICB, a large shift in the NWB community was not observed.
Picoeukaryotes dominated both in terms of abundance (Table 3) and Chl a,
through the < 2 µm fraction (Fig. 5d). This is consistent with
previous observations of early stage spring blooms (Joint et al., 1993).
Although the < 2 µm Chl a fraction showed little variation
throughout the study (0.45–0.58 mg m-3), variation in the
< 2 µm phytoplankton composition did occur, with an apparent
succession from picoeukaryotes to Synechococcus and nanoplankton.
This may represent a community shift early in development of the spring bloom
or may demonstrate the inherent variability within pre-bloom communities.
The increase in total Chl a in the NWB was driven primarily by the 2 to
10 µm fraction, which was likely composed of the nanoplankton,
which itself had a threefold increase in population size (from 484 to
1384 cells mL-1, Table 3). The phytoplankton responsible for the
observed increase in the > 10 µm Chl a and PP fraction cannot
be confidently determined; large diatoms were absent and thus could not have
contributed. The microzooplankton population consisted of ciliates and
dinoflagellates (Gyrodinium and Gymnodinium), both of which
have been reported to be mixotrophic (Putt, 1990; Stoecker, 1999), and thus
could potentially have contributed to the Chl a measurements. Furthermore,
it is possible that part of the nanoplankton community, as measured by flow
cytometry, was > 10 µm, and thus the increasing concentration of
nanoplankton could have also contributed to the increase in the
> 10 µm fraction.
Relative independence of the coccolithophore community
The traditional view on the seasonality of coccolithophores is that they
succeed the diatom spring bloom, forming coccolithophore blooms in late
summer. However, here we observed a typical North Atlantic community of
coccolithophores (Savidge et al., 1995; Dale et al., 1999; Poulton et al.,
2010), growing alongside the ICB diatom bloom, rather than just succeeding
the diatoms. This is consistent with the rising tide hypothesis of Barber
and Hiscock (2006), as well as observations from both in situ (Leblanc et
al., 2009) and satellite measurements (Hopkins et al., 2015) suggesting that
coccolithophores are present in North Atlantic spring blooms. Despite the
contrasting environment and overall community structure of the NWB, the
coccolithophore dynamics were similar, appearing independent of the overall
community dynamics. Species-specific growth rates of coccolithophores
(calculated from changes in cell concentration) found that E. huxleyi had the same net growth rate at both sites (μ=0.06 d-1),
while the net growth rate of C. pelagicus was comparable to
E. huxleyi in the ICB, but was slightly higher in the NWB (μ= 0.13 d-1). Culture experiments of E. huxleyi and
C. pelagicus have found comparable gross growth rates at
temperatures below 10 ∘C (Daniels et al., 2014), and our in situ
observations support this conclusion. That C. pelagicus has higher
net growth rates could also be indicative of higher grazing on the relatively
smaller E. huxleyi (Daniels et al., 2014).
Contrasting patterns of diatoms
The diatom bloom in the ICB, which began between 26 March (day 86) and
7 April (day 98), was initially dominated by Chaetoceros
(71–67 % of total cell numbers, Fig. 4b). As the community developed
however, Pseudo-nitzschia succeeded as the dominant diatom genus
(65–73 % of total). Both Chaetoceros and
Pseudo-nitzschia are common spring bloom diatoms (Sieracki et al.,
1993; Rees et al., 1999; Brown et al., 2003), with Chaetoceros often
dominant in the earlier stages of North Atlantic spring blooms (Sieracki et
al., 1993; Rees et al., 1999). Resting spores of Chaetoceros have
also been observed to dominate the export flux out of the Iceland Basin
during the North Atlantic spring bloom in May 2008 (Rynearson et al., 2013),
suggesting dominance of the spring bloom prior to this period, consistent
with the early community observed in our study.
Pseudo-nitzschia (previously identified as Nitzschia in
other studies) tends to dominate later in the spring bloom (Sieracki et al.,
1993; Moore et al., 2005), also consistent with this study. This suggests
that as a genus, Chaetoceros spp. are either able to adapt more quickly
than Pseudo-nitzschia, or that they have a wider niche of growing
conditions through a large diversity of species. However, once established,
Pseudo-nitzschia spp. are able to outcompete Chaetoceros,
resulting in a community shift. That the succession of the diatom community
observed in the ICB is consistent with that expected in the main diatom
spring bloom suggests that a mini-diatom bloom occurred prior to the
formation of the main spring bloom.
The observed variability in the relationship between diatoms (the main source
of bSiO2) and bSiO2 was likely due to the species-specific
variability in the cellular bSiO2 content of diatoms (Baines et al.,
2010). The abundance of Pseudo-nitzschia, rather than
Chaetoceros, best explained the trend in bSiO2 (r=0.92, p < 0.001, n=8), suggesting that Pseudo-nitzschia was the
major producer of bSiO2. Previously, Chaetoceros has been
observed as the major exporter of bSiO2 in the Iceland Basin (Rynearson
et al., 2013). Here, as the major producer of bSiO2,
Pseudo-nitzschia has the potential to also be the major exporter of
bSiO2.
In contrast to the ICB, diatoms appeared to be virtually absent
(< 0.5 cells mL-1) in the NWB. While the dSi : NO3 ratio was
below the 1:1 requirement for diatoms, consistent with previous studies of
North Atlantic blooms (Leblanc et al., 2009), dSi did not become depleted
(always above 5 mmol Si m-3, Table 1), and thus was not limiting.
Furthermore, significant and increasing concentrations of particulate
silicate (bSiO2) were measured throughout the cruise (Fig. 4a). As the
main source of bSiO2, diatoms would therefore be expected to be present.
Although absent in the Lugol's counts, examination of SEM images found
significant numbers (101–600 cells mL-1) of small
(< 5 µm) diatoms (predominantly Minidiscus spp.) that
were too small to be identified by light microscopy. However, they may still
constitute an important component of the nanoplankton, as measured by flow
cytometry. As a result of their small cell size, nano-sized diatoms, such as
Minidiscus, are easily missed when identifying and enumerating the
phytoplankton community, and as such their potential biogeochemical
importance may be greatly underestimated (Hinz et al., 2012). Other
nano-sized diatom species have been observed as major components of the
phytoplankton community on the Patagonian Shelf (Poulton et al., 2013), in
the Scotia Sea (Hinz et al., 2012), the north-east Atlantic (Boyd and Newton,
1995; Savidge et al., 1995) and in the Norwegian Sea (Dale et al., 1999).
The Minidiscus spp. observed in this study exhibited a significant
increase in population size during the study, from initial concentrations of
100 to 200 cells mL-1, then up to 600 cells mL-1 by the end of
the study, and correlated well with both bSiO2 (r=0.93, p < 0.01, n=6), and Chl a (r=0.93, p < 0.01, n=6).
Furthermore, the increasing concentration of Minidiscus corresponded
to the increase in the 2 to 10 µm Chl a size fraction (Fig. 5d).
The maximum net growth rate of Minidiscus, estimated from changes in
cell abundances (μ= 0.13 d-1), was significantly higher than that
calculated for the total community using Chl a (μChl= 0.05 d-1). While different methods were used to
determine these growth rates, it does suggest that conditions were favourable
for the small nano-sized diatoms to grow more rapidly than the bulk
community.
The question therefore remains as to why the larger (> 10 µm)
diatoms were virtually absent in an environment that is physically stable and
nutrient replete, while small diatoms were able to thrive. The fate and
ecology of overwintering oceanic diatoms is poorly understood. Many diatom
species, both neritic and pelagic, are capable of forming resting stages that
sink post-bloom (Smetacek, 1985; Rynearson et al., 2013), yet diatoms must be
present in spring when the diatom bloom begins. Therefore, either a diatom
population is sustained in the upper water column over winter (Backhaus et
al., 2003), or the spring diatom community is sourced from elsewhere
(horizontally or vertically). In relatively shallow coastal environments,
benthic resting stages overwinter until spring when they are remixed up into
the water column, providing the seed population for the spring bloom (McQuoid
and Godhe, 2004). It is unlikely that oceanic diatom blooms are seeded from
the sediment, as the depths are far too great for remixing. However, viable
diatom cells have been observed suspended at depth (> 1000 m) in the
ocean (Smetacek, 1985), and it is possible that these suspended deep
populations are remixed to seed the spring bloom. An alternative hypothesis
is based on the observation that diatom blooms generally occur first in
coastal waters before progressing to the open ocean (Smetacek, 1985),
suggesting that coastal diatom populations are horizontally advected into
pelagic waters, thus seeding the spring bloom in the open ocean from shelf
waters. The location of the source coastal populations, and their transit
time to the open ocean location, would then affect the timing of the diatom
blooms
With such low concentrations of > 10 µm diatoms
(< 0.5 cells mL-1) in the NWB, it is possible that the
overwintering diatom population was too small to seed the spring bloom.
Grazing pressure by microzooplankton and mesozooplankton may influence the
composition and timing of the onset of the spring bloom (Behrenfeld and Boss,
2014). The potential grazing pressure from the significant microzooplankton
population (10.8–17.6 cells mL-1) in the NWB may have exerted such a
control on the observed diatom population that it could not develop into a
diatom bloom. Instead, an alternative seed population of diatoms may be
required to overcome the grazing pressure and initiate the diatom bloom in
the NWB. Whether the absence of large diatoms is a regular occurrence in the
NWB, or whether inter-annual shifts between small and large diatoms occur, as
observed in the north-east Atlantic (Boyd and Newton, 1995), will have
significant implications for export and the functioning of the biological
carbon pump. The absence of larger diatoms in pelagic spring blooms in the
Norwegian Sea has also been observed by Dale et al. (1999), and it may be
that large diatoms are completely absent from the pelagic south-east
Norwegian Sea. The lack of large diatoms in the NWB could explain the
seasonal profile of satellite Chl a (Fig. 3d); with no large diatoms
present, the spring bloom is less intense, peaking at only ∼ 60 %
of the Chl a concentration found in the ICB.
Clearly, further work is required to examine why large diatoms are absent
from the initial stages of the spring bloom in the NWB, and whether they
ever become abundant in this region.
Conclusions
During March–May 2012, satellite and in situ data from study sites in the
Iceland Basin (ICB) and the Norwegian Basin (NWB) suggested that despite very
different physical environments, the two sites both represented early stages
in the development of the North Atlantic spring bloom. Spring bloom
initiation in the ICB was limited by the physical environment, with periods
of increased mixing inhibiting bloom formation. The physicochemical
environment alone did not limit bloom formation in the NWB as, in spite of
a stable stratified water column and ample nutrients, Chl a biomass and
primary production were relatively low. Phytoplankton efficiency
(Chl a-normalised primary production) was also lower in the NWB, suggesting
that the phytoplankton community composition and/or physiology was also a
limiting factor in bloom formation.
The phytoplankton community in the NWB was dominated by the
< 2 µm Chl a fraction, with high concentrations of
picoeukaryotes (∼ 18 000 cells mL-1) succeeded by
Synechococcus and nanoplankton. In contrast, although the initial
dominance of the < 10 µm Chl a fraction (picoeukaryotes and
nanoplankton) was succeeded by diatoms dominating in the > 10 µm
Chl a fraction, the ICB phytoplankton community generally followed the
rising tide hypothesis, with most of the community positively responding
to the onset of the diatom bloom. Interestingly, coccolithophore dynamics
were similar at both sites, independent of the overall community, with
similar concentrations of the main species Emiliania huxleyi and
Coccolithus pelagicus.
In terms of the diatom community, Chaetoceros initially dominated the
ICB diatom bloom, but was replaced by Pseudo-nitzschia as the bloom
progressed, suggesting Chaetoceros as a key species in diatom bloom
formation, while Pseudo-nitzschia was the major source of
particulate silicate (bSiO2). The lack of large (> 10 µm)
bloom-forming diatoms in the NWB, while small (< 5 µm) diatoms
were present in high numbers (101–600 cells mL-1), suggests that
microzooplankton grazing, coupled with a potential lack of a seed
population, restricted diatom growth in the NWB, or that large diatoms
are absent in NWB spring blooms.
These results suggest that despite both phytoplankton communities being in
the early stage of bloom formation and exhibiting positive net growth rates,
different physicochemical and biological factors control bloom formation
with the resulting blooms likely to be significantly different in terms of
biogeochemistry and trophic interactions throughout the growth season.
Clearly, more in situ studies are needed in the transitional period between
winter and the peak productivity of the spring bloom to examine
compositional differences, growth and mortality factors, and how regional
variability impacts on upper ocean biogeochemistry and deep-sea fluxes of
organic material. Coupled studies of satellite-derived products, including
bloom phenology and phytoplankton physiology, and in situ processes are
needed to examine the full spectrum of factors forming the spring bloom.