Primary production on the coast and in Greenland fjords sustains important
local and sustenance fisheries. However, unprecedented melting of the
Greenland Ice Sheet (GrIS) is impacting the coastal ocean, and its effects
on fjord ecology remain understudied. It has been suggested that as glaciers
retreat, primary production regimes may be altered, rendering fjords less
productive. Here we investigate patterns of primary productivity in a
northeast Greenland fjord (Young Sound, 74∘ N), which receives run-off from
the GrIS via land-terminating glaciers. We measured size fractioned primary
production during the ice- free season along a spatial gradient of meltwater
influence. We found that, apart from a brief under-ice bloom during summer,
primary production remains low (between 50 and 200 mg C m-2 d-1) but steady throughout the ice-free season, even into the fall. Low
productivity is due to freshwater run-off from land-terminating glaciers
causing low light availability and strong vertical stratification limiting
nutrient availability. The former is caused by turbid river inputs in the
summer restricting phytoplankton biomass to the surface and away from the
nitracline. In the outer fjord where turbidity plays less of a role in light
limitation, phytoplankton biomass moves higher in the water column in the
fall due to the short day length as the sun angle decreases. Despite this,
plankton communities in this study were shown to be well adapted to low-light conditions, as evidenced by the low values of saturating irradiance
for primary production (5.8–67 µmol photons m-2 s-1).
With its low but consistent production across the growing season, Young
Sound offers an alternative picture to other more productive fjords which
have highly productive spring and late summer blooms and limited fall
production. However, patterns of primary productivity observed in Young
Sound are not only due to the influence from land-terminating glaciers but
are also consequences of the nutrient-depleted coastal boundary currents and
the shallow entrance sill, features which should also be considered when
generalizing about how primary production will be affected by glacier
retreat in the future.
Introduction
The coastal marine coastal ecosystems around Greenland are currently
experiencing rapid changes due to climate warming. The Greenland Ice Sheet
(GrIS) is melting at unprecedented rates
(Chen et al., 2006; Enderlin et al., 2014),
reaching a record melt extent in 2012, where 97 % of the total ice sheet
area displayed melting (Nghiem et al., 2012).
Subglacial discharge as well as ocean warming is causing increased calving
rates and the retreat of tidewater glaciers
(Howat et al., 2007; Rignot et al., 2010;
Straneo and Heimbach, 2013), though since 2009, 84 % of the rapid mass
loss of the GrIS is said to be due to increased surface run-off
(Enderlin et al., 2014). In southern Greenland freshwater
discharge into the surrounding coastal region has increased by almost 50 %
over just the last 2 decades (Bamber et al., 2012). This
reported freshening of fjords and coastal waters around Greenland
(Böning et al.,
2016; Sejr et al., 2017) has major consequences for the marine ecosystem as
well as for the inshore fisheries (Meire et al.,
2017). However, the magnitude and direction of these effects on the
different fjord ecosystems around Greenland are still largely unclear.
Studies from tidewater glacial fjords suggest that melting in late summer is
beneficial to pelagic primary production as subglacial discharge causes
upwelling at the glacier front (Hopwood et al., 2018;
Mortensen et al., 2013). This subsidizes plankton communities in the surface
layer with fresh nutrients while stratifying the water column
(Juul-Pedersen
et al., 2015; Krawczyk et al., 2015b; Meire et al., 2015, 2017). For
example, the tidewater glacial fjord, Godthåbsfjord, on the southwest
coast of Greenland features both a highly productive spring bloom (1743 mg C m-2 d-1; Juul-Pedersen et al., 2015) as well as a
second, prolonged, almost equally as productive late summer bloom (1383 mg C m-2 d-1; Juul-Pedersen et al., 2015) due to
nutrients subsidies derived from upwelling at the glacial front (Meire et
al., 2017). Alternatively, other glacial fjords without these upwelling
mechanisms report summer melting to introduce nutrient-poor freshwater,
which dilutes available nutrients in the upper stratified layers
(Reisdorph and Mathis, 2015).
Young Sound is a northeast Greenland fjord devoid of any glacial upwelling
mechanisms. It is a seasonally ice-covered fjord that is influenced by
meltwater from the GrIS via land-terminating glaciers
(Citterio et al., 2017). Thus at the onset of GrIS melt in the
summer a shallow freshwater lens is established throughout the fjord
(Bendtsen et al., 2007; Rysgaard
et al., 1999). In contrast, to Godthåbsfjord, Young Sound records a more
moderate spring bloom that is less than a quarter as productive (<300 mg C m-2 d-1) and has low
annual pelagic primary productivity (10.3 g C m-2 yr-1) attributed
to the short open-water period (Rysgaard
et al., 1999).
Previously, it was considered that primary production in Young Sound and
other Arctic fjords is proportional to the length of the open-water
period (Rysgaard et al., 1999) and that
future annual primary production across the Arctic will increase as the
ice-free season lengthens. However, recent research on the effects of
freshening in the Arctic suggest that an increase in freshwater inputs
intensifies stratification and impedes the vertical nutrient supply
counteracting the effects of a lengthening of the open-water season
(Bergeron
and Tremblay, 2014; Coupel et al., 2012, 2015; McLaughlin and Carmack, 2010;
Yun et al., 2016). Furthermore, freshwater input in the coastal Arctic also
brings large sediment loads and/or glacier flour, clouding the water column
and affecting the primary productivity via light limitation
(Wiktor et al., 1998). Murray et al. (2015) demonstrated a
strong relationship of water column turbidity and light attenuation in two
Greenland fjords (Godthåbsfjord and Young Sound) with potential
implications for primary production. Thus, it is likely that the light
environment for primary producers in Young Sound is affected by both sea ice
cover in the spring and run-off in the summer, and the vertical nutrient
supply in the fjord is limited by stratification due to freshwater input
that lacks a glacial upwelling mechanism.
As Young Sound is one of the locations of the Greenland Ecosystem Monitoring
programmes (see Christensen et al., 2017, and articles
therein), rates of marine primary productivity there have been reported in
several articles over the last 20 years
(e.g. Rysgaard et al.,
1999; Nielsen et al., 2007). This study, however, focuses on determining
spatio-temporal patterns during one open-water season with the aim of
investigating the impact of freshwater input on pelagic primary production
there. Based on previous findings we sought to determine if the low
productivity in Young Sound was caused by turbid freshwater input or the
short open-water period as previously hypothesized. We suggest that future
productivity in Young Sound will be constrained by increasing run-off, which
both reduces photic zone depth and increases stratification, rather than
reduced ice cover. Furthermore, we discuss how strong stratification and the
unique circulation of the fjord limits the renewal of nutrients to the
surface water, making this fjord extremely nutrient-depleted throughout the
productive season. Little is known about how freshwater run-off in
non-tidewater glacial fjords will affect primary productivity, even though
70 %–50 % of freshwater run-off from the Greenland Ice Sheet comes from land-terminating glaciers (Enderlin et al., 2014), making this
study important as glaciers continue to recede.
MethodsStudy area
The study was conducted in Young Sound, a high-Arctic fjord in northeast
Greenland (74.2–74.3∘ N, 19.7–21.9∘ W; Fig. 1). Young
Sound is 90 km long, 2 to 7 km wide, and covers an area of 390 km2. The
maximum depth of the fjord is 330 m with two shallow sills; the outermost
reaches ∼45 m depth and separates the deeper parts of
the fjord from the Greenland Sea. Sampling was conducted at four stations
located along a length section from the inner Tyroler fjord arm (Station 1)
to the shelf waters on the outer side of the sill (Station 4) (Fig. 1).
Glaciers cover ca. 33 % of the drainage area of the fjord and
land-terminating glaciers contribute 50 %–80 % of the annual freshwater
run-off with the highest contributions coming from the Tyroler, Lerbugt, and
Zackenberg rivers in the inner fjord
(Bendtsen et al., 2014; Citterio et
al., 2017).
Satellite imagery of Young Sound, northeast Greenland (a–c). Panel (a) shows the location of all CTD sampling stations (small dots) and the four main sampling stations (large dots; a), and (b–c) show the actual
ice and snow cover on 12 July 2014 (b) and 11 October 2014 (c). Fluorescence (d, e) salinity (f, g), and turbidity (h, i) contour plots
of the CTD transects in summer ((d, f, h) 8 August 2014) and fall ((e, g, i),
4 October 2014). (a–c) Contains modified Copernicus Sentinel data 2014 processed by Sentinel Hub.
The four stations were selected to represent a gradient of changing physical
conditions in Young Sound. Station 1 in the inner Tyroler fjord, represents
the inner fjord section and is impacted by run-off from the Tyroler River
(bottom depth: 128 m). Station 2 is located at the mouth of the Zackenberg
River and represents the central part of the fjord also affected by run-off
(bottom depth: 229 m). Station 3 lies midway out of the fjord and is also
the standard sampling station for the on-going time series and the location
of previous reports of primary productivity in Young Sound
(Nielsen et al., 2007;
Rysgaard et al., 1999; bottom depth: 163 m), and finally Station 4 was
positioned just outside of the fjord in the Greenland Sea and reflects shelf
conditions (Fig. 1, bottom depth: 229 m). Throughout the paper we refer to
the inner fjord stations 1 and 2 as “inner fjord” and to stations 3
and 4 as “outer fjord”. The stations 1, 2, 3, and 4 are also part of the
transect monitored by the Greenland Ecosystem Monitoring (GEM) MarineBasis
Zackenberg programme, in which they are named Tyro 05, YS 3.18, Standard
Station, and GH 05, respectively.
Sampling
The first sampling was conducted through the sea ice on 11 July 2014
(Julian day 192), through a hole in the ice at Station 3, when only the
central part of the fjord was still ice covered (Fig. 1). The ice broke up
in the central part on 15 July 2014 and the fjord was rendered ice-free
within 24 h. Subsequently, stations were sampled approximately every
10th day (from 17 July to 10 August; Julian days 198–222) and then again in
the fall period before new ice formation (4 September–6 October: Julian
days 247–279). Julian days were used during analyses but replaced by
calendar days in figures for simplicity.
After the sea ice break-up, sampling was carried out from the research
vessel Aage V. Jensen. A Seabird SBE 19+ conductivity–temperature–depth (CTD) profiler was deployed at every sampling
occasion and recorded vertical profiles of temperature, salinity,
chlorophyll a fluorescence (fluchl; Seapoint), turbidity (Seapoint;
FTU turbidity units), and photosynthetically active radiation (PAR; 4π sensor from
Biospherical; µmol m-2 s-1). Water was sampled using a mini
rosette with 12–1.7 L Niskin bottles from 6 standard depths (1, 10, 20,
30, 40, and 100 m) and one or two additional depths of fluorescence maximum
(DFM) when this did not overlap with one of the standard depths. The DFM was
approximated prior to every sampling using fluorescence profiles from a
Satlantic Free-falling Optical Profiler
(Murray et al., 2015).
Underwater light was recorded relative to a deck sensor.
Additionally, CTD profiles at approximately 25 stations (Fig. 1a) along the
length of the fjord were recorded on four separate occasions during the
season: 25 July (Julian day: 206), 8 August (220), 17 September
(260), and 4 October (277). For simplicity, only one date
from each season (summer and fall – see data analysis section below) was
chosen to be depicted in Fig. 1d–i, as the patterns were visibly similar among
dates within the same season.
Light attenuation was estimated from the CTD profiles using a two-phase
Weibull function as described in
Murray et al. (2015). This
technique ensured that the pronounced changes in turbidity with depth were
reflected in the light attenuation, which decreased with depth. The photic
depth (Zp) was calculated as the last depth from the surface with a
positive daily primary production, assuming a respiration equal to 5 %
of Pm. The mixed-layer depth (Zm) was regarded as the largest
density change below 5m. The stratification index (SI) was determined as the
difference between the density at 80 and 2 m as in
Tremblay et al. (2009).
Samples for nutrient determination were taken at all sampling depths in the
water column. Water was filtered with Whatman GF/F filters before being stored in previously
acid-washed 30 mL high-density polyethylene (HDPE) plastic bottles and frozen until analysis
(-18∘C). Analysis for inorganic nutrients (nitrite + nitrate,
orthophosphate, and silicate) were measured on a Smartchem200 (by AMS
Alliance) autoanalyser (for more detail, see
Paulsen et al., 2017). Profiles
of nitrate + nitrite (NOx) were completed using linear interpolation;
the nitracline (ZNOx) was determined by visual inspection of the
relationship of NOx and density, whereby we approximated the isopycnal
and the corresponding depth at which there is a consistently increasing
gradient of NOx above a 0.5 µM threshold (adapted from Omand and Mahadevan, 2015).
Chlorophyll a (Chl a) concentrations were measured in triplicates at each
sampling depth by filtering 250 mL of water from each sampling depth on 25 mm
Whatman GF/F filters (nominal pore size: 0.7 µm). Filters were then
extracted in 5 mL 96 % ethanol for 12–24 h and analysed on a Turner
Design fluorometer calibrated against a Chl a standard according to
Jespersen and Christoffersen (1987). The measurements
were done in triplicates. Chl a concentrations were used to calibrate the
chlorophyll a fluorescence (fluchl) profiles from the CTD. At each
sampling depth for chlorophyll a, a factor F was calculated as
F=fluchl/[chla]. The F factors were then linearly interpolated
between sampling depths and multiplied with fluchl in order to obtain a
calibrated depth profile of Chl a from 0 to 100 m. The depth of the deep
chlorophyll a maximum (DCM) was then calculated and compared to the DFM. The
DCM and DFM were positively correlated, and after accounting for outliers,
did not differ from a 1:1 relationship (p=0.721).
At 1 m and DFM depths Chl a was also determined on 10 µm polycarbonate
filters to estimate the contribution of different size fractions to
phytoplankton biomass. In order to integrate these fractions through the
entire water column, we applied the same fractions to each metre from the
surface and fluorescence maximum depths to the middle depth between these
two and the fractions at the DFM from there to the bottom of the profile
(100 m), after which we summed up the contribution of each fraction for the
whole water column. In the case of a third depth in between the surface and
DFM, the same process was taken between the surface and middle depth as
between surface and DFM. Note that the chlorophyll a from 8 September (Julian
day: 251) at Station 1 was only integrated to 40m due to an incomplete CTD
profile.
Primary production
Primary production (PP) was measured as 14C uptake
(Nielsen, 1952) according to
Markager
et al. (1999). Briefly, samples were collected at 1 m depth and at one or
two additional depths with a notable DFM (26 sampling dates in total). The
samples were brought to the laboratory and incubated for ca. 4 h at in situ temperature in an ICES incubator (Hydro-Bios, Germany) at 11 different light
intensities and in darkness. Flat 62 mL bottles (Nunc) were illuminated from
both sides with white LED light. The actual light intensity was measured
before and after each incubation with a 2π sensor (LI-COR 192UW quantum
sensor) at 16 positions in the incubator. The 14C bicarbonate (obtained
from DHI, Denmark) was added to an 800 mL sample and dispensed into the Nunc
bottles. In order to maximize sensitivity and save isotope, the addition of
isotope was adjusted according the chl a concentration and hence the expected
uptake and varied from 6 to 80 µCi per 800 mL of sample.
Furthermore, three Nunc bottles incubated at low, medium, and high light were
spiked with additional isotope, in order to measure production in three
different size fractions: >10µm, GF/F (nominal pore
size: 0.7 µm) to 10 µm, and <0.7µm, henceforth referred to as the “dissolved fraction”. After the incubation, the
total organic carbon production (TOC) was measured from a 10 mL sample taken
from these three Nunc bottles and added to glass vials in which 500 µL 1 N HCl was added and the vials were gently bubbled five times over 48 h
before the addition of 10 mL scintillation cocktail. The remaining ca. 52 mL in
the three spiked Nunc bottles were filtered through 10 µm pore
filters and the filtrate was collected. This filtrate and the content of
the other nine Nunc bottles were filtered through GF/F filters. All filters
were placed in plastic vials and acidified with 200 µL 1 N HCl. Then
the vials were allowed to stand for 24 h before they were closed and
stored in a freezer. Within 1–2 months all vials were counted in a Perkin
Elmer TriCarb 2910 TR scintillation counter. The 14C uptake was
calculated from the effect volume and the added amount of 14C, and
carbon fixation was then calculated from the dissolved inorganic carbon (DIC) concentration. The
dissolved fraction was calculated by subtracting the uptake on GF/F filters
from the TOC samples. PP fractions were integrated over 100 m in the same way
as the Chl a fractions.
The areal primary production was calculated according to
Lyngsgaard et al. (2014). From the carbon uptake on a
GF/F (nominal pore size: 0.7 µm) filter from each bottle, the
parameters in a P-I curve were estimated for each depth. These were divided
with the chl a concentration measured in a subsample from the same carboy
from where the water for primary production was collected in order to obtain
chlorophyll a specific parameters for each depth. These were then
extrapolated as described in Lyngsgaard et al. (2014)
and multiplied with the continuous chl a profile estimated from the
CTD profiles giving volume-specific P-I parameters for each depth (10 cm
intervals). Finally, the daily areal production was estimated by integrating
over 24 h for every metre down to 100 m depth. Note that the primary
production data from 8 September (Julian day: 251) at Station 1 was only
integrated to 40 m due to an incomplete CTD profile. The light intensity at
each depth was calculated from the light attenuation and the surface light
measured at the nearby Zackenberg Research Station as part of the GEM
programme.
Data analysis
Data have been divided into two seasons – summer and fall – for analyses.
Summer and fall seasons correspond to the sampling periods 1 July–10 August
(Julian days 192–222) and September 4–October 6 (Julian days 247–279), respectively, as water column properties underwent a strong transition
between these two periods primarily related to the inflow of freshwater, which ceases in fall (Fig. 1f–g); see the “Results” section). Data analysis was performed
using R (R Core Team, 2014) – employing the zoo
(Zeileis and Grothendieck, 2005) and RColorBrewer
packages – Ocean Data View (Schlitzer,
2016) and SAS® software.
Environmental time series
Annual incident PAR data and sea ice break-up (Fig. 2a), as well as
Zackenberg River discharge (Fig. 3c) were obtained from the GEM programme
website (http://g-e-m.dk, last access: 30 September 2019). Incident PAR (µmol s-1 m-2; Fig. 3a), measured as part of the GEM ClimateBasis programme, is recorded every 30 min, using a LI-COR quantum sensor located 2 m above terrain at the
Zackenberg Research Station, and wind velocity (Fig. 3b) is also logged as
part of the ClimateBasis programme. Sea ice break-up dates, monitored by the
MarinBasis programme, are estimated using both satellite images and a
time-lapse camera situated above the fjord at the approximate location of the
MarinBasis standard sampling station (Station 3). Zackenberg River discharge
(Q m s-1; Fig. 3c) is monitored by the GEM ClimateBasis programme.
Average (2004–2014) daily surface PAR (black line curve) in Young
Sound over 1 year (a). Black horizontal bars show ice cover for the years
2004–2014 (a). Actual PAR per year during the ice-free season (b). PAR data
are taken from the Greenland Ecosystem Monitoring (GEM) database, and ice
cover is estimated from daily photos taken from a camera situated on land
approximately looking down on Station 3 (NB ice break-up at other main
stations likely occurred on different dates)
Daily PAR (mol m-2 d-1; a), average wind velocity at 10 min intervals (m s-1; b), Zackenberg River discharge (Q m3 s-1; c), and accumulated discharge (km3; red line; c). Dashed lines
separate out the range of dates sampled in the summer and fall.
ResultsPhysical and chemical environment
In 2014, ice break-up in the main fjord occurred on 27 July (Fig. 2a); thus
total annual surface PAR during the open water was lower than the previous 9 years (Fig. 2a). Despite the late break-up in 2014, the overall trend is
toward an earlier break-up. Based on sea ice data from 1950 to 2014, ice breaks
up 0.15 d yr-1 earlier corresponding to 1.2 d earlier in a
10-year period (Middelbo et al., 2019), which adds 2.6 % per
decade to the annual amount of PAR in the water column. There is a 17 times
difference (39.2 versus 2.36 mol m-2 d-1) in daily irradiance
between July and October, so it is clear from Fig. 2 that the date for ice
break-up is much more important for determining light availability for
marine primary producers than the date for sea ice formation in autumn. It
is important to note however, that due to continental warming, ice broke up
earlier in the inner part of the Tyroler fjord, approximately in mid-June,
based on estimates from satellite images. Thus, a square metre of surface
water in the inner part of the fjord receives almost twice (1.87) the
annual irradiance compared to the outer fjord.
Discharge of the Zackenberg River started on 4 June (Julian day: 155),
peaked on 16 August (228) with the outburst flood from a glacial lake,
reaching 169 m3 s-1, and ended on 28 September (271) in 2014 (Fig. 3c). Total accumulated discharge of the Zackenberg River in 2014 was 0.22 km3, within the normal range of annual discharge (0.13–0.34 km3; Citterio et al., 2017).
CTD transects (Fig. 1d–i) offer a coarse seasonal view of the extremes in
physical conditions during the ice-free period in the fjord. Shallow
salinity stratification was consistent across the horizontal gradient of the
fjord even to the outermost station in the Greenland Sea in the summer
(Fig. 1f). In the fall, the upper 30 m was relatively well mixed but a
pycnocline was still present around 30 m in the fjord while, outside the
fjord stratification was disrupted by deep mixing (Fig. 1f). Turbidity was
most pronounced throughout the upper water column at the innermost stations
due to run-off from the Tyroler River in the summer time with another
pronounced increase in turbidity in stations just past the outflow of the
Zackenberg River (Fig. 1h). In the fall, after run-off from the rivers
ceased, turbidity was lower and more homogenous throughout the upper water
column across the entire transect. An area with high turbidity was observed
on the outer coast, which was likely related to resuspension of sediment due
to large ocean swells hitting the shallow area around the outer sill and the
small island there (Fig. 1i). The phytoplankton biomass, as described by
chlorophyll a fluorescence, showed low values both at the surface and at depth
in the water column. Fluorescence was concentrated higher up in the water
column in the innermost stations, but the peak deepened moving out the
fjord (Fig. 1d). However, variation in DCM during the summer in the inner
fjord, does not allow for detection of any trends across stations (Table 1;
summer mean ± SD DCM at main sampling stations: 28±8.2 m). In
the fall, fluorescence was more homogenous throughout the upper water column
(Fig. 1e), and the DCM moved higher up in the water column in all stations
(fall mean ± SD DCM at main sampling stations: 18±11) except
for the outermost stations, which were subject to deep mixing (DCM: 69 m)
from high winds that took place at the end of the September (Fig. 3b). Further inspection of profiles suggests that fluorescence profiles may not
be the best parameter to judge vertical distribution of biomass; rather, it
is best to consider the profiles of chlorophyll a due to the systematic
variations in fluorescence per unit of chlorophyll a (see Fig. S2 in the Supplement and results
below).
Summary table. Zp: photic depth (m); Turb Z0: surface turbidity (FTU); I0: surface irradiance (µmol photon m-2 s-1); Zm: mixed-layer depth (m); SI: stratification
index; ZNOx: nitracline depth (m); DCM: depth of chlorophyll a
maximum (m); Chl: areal chlorophyll a (mg chl a m-2); PP: areal
primary production (mg C m-2 d-1).
In general, nutrient concentrations increased with depth. Nitrate + nitrite (NOx) concentrations increased from a mean ± SD surface
value of 0.15±0.27 to 4.32±1.21µM at 100 m
depth. Phosphate concentrations increased slightly from 0.38±0.30µM at the surface to 0.80±0.35µM at 100 m depth,
though this increase is not significant, indicating that phosphorous in not
used up at the surface and thus not deficient. Indeed, the average NOx-to-phosphate ratio (N:P) for the data set is 2.2±2.6 (mean ± SD), much below the Redfield value of 16; as such, communities are deficient
in nitrogen with phosphorous in surplus (Fig. S1). Silicate increased from
4.35±1.88 to 6.87±0.75µM at 100 m depth,
though at the surface silicate concentrations are variable and range from
0.69 to 10.0 µM, due to high concentrations of silicate (range: 3–40 µM) in the meltwater run-off (Paulsen et al., 2017).
As such, the NOx to silicate ratio (N:Si) for the data set (mean ± SD: 0.28±0.30) is variable but in general much lower than
the Redfield value of 1.07 (Fig. S1). While the rivers enrich the surface
water with silicate, NOx (range: 0.06–1.7 µM) and phosphate
(0.08–0.6 µM) concentrations in river run-off are generally in the
range of surface water concentrations for these nutrients. For further
details of nutrient profiles in the water column and run-off, see Fig. S1 in
Paulsen et al. (2017). The
average nitracline (ZNOx) in the data set is 29±9.5 m (mean ± SD) and is not different among stations or between seasons (t test: p=0.07). However, there was a tendency for a shallower ZNOx in the
summer, especially in the innermost Station 1. Due to high turbidity in
Station 1 in the summer, biomass was concentrated higher up in the water
column and thus had not depleted nitrate down as far (Table 1).
The mixed-layer depth (Zm) increased over the season at all stations
(Fig. 4a; Table 1) from a mean (± SD) of 9.3±4.6 m in the
summer to 27.1±5.5 m in the fall excluding the last sampling date of
Station 4, which had an unusually deep Zm (86 m). The SI was not significantly different between seasons (mean ± SD SI in
summer and fall, respectively: 6.3±3.5 and 3.4±0.9 kg m-3), though it did decline to 0.68 in Station 4 on the last sampling
day on 4 October related to deep wind mixing from the previous days'
storm.
Mixed-layer depth (Zm; a), photic depth (Zp; b), and the
ratio between the two (Zp:Zm) over the length of the
sampling season at each station.
Photic depth (Zp) at Station 1 increased steadily (from 16.1 to 38.3 m)
over the season while in Station 2, Zp increased rapidly in the
beginning of the season and then only slightly toward the end (Fig. 4b;
Table 1). There was no change in Zp in Station 3 throughout the
season (mean ± SD: 26.5±2.5 m), while photic depth in Station 4 had the opposite pattern of Station 1, decreasing over the growing season
(from 38.4 to 18.9 m; Fig. 4b; Table 1), though this trend may be confounded
by a resuspension event related to large ocean swells late in the season. As
expected, there was a negative relationship of photic depth with average
surface (0–5 m) turbidity (Zp=24.4esurf.turb.⋅-3.99; R2=0.48; p<0.0001) as in Murray et al. (2015).
The ratio of Zp:Zm indicates whether a productive DCM is possible as
it requires enough light to be available below the pycnocline. The trend was
similar among stations (Fig. 4c) with increasing values from ice break-up
reaching a maximum at the very end of July and beginning of August (Julian
days 208–222) and then decreased to values of 1 or less beginning in early
September (Julian day 247) as the photic and mixing depths met. Thus, in
most cases, there was sufficient light below the pycnocline to allow for a
productive DCM. Similarly, the ratio of the photic depth to the nitracline
(Zp:ZNOx) was 1.1±0.6 (mean ± SD) throughout
the season, indicating that across seasons the depth of the nitracline was
driven by light and thus phytoplankton uptake of nitrate, again allowing for
a productive DCM. On the other hand, the ratio of Zm:ZNOx, which
can indicate the potential of nutrient replenishment in the mixed layer, was
significantly different between seasons (t test: p<0.001) with a
mean of 0.37±0.17 in the summer and 0.99±0.4 in the fall;
thus, implying that the mixing depth in the summer was much shallower than
the depth where nutrients are available, but that in the fall mixing depths
were sufficient to bring nutrients into the mixed layer.
Chlorophyll a and primary production
Water column chl a varied among stations and along the season (Fig. 5a; Table 1), with the highest integrated values found at the outermost stations 3 and
4 (mean ± SD: 34.2±16.1 mg chl a m-2). Values at stations 1
and 2 were significantly lower (mean ± SD: 17.4±6.9 mg chl a m-2; paired t test; p=0.002) throughout the summer and fall months.
At stations 2, 3, and 4, there was a trend of primarily large cell size
earlier in the season, whereas later in the season small cells dominated. At
Station 1, small cells dominated throughout the season (Fig. 5a).
Integrated chlorophyll a (mg C m-2; a) and primary production
(mg C m-2 d-1; b) for each fraction over the length of
the sampling season at each station. Note: data from Station 1 on 8 September only
integrated to 40 m.
The average areal primary production in the study was 92 mg C m-2 d-1 ranging from 10.6 to 628 mg C m-2 d-1 (Table 1; Figs. 5b and 6a). However, areal production showed little pattern seasonally or
spatially, apart from evidence of an under-ice bloom at Station 3 on 11 July
(Julian day 192) which reached 628 mg C m-2 d-1 (Table 1). Other notable features are the high primary production on the first
sampling date in Station 1 (207 mg C m-2 d-1; Table 1) despite
low chlorophyll a biomass (12.5 mg chl a m-2), whereas Station 4 showed a
small peak in primary productivity in late summer (155 mg C m-2 d-1; Table 1) in accordance with the peak in chlorophyll a biomass.
Only 6 of the 26 primary production estimates were above 100 mg C m-2 d-1, 5 of which were before the 10 August (Julian day: 222),
which suggests a tendency toward a higher production over the first
approximately 4 weeks of the ice-free period. However, there was no
difference observed between areal primary production in summer and fall
(summer mean ± SD: 83.8±57.3 mg C m-2 d-1 – excluding under-ice bloom; fall: 60.4±27.3 mg C m-2 d-1; t test: p>0.05). There is some
indication in stations 1, 2, and 3 for a decrease in primary production in
the summer season and recovery to similar rates in the fall, while Station 4
shows an opposite trend peaking in late summer and falling back off in the
fall. But low sample size prohibits statistical analysis of these trends.
Similarly, it is difficult to observe consistent patterns of fractioned
primary production observed among stations or throughout the season (Fig. 5b).
Areal primary production (mg C m-2 d-1; a) and specific
areal primary production (mg C mg chl a-1 d-1; b) over the
length of the sampling season at each station.
While patterns in areal primary production spatially and over the season are
difficult to discern, there are some recognizable patterns when looking at
the depth distribution of chlorophyll a and primary production (Figs. S2 and S3, respectively). These patterns are summarized in Fig. 7 where we distinguish
between inner and outer fjord patterns. Inner fjord stations such as stations 1 and 2 experienced high turbidity (Table 1) and hence greater light
attenuation in the surface. In these stations carbon fixation was confined
to the upper 5 m. Indeed, > 50 % of the total water
column primary production took place above 4 m in Station 1 in the
summer. On the other hand, stations 3 and 4 exhibit maximum production at
depth and 50 % of areal production is reached further down around 20 m in the summer months. We observed opposite patterns in the fall,
however; production is concentrated further down around 12–15 m in the
inner fjord stations compared to in the summer, while production moves
further up in the water column in the outer fjord stations in the fall (Fig. S2).
Conceptual diagram of the water column profiles for density, PAR,
nitrate + nitrite ([NOx]) and chlorophyll a in the inner fjord (a) and
outer fjord (b) during summer and fall in Young Sound, where Zm is
the mixed-layer depth, Zp is the photic depth, and ZNOx is the
nitracline.
Photosynthetic parameters
The chlorophyll a standardized maximum carbon uptake (PmB) varied
from 0.072 to 2.62 g C g-1 chl a h-1 with a mean (± SD)
value of 0.66±0.56 g C g-1 chl a h-1. High values, above
2 g C g-1 chl a h-1, were observed only in the beginning of the
growing season (i.e. before the end of July; Table S1 in the Supplement). Values from 1 m
depth were higher than the values from the DFM for 18 out of 20 d, but
the difference was not significant (paired t test, p=0.19). The light
utilization efficiency value (αB) varied from 0.67 to 48 g C g-1 chl a mol-1 photons m2 with a mean (± SD) value
of 8.72±8.52 g C g-1 chl a mol-1 photons m2, and no
difference was detected between depths (Table S1). The Ik values
(PmB/αB) express the light level that is saturating
for carbon fixation. Values were low, ranging from 5.8 to 67 µmol photons m-2 s-1 with a mean (± SD) value of 26±15µmol photons m-2 s-1. The values at 1m were slightly
higher (29 versus 26 µmol photons m-2 s-1), but the
difference was not significant. Some high values were seen from mid-July to
mid-August at 1 m, but overall there was no detectable pattern in the values
(Table S1).
DiscussionAreal patterns of primary production indicate low-light-adapted communities
This study contributes significantly to the sparse knowledge of spatial and
temporal patterns of primary productivity in northeast Greenland fjord
system, and expands on previous studies of primary productivity in Young
Sound, confirming that it is indeed a low-productivity fjord throughout the
open-water season. Primary production rates in this data set the fall within
the range of values measured previously in Young Sound by Rysgaard et al. (1999) (this data set: 206.8–10.8 mg C m-2 d-1 (Figs. 5b
and 6a; Table 1); Rysgaard et al. (1999): 277.9–4.2 mg C m-2 d-1) with the exception of the high rates of primary production
measured under the ice at Station 3 on 11 July. However, these rates are
much lower compared to other Arctic fjords (Simo-Matchim et al.,
2016 – compiled literature review within).
Low productivity in Young Sound was initially considered to be a consequence
of the late break-up of sea ice, thus resulting in a short productive season
(Nielsen et al., 2007; Rysgaard et al., 1999). Earlier studies also showed generally low rates of
primary production under the ice in Young Sound (28–122.5 mg C m-2 d-1) due to thick snow cover on ice creating poor light conditions (Glud et al., 2007; Nielsen et al., 2007;
Rysgaard et al., 2001). Our study, however, reports an under-ice primary
production rate of 628 mg C m-2 d-1 (Figs. 5b and 6a; Table 1). These high rates of primary production are short-lived, however, and
correspond to the days just before the sea ice breaks up when ice has
thinned, snow cover has melted away, and more light can reach the water
column (Glud et al., 2007; Rysgaard et al., 2001).
This peak in primary production likely consumes much of the available
nutrients; indeed, NOx concentrations between 1 and 30 m were less than
1 µM during this peak. Nielsen et al. (2007) also report low NOx
concentrations below the ice already in June (<2µM in the
upper 30 m of the water column).
Due to general low productivity, low temporal resolution, and high
variability in the data, it is difficult to discern any consistent seasonal
patterns of primary production in the stations sampled (Figs. 5b and 6) in
spite of very clear environmental changes, most notably in the influence
from run-off from land changing stratification patterns and the change in
day length (Fig. 4). However, interesting, steady rates of primary
productivity are documented well into the fall, and while the rates are
still low, they are comparable to that of the summer season (Table 1). In
Young Sound, we do not notice a traditional spike in primary productivity in
the late summer or fall – often termed a “fall bloom” and typical in many
high-latitude systems (Wassmann and Reigstad, 2011); rather, primary productivity in September through to early October remains steady and rates
are not different to those measured during July and August, even though
daily PAR in the fall is less than a quarter of the summer PAR due to
shorter day lengths (Fig. 3a). In Godthåbsfjord in west Greenland, when
daily PAR decreases to a quarter of the summer PAR in November, primary
production rates also decrease to less than a quarter of summer rates
(Juul-Pedersen et al., 2015). Simo-Matchim et al. (2016), also
report generally lower rates of primary productivity in Arctic fjords in the
late fall, thus making our finding significant. This could indicate that
phytoplankton in Young Sound are so well adapted to low-light conditions
that it allows for a low but steady rate of primary productivity well
throughout the fall when some nutrients are able to be mixed into the photic
zone.
In this study, we measured primary production using P-I curves (Table S1),
which give some additional indications of photosynthetic performance which
we can use to compare across systems. The Ik parameter, or the light
intensity at which photosynthesis is initially saturated, ranged from 6 to 67
(mean ± SD: 26±15) µmol photons m-2 s-1,
which is rather low compared to other studies carried out in the Arctic
(Gallegos et al., 1983; Fernández-Méndez et al., 2015; Jensen et al., 1999;
Armelle Simo-Matchim, personal communication, 2018). Values from those studies range from
18.9 to 533 µmol photons m-2 s-1, with an average of 97.1 µmol photons m-2 s-1, an order of magnitude higher than the
values we find in this study. Even in the central Arctic Ocean where
ice cover heavily limits light availability, Ik values average 293 in
August and 15 µmol photons m-2 s-1 in September
(Fernández-Méndez et al.,
2015). River-influenced Labrador fjords (Simo-Matchim et al., 2016) also show
higher values of 78.6–203 µmol photons m-2 s-1
(Armelle Simo-Matchim, personal communication, 2018). The low Ik values we find in
this study are the main evidence that we have to argue that plankton
communities in Young Sound are especially adapted to low-light conditions,
thus giving them an advantage during summer when turbidity is high and
during fall with so little incident irradiance.
Low-light adaption is also evidenced by the smaller cells that dominated in
the inner fjord throughout the season (Fig. 5). Smaller cells have no cell
walls and more efficient pigment packaging that give them a higher affinity
to light (Raven, 1998; Taguchi, 1976). Plastidial
16S rRNA gene sequence data and flow cytometry cell counts confirm that
picophytoplankton dominate biomass in much of the inner fjord (unpublished
data) with freshwater cyanobacteria comprising a large fraction of the
phytoplankton community there (Paulsen et al., 2017).
Surprisingly the picophytoplankton community was not dominated by the green
algae Micromonas sp. as is often found in other Arctic regions
(Lovejoy et al., 2007; Terrado et al., 2011); rather, the data suggests the picogroup was comprised of a mixture of
freshwater cyanobacteria, diatoms, and different green algae, as in
Sørensen et al. (2012). Larger cells were more
present in the summer in the outer fjord (Fig. 5) and are dominated by large
diatoms and also dinoflagellates (Krawczyk et al., 2015a), but
community diversity was higher in the inner fjord (unpublished data). A
higher diversity of smaller cell sizes contributes a competitive edge when
it comes to light utilization efficiency
(Schwaderer et al., 2011).
Finally, another indication of low-light adaptation is seen in the specific
primary production; that is the areal primary production per unit
chlorophyll (mg C mg chl a-1 d-1; Fig. 6b). In general, seasonal
patterns are similar to the ones we see in areal primary production (Fig. 6a); however, it is notable that in the summer in the inner fjord (Station 1), there are much higher rates of primary production per unit Chl a than in
Station 3 where the highest rate of areal production took place under the
ice on the first sampling day. And, with the exception of the high under-ice
production in Station 3, in general stations 1 and 2 in the inner fjord have
higher rates of specific primary production than the outer fjord stations.
Thus, these smaller-cell-sized communities have functionally adapted to
their low-light environment and are more efficient per unit chlorophyll than
outer fjord communities.
Freshwater input determines vertical patterns in primary production
Light is limiting in Young Sound during the spring and early summer due to
the presence of sea ice, but light limitation during the summer after the
ice breaks up can be linked to the turbidity of the water column induced by
meltwater run-off (Murray et
al., 2015), which gradually increases throughout the summer and ceases in
the fall (Fig. 3c). This affect was most noticeable at Station 1, which is
strongly affected by run-off from the Tyrol River, where the photic depth
deepened from 16 m in the summer to 38 m in the fall (Fig. 4b). In the fall
however, light is limited due to a decrease in daily PAR; and sun angles are
much lower than in the summer. Figure 7 illustrates this difference, where PAR
is attenuated rapidly at the surface in the summer due to the turbid surface
layer in the inner fjord, whereas in the fall, surface PAR starts off lower but is attenuated slower when there is less turbidity in the upper water
column. A part from some variation, the nitracline, however, remained very
consistent across stations and seasons at approximately 30 m depth, just
below the average photic depth for all stations (Fig. 7).
The effects of this changing light environment are seen in the distribution
of biomass and carbon fixation in the water column. In the outer fjord
during the summer, primary productivity peaks closer to the nitracline
exhibiting a classic DCM as would be expected in an oligotrophic system,
whereas during the fall, productivity moves higher up in the water column due
to short day length. However, in the turbid inner fjord during the summer,
the production takes place higher up in the water column as is the case in a
typical estuary; however, during the fall the production actually moves to an
intermediate depth (12–15 m) in the water column. Hence, the distribution of
biomass and productivity in the water column is indicative of a dual light- and nutrient-deficient system. Phytoplankton face a constant trade-off: in
summer, phytoplankton can still grow – though with low rates – in the
deeper layers bordering the nitracline. However, in the fall light is low
and days short, forcing phytoplankton closer to the surface where light
limitation is less pronounced but nutrients are strongly limiting, unless
they are adapted to low light, in which case they can afford to be further
down in the water column and closer to nutrients.
Nutrient availability is dependent on circulation inside and outside the fjord
Nitrate availability in the photic zone is determined both by winter surface
concentrations prior the spring bloom and vertical mixing processes that
replenish nitrate to the photic zone during the summer and autumn. In Young
Sound, NOx concentrations in February in surface water are around 3 µM (Rysgaard et al., 1999). Outside
the fjords on the East Greenland Shelf in April, nitrate concentrations are
only 3–5 µM (Michel et al., 2015),
and maximum concentrations in the summer inside and outside the fjord at
depth are around 4–8 µM (this study; Paulsen et al.,
2017). As a comparison, NOx concentrations during winter in the surface
waters of Godthåbsfjord (west Greenland) reach up to 12.5 µM (Juul-Pedersen et al., 2015), while concentrations just below
the photic zone can be around 10 µM in Disko Bay
(Sejr et al., 2007). So, the location of Young Sound on an
“outflow” shelf dominated by surface water already depleted in nutrients
(Michel et al., 2015) is clearly an important component contributing to
limiting nutrients within the fjord.
A lack of mixing processes during summer also has limited capacity to
replenish nitrate to the photic zone in Young Sound. First, the maximum
tidal amplitude in Young Sound is only 0.8 m (Bendtsen et
al., 2007), which is low compared to the tidal amplitude in the more
productive Godthåbsfjord of up to 5 m (Blicher et al.,
2013). Additionally, in Young Sound, river discharge throughout the summer
creates a surface lens of freshwater and hence a mixed-layer depth shallower
than 10 m, but in the fall when river run-off ceases, the mixed-layer depth
deepens to approximately 30 m where the nitracline also sits (Fig. 7). In
that period, nutrients may be mixed up via estuarine mixing and internal
waves generated at the sill (Boone et al.,
2018; Cottier et al., 2010) bringing up some nutrients, which may account
for the low but significant rates of primary production during that time
period. Though patterns of stratification are very different between seasons, the water column remains stratified well into the fall. There was some
increase in wind speed, as well as a large storm towards the end of the
season (Fig. 3b). The stratification index in fall tended to be slightly
lower than in the summer though not significantly different, except in
Station 4 on the last sampling day in October after the storm had passed where
the value was much lower (Table 1). SI values in this study are 2–3 times
higher than SI values calculated in the same way in Labrador fjords also
influenced by river run-off (Simo-Matchim et al., 2016).
This suggests that in the absence of mechanical mixing, any increase in the
stratification index due to freshening could reduce vertical mixing even
further.
Perspectives
Ice break-up occurs much later in Young Sound than in other well-studied
west Greenland fjords (e.g. Godthåbsfjord; Disko Bay) limiting light
availability in the water column, which is why it has been suggested that an
increased length of open-water season would benefit primary production in
Young Sound (Glud et al., 2007;
Rysgaard et al., 1999). However, current trends in ice break-up dates show
that sea ice is breaking up 1.2 d per decade in Young Sound, amounting to
a less than a 1 % addition of surface PAR to the annual open-water PAR
budget. Later ice formation in the fall will also not likely increase the
annual PAR as the incident irradiance in the fall is already low; however,
enhanced wind mixing from storms due to later ice formation could increase
the resupply nutrients to the photic zone in the fall, though it is still
unlikely that changing ice conditions will be a strong driver for change in
the future, even if there is an increase in the open-water season. With
ongoing climate change, we expect an increase and earlier onset of run-off
causing the turbidity and the strong stratification that we see in this
study. Mernild et al. (2008) model an increase of up to 5 times
the discharge from the Zackenberg drainage basin in 50 years time,
which is likely to influence the freshwater content of the fjord and coastal
waters.
On the other hand, there is no evidence yet of increased discharge in Young
Sound, and there has been no change in salinity in the upper 30 m of the
water column over the last 13 years (Sejr et al., 2017), as the
estuarine circulation in Young Sound results in a short residence time of
∼1 month for fresh surface waters inside the fjord
(Bendtsen et al., 2014). Instead, Sejr et al. (2017) report increased freshening of the 30–50 m layer of the water column
inside the fjord over the last 13 years, which they attribute to exchange of
freshening shelf waters inside the fjords. It is speculated that shelf
waters are freshening due to the accumulation of run-off from the numerous
fjords along the northeast coast of Greenland in the East Greenland Current
(Bendtsen et
al., 2014; Sejr et al., 2017), or changes could be related to the melting of sea
ice during summer (Boone et al.,
2018). The import of the freshened waters, however, will likely not provide
the system with any extra nutrients, as east Greenland coastal waters are
rather nutrient-depleted (Michel et al.,
2015). Furthermore, there is little exchange in Young Sound in water deeper
than 50 m, due to the shallow entrance sill (45 m;
Bendtsen et al., 2007), though there is a decreasing
trend in salinity in bottom water inside the fjord, likely due to the
increasing freshwater content inside the fjord
(Sejr et al., 2017) which is mixed
down to deeper depths via turbulent diffusion (Bendtsen et
al., 2007).
Freshening in other parts of the Arctic ocean has caused a deepening
halocline resulting in a deepening nitracline and chlorophyll a maximum
(McLaughlin and Carmack, 2010). It has been modelled that
increased run-off in Young Sound would not necessarily influence the mixed-layer depth (Bendtsen et al., 2014). However,
it would decrease the surface salinity and increase the freshwater content,
thereby increasing the density difference between the upper and lower water
column – increasing the stratification index and the amount of energy
required for mixing and hence nutrient replenishment to surface layers in
the fall. Studies from a tidewater glacier fjord (Godthåbsfjord) in
Greenland report that meltwater, while it creates strong stratification,
actually enhances primary productivity due to the upwelling driven by
subglacial discharge bringing up nutrients throughout the summer melt
period. Stratification induced by the meltwater actually stabilizes the
water column replete with nutrients, sustaining high primary productivity
throughout the summer (Juul-Pedersen et
al., 2015; Meire et al., 2017). Consequently, a mechanism has been suggested
whereby fjords receiving run-off from rivers or land-terminating glaciers
lack the mixing and nutrient replenishment provided by tidewater glaciers,
resulting in lower-productivity fjords (Meire et
al., 2017). On the other hand, primary production rates in river-influenced
Labrador fjords are similar to those found in Godthåbsfjord despite
their being ice covered throughout the spring
(Simo-Matchim et al., 2016).
Therefore, it is difficult to make generalizations about glacial fjords
across the Arctic. It is likely an interplay between ice cover and timing of
ice break-up, freshwater input (either locally produced or allochthonous to
the system), the degree of stratification and mixing properties (including tidal
mixing, which can vary dramatically around the coast of Greenland), coastal
boundary currents, and the depth of entrance sills determining exchange of water
masses within a fjord, as well as glacier type (marine vs. land-terminating)
that determine the overall circulation and productivity of a fjord.
Conclusions
Seasonal observations from this high-Arctic fjord show a system that is
characterized by an isolated surface layer due to run-off from
land-terminating glaciers that exhibits a very shallow mixed layer in the
summer and a deeper mixed layer in the fall (Fig. 7). There is a spatial
gradient moving out the fjord, whereby light is attenuated rapidly in the
inner fjord during the summer due to turbidity introduced by rivers (Fig. 7a); a majority of primary production takes place in the upper metres. In
the fall, a shallow DCM forms in the inner fjord despite a low-light
environment, likely due to low-light adaptivity of the phytoplankton. On the
other hand, the outer fjord exhibits a more traditional DCM in the summer
where there is sufficient light for phytoplankton to grow as close to the
nitracline as possible – nitrate is depleted down to 30 m throughout the
growing season. In the fall the DCM moves to the surface away from the
nitracline in the outer fjord, due to low sun angle and limited light
availability. While an extremely unproductive fjord, minimal productivity is
maintained in Young Sound throughout the summer and the fall through an
interplay and trade-off between (a) low-light availability, which in the
spring is caused by the presence of sea ice, in the summer by river-induced
turbidity, and in the fall due to short day length and low sun angle, and (b) low nutrient availability, due to the inherently low nutrient concentrations
and depletion of nutrients early on in the season under the ice combined
with intense stratification throughout the season that allows for little
vertical mixing of the water column. Thus, we conclude that future
productivity in Young Sound will likely be more affected in the future by
increased run-off locally and freshening of the coastal current from land
rather than the length of the open-water season.
Currently there are few seasonal primary production studies in glacier-influenced fjords across the Arctic and even fewer around Greenland
(Simo-Matchim et al., 2016).
More studies are needed to determine the main processes controlling
productivity in different types of fjords – e.g. those influenced by marine
vs. land-terminating glaciers, silled vs. non-silled and shallow silled
fjords, ice-covered vs. non-ice-covered fjords, as well as fjords influenced
by different boundary currents or mixing processes – before large
generalizations about the future productivity of Greenland fjords can be
made.
Data availability
Environmental data used in this publication may be found on the Greenland Ecosystem Monitoring website (http://g-e-m.dk, last access: 30 September 2019). Other data may be extracted directly from the current article or requested from the corresponding author. Authors plan to publish the complete data set in a repository at a later date.
The supplement related to this article is available online at: https://doi.org/10.5194/bg-16-3777-2019-supplement.
Author contributions
JMH analysed data and wrote the paper. TJP and SM measured primary
production. SM modelled light and primary production data and was involved
in data analysis and interpretation along with MKS and MLP. SM, TJP, EFM, LM, and MKS designed the study, and EFM and MLP collected complementary data in
the field. All authors significantly contributed to the final interpretation
of the results, including commenting on and editing the paper.
Competing interests
The authors declare that they have no conflict of interest.
Disclaimer
Johnna M. Holding was supported by the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie actions (grant number. 752325), whereby the research contained in this document reflects only the authors' views and the agency is not responsible for any use that may be made of the information it contains.
Acknowledgements
This study is a contribution to the MarineBasis Zackenberg programme, part of the Greenland Ecosystem Monitoring Programme (GEM) and the Arctic Science Partnership (ASP).
Parts of the data included in this study were provided by the ClimateBasis, MarineBasis, and GeoBasis programmes of GEM. Satellite images were acquired from the Sentinel Playground, Sinergise Ltd.
Finally, we would like to acknowledge Egon Frandsen, Kunuk Lennert, and Ivali Lennert for excellent assistance during fieldwork.
Financial support
This research has been supported by the Danish Environmental Protection Agency's programme for Arctic research (DANCEA) (grant no. MST-112-0023), The Carlsberg Foundation (grant no. 2013_01_0532), the Norwegian Research Council (MicroPolar) (grant no. RCN 225956), and the European Commission, H2020 Research Infrastructures (GrIS-Melt (grant no. 752325) and INTAROS (grant no. 727890)).
Review statement
This paper was edited by Stefano Ciavatta and reviewed by Jose Iriarte and one anonymous referee.
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