10.1029/2022GB007411
Key Points:• H
 igher nutrient concentrations
in a Greenlandic fjord withmarine-terminating glaciers were
found in 2019 compared to 2018
• Intense summer melting during 2019led to higher subglacial discharge andenhanced nutrient upwelling• Intensified upwelling of nutrients
into the euphotic zone increased
productivity of large diatoms
Supporting Information:

Supporting Information may be found in
the online version of this article.
Correspondence to:

N. Kanna,
nkanna@g.ecc.u-tokyo.ac.jp
Citation:

Kanna, N., Sugiyama, S., Ando, T.,
Wang, Y., Sakuragi, Y., Hazumi, T.,et al. (2022). Meltwater discharge
from marine-terminating glaciers
drives biogeochemical conditions in a
Greenlandic fjord. Global Biogeochemical
Cycles, 36, e2022GB007411. https://doi.
org/10.1029/2022GB007411
Received 30 MAR 2022
Accepted 1 NOV 2022

Meltwater Discharge From Marine-Terminating Glaciers
Drives Biogeochemical Conditions in a Greenlandic Fjord
Naoya Kanna1 , Shin Sugiyama2,3 , Takuto Ando4, Yefan Wang5 , Yuta Sakuragi5
Toya Hazumi6, Kohei Matsuno3,6 , Atsushi Yamaguchi3,6 , Jun Nishioka2,3 , andYouhei Yamashita7,

Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba, Japan, 2Institute of Low Temperature Science,
Hokkaido University, Sapporo, Japan, 3Arctic Research Center, Hokkaido University, Sapporo, Japan, 4Estuary ResearchCenter, Shimane University, Matsue, Japan, 5Graduate School of Environmental Science, Hokkaido University, Sapporo,
Japan, 6Faculty/Graduate School of Fisheries Sciences, Hokkaido University, Hakodate, Japan, 7Faculty of Environmental
Earth Science, Hokkaido University, Sapporo, Japan
1

Abstract An increasing body of work has shown the potential impacts of subglacial discharge frommarine-terminating glaciers on the marine environment around Greenland. Upwelling of nutrients associatedwith rising buoyant plumes near the front of marine-terminating glaciers plays a key role in maintaining
the high productivity of connected fjords. The response of protist communities to subglacial discharges into
fjords nevertheless remains poorly understood. Here we show data of water properties, nutrients, and protist
communities during two summers in 2018 and 2019 in a Greenlandic fjord system fed by marine-terminating
glaciers. This study included the period of intense summer melting of the Greenland Ice Sheet in 2019. The
data revealed high nutrient concentrations in 2019 that were attributed to intensified upwelling of nutrientsand dissolved iron into the subsurface layer. The source of the iron and the nutrients was subglacial discharge
and deep fjord water, respectively. Intense glacial discharges in 2019 mitigated nitrate and phosphate limitationsof phytoplankton in the fjord and resulted in an increase of chlorophyll a in the subsurface layer and growth oflarge diatoms. Heterotrophic protists such as dinoflagellates, tintinnids, and nanoflagellates were more abundantin the summer of 2019. We concluded that nutrient upwelling by subglacial discharges was the major driverof the structure of lower trophic levels in fjord ecosystems. We hypothesize that the more intense melting ofglaciers and related increase in subglacial discharge will enhance nutrient upwelling, and increased summer
productivity in fjords until the glaciers retreat and terminate on land.
1. Introduction© 2022. American Geophysical Union.
All Rights Reserved.

KANNA ET AL.

Nearly 35% of outlet glaciers of the Greenland Ice Sheet terminate in the ocean (Gardner et al., 2013) wherelarge volumes of freshwater are discharged from the glacier bed, which is situated below sea level. Subglacial discharge and associated upwelling plumes entrain large volumes of saline, warm, deep fjord water (e.g.,
Rignot et al., 2010). Heat carried by the upwelling plumes induces underwater melting and undercutting of
the glacier front, which facilitate loss of ice due to calving (Fried et al., 2015). The increase of frontal ablation during the period of intensive meltwater discharge results in retreat and thinning of the glacier (Carroll
et al., 2016; Sutherland et al., 2019). The influence of the ocean is thought to be a driver of the widespreadretreat and thinning of marine-terminating glaciers in Greenland (e.g., Cowton et al., 2018; Howat & Eddy, 2011;
Straneo & Heimbach, 2013). Changes in the productivity of the fjords associated with the melting and retreat ofmarine-terminating glaciers have been of great concern in not only Greenlandic fjords (Hopwood et al., 2018;
Meire et al., 2017) but also the Arctic fjords of Svalbard (Laufer-Meiser et al., 2021) and the Canadian Arctic
Archipelago (Bhatia et al., 2021; Williams et al., 2021) because long-term retreat of the glaciers into shallower
water or onto land will reduce upwelling of nutrients. Such a connection between ice-ocean interactions and the
productivity of marine ecosystems is not exclusive to the northern hemisphere. Similar observations have beenreported at changing glaciers in the Antarctic Peninsula fjord (Cape, Vernet, et al., 2019; Forsch et al., 2021).
Previous studies have suggested that glacier retreat will impact marine productivity because the high productivityof proglacial fjords is sustained by the transport of materials by buoyant plumes near the glacier front (Lydersen
et al., 2014; Sugiyama et al., 2021).

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10.1029/2022GB007411

An important function of the plume in the biogeochemistry of a fjord is the entrainment of nutrient-rich deep
fjord water. Fjord circulation driven by the buoyant plume greatly enhances delivery to the euphotic zone ofnitrate, the potentially limiting nutrient for phytoplankton throughout summer (Hopwood et al., 2018; Kanna
et al., 2018; Meire et al., 2016). The flux of nitrate into Greenlandic fjords from major marine-terminating
glaciers has been estimated to exceed 2 Gmol yr −1, which is higher than the flux from Arctic rivers to the Arctic
Ocean (Cape, Straneo, et al., 2019; Hopwood et al., 2018). Summer production in Greenlandic glacial fjords isstrongly influenced by the upwelling of nitrate near the glacier fronts and is therefore affected by the quantity of
subglacial discharge (Bhatia et al., 2021) and the depth of the glacier grounding line (Hopwood et al., 2018). The
volume of subglacial discharge is highly dependent on climatic conditions. For example, unprecedented atmospheric conditions in July 2019 caused remarkably high surface melting (a mass loss of 223 ± 12 Gt month −1,
Sasgen et al., 2020). There has been a trend of rapid warming and increasing occurrence of intensive melt eventsin Greenland, as well as long term trend of increasing annual meltwater flux (Trusel et al., 2018). However, theimpacts of this trend on the nitrate flux into the fjords, summer productivity, and the structure of protist communities are unknown.
Glacial meltwater also delivers large quantities of iron (Fe) to the euphotic zone. Subglacial discharge upwells
as a plume that is turbid and rich in Fe (Bhatia, Kujawinski, et al., 2013; Hawkings et al., 2014; Hopwood
et al., 2016; Kanna et al., 2020). The plume water subducts beneath a layer of relatively fresh surface wateroriginating from land-terminating glaciers and rivers, resulting in summer phytoplankton blooms at the boundary of the fresh surface layer and subsurface plume water (Kanna et al., 2018; Meire et al., 2017). While theupwelling of nitrate-rich, deep fjord water potentially mitigates the nitrate limitation of phytoplankton, Fe-rich
subglacial discharge renders the fjord ecosystem replete with Fe (Hopwood et al., 2016; Kanna et al., 2020). Thismechanism is important because Fe-deficiency limits uptake of nitrate by phytoplankton, even though the watercontains sufficient amounts of nitrate (e.g., Morel & Price, 2003; Twining & Baines, 2013).
Iron exhibits non-conservative behavior across the salinity gradient in glacial fjords. Significant amounts ofglacier-sourced Fe are removed by flocculation and precipitation upon mixing with seawater (Hopwood
et al., 2020; Schroth et al., 2014; R. Zhang et al., 2015). The transformation of Fe from particulate to dissolved
forms is likely affected by the occurrence of dissolved organic matter (DOM) in the fjord. The DOM in estuarine
and coastal waters often includes humic substances (Batchelli et al., 2010; Laglera & van den Berg, 2009). Humic
substances are heterogeneous mixtures of organic molecules that form during the decay of biogenic remains, andcan function as Fe ligands (Gledhill & Buck, 2012). Humic substances may contribute to the long-range transportof Fe because they prevent the Fe precipitating and flocculating by forming a complex with Fe (e.g., Yamashita
et al., 2020). However, the impact of humic substances on the delivery of Fe into glacial fjords has not been
quantified.
In this study, we focused on function of the plume in the biogeochemistry of a Greenlandic fjord system fed bymarine-terminating glaciers: an entrainment of nutrient-rich water and delivery of Fe. The observations weremade during two successive summer seasons of 2018 and 2019. We hypothesized that plume formation during alarge melt event in 2019 in Greenland promoted a large amount of upward nitrate flux from deep fjord water aswell as Fe flux from subglacial discharge. We evaluated the impact of upwelling plumes on nitrate fluxes and the
distribution of protist communities in the fjord by comparing our results from the two summers. In addition toprocesses related to nitrate, we investigated the linkage of humic substances with Fe in the fjord with a focus on
humic-like fluorescent dissolved organic matter (FDOMH). By combining these datasets, we interpret the impact
of subglacial discharge on summer productivity in a fjord system.

2. Materials and Methods
2.1. Study Area
Inglefield Bredning is an 80-km-long fjord system in northwestern Greenland (Figure 1). The fjord is fed bynine marine-terminating glaciers, which terminate at water depths from approximately 150 to 600 m (Porter
et al., 2014; Wang et al., 2021; Willis et al., 2018). Bowdoin Glacier (Kangerluarsuup Sermia in Greenlandic;
Bjørk et al., 2015) flows into the 20-km-long Bowdoin Fjord, which connects to Inglefield Bredning (Figure 1).
This region has been the focus of intensive field observations targeting glacier–ocean interactions (Sugiyama
et al., 2021). Previous studies have reported the impact of subglacial discharge on the marine ecosystem in
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Figure 1. (a) Location of the study area in Greenland (circle). (b) Four areas described in the text. White arrows denote the directions of water circulation (Willis
et al., 2018). Bathymetric data are taken from Morlighem et al. (2017). (c) Locations of seawater and iceberg sampling in 2017–2019. Hydrographic data near theglaciers (stars) are taken from Willis et al. (2018). The background is a Copernicus Sentinel image acquired on 10 August 2019 and processed with Sentinelflow(https://github.com/juseg/sentinelflow).

Bowdoin Fjord (Kanna et al., 2018, 2020; Naito et al., 2019; Nishizawa et al., 2019; Podolskiy & Sugiyama, 2020)and Inglefield Bredning (Matsuno et al., 2020).
2.2. Sampling
We used a trace-metal-clean method for sampling seawater (Kanna et al., 2020). Low-density polyethylene(LDPE) bottles (125 mL, Thermo Fisher Scientific), Acropak capsule with supor membrane filters (0.2-μm
pore size, Pall Corp.) and Teflon-coated 2.5-L Niskin-X samplers (General Oceanics, Inc.) were thoroughly
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acid-cleaned in a class-100 clean-air laboratory following a previously reported method (Cutter et al., 2010).
Sampling and CTD (conductivity-temperature-depth) casts in Inglefield Bredning were carried out from 12 to
19 August 2019 at nine stations (St. 1–9) (Figure 1c), including two nearby stations that were sampled from 13
to 17 August 2018 (St. 2′ and 9′). Data from Bowdoin Fjord in 2017 and Inglefield Bredning in 2018 have beentaken from Kanna et al. (2020) and Matsuno et al. (2020), respectively. Seawater samples were collected froma 5-m-long motorboat with the Niskin-X samplers suspended on a Kevlar rope. Teflon-coated messengers wereused to close the samplers. Samples for dissolved Fe (dFe) analyses were dispensed into LDPE bottles after
filtration through a 0.2-μm Acropak capsule filter attached to spigots of the samplers on board. The samples weretransported to Japan and acidified to a pH less than 1.8 by addition of ultrapure hydrochloric acid (Tamapure
AA-10, Tama Chemicals) in a clean-air laboratory three weeks after the samples were collected. The acidified
samples were stored for 6 months prior to analysis. Samples for dissolved organic carbon (DOC) and FDOMH
analyses were dispensed into acid-cleaned, 30-mL polycarbonate jars (Thermo Fisher Scientific Inc.) after filtration through a 0.2-μm Acropak capsule filter. Samples for macronutrient and suspended particle analyses werecollected into 10-mL acrylic vials (Sanplatec Corp.). Samples for analyses of Chlorophyll a (Chl. a) were filteredonto a polycarbonate filter (10-μm pore size, Whatman, Inc.) and a glass fiber filter (0.7-μm nominal pore size,
Whatman GF/F) under a gentle vacuum (<0.013 MPa). The Chl. a was then extracted in N,N-dimethylformamide(FUJIFILM, Wako Pure Chemical Corp.) for 2 weeks at −20°C (Suzuki & Ishimaru, 1990). Samples for microscopic analysis of protist communities were collected into 500-mL plastic bottles and fixed with 1% glutaraldehyde. All samples, except those for the Fe and microscopic analyses, were immediately frozen at −20°C in a
portable freezer and then stored at −20°C in a freezer room until analysis in Japan.
Eight pieces of floating ice were randomly collected and dispensed into LDPE buckets (6-L capacity, AS ONE
Corp.) (“St. Ice” in Figure 1c). The ice samples were identified as originating from icebergs because the δ 18Oof the ice (−27.1 ± 1.1‰, Appendix Table 1 in Supporting Information S1) was low compared to the value(+0.05‰) reported for sea ice (Alkire et al., 2010). The iceberg samples were melted at ambient temperatureon the day of the sampling and immediately filtered with acid-cleaned Millex syringe filters (0.2-μm pore size,
Merck Millipore Corp.) for analysis of DOC and FDOMH. The meltwater was also subsampled without filtration
for macronutrient analysis.
Vertical distributions of water properties in Inglefield Bredning were measured at approximately 2-m intervals
by using a CTD sensor (SBE 37-SM, Sea Bird Scientific). The precisions of the conductivity, temperature, andpressure measurements were ±0.003 m S cm −1, ±0.002°C and ±0.1% of full-scale range (350 dbar), respectively.
Salinity in seawater was also measured with a salinometer (AUTOSAL 8400B, Guildline Instruments). The
measured salinity in grab samples was used for calibration of the CTD sensor.
2.3. Sample Analyses
Procedures for analysis of Fe in seawater have been detailed by Kanna et al. (2020). The dFe in seawater samples waspreconcentrated with a Nobias Chelate-PA1 resin column (Hitachi High Technologies) (Evans & Nishioka, 2018;
Sohrin et al., 2008). The acidified seawater samples were adjusted to pH 6.0 ± 0.1 by addition of a 3.6-M buffer
solution prepared from acetic acid and aqueous ammonia. The Fe concentrated onto the resin was eluted with
1-M nitric acid and analyzed with a graphite furnace atomic absorption spectrophotometer (Z-2700, Hitachi HighTechnologies). All reagents used for the Fe analysis were ultrapure grade. Our pre-concentration process wasvalidated by measuring the Fe concentrations in certified reference materials for trace metals (National ResearchCouncil Canada). The measured Fe concentrations in NASS-6 (containing 0.483 ± 0.045 μg kg −1) and CASS-6(containing 1.53 ± 0.12 μg kg −1) were 0.490 ± 0.01 μg kg −1 (n = 3) and 1.40 ± 0.05 μg kg −1 (n = 3), respectively.
The DOC analysis was conducted with a total organic carbon analyzer (TOC-VCSH, Shimadzu) equipped with ahigh-temperature combustion furnace. The accuracy and consistency of the measured DOC concentrations were
evaluated by analyzing a reference seawater (produced by Dr. D. A. Hansell, University of Miami, Florida, USA).
The measured DOC concentration in the reference seawater (containing 41–43 μmol L −1) was 41.3 ± 0.9 μmol L −1
(n = 25). The FDOM was analyzed with a spectrofluorometer (Fluoromax-4, Horiba, Ltd.). The excitation emission matrix spectra (EEMs) were scanned with a 0.25-s integration time and collected at excitation wavelengths(Ex) ranging from 250 to 450 nm and emission wavelength (Em) ranging from 290 to 600 nm. EEMs of samples
were corrected and calibrated to Raman Unit (RU) according to Tanaka et al. (2014). The FDOMH was quantified
as the fluorescence intensity at Ex = 320 nm and Em = 420 nm, respectively (Yamashita et al., 2007, 2020). The
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fluorescence intensity was calibrated to the area under the water Raman peak of ultrapure water (Ex = 320 nm),which was analyzed daily with freshly prepared ultrapure water and calibrated to Raman units (RU320, nm −1)(Yamashita et al., 2020).
For macronutrient analysis, the frozen samples were thawed at 4°C for 2 days, and then the samples were equilibrated to room temperature before analysis (Macdonald et al., 1986; J.-Z. Zhang & Ortner, 1998). The macronutrient concentrations were measured using an autoanalyzer (QuAAtro, BL TEC, Ltd.) with a continuous flow
system. The measurements were calibrated with reference seawater materials (KANSO Technos Co., Ltd.). Chl. aconcentrations were determined with a fluorometer (10-AU, Turner Designs) using the non-acidification method(Welschmeyer, 1994). We used a particle counter (Coulter Multisizer III, Beckman Coulter, Inc.) to determine
the concentrations of suspended particles with diameters of 0.7–18 μm. The δ 18O values of the ice samples were
determined with an isotope water analyzer (Picarro L2120-i, Picarro, Inc.) with an analytical precision of ±0.3‰.
The procedures we used for microscopic analyses have been detailed by Matsuno et al. (2020). The 500-mL
water samples were stored on a stone table for more than 1 day to allow the protist cells to settle to the bottom ofeach bottle. The samples were concentrated to 20 mL using a syphon, and then an aliquot of 0.25–1.0 mL was
mounted on a glass microscope slide with lines. The micro- and nano-protist communities were counted under aninverted microscope with 40–400× magnification and identified to the species/genus level (Evagelopoulos, 2002;
Fukuyo et al., 1997; Hasle & Syvertsen, 1997; Maeda, 1997; Taniguchi, 1997). A double-staining method with
4′,6-diamidino-2-phenylindole (DAPI) and fluorescein isothiocyanate (FITC) (Sherr & Sherr, 1983) was used tocount nanoflagellates in the water samples fixed in 2019. Sub-samples (50 mL) were gently filtered (<80 mmHg) onto black-stained, 0.8-μm pore size filters (Advantec Corp.) and stained with DAPI and FITC for 15 min.
After the staining, the filter was mounted on a glass slide with mounting fluid (FA, VMRD, Inc.). Autotrophic
and heterotrophic nanoflagellates on the filter were counted under an epifluorescence microscope (ECLIPSE
80i, Nikon Corp.). For the water samples fixed in 2018, we counted nanoflagellates without distinction. The
protist biovolumes were calculated using the measured cell sizes (lengths and widths) (Sun & Liu, 2003). The
carbon biomasses were estimated using the carbon–volume relationship (Menden-Deuer & Lessard, 2000).
The biomasses (μgC L −1) were calculated from the carbon biomass per cell and from the cell abundances (cellsL −1).

3. Results
3.1. Hydrography
Based on geographical characteristic and similarities of water properties, our 2019 data set was classified into
four areas: (a) Area A (Sts. 1–3); (b) Area B (Sts. 4–6); (c) Area C (Sts. 7–8); and (d) Area D (St. 9) (Figures 1band 1c). Area A is located on a shallow sill (“Sill A” in Figure 1b) in front of the Melville Glacier. Area B is
located in a ∼500-m-deep basin south of a sill (“Sill B” in Figure 1b). The Farquhar Glacier, Tracy Glacier,and the northern terminus of the Heilprin Glacier flow into Area B. Area C is located in front of the southern and central termini of the Heilprin Glacier which flows into the fjord through three separate termini. Area
D is approximately 40 km west from the above-mentioned largest glaciers. Because the influence of glacial
discharge was expected to be weaker than that of the other areas, data obtained from Area D were compared todata from the other areas. To compare biogeochemical conditions between 2018 and 2019, data obtained fromtwo stations (St. 2 and 9 for 2019 and St. 2′ and 9′ for 2018) were used (Figure 1c). Although the distance between
St. 9 and 9’ is apart (approximately 8.5 km), the both stations are very similar in terms of physical water properties (Willis et al., 2018).
Surface waters in the four areas were relatively fresh and warm (Figures 2a, 2b, 2d, 2e, 2g, and 2h). Characteristics of the waters are derived from ice melt from the Greenland Ice Sheet and peripheral glaciers as well as
the atmospheric heating. Minor changes of salinity in the surface water have also been attributed to the meltingof sea ice (Kanna et al., 2018). The waters were underlain by Polar Water (potential temperatures (θ) < −1°C,
salinity (S) close to 33.6) that originated in the Arctic Ocean (Bâcle et al., 2002; Willis et al., 2018). In the recent
literature, Polar Water has been referred to as Baffin Bay Polar Water (Rysgaard et al., 2020). The θ in Areas B,
C, and D gradually increased with depth and exceeded 0°C in the regions below 250 m (Figures 2d and 2g). The
water that forms this deep, warmer layer is referred to as Atlantic Water (θ > 0°C, S > 34.2), and it originatesfrom the North Atlantic (Bâcle et al., 2002; Willis et al., 2018). In the recent literature, Atlantic Water has been
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Figure 2. Vertical profiles of θ and salinity obtained in (a and b) Area A, (d and e) Area B, and (g and h) Area C. Salinity versus θ along with isopycnals (σθ) in (c)Area A, (f) Area B, and (i) Area C. Red and black lines represent mixing lines of seawater with subglacial discharge (SD) and submarine meltwater (SM), respectively.
All graphs contain data from Area D for comparison. Shaded area shows the density range of plume water as described in the text.

referred to as Subpolar Mode Water (Rysgaard et al., 2020). In Area A, the θ of water below a depth of 250 m
was less than 0°C (Figure 2a) because Sill A (Figure 1b) prevents intrusion of Atlantic Water into the region.
Analysis of the θ versus S diagram indicated that the properties of the upper water layer (<150 m), which wascharacterized by density less than 27.0 σθ, differed significantly among the four areas (Figures 2c, 2f, and 2i).
The differences were most likely due to the magnitude of the mixing of seawater with meltwater supplied by themarine-terminating glaciers. The variations of θ and S were larger in Areas A and B than in Area D. To deduce therelative contribution from submarine meltwater and subglacial discharge on changes in the θ and S of seawater,
we used a mixing model of both meltwaters with seawater that has been used by several studies (e.g., Gade, 1979;
Kanna et al., 2020; Mankoff et al., 2016; Mortensen et al., 2013; Ohashi et al., 2020; Straneo et al., 2012; Willis
et al., 2018). Two mixing lines were plotted on the θ−S diagram (Figures 2c, 2f, and 2i). One line corresponds tomixing with submarine meltwater which is from the ice front under the water surface (SM line), and the other tomixing with subglacial discharge water (SD line). The bathymetry near the glacier fronts and CTD data reported
by Willis et al. (2018) suggest that the depth of the grounding line is 250 m for the southern and central termini ofthe Heilprin Glacier, 290 m for the Melville Glacier, and 470 m for the Tracy Glacier. When subglacial discharge
and submarine meltwater mix with the seawater near the glacier fronts, the properties of the water are expected
to correspond to densities within the ranges bounded by the mixing lines on the θ−S diagram (shaded areas in
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Figure 3. Vertical profiles of dFe, DOC, and FDOMH in (a–c) Area A, (d–f) Area B, and (g–i) Area C. All graphs containdata from Area D for comparison. Shaded areas show the depth range of plume water as described in the text.

Figures 2c, 2f, and 2i). We refer to this water as the plume water. The densities of the plume water in Areas A
and B were 25.7–27.0 σθ and 25.3–27.0 σθ, respectively (Figures 2c and 2f). The density of the plume water in
Area C fell within a relatively narrow range of 26.45–26.9 σθ (Figure 2i). The greater range of the density of theplume water in Areas A and B compared to the other areas indicated that the influence of meltwater was moresignificant in Areas A and B.
3.2. Distributions of dFe, DOC, FDOMH, Nutrients, Chl. a, and Suspended Particles
In general, dFe concentrations were lower near the surface and gradually increased with depth (Figures 3a, 3d,
and 3g). The dFe concentrations in Area D, 2.4–4.0 nmol kg −1, were lower than the concentrations of
3.4–12.3 nmol kg −1 near the glaciers (Areas A–C). The DOC concentrations in Area D, 59–71 μmol L −1, werehigher than the concentrations in other areas below a depth of 40 m (mostly less than 59 μmol L −1) (Figures 3b, 3e,and 3h). The FDOMH levels were lowest near the surface and increased with depth in all areas (Figures 3c, 3f,
and 3i). The FDOMH levels in the plume water in Areas A and C were positively correlated with the dFe concentrations (Figure 4a) but uncorrelated with the DOC concentrations (Figure 4b). The DOC concentrations in theplume water in Area A were negatively correlated with salinities (Figure 4c). There was a positive correlation
between FDOMH and salinity in plume water in Areas A−C (Figure 4d).
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Figure 4. Relationships between (a) dFe and FDOMH, (b) DOC and FDOMH, (c) salinity and DOC, and (d) salinity and
FDOMH in seawater. Data of plume water are represented by filled markers. Linear relationships were evaluated against theplume water based on Pearson correlation coefficients (r). The value of FDOMH obtained at depths shallower than 30 m,
where light penetration was >1% (Appendix Figure 1 in Supporting Information S1), was excluded from the evaluation
because of the influence of photochemical degradation.

An increase of the nitrate + nitrite concentrations from near-surface to deeper waters was commonly observed in
all areas (Figures 5a, 5g, and 5m). The nitrate + nitrite concentrations in Areas A and B increased rapidly from adepth of 20 m to the deeper regions, and the concentrations at a depth of 20–100 m were notably higher in Areas
A and B than in Area D. Vertical distributions of phosphate and silicate concentrations were similar to those ofnitrate + nitrite (Figures 5b, 5c, 5h, 5i, 5n, and 5o), except for a slight increase of silicate concentrations near thesurface. Silicate can be supplied to the fjord surface from proglacial streams (e.g., Hawkings et al., 2017), but the
supply from subglacial meltwater is insignificant because the silicate concentration of iceberg samples was low(Appendix Table 1 in Supporting Information S1). The Chl. a concentrations of large phytoplankton (>10 μm)
peaked at a depth of 20 m, except for Area C, where the concentration peaked at a depth of 10 m (Figures 5d, 5j,
and 5p). The highest concentration of 6.3 μg L −1 was observed in Area B (Figure 5j). The Chl. a concentrationsof small phytoplankton (0.8–10 μm) peaked at a depth of 20 m in all areas (Figures 5e, 5k, and 5q). The highest
concentration of small phytoplankton, which exceeded 1 μg L −1, was found in Area D. High environmental levelsof suspended particles were present in all areas, but relatively large variations were found below a depth of 50 m
in Area B (Figures 5f, 5l, and 5r).

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Figure 5. Vertical profiles of nutrients, Chl. a, and suspended particulate counts in (a–f) Area A, (g–l) Area B, and (m–r) Area C. All graphs contain data from Area D
for comparison. Shaded areas show the depth range of plume water as described in the text.

3.3. Comparisons Between 2018 and 2019
Water properties within 100 m of the surface showed interannual variations between 2018 and 2019 (Figure 6).
In 2019, the salinity (32.3∼33.6) of plume water at −0.6 < θ < −0.1°C in Area A was significantly lower than thesalinity (33.0–33.7) in Area D (Figures 6a–6c). The difference of the salinity was insignificant between Areas A
and D in 2018 (Figures 6a–6c).
The water column in Area A was more enriched in dFe in 2019 (∼5.5 nM) than during the summer of 2018(∼3.6 nM) (Figure 6d). Seawater below a depth of 20 m in Area A was also enriched in nutrients in 2019
(Figures 6e, 6f, and 6g). Even at a distance from the glaciers in Area D (>40 km), the concentrations of
nitrate + nitrite and silicate were relatively high below a depth of 30 m in 2019 (Figures 6e and 6g). Whereas thenitrate + nitrite concentrations were almost at the limit of detection at depths of 0–10 m in both years (Figure 6e),the concentrations of silicate and phosphate were well above the corresponding limits of detection at the same
depths (Figures 6f and 6g). The surface layer was relatively depleted in phosphate but slightly enriched in silicate
in 2019. The Chl. a concentrations in Area D were notably high in 2019 and reached 4.2 μg L −1 at a depth of 20 m
(Figure 6h). This concentration was nine times the concentration measured in the same area in 2018. The Chl. aconcentration in Area A in 2019 was 3.4 times the concentration in the same area in 2018 (Figure 6h).
Vertical distributions of protist communities also differed between the 2 years (Figure 7). In 2019, there was agreater variety of micro-protist taxa in the surface layer (0–20 m) (Figures 7a–7d). The integrated biomass of thewhole micro-protist community within the surface layer in 2019 was 320 mg C m −2 in Area A and 452 mg C m −2
in Area D. Diatom taxa (mostly Thalassiosira spp. and Chaetoceros spp.) were observed only in 2019 at the twoareas (Figures 7b and 7d). The biomass of nanoflagellates in Area A was several orders of magnitude higher in2019 than in 2018 (Figures 7e and 7f), whereas the biomasses in both years were similar in Area D (Figures 7g
and 7h). Heterotrophic nanoflagellates accounted for 89% of the total nano-protist biomass in 2019. The biomassof nanoflagellates significantly correlated to the Chl. a concentration in 2019 (Pearson correlation coefficients(r) = 0.71, p < 0.01), but not in 2018.

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Figure 6. Comparison of (a) θ versus salinity along with isopycnals (σθ), (b and c) water properties, and (d–h) biogeochemical components obtained in 2018 and 2019.
Blue and black lines in (a) represent mixing lines of seawater with subglacial discharge and submarine meltwater for Area A, respectively.

4. Discussion
4.1. Distribution of Plume Water in the Fjord
The water mass structures reported by Willis et al. (2018) indicate that water at depths of 75–175 m near
Farquhar and Tracy Glaciers is noticeably warmer than water at similar depths more than 20 km off the glaciers

Figure 7. Comparison of (a–d) micro-protist biomass and (e–h) nano-protist biomass obtained in 2018 and 2019. Note that the scale of the x-axis in (e) is different from the others.

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10.1029/2022GB007411(see Figure 5 in Willis et al., 2018). This warm layer is formed by upward transport and mixing of warmer andsaltier deep waters by rising subglacial discharges. Our observations were consistent with their observations andinterpretations. The counterclockwise circulation pattern in Inglefield Bredning moves subglacial water awayfrom the terminus of the Farquhar and Tracy Glaciers and affects the θ distribution in Areas A and B. Discharges
from the Melville Glacier affect the θ distribution in Area A. The θ profiles obtained in Areas A and B revealed
warm water at depths of 80–170 m (Figure 2a) and 80–140 m (Figure 2d). The indication was that plume water
was warmer in these areas compared to Area D. In contrast, water at depths of 20–80 m was colder in Areas A
and B. The θ values of plume waters were relatively uniform throughout all depths (Figures 2a and 2d). Moreover, the salinities of the plume waters of Areas A and B changed rapidly on the θ−S diagram (Figures 2c and 2f),that is, the salinity decreased along a line parallel to the SD line. We attributed the changes of salinity to mixingof seawater with subglacial discharge, as reported in previous studies in this region (Kanna et al., 2020; Ohashi
et al., 2020; Willis et al., 2018). The conclusion of our water mass analysis was that the properties of the water
sampled in Areas A and B indicated mixing of fjord water with subglacial discharge water upwelled to a depthof ∼20 m.
In contrast to Areas A and B, a layer of relatively warm water was not apparent in the plume water of Area C,
although a layer of cold water (relative to Area D) was apparent at depths of 50–100 m (Figure 2g). The tendencyof the θ and S values to lie along a line parallel to the SD line was less apparent in Area C than in Areas A and
B (Figure 2i). This observation is also consistent with the previous study in this region (Willis et al., 2018).
We expect that Area C did not capture the subglacial discharge from Heilprin Glacier due to counterclockwise
circulation in Inglefield Bredning. As shown in Figure 1b, currents from outside of Inglefield Bredning flow
along southern shore before circulating past Heilprin, Tracy, and then exiting along the northern shore (Willis
et al., 2018). Area C is located upstream of these glaciers in terms of the direction of the water currents and therefore there is less ocean-ice interaction compared to Areas A and B.
4.2. Distributions of DOC, FDOMH, and dFe
In order to evaluate sources of DOM in Inglefield Bredning, fluorescence indices were calculated from theratio of fluorescence emission intensity at a shorter and longer wavelength at a fixed excitation wavelength.
The fluorescence index (FI, Em = 470/520 nm at Ex = 370 nm) is thought to distinguish between terrestrial and soil sources (FI < 1.4) and aquatic and microbial sources (FI > 1.9) of organic matter (Birdwell &Engel, 2010; Cory & McKnight, 2005; Huguet et al., 2009). The biological index (BIX, Em = 380/430 nm
at Ex = 310 nm) has been used to distinguish between detrital (allochthonous) sources (BIX < 0.6) andfreshly produced (autochthonous) sources (BIX > 0.8) of organic matter (Birdwell & Engel, 2010; Cory &McKnight, 2005; Huguet et al., 2009). The FI and BIX values were not estimated for the iceberg samples
because these samples contain relatively large errors due to low DOC concentration (Appendix Table 1 in
Supporting Information S1). For the seawater samples, the FI ranged from 1.6 to 1.9, indicating that DOM in
Inglefield Bredning may be a mixture of organic matter from terrestrially and microbially sources. The BIX
values ranged from 0.98 to 1.2. Given that the BIX in the seawater was larger than 0.8, DOM in Inglefield
Bredning is freshly produced DOM.
The relationships between DOC concentrations and salinities in Inglefield Bredning are less clear (Figure 4c)compared to other coastal environments (e.g., Cao et al., 2016; Yamashita et al., 2011). The supply of DOC
from subglacial discharge is not likely significant in Inglefield Bredning because DOC concentrations in glacial
meltwaters around Greenland are usually low relative to seawater. For example, the DOC concentration is lower
in supraglacial water (12–30 μmol L −1, Bhatia et al., 2010; Bhatia, Das, et al., 2013; Holland et al., 2019; Lawson
et al., 2014), snow (16 μmol L −1, Lawson et al., 2014) and icebergs (9.4 ± 4.6 μmol L −1, Appendix Table 1 in
Supporting Information S1) than in fjord water (∼70 μmol L −1, Figures 3b, 3e, and 3h; ∼130 μmol L −1, Paulsen
et al., 2017, 2019). While the DOC concentrations in subglacial discharge from land-terminating glaciers arevariable from <10 to 100 μmol L −1, most of the measurements taken at peak melt in July and August are at thelower end of this value (Bhatia et al., 2010, Bhatia, Kujawinski, et al., 2013; Kellerman et al., 2020; Lawson
et al., 2014; Pain et al., 2020; Paulsen et al., 2019). Moreover, the positive correlations between the levels of
FDOMH and salinity in the plume water, irrespective of sampling areas (Figure 4d), indicated dilution of theplume water endmember by a glacial meltwater endmember. FDOMH has been used for several decades to traceterrestrial organic matter in the ocean (e.g., Coble, 1996; Walker et al., 2009). For example, an inverse linear
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Table 1
Summary of Vertical Gradients and Mean Brunt–Väisälä (BV) Frequency Squared in the Nitracline in Areas A−D and
Bowdoin Fjord
Approx.
distance fromglacier(s) (km)Nitracline
depth (dz,m)

Nitracline concentration(d(NO3 − + NO2 −), µmol
kg −1)

Vertical gradientof nitrate + nitrite(d(NO3 − + NO2 −)/dz, mmol
m −4)Mean BV
frequency squaredin nitracline (N 2,
10 −4 s −2)

Area A8

20–50

2.1–11.9

0.21–0.34

4.1–5.5

Area B20

20–50

3.6–15.6

0.21–0.35

3.5–3.9

Area C4

20–50

1.7–6.8

0.15–0.16

3.9–4.1

Area D40

20–50

0.1–6.7

0.21

3.6

1

0–20

0.1–11.5

0.57

49

Bowdoina

Kanna et al. (2020).

arelationship between the levels of FDOMH and salinities in the North Atlantic have been attributed to terrestrial
FDOMH supplied directly from surrounding continents (Jørgensen et al., 2011) as well as from large Arctic rivers
via the Arctic Ocean (Amon & Budéus, 2003; Benner et al., 2005; Opsahl et al., 1999). Our data showed trends
that differed from those in the North Atlantic.
Here, we discuss relationships between FDOMH and dFe concentrations in Inglefield Bredning. Vertical profilesof water temperature indicate that Polar Water (<0°C) that had originated in the Arctic Ocean is distributed at
depths of 50–200 m in Inglefield Bredning (Figures 2a, 2d, and 2g). In the Arctic Ocean, complexes of Fe-humic
substances (Fe-HS complexes) account for approximately 80% of dFe concentrations, and concentrations of
Fe-HS complexes are highly correlated with FDOM as well as dFe concentrations (Laglera et al., 2019). Such
Fe-HS complexes are thought to be exported from the Arctic Ocean to the North Atlantic (Laglera et al., 2019)and probably to Baffin Bay. The relationships between FDOMH and dFe in the layer of Polar Water are less clear,suggesting that Arctic-origin Fe-HS complexes are not among the major factors that control dFe concentrationsin Inglefield Bredning. On the other hand, we found a significant correlation between the FDOMH levels anddFe concentrations in the plume waters of Areas A and C (Figure 4a). The result indicated that FDOMH inglacial meltwater may be an important determinant of the dFe concentration in Areas A and C. The BIX values
suggest that FDOMH in Inglefield Bredning is freshly produced DOM. Although a high contribution of microbially derived DOM in glacial meltwaters has been reported in elsewhere (e.g., Kellerman et al., 2020; Marshallet al., 2021; Pain et al., 2020), its contribution in our studied fjord is unclear. The absence of a significant
correlation between dFe and FDOMH in the plume water of Area B (Figure 4a) was probably due to the highconcentration of suspended sediment (Figure 5l) and removal of FDOMH by adsorption onto sediment particles.
Alternatively, Fe nanoparticles (<0.2 μm) might have overwhelmed the organically bound Fe species. Further
studies are needed to understand the influence of organic matters on Fe speciation in proglacial fjords.
4.3. Influence of Subglacial Discharge on Nutrient Concentrations and dFe Distributions in the Fjord
The plume waters in Areas A and B were strongly influenced by subglacial discharge, whereas its influence on
the water in Area C was relatively weak. To quantify the flux of nitrate supplied from the plume water to thenear-surface layer (∼20-m depth) in Areas A−D, we compared the vertical gradients of the nitrate + nitrite concentrations (d(NO3 − + NO2 −)/dz) which are an important metric of nitrate diffusion (Nishioka & Obata, 2017). An
example in Bowdoin Fjord is that the d(NO3 − + NO2 −)/dz at a station 1 km off the terminus of Bowdoin Glacier(Figure 1c) was steep at depths of 0–20 m (Table 1). This steep gradient reflects that an upwelling plume distributes nitrate-enriched water into the near-surface layer in Bowdoin Fjord (Kanna et al., 2018, 2020). In Inglefield
Bredning, the d(NO3 − + NO2 −)/dz was the highest in Area B followed by Area A (Table 1). The gradient was
relatively small in Areas C and D (Table 1). We deduced that the steep gradients in Areas A and B were due tointrusions of an upwelling plume water.
In addition to the d(NO3 − + NO2 −)/dz, the flux of nitrate is inversely proportionate to the Brunt–Väisälä frequency(N) wherein the flux is proportionate to the turbulent kinetic energy dissipation (ε) in seawater (Osborn, 1980).
The N is an important metric of oceanic vertical stability. The low N 2 value in the nitracline in Areas B and D
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indicated weak stratification (Table 1) compared to the near-surface layer of the fjord (N 2 > 10 −3 s −2, Appendix
Figure 2 in Supporting Information S1). Because the N 2 values in Areas B and D were comparable, the relative
magnitudes of the flux of nitrate would depend on the values of ε and d(NO3 − + NO2 −)/dz. A recent study hasreported relatively low values of ε (∼10 −9 W kg −1) in the upper ∼200 m in proglacial fjords along northwest
Greenland, except for a high value of ε (∼10 −7 W kg −1) near the front of a marine-terminating glacier (<2 km)(Bendtsen et al., 2021). Although no measurement of ε has been performed in Inglefield Bredning, the value of εmay have been greater in Area B because of the influence of subglacial discharge.
Overall, the flux of nitrate + nitrite is expected to be the highest in Area B, which is characterized by weak stratification and a steep gradient of nitrate + nitrite concentrations. The highest abundance of large phytoplankton
was found near the surface in Area B (Figure 5j), which is likely associated with the high flux of nitrate + nitrite.
The lower abundance of large phytoplankton in Area A (Figure 5d) may be associated with the smaller flux ofnitrate + nitrite because of the stronger stratification of the fjord (N 2: Area A > Area B, Table 1). We note thatthe interplay between light availability and the flux of nitrate + nitrite is also important as a determinant forabundance of phytoplankton.
Subglacial discharge plays a key role in the supply of Fe to the fjords because glacial meltwater is rich in Fe(Bhatia, Kujawinski, et al., 2013; Hawkings et al., 2014, 2018; Kanna et al., 2020). In order to quantify Fe derived
from subglacial discharge, we calculated the differences of dFe and nitrate + nitrite concentrations (hereafter
Fe-diff and N-diff, respectively) on the same isopycnals in seawater at stations between near and far from theglaciers. An example in Bowdoin Fjord is that Fe-diff and N-diff is computed by subtracting the concentrations at
St. 10 from those at stations within the Bowdoin Fjord (indicated by “+” in Figure 1c), respectively. The relatively
high Fe-diff (>5 nmol kg −1) and N-diff (∼10 μmol kg −1) within the density range of plume water indicated theinfluence of subglacial discharge from Bowdoin Glacier (Figure 8a). The median value of Fe-diff (7.0 nmol kg −1)
peaked within 15 km from the Bowdoin Glacier (Figure 8e). In the same manner, value of Fe-diff and N-diffwas calculated for Areas A−C by subtracting the concentrations at St. 9 (Area D) from those at stations within
Inglefield Bredning on the same isopycnals. The N-diff values of the plume water in Areas A and B were as muchas 9 μmol kg −1 (Figures 8b and 8c) reflecting the significant influence of subglacial discharge on nitrate + nitrite
enrichment of the subsurface layer. The N-diff in Area C was somewhat low (∼5 μmol kg −1) in the plume water(Figure 8d). The Fe-diff of plume water was 0–2 nmol kg −1 in Area A, 1–5 nmol kg −1 in Area B, and 2–9 nmol kg −1
in Area C (Figures 8b–8d). The Fe-diff was expected to be high near a glacier because a significant portion of
the Fe is removed after subglacial discharge mixes into the fjord water (Hopwood et al., 2020; Kanna et al., 2020;
Krause et al., 2021). In Area C, the median value of Fe-diff in the plume water was 3 nmol kg −1 within 4 km of the
Heilprin Glacier (Figure 8e). However, the median value in Area B (2.6 nmol kg −1) was greater compared to thevalue in Area A (0.7 nmol kg −1) (within 8 km of the Melville Glacier), even though Area B was located approx.
20 km off the Tracy and Farquhar Glaciers (Figure 8e). Because the dFe exhibits non-conservative behavior
across salinity gradients (e.g., Hopwood et al., 2020), the net and gross fluxes of dFe from the glaciers into thefjord were presumably different. Nevertheless, we deduced that the higher Fe-diff in Area B was associated withthe larger amount of Fe supplied by the subglacial discharges of the Tracy and Farquhar Glaciers.
4.4. Impact of the Intense Summer Melting During 2019 on Nutritional and Biological Conditions in theFjord
The unusual atmospheric pattern in the summer of 2019 led to the largest melt event ever observed for theGreenland Ice Sheet (Sasgen et al., 2020; Tedesco & Fettweis, 2020). Summer mean air temperatures in Northwestern Greenland were 4°C warmer in 2019 than in 2018 (Appendix Figure 3a in Supporting Information S1).
A significant amount of meltwater (∼2,000 m 3 s −1) was also discharged from Northwestern Greenland, which
was estimated from two regional climate models (77.3–77.9°N and 65.0–70.0°W gridded regions, Mankoff
et al., 2020) (Appendix Figure 3c in Supporting Information S1). Runoff from Qaanaaq Glacier, an outlet glacierof the Qaanaaq Ice Cap (Figure 1c) was several times greater in 2019 than in 2018 (Kondo et al., 2021) (Appendix Figure 3b in Supporting Information S1). Since glacial meltwaters are not significant sources of nitrate
and phosphate (Hopwood et al., 2020; Kanna et al., 2018, 2020; Meire et al., 2017), large discharges of glacial
meltwater might therefore be expected to cause a dilution of nutrient concentrations in surface waters. Sea ice
covering Inglefield Bredning also disappeared approximately a week earlier in 2019 than in 2018 (Appendix
Figure 4 in Supporting Information S1). The earlier melting of sea ice is considered to lead to earlier initiaKANNA ET AL.

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Table 2Comparison of Biomass of Protist Community Taxa in Chl. a Maximum Layer Based on Data Obtained in 2018 and 2019
2018

2019

Taxon

Trophic

Area A (µgC L −1)

Area D (µgC L −1)

Area A (µgC L −1)

Area D(µgC L −1)

Diatoms

Autotrophic

0

0

3.2

12.4

Mixotrophic/Heterotrophic

0.01

13

3.1

12.2

Heterotrophic

3.7

2.9

4.7

3.4

Heterotrophic

1.0

0

0.5

3.1

Autotrophic/Heterotrophic

0.008

6.1

8.0

7.8

Dinoflagellates
Oligotrich
Tintinnids
Nanoflagellatestion of phytoplankton blooms because phytoplankton can acquire light, resulting in the depletion of nutrients inseawater in early summer. However, in the summer of 2019, nutrients and dFe in seawater remained more abundant compared to 2018 (Figures 6d–6g). Here we highlight how protist community distributions in plume water
differed between the two summers.
The lower salinities at depths shallower than 30 m in Areas A and D (Figure 6b) in 2019 indicated that the inputsof freshwater to the fjord were greater in 2019 than in 2018 at the time of sampling. The θ–S data from Area A
were aligned parallel to the SD line on the θ−S diagram in 2019 (Figure 6a). The properties of the water in 2019varied along the SD line under the influence of subglacial discharge. The changes of θ and S were smaller for the
sampled water in Area A in 2018 (Figure 6a). This observation confirmed that the subglacial discharge and its
influence on the fjord were greater in 2019 than in 2018 at the time of sampling.
The subglacial discharge led to larger vertical fluxes of nutrients and dFe from the deeper layer to 20 m in 2019
(Figures 6d–6g). Most likely, the subglacial discharge alleviated nitrate limitation of phytoplankton growth. The
stimulation of phytoplankton growth in 2019 was implied by the formation of a Chl. a maximum layer (CML) at
a depth of 20 m (Figure 6h) and by depletion of nitrate + nitrite concentrations in the CML in Area D (Figure 6e).
The existence of the CML was more obvious in Area D, probably because the light required for phytoplankton
growth was more available in Area D compared to Area A. The total Chl. a concentration in the CML in Area D
was up to sevenfold greater in 2019 than in 2018, and the Chl a of large phytoplankton accounted for 68% of thetotal Chl. a in 2019 (Figures 5d, 5j, and 5p). Because of their relatively low cell surface area-to-volume ratios, thegrowth of large phytoplankton is more sensitive to Fe and nutrient deficiencies than that of small phytoplankton(Sunda & Huntsman, 1997; Timmermans et al., 2004). Large phytoplankton thus grew faster than small phytoplankton in 2019.
Among large phytoplankton, diatoms are the predominant contributors to carbon fixation globally and accountfor 40% of the total primary production in the ocean (Sarthou et al., 2005). Subglacial discharges and upwelling
plumes also supplied phosphate into the subsurface euphotic zone and stimulated silicate consumption by large
diatoms in 2019. The diatoms (mostly Thalassiosira spp. and Chaetoceros spp.) in the CML accounted for 28%
and 40% of the total micro-protist biomass in Areas A and D, respectively (Figures 7a–7d and Table 2). On theother hand, the diatoms did not thrive at both areas in 2018. Although the dFe, nitrate + nitrite, and silicate
concentrations were lower in 2018, they were not likely limiting for diatoms in 2018 because the dFe:N and Si:N
ratios at a depth of 30 m (just below CML) were higher than the reported nutrient uptake and elemental composition ratios of diatoms (Table 3). It is worthy to mention that the dFe:N ratio (>0.2) in the water column at bothareas in 2018 (Figure 9a) was an order of magnitude greater than the phytoplankton cellular Fe:N ratio of 0.03
(Ho et al., 2003; Kanna et al., 2020; Maldonado & Price, 1996; Sunda & Huntsman, 1995; Twining et al., 2004).
The result from the dFe:N ratio in the seawater suggests that the seawater within Inglefield Bredning is dFe
replete with respect to other phytoplankton demand as well as diatoms. However, N:P and Si:P ratios at stationsin 2018 were much lower than the values reported for diatoms (Table 3), and thus the ratios in seawater were notfavorable to the growth of diatoms in 2018. The high abundances of heterotrophic dinoflagellates and tintinnids
in the CML in 2019 (Table 2) created high grazing pressure on diatoms and nanoflagellates. We neverthelessexpected that diatoms would grow at greater depths in the euphotic zone after the period of observations in 2019because the high N:P and Si:P ratios are available below a depth of 20 m (Figures 9b and 9d). This observation
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Figure 8. (a–d) Relationships among density (σθ), Fe-diff, and N-diff (indicated by the color scale) in seawater. The Fe-diff and N-diff in (a) was computed bysubtracting dFe and nitrate + nitrite concentrations at St. 10 from those at stations within the Bowdoin Fjord on the same isopycnals, respectively. The Fe-diff andN-diff in (b–d) was computed by subtracting the concentrations at St. 9 from those at stations within each area on the same isopycnals, respectively. Shaded area shows
the density range of plume water as described in the text. (e) Box plot of Fe-diff in plume water. The bottom and top of the box indicate the 25th and 75th percentiles,
respectively, and the line inside the box indicates the median. The bottom and top error bar show minimum and maximum values, respectively.

Table 3Comparisons of dFe and Nutrient Ratios in Seawater, Nutrient Uptake Ratios From Culture Experiments, and Elemental Composition Ratios of Diatoms
dFe and nutrient ratios in seawater at depth of 30 m
Area A

Area D

Area A

Area D

Thalassiosira

Chaetoceros

Other diatoms

Elemental
composition
ratios ofdiatomsb

0.9

1.2

9.2

6.4

2.6–13.2

5.4–9.7

5.7–1810 ± 4

2018
N:P (mol mol )
−1

2019

Nutrient uptake ratios from culture experimentsa

Si:P (mol mol )

3.0

3.2

12

10

3.7–21

7.1–11.6

12.2–29.9

5.9 ± 1.3

Si:N (mol mol −1)

3.2

2.6

1.3

1.6

0.3–2.8

0.7–1.6

1.1–2.2

0.8 ± 0.3

dFe:N (mmol mol −1)

6.4

4.1

0.7

1.0

0.48

–

–

ca. 0.23−1

Takeda (1998), Kudo (2003), Timmermans et al. (2004), and Price (2005). bSarthou et al. (2005).

a

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10.1029/2022GB007411

Figure 9. Comparisons of dFe and nutrient ratios in seawater obtained in 2018 and 2019.

implies that intense summer melting of glaciers has the potential to generate high-nutrient conditions in proglacial fjords and subsequently increase the production of diatoms during the summer.
We further expected that the production of large phytoplankton such as diatoms in 2019 would cause an increaseof mesozooplankton populations. The food webs observed in 2019 were characterized by an abundance of heterotrophic nanoflagellates, unlike the observations in 2018 (Matsuno et al., 2020). Since the heterotrophic nanoflagellates are the essential link from bacteria to ciliates and heterotrophic dinoflagellates that are preyed upon by themesozooplankton (Levinsen & Nielsen, 2002), they would also contribute to an increase of biological production.
We note that the amount of light available for phytoplankton is also an important driver for making differencesin summer production in Inglefield Bredning. Observations such as long-term monitoring of physical processes(e.g., glacier runoff and fjord circulation), biogeochemical conditions (nutrients, trace metals, organic carbon,
and so on), and biological processes (e.g., primary production and zooplankton grazing) are also lacking in Inglefield Bredning. There is the limitation of our single “snapshot” observation, which was performed only in latesummer. Future work is needed on relevant spatial and temporal scales to fully understand what are the drivers of
the observed changes in biogeochemical conditions in Inglefield Bredning.

5. Summary
Our results indicate the impact of subglacial discharges from marine-terminating glaciers on the lower trophic
levels of fjord ecosystems in Inglefield Bredning. The high abundance of phytoplankton, especially large diatoms,in the summer of 2019 was caused by the intensification of the upwelling plumes enriched with Fe, nitrate, phosphate, and silicate to the subsurface euphotic zone. Marine-terminating glaciers in Greenland are retreating andthinning (Howat & Eddy, 2011; Sakakibara & Sugiyama, 2018). Retreat of the glaciers above sea level may
reduce summer productivity because pumping of nutrient-rich deep water by upwelling plumes will be lost, assuggested by recent studies (Hopwood et al., 2018; Meire et al., 2017). Moreover, high sediment surface plumes
will reduce light availability for primary producers. Stronger and deeper stratification of fjords may also reducesummer productivity because nitrate supplied from upwelling plumes is blocked at the stratified layer. Further
investigations will be required to elucidate the mechanism linking subglacial discharges and fjord productivity,and long-term monitoring will be required to evaluate changes to Greenlandic glaciers and coastal waters.

Data Availability Statement
Copernicus Sentinel data (2018 and 2019) were processed with Sentinelflow (https://github.com/juseg/sentinelflow) by J. Seguinot. Air temperature data are distributed by the U.S. National Oceanic and Atmospheric Administration National Climatic Data Center. BedMachine v4 (https://doi.org/10.5067/VLJ5YXKCNGXO) data were
downloaded via the National Snow and Ice Data Center. Some of the CTD data in Inglefield Bredning were
downloaded via the Oceans Melting Greenland website (https://doi.org/10.5067/OMGEV-CTDS1).

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Acknowledgments
We thank the members of the 2018and 2019 field campaign in Greenland.
Special thanks are due to T. Oshima,
K. Peterson, I. Asaji, Y. Fujishi, and
S. Daorana for providing logisticalsupport. We are grateful to S. Matoba
and I. Oyabu for assistance with sample
handling and analysis and to K. Kondo
for providing the glacier runoff data set.
This research was funded by the Japanese
Ministry of Education, Culture, Sports,
Science and Technology through projects
ArCS (JPMXD1300000000) and ArCS
II (JPMXD1420318865). Funding was
also provided by a Sasakawa Scientific
Research Grant from The Japan Science
Society. Data used in this study areavailable on Arctic Data archive System,
https://ads.nipr.ac.jp/dataset/A20181001002 and https://ads.nipr.ac.jp/dataset/
A20191024-001. Finally, we would like tothank two anonymous reviewers for theirconstructive comments.

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