Introduction
Estimates of annual primary production (PP) in the ice-covered central
Arctic basins are among the lowest of all oceans worldwide
(Sakshaug et al., 2004). On an annual base, the total
incoming irradiance and the depth of the winter mixing as a proxy for
nutrient stocks are the two main factors that constrain Arctic primary
production (Ardyna et al., 2011; Popova et
al., 2010). Available irradiance is generally sparse due to the low angle of
the sun around the North Pole, and the attenuation effect of sea ice
(Sakshaug and Slagstad, 1991). When enough light becomes available
for PP between May and September (Arndt and
Nicolaus, 2014; Leu et al., 2011), Arctic phototrophs grow in the water
column (phytoplankton), in and below sea ice (sea-ice algae) and in melt
ponds (melt-pond algae). Light is the main limiting factor for the
phytoplankton below thick ice at the beginning of the productive season
(Sherr et al., 2003). However, during the summer months
the total incoming irradiance increases since daylight is available during
24 h, and sea ice is melting away. North of 78∘ N latitude, the
productive season is shorter (June to September) than in southern Arctic
regions, since it is restricted by the amount of light penetrating through
the dense sea-ice cover (Leu et al., 2011).
Nutrients become limiting as the season advances (Tremblay and
Gagnon, 2009), due to strong vertical stratification and reduced wind-driven
mixing affected by sea ice (Carmack et al., 2006).
The central Arctic Ocean is divided into two deep basins separated by the
Lomonosov Ridge: the Eurasian and the Amerasian basins (Fig. 1). These
central basins cover 40 % of the Arctic Ocean, but due to their
inaccessibility, data for both regions are scarce
(Matrai et al., 2013). The two central basins differ in
the inflow of waters. Low-salinity, phosphate-rich and nitrate-depleted
Pacific waters enter the Amerasian Basin through the Bering Strait. Warm,
high-salinity Atlantic waters with a higher N : P ratio reach the Eurasian
Basin through the Fram Strait, but remain submerged under a layer of fresher
Arctic surface water for ∼ 5 years before upwelling
(Jones et al., 1998). Since most of the studies regarding
nutrient limitation in Arctic waters come from the Amerasian Basin, nitrate
is considered the main limiting nutrient for primary production in the
central Arctic Ocean (Tremblay and Gagnon, 2009; Tremblay
et al., 2012). However, nutrient ratios in the Eurasian Basin are very
different to the Amerasian pointing towards silicate limitation rather than
nitrate in some regions (Codispoti et al., 2013;
Sakshaug et al., 2004; Wheeler et al., 1997). In late summer, mostly
regenerated production based on ammonium takes place
(Martin et al., 2012). Grazing pressure and the microbial
loop also play an important role controlling recycling of nutrients vs.
export (Boetius et al., 2013; Olli
et al., 2007; Yager et al., 2011), but remain understudied in the central
Arctic Ocean.
Sparse sampling, high spatial and temporal variability and the use of
different methodologies to estimate PP in and under the ice, as well as in
ice-free regions, result in poorly constrained PP values for the central
Arctic basins (Miller et al., 2015). These range
from 1 Tg C yr-1, assuming no production in ice-covered areas
(Hill et al., 2013), to 119 Tg C yr-1 when
taking into account the total amount of nutrients used for PP from the mixed
layer (Codispoti et al., 2013). The annual
areal net primary productivity (NPP) estimates for the Eurasian Basin, including sea-ice algae, range
between 10 and 15 g C m-2 yr-1, twice as much as in the Amerasian
Basin (Codispoti et
al., 2013; Gosselin et al., 1997; Sakshaug et al., 2004; Ulfsbo et al.,
2014; Wheeler et al., 1996). In the central Arctic Ocean sea-ice algae can
contribute up to 57 % of the NPP in summer (Gosselin et
al., 1997), but their patchy distribution, the technological challenges in
sampling them and the difficulties to obtain in situ estimates of their PP,
cause a high uncertainty in the overall estimates
(Fernández-Méndez et al., 2014; Katlein et al., 2014a).
Physical parameters and autotrophic biomass of the eight ice
stations sampled during the expedition ARKXXVII/3 to the Eurasian Basin of
the central Arctic during August–September 2012.
Station number
1
2
3
4
5
6
7
8
Station ID
PS80/3_224
PS80/3_237
PS80/3_255
PS80/3_277
PS80/3_323
PS80/3_335
PS80/3_349
PS80/3_360
Date
9 Aug 2012
14 Aug 2012
20 Aug 2012
25 Aug 2012
4 Sep 2012
7 Sep 2012
18 Sep 2012
22 Sep 2012
Latitude
84∘3.03′ N
83∘59.19′ N
82∘40.24′ N
82∘52.95′ N
81∘55.53′ N
85∘6.11′ N
87∘56.01′ N
88∘49.66′ N
Longitude
31∘6.83′ E
78∘6.20′ E
109∘35.37′ E
130∘7.77′ E
131∘7.72′ E
122∘14.72′ E
61∘13.04′ E
58∘51.81′ E
Incoming PAR (µmol photons m-2 s-1)
249 ± 90
174 ± 90
104 ± 71
101 ± 57
81 ± 63
49 ± 43
25 ± 15
13 ± 7
Ice cover
80 %
80 %
70 %
80 %
60 %
50 %
100 %
100 %
Ice thickness (m)
1.2
1.2
0.9
0.9
0.8
1.4
1.9
1.8
Ice type (FYI/MYI)
FYI
FYI
FYI
FYI
FYI
FYI
MYI
MYI
Melt-pond coverage (%)
40 %
20 %
40 %
50 %
10 %
30 %
20 %
20 %
Melt-pond depth (m)
0.6
0.2
0.3
0.4
0.3
0.2
0.3
0.3
Melt-pond salinity
18
1
0.5
2
14
0.4
30
12
Euphotic zone depth (m)
24
29
30
29
33
29
15
7
Euphotic zone Chl a (mg m-2)
3.2
17
8
8
11
17
3
1.2
Sea-ice Chl a (mg m-2)
1.2
1.7
0.6
0.4
0.3
0.4
8
8
Melt-pond Chl a (mg m-2)
0.3
0.02
0.1
0.02
0.1
0.02
0.3
0.04
Ice was classified in two types: first year (FYI) and multi-year (MYI)
according to its structure and physical properties. The euphotic zone depth
is a weighted average of the euphotic zone depth below bare ice, ponded ice
and open water at each station. Chlorophyll a (Chl a) was integrated for the melt-pond depth, the sea ice
∼ 600 could be applied to obtain carbon units (Laney et al., 2014).
Recent evidence suggests that the rapid Arctic warming and sea-ice retreat
are changing key factors governing primary productivity, especially in the
central Arctic basins. The percentage of thick multi-year ice (MYI) has been
decreasing rapidly (Laxon et al., 2013;
Maslanik et al., 2007; Stroeve et al., 2012), reducing the annual mean ice
thickness from 3.6 to 1.2 m since 1975 (Lindsay and Schweiger,
2015). A summerly ice-free Arctic has been predicted to occur around 2050
(Wang and Overland, 2012). The lowest sea-ice extent since the
beginning of recorded observations was reached in September 2012
(NSIDC, 2012) leaving 45 % of the Eurasian Basin north of 78∘ N ice-free
(< 15 % ice cover). Furthermore, an increase in melt-pond-covered
sea ice has been observed (Rösel and Kaleschke, 2012),
enlarging the habitat of phytoplankton and sea-ice algae
(Kramer and Kiko, 2011; Lee et al., 2011). All of
these changes combined lead to an increase in the amount of irradiance
reaching the water column in the central Arctic Ocean
(Nicolaus et al., 2012). On the other hand, nutrient
availability in the euphotic zone of the deep central Arctic Ocean may
decrease due to the stronger stratification caused by increased freshwater
storage. An increase in nutrients from river runoff has been hypothesized,
but a recent study by Le Fouest et al. (2013) indicates
that these nutrients will not be enough to increase primary production in
the deep central Arctic substantially, since they will be consumed at the
shelf seas. Furthermore, changes in light conditions and nutrient
availability might affect the timing of sea ice and water column blooms and
the composition of the autotrophic biomass; this will have implications for
timing and food quality available for grazers (Leu et al., 2010; Slagstad et al., 2011) and
for total export to the deep sea (Lalande et al., 2013).
This study assesses primary productivity in the Eurasian Basin of the
central Arctic Ocean at the time of the sea-ice minimum extent in summer
2012, in comparison to previous estimates. It aims to quantify the relative
contribution of sea ice, melt ponds and water column to total NPP, both in
situ and for the entire Eurasian Basin, with a focus on the bottom-up
limiting factors of NPP (light and nutrients) at different timescales.
Using complementary approaches we test the hypothesis that primary
productivity – including that of under-ice algae – could increase with
decreasing ice cover in the central Arctic Ocean.
Methods
Study site and sampling
Sea ice, melt ponds and water column were sampled during the R/V
Polarstern
expedition ARK-XXVII/3 to the Eurasian Basin of the central Arctic Ocean
during summer 2012. The expedition started in early August visiting the ice
margin and heading towards the Laptev Sea (Fig. 1a). At the beginning of
September the ice-free shelf edge of the Laptev Sea (77–80∘ N,
118–133∘ E) was sampled (Fig. 1b) and at the end of the month the
central Arctic was reached (85–88∘ N, 52–123∘ E) (Fig. 1c).
The expedition covered a large portion of the Eurasian Basin and
included 33 water stations in Atlantic-influenced waters entering the Arctic
through Fram Strait (Atlantic inflow as described in Rudels, 2012),
as well as eight ice stations expanding through different nutrient
regimes, ice coverage (from ice-free waters to 100 % ice cover) and ice
types according to age, thickness, pond and snow cover and topography. First
year ice (FYI) was rather flat with a high coverage of melt ponds and MYI is
thicker and has more snow on top (Table 1).
Sea-ice concentration and melt-pond coverage were assessed during the entire
cruise by observations from the bridge (Hendricks et
al., 2012) (Table S1 in the Supplement). Sea-ice thickness was additionally measured with an
airborne electromagnetic (EM) bird as described in
Haas et al. (2009). Sea ice was sampled using an
ice corer (9 cm diameter) (Kovacs Enterprise, Roseburg, USA). Ice cores were
cut into two equal sections (top and bottom) for primary productivity
measurements and in 10 cm sections for biomass and nutrient measurements.
Ice cores were melted in the dark at 4 ∘C for 24 h on a shaker
(Mikkelsen et al., 2008; Rintala et al., 2014).
Seawater from 50 to 100 m depth from a nearby station filtered through a
0.2 µm filter (200 mL per cm of ice) was added to the ice sections used
for pigment analysis (Thomas and Dieckmann, 2010).
Melt-pond water samples were obtained with a hand pump (Model 6132-0010,
Nalgene, Penfield, NY, USA) and melt-pond depth, temperature and salinity
were measured in situ using a hand-held conductivity metre (315i with
TetraCon electrode cell, WTW GmbH, Weilheim in Oberbayern, Germany). Water
column profiles of temperature and salinity were obtained using a
conductivity–temperature–depth (CTD) system with a Carousel Water Sampler
(Sea-Bird Electronics Inc., Washington, USA). Water below the ice was
sampled using a peristaltic pump (Masterflex®
E/STM portable sampler, 115 VAC, Oldham, UK), while
water samples in ice-free areas were collected at 2–5 m depth during the
upcast of the CTD rosette sampler. Flow cytometer samples showed no evident
difference in relation to either sampling method. To exclude the effect of
propeller mixing in the upper 20 m of CTD profiles, additional vertical
profiles of under ice salinity, temperature and fluorescence were obtained
by manually lowering a CTD probe through holes in the ice floes sampled
(ice CTD; Sea and Sun Technology CTD75M, Trappenkamp, Germany).
Fluorescence in the water column was measured with two fluorometers (Turner
Cyclops, California, USA) attached to the ship CTD and the ice-CTD.
Fluorescence values were calibrated a posteriori with chlorophyll a
(Chl a) concentrations from water samples using high-performance liquid
chromatography (HPLC) as described in Tran et al. (2013)
and David et al. (2015). Chl a in the ice and melt ponds
was measured using the same HPLC method.
For the nutrient addition experiments, 20 L of seawater was collected at
station 3 at the depth of the maximum Chl a concentration (25 m) using the
ship's CTD sampler, and a piece of sea ice (40 cm × 40 cm)
was cut with an ice saw at station 8 and melted in the dark in 0.2 µm
filtered seawater from the same location (Rozanska et al., 2009; Thomas and Dieckmann, 2010).
In situ net primary production
Net primary production (NPP) was measured using the 14C uptake method
(Steemann Nielsen, 1952) with minor modifications. Melted
sea ice, seawater and melt-pond samples were spiked with 0.1 µCi mL-1
of 14C, labelled sodium bicarbonate (Moravek Biochemicals,
Brea, USA) and distributed in 10 clear bottles (20 mL each). Subsequently
they were incubated for 12 h at -1.3 ∘C under different scalar
irradiances (0–420 µmol photons m-2 s-1) measured with a
spherical sensor (Spherical Micro Quantum Sensor US-SQS/L, Heinz Walz,
Effeltrich, Germany). At the end of the incubation, samples were filtered
onto 0.2 µm nitrocellulose filters and the particulate radioactive
carbon uptake was determined by liquid scintillation counting using filter
count scintillation cocktail (Perkin Elmer, Waltham, USA). The carbon uptake
values in the dark were subtracted from the carbon uptake values measured in
the light incubations.
Dissolved inorganic carbon (DIC) was measured for each sample using the flow
injection system (Hall and Aller, 1992). The DIC concentration was
taken into account to calculate the amount of labelled bicarbonate
incorporated into the cell. Carbon fixation rates were normalized
volumetrically and by Chl a (10.1594/PANGAEA.834221).
Photosynthesis-irradiance curves (PI curves) were fitted using
MATLAB® according to the equation proposed by
Platt et al. (1980) including a photoinhibition
parameter (β) and providing the main photosynthetic parameters:
maximum Chl a normalized carbon fixation rate if there was no
photoinhibition (Pb) and the initial slope of the saturation
curve (α). The derived parameters, light intensity at which photosynthesis
is maximal (Im), the carbon fixation rate at that maximal irradiance
(Pmb) and the adaptation parameter or photoacclimation index
(Ik), were calculated according to Platt et al. (1982) (Table 2).
Depth-integrated in situ rates were calculated for each environment as a
function of the available photosynthetically active radiation (PAR).
Irradiance profiles were calculated for each environment (sea ice, melt
pond, water under the ice and open water) from the daily average incoming
solar shortwave irradiance measured by a pyranometer (Kipp & Zonen,
Delft, the Netherlands) mounted on the ship. We used light attenuation
coefficients of 10 m-1 for snow, 1.5 m-1 for sea ice
(Perovich, 1996) and 0.1 m-1 for Atlantic-influenced Arctic
seawater, based on literature values and observations during the cruise.
Planar irradiance was transformed to scalar irradiance according to
Ehn and Mundy (2013) and Katlein et al. (2014). Water column production was integrated over the euphotic zone (1 %
of incoming irradiance) and sea-ice production over the ice thickness.
Melt-pond coverage and sea-ice concentration (Table 1) were taken into
account when calculating the total primary production per area.
Average photosynthesis versus irradiance curves (PI curve)
for each environment. The average fitted curve and the photosynthetic
parameters derived from it were used to calculate the in situ primary production in each
environment during August and September for the Eurasian Basin using the
irradiance-based CAOPP model. The dots represent the experimental
measurements, the black solid line is the fitted curve, the dashed lines are
the minimum and the maximum, and the grey shaded area is the standard
deviation. Average PI parameters are represented on the top left corner.
Photosynthetic parameters and incoming irradiance of the
different environments in the central Arctic divided in August and September.
Photosynthetic parameters
Environment (n PI
Pb
Pmb
α
β
Im
Ik
I
curves)
(mg C (mg Chl a)-1 h-1)
(mg C (mg Chl a)-1 (µmol photons m-2 s-1)-1 h-1)
(µmol photons m-2 s-1)
(µmol photons m-2 s-1)
Mean (Min–Max)
August
Melt pond (n = 4)
2036 (65–6670)
2.8 (0.4–8)
0.05 (0.002–0.15)
13.6 (0.08–50)
379 (135–785)
139 (50–290)
145 (102–279)
Sea ice (n = 7)
105 (0.08–377)
0.3 (0.07–0.7)
0.005 (0.001–0.01)
0.6 (0–2.3)
326 (166–876)
64 (34–98)
53 (24–229)
Water under the ice (n = 4)
300 (0.2–1160)
0.6 (0.2–1.4)
0.01 (0.003–0.02)
1.9 (0–7.3)
331 (158–787)
56 (29–80)
3 (0.7–22)
Open water (n = 2)
1290 (391–2187)
3.5 (2.2–4.7)
0.05 (0.004–0.08)
7.7 (0.2–15)
797 (143–1450)
293 (52–533)
32 (1.3–140)
September
Melt pond (n = 4)
1.8 (1.3–2.5)
1.2 (0.4–2.3)
0.03 (0.004–0.07)
0.003 (0.001–0.004)
187 (144–252)
58 (32–290)
29 (13–91)
Sea ice (n = 6)
0.07 (0.03–99)
0.06 (0.04–0.2)
0.002 (0.001–0.004)
0 (0–0.5)
127 (96–402)
26 (17–64)
4 (1–38)
Water under the ice (n = 4)
0.5 (0.2–0.8)
0.4 (0.2–0.7)
0.02 (0.01–0.02)
0.001 (0–0.002)
319 (102–599)
26 (14–38)
0.7 (0.2–6)
Open water (n = 7)
0.5 (0.4–0.9)
0.5 (0.3–0.9)
0.03 (0.02–0.05)
0 (0–0.001)
85 (59–734)
15 (9–26)
16 (1.3–240)
Pb is the maximum Chl a normalized carbon fixation rate if there was no
photoinhibition, α is the initial slope of the saturation curve,
β is the photoinhibition parameter, Pmb is the carbon
fixation rate at maximal irradiance, Im is the light intensity at which
photosynthesis is maximal, Ik is the adaptation parameter or
photoacclimation index. I is the average daily irradiance received in each
environment from the surface to the bottom of the pond, the ice or the
euphotic zone in the water column.
* Open waters in September correspond to the Laptev Sea region.
Central Arctic Ocean Primary Productivity model
We developed the Central Arctic Ocean Primary Productivity (CAOPP) model as
an irradiance-based model to obtain estimates of sea ice, melt pond and
water column NPP in the central Arctic (north of 78∘ N). This
model is based on the photosynthesis equation from Platt
et al. (1980) and the under-ice light parameterization of Arndt
and Nicolaus (2014). Average Chl a profiles and average PI curves were
calculated for each environment (Fig. 2): melt ponds (MP), MYI,
FYI, water under the ice (WUI) and open water (OW).
Key parameters for photosynthetic activity (Table 2) were calculated from
the measured PI curves during summer 2012, excluding those where the
coefficient of determination of the fit (R2) was smaller than 0.5. NPP
was calculated as described in Sect. 2.2 for each grid point of a 10 km
polar stereographic grid, and a vertical integration with a resolution of
10 cm in the ice and 1 m in the water column. Downwelling solar irradiances at
the surface (PAR) were calculated from the European Centre for Medium-Range
Weather Forecast (ECMWF) Era Interim re-analyses (Dee et al., 2011). Downwelling transmitted
irradiances underneath the sea ice were calculated using the light
parameterization of Arndt and Nicolaus (2014) based on sea-ice data from Ocean and Sea
Ice Satellite Application Facility (OSISAF) (Andersen et al., 2007).
Light extinction in all media was assumed to follow an exponential decay.
For water and sea ice we used the same light extinction coefficients as
presented above. NPP was calculated as a function of PAR for every depth
multiplied with the according Chl a concentration and integrated over the
euphotic zone (1 % incoming PAR). For pixels with a sea-ice
concentration > 15 %, the WUI average PI curve was used, while for pixels
with < 15 % sea-ice concentration the OW average PI curve was
used. Note that the OW average PI curve is based on data obtained close to
the Laptev Sea area. For melt ponds, an average depth of 0.4 m was used
based on observations during the expedition (Hendricks
et al., 2012). Since satellite-based melt-pond cover data were not available
for summer 2012, a constant melt-pond concentration was used for FYI (26 %)
and for MYI (29 %) following Arndt and Nicolaus (2014) and
Rösel and Kaleschke (2012). These values are similar to the
average melt-pond coverage observed during our cruise (30 ± 15 %)
(Hendricks et al., 2012). Total depth-integrated NPP
(INPP) was calculated as an average of the three compartments, i.e. open
water, water covered by sea ice and water covered by sea ice with
melt ponds, weighted with the respective areal fraction. To estimate the
total range of INPP, we ran the CAOPP model three times using the average,
the minimum and the maximum photosynthetic parameters.
To investigate differences in NPP in different sectors of the deep Eurasian
Basin due to changes in the sea-ice conditions, we ran the model under two
different scenarios: one with sea-ice conditions previous to the rapid
sea-ice decline in the 1980s and another one with no sea-ice cover in summer.
For the first scenario, we chose 1982 as a representative year previous to
the long-term trend of sea-ice decline (Fig. 1c). For the second scenario we
chose a summer ice-free scenario that has been predicted to occur around
2050 (Wang and Overland, 2012). For the 1982 scenario, the
sea-ice coverage information was retrieved from OSI SAF
(Andersen et al., 2007) and the incoming irradiance
from data re-analysis (Arndt and Nicolaus, 2014). For the
ice-free scenario, the ice cover was removed from the model, and all other
parameters, including incoming irradiance, were kept as in 2012. Both
scenarios assume no changes in the photosynthetic parameters, and the
nutrient concentrations were set as observed in 2012. The mean results for
September 1982, 2012 and 2050 are compared in Table 5 to detect the
increasing or decreasing trend in NPP.
Nutrient addition experiments
Two nutrient addition experiments were performed during the cruise at ice
stations 3 and 8 (Fig. 1). For the first one, seawater from the depth of the
Chl a maximum (25 m) was collected, and for the second one, MYI with a brown
coloration due to the high content of sea-ice algae was melted in filtered
seawater taken at the same spot. Both samples were pre-filtered through a
100 µm mesh to remove grazers and kept at 0 ∘C and
65 µmol photons m-2 s-1 in 25 L transparent bottles until
the start of the experiment. Chl a was monitored every day with a Turner
Trilogy Fluorometer (model 7200-000) (Turner, California, USA) to identify
the end of a possible lag effect. Once Chl a reached a stable concentration
(6 days for seawater and 4 days for sea ice) the sample was mixed and
distributed in 10 transparent 5 L Nalgene bottles (2 L in each). The initial
biomass concentration in the samples was estimated by measuring Chl a and
particulate organic matter. A sub-sample (0.5 L) was filtered through a
pre-combusted glass fiber filter (GF/F) (0.7 µm pore size, Whatman,
Kent, UK) and analysed with an elemental analyser (EA3024-IRMS,
EuroVetorSpA, Milan, Italy) to quantify particulate organic carbon (POC) and
particulate organic nitrogen (PON). For Chl a quantification a sub-sample (0.5 L) was filtered
through a GF/F filter and the pigments were extracted with 90 % acetone
during 24 h (Parsons et al., 1984). The fluorescence was
then measured with a Turner Fluorometer (Turner, California, USA).
Nutrient concentrations (nitrate, phosphate and silicate) were measured with
a standard photometric method using a Technicon TRAACS 800 continuous flow
auto-analyser (Technicon Corporation) according to established methods
(Boetius et al., 2013). Five different treatments in
duplicate were incubated at 75 µmu mol photons m-2 s-1. This
irradiance is slightly higher than the average irradiance below the ice at
the end of the productive season to avoid light limitation and prevent
photoinhibition. The five treatments consisted of a control with no nutrient
addition (C), a positive control with the three nutrients added (C+) and
three treatments with one nutrient added in each (N+, P+ and Si+). In
each treatment, the added nutrient concentration resembled the concentration
of that nutrient in deep waters (> 100 m) at the same ice
station. Biomass (Chl a, POC and PON) and nutrients were measured in each
treatment after 2 days and compared to the initial value. In parallel a
sub-set of four samples (20 mL each) from each treatment were spiked with
14C bicarbonate to estimate NPP as described above. Three samples were
incubated under light conditions (75 µmol photons m-2 s-1)
and one in the dark for 24 h. Previous to incubation and at the end of the
experiments the qualitative algal composition from each treatment was
studied with a plankton chamber (Hydro-Bios, Altenholz, Germany) and an
inverted light microscope with phase contrast optics (Axiovert 40C, Carl
Zeiss, Jena, Germany) with an integrated camera (AxioCamMRc, Carl Zeiss, Jena,
Germany). No qualitative shifts in the community composition were observed
before or after the incubation.
Annual new production
We determined the mixed layer depth during the previous winter from
temperature in our summer CTD profiles of the upper Arctic Ocean, following
Rudels (1995) and Korhonen et al. (2013). In the temperature profiles during the Arctic Ocean melting season,
the winter mixed layer depth is indicated by a temperature minimum above the
lower halocline. Any conservative property, such as salinity, observed at
the depth of this temperature minimum, represents the conditions of the
mixed layer during the previous winter. An estimate of the change from the
previous winter is given by the difference between a conservative property
in summer and its reference value at the depth of the temperature minimum.
The vertical integral of these differences represents the addition or
removal of a quantity or substance, for example nitrate, since the previous
winter. All oceanographic data used in this study are available from the
Earth system database PANGAEA (Rabe et al., 2012) (Table S1).
Nutrients (phosphate, silicate and nitrate) in the water column were
measured at discrete depths (2, 10, 20, 30, 50, 75 and 100 m) as described
above (Bakker, 2014) (Table S1). Subsequently, we interpolated
total inorganic nitrogen (TIN = NO3- + NO2-),
phosphate and silicate to the vertical resolution of the continuous
temperature profiles (Reiniger et al., 1968), to
calculate the nutrient inventory in the layer above the temperature minimum.
We then derived the uptake since last winter by calculating the difference
between the integrated nutrient profile at the end of the productive season
(August–September) and the nutrient value at the temperature minimum depth,
which represents the initial nutrient concentration available in winter in
the mixed layer. This approach is similar to the one used by
Codispoti et al. (2013) with the main
difference that they used the few available winter surface nutrient
concentrations. The annual TIN, phosphate and silicate uptake were then
transformed to carbon units using the Redfield ratio 106C : 16N : 15Si : 1P (Brzezinski,
1985; Codispoti et al., 2013; Cota et al., 1996; Harrison et al., 1977;
Smith et al., 1997) giving annual new production estimates for sea ice and
water column during the Arctic productive season. Since the description of
new production refers to production based on nitrate, most of the annual new
production estimates are based on nitrogen draw-down (Dugdale
and Goering, 1967). Ratios higher than the Redfield C : N ratio (7.3–8.3) seem to be
common in Arctic phytoplankton and sinking material (Frigstad et al.,
2014; Tamelander et al., 2013; Tremblay et al., 2008). Using these ratios
would result in a ∼ 10 % increase in the new production
estimates, but to be able to compare our results with previous estimates we
chose the commonly used Redfield ratio. Silicate can also be used to
estimate diatom-based new production (Yool et al.,
2007). Both higher and lower N : Si ratios have been reported for Arctic
diatoms (Simpson et al., 2013; Spilling et al., 2010)
depending on the time of the year and the amount of detritus material
present. To be consistent with the nitrogen-based estimates, we used
Redfield ratios for silicate as well. To calculate an average daily rate, we
assumed a productive season of 120 days (Gradinger et al.,
1999). This method assumes that lateral input of nutrients from rivers or
shelves is negligible which should be the case in the deep part of the
central Arctic Ocean north of 78∘ N (Le Fouest et al., 2013).
Nutrient inventories and molar ratios in each environment
during summer 2012 separated into the three nutrient regimes observed.
Nutrients
Nitrate
Phosphate
Silicate
N : P
N : Si
(mmol m-2)
mol : mol
Ice margin (6–18 August 2012)
Melt pond (n = 2)
0.1–0.8
0–0.12
0.01–1.6
6.8–85
0.5–9
Sea ice (n = 2)
0.3–0.8
0.03–1.3
0.2–0.5
0.6–11
0.6–4
Seawater (n = 9)
76–157
7–16
27–77
9–11
1.7–2.8
Laptev Sea (20 August–10 September 2012)
Melt pond (n = 4)
0.2–0.4
0–0.15
0.1–0.8
2–114
0.4–5
Sea ice (n = 4)
0.2–0.7
0.01–0.06
0.1–0.4
5.2–15
0.6–4
Seawater (n = 17)
8–126
4.5–19
35–220
1.2–8.6
0.1–1
North of 85∘ N (18–27 September 2012)
Melt pond (n = 2)
0.06–0.2
0.01–0.06
0.1–0.9
1–18.3
0.2–0.5
Sea ice (n = 2)
0.2–1.7
0.04–0.1
0.1–0.2
4.7–17
1–16
Seawater (n = 6)
4–31.0
1.5–3.5
12–23
3–9
0.3–1.7
Nutrient concentrations in mol L-1 are available in PANGAEA (doi in
Table S1 in the Supplement). Nutrient concentrations were integrated for melt-pond depth,
sea-ice thickness and water column euphotic zone (1 % incoming PAR).
N : Si and N : P molar ratios in the euphotic zone of the water
column during summer 2012. In (a), the light blue-green range represents
N : Si ratios optimal for diatom growth, red marks an excess of N, blue-purple
represents depletion. In (b), all values are below the N : P Redfield
ratio of 16 indicating a general nitrate depletion with respect to phosphate.
Results
Environmental conditions
Sea ice, melt ponds, and water column environments were sampled in the
Eurasian Basin in August and September 2012 at the end of the productive
season, including completely and partially ice-covered areas above the
abyssal basins as well as open waters on the Eurasian shelf. From the eight
ice stations sampled, stations 1, 2 and 3 represent the ice margin (Nansen
Basin) in early August (Fig. 1a); 4, 5 and 6 represent the degraded ice
cover (average 1 m thickness) above the continental slope of the Eurasian
margin (Fig. 1b), and 7 and 8 represent MYI (average 1.8 m thickness) in the
central Arctic Ocean (Amundsen Basin) in late September (Fig. 1c). In
September, a thin snow cover of 0.02 and 0.06 m thickness was observed. Melt-pond cover varied between 10 and 50 %, and from mid-September most of the
melt ponds were frozen over (< 0.1 m ice thickness). Salinity in the
ice (0–4) and the water column (30–34) were in typical ranges for these
environments, while steep gradients were found in melt ponds (vertical
gradients of 0.4 at the surface to 32 at the bottom) and also between
different melt ponds, depending if they were open to the seawater below or
closed. The daily mean incoming irradiance showed a strong temporal decrease
from a 24 h average of 250 µmol photons m-2 s-1 in early
August to 13 µmol photons m-2 s-1 in late September. In the
water column directly below the ice, photosynthetically active radiation
(PAR) decreased from 40 µmol photons m-2 s-1 in early
August to 1 µmol photons m-2 s-1 in late September.
Integrated net primary productivity (INPP) in the water
column of the central Arctic Eurasian Basin in August–September 2012. The
eight ice stations are circled with a black line. The three boxes indicate
different nutrient regimes characterized by the concentrations of nitrate (N),
phosphate (P) and silicate (Si) in the water column. The superscripts
on each nutrient indicate if there was high (+), medium (∼)
or low (-) amounts of that nutrient in the euphotic zone. High is defined as
concentrations of nitrate > 3 µM, phosphate > 0.3 µM,
and silicate > 3 µM. Low or depleted is
defined as concentrations of nitrate < 1 µM, phosphate < 0.2 µM
and silicate < 1.5 µM.
Nutrient addition experiments on seawater from ice station 3 (a, b)
and sea ice from ice station 8 (c, d). (a) and (c) show
the NPP rate of each treatment after 24 h of nutrient addition. (b) and
(d) show the nutrient uptake in each treatment after nutrient addition.
C is control, N+ is nitrate, P+ is phosphate, Si+ is silicate,
C+ is all nutrients added.
Integrated nutrient inventories were very low in all environments in
accordance with the time of the year (Table 3). Nutrient distributions in
the euphotic zone of the water column were reflected in the N : P and N : Si
ratios (Fig. 3) leading to the characterization of three distinct nutrient
regimes in the Eurasian Basin during the cruise: (1) silicate-depleted ice
margin in early August, (2) nitrate-depleted Laptev Sea margin, and (3) all
nutrient-depleted high central Arctic Ocean (north of 85∘ N)
in late September (Fig. 4; Table 3). Nutrient depletion is defined here
as concentrations lower than 1 µmol L-1 nitrate, 0.2 µmol L-1
phosphate, and 1.5 µmol L-1 silicate.
Photosynthesis and irradiance
Despite the high spatial and temporal variability present in our data set,
certain patterns emerged when comparing the photosynthetic parameters of
sea-ice algae, melt-pond phototrophs and water column phytoplankton (Table 2).
A general decrease in all photosynthetic parameters was detected between
August and September. However, the low number of samples and the wide area
sampled makes it difficult to further differentiate the photosynthetic
parameters. Sea-ice algae showed the best adaptation to low light (initial
slope of the PI curve α). Photoinhibition (β) was lower in
sea-ice algae than in melt-pond phototrophs and under-ice phytoplankton, but
higher than for phytoplankton in ice-free waters (Table 2). In late summer
(August and September), sea-ice algae were adapted to light intensities
between 20 and 100 µmol photons m-2 s-1, similar to the
under-ice phytoplankton (14–80 µmol photons m-2 s-1). These
irradiances were generally higher than the average irradiance available
under the ice (0.2–20 µmol photons m-2 s-1, Table 2).
Phytoplankton showed higher photoinhibition below the ice than in ice-free
waters. Furthermore, in September under-ice phytoplankton showed a higher
range of light intensities at which photosynthesis is maximal (Im) than
phytoplankton in open waters. Melt-pond phototrophs and phytoplankton in
open waters close to the ice margin in early August reached the highest
carbon fixation rates (Pmb). However, they also showed the highest
photoinhibition rates at high irradiances (Table 2), despite being adapted
to higher irradiances (Ik: 50–290 µmol photons m-2 s-1)
than sea-ice algae and phytoplankton. In general, the light
intensity to which the sea-ice and melt-pond communities were adapted
(Ik) and the light intensity at which photosynthesis is maximal
(Im) were similar to what they received (I) at the time of sampling. In
contrast, phytoplankton below the ice and in open waters, generally received
less light than what they would need to perform optimally.
Nutrient addition experiments
For the first nutrient addition experiment, seawater was collected from the
Chl a max depth (25 m) at ice station 3. It had low nitrate (1.3 µmol L-1),
phosphate (0.1 µmol L-1) and silicate (1.2 µmol L-1)
concentrations, and a Chl a concentration of 1.6 µg L-1.
Four days after the addition of 13 µmol L-1
NO3-, 0.8 µmol L-1 PO43- and 10 µmol L-1
SiO43-, to reach concentrations as below the mixed layer,
NPP increased in the silica (Si+) treatment and in the positive control
with all nutrients (C+) (Fig. 5a). POC, PON and Chl a only increased
significantly when all nutrients were added (Fig. 6a). The increase in NPP
corresponded to a carbon yield of 1.3 mg C L-1 d-1, matching the
POC increase of 1.6 mg C L-1 d-1 and the increase in PON
(0.15 mg N L-1 d-1). The C : N ratio in the Si+ and C+ treatments
increased compared to the other treatments from 10 to 14. Silicate uptake
increased significantly in the Si+ and C+ treatments (1.7 and
1.9 µmol L-1 d-1) compared to the control with no nutrient
addition (0.2 µmol L-1 d-1; Fig. 3b). This would correspond
to a silicate yield of 0.07 mg Si L-1 d-1. The organism
responsible for the response was the chain forming diatom Chaetoceros socialis (Fig. 7a).
The sea ice sampled at station 8 was depleted in nutrients with very low
nitrate (0.2 µmol L-1), phosphate (0.1 µmol L-1) and
silicate (1 µmol L-1) concentrations. In this case, the addition
of nutrients resulted in measurable nutrient uptake, but neither in a
measurable increase in biomass nor in NPP (Figs. 5c, d and 6b). Nitrate yield
in the N+ treatment was 0.019 mg N L-1 d-1, twice as much as the
PON increase (0.008 mg N L-1 d-1), indicating nitrate storage in
the cells. The community composition of this sample was formed by typical
sea-ice diatoms in a healthy state (with visible chloroplasts): Nitzschia sp.,
Pseudonitzschia sp., Fragilariopsis sp. and Entomoneis sp. (Fig. 7b).
A few micrograzers (flagellates) were observed with the
microscope and they might have contributed to nutrient uptake.
Biomass changes in nutrient addition experiments.
(a) Nutrient addition experiment with seawater from the Chl a max depth at
station 3. (b) Nutrient addition experiment with sea ice from station 8.
Duplicates of each treatment were incubated for 2 days after nutrient addition.
Microscopy images of the community composition of the two
nutrient experiments: (a) seawater phytoplankton and (b) sea-ice algae.
Net primary production in sea ice, melt ponds and water column
Integrated over the depth of the euphotic zone, phytoplankton constituted
most of the phototrophic biomass, expressed in Chl a units, in all FYI
stations (70–98 %), while sea-ice algae accounted for 68–86 % of the
biomass in the two MYI stations (Table 1). MYI contained almost 1 order of
magnitude more Chl a than FYI. Melt-pond water, excluding algal aggregates
located at the bottom (Fernández-Méndez et al.,
2014), contributed the least to integrated biomass (0.1–6 %). The two melt
ponds with the highest Chl a values (∼ 0.3 mg m-2) had the
highest salinity (18 and 30, respectively).
Net primary production of the water column was also integrated over the
depth of the euphotic zone, which varied spatially. In open waters north of
Svalbard and the Laptev Sea margin, the euphotic zone depth was 45 m. In the
partially ice-covered areas of the ice margin it ranged between 24 and 33 m,
and below thicker ice, north of 85∘ N in late September, it
was between 7 and 15 m deep (Fig. 8a). Water column INPP
measured from samples collected with the ship's CTD varied
from 18 to 308 mg C m-2 d-1 (average 95 ± 78, n = 11) in
ice-free waters of the central Arctic Ocean in summer 2012, and from 0.1 to
232 mg C m-2 d-1 (average 33 ± 50, n = 22) in ice-covered
waters (Fig. 2; Table S2). The large uncertainties in these values derive
from averaging all stations, which are spatially and temporarily diverse.
The highest INPP rates occurred at stations close to the shelves at the
beginning of August, in a water mass that was not yet nutrient depleted
(Fig. 4). The area adjacent to the Laptev Sea, which showed nitrate
depletion, had INPP rates ∼ 100 mg C m-2 d-1. The
lowest INPP rates of < 1 mg C m-2 d-1 were measured in
nutrient-depleted ice-covered waters north of 85∘ N in late
September where PAR below the ice was 0.2–12 µmol photons m-2 s-1 (Fig. 4).
Total INPP rates including water below the ice, sea ice and melt ponds
(0.8–60 mg C m-2 d-1, n = 8) also showed highest values along the
ice edge and lowest in the northernmost stations, decreasing from late
summer to early autumn. INPP in the water under the ice (0.1–60 mg C m-2 d-1)
contributed 63–99 % to total INPP at ice margin stations (ice
stations 1 to 6), while sea ice, in an advanced melting stage, contributed
0.1–33 % (0.2–13 mg C m-2 d-1; Table S2 and Fig. 9). Melt-pond-INPP ranged between 0.01 and 4 mg C m-2 d-1, and their
contribution to total INPP was highly variable (0.05–34 %). They
contributed significantly to INPP at stations 3, 7 and 8 (24–34 %).
Sea-ice algae contributed significantly (50–62 %) to total INPP at
stations 7 and 8, despite their low total INPP rates (1.5 and
0.5 mg C m-2 d-1,
respectively), because the water column production was very low (Fig. 9).
Annual new primary production
The depth of the temperature minimum associated with haline convection
during last winter had a mean of 55 m but ranged from 15 to 93 m depth (Fig. 8b).
The depth of the winter haline convection sets the total amount of
nutrients available at the surface for annual production. These nutrients
will be used in the euphotic zone as the productive season evolves.
Therefore, in situ production is integrated until the euphotic zone depth
while annual production based on nutrient uptake is integrated until the
winter haline convection depth. Stations north of 85∘ N covered by
MYI showed the deepest values. According to the nutrient profiles at the end
of the productive season, the total inorganic nitrogen
(NO3- + NO2-) consumption was 119 ± 46 mmol m-2.
Using the Redfield ratio (106C : 16N), we estimated the carbon used
up for annual new production from nitrogen consumption to be between 0.6 and
17 g C m-2 yr-1 (average:
9.4 ± 3.6 g C m-2 yr-1;
Fig. 10). Assuming a productive season of 120 days
(Gradinger, 2009), the average INPP rate for the Eurasian
Basin was 78 ± 30 mg C m-2 d-1, which is in the upper range
of our in situ measurements in late summer including sea-ice INPP. This
value decreases if we increase the length of the productive period. Indeed,
due to earlier sea-ice retreat it might be that the productive season in the
central Arctic Ocean was longer in 2012. Annual new production is
homogenously distributed through the Eurasian Basin. Only the most northern
stations show higher annual INPP (13–17 g C m-2 yr-1),
corresponding to the shallowest euphotic zone as well as the deepest winter
haline convection depth (70–80 m) causing a higher nutrient availability and draw-down.
New production based on phosphate drawdown using Redfield gives a similar
range (1–16 g C m-2 yr-1). Using silicate draw-down in the ratio
typical for diatoms (7 C : Si) gives an annual carbon uptake range of
0.01–7 g C m-2 yr-1, meaning that around 10–50 % of the annual carbon
uptake based on nitrate was performed by this group of phytoplankton (Fig. 10).
Sea-ice algae sampled in August–September showed an C : Si ratio average
of 9. Using this higher C : Si ratio, and assuming that sea-ice algae are the
main consumer of silicate during the growth season, this would yield annual
carbon uptake values 20–30 % higher. However, sea-ice algae may have a
C : Si ratio closer to Redfield during the growing season when new production
occurs. The new production value would decrease if nutrient uptake by
heterotrophs were taken into account, and increase if nutrient
replenishment by physical advection or biological remineralization would
take place. Unfortunately we could not assess these processes during the mission.
Euphotic zone depth (1 % PAR) weighted average (a), and
winter mixed layer depth (b) estimated from summer temperature profiles.
Average and standard deviations: euphotic zone depth 34 ± 6 m; winter
mixed layer depth 54 ± 15 m.
Integrated net primary production in the central Arctic at
different times and spatial scales. The number of daily measurements is
given in Table 2. The contribution by sub-ice-algal aggregates is not
included in any of the values presented in this table.
Integrated net primary production (INPP)
Daily
Monthly
Annual
In situ
August
September
2012
Mean ± SD
Mean (Min–Max)
Mean ± SD
INPP in the Eurasian Basin
mg C m-2 d-1
mg C m-2 d-1
g C m-2 yr-1
Total
24 ± 19
54
(21–180)
34
(21–65)
9.4 ± 3.6
Sea ice
2.2 ± 4.1
5.8
(0.06–42)
2.6
(0.02–20)
Melt ponds
0.9 ± 1.3
0.5
(0.2–1.7)
0.7
(0.06–3)
Water under the ice
20 ± 20
31
(4.5–116)
12
(3–50)
Open water
84 ± 38
97
(62–115)
56
(43–50)
Mean Area
Sum
Sum
INPP in the central Arctic (78∘ N)
Tg C d-1
Tg C month-1
Tg C yr-1
Total
0.09 ± 0.07
5.7
(1.7–24)
3.4
(1.78–8.45)
36
INPP in the Eurasian Basin
Tg C d-1
Tg C month-1
Tg C yr-1
Total
0.04 ± 0.03
3.1
(1.2–10)
1.9
(1.1–3.6)
7.4 ± 6.7
Sea ice
0.004 ± 0.007
0.2
(0.002–1.7)
0.08
(0.0008–0.6)
FYI
0.004 ± 0.009
0.05
(0.002–0.4)
0.008
(0.0004–0.06)
MYI
0.002 ± 0.001
0.2
(0.0003–1.2)
0.07
(0.0002–0.5)
Melt ponds
0.002 ± 0.002
0.02
(0.007–0.07)
0.02
(0.002–0.09)
Water under the ice
0.04 ± 0.04
1.3
(0.2–6.8)
0.4
(0.1–1.6)
Open water
0.16 ± 0.071
1.5
(1–1.8)
1.4
(1–1.3)
Comparison of three runs of the CAOPP model using the
photosynthetic parameters measured in situ in summer 2012. Sea-ice extent,
multiyear ice fraction, incoming irradiance and mean INPP in Tg C month-1
are presented for the month of September in 1982, 2012 and
2050. Since the purpose is a magnitude comparison between different
scenarios in the different sectors of the Eurasian Basin (depicted in
Fig. 13), only the mean is shown. Min and Max values would deviate from the mean
as presented in Table 4 for 2012.
CAOPP results for September north of 78∘ N
September ice
MYI
Incoming
INPP
extent
fraction
irradiance
September
mean
mean
mean (Min–Max)
mean
mio. km-2
%
µmol photons m-2 s-1
Tg C month-1
1982 (7.17 million km2)
Eurasian Basin (78–90∘ N, 45∘ W–135∘ E)
1.78
71
59 (28–122)
0.93
Laptev (78–90∘ N, 90–135∘ E)
0.53
92
54 (28–84)
0.26
Kara (78–90∘ N, 45–90∘ E)
0.50
85
59 (31–75)
0.27
Barents (78–90∘ N, 0–45∘ E)
0.44
88
64 (30–104)
0.26
Greenland (78–90∘ N, 45∘ W–0∘ E)
0.31
82
63 (29–122)
0.13
2012 (3.42 million km2)
Eurasian Basin (78–90∘ N, 45∘ W–135∘ E)
1.01
51
45 (23–102)
1.88
Laptev (78–90∘ N, 90–135∘ E)
0.29
12
47 (24–84)
0.63
Kara (78–90∘ N, 45–90∘ E)
0.16
30
42 (25–76)
0.66
Barents (78–90∘ N, 0–45∘ E)
0.25
50
42 (25–69)
0.46
Greenland (78–90∘ N, 45∘ W–0∘ E)
0.30
77
52 (24–102)
0h.13
2050 (No ice) Wang and Overland (2012)
Eurasian Basin (78–90∘ N, 45∘ W–135∘ E)
0
0
45 (23–102)
2.91
Laptev (78–90∘ N, 90–135∘ E)
0
0
47 (24–84)
0.87
Kara (78–90∘ N, 45–90∘ E)
0
0
42 (25–76)
0.81
Barents (78–90∘ N, 0–45∘ E)
0
0
42 (25–69)
0.72
Greenland (78–90∘ N, 45∘ W–0∘ E)
0
0
52 (24–102)
0.51
Depth-integrated net primary productivity (INPP) and the
contribution of sea ice, melt ponds and water at eight ice stations in the
Eurasian Basin during summer 2012. The size of the pie chart represents the
magnitude of INPP in mg C m-2 d-1. The values are depicted next to
each pie chart.
New production in the Eurasian Basin during 2012. Carbon
uptake since last winter estimated from nitrate (a), phosphate (b) and
silicate (c) drawdown in the mixed layer. Redfield ratio C : N : Si : P of
106 : 16 : 15 : 1 was used to convert nutrient uptake into annual new production.
Arctic primary production model: CAOPP estimates
Average PI curves and Chl a profiles were calculated for each environment
from summer 2012 measurements. They were used to calculate NPP as a function
of available PAR for the Eurasian Basin of the Arctic Ocean
(78–90∘ N, 135∘ E–45∘ W)
using the CAOPP model. We present here the results calculated with average
parameters, and the minimum and maximum values are available in Table 4. The
average total INPP for the Eurasian Basin was 54 mg C m-2 d-1 in
August and 34 mg C m-2 d-1 in September 2012. We observed a
decrease in total INPP from August to September, in parallel with a decrease
in incoming irradiance (Fig. 11). On average at a basin scale, in late
summer–early autumn, sea-ice algae contributed 6 % to total INPP in the
Eurasian Basin, while NPP in melt ponds was almost negligible (1 %)
(Fig. 12). Algal aggregates trapped in melt ponds were not taken into account due
to their patchiness and difficulty to upscale their contribution to NPP
(Fernández-Méndez et al., 2014). Ice-covered waters
contributed significantly less (36 %) to total NPP per month than open
water (57 %) north of 78∘ N.
When running the CAOPP model with the sea-ice conditions of September 1982
(Fig. 13) (mainly > 2 m thick MYI), the INPP in the Eurasian
Basin was half the NPP in September 2012 (Table 5) assuming that the
nutrient concentrations in surface waters and the percentage of melt pond
cover were the same in 1982 as in 2012, since no data were available for
1982. In general, the reduction of both MYI and FYI from 1982 to 2012 has
led to a ∼ 20 % decrease in the contribution of sea-ice
production to total INPP and an increase in water column contribution to
total INPP. The fraction of MYI has been reduced the most in the Laptev Sea,
where the total INPP has increased 53 % according to our model. In a
potential scenario in which the Arctic would be completely ice-free in
September (2050) and nutrients and the mixed layer depth would remain as in
2012, INPP could increase 60 % on average in the Eurasian Basin north of
78∘ N with the biggest increases occurring in the Barents
and Greenland sectors due to the reduction in MYI fraction and the
consequent increase in euphotic zone depth from 6–25 m to ∼ 50 m (Table 5).
Discussion
Importance of sea-ice productivity in the central Arctic Ocean
The role of sea-ice algae varies regionally and seasonally in the Arctic
Ocean (Dupont, 2012; Legendre et al., 1992). In
agreement with previous data by Gosselin et al. (1997)
for August 1994, sea-ice algae contributed up to 60 % to total NPP in
those parts of the central Arctic Ocean covered by MYI at the end of the
productive season in 2012. However, our contribution estimate is
conservative, since the sub-ice-algal aggregates formed by Melosira arctica that we observed
at all stations can contribute up to 90 % of total NPP at a local scale
(Fernández-Méndez et al., 2014). Due to their patchy
distribution and the difficulties in upscaling sub-ice-algal aggregates
contribution to NPP (Katlein et al., 2014a), they were not
included in the sea-ice NPP estimates presented in this study, although they
were observed at all stations.
Total mean INPP in mg C m-2 d-1 and in each
environment: melt ponds, sea ice and water in the central Arctic Ocean
during August and September 2012 as modelled with the CAOPP model. The grey
line depicts the average sea ice extent for each month. Note the different
scales in the different panels.
Fraction contribution of NPP in each environment (melt
ponds, sea ice and water column) to total NPP in the central Arctic during
August and September 2012 according to the upscaling performed using the
CAOPP model. The assumptions for key factors governing NPP are explained in
the “Methods” section. Note the different scales of the panels.
September mean total INPP for two runs of the CAOPP model
under contrasting sea-ice conditions: (a) sea-ice cover and incoming
irradiance as in 1982, (b) no-ice cover as predicted for 2050. Nutrient
concentrations and photosynthetic parameters as in September 2012.
In areas covered by FYI, sea-ice productivity contributed only 1–30 % to
total INPP (Fig. 12). MYI has different physical properties than FYI
(Lange et al., 2015; Spindler, 1994) and generally hosts
a higher algal biomass concentration (Werner et al., 2007). In
total, MYI and FYI together fixed 0.31 Tg C during August and September 2012,
without taking the patchily distributed under-ice and melt-pond-algal
aggregates into account (Fernández-Méndez et al.,
2014). This corresponds to 6 % of the total carbon fixed in the Eurasian
Basin north of 78∘ N in summer. This estimate is in
agreement with annual estimates from a biophysical model where sea-ice
primary production contributes 7.5 % to total annual PP for the whole
Arctic (Dupont, 2012).
However, our sea-ice INPP measurements (0.1–13 mg C m-2 d-1) in
August and September fell in the lower end of the range of previously
reported values from 2 decades earlier in the same area (0.5–310 mg C m-2 d-1,
Gosselin et al., 1997). This difference could be due to interannual variability, or to the loss of MYI, highlighting
the need for more NPP data from the central Arctic Ocean. The higher end of
the range in that study (AOS expedition, 1994) refers to sub-ice-algal
communities formed by sub-ice diatoms like Melosira arctica. This diatom was also found to
comprise much of the total-algal biomass during our expedition at station 7,
showing an INPP of 13–40 mg C m-2 d-1, similar to the AOS
expedition estimates (Fernández-Méndez et al.,
2014), and even more to total export flux. The rapid sea-ice melt in
July/August 2012 led to major sinking of fresh-algal biomass to the
seafloor of the Arctic basins (Boetius et al., 2013).
If we assume that the sinking algae had previously contributed to NPP at the
surface, and that they occurred throughout the entire Eurasian Basin north
of 78∘ N (1.8 × 1012 m2), the average 9 g C m-2
(range: 1–156 g C m-2) of sub-ice algae found deposited at the seafloor
would have contributed an additional 16 Tg C to INPP. From the nitrate
annual drawdown, we calculated a total carbon uptake of 17 ± 7 Tg C yr-1
in the Eurasian Basin north of 78∘ N. However,
this calculation does not take into account lateral scavenging of nutrients
by sub-ice algae such as Melosira arctica. Algal filaments hanging from the sea ice are
transported along the Transpolar drift, from the Siberian shelves where ice
is formed, to the central Arctic Ocean. Hence, they may have a better access
to nutrients than phytoplankton. This lateral scavenging of nutrients by the
sub-ice algae should be added to the nutrient drawdown calculated from
vertical profiles. Accordingly, when adding the nutrients taken up by the
sub-ice algae, the total new production could be 17 + 16 = 33 ± 7 Tg C yr-1
in the deep basins of the Eurasian Basin. The overall
contribution of sea-ice productivity would be 50 %. When including sub-ice
algal aggregations such as Melosira arctica filaments, the average total production of
33 Tg C yr-1 in the Eurasian Basin of the central Arctic Ocean is higher than
previously estimated (22 Tg C yr-1,
Codispoti et al., 2013). Therefore, studies that do not include sea-ice
productivity and sub-ice-algal aggregations may substantially underestimate
annual NPP in the central basins and other ice-covered regions
(Matrai and Apollonio, 2013).
Melt ponds contributed up to 4 % to total INPP, which is in the range of
previously reported estimates (< 1 to 10 %, Arrigo, 2014; Lee et al., 2012). Some melt ponds
also contain significant accumulations of algal biomass
(Fernández-Méndez et al., 2014), and hence might also become more
important for total Arctic PP as their coverage continues to increase
(Lee et al., 2011; Rösel and Kaleschke, 2012).
Some of the sea-ice algae trapped in melt ponds can rapidly adapt to the
changing conditions, as we observed in their high Chl a normalized maximum
photosynthetic rates compared to all other environments. Sea-ice algae are
low light adapted (Table 2; Cota, 1985) and show lower
photoinhibition in late summer (Michel et al., 1988;
Mundy et al., 2011). However, in June–July when they receive 90 % of the
annual light flux (Arndt and Nicolaus, 2014), they have their
peak in production and thus seem to adapt to higher light conditions. This
would have already been exported to the deep sea when we did our sampling in
August–September.
An important question concerns the ability of sea-ice algae to deal with
nutrient limitations. Integrated over the ice thickness and melt-pond depth,
nutrient concentrations were significantly lower than in the water column.
N : P molar ratios in sea ice were in general below Redfield (16 : 1) indicating
prior production by ice algae limited by nitrate (Maestrini et al., 1986; Smith et al., 1997). Melt-pond nutrient ratios were very variable (Table 3) highlighting the high
spatial heterogeneity of this environment. Very high N : Si ratios
(> 3) at some stations point towards silicate limitation as
well. Our nutrient addition experiment (Fig. 3d) suggests that sea-ice
algal communities can take up nutrients without increasing their biomass,
which is in agreement with previous findings that sea-ice diatoms can store
nutrients in their cytoplasma (Kamp
et al., 2011; Needoba and Harrison, 2004). This may be an important
physiological trait of sea-ice algae to cope with the oligotrophic
conditions of the deep central Arctic Ocean.
Light and nutrients as limiting factors
Seasonal light availability in the central Arctic Ocean limits
photosynthesis (Leu et al., 2011; Wassmann and
Reigstad, 2011). Our in situ measurements and upscaling results using the
CAOPP model clearly show the strong effect of sea-ice cover and season on
NPP (Figs. 4 and 5). The comparison between ice-free and ice-covered waters
of the Eurasian Basin reveals the indirect effect of sea ice through light
attenuation, limiting phytoplankton productivity in ice-covered waters. This
is noticeable at the end of the productive season (mid-September), north of
87∘ N, below MYI, where the euphotic zone is reduced to the
upper 7–15 m (Fig. 8a). Hence, years with an extensive ice melt as in 2012
host twice as much NPP in the Eurasian Basin as years with typical (previous
to the current trend of sea-ice extent decrease) sea-ice cover such as 1982 (Table 5).
Sea-ice algae are adapted to low light but can profit from increased light
availability in thin ice in late summer (Ik range from sea ice and melt
ponds 17–290 µmol photons m-2 s-1; Table 2). However, lack
of snow covering the ice at the beginning of the growth season can also be
detrimental for the sea-ice community due to photoinhibition and ice bottom
ablation (Juhl and Krembs, 2010; Lund-Hansen et
al., 2014; Mundy et al., 2011). In our study, evidence for photoinhibition
was mainly recorded in August on sea-ice algae trapped at the ice surface of
melt ponds where the irradiance was maximal (up to
279 µmol photons m-2 s-1;
Fig. 2; Table 3). However, the highest irradiance fluxes
in 2012 occurred in June (Arndt and Nicolaus, 2014), so the
potential for photoinhibition was higher in the earlier summer months,
especially if no snow was covering the ice. Phytoplankton sampled at 2–5 m
depth on the contrary showed almost no photoinhibition under irradiances up
to 420 µmol photons m-2 s-1, allowing them to potentially
benefit even more from an increase in irradiance reaching the water column.
Besides constraining the total amount of carbon that can be converted into
biomass during the productive season (Codispoti
et al., 2013), nutrients also play an important role since they determine
algal photoadaptation (Sakshaug and Slagstad, 1991). During our
cruise we identified three different nutrient regimes from integrated molar
ratios over the euphotic zone at the end of the productive season (Fig. 3;
Table 3). Along the ice margin in the Nansen Basin in August, silicate was
the most depleted nutrient with N : Si ratios as high as 3 (Fig. 3), which
were also reported for the year 1994 by Gosselin et al. (1997). This may be due to nitrate input from Atlantic waters
(Rudels, 2012), but little is known about upward nutrient mixing
rates. In the area adjacent to the Laptev Sea, silicate concentrations were
higher, probably due to the large seasonal riverine input
(Le Fouest et al., 2013), with N : Si ratios below 1 and N : P
ratios (1–9) below Redfield (16), indicating nitrate depletion. In late
September north of 85∘ N, all depth-integrated nutrient
concentrations were low (Table 3). This indicates a general nutrient and
light depletion typical of the end of the season (Wheeler et
al., 1997), partly due to the reduced depth of the euphotic zone (7–15 m).
When calculating the annual new production from nutrient drawdown for the
Eurasian Basin in 2012, estimates derived from nitrogen and phosphate yield
similar results (1–17 g C m-2 yr-1), which are in accordance with
the latest maximum net community production estimate for this region
(14 g C m-2 yr-1, n = 6; Codispoti et al.,
2013). Estimates derived from silicate, using a C : Si ratio of 7
(Brzezinski, 1985; Harrison et al., 1977), yield
annual NPP rates half of the estimates derived from nitrogen or phosphate,
suggesting that diatom production makes up for about 50 % of annual new
production, as biogenic silica is the main component of diatom frustules
(Martin-Jézéquel et al., 2000). Assuming that sea-ice
algae would contribute the most to silicate uptake during the growth season
and that they have a higher C : Si ratio as measured at the end of the season,
the contribution of diatoms to annual production would increase up to
70 %. However, diatoms typically have close to Redfield carbon to nutrient
ratios during the growing season when nutrients are available. The observed
N : Si ratios (Fig. 3) suggest that nitrate was limiting NPP in the Amundsen
Basin (from the Laptev Sea slope to the North Pole), but silicate was
limiting NPP in the Nansen Basin (close to the ice margin in the Kara and
Barents sectors) of the Eurasian Basin, that is influenced by Atlantic
waters. Thus, diatoms are probably limited in the Nansen Basin as soon as
the first spring bloom has consumed all the silicate in the mixed layer.
Indeed, the increase in NPP and biomass of the diatom Chaetoceros socialis in a sample from the
water below the ice at the ice margin, after silicate addition, supports
this idea (Figs. 5a, b, 6a, 7a).
Taking into account the export of sub-ice algae earlier in the season 2012
(average 9 g C m-2; Boetius et al., 2013) and
the C : Si molar ratio of diatoms (7), an average of 107 mmol Si m-2 had
already been removed from surface waters before August. Since sea-ice-algal
production starts earlier than phytoplankton productivity
(Søreide et al., 2006), sea-ice algae might
contribute to nutrient removal in surface waters at the beginning of the
season leaving reduced nutrient concentrations for the phytoplankton bloom.
However, since most of the sea ice in the central Arctic Ocean originates in
the shelf areas of the Eurasian Basin and is then transported by the
transpolar drift (Pfirman et al., 1997), the sub-ice algae
growing attached to the bottom of the ice might have access to the nutrients
mixed up on the shelves, upwelled at the shelf edge or ice edge earlier in
the season and to the surface nutrients of a wider area while they drift
with the ice (Carmack et al.,
2006; Cota et al., 1990; Fernández-Méndez et al., 2014; Syvertsen,
1991). This, together with the capability of ice algae to store nutrients (Kamp
et al., 2011), might provide them with an advantage over phytoplankton.
Besides the bottom-up control of primary production, there are other factors
limiting the amount of biomass present in the ice or the water column, such
as grazing. Arctic zooplankton and under-ice fauna are known to feed on
sea-ice algae and phytoplankton (Hop et
al., 2011; Søreide et al., 2006), transferring the fixed carbon to higher
trophic levels. In the central Arctic Ocean grazing has been reported to
consume 15 % of NPP (Olli et al., 2007). At the time of sampling, the
theoretical carbon demand of the dominant zooplankton and under-ice grazers
(Calanus spp. and the ice amphipod Apherusa glacialis) was on average 19 mg C m-2 d-1 in the
Eurasian Basin calculated from all stations investigated in this study
(David et al., 2015). This would correspond to more than
80 % of the mean daily NPP measured in ice-covered areas, indicating that
algal biomass could periodically be significantly controlled by grazers in
the central Arctic Ocean, especially at the end of the productive season.
The total POC export fluxes measured in August/September with short-time
sediment traps was 31 mg C m-2 d-1 on average
(Lalande et al., 2014), which is higher than the average INPP
measured in situ (24 mg C m-2 d-1). However, the carbon flux was
mainly composed of debris and the few algae observed in the sediment traps
using light microscopy were flagellates. According to seafloor observations
in 2012 in the same area, the largest amount of algal carbon export had
occurred already in June/July in 2012 during the main melting event, and was
due to the productivity of sub-ice-algal communities
(Boetius et al., 2013). These results suggest that the
system was predominantly heterotrophic at the time of sampling.
Using the CAOPP model and according to the light fluxes calculated by
Arndt and Nicolaus (2014), we estimate that 88 % of the
annual PP occurs between May and July, and only 12 % in August and September,
using late summer NPP rates and biomass measurements to extrapolate to the
earlier part of the season. The CAOPP model estimate matches very well with
our estimates based on in situ NPP in August and September, and with the
annual new production estimate based on nitrate drawdown, where we estimate
that 15 % of the annual PP occurs in late summer and the rest earlier in
the season. A more elaborate model taking into consideration quick changes
in photosynthetic parameters, grazing and seasonal shifts in standing stock
and nutrient availability (Palmer et al., 2014) would
be necessary to improve these estimates and to more accurately simulate
primary productivity under different scenarios. However, a better
understanding of the future of productivity in the central Arctic Ocean
foremost depends on better biological ground truth data for the entire season.
Effects of sea-ice reduction on primary production in the central Arctic Ocean
An increase in open-water NPP due to sea-ice retreat has already been
predicted by satellite derived and in situ data in the Eurasian Arctic
(Arrigo and van Dijken, 2011; Vetrov and Romankevich,
2014), especially in the Kara and Barents seas (Pabi et al.,
2008). However, changes in productivity in sea-ice and in water under the
ice cannot be detected by satellites. In September 2012, during our cruise,
sea-ice extent reached its lowest ever recorded (Parkinson
and Comiso, 2013). Another model study predicted enhanced productivity in
the East Siberian and Laptev seas due to the great summer cyclone
(Zhang et al., 2014). By comparing our results with previous
estimates from the Eurasian Basin and recent syntheses of all PP data
available (Codispoti et
al., 2013; Hill et al., 2013; Matrai et al., 2013), we tried to assess the
impact of sea-ice retreat on NPP. The sea-ice retreat in 2012 in the
Eurasian Basin increased the open-water area in August–September by 45 %
compared to earlier years. The INPP rates measured in the open waters of the
Laptev region (84 ± 38 mg C m-2 d-1) are higher than INPP
measurements from the same area using the same method in August 1995, when
most of the Laptev Sea area was ice covered
(21 ± 8 mg C m-2 d-1;
Grossmann and Gleitz, unpublished measurements from R/V Polarstern
expedition ARK XI/1). The average from satellite data from 2003 to 2012 for
open waters of this region (71 mg C m-2 d-1;
Vetrov and Romankevich, 2014) is also slightly lower than
our measurements during the sea-ice record minimum. No error ranges were
provided for these earlier observations; hence, it remains uncertain if they
indicate significant temporal changes.
As retreating sea ice leaves behind more open-water areas in summer,
different Arctic regions are expected to react differently to the increase
in irradiance received (Arrigo et al., 2008). To test this,
we removed the ice cover in our forcing input data from our CAOPP model – mimicking
predicted sea ice conditions for 2050 – and compared the results
from September with our 2012 results (Table 5; Figs. 11 and 13). Based on the
changes in light penetrating through the ice and assuming no change in
nutrient availability, total INPP for September would increase by 292 % in
the Greenland sector, 56 % in the Barents, 38 % in the Laptev and 23 %
in the Kara sector of the central Arctic Ocean north of 78∘ N
(Fig. 13; Table 5). These increases represent only 10–15 % of the seasonal
NPP in these regions according to our model and directly represent the
higher INPP in open waters. The relationship between sea ice decrease and
INPP increase also arises when comparing the model results of 1982 and 2012.
In this case, for the entire Eurasian Basin, a 45 % decrease in the ice
cover leads to a doubling in the September INPP. In the Amerasian Basin,
similar increases in phytoplankton annual production have been predicted
mainly due to earlier sea ice retreat (Arrigo et al., 2008; Kahru et al.,
2011). However, the loss of ice-attached biomass, such as sub-ice-algal
aggregates which are not taken into account in these calculations, might
counteract the increase in water column PP as sea ice disappears. The
regional variability of changes is due to different sea-ice coverage of the
different areas. However, sea-ice retreat will affect not only light
transmission but also water column stratification that might hinder
nutrient upwelling (Codispoti et al., 2013).
Depending on the future role of winds and sea-ice drift vs. stratification by
freshening and warming, nutrient availability in the euphotic zone could
change. For example, if ice formation occurs later in September, and if
winds would also increase and cause upwelling, a second productivity peak
might be observed at the end of the season (Ardyna et al.,
2014). In contrast, if stratification increases, less nutrients would be
available, resulting in a decrease in NPP for the month of September.
Sea-ice-algal productivity would likely increase and shift to earlier
periods of the year, and their rapid export from the melting of their
habitat in July and August will decrease nutrient availability
(Boetius et al., 2013; Lalande et al., 2009). The
phytoplankton community will probably shift from diatoms towards small
picoplankton due to the freshening of the upper layers
(Li et al., 2009), especially in the silicate limited
area of the Eurasian Basin, where small picoplankton is already present
(Kilias et al., 2013), and would be more nutrient efficient
at low silicate concentrations. This shift in the phytoplankton community
together with the disappearance of the sea-ice communities could have
potentially detrimental consequences for the Arctic food web (Bhatt et al., 2014).
Limitations and uncertainties of Arctic NPP estimates
The central Arctic Ocean remains one of the most challenging environments to
sample due to its remoteness and the year-round ice cover on top of its deep
basins. The majority of Arctic NPP estimates are from seasonally ice-free
waters, mainly shelves, sampled during the spring or summer months
(Hill et al., 2013; Matrai et al.,
2013). Ice-associated NPP has been widely neglected in previous Arctic PP
estimates, because it can not be assessed remotely via satellite-borne
sensors (Arrigo and van Dijken, 2011), and also due to
methodological and logistical problems to measure it in the field
(Matrai et al., 2013). Uncertainties of 2 orders of magnitude
in NPP estimates for the central Arctic Ocean reflect the high
spatial and temporal variability characteristic for this environment
(Tremblay et al., 2012). Thus, it remains difficult to
establish regionally representative baselines in Arctic NPP, to be able to
detect significant changes in productivity related to the ongoing sea-ice retreat.
This study provides summer in situ NPP data from the under-sampled Eurasian
Basin including water column, sea ice and melt pond that can be used to
validate ocean general circulation models predicting changes in Arctic PP
(Ferland et al., 2011; Tremblay et al., 2012).
Photosynthetic parameters derived from PI curves under realistic conditions
are important for modelling primary productivity
(Popova et al., 2012; Vancoppenolle et al., 2013). A
combination of in situ obtained photosynthetic parameters and a light
parameterization for light transmittance of sea ice (CAOPP model) enabled us
to estimate INPP for the entire Eurasian Basin, including ice-covered areas
(Fig. 11). Although the CAOPP model does not include nutrient information,
the PI curves were measured at the end of the season in nutrient limited
waters. Hence, using the same parameters to model PP earlier in the season,
when more nutrients are available, will underestimate productivity.
Photosynthetic parameters vary locally, seasonally and vertically as well as
horizontally in the water column and in the sea ice (Behrenfeld and Falkowski, 1997;
Duarte et al., 2015; Palmer et al., 2014). Therefore, the photosynthetic
parameters cover a wide range (Table 2) and are not well constrained. This
leads to 2 orders of magnitude difference between the minimum and the
maximum NPP calculated with the model. To constrain the results further,
more in situ measurements are needed to capture the regional and temporal
variability in photosynthetic parameters.
In addition, nitrate vs. ammonium uptake rates should be included in such
studies to estimate the importance of new versus regenerated production at
each period of the productive season (Dugdale and
Goering, 1967; Tremblay and Gagnon, 2009). With our approaches, the in situ
measurements in late summer were probably mainly measuring regenerated
production, while the annual estimates of production based on nutrient
drawdown is only taking into account the new production.
Another limitation of our upscaling using the CAOPP model is that the light
parameterization assumes a constant extinction coefficient in the water
column and is not spectrally resolved (Manes
and Gradinger, 2009; Palmer et al., 2011; Sakshaug and Slagstad, 1991). This
could lead to NPP overestimation in open-water coastal areas
(Alver et al., 2014). A recent INPP estimate for the
Arctic Ocean Basin including the Amerasian Basin based on NPP measurements
only in ice-free waters (0.4 Tg C month-1 (Arrigo et al., 2011; Bélanger et al., 2013)
is at the lower end of our estimated range for the water under the ice in
the Eurasian Basin in August (0.2–6.8 Tg C month-1), but suggests that
our model can give realistic estimates. Seasonality remains a critical issue
in the central Arctic Ocean since there are still no measurements of early
spring photosynthetic parameters from communities thriving in and under the
ice. Assessing the algal biomass below the ice using automated autonomous
systems such as ice tethered profiles (ITPs) that drift with the ice during
an entire year might be an important step forward to improve our
understanding of the annual cycle of primary production in the central basins (Laney et al., 2014).