Glacial meltwater from the western Antarctic Ice Sheet is
hypothesized to be an important source of cryospheric iron, fertilizing the
Southern Ocean, yet its trace-metal composition and factors that control its
dispersal remain poorly constrained. Here we characterize meltwater iron
sources in a heavily glaciated western Antarctic Peninsula (WAP) fjord.
Using dissolved and particulate ratios of manganese to iron in meltwaters,
porewaters, and seawater, we show that surface glacial melt and subglacial
plumes contribute to the seasonal cycle of iron and manganese within a fjord
still relatively unaffected by climate-change-induced glacial retreat.
Organic ligands derived from the phytoplankton bloom and the glaciers bind
dissolved iron and facilitate the solubilization of particulate iron
downstream. Using a numerical model, we show that buoyant plumes generated
by outflow from the subglacial hydrologic system, enriched in labile
particulate trace metals derived from a chemically modified crustal source,
can supply iron to the fjord euphotic zone through vertical mixing. We also show that
prolonged katabatic wind events enhance export of meltwater out of the
fjord. Thus, we identify an important atmosphere–ice–ocean coupling
intimately tied to coastal iron biogeochemistry and primary productivity
along the WAP.
Introduction
Warm atmospheric temperatures are accelerating glacial retreat and
increasing meltwater discharge, rapidly changing Earth's cryosphere
(Mouginot
et al., 2019; Rignot et al., 2013). Ranging from diffuse flows to waterfalls and
streams, cryospheric meltwaters deliver dissolved and particulate material,
altering coastal ocean biogeochemistry. Glacial meltwater enters the ocean
through surface runoff, direct melting of glacial ice (including icebergs),
and discharge from liquid water reservoirs beneath glaciers, carrying iron
(Fe) and other trace metals weathered from continental crust. In the surface
ocean, the delivery of new Fe is critical for the growth of phytoplankton,
and when enhanced, naturally or artificially, primary production, and
potentially carbon export, increases (Boyd et al., 2019).
However, direct measurements of Fe in heavily glaciated fjords reveal that
up to 90 %–99 % of dissolved Fe (dFe) originating from glaciers is removed
upon mixing with seawater due to estuarine-type removal processes,
including precipitation of insoluble oxyhydroxides, adsorption to the
surfaces of particles, and aggregation of colloids and particles
(Boyle et al., 1977; Schroth et al., 2014). Together, these
processes are known as scavenging and constitute a major control on the
distribution of Fe in the ocean by converting soluble forms of Fe into
colloidal aggregates and particles (Wu et al., 2001). Constraints
on the flux of newly delivered glacial Fe that escapes this sink and is
transported across continental shelves will enable better predictions of
open ocean primary production and carbon sequestration, especially in
oceanic regimes where Fe is a limiting nutrient. Given that recent studies
revealed a critical role for manganese (Mn) in co-limiting primary
production in coastal Antarctica and the core of the Antarctic Circumpolar
Current (Browning et al., 2021; Wu et al., 2019),
an investigation of Mn delivery by glacial meltwaters is also needed
(Bown et al., 2018). Currently, very little is
known about how glacial meltwaters affect marine Mn cycling.
Evidence for Fe delivery from the cryosphere is historically based on
geochemical analysis of endmember glacial discharge
(Hawkings
et al., 2014; Raiswell and Canfield 2012; Hodson et al., 2017; Hawkings et al., 2020) and
discrete sampling of glacial ice (e.g., Hopwood et al., 2018) and seawater adjacent
to marine-terminating glaciers and ice sheets
(Hopwood
et al., 2016; Annett et al., 2015; Gerringa et al., 2015; Alderkamp et al., 2012; Sherrell et al., 2018). Trace-metal studies at the ice–ocean interface have been conducted previously in
fjords experiencing intense seasonal melt, such as in Alaska, Greenland, and
Svalbard
(Hopwood
et al., 2016; Kanna et al., 2020; Schroth et al., 2014; Zhang et al., 2015). These temperate and
high Arctic coastal waters are experiencing large freshwater and sediment
fluxes as a result of increased glacial discharge, which in turn creates
extreme physical and geochemical gradients. Ultimately, such dramatic
changes in turbidity decrease light availability while strong stratification
reduces macronutrient supply to local primary producers
(Holding et al., 2019; Meire et al., 2017). Even with high particulate and
dissolved Fe contents, meltwaters from these fjords do not feed directly
into offshore waters without undergoing significant scavenging, mixing, and
dilution (Hopwood et al., 2015), bringing into question
the effectiveness with which glacial-meltwater-derived Fe may fertilize the
surrounding ocean.
In Antarctica, fjords are less well-studied than their Arctic counterparts,
but they are also locations of intense seasonal blooms with comparable or higher
primary production relative to the adjacent continental shelves and high
sequestration efficiencies of organic carbon
(Vernet
et al., 2008; Grange and Smith 2013; Taylor et al., 2020). Along the western Antarctic
Peninsula (WAP), 674 marine-terminating glaciers drain into the coastal
ocean, primarily in fjords (Cook et al., 2016). The
vast majority of these marine-terminating glaciers are retreating due to
intrusions of warm deep water from the shelf, but many still remain as
“cold-water” glaciers (that is, local ocean temperatures are too cold to
melt the glacier terminus), particularly in the northern WAP where Weddell
Water from the eastern side advects and mixes into the Bransfield Strait
(Cook et al., 2016; Pritchard and
Vaughan, 2007). These glaciers are thought to have relatively small
subglacial meltwater discharge, with suspended sediment signatures that
spread laterally in the coastal ocean (Domack
and Ishman, 1993; Domack and Williams, 2011). This makes cold glaciomarine
Antarctic fjords unique locations for sampling subglacial discharge with
minimal dilution by ambient seawater.
Subglacial environments distinguish themselves from other cryospheric
sources of Fe to the oceanic euphotic zone. Within the subglacial cavity,
anoxia develops due to enhanced microbial respiration processes, high
weathering rates, and limited diffusion of oxygen and exchange with the
coastal ocean (Mikucki et al., 2009). The result is
increased solubility of iron as Fe(II) and other redox sensitive elements,
such as Mn. Meltwater discharge from beneath marine-terminating glaciers
enters the ocean in the subsurface but may be mixed into the surface because
of the positive buoyancy of meltwater–seawater mixtures. Enhanced vertical
shear occurs episodically in the Antarctic coastal ocean as cooled dense
parcels of air accelerate down ice sheets, generating the strongest coastal
winds on Earth (> 30 m s-1), near the coast. These episodic
katabatic wind events could also be important for enhancing the supply of
subsurface meltwaters to the surface
(Jackson et al., 2014; Lundesgaard et al., 2019). The
subglacial meltwater source represents a large uncertainty in the supply of
cryospheric Fe to the ocean given the challenge of acquiring samples of this
reservoir directly or with minimal alteration, particularly in Arctic
environments with intense seasonal melt flows and associated sediment
turbidity (Straneo and Cenedese, 2015).
We present trace-metal results from two expeditions (December 2015 and April
2016) to Andvord Bay, a cold glaciomarine fjord located midlatitude along
the WAP. This study is part of the FjordEco project which assessed the
ecosystem function and seasonality of Andvord Bay
(Pan
et al., 2019, 2020; Ziegler et al., 2020; Eidam et al., 2019; Lundesgaard et al., 2020, 2019;
Hahn-Woernle et al., 2020). The WAP is host to the most extensive collection of
glaciomarine fjords on the Antarctic continent, and its shelf waters are
subject to ongoing biogeochemical and ecological alteration linked to
large-scale changes to the western Antarctic Ice Sheet
(Henley et al., 2020). We present a detailed and
unprecedented picture of fjord Fe and Mn biogeochemistry and seasonality in
the early stages of glacier retreat associated with recent climate change
(Pritchard and Vaughan, 2007).
MethodsOceanographic setting and sampling
Andvord Bay is a glaciomarine fjord located midlatitude along the west
Antarctic Peninsula (WAP). This site was chosen because it has been
identified as a productivity “hotspot”
(Grange and Smith, 2013), and because of its
proximity to long-standing ecological research programs (Palmer Long Term
Ecological Research program). This location is characterized by converging
deep water masses with distinct physical properties (relatively warm
modified Upper Circumpolar Deep Water, cold Weddell Water).
Bordering Andvord Bay are 11 marine-terminating glaciers (Fig. 1) with Moser
and Bagshawe glaciers responsible for the majority of the solid ice flux.
These glaciers are cold-water (-1 to -0.5 ∘C), resulting in weak
meltwater signatures within the fjord (Lundesgaard et al., 2020). Observations and
sampling of Andvord Bay were conducted during two cruises as part of the
FjordEco program: LMG15-10 from 27 November to 22 December 2015 (late
spring) on R/V Laurence M. Gould, NBP16-03 from 4 to 26 April (fall) aboard R/V
Nathaniel B. Palmer. On 11 December 2015 a strong katabatic wind event, with peak along-fjord
velocities of 30 m s-1, was observed and lasted for 5 d. Atmospheric
observations by two automatic weather stations (Neko Harbor, Useful Island)
recorded episodes of high-velocity katabatic winds between field seasons,
showing that these are common events in this study region.
Regional map of study region (red box, inset right) and model
domain (dashed red box) with nearby Palmer Station, shelf station (Stn B),
and Bismarck Strait (BS). Bathymetric map of Andvord Bay with important
stations labeled (GS: Gerlache Strait; AC: Aguirre Channel; EC: Errera Channel; OB: Outer Basin; S4: Sill 4; S3: Sill 3; MB: Middle Basin; IBA: Inner Basin A; IBB: Inner Basin B) and the
surrounding tidewater glaciers numbered (4: Moser Glacier; 7: Bagshawe
Glacier). The locations for sediment cores collected in January 2016 and
included in this study are indicated by the star. The dashed yellow line
indicates the transect along which vertical sections are plotted. The blue
outline (inset right) shows glacial fronts where meltwater is introduced in
the model.
A total of 18 stations per season were sampled for Fe geochemical variables
using acid-cleaned 12 L Go-Flo bottles (General Oceanics) suspended in
series on a clean hydroline (Amsteel) and triggered with acid-cleaned Teflon
messengers designed by Ken Bruland (UC Santa Cruz). This sampling effort
coincided with concurrent CTD stations. Once on board, Go-Flo bottle tops
and bottoms were covered with plastic and placed on a wooden rack located
within the trace-metal clean shipboard plastic “bubble”, which was
positively pressurized with HEPA-filtered air. Sample bottles were soaked in
a soap detergent overnight with heat applied (60 ∘C),
followed by a 1-week soak in 3N HNO3 (trace-metal grade) at room
temperature and finally a 1-week soak in a 3N HCl (trace-metal grade)
bath at room temperature. Rinsing with ultrapure Milli-Q water occurred after
each step. Samples for dFe analysis were pressure-filtered (N2 gas,
99.99 %) directly from Go-Flo bottles through 0.2 µm Acropak 200
capsule filters (VWR International) into low-density polyethylene bottles
(Nalgene) and acidified to pH 1.7 to 1.8 using HCl (Optima grade, Fisher
Scientific). Samples for Fe-binding ligands were similarly filtered in-line
but collected in fluorinated high-density polyethylene (Nalgene) bottles,
unacidified, and frozen at -20 ∘C until laboratory analysis
back on land. This sampling protocol followed established trace-metal clean
methods to the standards of the GEOTRACES program to avoid metal
contamination. In addition to the filtered samples, unfiltered seawater was
sampled directly from the Go-Flo bottles and acidified to pH 1.8 and stored
for > 6 months (up to 2 years) and vacuum-filtered prior to
analysis using acid-cleaned 0.4 µm polycarbonate (PC) filters in a
Teflon filtration apparatus to determine total dissolvable Fe (TDFe). Labile
particulate Fe (LpFe) is calculated as the difference between TDFe and dFe.
Particulate samples were collected on 0.4 µm PC filters and stored at
-20 ∘C until complete digestion using an HNO3–HF mixture. The
digestion method employed is described in Planquette and Sherrell (2013) and
is widely used in the GEOTRACES program
(Cutter and Bruland,
2012; Fitzsimmons et al., 2017) .
Attention to cleanliness was applied when sampling icebergs during small
boat deployments in the fjord. Floating icebergs were sampled using a clean
stainless-steel pickaxe and rust-free stainless-steel screwdriver and
plastic mallet for chiseling pieces of ice. Samples were collected by slowly
(engine idled) approaching the target piece of floating ice from downwind,
limiting the chance of engine exhaust contamination. Each piece of ice was
collected above freeboard (sea surface), to reduce the chance the ice was
altered by seawater, and rinsed with Milli-Q prior to placing into
acid-cleaned 2 gallon Ziploc polyethylene bags and storing at -4 ∘C until sample processing. Prior to filtration, ice samples were removed
from the freezer and left to melt at ambient shipboard temperatures. Once
completely melted, a small incision was made on the Ziploc bags using a
clean stainless-steel razor, and contents were poured into the Teflon filtration
manifold or directly into sample bottles, thus collecting samples for
dissolved, total dissolvable, and particulate trace-metal fractions. We note
that steel-free tools should be used when available, such as titanium tools
and ceramic knives, for the cleanest method for sampling of icebergs.
Trace-metal concentrations
Stored acidified filtered seawater samples were analyzed for Fe at Scripps
Institution of Oceanography using flow injection with chemiluminescence
methods described by Lohan et al. (2006).
Dissolved Fe in the samples was oxidized to iron(III) for 1 h with 10 mM
Q-H2O2 (Suprapur grade), buffered in-line with ammonium acetate
to pH ∼ 3.5, and pre-concentrated and matrix removed on a
chelating column packed with a resin (Toyopearl®
AF-Chelate-650M). Dissolved Fe was eluted from the column using 0.14 M HCl
(Optima grade, Fisher Scientific), and the chemiluminescence was recorded by
a photomultiplier tube (PMT, Hamamatsu Photonics). The manifold was modified
based on Lohan et al. (2006). Standardization of Fe was carried out with a
matrix-matched standard curve (0, 0.4, 0.8, 3.2, 10 nmol kg-1 added
high-purity Fe metal ICP spectrometry standard in 2 % HNO3) using
0.34 nM dFe Pacific surface seawater. Standards were treated identically to
samples. Accuracy was assessed by repeated measurements of GEOTRACES coastal
and Pacific Ocean reference seawater samples. Our measurements of GSC gave
Fe = 1.391 ± 0.115 nM (n=19, over a 3-month period, consensus
1.535 ± 0.115 nM). Our measurements of GSP gave Fe = 0.164 ± 0.024 nM (n=8, over a 1-month period, consensus 0.155 ± 0.045 nM).
Consensus values are from the most recent July 2019 compilation
(geotraces.org). Precision, determined by replicated analyses of an in-house
large-volume reference seawater sample within each analytical session, was
typically ± 5 % or better. For the duration of these analyses, the
average limit of detection (defined as 3× the standard deviation of the
blank) was 0.036 nM dFe (n=10).
A subset of the seawater samples and all freshwater samples were run for Fe
and Mn at Rutgers University using isotope dilution inductively coupled
plasma mass spectrometry (ICP-MS) methods based on Lagerström et al. (2013)
and similar to those described in Annett et al. (2017). Briefly, 10 mL aliquots of
seawater samples were extracted using a commercially available automated
SeaFAST pico system (Elemental Scientific, Inc.) after online buffering to a
pH of approximately 6.5 using ammonium acetate buffer, achieving a 25-fold
pre-concentration after column elution in 0.4 mL of 1.6 M ultrapure nitric acid
(Optima grade, Fisher
Scientific)(Lagerström
et al., 2013). Isotope dilution was used to standardize Fe, while Mn was
standardized using an external matrix-matched standard treated identically to
samples. The analysis of the concentrate was performed on an Element 2
sector-field ICP-MS (Thermo Fisher Scientific). Accuracy and precision
(± 3 %, 1SD, for Fe and Mn) were assessed by repeated measurements of
in-house large-volume reference seawater samples within each analytical
session. Blanks averaged 51 pmol kg-1 for Fe (n=59; limit of
detection, or LOD = 48 pmol kg-1) and 4 pmol kg-1 for Mn (n= 69; LOD = 4 pmol kg-1) for all analytical runs. A comparison of the
seawater analysis methods employed here is shown in Fig. S1. In general,
there is good agreement (average 11 % and 6 % difference between late spring and
fall, respectively) between the chemiluminescence and ICP-MS methods,
comparable to the uncertainty of GEOTRACES consensus values from the
intercalibration of 13 trace-metal laboratories (for Fe, RSD 10 %,
https://www.geotraces.org/standards-and-reference-materials/, last access: 1 March 2021).
Total dissolvable trace metals and particle digests, including freshwater
dissolved metals (i.e., glacial melt), were analyzed using direct-injection
ICP-MS methods using external standards and added In as a matrix and
instrument drift corrector for the quantification of particulate Fe, Mn,
aluminum (Al), and titanium (Ti) concentrations
(Annett et al., 2017).
Sediment cores and diffusive flux
Cores for this study were collected using a 12-barrel Megacore multi-coring
device aboard the R/V Nathaniel B. Palmer cruise NBP16-01 in January 2016. Multiple barrels
were sampled from a single Megacore deployment. See Taylor et al. (2020) for a complete account of coring efforts and Komada et al. (2016) for a
description of the pore water sampling procedures. Porewater dFe
and dMn were determined colorimetrically using the ferrozine and formaldoxime
techniques, respectively (Armstrong
et al., 1979; Burdige and Komada, 2020). For dFe, hydroxylamine-HCl (0.2 % v/v
final concentration) was added to the samples before analysis, to reduce any
dissolved Fe(III) in the samples to Fe(II). For dMn, a hydroxylamine
solution was added to an acidified (pH ∼ 1–2) sample, and an
EDTA solution was added to remove interference from a colored Fe complex.
Porewater oxygen concentrations were measured using a polarographic
microelectrode
(Brendel
and Luther, 1995; Luther et al., 1998, 2008). A sequential extraction technique
(Goldberg
et al., 2012; Poulton and Canfield, 2005) was used to determine sediment Fe
speciation for the following fractions: Feox (highly reactive, poorly
crystalline iron oxides), Femag (magnetite), Feprs (Fe in
poorly reactive sheet silicates), FeT (total sediment Fe), Fepyr
(Fe in pyrite), and finally FeU (unreactive pool under all treatments = FeT- (Feox+ Femag+ Feprs+ Fepyr)).
All extracts were analyzed for Fe by flame atomic absorption spectrometry
(for details see Burdige and Komada, 2020).
In this study, we investigate the potential for efflux of dissolved trace
metals as a source to the overlying water column. Using Eq. (1), we can
estimate the approximate sediment diffusive flux (Jsed) for dissolved
porewater species.
Jsed=-ϕDseddCdz
In this equation, ϕ is the porosity of the sediments and was found to
be 0.9 on average near the sediment surface. Porewater analyses of dissolved
Fe and Mn in the Outer Basin (OB) cores reveal high variability in the
top-of-core gradient (dCdz) in porewater Fe and Mn (Fig. S2). An
average of two cores gives a gradient of 21.9 µM cm-1 dissolved
Fe and 3.6 µM cm-1 dissolved Mn. Assuming a diffusion
coefficient for Fe and Mn in free solution for seawater (DSW) at
0 ∘C to be 3.15x10-10 m2 s-1 for Fe(II) and
3.02 × 10-10 m2 s-1 for Mn(II), we can then estimate the
diffusion coefficient in the sediments (Dsed) using the following
relationship (Boudreau, 1996;
Halbach et al., 2019):
Dsed=DSW1-2lnϕ.
Iron-binding ligands
A subset of seawater samples was analyzed for dFe-binding ligands using
single analytical window methods. The methods applied here are described
extensively in Buck et al. (2018). Briefly, natural seawater samples were titrated
with dFe (0–35 nM) in order to fully saturate the natural ligands. Following
a 2 h equilibration with the added Fe, a well-characterized ligand
(salicylaldoxime, SA) was added to compete with natural dFe-binding ligands.
The concentration of SA used in this study to examine ligands was 25.0 µmol L-1 (αFe(SA)x=115). After at least 15 min
of equilibration, the Fe(SA)x electroactive complex was measured using
adsorptive cathodic stripping voltammetry (ACSV) on a hanging mercury drop
electrode (BioAnalytical Systems, Incorporated). Peak heights were measured
using ECDSOFT, and sensitivity was optimized in ProMCC
(Omanović
et al., 2015). A combination of traditional linearization techniques was
previously applied to determine the concentrations and strengths of natural
ligands within the seawater sample using ProMCC
(Omanović et al., 2015). The uncertainty on modeled complexation
parameters was optimized using single- or multiple-ligand fitting. These
methods were applied successfully to the GEOTRACES speciation data sets
(Buck et al.,
2015, 2018).
We calculate the capacity for the free ligand pool to bind Fe at equilibrium
(Fitzsimmons
et al., 2015), or αFeL′, defined as
αFeL′=1+eL×K,
where eL is the difference between the total ligand concentration (Lt) and
the dFe concentration, and K is the conditional stability constant.
Numerical model simulations
Based on Hahn-Woernle et al. (2020), the ocean in the Andvord Bay region is
modeled with the primitive-equation, finite-difference Regional Ocean Model
System (ROMS; Haidvogel et al., 2008). The grid has a
horizontal resolution of ∼ 350 m and a terrain-following
vertical coordinate system with 25 depth layers. Due to the changing
terrain, the fixed number of layers, and surface intensified resolution, the
maximum thickness for deeper layers is 84.6 m, and the minimum thickness for
surface layers is 0.5 m (to better resolve the surface currents, for example). The
domain has three open boundaries: the western end of Bismarck Strait, a
passage to the continental shelf in the northwest, and along Gerlache Strait
to the northeast (Fig. 1). Boundary and initial conditions were derived from
CTD and ADCP observations. The model is forced with tidal and meteorological
data (from TPXO8 Egbert and
Erofeeva 2002 (updated) and RACMO van Wessem et al., 2014,
respectively) and run from November 2015 for 5 months. After 1 month,
the transient effects, based on dynamics and thermodynamics, were found to
no longer be present, and the system was consistent. Only the final 4
sea-ice-free months were analyzed (December through March). Processes like
melting of icebergs and floating sea ice are not modeled directly; therefore
such local freshwater sources are represented in a surface intensified
meltwater input applied along the glacial fronts (for further details see
Hahn-Woernle et al., 2020). These new freshwater sources also include surface
runoff and local melt of glacial ice, while precipitation and snowfall are
represented in the meteorological forcing. To represent the seasonal cycle
of temperature-induced melting, the volume flux of inflowing meltwater
follows a bell-shaped temporal distribution peaking at the end of January.
We use this model to identify the potential supply pathways and estimate the
hydrographic export of three Fe-rich sources in Andvord Bay: surface glacial
meltwater, subsurface subglacial plume, and deep water masses located within
the inner basin. For this purpose, we designed three model experiments with
numerical “dyes” to track potential iron pathways: one, to track the
current seasonal input of meltwater from glaciers in Andvord Bay (surfacemeltwater dye experiment) released along the glacial fronts in the inner fjord at 0–50 m depth (Fig. 1), and two additional experiments involving subsurface water masses in
front of Bagshawe Glacier in Inner Basin A (IBA, 64∘53′36′′ S,
62∘34′48′′ W) at two different depths (subsurface and deep dye experiments). Due
to the model geometry, the mean depths at which the subsurface and deep dyes were
released were 107 (94–120 m) and 314 m (290–342 m), respectively. Covering
two horizontal grid cells each (with different thickness), the subsurface
and deep dyes had initial volumes of 5 × 106 and 11.3 × 106 m3, respectively. It follows from the experiment setup that the surface
meltwater dye has a continuous source while the total amount of the other
two dyes is a constant as long as they do not leave through the open
boundaries of the model domain.
ResultsSeasonality and hydrography in Andvord Bay
In Andvord Bay (Fig. 1), seasonal changes in phytoplankton biomass were
documented, as indicated by the proxy chlorophyll a, which shows a 10-fold
concentration decrease across all taxonomic classes between the late spring
and fall cruises (Pan et al., 2020).
Associated with these changes in primary production, depletion of the
surface macronutrients nitrate (N) and silicic acid (Si) were observed
(Ekern, 2017). Increased Si concentrations, with respect to
nitrate, within the inner fjord are driven by dissolution of biogenic silica
sediments, or weathering of the bedrock by contact with the 11 marine-terminating glaciers feeding into Andvord Bay since Si-to-N ratio is
highly correlated with meltwater fraction (MWf) below the surface layer
(Hawkings et al., 2018;
Ng et al., 2020). Surface stocks of macronutrients were never exhausted (Fig. 2).
The phytoplankton community was dominated by small size classes, with very
few large diatoms (Pan et al., 2020). The
microplankton class, including large diatoms, was sparingly present in the
fall; however, benthic cameras captured a large sedimentation event of
marine aggregates indicative of a large diatom bloom in late January. The
export of biogenic particles from the surface also showed a distinct
seasonality indicated by increased chlorophyll a pigment content in seafloor
surface sediments in fall (Ziegler et al.,
2020), as well as higher respiration rates from chamber incubation
experiments in the fall compared to spring (data not shown), although no
indication of sulfate reduction was observed in sediment box and Kasten
cores (2.3 m long), suggesting that oxygen, nitrate, and metal oxides were
sufficient to oxidize organic matter within the upper sediments (Craig Smith,
personal communication, 2018).
Seasonal phytoplankton, macronutrient, micronutrient, temperature, and
meltwater distributions plotted as sections extending from the inner basin
(IB, left) towards Gerlache Strait (GS, right). Plots were made with Ocean
Data View visualization software (Schlitzer, 2002, Ocean Data View, last
access: 1 February 2021).
Derived glacial MWf (Fig. 2), based on salinity and oxygen isotopes of
seawater, ranged from 0.75 %–2 % in late spring and from 0.5 %–2.5 % in the
fall (Pan et al., 2019). The fjord also
exhibited a gradient in meltwater content, with the highest MWf at the glacier
terminus. Using a simple mass balance for the surface layer in Andvord Bay,
we estimate an approximate meltwater input of 23 600 m3 d-1 in
order to account for the observed changes in oxygen isotope ratios. This
estimate is within the derived estimates of surface meltwater flux generated
by warm atmospheric temperatures (1.4 × 104 to 1.2 × 105 m3 d-1; Lundesgaard et al., 2020). The MWf is
strongly correlated with phytoplankton abundance within Andvord Bay; for a
detailed discussion see Pan et al. (2019). We find that glacial meltwater impacts
phytoplankton within the fjord, but the geographical influence of meltwater
can extend across the shelf, hundreds of kilometers from the coastal inputs
(Dierssen et al., 2002;
Meredith et al., 2017).
Physical properties measured in the study region showed the dominant water
masses in the fjord were Antarctic Surface Water (cold fresh) and Bransfield
Strait water (cold salty) (Lundesgaard et al.,
2020). However, during late spring, greater influence of modified Upper
Circumpolar Deep Water was observed outside of the fjord, indicated by its
distinctly higher temperature at depth, but this water mass is prevented
from entering the fjord due to a shallow sill near the fjord mouth in the
Gerlache Strait (Fig. 2). Optical measurements recorded a change in the
particle concentration and assemblage between the two cruises. Profiles of
beam attenuation coefficient and particulate backscattering coefficient
showed strong seasonality (see Fig. 4 and discussion in Pan et al., 2019). Pan et al. (2019)
interpreted these optical signatures in the upper water column as a change
from a surface biogenic-dominated signal in late spring to a subsurface
lithogenic-dominated signal in the fall, composed of fine suspended
particles contained within plumes. An important feature observed within the
fjord was a subsurface neutrally buoyant plume (∼ 100 m)
characterized by a point source of relatively cold and particle-laden water
emanating from the terminus of Bagshawe Glacier and extending several
kilometers over the inner basin (Fig. S3).
Surface (< 20 m) dissolved Fe (a, b) and meltwater fraction (c, d) for late spring (left two panels) and fall (right two panels).
Plots were made with Ocean Data View visualization software (Schlitzer,
2002, Ocean Data View, last access: 1 February 2021).
Strong buoyant plumes can drive circulation in fjords via the “meltwater
pump”, but small amounts of basal and subglacial melt have a negligible
effect on circulation in Andvord Bay. While this process is described
in depth for Arctic glaciers, Andvord Bay differs in that ocean temperatures
are approximately -1 ∘C at depth, too cold to ablate the glacier
terminus, and neutral buoyancy is reached below the surface layer (indicated
by subsurface sediment plumes; Domack and Ishman, 1993).
However, cold-water glaciers must have some mass loss even at seawater
temperatures below the glacial ice melting point. Two important consequences
of these plumes are a flux of suspended particulate matter within subsurface
“layers” as indicated by a high beam attenuation coefficient and optical
backscatter (Fig. S3 in Pan et al., 2019), and general mid-water cooling found in
the inner fjord (Fig. 8 in Lundesgaard et al., 2020). Downstream mixing
mechanisms, such as flow over topographic features or wind-induced
upwelling, can displace plume water closer to the euphotic zone.
Water column trace metals
Dissolved Fe concentrations in the surface, defined as the upper
∼ 20 m based on similar mixed layer depths (MLDs) for both
seasons (Lundesgaard et al., 2020), changed seasonally with an overall increase in
dFe concentration in the fall (Fig. 3). The average surface concentration
during late spring was 2.47 ± 0.92 nM (n=21), while in fall it was
6.67 ± 1.41 nM (n=19). Water column trace metals are presented in
Table S1. These concentrations are within the ranges of dFe determined in
prior studies (1–31 nM) in the northern WAP region but indicate that large
temporal variability exists in surface waters in this region (Bown et al., 2018;
Hatta et al., 2013; Sañudo-Wilhelmy et al., 2002; Ardelan et al., 2010; Martin et al., 1990). The
smaller range of surface concentrations during late spring suggests that dFe
was more tightly controlled by phytoplankton uptake, whereas in the fall,
patchiness among stations arises due to varying proximity to Fe sources and
the effects of circulation and mixing. Vertical profiles of dFe showed a
steep increase to values greater than 10 nM at the deepest depths sampled
during late spring, especially at stations located within the inner fjord
and basins (Figs. 2, 4). In the subsurface (50–150 m), an enriched dFe source
was present with average concentrations 3.68 ± 1.52 nM in late spring
and 7.38 ± 2.49 nM in the fall. Deep water masses more than 150 m
deep had the highest average concentrations of dFe, and similar mean
concentrations were observed for both seasons (8.79 ± 4.75 nM in late
spring, 6.37 ± 2.38 nM in fall). The greatest concentrations of dFe
were found in the inner fjord and basin stations, with the exception of one
station located at the mouth of the fjord near Aguirre Channel (station AC
in Fig. 1). Water column concentrations were lower in the Gerlache Strait
and fjord mouth. The general shapes of the profiles in late spring are
characteristic of a stratified water column, with dramatic ferriclines below
the surface.
Depth profiles of dissolved Fe [nM] sampled in the Andvord Bay
region for December 2015 (a) and April 2016 (b). The colored lines indicate
highlighted profiles: the geometric mean of the linearly interpolated data
points within Andvord Bay (black), Station B on the continental shelf (light
blue; see Fig. 1), Station GS (Gerlache Strait, yellow), and Station S3 (dark
blue). Other Andvord Bay stations are shown in grey. The dashed line is the
average bottom depth within the fjord.
In the fall, surface dMn was more than double that observed in late
spring, but surface dFe showed a greater seasonal increase, such that the
dissolved Mn : Fe ratio decreased overall and was more variable than in late
spring. Concentrations of dMn remained below 4.5 nM, even at depth in the
late spring. Labile particulate Mn (LpMn = TDMn - dMn) showed strong
co-variation with LpFe and beam attenuation coefficient c(660). The
comparatively high surface dissolved Mn : Fe ratios in late spring were
presumably due to intense biological drawdown of Fe during the vernal bloom,
evidenced from low concentrations of dFe where phytoplankton biomass (as
chl a) was highest (Fig. 5a). In the late spring, dFe is anti-correlated
with MWf (Fig. 5c), whereas there was no significant trend between dFe,
biomass, and MWf variables in the fall (Fig. 5b, d). The correlation between
dMn and dFe was stronger in the fall, however, compared to the late spring
(Fig. 5e, f).
Labile particulate iron (LpFe = TDFe - dFe) concentrations were elevated
in the inner basins in late spring and fall and strongly correlated
with suspended particle concentrations, indicated by optical beam
attenuation coefficient c(660) m-1 (Fig. 5n). Average TDFe and LpFe
concentrations in the surface were comparable to surface waters in Ryder Bay
(southern Antarctic Peninsula), where TDFe varied temporally from 57 to 237 nM (Annett et al., 2015). This comparison
between LpFe and TDFe is valid since TDFe is much greater than dFe in these
two coastal locations; hence it is a good approximation of LpFe. The LpFe
maxima were associated with high turbidity in the inner basins, reaching as
high as 900 nM at 300 m depth in the fall (Fig. 6). Dissolved Fe and LpFe
were correlated (r2=0.48 late spring n=19; 0.77 fall n=28)
(Fig. 5g, h). On average, dFe made up 3.1 % (late spring) and 4.6 %
(fall) of the total dissolvable pool. The LpMn concentrations displayed
similar seasonality to LpFe and a similar association with total particles,
but they were more strongly correlated in the fall (Fig. 5l). Dissolved Mn and
LpMn were highly correlated (r2=0.70 late spring n=19; 0.79 fall
n=28; Fig. 5i, j). On average, dMn composed 52 % (late spring) and
57 % (fall) of the total dissolvable pool.
Dissolved trace metals plotted against observed and derived
variables for December 2015 (a, c, e) and April 2016 (b, d, f). Dissolved Fe
(a–b) versus logChlorophyll a concentrations. Dissolved Fe (c–d) versus
meltwater fraction. Dissolved Mn (e–f) versus dissolved Fe. Least-squares
regression lines are shown where they are statistically significant (p<0.005).
Figure 5 (continued). Dissolved Fe and Mn concentrations versus labile
particulate Fe and Mn for each season. Dissolved Fe (g–h), labile
particulate Mn (k–l), and beam attenuation coefficient (m–n) versus labile
particulate Fe. Dissolved Mn (i–j) versus labile particulate Mn.
Least-squares regression lines are shown where they are statistically
significant (p<0.005).
Total dissolvable trace metals and beam attenuation coefficient
c(660) for both seasons. The transects are plotted as distance from the
Bagshawe Glacier terminus. Plots were made with Ocean Data View
visualization software (Schlitzer, 2002, Ocean Data View, last access: 1 February 2021).
Glacial ice and plume trace metals
Glacial ice and plume samples were analyzed for Fe, Mn, Al, and Ti
concentrations, which are presented in Table 1. Three glacial ice samples
were analyzed for dFe (72 ± 121 nM) and dMn (49 ± 83 nM). Visual
inspection of Glacial Ice 3 and 4 showed these pieces contained low particle
loads, while Glacial Ice 1 and 2 had a comparatively high content of dark
colored coarse-grained particles. Hence, these and the “clean” glacial ice
samples are indicative of the variability of trace-metal concentrations in
icebergs found in Andvord Bay. Labile particulate trace-metal concentrations
were 2 orders of magnitude higher than the dissolved fraction based on two
ice samples (41 ± 86 µM LpFe, 3.6 ± 5.1 µM LpMn). We
did not determine labile particulate trace metals for Glacial Ice 3 and 4;
thus these average labile particulate concentrations are skewed toward a
high value. Total particulate trace metals showed similar concentration
variability to the dissolved fraction (95 ± 181 µM TpFe,
2.7 ± 5.1 µM TpMn). For Glacial Ice 3 and 4, the concentration
of dMn was greater than TpMn. The ratios of labile and total particulate
Mn : Fe were 0.061 ± 0.002 mol : mol and 0.028 ± 0.004 mol : mol,
respectively.
Dissolved Al and Ti were not analyzed for these ice samples, but total
dissolvable and total particulate samples were analyzed for Glacial Ice 1
and 2 and 1–4, respectively. We defined the refractory particulate trace-metal concentration as the difference between the total particulate and
total dissolvable fractions (RpTM = TpTM - TDTM). Total dissolvable Al and
Ti average concentrations were skewed due to the heavy particle load present
within Glacial Ice 1 and 2 (603 ± 716 µM TDAl, 20.8 ± 27.1 µM TDTi). Total particulate Al and Ti had similar variability to the
total dissolvable fraction and included all four glacial ice samples with
averages of 428 ± 790 µM TpAl and 13.4 ± 25.7 µM
TpTi; therefore the average total particulate concentrations were lower than
the average determined for total dissolvable Al and Ti in Glacial Ice 1 and 2. We found the labile particulate concentration to be a valid comparison to
total dissolvable particulate concentration since dFe concentration was on average 1.8 ± 1.5 %
of TpFe concentration. Thus, the particulate fraction dominated trace-metal
speciation of total Fe, Mn, Al, and Ti in glacial ice.
Glacial ice and seawater samples analyzed for dissolved, labile,
and total particulate trace metals. Crustal averages from Taylor and
McClellen (1995): Mn : Fe (0.017 mol : mol), Fe : Al (0.2), and Al : Ti (35).
Four seawater samples were collected from 100–110 m depth, corresponding to
the core of the subsurface turbidity plume within IBA. Average
concentrations of dissolved metals were 8.75 ± 2.25 nM dFe and
5.52 ± 0.62 nM dMn. LpFe (351 ± 148 nM) and LpMn (8.23 ± 2.68 nM) were indistinguishable from the total particulate fractions (416 ± 93 nM TpFe, 9.52 ± 2.05 nM TpMn) within measurement error, including
filter splitting and sample distribution uncertainties. The average ratio of
labile particulate Mn : Fe was 0.024 ± 0.003 mol : mol. Particles collected
from the plume had high concentrations of Al and Ti but with distinctly
different lability from that of Mn and Fe. The TDAl was 894 ± 68 nM
while TpAl was 1734 ± 369 nM. Similarly, TDTi was 14.1 ± 0.45 nM
and TpTi was 45.1 ± 10.7 nM. The total dissolvable Al : Ti ratio was
64 ± 6 mol mol-1 and the total particulate Al : Ti ratio was
39 ± 1 mol mol-1. The Al : Ti ratio is elevated above the crustal
ratio (35 mol mol-1) in the total dissolvable fraction, suggesting a
larger adsorbed fraction for Al than for Ti.
Glacial sediments
Solid phase Fe speciation of one sediment core from the Outer Basin station
(OB, 64∘46′46′′ S, 62∘43′57′′ W, ∼ 500 m, collected in January 2016) showed an enrichment of authigenic Fe oxides
at the surface. Chemical treatments of the sediments with HCl poorly dissolves
crystalline Fe oxy(hydr)oxides (ferrihydrite and lepidocrocite),
which are found to be 10 % of the total particulate Fe of the surface
sediments in this location, compared to an average of 2 % below 1.5 cm
(Fig. S4). In the surficial sediments, a larger portion of the Fe is
associated with poorly labile sheet silicates (e.g., structural Fe(III) in
clays, 36 %), and a comparable fraction is refractory and is not liberated
by any of the solution treatments (31 %). Other fractions of particulate
Fe are associated with more crystalline Fe oxides (goethite, hematite) and
the minerals magnetite and pyrite. Porewater analyses were performed on two
OB cores using colorimetric methods, revealing high concentrations of dFe
and dMn. Below the well-oxygenated layer (upper ∼ 0.5 cm), but
within the upper 10 cm, dFe reaches its peak concentration of 80 µM,
while maximum dMn is 6 µM. Down-core from the peak, concentrations
tend to decrease for both trace metals, but there is considerable
variability between 15 and 25 cm, including several deeper local maxima. The
average porewater concentration of dFe in the top 2.5 cm is 26 µM
(Fig. S2). There is considerable difference in the porewater concentrations
of the two OB cores, indicating bioturbation of the sediments resulting in
large variability on small scales. Points excluded from the oxygen profiles
were below the detection limit, while several samples were lost from the
porewater profiles, represented as gaps in the vertical traces of dFe and
dMn.
Fe-binding organic ligands
To gain insight into the speciation of dFe within the fjord, we analyzed
seawater samples for Fe-binding ligands and to identify comparative
strengths of organic Fe complexes (see Sect. 2). There is potential to overestimate
ligand concentrations using these methods (Gerringa et al., 2021);
however, the trends within these data and interpretations are valid.
Analysis of the ligands within Andvord Bay shows a down-fjord gradient in
both quantity and quality (all ligand data presented in Table 2). In the
late spring, strong ligands (LogKFeL,Fe′cond≥12.0) were
detected in the surface at stations located within the fjord at
concentration levels ranging from 4.06 ± 1.74 nM at Inner Basin A (IBA)
to 7.27 ± 1.97 nM at Sill 3 (S3), while only weak ligands
(LogKFeL,Fe′cond<12.0) were detected in the Gerlache Strait
(GS; 5.72 ± 2.21 nM). An excess of strong ligands, relative to
dFe, was detected in the inner basins. A gradient in concentration of
undersaturated ligands (eL in Table 2) is observed towards the GS, with
increasing eL. Within the fjord, weak ligands were detected at Inner
Basin B (IBB), closest to Moser Glacier. In the fall, total ligand
concentrations (Lt) were elevated everywhere within the fjord, but the
surface ligands were somewhat weaker compared to the late spring. The
greatest concentrations of ligands were found closest to the glaciers (range
11.18–15.42 nM) and in the GS (12.00 ± 2.94 nM). For both seasons,
weak ligands were detected in the subsurface, but a greater concentration in
the fall suggested that these ligands have a local source within the fjord.
Compared to other stations in the fall, we found the plume to contain a
small excess of weak ligands (IBA, 110 m). Interestingly, the highest
concentration of strong ligands (17.44 ± 1.12 nM) among all sites was
in deep water of Station IBA, at 280 m. This is the deepest depth sampled
for Fe-binding ligands, and the IBA bottom depth was 382 m. We found a
down-fjord gradient in ligand strength at the surface, decreasing with
distance from the inner basins (LogKFeL,Fe′cond=11.95 at
IBA, 11.03 at GS).
Ligand concentrations and equilibrium constants detected in
seawater samples. Fe′ is the free (unbound) iron concentration. Lt is
the total ligand concentration. logK is the conditional stability constant.
eL is the excess ligand concentration (eL=Lt- [dFe]). logαFeL′ is the complexation capacity. RFe′ is the ratio of Fe′ of
reoccupied stations, expressed as a percentage.
We determined the free (uncomplexed) Fe concentration (Fe′ in Table 2)
within samples analyzed for Fe-binding ligands. In the surface, a greater
mean concentration of Fe′ was found in the fall (8.74 ± 6.43 pM, n=7) compared to the late spring (2.44 ± 2.18 pM, n=7). Water below
the surface showed similar concentrations for each season (5.8 ± 0.21 pM late spring, 4.61 ± 2.22 pM fall). The greatest concentrations of
Fe′ were observed mid-fjord at the surface (18.7 pM Fe′ at MB, 15.67 pM Fe′
at S3) in the fall.
Dye experiments
To study the transport pathways for dFe, we use numerical passive dyes in
the Hahn-Woernle et al. (2020) regional model of Andvord Bay (see Fig. 1 in
Hahn-Woernle et al., 2020) to track three
potential sources of dFe: surface glacial meltwater (0–50 m) from Bagshawe
and Moser Glacier termini, neutrally buoyant subsurface plume (100 m), and
deep water located in IBA (300 m; as in Methods). Due to numerous inputs and
complex biogeochemical processes which result in observed dFe distributions
in time and space, we simplify the problem by assuming no removal over the
duration of simulated dye experiments. We use this approach to illustrate
the multiple transport pathways for dFe supply to the fjord and surrounding
ocean from December through March (St-Laurent
et al., 2017). The results are presented first for the surface meltwater
experiment, followed by two fixed-volume experiments, referred to as
subsurface and deep dye experiments.
Most of the surface glacial meltwater dye remains in the upper 100 m
throughout the model run, and due to its proximity to the surface, it is
quickly dispersed over a large region by relatively rapid surface currents.
It takes about 10–15 d for the surface meltwater to exit the fjord mouth,
where most ends up in the central and northern Gerlache Strait after 120 d (Fig. S5a).
The subsurface dye (100 m) is spread more rapidly than the deep dye (300 m).
After 8 d, the subsurface dye reaches the fjord mouth, which is 4 d
before the deep dye, implying it has a shorter residence time within the
fjord compared to the deep dye. We loosely define residence time as the
model timestamp at which a fixed fraction of dye remains within the fjord
domain. After 22 d, 25 % of the subsurface dye has left the fjord,
while it takes the deep dye almost twice as long (43 d). At the end of
the 120 d long model run, less than 18 % of the subsurface dye and over
30 % of the deep dye remain in the fjord domain (Fig. S6a). Looking at the
whole model domain in Fig. 1, which includes Andvord Bay and Gerlache
Strait, only 59 % of the subsurface dye and 75 % of the deep dye are
still present after 120 d. The missing 41 % (25 %) has mainly left
the model domain through the Gerlache Strait to the north, where these
waters mix with Bransfield Strait water and subsequently with the southern
Antarctic Circumpolar Front waters.
We analyzed the vertical distribution of the subsurface and deep dyes along
the fjord mouth and horizontally over different depth layers. Within the
first day, the subsurface dye spreads over the depth range of 20 to 125 m
and the deep dye over 125 to 500 m (> 1 % of dye per depth
layer). The subsurface dye leaves the fjord mainly within the upper 200 m.
After 8 d, as the subsurface dye reaches the fjord mouth (Fig. S5b), the
maximum concentration is still found close to its release depth at 100–125 m. Over the next few days, surface layer concentrations (< 20 m)
increase, but the highest concentration is soon found below 125 m (after 2 weeks) (Fig. S6a).
The deep dye remains mainly below 200 m as it passes the fjord mouth
(maximum water depth at the fjord mouth is 360 m). After 12 d, as the
deep dye reaches the fjord mouth, the maximum concentration is found below
300 m depth. In contrast to the subsurface dye, the deep dye remains longer
in the proximity of the fjord mouth and on several occasions re-enters the
fjord, leading to a longer residence time within the fjord (Fig. S5c). The
majority of the deep dye leaves the fjord at depths below 100 m and along
the southwestern coastline. Both dyes, subsurface and deep, have low
concentrations in the upper 100 m of the northeastern flank of the fjord
mouth. This is due to the inflow of external water from the GS along the
northeastern coastline. Throughout the run, the deep dye is confined to the
inner basins of the fjord. In all cases, the dyes remain at higher
concentrations and for longer periods in the subsurface fjord waters than in
the surface layer, which shows faster transport out of the fjord.
DiscussionIron sources in a heavily glaciated fjord
Due to the proximity to glaciers and influence of ice within Andvord, we
hypothesized meltwaters to be an important source of Fe. We focus on
quantifying dissolved, total dissolvable and particulate Fe and Mn, as well
as total dissolvable and particulate Al and Ti. Ratios of these elements are
treated as proxies for contributions of various endmembers. Candidate
endmembers include reducing sediments, weathered crustal material, and
biogenic particles
(Taylor
and McLennan, 1995; Twining et al., 2004). Where possible, we estimate fluxes of
dFe. We begin by examining the relationship between glacial meltwater and
dFe.
Role of surface glacial meltwater
Glacial meltwater at the surface has the potential to be a significant
source of Fe to phytoplankton. There exists a weakly negative correlation
between derived MWf and dFe at the start of the melt season (late spring:
r2=0.29, n= 30; early fall: r2= 0.05, n= 13; Fig. 5c, d). One possible explanation is that increased meltwater at the surface
leads to greater stratification and limits upwelling of Fe-rich deep water,
with the effect augmented by removal processes, such as biological drawdown
and scavenging of dFe onto sinking particles. Indeed, higher rates of
primary production are associated with greater fractions of meltwater in
Andvord Bay (Pan et al., 2020). While we
observe high concentrations of dissolved and particulate trace metals within
glacial ice, we note that the icebergs within Andvord were predominantly
“clean” ice, with little sediment embedded in the ice, indicated by
relatively low dFe and TpFe (for instance, Glacial Ice 3 and 4 in Table 1).
Based on Fe : Al ratios in particles and average values for continental crust
(Taylor and McLennan, 1995), we estimate
87 ± 22 % (n=4) of the particulate Fe contained within Andvord
icebergs is terrigenous in origin. This is consistent with mechanical
weathering of continental crust followed by inclusion of the particles into
the ice (freeze-in; Raiswell et al., 2018). Low Fe : Ti
and Al : Ti ratios also reflect a continental crust source, but it is worth
noting that Glacial Ice 2 had significantly more Mn and Al, relative to
continental Fe and Ti. Further, Mn and Al solid speciation suggests there
are high concentrations of Mn and Al oxides, which may be formed when
crustal material is altered (Raiswell et al., 2018).
It is also possible that fjord sediments were the source of particulate
matter within Glacial Ice 2, which would correspondingly have higher Mn
content (and higher Mn : Fe) than what is found in basal ice interacting with
the subglacial environment
(Hawkings et al., 2020).
Continental crust material delivered to the ocean would contain a relatively
low Mn content compared to Fe (Fe is 4 % w/w in crustal material, while Mn
is 0.08 % w/w, Rudnick and Gao, 2013).
Visual inspection suggests that the majority of the ice within Andvord has
relatively low concentrations of particles, whereas basal ice, with dark
layers of sediment (Glacial Ice 1 in Table 1), will likely skew the average
towards high values (Hopwood et al., 2019). A compilation
of TDFe in icebergs in Antarctica estimated an average concentration of 24 µM (Hopwood et al., 2019). Our two measurements of
LpFe in glacial ice are different (mean for this study is 61 ± 70 µM LpFe, n=2) but are within the range of concentrations determined
in the previous study. Thus, we use our mean concentration (Table 1) as
indicative of the glacial ice composition in Andvord to compute the
following meltwater fluxes. It is important to note that the mean and median
values in glacial ice are likely different, with median values closer to
Glacial ice 1 and 2 concentrations. Using a range of estimated surface
glacial meltwater volume inputs (2.4 × 104 m3 d-1 for this
study based on oxygen stable-isotope mass balance; 1.8 × 104 to 1.2 × 105 m3 d-1, Lundesgaard et al., 2020; 1.1 × 106 m3 d-1, Hahn-Woernle et al., 2020, including other freshwater sources that are not
precipitation) and assuming the input of meltwater is distributed evenly
over the fjord surface layer, we calculate fluxes on the order of 15 to 704 nmol m-2 d-1 for dFe and 10 to 487 nmol m-2 d-1 for dMn.
Based on modeling work in this paper, it will become evident that meltwater
released to Andvord does not stay within the fjord. Additionally,
significant metal loss results from scavenging processes, transferring Fe to
depth on sinking particle surfaces, rendering it inaccessible for
phytoplankton uptake. Still, the availability of excess macronutrients
within Andvord Bay (Fig. 2) means that substantial increases in the supply
of trace metals from glacial meltwater could stimulate growth in the
euphotic zone if light were not limiting (Pan et al., 2020).
The nature of Fe in subglacial plumes
The inner basins consistently show higher beam attenuation and particle
backscattering coefficients than mid-fjord and shelf stations (see Fig. 3
in Supplement in Pan et al., 2019). These signals are attributed to
ultra-fine suspended sediments (< 0.8 µm) contained within a
buoyant plume. The high particle backscattering coefficient in the surface
at all stations in late spring is due to the high concentrations of biogenic
particles associated with the vernal bloom. Inner basins also show local
maxima in beam attenuation coefficients at 70–150 m, as well as approaching
the benthic boundary layer (Fig. 6). Buoyant turbulent plumes that spread
laterally are consistent with the presence of glacial meltwater plumes, or
“cold tongues”, which originate at the glacier grounding line (described
in Domack and Williams, 2011), entrain deep water masses,
and resuspend sediments (Straneo and Cenedese, 2015).
Since ocean temperatures remained below 0 ∘C in Andvord (see Fig. 2), there is little to suggest basal melting of the ice, as is observed
further south along the WAP. It appears reasonable on the basis of the
evidence given above that the subsurface plume signature is subglacial in
origin.
Total digestion and subsequent analyses of marine particles collected within
the plume revealed high concentrations of weathered crustal sediments
(82 %–86 % of TpFe, 61 %–64 % of TpMn) and also ingrowth of authigenic
particles most likely consisting of precipitated Fe- and Mn-oxide phases
(16 %–18 % TpFe, 36 %–39 % TpMn). These results suggest that the origin of
plume particles is a chemically altered crustal source (see Supplement).
Labile particulate Fe is 82 %–100 % of TpFe (Table 1). The Fe : Al and Fe : Ti
in plume particles (0.24 ± 0.01 and 9.25 ± 0.24 mol mol-1, respectively) were elevated above the average crustal ratios
(0.2 mol mol-1 Fe : Al, 7 mol mol-1 Fe : Ti), which implies these
samples are enriched in Fe relative to both crustal Al and Ti. In agreement
with these results, particulate Al : Ti (39 ± 1 mol mol-1) was
elevated above crustal ratios (35 mol mol-1), indicating a large oxide
fraction is associated with this particulate matter, since the total
dissolvable fraction, more enriched in Al than the total particulate
fraction, forms when Al is heavily scavenged on to oxy(hydr)oxides at
oceanic pH levels (Kryc et al., 2003).
This substantiates our claim that most of the Fe found in the plume is
weakly adsorbed to particles and recently precipitated, since dilute HCl
leaches liberate the most labile forms of Fe, most likely oxy(hydr)oxides
(e.g., ferrihydrite) in addition to some Fe from clays. This could include
oxides directly precipitated from the anoxic subglacial source, as well as a
potential fraction of oxides derived from fjord sediments and porewaters
entrained at the grounding line.
Cold-water glaciers are locations where the subglacial environment flows
directly into the fjord with minimal mixing with seawater since lower
meltwater production cannot induce much turbulence and vertical currents at
the glacier face. We find elevated concentrations of dMn (∼ 15 nM, Fig. 2) emanating from the inner fjord, indicative of the reducing
conditions beneath Moser and Bagshawe glaciers, consistent with other
studies of subglacial environments (Henkel et al., 2018; Zhang et al., 2015). Compared
to subglacial fluids in contact with bedrock, we report relatively low
concentrations of dFe within the plume (8.75 ± 2.25 nM) < 1 km
away from the glacier terminus. If we assume a MWf of 0.01 for the plume,
and assuming a deep fjord seawater concentration of zero, the subglacial
meltwater endmember would have a dFe concentration of 875 ± 231 nM,
which is higher than the mean value for TDFe measured within the plume
(347 ± 160 nM), suggesting settling loss through flocculation is likely
occurring even within 1 km of the grounding line. The subglacial endmember
dFe estimated here is lower than the range used to parameterize subglacial
inputs from ice shelves to the Southern Ocean (SO) (3–30 µM in Death et al., 2014). The long
residence time and enhanced chemical weathering beneath large glaciers in
west Antarctica (PIG, Thwaites Glacier) could result in larger accumulations
of dissolved trace metals in subglacial outflow, compared to small glaciers
located along the WAP. However, subglacial discharge from large glaciers
occurs at some distance from the open continental shelf waters because of
the broad floating horizontal ice shelves, which make up about 45 % of the
Antarctic coastline (Schodlok et al., 2016).
Scavenging during advective transport under ice shelves reduces the flux of
dFe upwelled into the euphotic zone tens to hundreds of kilometers away from the point
source of meltwater discharge (Krisch et al., 2021). Our
results suggest that assumptions of high export efficiency to the coastal
ocean (i.e., using endmember dFe concentrations from glacial runoff and
groundwaters as in Death et al., 2014) potentially overestimates dFe supply from
anoxic subglacial environments because significant dFe boundary scavenging
occurs during lateral transport. It is therefore important, albeit
difficult, to parameterize scavenging and removal at the ice–ocean interface
as all studies suggest intense removal of dFe on short time and length
scales.
Role of sediments
Analyses of Andvord Bay sediments reveal they are compositionally distinct
from temperate fjords consisting of poorly sorted fine silt and clay, many
dropstones, suspension deposits and ice-rafted debris
(Eidam et al., 2019). Sediment
accumulation rates are spatially variable, but a weak along-fjord gradient
is present. These deposits suggest sluggish circulation, allowing for the
deposition of sediments close to their source, likely through flocculation
processes (Cowan and Powell, 1990).
Profiles of beam attenuation coefficient show the highest concentration of
particles in the inner basins compared to other station locations (see
Fig. 4 in Pan et al., 2019). There is little evidence for mechanical resuspension
through gravity flows (i.e., turbidites) along the steep basin walls, yet
such processes could be responsible for the near-bottom elevation in water
column particles (Eidam et al., 2019).
The presence of elevated particles in the inner basins is accompanied by the
greatest concentrations of dissolved and labile particulate Fe and Mn (Fig. 6), demonstrating the potential of resuspended fjord sediments as a source
of dissolved trace metals.
Based on the core top porewater profiles, we estimate the sedimentary efflux
to be 43.7 µmol m-2 d-1 for dFe and 7.2 µmol m-2 d-1 for dMn, due to diffusion alone (Fig. S2). This magnitude of flux
was also observed in the shelf sediments in the vicinity of South Georgia
Island in the SO (Schlosser et al., 2018). Abundant epibenthic fauna
were observed within Andvord Bay, which mix the sediments through
bioturbation while consuming labile organic matter. Taylor et al. (2020) used
234Th as a proxy to investigate the effect of bioturbation on short
timescales and found Andvord Bay sediments possess a high mixing coefficient
down to 5 cm (Db=36 cm2 yr-1) consistent with greater
deposition and subsequent utilization of organic carbon in the sediments
compared to data from the adjacent continental shelf. We believe this
accurately reflects the conditions in this fjord: bioturbation by dense
aggregations of epibenthic fauna within the basins.
These flux estimates are not surprising when compared to a global
compilation of in situ measurements of sedimentary efflux of dFe, which is on
average ∼ 12 µmol m-2 d-1 for water masses
located on continental margins and with O2 concentrations greater than
63 µmol L-1
(Dale et al., 2015). The bottom
water oxygen concentration in Andvord Bay always exceeded 230 µmol L-1. The bottom water O2 concentration for OB at the time
sediments were cored was 270 µmol L-1. Abundant epibenthic fauna
found within Andvord (Ziegler et al., 2017,
2020) would introduce oxygen to the upper few centimeters of the sediments
through bioturbation and could decrease the efflux of reduced metals
(Severmann et al., 2010). Taylor et al. (2020) found Andvord Bay sediments possessed high inventories of 210Pb
relative to open shelf and Palmer Deep stations, indicating a high mixing
coefficient for sediments between 7 and 22 cm depth on timescales of 100 years (Taylor et al., 2020). The
effect of this process is mixing of oxide- and organic carbon-rich surficial
sediments further down in the core on short to long timescales. These dFe
flux estimates, together with solid phase speciation results, highlight the
importance of rapid oxidation and precipitation occurring at the seawater
interface, which effectively retain most Fe as oxy-hydroxides within the
sediments (Burdige and Komada,
2020; Laufer-Meiser et al., 2021). The Fe oxides are enriched within the
penetration depth of oxygen (∼ 0.5 cm, Fig. S2 inset) and once
bioturbated downward could be a source of dFe following microbial cycling.
Multiple local maxima of porewater dFe were observed deeper in the cores.
While dissimilatory iron reduction would be a source for Fe, oxidation of Fe
with bottom water O2 and Mn(IV) is important sinks and exert a control
on the dFe concentration of deep water masses. The deep inner basin water
column samples had high dFe concentrations concomitant with high LpFe
concentrations (Figs. 2, 6), suggesting some loss of porewater dFe to the
water column and rapid formation of authigenic Fe mineral particles.
Therefore, the fluxes calculated from porewater profiles are upper limit
estimates because they do not account for oxidative losses at the
sediment–water interface (e.g., Burdige and Komada, 2020). In the Ross Sea,
Marsay et al. (2014) estimated spatially variable efflux spanning 0.028–8.2 µmol m-2 d-1 based on water column dFe profiles, which might
better illustrate the net effect of rapid oxidation of reduced Fe, for which
large uncertainties remain
(Marsay et al., 2014).
Due to weak midwater circulation, low tidal energy, and stratification of
the surface, a disconnect between deep water masses enriched in dFe and the
surface of Andvord Bay persists during prolonged quiescent periods. For
these reasons, we believe most sedimentary-sourced Fe from diffusion and
resuspension is restricted to deep water masses and therefore plays a minor
role in dFe concentrations within the upper water column. There is
potential, however, for resuspension and entrainment of surface sediments
where subglacial meltwater discharges at the grounding line. Due to the low
inferred volume of discharge and lack of strong tides in Andvord Bay, it is
unclear if resuspended sediments contribute to the total particulate mass
within the plume.
The Mn : Fe ratio is a useful signature of the source of dissolved and
particulate trace metals in Antarctica and has been applied to the PAL LTER
data set (Annett et al., 2017).
Applying this same framework to our study, we find that water column
dissolved trace metals are heavily influenced by surface glacial ice melt
and subglacial meltwater and to a lesser extent sediment sources within
the fjord, irrespective of season, depth, and meteoric water input (Fig. 7).
Due to the shorter residence time of dFe relative to dMn (i.e., inorganic
oxidation of Mn(II) is 107 times slower than Fe(II)
Sherrell et al., 2018), we would expect the
porewater dissolved Mn : Fe ratio to tend towards higher values once exposed
to the seawater oxidative front. We therefore cannot rule out porewaters as
a source of dMn to the water column. A similar process occurs within the
plume, where the elevated dissolved Mn : Fe (0.65 mol mol-1) relative to
labile particulate Mn : Fe (0.024 mol mol-1) shows the effect of rapid
conversion of Fe to authigenic mineral particles. Although we do not have
comparable measurements for sedimentary labile particulate Mn, based on
labile particulate Mn : Fe, we find that the water column labile particulate
Mn : Fe ratio is precisely the same ratio as particles found within the
subglacial plume, again irrespective of when and where the sample was taken
(Fig. 8), suggesting plume particles remain suspended throughout the fjord
water column.
Dissolved Fe and Mn plotted for water column samples. The color bar
shows depth (a) or meltwater fraction (b). For both
panels, the December 2015 cruise is indicated by filled circles, and the April 2016 cruise is indicated by filled diamonds. The lines indicate the average
Mn : Fe ratio for each candidate source.
Labile particulate Fe and Mn plotted for water column samples. The
color bar shows the influence of depth (a) or meltwater fraction (b). For both panels, the December 2015 cruise is indicated by filled
circles, and the April 2016 cruise is indicated by filled diamonds. The lines
indicate the average ratio of Mn : Fe determined from candidate sources.
Organic speciation of dissolved Fe
It has been hypothesized that excess ligands (eL= [Lt] - [dFe])
increase the solubility of particulate Fe phases
(Thuróczy
et al., 2011; Gledhill and Buck, 2012; Wagener et al., 2012; Tagliabue et al., 2019). The
persistence of exchangeable pools of dFe would therefore be controlled
primarily by particle assemblage and organic ligand complements, where pFe
dominates total Fe speciation. We observe consistency between late spring
and fall in the relative contribution of dFe to total Fe (4 %–5 % of
LpFe, respectively), implying dFe is controlled by scaling closely to LpFe
(Fig. 5g, h) since both pools have large interseason differences. An increase
in eL between seasons is observed (average 2.1 ± 1.3 nM late spring n=9,
6.0 ± 3.2 nM fall n=12). The ligands are likely produced during
microbial high-affinity uptake or remineralization processes following the
termination of a bloom (Gledhill
and Buck, 2012; Hogle et al., 2016). The only subsurface sample to contain strong
Fe-binding ligands is the deep inner basin adjacent to Bagshawe Glacier
(IBA), possibly indicating these ligands have a sedimentary source. It
appears, based on these results, ligands in Andvord Bay have the capacity to
complex additional Fe input, as well as prevent significant loss due to
scavenging
(Thuróczy et al., 2012).
The nature of these ligands, taken together with the low concentration of
dFe and abundance of LpFe within the plume, leads us to speculate that Fe
minerals are the target for ligand-mediated mineral dissolution and perhaps
microbial uptake, previously hypothesized to occur in deep-sea hydrothermal
vent plumes (Li et al., 2014). In the fall, despite a greater
eL, a lower average conditional stability constant of the ligand pool
results in lower complexation capacity and inferred ability to compete with
particle binding sites
(Ardiningsih et al.,
2021). However, the ratio of dFe to LpFe does not reflect a greater
enrichment of particles.
While we observe a seasonal increase in the excess ligand concentration,
there is no significant change in the ratio of Lt : dFe (late spring
1.8 ± 0.5, fall 2.0 ± 0.7). In the Amundsen sector, Thuróczy
et al. (2012) found waters heavily influenced by the Pine Island Glacier to have
Lt : dFe ratios < 2.5 throughout the water column, with
relatively weaker ligands compared with those found in the highly productive
surface waters of the polynya. These findings are similar to an Arctic
study, where Ardiningsih et al. (2021) detected weaker ligands close to the 79 N
Glacier terminus along the northeast Greenland shelf compared to the
adjacent open ocean. We too identify weaker Fe-binding ligands associated
with the glaciers, and only at MB and Sill 3 did we observe elevated
Lt : dFe (3.13 and 2.99, respectively, in the fall). It is possible that
sea ice released strong Fe-binding ligands in Andvord that remained in the
surface until sampling in the late spring
(Lannuzel
et al., 2015). The presence of strong excess Fe-binding ligands at IBA and S3
during the bloom onset also corresponds to elevated NO3- : dFe (data
not shown) above the threshold for potential Fe limitation of coastal
diatoms in the California Current region (10–12 µmol nmol-1; King and Barbeau, 2011). The presence of strong
Fe-binding ligands might suggest an active microbial strategy in this
coastal region to sequester additional Fe from particulate phases during the
bloom initiation.
The intense seasonality in primary production and the presence of an
undersaturated ligand pool could further increase the bioavailability of
particles for downstream communities, where particles within the water
column are rare. We calculated the capacity for the free Fe-binding ligands
to bind Fe (αFeL′=1+ (eL⋅K)). Calculations
of αFeL′ are included for each sample in Table 2 as well as the
inter-seasonal percent change in Fe′ for reoccupied stations (RFe′). We
find the αFeL′ increased between late spring and fall at IBA
and Sill 4, while a decrease was found at the IBB, Sill 3, and Gerlache Strait
stations. While all reoccupied stations show an increase in the Fe′
concentration (RFe′), the percent change is greatest where αFeL′ decreased in the fall. Thus, the seasonal increase in Fe′
reflects the increase in dFe concentrations as well as lower complexation
coefficient of weaker Fe–ligand complexes, which contribute most to dFe
speciation in the fall and are associated with surface waters adjacent to
glaciers.
These first results of organic speciation of dFe in an Antarctic fjord
highlight the importance of seasonal ligand sources in establishing the
solubility of new Fe entering the coastal ocean. Accurate ligand pools are
not currently represented within SO biogeochemical models
(Death
et al., 2014; Oliver et al., 2019; Person et al., 2019; St-Laurent et al., 2019). During the bloom
initiation, overall ligand strengths are higher than in the fall; however,
concentrations of ligands increase following the bloom. Concurrently, dFe
concentrations increase and do not saturate the ligands to the same extent
as in late spring. This is due to a greater relative increase in ligand
concentrations compared to dFe. Ligand-mediated complexation has the
potential to greatly expand the spatial extent over which solubilization of
particulate Fe occurs and could be critical for sustaining productivity over
a larger geographical region
(Lippiatt et al., 2010; Ardiningsih et al., 2021). Thus, the size, sinking rate, and
composition of particles is critical to their lateral transport and
reactivity over time with excess ligands. Our understanding of how
cryospheric Fe is transformed after entering the coastal ocean is an
important step towards understanding its impact on marine productivity and
global biogeochemical cycles of the macronutrients. For the marine Fe cycle,
these geochemical transformations control the bioavailability of Fe, while
vertical advection and mixing supply this critical micronutrient to the
surface ocean and the euphotic zone.
Using dye experiments to explore Fe sources and export
Rapid communication between the surface and subsurface water masses occurs
during katabatic wind events. The large magnitude of vertical shear
initializes an upwelling cell close to the inner basins of the fjord. Using
an idealized model of a fjord, Lundesgaard et al. (2018) found that katabatic
winds can laterally export the surface layer, depending on wind velocity,
elapsed time of the event, and whether the wind is along-fjord versus
off-axis. Within this idealized model of the fjord, the forcing event leads
to outcropping of deeper isohalines (up to 0.3 PSU greater) at the surface
along the northern flank of the fjord, corresponding to upwelling (see
Fig. 11 in Lundesgaard et al., 2019). Wind-induced overturning circulation, along
with deepening of the mixed layer by up to 25 m, would increase surface dFe
concentrations at Sill 3. These general model results showed that
wind forcing caused water at depths of 50–150 m to upwell rapidly (within 24 h) near the glacier termini. This is an important consequence explored
further in the highly resolved model representation of the study region by
Hahn-Woernle et al. (2020).
The results of the dye experiments allow for the determination of fluxes,
either prescribed (in the case of glacial meltwater) or as a result of wind
forcing. St. Laurent et al. (2017) applied similar methods in the Amundsen Sea with
explicit coupling of sea ice–ice sheet–ocean interactions
(St-Laurent et al., 2017). In a more rigorous
biogeochemical model, which included ocean interactions with both sea ice
and ice shelves, as well as parameterized Fe reactions, the productive
waters in the Amundsen Sea Polynya were supplied by an advected source of
dFe from the “meltwater pump” and coastal currents, but this model lacked
explicit contributions of subglacial Fe
(St-Laurent et al., 2019). These prior
modeling results highlight the importance of lateral exchange of surface
water masses, providing the impetus to investigate the export of the surface
water out of the fjord mouth as explored in the following section.
Surface meltwater Fe sources and export
Given that the MWf varied from 1 %–2.5 % within Andvord Bay during the time
of sampling, it is expected that the input of glacial meltwater throughout
the melt season would supply some dFe to the surface. We extracted vertical
profiles of MWf from the model at Sill 3 and Gerlache Strait stations and
found that glacial meltwater originating from Bagshawe and Moser glaciers
reaches maximum concentration during the summer bloom (late January 2016)
and is relatively constrained to the upper 25 m (Fig. S7b). In early
February, when the bloom was terminated, glacial meltwater concentrations in
the fjord decreased due to a weakening meltwater input and lateral
dispersal. The weakening input is designed to reflect the seasonal cycle of
ice melting. Ocean circulation dispersed the meltwater into the Gerlache
Strait, as shown by a progressive increase in meltwater in the upper water
column throughout the melt season (Fig. S7a). If the volume flux of
meltwater input is indeed correlated to the seasonal air temperature cycle,
as it is parameterized in the model, the results in Fig. 3 would reaffirm
that meltwater is an important control on the accumulation of phytoplankton
biomass within Andvord Bay (Pan et al.,
2020).
The effect of the wind in driving vertical fluxes will vary with wind
direction and location within the fjord. The vertical velocity is analyzed
for the observation site at Sill 3 and in front of Bagshawe Glacier (IBA).
The latter site is an example location for which katabatic winds are
expected to lead to intensified upwelling and is also the location of the
subsurface and deep dye experiments. Figure 9a and b depict the
relationship between the katabatic wind events and vertical velocities at 20 m: landward-blowing wind generally leads to downwelling, while
seaward-blowing katabatic wind leads to upwelling. Based on observations of
dFe from the late spring prior to a wind event that started on December 11
([dFe] at 20 m: 1.97 nM at S3, 2.01 nM at IBA), and the modeled maximum
vertical velocities during the wind event (2.09 × 10-5 m s-1 at
S3, 5.08 × 10-5 m s-1 at IBA), we computed the upwelling flux of
dFe into the surface (20 m) at Sill 3 and IBA to be 3.54 and 8.81 µmol m-2 d-1, respectively.
These results shed light on the spatial heterogeneity of upwelling
conditions within the fjord. Model results for Sill 3 are supported by late
spring observations of elevated dFe and low meltwater fraction at this
station (Fig. 3). This is also corroborated by increases in surface dFe
concentrations observed during repeat occupations of Sill 3 station before
(3.19 ± 1.53 nM dFe) and after the wind event (3.94 ± 1.92 nM dFe). We argue that these punctuated periods of upwelling could be a
substantial source of dFe to surface waters in Andvord Bay. Further, this
supply, together with the flux of glacial meltwater, provides dFe to fuel
phytoplankton community growth.
The efficiency with which wind events export the fjord surface water is
explored in the glacial meltwater dye experiment. To account for the
changing amount of meltwater in the fjord, export across the fjord mouth in
Fig. 9c is given as the percentage of the total amount of dye present within
the fjord to resolve the effect of katabatic winds on dispersal dynamics of
Fe-rich sources. The meltwater dye experiences up to a 28-fold increased
export into the Gerlache Strait during periods of strong along-fjord wind,
primarily through the surface. To analyze the correlation between
along-fjord wind velocity and the relative meltwater export, we first apply
a 24 h Gaussian filter to the relative export of glacial meltwater (Fig. 9), to exclude tidal signals. Applying the same filter to the wind time
series, we find the wind and export data are positively correlated (r= 0.628). The correlation between export and along-fjord winds supports the
results by Lundesgaard et al. (2019), who found that katabatic winds control the
export of fjord water. This has important implications for the dispersal of
Fe-rich waters downstream, which eventually mix with Fe-poor waters located
on the continental shelf (Annett et al., 2017).
(a) Modeled vertical velocities at 20 m for the following
locations: Bagshawe Glacier (IBA), Sill 3, and the fjord region average. The 24 h Gaussian filter applied to time series of along-fjord wind velocity (b) and relative meltwater export out of the fjord (c). Wind events exceeding an
absolute velocity of 8 m s-1 are indicated by vertical dashed lines.
Wind speed data are based on bias-corrected RACMO model output for the center
of the fjord, used to force the ROMS model. The transport of meltwater dye
is shown relative to the total amount of meltwater dye within Andvord Bay to
focus on the physical dynamics and not the changes in volume of dye present
in the fjord.
Subsurface and deep sources supplying Fe to export
As discussed in the previous section, periods of vertical mixing due to
overturning circulation and mixed layer deepening are shown to occur during
katabatic wind events (Lundesgaard et al., 2019, 2020). This could be an important
mechanism for supplying additional dFe to the fjord surface from the
subglacial plume. We examine this possibility here using the subsurface and
deep dye tracers. Prior to the wind event on 11 December, the subsurface dye
increases gradually in the upper 20 m (Fig. S6b). With the onset of the wind
event, the vertical transport of the subsurface dye into the upper 20 m
intensifies and reaches a maximum of 32.7 × 103 m3 d-1. In
comparison, the deep dye does not enter the upper 20 m prior to the wind
event, and its maximum vertical transport is only 4.2 × 103 m3 d-1. It follows that katabatic wind events increase mixing in front of
Bagshawe Glacier and have a particularly strong effect on water masses at
intermediate depth. Assuming a mean concentration of 8.75 nM dFe for the
subsurface plume (Table 1) and 8.68 nM dFe for deep (∼ 300 m)
IBA waters in the late spring, these periods of vertical mixing correspond
to dFe fluxes of up to 2.81 nmol dFe m-2 d-1 and 0.36 nmol m-2 d-1 (3.17 nmol m-2 d-1 combined) based on the
subsurface dye and deep dye, respectively. Following the katabatic wind
event, which lasted approximately 11 d, model results show that 36 % of
the subsurface dye has shoaled above 75 m, with 10 % of dye found within
the surface layer (< 20 m, Fig. S6b). Of the deep water dye, less
than 1 % is found within the surface layer. The behavior of the deep water
masses suggests an insignificant contribution of deep water masses to the
surface hydrography and thus to surface dFe inventory. The vertical fluxes
estimated in this section are interpreted as a lower bound for the
contribution of the subsurface plume, since the modeled subglacial plume is
a fixed volume, when in reality, subglacial meltwater might be supplied
continually throughout the melt season. Compared to the flux of surface
glacial meltwater input, and the flux due to subsurface and deep water
mixing, the upwelling flux generated by wind events is the largest by an
order of magnitude.
The quicker export of the subsurface dye, relative to the deep dye, and
therefore the low surface dye concentration, is mainly due to its proximity
to the ocean surface (Fig. S5b). The upper water column is controlled by
katabatic winds, which exports the surface layer out of the fjord mouth. In
contrast, the deep dye is exported more slowly and is more continuously
released to Gerlache Strait (Fig. S5c). These modeling results provide
evidence for the flushing of fjord water to the Gerlache Strait, which
coincides with periods of intensified winds. Thus, katabatic winds are
important both for replenishing the surface Fe concentrations from the
subglacial plume and for exporting Fe-rich surface waters. It is
reasonable to assume that in the absence of a strengthened buoyancy-driven
overturning circulation, sources from fjord sediments are negligible in
supplying the surface with dFe in Andvord Bay.
Conceptual diagram showing the important seasonal sources of new
Fe during the growth and melt season. The red arrows indicate the major
fluxes (in µM m-2 d-1), with the size ranges showing
the uncertainty in the measurement – some fluxes are difficult to quantify.
These fluxes also vary from season to season and from location to location
and may even be going through long-term changes due to human influences,
such as climate change, though this is not shown here. The small arrows show
internal transformations of Fe, which play an important role in the supply
of Fe to phytoplankton. See text for a description of important processes
highlighted by circled numbers.
Wind driven meltwater export from WAP fjords
Given that the west Antarctic Peninsula hosts the greatest number of
glaciomarine fjords on the continent, and multiple katabatic wind events
occur throughout the year, wind events can play a crucial role in the
export of Fe and Mn to the larger shelf water region. The modeled export of
meltwater integrated over the week after the wind event on December 11 is
38 × 107 m3, which is about 43 % of the meltwater input during the
same time. For comparison, during the following week, with relatively calm
wind conditions, only 20 % of the meltwater input is exported. We estimate
the Fe export to be 272 mol dFe per week and 245 mol dMn per week for
this event. However, the warming climate may lessen the likelihood for
pulsed export of meltwater-derived Fe by intensifying coastal currents due
to declines in sea ice (Moffat et al.,
2008) and reduced surface cooling, decreasing the velocity and frequency of
katabatic winds over the west Antarctic Ice Sheet
(Bintanja et al., 2014).
The large variability in inferred dFe content of glacial meltwaters along
the WAP (Annett et al., 2017)
means that supply likely depends on fjord-specific processes and future
changes in ice volume. Advected sources of dFe remain the largest
contribution (∼ 50 %) to the inventory on the productive
continental shelves
(De Jong et al., 2015),
while reducing marine sediments are thought to be the main source of dMn
(Annett
et al., 2015; Sherrell et al., 2015, 2018). Therefore, we believe that a latitudinal
assessment of WAP fjords could begin to address variable responses to ocean
and atmospheric forcing in these productive ecosystems. Indeed, less than
160 km south of Andvord Bay, observations of warm modified UCDW intrusions
and an invigorated “meltwater pump” present an alternative mechanism for
sustaining local primary production in Barilari Bay, a glaciomarine fjord
(Cape et al., 2019).
The scope of our results should be highlighted. If we assume Andvord Bay is
representative of a typical cold-water fjord, and similarly, Barilari Bay is
representative of a warm-water fjord (6 % MWf at surface; Cape et al., 2019),
then we can estimate the glacial meltwater export resulting from a single
wind event for the entire western coast of the WAP (see Supplement). A total of 3.6 × 1010 m3 (36 km3) of surface glacial meltwater is exported
seaward, which corresponds to 2.0 × 106 mol dFe and 1.8 × 106 mol dMn. Thus, katabatic winds are highly efficient at delivering surface
meltwater produced near the coast to the continental shelves and Antarctic Circumpolar Current (ACC), where
Fe and Mn limit and co-limit primary production
(Browning et al., 2021). However, this volume of surface
meltwater exported per year from WAP fjords is small compared to the total
basal meltwater production rate due to warm ocean temperatures for the
largest ice shelves in Antarctica. Using highly accurate remote sensing
topographic measurements, Adusumilli et al. (2020) found that the major Antarctic
ice sheets have a steady-state meltwater production value of 1100 ± 60 km3 yr-1. In a different modeling study, it was estimated that 300–800 km3 yr-1 meltwater enters the SO accounting for observed
trends in SO sea surface temperature, sea ice expansion, and sea surface
height (Rye et al., 2020). The “effective” fluxes of Fe and Mn may be lower than
what was calculated here because of the non-conservative behavior of these
elements during their lateral advection to the shelf. It should be noted
that the WAP feeds most directly into the Antarctic Circumpolar Current
(ACC), which advects modified coastal waters downstream to the productive
Scotia Sea region, potentially magnifying the ecological impact of WAP fjord
meltwater production.
Andvord Bay as a source of Fe and Mn to shelf waters of the
western Antarctic Peninsula
We have argued that, for glaciers terminating in cold-water fjords with a
resultant absence of buoyancy-driven upwelling, the interaction of the ice
sheet, atmosphere, and surface ocean is important for resupplying the
surface waters with Fe throughout the summer season. Using a high-resolution
ROMS model of the study region, we showed katabatic wind events result in
pulsed export of the surface layer to the adjacent shelf water, while
upwelling and vertical mixing entrains subglacial plume water in the inner
fjord. Observed surface concentrations of dFe in fall lend support to these
modeled dynamics since elevated concentrations of dFe and meltwater are
found within the inner fjord and at Sill 3 (see Fig. 3). At both fjord
locations, upwelling of subsurface water masses occurs, potentially
entraining subglacial plume water. We summarize the findings of this study
in a conceptual diagram showing important seasonal sources of Fe during the
growth and melt season (Fig. 10). We highlight important processes in the
diagram using circled number notation. We found ocean temperatures are cold ①
and do not melt the fronts of glaciers, but warm summer atmospheric
temperatures contribute to the surface melting of glacial ice ②. Variability
in dissolved and particulate Fe concentrations in glacial ice imposes large
uncertainties in the calculated Fe flux associated with melting. Iron occurs
in glacial ice predominantly in the form of refractory Fe-bearing mineral
particles ③. Only a small fraction of Fe from these particles may be
stabilized by excess organic ligands. Another Fe source is fjord sediments ④, though there is considerable uncertainty shown in the magnitude of this
flux because evidence indicates that a significant fraction of porewater Fe
rapidly precipitates at the oxidative front, forming a rich surface layer of
Fe oxyhydroxides at the sediment surface ⑤. Intense bioturbation of fjord
sediments mixes the surface sediments downwards, fueling redox processes in
deeper sediment layers. The dFe that escapes this sink enriches deep waters
within the fjord basins. Small amounts of subglacial meltwater discharge
enter the ocean and form turbid buoyant subsurface plumes ⑥. Within the
plumes, speciation is dominated by high concentrations of labile authigenic
Fe-bearing particles that can be solubilized by Fe-binding organic ligands ⑦. Seaward-blowing katabatic winds ⑧ occur episodically and cause upwelling
and vertical mixing, supplying additional Fe to the surface phytoplankton
assemblage. These intense energetic periods facilitate the dispersion and
export of surface Fe, Mn, and meltwater away from the fjord where it is
advected downstream in the Gerlache Strait and into the Bransfield Strait ⑨.
In Andvord Bay, primary production will be sensitive to future changes in
subglacial discharge as Antarctic glaciers continue to melt in response to
oceanic and atmospheric warming (Smith et al.,
2020). In the short term, increased Fe and Mn supply may increase primary
production. Conversely, in the long term, increased meltwater discharge will
generate a greater flux of sediment to the fjord
(Brinkerhoff et al., 2017), reducing light availability for
primary producers, while stratifying the upper water column and preventing
nutrient replenishment (Hopwood et al., 2018). A key question
outside the scope of this research is how the quantity and quality of
Fe-binding ligands will change in the future. To a first approximation,
decreases in the magnitude of local phytoplankton blooms and associated
ligand sources is expected to reduce efficacy of solubilization of
particulate Fe and natural fertilization downstream resulting from this
fjord. This climatic trend is not yet realized within Andvord Bay
(Eidam et al., 2019) but is expected to
decrease dFe export through increased scavenging and sedimentation, further
resembling high-Arctic and temperate fjords
(Hopwood et al., 2016).
Data availability
All CTD data from this study are available at the US Antarctic Program (USAP)
Data Center: 10.15784/601158 (Vernet et al., 2019).
The supplement related to this article is available online at: https://doi.org/10.5194/bg-18-6349-2021-supplement.
Author contributions
KOF designed the study, conducted the analyses, and led the writing of the
manuscript. LHW performed numerical dye simulations. RMS, VJR, and KB
assisted in the preparation of multi-elemental analyses. DB provided data
for sediment core analyses. LHW, RMS, DB, MV, and KAB were
involved in discussing the results and their implications and contributed
to the drafting of the manuscript.
Competing interests
The authors declare that they have no conflict of interest.
Disclaimer
Publisher’s note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Acknowledgements
The authors would like to thank all participating principal investigators
and their affiliates during the NSF FjordEco project.
Lauren Manck (University of Montana) assisted with sampling efforts during
NBP1603. We would like to thank the captain and crew of R/V Laurence M. Gould and
RVIB Nathaniel B. Palmer and United States Antarctic Program contractors. We
also thank Brian Powell (University of Hawai'i, Manoa) for helpful
comments and for providing resources for the modeling effort. We would also
like to thank the two anonymous reviewers for their attention to detail.
Their efforts have greatly improved this paper.
Financial support
This research has been supported by the National Science Foundation (grant
no. PLR-1443705). Funding for speciation work was funded through an NSF
grant (NSF OCE-1558841). Kiefer Forsch was supported by an NSF GRF (NSF 15-597).
Review statement
This paper was edited by Jack Middelburg and reviewed by Rob Middag and one anonymous referee.
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