Freshwater discharge from glaciers is increasing across the Arctic in
response to anthropogenic climate change, which raises questions about the
potential downstream effects in the marine environment. Whilst a combination
of long-term monitoring programmes and intensive Arctic field campaigns have
improved our knowledge of glacier–ocean interactions in recent years,
especially with respect to fjord/ocean circulation, there are extensive
knowledge gaps concerning how glaciers affect marine biogeochemistry and
productivity. Following two cross-cutting disciplinary International Arctic
Science Committee (IASC) workshops addressing the importance of glaciers
for the marine ecosystem, here we review the state of the art concerning
how freshwater discharge affects the marine environment with a specific
focus on marine biogeochemistry and biological productivity. Using a series
of Arctic case studies (Nuup Kangerlua/Godthåbsfjord, Kongsfjorden,
Kangerluarsuup Sermia/Bowdoin Fjord, Young Sound and Sermilik Fjord), the
interconnected effects of freshwater discharge on fjord–shelf exchange,
nutrient availability, the carbonate system, the carbon cycle and the
microbial food web are investigated. Key findings are that whether the effect
of glacier discharge on marine primary production is positive or negative
is highly dependent on a combination of factors. These include glacier type
(marine- or land-terminating), fjord–glacier geometry and the limiting
resource(s) for phytoplankton growth in a specific spatio-temporal region
(light, macronutrients or micronutrients). Arctic glacier fjords therefore
often exhibit distinct discharge–productivity relationships, and multiple
case-studies must be considered in order to understand the net effects of
glacier discharge on Arctic marine ecosystems.
Introduction
Annual freshwater discharge volume from glaciers has increased globally in
recent decades (Rignot
et al., 2013; Bamber et al., 2018; Mouginot et al., 2019) and will continue
to do so across most Arctic regions until at least the middle of this
century under a Representative Concentration Pathway (RCP) 4.5 climate
scenario (Bliss et al., 2014; Huss and Hock, 2018). This increase in discharge
(surface runoff and subsurface discharge into the ocean) raises questions
about the downstream effects in marine ecosystems, particularly with respect
to ecosystem services such as carbon sequestration and fisheries (Meire
et al., 2015, 2017; Milner et al., 2017). In order to understand the effect
of glaciers on the present-day marine environment and under future climate
scenarios, knowledge of the physical and chemical perturbations occurring in
the water column as a result of glacier discharge and the structure,
function, and resilience of ecosystems within these regions must be
synthesized.
Quantifying the magnitude of environmental perturbations from glacial
discharge is complicated by the multiple concurrent, and occasionally
counteracting, effects that glacial discharge has in the marine
environment. For example, ice-rock abrasion means that glacially fed rivers
can carry higher sediment loads than temperate rivers (Chu et al.,
2009; Overeem et al., 2017). Extensive sediment plumes where glacier
discharge first enters the ocean limit light penetration into the water
column (Murray
et al., 2015; Halbach et al., 2019), and ingestion of glacial flour particles
can be hazardous, or even fatal, to zooplankton, krill and benthic fauna (White
and Dagg, 1989; Włodarska-Kowalczuk and Pearson, 2004; Arendt et al.,
2011; Fuentes et al., 2016). However, these plumes also provide elevated
concentrations of inorganic components such as calcium carbonate, which
affects seawater alkalinity (Yde et al., 2014;
Fransson et al., 2015), and dissolved silicic acid (hereafter Si) (Brown
et al., 2010; Meire et al., 2016a) and iron (Fe) (Statham et al., 2008;
Lippiatt et al., 2010), which can potentially increase marine primary
production (Gerringa et
al., 2012; Meire et al., 2016a).
Locations of five key Arctic field sites, where extensive work
bridging the glacier and marine domains has been conducted, discussed herein
in order to advance understanding of glacier–ocean interactions. 1: Kongsfjorden (Svalbard); 2: Young Sound (E Greenland); 3: Sermilik (SE
Greenland); 4: Nuup Kangerlua/Godthåbsfjord (SW Greenland); 5: Bowdoin Fjord/Kangerluarsuup Sermia (NW Greenland).
The impacts of glacier discharge can also depend upon the spatial and
temporal scales investigated (van de Poll et al., 2018). In
semi-enclosed Arctic coastal regions and fjord systems, summertime discharge
typically produces strong, near-surface stratification. This results in a
shallow, nutrient-poor layer which reduces primary production and drives
phytoplankton biomass deeper in the water column (Rysgaard
et al., 1999; Juul-Pedersen et al., 2015; Meire et al., 2017). On broader
scales across continental shelves, freshening can similarly reduce vertical
nutrient supply throughout summer (Coupel et al., 2015)
but may also impede the breakdown of stratification in autumn, thereby
extending the phytoplankton growing season (Oliver et al., 2018). Key research
questions are how and on what spatial and temporal timescales these
different effects interact to enhance, or reduce, marine primary production.
Using a synthesis of field studies from glacier catchments with different
characteristics (Fig. 1), we provide answers to three questions arising from
two interdisciplinary workshops on the importance of Arctic glaciers for
the marine ecosystem under the umbrella of the International Arctic Science
Committee (IASC).
Where and when does glacial freshwater discharge promote or reduce
marine primary production?
How does spatio-temporal variability in glacial discharge affect marine
primary production?
How far-reaching are the effects of glacial discharge on marine
biogeochemistry?
Fjords as critical zones for glacier–ocean interactions
In the Arctic and sub-Antarctic, most glacial discharge enters the ocean
through fjord systems (Iriarte et al., 2014;
Straneo and Cenedese, 2015). The strong lateral gradients and seasonal
changes in environmental conditions associated with glacial discharge in
these coastal environments differentiate these ecosystems from offshore
systems (Arendt
et al., 2013; Lydersen et al., 2014; Krawczyk et al., 2018). Fjords can be
efficient sinks for organic carbon (Smith et al., 2015) and
CO2 (Rysgaard
et al., 2012; Fransson et al., 2015), sustain locally important fisheries (Meire et al., 2017) and are critical zones
for deep mixing which dictate how glacially modified waters are exchanged
with the coastal ocean (Mortensen
et al., 2014; Straneo and Cenedese, 2015; Beaird et al., 2018). Fjord-scale
processes therefore comprise an integral part of all questions concerning
how glacial discharge affects Arctic coastal primary production (Arimitsu
et al., 2012; Renner et al., 2012; Meire et al., 2017).
Fjords act as highly stratified estuaries and provide a pathway for the
exchange of heat, salt, and nutrients between near-glacier waters and
adjacent coastal regions (Mortensen et al., 2014, 2018;
Straneo and Cenedese, 2015). In deep fjords, such as those around much of
the periphery of Greenland, warm, saline water is typically found at depth
(>200 m), overlaid by cold, fresher water and, during summer, a
thin layer (∼50 m or less) of relatively warm near-surface
water (Straneo et al., 2012). The injection of
freshwater into fjords from subglacial discharge (Xu et al., 2012; Carroll et
al., 2015) and terminus (Slater et al., 2018) and
iceberg melt (Moon et al., 2018) can drive substantial
buoyancy-driven flows in the fjord (Carroll et al.,
2015, 2017; Jackson et al., 2017), which amplify exchange with the shelf
system as well as submarine melting and the calving rates of glacier
termini. To date, such modifications to circulation and exchange between
glacier fjords and shelf waters have primarily been studied in terms of
their effects on ocean physics and melting at glacier termini, yet they also
have profound impacts on marine productivity (Meire
et al., 2016a; Kanna et al., 2018; Torsvik et al., 2019).
While renewal of fjord waters from buoyancy-driven processes is mainly
thought to occur over seasonal to sub-annual timescales (Gladish
et al., 2014; Mortensen et al., 2014; Carroll et al., 2017), energetic shelf
forcing (i.e. from coastal/katabatic winds and coastally trapped waves) can
result in rapid exchange over synoptic timescales (Straneo et al., 2010;
Jackson et al., 2014; Moffat, 2014) and similarly also affect marine
productivity (Meire et al., 2016b). Katabatic winds are
common features of glaciated fjords. Down-fjord wind events facilitate the
removal of low-salinity surface waters and ice from glacier fjords, as well as the
inflow of warmer, saline waters at depth (Johnson et al., 2011). The frequency, direction
and intensity of wind events throughout the year thus adds further
complexity to the effect that fjord geometry has on fjord–shelf exchange
processes (Cushman-Roisin
et al., 1994; Spall et al., 2017). Topographic features such as sills and
lateral constrictions can exert a strong control on fjord–shelf exchange (Gladish
et al., 2014; Carroll et al., 2017, 2018). Ultimately, circulation can
thereby vary considerably depending on fjord geometry and the relative
contributions from buoyancy, wind and shelf forcing (Straneo and Cenedese, 2015;
Jackson et al., 2018). Some variability in the spatial patterns of primary
production is therefore expected between Arctic glacier fjord systems as
differences in geometry and forcing affect exchange with the shelf and water
column structure. These changes affect the availability of the resources
which constrain local primary production (Meire
et al., 2016b; Arimitsu et al., 2016; Calleja et al., 2017).
Fjord–shelf processes also contribute to the exchange of active cells and microbial
species' resting stages, thus preconditioning primary production prior to
the onset of the growth season (Krawczyk
et al., 2015, 2018). Protists (unicellular eukaryotes) are the main marine
primary producers in the Arctic. This highly specialized and diverse group
includes species that are ice-associated (sympagic) and/or pelagic. Many
protists in fjords and coastal areas of the Arctic maintain diverse seed
banks of resting stages, which promotes the resilience and adaptability of
species on timescales from seasons to decades (Ellegaard and Ribeiro, 2018). Yet seawater
inflow into fjords can still change the dominant species within a single
season. In Nuup Kangerlua (Godthåbsfjord), the spring phytoplankton bloom is typically
dominated by Fragilariopsis spp. diatoms and Phaeocystis spp. haptophytes. Unusually prolonged coastal
seawater inflow in spring 2009 led to the mass occurrence of chain-forming
Thalassiosira spp. diatoms and the complete absence of the normally abundant Phaeocystis spp. (Krawczyk
et al., 2015) – a pattern which has been found elsewhere in the Arctic,
including Kongsfjorden (Hegseth and Tverberg, 2013).
Pelagic primary production in Arctic glacier fjords
Key factors controlling rates of primary production across Arctic marine
environments are light availability, nutrient availability and grazing (Nielsen, 1999; Taylor et
al., 2013; Arrigo and van Dijken, 2015; Tremblay et al., 2015). Seasonal
changes in the availability of bioessential resources, the structure of the
water column and the feeding patterns of zooplankton thereby interact to
produce distinct bloom periods of high primary production shouldered by
periods of low primary production. In glacier fjords, strong lateral and
vertical gradients in some, or all, of these factors create a far more
dynamic situation for primary producers than in the open ocean (Etherington
and Hooge, 2007; Arendt et al., 2010; Murray et al., 2015).
Primary production for Arctic glacier fjord systems including
Disko Bay (Andersen,
1977; Nielsen and Hansen, 1995; Jensen et al., 1999; Nielsen, 1999; Levinsen
and Nielsen, 2002), Godthåbsfjord (Juul-Pedersen et al., 2015; Meire et
al., 2017), Kangerlussuaq (Lund-Hansen et al., 2018),
Kongsfjorden (Hop
et al., 2002; Iversen and Seuthe, 2011; Hodal et al., 2012; van de Poll et
al., 2018), Nordvestfjord/Scoresby Sund (Seifert et al., 2019), Hornsund (Smoła et al., 2017), Young Sound (Rysgaard et
al., 1999; Meire et al., 2017; Holding et al., 2019), the Canadian Arctic
Archipelago (Harrison et al., 1982) and Glacier Bay (Reisdorph and Mathis, 2015). Circles represent glacier fjords,
triangles are sites beyond glacier fjords and bold markers are <80 km from a marine-terminating glacier. Error bars are standard deviations for
stations where multiple measurements were made at the same station. Dashed
line is the pan-Arctic mean primary production (March–September). Shaded
area is the pan-Arctic shelf range of primary production for May–August
(Pabi et al., 2008).
Large inter- and intra-fjord differences in primary production are
demonstrated by field observations around the Arctic which show that glacier
fjords range considerably in productivity from very low (<40 mg C m-2 d-1) to moderately productive systems (>500 mg C m-2 d-1) during the meltwater season (e.g.
Jensen et al., 1999; Rysgaard et al., 1999; Hop et al., 2002; Meire et al.,
2017). For comparison, the pan-Arctic basin exhibits a mean production of
420±26 mg C m-2 d-1 (mean March–September 1998–2006) (Pabi et al., 2008), which has increased
across most regions in recent decades due to reduced summertime sea-ice
coverage (Arrigo and van Dijken, 2015), and summertime (May–August) Arctic
shelf environments exhibit a range of 360–1500 mg C m-2 d-1
(Pabi et al., 2008). So is it possible to generalize how productive Arctic
glacier fjords are?
Extensive measurements of primary production throughout the growth season in
glacier fjords are only available for Godthåbsfjord (Juul-Pedersen et al., 2015; Meire et
al., 2017), Young Sound (Rysgaard et
al., 1999; Meire et al., 2017; Holding et al., 2019), Glacier Bay
(Alaska, Reisdorph and Mathis, 2015), Hornsund
(Svalbard, Smoła et al., 2017) and Kongsfjorden (Iversen and Seuthe, 2011; van de Poll et al.,
2018). Observations elsewhere are sparse and typically limited to summertime-only data. Generalizing across multiple Arctic glacier fjord systems
therefore becomes challenging due to the paucity of data and the different
geographic and seasonal context of individual primary production data points
(Fig. 2). Furthermore there are potentially some methodological implications
when comparing direct measurements of primary production using 14C
uptake (e.g. Holding et al., 2019), with estimates
derived from changes in water column macronutrient (e.g. Seifert et al., 2019) or
dissolved inorganic carbon (e.g. Reisdorph and Mathis, 2015)
inventories.
Nevertheless, some quantitative comparison can be made if we confine
discussion to months where a meltwater signal may be evident in most
glaciated regions (July–September). All available data for Arctic glaciated
regions can then be pooled according to whether it refers to primary
production within a glacier fjord and whether or not it could plausibly be
influenced by the presence of a marine-terminating glacier (see Sect. 5).
For the purposes of defining the spatial extent of individual glacier
fjords, we consider broad bay areas such as the lower and central parts of
Glacier Bay (Etherington and Hooge, 2007; Reisdorph and
Mathis, 2015), Scoresby Sund (Scoresby Sound in English; Seifert et
al., 2019) and Disko Bay (Jensen et al., 1999;
Nielsen, 1999) to be beyond the scale of the associated glacier fjords on
the basis of the oceanographic interpretation presented in the respective
studies. Defining the potential spatial influence of marine-terminating
glaciers is more challenging. Using observations from Godthåbsfjord,
where primary production is found to be affected on a scale of 30–80 km down-fjord from the marine-terminating glaciers therein (Meire et al., 2017), we define a region
<80 km downstream of calving fronts as being potentially influenced
by marine-terminating glaciers.
July–September marine primary production (PP) data from studies conducted in glaciated Arctic regions. PP data points are categorised into four groups according to whether or not they are within 80 km of a marine-terminating glacier and whether or not they are within a glacier fjord. Data sources as per Fig. 2. n is the number of
data points; where studies report primary production measurements at the
same station for the same month at multiple time points (e.g. Juul-Pedersen et al., 2015) a single mean is used
in the data compilation (i.e. n= 1 irrespective of the historical extent
of the time series).
Mean PP(± standard deviation)Categorymg C m-2 d-1nData from(I) Marine-terminating glacier influence, non-fjord847±85211Disko Bay, Scoresby Sund, Glacier Bay, North Greenland, Canadian Arctic Archipelago(II) Marine-terminating glacier influence, glacier fjord480±40333Godthåbsfjord, Kongsfjorden, Scoresby Sund, Glacier Bay, Hornsund,(III) No marine-terminating glacier influence, non-fjord304±26142Godthåbsfjord, Young Sound, Scoresby Sund, Disko Bay, Canadian Arctic Archipelago(IV) No marine-terminating glacier influence, glacier fjord125±10235Godthåbsfjord, Young Sound, Kangerlussuaq, Disko Bay
Four exclusive categories of primary production data result (Table 1).
Primary production for group I is significantly higher than any other group,
and group II is also significantly higher than group IV (p<0.025).
Primary production is higher in regions designated as having a potential
marine-terminating glacier influence. On the contrary, other near-glacier
regions (i.e. with land-terminating glaciers) seem to have low summertime
primary productivity, irrespective of how mean Arctic primary production is
defined (Table 1). What processes could lead to such differences? In the
next sections of this review we discuss the biogeochemical features of
glacier-affected marine regions that could potentially explain such trends
if they do not simply reflect data deficiency.
Effects of glacial discharge on marine resource availability
One of the most direct mechanisms via which glacial discharge affects
downstream marine primary production is by altering the availability of
light, macronutrients (such as nitrate, NO3; phosphate, PO4; and
silicic acid, Si) and/or micronutrients (such as iron and manganese) in the
ocean. The chemical composition of glacial discharge is now relatively well
constrained, especially around Greenland (Yde
et al., 2014; Meire et al., 2016a; Stevenson et al., 2017), Alaska (Hood
and Berner, 2009; Schroth et al., 2011) and Svalbard (Hodson et al., 2004, 2016). Whilst high
particle loads (Chu et
al., 2012; Overeem et al., 2017) and Si are often associated with
glacially modified waters (Fig. 3a) around the Arctic (Brown
et al., 2010; Meire et al., 2016a), the concentrations of all macronutrients
in glacial discharge (Meire et al.,
2016a) are relatively low and similar to those of coastal seawater (Fig. 3a, b and c).
Macronutrient concentrations in Arctic rivers can be higher than in glacier
discharge (Holmes et al., 2011) (Fig. 3d, e and
f). Nevertheless, river and glacier meltwater alike do not significantly
increase the concentration of PO4 in Arctic coastal waters (Fig. 3c and
f). River water is, relatively, a much more important source of NO3
(Cauwet and Sidorov, 1996; Emmerton et al., 2008; Hessen et al., 2010), and
in river estuaries this nutrient can show a sharp decline with increasing
salinity due to both mixing and biological uptake (Fig. 3e). Patterns in Si
are more variable (Cauwet and Sidorov, 1996; Emmerton et al., 2008; Hessen
et al., 2010). Dissolved Si concentration at low salinity is higher in
rivers than in glacier discharge (Fig. 3a and d), yet a variety of
estuarine behaviours are observed across the Arctic. Peak dissolved Si
occurs at a varying salinity, due to the opposing effects of Si release from
particles and dissolved Si uptake by diatoms (Fig. 3d).
A notable feature of glacial freshwater outflows into the ocean is the
high turbidity that occurs in most Arctic glacier fjords. High turbidity in
surface waters within glacier fjords arises from the high sediment transport
in these drainage systems (Chu et al., 2012),
from iceberg melting and also from the resuspension of fine sediments (Azetsu-Scott
and Syvitski, 1999; Zajączkowski and Włodarska-Kowalczuk, 2007;
Stevens et al., 2016). The generally high sediment load of glacially derived
freshwater is evident around Greenland, which is the origin of
∼1 % of annual freshwater discharge into the ocean yet
7 %–9 % of the annual fluvial sediment load (Overeem et al., 2017). Sediment load is
however spatially and temporally variable, leading to pronounced inter- and
intra-catchment differences (Murray et al., 2015). For example, satellite-derived estimates of sediment load for 160 Greenlandic glacier outflows
suggest a median sediment load of 992 mg L-1, but some catchments
exhibit >3000 mg L-1 (Overeem et al., 2017). Furthermore it is
suggested that >25 % of the total annual sediment load is released
in a single outflow (from the Sermeq glacier) (Overeem et al., 2017).
The extent to which high turbidity in glacier outflows limits light
availability in downstream marine environments is therefore highly variable
between catchments and with distance from glacier
outflows (Murray et al., 2015; Mascarenhas and Zielinski, 2019). The occurrence, and
effects, of subsurface turbidity peaks close to glaciers is less well
studied. Subsurface turbidity features may be even more spatially and
temporally variable than their surface counterparts (Stevens et al., 2016; Kanna et
al., 2018; Moskalik et al., 2018). In general, a spatial expansion of
near-surface turbid plumes is expected with increasing glacier discharge,
but this trend is not always evident at the catchment scale (Chu
et al., 2009, 2012; Hudson et al., 2014). Furthermore, with long-term
glacier retreat, the sediment load in discharge at the coastline is
generally expected to decline as proglacial lakes are efficient sediment
traps (Bullard, 2013; Normandeau et al., 2019).
(a) Si, (b)NO3 and (c)PO4 distributions across the
measured salinity gradient in Kongsfjorden in summer 2013 (Fransson et al., 2016), 2014 (Fransson et al., 2016), 2015 (van de Poll et al., 2018) and 2016 (Cantoni et al., 2019).
Full depth data are shown, with a linear regression (black line) for
glacially modified waters (S<34.2) during summer 2016. The position
of stations varies between the datasets, with the 2016 data providing the
broadest coverage of the inner fjord. Linear regression details are shown in
Table S1 in the Supplement. (d) Si, (e)NO3 and (f)PO4 distributions
in surface waters of three major Arctic river estuaries: the Lena, Mackenzie
and Yenisey (Cauwet and Sidorov, 1996; Emmerton et al., 2008; Hessen et al.,
2010). Note the different y- and x-axis scales.
In addition to high turbidity, the low concentration of macronutrients in
glacier discharge relative to saline waters is evidenced by the estuarine
mixing diagram in Kongsfjorden (Fig. 3) and confirmed by extensive
measurements of freshwater nutrient concentrations (e.g. Hodson et al.,
2004, 2005). For PO4 (Fig. 3c), there is a slight increase in
concentration with salinity (i.e. discharge dilutes the nutrient
concentration in the fjord). For NO3, discharge slightly increases the
concentration in the upper-mixed layer (Fig. 3b). For Si, a steady decline
in Si with increasing salinity (Fig. 3a) is consistent with a discharge-associated Si supply (Brown
et al., 2010; Arimitsu et al., 2016; Meire et al., 2016a). The spatial
distribution of data for summer 2013–2016 is similar and representative of
summertime conditions in the fjord (Hop et al., 2002).
Whilst dissolved macronutrient concentrations in glacial discharge are
relatively low, a characteristic of glaciated catchments is extremely high
particulate Fe concentrations. High Fe concentrations arise both directly
from glacier discharge (Bhatia et al., 2013a; Hawkings et al., 2014) and
also from resuspension of glacially derived sediments throughout the year (Markussen et al.,
2016; Crusius et al., 2017). Total dissolvable Fe (TdFe) concentrations
within Godthåbsfjord are high in all available datasets (May 2014,
August 2014 and July 2015) and strongly correlated with turbidity (linear
regression: R2=0.88, R2=0.56 and R2=0.88,
respectively, Hopwood
et al., 2016, 2018). A critical question in oceanography, in both the Arctic
and Antarctic, is to what extent this large pool of particulate Fe is
transferred into open-ocean environments and thus potentially able to affect
marine primary production in Fe-limited offshore regions (Gerringa
et al., 2012; Arrigo et al., 2017; Schlosser et al., 2018). The mechanisms
that promote transfer of particulate Fe into bioavailable dissolved phases,
such as ligand-mediated dissolution (Thuroczy et al.,
2012) and biological activity (Schmidt
et al., 2011), and the scavenging processes that return dissolved Fe to the
particulate phase are both poorly characterized (Tagliabue et
al., 2016).
Fe profiles around the Arctic show strong spatial variability in TdFe
concentrations, ranging from unusually high concentrations of up to 20 µM found intermittently close to turbid glacial outflows (Zhang
et al., 2015; Markussen et al., 2016; Hopwood et al., 2018) to generally low
nanomolar concentrations at the interface between shelf and fjord waters (Zhang
et al., 2015; Crusius et al., 2017; Cape et al., 2019). An interesting
feature of some of these profiles around Greenland is the presence of peak
Fe at ∼50 m depth, perhaps suggesting that much of the
Fe transport away from glaciers may occur in subsurface turbid glacially
modified waters (Hopwood et al., 2018; Cape
et al., 2019). The spatial extent of Fe enrichment downstream of glaciers
around the Arctic is still uncertain, but there is evidence of global variability downstream of glaciers on the scale of 10–100 km (Gerringa
et al., 2012; Annett et al., 2017; Crusius et al., 2017).
Non-conservative mixing processes for Fe and Si
A key reason for uncertainty in the fate of glacially derived Fe is the
non-conservative behaviour of dissolved Fe in saline waters. In the absence
of biological processes (i.e. nutrient assimilation and remineralization),
NO3 is expected to exhibit conservative behaviour across estuarine
salinity gradients (i.e. the concentration at any salinity is a linear
function of mixing between fresh and saline waters). For Fe, however, a
classic non-conservative estuarine behaviour occurs due to the removal of
dissolved Fe (DFe
For consistency, dissolved Fe is defined
throughout operationally as <0.2µ m and is therefore
inclusive of ionic, complexed and colloidal species.
) as it flocculates
and is absorbed onto particle surfaces more readily at higher salinity and
pH (Boyle et al., 1977). Dissolved Fe concentrations almost
invariably exhibit strong (typically ∼90 %)
non-conservative removal across estuarine salinity gradients (Boyle et al., 1977; Sholkovitz et
al., 1978), and glaciated catchments appear to be no exception to this rule (Lippiatt et al., 2010). Dissolved Fe
in Godthåbsfjord exhibits a removal of >80 % DFe between
salinities of 0–30 (Hopwood
et al., 2016), and similar losses of approximately 98 % for Kongsfjorden
and 85 % for the Copper river/estuary (Gulf of Alaska) system have been
reported (Schroth et al.,
2014; Zhang et al., 2015).
Conversely, Si can be released from particulate phases during estuarine
mixing, resulting in non-conservative addition to dissolved Si
concentrations (Windom et al., 1991), although salinity–Si
relationships vary between different estuaries due to different extents of
Si release from labile particulates and Si uptake by diatoms (e.g. Fig. 3d).
Where evident, this release of dissolved Si typically occurs at low
salinities (Cauwet and Sidorov, 1996; Emmerton et al., 2008; Hessen et al.,
2010), with the behaviour of Si being more conservative at higher salinities
and in estuaries where pronounced drawdown by diatoms is not evident (e.g. Brown et al., 2010).
Estimating release of particulate Si from Kongsfjorden data (Fig. 3c) as the
additional dissolved Si present above the conservative mixing line for
runoff mixing with unmodified saline water that is entering the fjord (via
linear regression) suggests a Si enrichment of 13%±2% (Fig. 3a).
This is broadly consistent with the 6 %–53 % range reported for estuarine
gradients evident in some temperate estuaries (Windom et
al., 1991). Conversely, Hawkings et al. (2017) suggest a
far greater dissolution downstream of Leverett Glacier, equivalent to a
70 %–800 % Si enrichment, and thus propose that the role of glaciers in the
marine Si cycle has been underestimated. Given that such dissolution is
substantially above the range observed in any other Arctic estuary, the
apparent cause is worth further consideration.
Dissolved Si distribution vs. salinity for glaciated Arctic
catchments. Data are from Bowdoin Fjord (Kanna et al., 2018),
Kongsfjorden (Fransson et
al., 2016; van de Poll et al., 2018), Sermilik Fjord (Cape et al., 2019), Kangerlussuaq (Hawkings et al., 2017; Lund-Hansen et al., 2018),
Godthåbsfjord (Hopwood et al., 2016;
Meire et al., 2016b), and the Gulf of Alaska (Brown et al., 2010). Linear
regressions are shown for large surface datasets only. Linear regression
details are shown in Table S1. Closed markers indicate surface data (<20 m depth), and open markers indicate subsurface data.
The general distribution of Si in surface waters for Kongsfjorden (Fransson et al., 2016),
Godthåbsfjord (Meire et al.,
2016a), Bowdoin Fjord (Kanna et al., 2018), Sermilik (Cape et al., 2019) and along the Gulf of Alaska (Brown et al., 2010) is similar; Si
shows pseudo-conservative behaviour declining with increasing salinity in
surface waters. The limited reported number of zero-salinity, or very low
salinity, endmembers for Godthåbsfjord and Bowdoin are significantly
below the linear regression derived from surface nutrient and salinity data
(Fig. 4). In addition to some dissolution of particulate Si, another likely
reason for this is the limitation of individual zero-salinity measurements
in dynamic fjord systems where different discharge outflows have different
nutrient concentrations (Kanna et al., 2018), especially given
that subglacial discharge is not directly characterized in either location
(Meire et al., 2016a; Kanna et al., 2018). As demonstrated by the two
different zero-salinity Si endmembers in Kongsfjorden (iceberg melt of
∼0.03µM and surface runoff of ∼5.9µM), pronounced deviations in nutrient content arise from mixing
between various freshwater endmembers (surface runoff, ice melt and
subglacial discharge). For example, total freshwater input into
Godthåbsfjord is 70 %–80 % liquid, with this component consisting of
64 % ice sheet runoff, 31 % land runoff, and 5 % net precipitation
(Langen et al., 2015) and being subject to additional inputs from iceberg melt
along the fjord (∼70 % of calved ice also melts within the
inner fjord, Bendtsen et al., 2015).
In a marine context at broad scales, a single freshwater endmember that integrates the net contribution of all freshwater sources can be
defined. This
endmember includes iceberg melt, groundwater discharge, surface and
subsurface glacier discharge, and (depending on location) sea-ice melt, which
are challenging to distinguish in coastal waters (Benetti et al., 2019).
Close to glaciers, it may be possible to observe distinct freshwater
signatures in different water column layers and distinguish chemical
signatures in water masses containing subglacial discharge from those
containing primarily surface runoff and iceberg melt (e.g. in
Godthåbsfjord, Meire et al., 2016a; and Sermilik, Beaird et al., 2018),
but this is often challenging due to mixing and overlap between different
sources. Back-calculating the integrated freshwater endmember (e.g. from
regression, Fig. 4) can potentially resolve the difficulty in accounting for
data-deficient freshwater components and poorly characterized estuarine
processes. As often noted in field studies, there is a general bias towards
sampling of supraglacial meltwater and runoff in proglacial environments
and a complete absence of chemical data for subglacial discharge emerging
from large marine-terminating glaciers (e.g. Kanna et al., 2018).
Macronutrient distributions in Bowdoin, Godthåbsfjord and Sermilik
unambiguously show that the primary macronutrient supply to surface waters
associated with glacier discharge originates from mixing rather than from
freshwater addition (Meire et al.,
2016a; Kanna et al., 2018; Cape et al., 2019), which emphasizes the need to
consider fjord inflow/outflow dynamics in order to interpret nutrient
distributions. The apparently anomalous extent of Si dissolution downstream
of Leverett Glacier (Hawkings et al., 2017) may therefore
largely reflect underestimation of both the saline (assumed to be
negligible) and freshwater endmembers rather than unusually prolific
particulate Si dissolution. In any case, measured Si concentrations in the
Kangerlussuaq region are within the range of other Arctic glacier estuaries
(Fig. 4), making it challenging to support the hypothesis that glacial
contributions to the Si cycle have been underestimated elsewhere (see also
Tables 2 and 3).
Deriving glacier–ocean fluxes
In the discussion of macronutrients herein we have focused on the
availability of the bioavailable species (e.g. PO4, NO3 and
silicic acid) that control seasonal trends in inter-annual marine primary
production (Juul-Pedersen et al., 2015; van de Poll et al., 2018; Holding et
al., 2019). It should be noted that the total elemental fluxes (i.e.
nitrogen, phosphorus and silicon) associated with lithogenic particles are
invariably higher than the associated macronutrients (Wadham et al., 2019),
particularly for phosphorus (Hawkings et al., 2016) and silicon (Hawkings et
al., 2017). Lithogenic particles are however not bioavailable, although they
may to some extent be bioaccessible, depending on the temporal and spatial
scale involved. This is especially the case for the poorly quantified
fraction of lithogenic particles that escapes sedimentation in inner-fjord
environments, either directly or via resuspension of shallow sediments
(Markussen et al., 2016; Hendry et al., 2019). It is hypothesized that
lithogenic particle inputs from glaciers therefore have a positive influence
on Arctic marine primary production (Wadham et al., 2019), yet field data to
support this hypothesis are lacking. A pan-Arctic synthesis of all available
primary production data for glaciated regions (Fig. 2 and Table 1), spatial
patterns in productivity along the west Greenland coastline (Meire et al.,
2017), population responses in glacier fjords across multiple taxonomic
groups (Cauvy-Fraunié and Dangles, 2019) and sedimentary records from
Kongsfjorden (Kumar et al., 2018) consistently suggest that glaciers, or
specifically increasing volumes of glacier discharge, have a net negative,
or negligible, effect on marine primary producers – except in the specific
case of some marine-terminating glaciers where a different mechanism seems
to operate (see Sect. 5).
Two linked hypotheses can be proposed to explain these apparently
contradictory arguments. One is that whilst lithogenic particles are
potentially a bioaccessible source of Fe, P and Si, they are deficient in
bioaccessible N. As NO3 availability is expected to limit primary
production across much of the Arctic (Tremblay et al., 2015), this creates a
spatial mismatch between nutrient supply and the nutrient demand required
to increase Arctic primary production. A related, alternative hypothesis is
that the negative effects of discharge on marine primary production (e.g. via stratification and light limitation from high turbidity) more than
offset any positive effect that lithogenic particles have via increasing
nutrient availability on regional scales prior to extensive sedimentation
occurring. A similar conclusion has been reached from analysis of primary
production in proglacial streams (Uehlinger et al., 2010). To some extent
this reconciliation is also supported by considering the relative magnitudes
of different physical and chemical processes acting on different spatial
scales with respect to global marine primary production (see Sect. 10).
The generally low concentrations of macronutrients and dissolved organic
matter (DOM) in glacier discharge, relative to coastal seawater (Table 2),
have an important methodological implication because what constitutes a
positive NO3, PO4 or DOM flux into the Arctic Ocean in a
glaciological context can actually reduce short-term nutrient availability
in the marine environment. It is therefore necessary to consider both the
glacier discharge and saline endmembers that mix in fjords, alongside
fjord-scale circulation patterns, in order to constrain the change in
nutrient availability to marine biota (Meire et al.,
2016a; Hopwood et al., 2018; Kanna et al., 2018).
Measured/computed discharge and saline endmembers for well-studied
Arctic fjords (ND, not determined/not reported; BD, below detection).
FjordDatasetSalinityNO3 (µM)PO4 (µM)Si (µM)TdFe (µM)KongsfjordenSummer 20160.0 (ice melt)0.87±1.00.02±0.030.03±0.0333.8±100(Svalbard)(Cantoni et al., 2019)0.0 (surface discharge)0.94±1.00.057±0.315.91±4.174±7634.50±0.171.25±0.490.20±0.061.00±0.33NDNuup Kangerlua/Summer 20140.0 (ice melt)1.96±1.680.04±0.0413±150.31±0.49Godthåbsfjord(Hopwood et al., 2016;0.0 (surface discharge)1.60±0.440.02±0.0112.2±16.313.8(Greenland)Meire et al., 2016a)33.57±0.0511.5±1.50.79±0.048.0±1.0NDSermilikSummer 20150.0 (subglacial discharge)1.8±0.5ND10±8ND(Greenland)(Cape et al., 2019)0.0 (ice melt)0.97±1.5ND4±4ND34.9±0.112.8±1ND6.15±1NDBowdoinSummer 20160.0 (surface discharge)0.22±0.150.30±0.20BDND(Greenland)(Kanna et al., 2018)34.3±0.114.7±0.91.1±0.119.5±1.5NDYoung SoundSummer 2014(Runoff July–August)1.2±0.740.29±0.29.52±3.8ND(Greenland)(Paulsen et al., 2017)(Runoff September–October)1.0±0.70.35±0.229.57±10.9ND33.6±0.1 (July–August)6.4±1.11.18±0.56.66±0.4ND33.5±0.04 (September–October)5.6±0.20.62±0.26.5±0.1ND
Flux calculations for dissolved nutrients (Fe, DOC, DON, NO3,
PO4 and Si) from Greenland Ice Sheet discharge. Where a flux was not
calculated in the original work, an assumed discharge volume of
1000 km3 yr-1 is used to derive a flux for comparative purposes
(ASi, amorphous silica; LPP, labile particulate phosphorous). For DOM,
PO4 and NO3, non-conservative estuarine behaviour is expected to
be minor or negligible. Note that whilst we have defined “dissolved” herein
as <0.2µm, the sampling and filtration techniques used,
particularly in freshwater studies, are not well standardized, and thus some
differences may arise between studies accordingly. Clogging of filters in
turbid waters reduces the effective filter pore size; DOP, DON, NH4 and
PO4 concentrations often approach analytical detection limits which,
alongside field/analytical blanks, are treated differently; low
concentrations of NO3, DON, DOP, DOC, NH4 and DFe are easily
inadvertently introduced to samples by contamination, and measured Si
concentrations can be significantly lower when samples have been frozen.
FreshwaterendmemberconcentrationNutrient(µM)FluxEstuarine modificationDataFe0.13>26 Mmol yr-1Inclusive, >80 % lossHopwood et al. (2016)1.6439 Mmol yr-1Assumed 90 % lossStevenson et al. (2017)0.05353 Mmol yr-1Discussed, not appliedStatham et al. (2008)3.70180 Mmol yr-1Assumed 90 % lossBhatia et al. (2013a)0.71290 Mmol yr-1Discussed, not appliedHawkings et al. (2014)DOC16–1006.7 Gmol yr-1Not discussedBhatia et al. (2010, 2013b)12–4111–14 Gmol yr-1Not discussedLawson et al. (2014b)15–10018 Gmol yr-1Not discussedHood et al. (2015)2–29024–38 Gmol yr-1Not discussedCsank et al. (2019)27–4740 Gmol yr-1Not discussedPaulsen et al. (2017)DON4.7–5.45 Gmol yr-1Not discussedPaulsen et al. (2017)1.70.7–1.1 Gmol yr-1Not discussedWadham et al. (2016)Si13–2822 Gmol yr-1InclusiveMeire et al. (2016a)9.64 Gmol yr-1DiscussedHawkings et al. (2017)(+190 Gmol yr-1 ASi)PO40.230.10 Gmol yr-1DiscussedHawkings et al. (2016)(+0.23 Gmol yr-1 LPP)0.260.26 Gmol yr-1Not discussedMeire et al. (2016a)NO31.4–1.50.42 Gmol yr-1Not discussedWadham et al. (2016)0.5–1.70.5–1.7 Gmol yr-1Not discussedPaulsen et al. (2017)1.791.79 Gmol yr-1Not discussedMeire et al. (2016a)
Despite the relatively well constrained nutrient signature of glacial
discharge around the Arctic, estimated fluxes of some nutrients from
glaciers to the ocean appear to be subject to greater variability,
especially for nutrients subject to non-conservative mixing (Table 3).
Estimates of the Fe flux from the Greenland Ice Sheet, for example, have an
11-fold difference between the lowest (>26 Mmol yr-1) and
highest (290 Mmol yr-1) values (Hawkings
et al., 2014; Stevenson et al., 2017). However, it is debatable if these
differences in Fe flux are significant because they largely arise in
differences between definitions of the flux gate window and especially how
estuarine Fe removal is accounted for. Given that the difference between an
estimated removal factor of 90 % and 99 % is a factor of 10 difference
in the calculated DFe flux, there is overlap in all of the calculated fluxes
for Greenland Ice Sheet discharge into the ocean (Table 3) (Statham
et al., 2008; Bhatia et al., 2013a; Hawkings et al., 2014; Stevenson et al.,
2017). Conversely, estimates of DOM export (quantified as DOC) are confined
to a slightly narrower range of 7–40 Gmol yr-1, with differences
arising from changes in measured DOM concentrations (Bhatia
et al., 2013b; Lawson et al., 2014b; Hood et al., 2015). The
characterization of glacial DOM, with respect to its lability, C:N ratio
and implications for bacterial productivity in the marine environment (Hood et
al., 2015; Paulsen et al., 2017), is however not readily apparent from a
simple flux calculation.
A scaled-up calculation using freshwater concentrations (C) and discharge
volumes (Q) is the simplest way of determining the flux from a glaciated
catchment to the ocean. However, discharge nutrient concentrations vary
seasonally (Hawkings et al., 2016; Wadham et al., 2016), often resulting in
variable C–Q relationships due to changes in mixing ratios between different discharge flow paths; post-mixing reactions; and seasonal changes in
microbial behaviour in the snowpack, on glacier surfaces, and in proglacial
forefields (Brown et
al., 1994; Hodson et al., 2005). Therefore, full seasonal datasets from a
range of representative glaciers are required to accurately describe C–Q
relationships. Furthermore, as the indirect effects of discharge on nutrient
availability to phytoplankton via estuarine circulation and stratification
are expected to be a greater influence than the direct nutrient outflow
associated with discharge (Rysgaard
et al., 2003; Juul-Pedersen et al., 2015; Meire et al., 2016a), freshwater
data must be coupled to physical and chemical time series in the coastal
environment if the net effect of discharge on nutrient availability in the
marine environment is to be understood. Indeed, the recently emphasized
hypothesis that nutrient fluxes from glaciers into the ocean have been
significantly underestimated (Hawkings et al.,
2016, 2017; Wadham et al., 2016) is difficult to reconcile with a synthesis
and analysis of available marine nutrient distributions (Sect. 4) in
glaciated Arctic catchments, especially for Si (Fig. 4).
A particularly
interesting case study concerning the link between marine primary
production, circulation and discharge-derived nutrient fluxes is Young
Sound. It was initially stipulated that increasing discharge into the fjord
in response to climate change would increase estuarine circulation and
therefore macronutrient supply. Combined with a longer sea-ice-free growing
season as Arctic temperatures increase, this would be expected to increase
primary production within the fjord (Rysgaard et
al., 1999; Rysgaard and Glud, 2007). Yet freshwater input also stratifies
the fjord throughout summer and ensures low macronutrient availability in
surface waters (Bendtsen et
al., 2014; Meire et al., 2016a), which results in low summertime
productivity in the inner and central fjord (<40 mg C m-2 d-1) (Rysgaard
et al., 1999, 2003; Rysgaard and Glud, 2007). Whilst annual discharge
volumes into the fjord have increased over the past two decades, resulting
in a mean annual 0.12±0.05 (practical salinity units) freshening of
fjord waters (Sejr et al., 2017), shelf waters have
also freshened. This has potentially impeded the dense inflow of saline waters into the
fjord (Boone et al., 2018) and
therefore counteracted the expected increase in productivity.
How do variations in the behaviour and location of higher-trophic-level organisms affect nutrient availability to marine microorganisms?
With the exception of some zooplankton and fish species that struggle to
adapt to the strong salinity gradients and/or suspended particle loads in
inner-fjord environments (Wçslawski and Legezytńska, 1998; Lydersen et al., 2014), higher-trophic-level
organisms (including mammals and birds) are not directly affected by the
physical/chemical gradients caused by glacier discharge. However, their food
sources, such as zooplankton and some fish species, are directly affected,
and therefore there are many examples of higher-level organisms adapting
their feeding strategies within glacier fjord environments (Arimitsu
et al., 2012; Renner et al., 2012; Laidre et al., 2016). Strong gradients in
physical/chemical gradients downstream of glaciers, particularly turbidity,
can therefore create localized hotspots of secondary productivity in areas
where primary production is low (Lydersen et al., 2014).
It is debatable to what extent shifts in these feeding patterns could have
broadscale biogeochemical effects. Whilst some species are widely described
as ecosystem engineers, such as Alle alle (the little auk) in the Greenland North
Water Polynya (González-Bergonzoni et al., 2017),
for changes in higher-trophic-level organisms' feeding habits to have
significant direct chemical effects on the scale of a glacier fjord system
would require relatively large concentrations of such animals.
Nevertheless, in some specific hotspot regions this effect is
significant enough to be measurable. There is ample evidence that birds
intentionally target upwelling plumes in front of glaciers as feeding
grounds, possibly due to the stunning effect that turbid, upwelling plumes
have upon prey such as zooplankton (Hop
et al., 2002; Lydersen et al., 2014). This feeding activity therefore
concentrates the effect of avian nutrient recycling within a smaller area
than would otherwise be the case, potentially leading to modest nutrient
enrichment of these proglacial environments. Yet, with the exception of
large, concentrated bird colonies, the effects of such activity are likely
modest. In Kongsfjorden, bird populations are well studied, and several
species are associated with feeding in proglacial plumes yet still
collectively consume only between 0.1 % and 5.3 % of the carbon produced by
phytoplankton in the fjord (Hop et
al., 2002). The estimated corresponding nutrient flux into the fjord from
birds is 2 mmol m-2 yr-1 nitrogen and 0.3 mmol m-2 yr-1
phosphorous.
Critical differences between
surface and subsurface discharge release
Critical differences arise between land-terminating and marine-terminating
glaciers with respect to their effects on water column structure and
associated patterns in primary production (Table 1). Multiple glacier fjord
surveys have shown that fjords with large marine-terminating glaciers around
the Arctic are normally more productive than their land-terminating
glacier fjord counterparts (Meire
et al., 2017; Kanna et al., 2018), and, despite large inter-fjord variability
(Fig. 2), this observation appears to be significant across all available
primary production data for Arctic glacier fjords (Table 1). A particularly
critical insight is that fjord-scale summertime productivity along the west
Greenland coastline scales approximately with discharge downstream of
marine-terminating glaciers but not land-terminating glaciers
(Meire et al., 2017). The primary explanation
for this phenomenon is the vertical nutrient flux associated with mixing
driven by subglacial discharge plumes, which has been quantified in field
studies at Bowdoin glacier (Kanna et al., 2018), Sermilik
Fjord (Cape et al., 2019), Kongsfjorden (Halbach et al., 2019) and in
Godthåbsfjord (Meire et al., 2016a).
As discharge is released at the glacial grounding line depth, its buoyancy
and momentum result in an upwelling plume that entrains and mixes with
ambient seawater (Carroll
et al., 2015, 2016; Cowton et al., 2015). In Bowdoin, Sermilik and
Godthåbsfjord, this nutrient pump provides 99 %, 97 % and 87 %,
respectively, of the NO3 associated with glacier inputs to each fjord
system (Meire
et al., 2016a; Kanna et al., 2018; Cape et al., 2019). Whilst the pan-Arctic
magnitude of this nutrient pump is challenging to quantify because of the
uniqueness of glacier fjord systems in terms of their geometry, circulation,
residence time and glacier grounding line depths (Straneo
and Cenedese, 2015; Morlighem et al., 2017), it can be approximated in
generic terms because plume theory (Morton et al., 1956) has been used
extensively to describe subglacial discharge plumes in the marine
environment (Jenkins, 2011; Hewitt, 2020). Computed
estimates of subglacial discharge for the 12 Greenland glacier fjord systems
where sufficient data are available to simulate plume entrainment (Carroll et al., 2016) suggest that
the entrainment effect is at least 2 orders of magnitude more important
for macronutrient availability than direct freshwater runoff (Hopwood et al., 2018). This is consistent with limited
available field observations (Meire et al.,
2016a; Kanna et al., 2018; Cape et al., 2019). As macronutrient fluxes have
been estimated independently using different datasets and plume entrainment
models in two of these glacier fjord systems (Sermilik and Illulissat), an
assessment of the robustness of these fluxes can also be made (Table 4) (Hopwood et al., 2018; Cape et al., 2019).
Exactly how these plumes, and any associated fluxes, will change with the
combined effects of glacier retreat and increasing glacier discharge remains
unclear (De Andrés et al., 2020) but may lead to large changes in fjord
biogeochemistry (Torsvik et al., 2019). Despite different definitions of the
macronutrient flux (Table 4; “A” refers to the out-of-fjord transport at a
defined fjord cross-section window, whereas “B” refers to the vertical
transport within the immediate vicinity of the glacier), the fluxes are
reasonably comparable and in both cases unambiguously dominate macronutrient
glacier-associated input into these fjord systems (Hopwood et al., 2018; Cape et al., 2019).
A comparison of upwelled NO3 fluxes calculated from
fjord-specific observed nutrient distributions (A) (Cape et al., 2019) and using regional nutrient
profiles with idealized plume theory (B) (Hopwood et al.,
2018). “A” refers to the out-of-fjord transport of nutrients, whereas “B” refers
to the vertical transport close to the glacier terminus.
Whilst large compared to changes in macronutrient availability from
discharge without entrainment (Table 3), it should be noted that these
nutrient fluxes (Table 4) are still only intermediate contributions to
fjord-scale macronutrient supply compared to total annual consumption in
these environments. For example, in Godthåbsfjord mean annual primary
production is 103.7 g C m-2 yr-1, equivalent to biological
consumption of 1.1 mol N m-2 yr-1. Entrainment from the three
marine-terminating glaciers within the fjord is conservatively estimated to
supply 0.01–0.12 mol N m-2 yr-1 (Meire et al., 2017), i.e. 1 %–11 % of the
total N supply required for primary production if production were supported
exclusively by new NO3 (rather than recycling) and equally distributed
across the entire fjord surface. Whilst this is consistent with observations
suggesting relative stability in mean annual primary production in
Godthåbsfjord from 2005 to 2012 (103.7±17.8 g C m-2 yr-1;
Juul-Pedersen et al., 2015), despite pronounced increases in
total discharge into the fjord, this does not preclude a much stronger
influence of entrainment on primary production in the inner-fjord
environment. The time series is constructed at the fjord mouth, over 120 km from the nearest glacier, and the estimates of subglacial discharge and
entrainment used by Meire et al. (2017)
are both unrealistically low. If the same conservative estimate of
entrainment is assumed to only affect productivity in the main fjord branch
(where the three marine-terminating glaciers are located), for example, the
lower bound for the contribution of entrainment becomes 3 %–33 % of total N
supply. Similarly, in Kongsfjorden – the surface area of which is
considerably smaller compared to Godthåbsfjord (∼230 km2 compared to 650 km2) – even the relatively weak entrainment
from shallow marine-terminating glaciers (Fig. 5) accounts for approximately
19 %–32 % of N supply. An additional mechanism of N supply evident there,
which partially offsets the inefficiency of macronutrient entrainment at
shallow grounding line depths, is the entrainment of ammonium from shallow
benthic sources (Halbach et al., 2019),
which leads to unusually high NH4 concentrations in surface waters.
Changes in subglacial discharge, or in the entrainment factor (e.g. from a
shift in glacier grounding line depth, Carroll et al., 2016), can
therefore potentially change fjord-scale productivity.
The plume dilution (entrainment) factor relationship with glacier
grounding line depth as modelled by Carroll et al. (2016) for
subglacial freshwater discharge rates of 250–500 m3 s-1 and
grounding lines of >100 m (shaded area). Also shown are the
entrainment factors determined from field observations for Kronebreen
(Kongsfjorden, Kr, Halbach et al.,
2019), Bowdoin (Bn, Kanna et al., 2018), Saqqarliup Sermia
(SS, Mankoff et al., 2016), Narsap Sermia (Ns, Meire et al., 2016a),
Kangerlussuup Sermia (KS, Jackson et al., 2017), Kangiata Nunaata Sermia
(KNS, Bendtsen et al., 2015), Sermilik (Sk, Beaird et
al., 2018) and Nioghalvfjerdsfjorden Glacier (the “79∘ N
Glacier”, 79N, Schaffer et al., 2020). Note that the 79∘ N Glacier
is unusual compared to the other Arctic systems displayed as subglacial
discharge there enters a large cavity beneath a floating ice tongue and
accounts for only 11 % of meltwater entering this cavity, with the rest
derived from basal ice melt (Schaffer et al., 2020).
A specific deficiency in the literature to date is the absence of measured
subglacial discharge rates from marine-terminating glaciers. Variability in
such rates on diurnal and seasonal timescales is expected (Schild et al., 2016; Fried et al., 2018), and
intermittent periods of extremely high discharge are known to occur, for
example from ice-dammed lake drainage in Godthåbsfjord (Kjeldsen et al., 2014). Yet determining
the extent to which these events affect fjord-scale mixing and biogeochemistry,
as well as how these rates change in response to climate forcing, will require
further field observations. Paradoxically, one of the major knowledge gaps
concerning low-frequency, high-discharge events is their biological effects;
yet these events first became characterized in Godthåbsfjord after
observations by a fisherman of a sudden Sebastes marinus (Redfish) mortality event in the
vicinity of a marine-terminating glacier terminus. These unfortunate fish
were propelled rapidly to the surface by ascending freshwater during a high-discharge event (Kjeldsen et al., 2014).
A further deficiency, yet to be specifically addressed in biogeochemical
studies, is the decoupling of different mixing processes in glacier fjords.
In this section we have primarily considered the effect of subglacial
discharge plumes on NO3 supply to near-surface waters downstream of
marine-terminating glaciers (Fig. 5). Yet a similar effect can arise from
down-fjord katabatic winds which facilitate the out-of-fjord transport of
low-salinity surface waters and the inflow of generally macronutrient-rich
saline waters at depth (Svendsen et al., 2002;
Johnson et al., 2011; Spall et al., 2017). Both subglacial discharge and
down-fjord winds therefore contribute to physical changes affecting
macronutrient availability on a similar spatial scale, and both processes
are expected to be subject to substantial short-term (hours-days), seasonal
and inter-fjord variability, which is presently poorly constrained
(Spall et al., 2017; Sundfjord et al., 2017).
Is benthic–pelagic coupling enhanced by subglacial discharge?
The attribution of unusually high near-surface NH4 concentrations in
surface waters of Kongsfjorden to benthic release in this relatively shallow
fjord, followed by upwelling close to the Kronebreen calving front (Halbach et al., 2019), raises questions
about where else this phenomenon could be important and which other
biogeochemical compounds could be made available to pelagic organisms by
such enhanced benthic–pelagic coupling. The summertime discharge-driven
upwelling flux within a glacier fjord of any chemical which is released into
bottom water from sediments, for example Fe, Mn (Wehrmann et al., 2014), dissolved organic phosphorous (DOP),
dissolved organic nitrogen (DON) (Koziorowska et al., 2018) or Si (Hendry et
al., 2019), could potentially be increased to varying degrees depending on
sediment composition (Wehrmann et al., 2014; Glud et al., 2000) and the
interrelated nature of fjord circulation, topography and the depth range
over which entrainment occurs.
Where such benthic–upwelling coupling does occur close to glacier termini it
may be challenging to quantify from water column observations due to the
overlap with other processes causing nutrient enrichment. For example, the
moderately high dissolved Fe concentrations observed close to Antarctic ice
shelves were classically attributed mainly to direct freshwater inputs, but
it is now thought that the direct freshwater input and the Fe entering
surface waters from entrainment of Fe-enriched near-bottom waters could be
comparable in magnitude (St-Laurent et al.,
2017), although with large uncertainty. This adds further complexity to the
role of coastal, fjord and glacier geometry in controlling nutrient
bioaccessibility, and determining the significance of such coupling is a
priority for hybrid model–field studies.
From pelagic primary production to the carbon sink
Whilst primary production is a major driver of CO2 drawdown from the
atmosphere to the surface ocean, much of this C is subject to
remineralization and, following bacterial or photochemical degradation of
organic carbon, re-enters the atmosphere as CO2 on short timescales.
The biological C pump refers to the small fraction of sinking C which is
sequestered in the deep ocean or in sediments. There is no simple
relationship between primary production and C export into the deep ocean as
a range of primary-production–C-export relationships have been derived
globally with the underlying cause subject to ongoing discussion (Le Moigne et
al., 2016; Henson et al., 2019).
Irrespective of global patterns, glacier fjords are notable for their
extremely high rates of sedimentation due to high lithogenic particle inputs
(Howe et al., 2010). In addition to
terrestrially derived material providing additional organic carbon for
burial in fjords (Table 3), ballasting of sinking POC (particulate organic
carbon) by lithogenic material generally increases the efficiency of the
biological C pump by facilitating more rapid transfer of C to depth (Iversen and Robert, 2015; Pabortsava et
al., 2017). With high sediment loads and steep topography, fjords are
therefore expected to be efficient POC sinks, especially when normalized
with respect to their surface area (Smith et al., 2015).
Organic carbon accumulation rates in Arctic glacier fjords are far lower
than temperate fjord systems, likely due to a combination of generally lower
terrestrially derived carbon inputs and sometimes lower marine primary
production, but Arctic fjords with glaciers still exhibit higher C
accumulation than Arctic fjords without glaciers (Włodarska-Kowalczuk et
al., 2019).
The limited available POC fluxes for Arctic glacier fjords support the
hypothesis that they are efficient regions of POC export (Wiedmann
et al., 2016; Seifert et al., 2019). POC equivalent to 28 %–82 % of primary
production was found to be transferred to >100 m depth in
Nordvestfjord (west Greenland) (Seifert
et al., 2019). This represents medium-to-high export efficiency compared to
other marine environments on a global scale (Henson et al., 2019). High lithogenic
particle inputs into Arctic glacier fjords could therefore be considered to
maintain a low-primary-production–high-C-export-efficiency regime. On the
one hand, they limit light availability and thus contribute to relatively
low levels of primary production (Table 1), but concurrently they ensure
that a relatively high fraction of C fixed by primary producers is
transferred to depth (Seifert et al., 2019).
Beyond the potent impact of high sedimentation on benthic ecosystems (Włodarska-Kowalczuk et al., 2001, 2005), which is beyond the scope of this
review, and the ballasting effect, which is sparsely studied in this
environment to date (Seifert et al., 2019), relatively little is known about
the interactive effects of concurrent biogeochemical processes on glacier-derived particle surfaces occurring during their suspension (or
resuspension) in near-shore waters. Chemical processes occurring at turbid
freshwater–saline interfaces such as dissolved Fe and DOM scavenging onto
particle surfaces and phosphate or DOM co-precipitation with Fe
oxyhydroxides (e.g. Sholkovitz et al., 1978; Charette and Sholkovitz, 2002;
Hyacinthe and Van Cappellen, 2004) have yet to be extensively studied in
Arctic glacier estuaries where they may exert some influence on nutrient
availability and C cycling.
Contrasting Fe- and NO3-limited regions of the ocean
Whether or not nutrients transported to the ocean surface have an immediate
positive effect on marine primary production depends on the identity of the
resource(s) that limits marine primary production. Light attenuation is the
ultimate limiting control on marine primary production and is exacerbated
close to turbid glacial outflows (Hop
et al., 2002; Arimitsu et al., 2012; Murray et al., 2015). However the
spatial extent of sediment plumes and/or ice mélange, which limit light
penetration into the water column, is typically restricted to within
kilometres of the glacier terminus (Arimitsu
et al., 2012; Hudson et al., 2014; Lydersen et al., 2014). Beyond the
turbid, light-limited vicinity of glacial outflows, the proximal limiting
resource for summertime marine primary production will likely be a nutrient,
the identity of which varies with location globally (Moore
et al., 2013). Increasing the supply of the proximal limiting nutrient would
be expected to have a positive influence on marine primary production,
whereas increasing the supply of other nutrients alone would not – a premise
of “the law of the minimum” (Debaar, 1994). Although proximal
limiting nutrient availability controls total primary production, organic
carbon and nutrient stoichiometry nevertheless has specific effects on the
predominance of different phytoplankton and bacterial groups (Egge and Aksnes, 1992; Egge and
Heimdal, 1994; Thingstad et al., 2008).
The continental shelf is a major source of Fe into the ocean (Lam and Bishop, 2008;
Charette et al., 2016), and this results in clear differences in proximal
limiting nutrients between Arctic and Antarctic marine environments. The
isolated Southern Ocean is the world's largest high-nitrate, low-chlorophyll
(HNLC) zone where Fe extensively limits primary production even in coastal
polynyas (Sedwick et al., 2011) and macronutrients are generally present at
high concentrations in surface waters (Martin
et al., 1990a, b). Conversely, the Arctic Ocean is exposed to extensive
broad shelf areas with associated Fe input from rivers and shelf sediments
and thus generally has a greater availability of Fe relative to
macronutrient supply (Klunder et al., 2012). Fe-limited
summertime conditions have been reported in parts of the Arctic and sub-Arctic (Nielsdottir
et al., 2009; Ryan-Keogh et al., 2013; Rijkenberg et al., 2018) but are
spatially and temporally limited compared to the geographically extensive
HNLC conditions in the Southern Ocean.
However, few experimental studies have directly assessed the nutrient
limitation status of regions within the vicinity of glaciated Arctic
catchments. With extremely high Fe input into these catchments, NO3
limitation might be expected year-round. However, PO4 limitation is
also plausible close to glaciers in strongly stratified fjords
(Prado-Fiedler, 2009), due to the low availability of PO4 in
freshwater relative to NO3 (Ren et al., 2019).
Conversely, in the Southern Ocean, it is possible that Fe-limited conditions
occur extremely close to glaciers and ice shelves (Fig. 6). High-NO3,
low-Fe water can be found in the immediate vicinity of Antarctica's
coastline (Gerringa et al., 2012;
Marsay et al., 2017) and even in inshore bays (Annett
et al., 2015; Höfer et al., 2019). Macronutrient data from Maxwell Bay
(King George Island, South Shetland Islands), for example, suggest that Fe
from local glaciers mixes with high-NO3, high-Si ocean waters,
providing ideal conditions for phytoplankton blooms in terms of nutrient
availability. The lowest surface macronutrient concentrations measured in
Maxwell Bay in a summer campaign were 17 µM NO3, 1.4 µM PO4 and 47 µM Si (Höfer et al., 2019).
Similarly, in Ryder Bay (Antarctic Peninsula), the lowest measured annual
macronutrient concentrations – occurring after strong drawdown during a
pronounced phytoplankton bloom (22 mg m-3 chlorophyll a) – were 2.5 µM NO3 and 0.4 µM PO4 (Annett et al., 2015). This
contrasts starkly with the summertime surface macronutrient distribution in
glaciated fjords in the Arctic, including Kongsfjorden (Fig. 3), where
surface macronutrient concentrations are typically depleted throughout
summer. These differences may explain why some Antarctic glacier fjords have
significantly higher chlorophyll and biomass than any of the Arctic
glacier fjord systems considered herein (Mascioni et al., 2019). However,
we note a general lack of seasonal and interannual data for Antarctic
glacier fjord systems precludes a comprehensive inter-comparison of these
different systems.
For a hypothetical nutrient flux from a glacier, the same flux could be
envisaged in two endmember scenarios: one several kilometres inside an
Arctic fjord (e.g. Godthåbsfjord or Kongsfjorden); and one at the
coastline of an isolated Southern Ocean island such as the Kerguelen (Bucciarelli
et al., 2001; Bowie et al., 2015), Heard (van der Merwe et al., 2019) or
South Shetland Islands (Höfer et al., 2019). In the
Arctic fjord, a pronounced Fe flux from summertime discharge would likely
have no immediate positive effect upon fjord-scale marine primary production
because Fe may already be replete (Hopwood
et al., 2016; Crusius et al., 2017). This is consistent with the observation
that Fe-rich discharge from land-terminating glaciers around west Greenland
does not have a positive fjord-scale fertilization effect (Meire et al., 2017) and may possibly be
associated with a negative effect (Table 1). Conversely, the same Fe input
into coastal waters around the Kerguelen Islands would be expected to have a
pronounced positive effect upon marine primary production, because the
islands occur within the world's largest HNLC zone. Where Fe is advected
offshore in the wake of the islands, a general positive effect on primary
production is expected (Blain
et al., 2001; Bucciarelli et al., 2001) even though there are marked changes
in the phytoplankton community composition between the Fe-enriched bloom
region (dominated by microphytoplankton) and the offshore HNLC area
(dominated by small diatoms and nanoflagellates) (Uitz et al., 2009). However,
even in these HNLC waters there are also other concurrent factors that
locally mitigate the effect of glacially derived Fe in nearshore waters,
because light limitation from near-surface particle plumes may locally
offset any positive effect of Fe fertilization (Wojtasiewicz et al., 2019).
Contrasting nutrient properties of water on the (a) southeast
Greenland shelf (data from Achterberg et al., 2018) with (b) the Ross Sea
shelf (data from Marsay et al., 2017). Note
the different scales used on the x axes.
The subglacial discharge pump; from macronutrients to iron
The effect of the subglacial discharge nutrient pump may similarly vary
with location. Contrasting the NO3 and DFe concentrations of marine
environments observed adjacent to different glacier systems suggests
substantial variations in the proximal limiting nutrient of these waters on
a global scale (Fig. 7). In Antarctic shelf regions, such as the western
Antarctic Peninsula, a high log-transformed ratio of summertime NO3:DFe
(median value 2) is indicative of Fe limitation. Across the Arctic there is
a broader range of ratios (median values -1.2 to 1.3) indicating spatial
variability in the balance between Fe and NO3 limitation (Fig. 7).
Variation is evident even within specific regions. The range of NO3:DFe
ratios for both the Gulf of Alaska (log10-2.5 to 1.7) and the south
Greenland shelf (log10-1.5 to 1.8) includes values that are indicative
of the full spectrum of responses from NO3 limitation to Fe/NO3
co-limitation to Fe limitation (Browning et al.,
2017). This suggests a relatively rapid spatial transition from excess to
deficient DFe conditions.
Variations in the ratio of dissolved NO3 and Fe in surface
waters (<20 m) adjacent to glaciated regions: whiskers show the
10th and 90th percentiles; bars shows the median, 25th percentile and 75th
percentile; and dots show all outliers. Data from the western Antarctic Peninsula (WAP,
Annett et al., 2017; Ducklow et al., 2017),
the south Greenland shelf (Achterberg et al., 2018;
Tonnard et al., 2020), Godthåbsfjord (Hopwood et al., 2016),
Kongsfjorden (Hopwood
et al., 2017), the Gulf of Alaska (Lippiatt et al., 2010) and the NE
Greenland shelf (Hopwood et al., 2018). For Kongsfjorden,
NO3 and Fe data were interpolated using the NO3–salinity
relationship.
How would the marine-terminating glacier upwelling effect operate in an
Fe-limited system? The physical mechanism of a nutrient pump would be
identical for glaciers with the same discharge and grounding line: one in a
high-Fe, low-NO3 Arctic system and one in a low-Fe, high-NO3
Antarctic system. However, the biogeochemical consequences with respect to
marine primary production would be different (Table 5). In the case of
subglacial discharge, for simplicity, we consider a mid-depth glacier
(grounding line of 100–250 m below sea level) with a constant discharge
rate of 250 m3 s-1. An entrainment factor of 6–10 would then be
predicted by plume theory (Fig. 5) (Carroll et al., 2016). In a
Greenland fjord with no sill to constrain circulation and a residence time
short enough that inflowing nutrient concentrations were not changed
significantly prior to entrainment, an average NO3 concentration of
5–12 µM is predicted in the entrained water compared to
∼2µM in glacier discharge (Hopwood et
al., 2018). Over a 2-month discharge period, this would produce a NO3
flux of 40–160 Mmol NO3, with 2 %–6 % of the NO3 flux arising
from meltwater discharge and 94 %–98 % from plume entrainment. Complete
utilization of this NO3 by phytoplankton according to the Redfield
ratio (106C:16N) (Redfield, 1934) would correspond to a
biological sink of 0.27–1.0 Gmol C.
In an analogous HNLC environment, surface NO3 requirements would
already vastly exceed phytoplankton requirements (Fig. 7) due to extensive
Fe limitation of primary production. Thus, whilst the upwelled NO3 flux
would be larger in an Fe-limited system, due to higher concentrations of
NO3 in the water column (see Fig. 6), the short-term biological effect
of upwelling NO3 alone would be negligible. More important would be the
upwelling of the proximal limiting nutrient Fe. If we assume that dissolved
Fe in the marine water column is in a stable, bioavailable form and that
additional dissolved Fe from freshwater is delivered to the marine
environment with a 90 %–99 % loss during estuarine mixing (Table 3), the
upwelled Fe flux can be estimated. Upwelled unmodified water from a depth of
100–250 m would be expected to contain 0.06–0.12 nM Fe (Marsay et al., 2017). The freshwater endmember
in the context of an Antarctic calving ice front would largely consist of
ice melt (rather than subglacial discharge, Hewitt, 2020), so we use an
intermediate freshwater Fe endmember of 33–680 nM in ice melt (Annett et al., 2017; Hodson et al., 2017).
Upwelling via the same hypothetical 250 m3 s-1 discharge as per the Arctic
scenario would generate a combined upwelled and discharge flux (after
estuarine removal processes) of 0.89–89 kmol Fe with 2 %–52 % of the Fe
arising from upwelling and 48 %–98 % from freshwater. Using an intermediate
Fe:C value of 5 mmol Fe mol-1C, which is broadly applicable to the
coastal environment (Twining and Baines, 2013), this would
correspond to a biological pool of 0.019–1.9 Gmol C. It should be noted
that the uncertainty on this calculation is particularly large because,
unlike NO3 upwelling, there is a lack of in situ data to constrain the
simultaneous mixing and non-conservative behaviour of Fe.
For a surface discharge of 250 m3 s-1, nutrient entrainment is
assumed to be negligible. In the case of Fe outflow into a low-Fe,
high-NO3 system, we assume that the glacier outflow is the dominant
local Fe source over the fertilized area during the discharge period (i.e. changes to other sources of Fe such as the diffusive flux from shelf
sediments are negligible). For the case of surface discharge into a
low-NO3, high-Fe system, this is not likely to be the case for
NO3. Stratification induced by discharge decreases the vertical flux of
NO3 from below, thus negatively affecting NO3 supply, although
there are to our knowledge no studies quantifying this change in
glacially modified waters.
Suppositional effect of different discharge scenarios calculated
from the Redfield ratio 106C:16N:1P:0.005Fe (Redfield,
1934; Twining and Baines, 2013). A steady freshwater discharge of 250 m3 s-1 is either released from a land-terminating glacier or from
a marine-terminating glacier at 100–250 m depth, in both cases for two
months into Fe-replete, NO3-deficient or Fe-deficient,
NO3-replete marine environments. Freshwater endmembers are defined as 2 µM NO3 and 33–675 nM dissolved Fe (Annett et al., 2017; Hodson et al.,
2017; Hopwood et al., 2018). Ambient water column conditions are defined as
Greenland (Achterberg et al., 2018)
(i.e. high-Fe, low-NO3) and Ross Sea (Marsay et al., 2017) (i.e. low-Fe,
high-NO3) shelf profiles.
It is clear from these simplified discharge scenarios (Table 5) that both
the depth at which glacier discharge is released into the water column and
the relative availabilities of NO3 and Fe in downstream waters could be
critical for determining the response of primary producers. The response of
primary producers in low-Fe regimes is notably subject to much larger
uncertainty, mainly because of uncertainty in the extent of Fe removal
during estuarine mixing (Schroth et al., 2014;
Zhang et al., 2015). Whilst the effects of the marine-terminating glacier
nutrient pump on macronutrient fluxes have been defined in numerous
systems, its effect on Fe availability is poorly constrained (Gerringa
et al., 2012; St-Laurent et al., 2017, 2019). Furthermore, Fe
bioavailability is conceptually more complicated than discussed herein, as
marine organisms at multiple trophic levels affect the speciation,
bioaccessibility and bioavailability of Fe, as well as the transfer between
less-labile and more-labile Fe pools in the marine environment (Poorvin et al.,
2004; Vraspir and Butler, 2009; Gledhill and Buck, 2012). Many microbial
species release organic ligands into solution, which stabilize dissolved Fe
as organic complexes. These feedbacks are challenging to model (Strzepek et al., 2005)
but may exert a cap on the lateral transfer of Fe away from glacier inputs (Lippiatt et al., 2010;
Thuroczy et al., 2012). To date, Fe fluxes from glaciers into the ocean have
primarily been constructed from an inorganic, freshwater perspective (Raiswell et
al., 2006; Raiswell and Canfield, 2012; Hawkings et al., 2014). Yet to
understand the net change in Fe availability to marine biota, a greater
understanding of how ligands and estuarine mixing processes moderate the
glacier-to-ocean Fe transfer will evidently be required (Lippiatt
et al., 2010; Schroth et al., 2014; Zhang et al., 2015).
Effects on the carbonate system
Beyond its impact on inorganic nutrient dynamics, glacial discharge also
affects the inorganic carbon system, commonly referred to as the carbonate
system, in seawater. The carbonate system describes the seawater buffer
system and consists of dissolved CO2 and carbonic acid, bicarbonate
ions and carbonate ions. These components buffer pH and are the main reason
for the ocean's capacity to absorb atmospheric CO2. The interaction
between these chemical species, which varies with physical conditions
including temperature and salinity (Dickson and
Millero, 1987), dictates the pH of seawater and the saturation state of
biologically important carbonate minerals such as aragonite and calcite
(ΩAr and ΩCa, respectively). Discharge generally reduces the
total alkalinity (TA, buffering capacity) of glacially modified waters
mainly through dilution (Fig. 8), which results in a decreased carbonate ion
concentration. Since carbonate ions are the main control on the solubility
of CaCO3, decreasing carbonate ion availability due to meltwater
dilution negatively impacts the aragonite and calcite saturation state (Doney et al., 2009; Fransson et al.,
2015). Glacier discharge can also moderate the carbonate system indirectly,
as higher primary production leads to increased biological dissolved
inorganic carbon (DIC) uptake, lower pCO2 and thus higher pH in
seawater. Therefore increasing or decreasing primary production also
moderates pH and the aragonite and calcite saturation state of marine
surface waters.
Total alkalinity measurements of glacial discharge across the Arctic reveal
a range from 20 to 550 µmol kg-1 (Yde
et al., 2005; Sejr et al., 2011; Rysgaard et al., 2012; Evans et al., 2014;
Fransson et al., 2015, 2016; Meire et al., 2015; Turk et al., 2016). Similar
to Si concentrations, the broad range is likely explained by different
degrees of interaction between meltwater and bedrock, with higher alkalinity
corresponding to greater discharge–bedrock interaction (Wadham et al., 2010;
Ryu and Jacobson, 2012), and also reflects local changes in bedrock geology (Yde et al., 2005; Fransson et al., 2015).
However, in absolute terms even the upper end of the alkalinity range
reported in glacial discharge is very low compared to the volume-weighted
average of Arctic rivers, 1048 µmol kg-1 (Cooper
et al., 2008). In an Arctic context, meltwater is therefore relatively
corrosive. In addition to low total alkalinity, glacier estuaries can
exhibit undersaturation of pCO2 due to the non-linear effect of salinity
on pCO2 (Rysgaard et al., 2012; Meire et al., 2015). This
undersaturation arises even when the freshwater endmember is in equilibrium
with atmospheric pCO2 and thus part of the CO2 drawdown observed in
Arctic glacier estuaries is inorganic and not associated with primary
production. In Godthåbsfjord this effect is estimated to account for
28 % of total CO2 uptake within the fjord (Meire et al., 2015).
Total alkalinity in Kongsfjorden during the meltwater season (data
from Fransson and Chierici, 2019). A decline in alkalinity is evident with
increasing freshwater fraction in response to the low alkalinity
concentrations in glacier discharge. Freshwater fraction was calculated
using an average marine salinity endmember of 34.96; hence some slightly
negative values are calculated in the outer fjord associated with the higher
salinity of unmodified Atlantic water. Linear regression details are shown
in Table S1.
By decreasing the TA of glacially modified waters (Fig. 8), glacier
discharge reduces the aragonite and calcite saturation states, thereby
amplifying the effect of ocean acidification (Fransson
et al., 2015, 2016; Ericson et al., 2019). High primary production can
mitigate this impact as photosynthetic CO2 uptake reduces DIC and
pCO2 (e.g. Fig. 9) in surface waters and increases the calcium carbonate
saturation state (Chierici
and Fransson, 2009; Rysgaard et al., 2012; Meire et al., 2015). In
relatively productive fjords, the negative effect of TA dilution may
therefore be counter balanced. However, in systems where discharge-driven
stratification is responsible for low productivity, increased discharge may
create a positive feedback on ocean acidification state in the coastal zone
resulting in a lower saturation state of calcium carbonate (Chierici
and Fransson, 2009; Ericson et al., 2019).
Low-calcium carbonate saturation states (Ω<1; i.e. corrosive conditions) have been observed in the inner part of Glacier Bay
(Alaska), demonstrating that glaciers can amplify seasonal differences in
the carbonate system and negatively affect the viability of shell-forming
marine organisms (Evans et al., 2014). Low ΩAr has also been
observed in the inner parts of Kongsfjorden, coinciding with high glacial
discharge (Fransson et al., 2016). Such critically low ΩAr
(<1.4) conditions have negative effects on aragonite-shell-forming
calcifiers such as the pteropod Limacina helicina (Comeau
et al., 2009, 2010; Lischka et al., 2011; Lischka and Riebesell, 2012;
Bednaršek et al., 2014). Under future climate scenarios, in addition to
the effect of increased glacier drainage in glacier fjords, synergistic
effects with a combination of increased ocean CO2 uptake and warming
will further amplify changes to the ocean acidification state (Fransson
et al., 2016; Ericson et al., 2019), resulting in increasingly pronounced
negative effects on calcium carbonate shell formation (Lischka and Riebesell, 2012).
Organic matter in glacial discharge
In addition to inorganic ions, glacial discharge also contains many organic
compounds derived from biological activity on glacier surfaces and
overridden sediments (Barker
et al., 2006; Lawson et al., 2014b). Organic carbon stimulates bacterial
activity, and remineralization of organic matter is a pathway to resupply
labile nitrogen and phosphorous to microbial communities. Similar to
macronutrient concentrations, DOM concentrations in glacial discharge are
generally low (Table 2) compared to runoff from large Arctic rivers, which
have DOM concentrations 1–2 orders of magnitude higher (Dittmar and Kattner, 2003;
Le Fouest et al., 2013). This is evidenced in Young Sound where dissolved
organic carbon (DOC) concentrations increase with salinity in surface
waters, demonstrating that glaciers are a relatively minor source of DOM to
the fjord (Paulsen et al., 2017).
While DOM concentrations are low in glacial discharge, the bioavailability
of this DOM is much higher than its marine counterpart (Hood
et al., 2009; Lawson et al., 2014b; Paulsen et al., 2017). This is likely
due to the low C:N ratio of glacial DOM, as N-rich DOM of microbial origin
is generally highly labile (Lawson et al., 2014a). It has
been suggested that as glaciers retreat and the surrounding catchments
become more vegetated, DOC concentrations in these catchments will increase (Hood
and Berner, 2009; Csank et al., 2019). However, DOM from non-glacial
terrestrial sources has a higher composition of aromatic compounds and thus
is less labile (Hood
and Berner, 2009; Csank et al., 2019). Furthermore, glacier coverage in
watersheds is negatively correlated with DOC:DON ratios, so a reduction in
the lability of DOM with less glacial coverage is also expected (Hood
and Scott, 2008; Hood and Berner, 2009; Ren et al., 2019).
While DOC is sufficient to drive bacterial metabolism, bacteria also depend
on nitrogen and phosphorus for growth. In this respect, bacteria are in
direct competition with phytoplankton for macronutrients, and increasing
additions of labile DOM downstream of glaciers could give bacteria a
competitive edge. This would have important ecological consequences for the
function of the microbial food web and the biological carbon sink (Larsen et al., 2015). Experiments with
Arctic fjord communities, including Kongsfjorden, have shown that when
bacteria are supplied with additional subsidies of labile carbon under
nitrate limitation, they outcompete phytoplankton for nitrate (Thingstad et al., 2008;
Larsen et al., 2015). This is even the case when there is an addition of
excess Si, which might be hypothesized to give diatoms a competitive
advantage. The implications of such competition for the carbon cycle are
however complicated by mixotrophy (Ward and Follows, 2016; Stoecker et
al., 2017). An increasing number of primary producers have been shown to be
able to simultaneously exploit inorganic resources and living prey,
combining autotrophy and phagotrophy in a single cell. Mixotrophy allows
protists to sustain photosynthesis in waters that are severely
nutrient limited and provides an additional source of carbon as a supplement
to photosynthesis. This double benefit decreases the dependence of primary
producers on short-term inorganic nutrient availability. Moreover,
mixotrophy promotes a shortened, and potentially more efficient, chain from
nutrient regeneration to primary production (Mitra et al.,
2014). Whilst mixotrophy is sparsely studied in Arctic glacier fjords, both
increasing temperatures and stratification are expected to favour
mixotrophic species (Stoecker and Lavrentyev,
2018), and thus an understanding of microbial food web dynamics is vital to
predict the implications of increasing discharge on the carbon cycle in
glacier fjord systems.
Regardless of the high bioavailability of DOM from glacial discharge, once
glacial DOM enters a fjord and is diluted by ocean waters, evidence of its
uptake forming a significant component of the microbial food web in the
Arctic has yet to be observed. Work from several outlet glacier fjords
around Svalbard shows that the stable isotopic C ratio of bacteria does not
match that of DOC originating from local glaciers, suggesting that glacially
supplied DOC is a minor component of bacterial consumption compared to
autochthonous carbon sources (Holding
et al., 2017; Paulsen et al., 2018). Curiously, a data synthesis of
taxonomic populations for glaciated catchments globally suggests a
significant positive effect of glaciers on bacterial populations in glacier
fjords but a negative effect in freshwaters and glacier forefields
(Cauvy-Fraunié and Dangles, 2019). This suggests that multiple
ecological and physical–chemical processes are at play, such that a
simplistic argument that increasing glacial supply of DOC favours bacterial
activity is moderated by other ecological factors. This is perhaps not
surprising as different taxonomic groups may respond differently to
perturbations from glacier discharge leading to changes in food web dynamics.
For example, highly turbid glacial waters have particularly strong negative
effects on filter-feeding (Arendt et al., 2011; Fuentes et al., 2016) and
phagotrophic organisms (Sommaruga, 2015) and may also lead to reduced viral
loads in the water column due to adsorption onto particle surfaces (Maat et
al., 2019).
Whilst concentrations of DOM are low in glacier discharge, DOM-sourced
nitrogen and phosphorous could still be relatively important in stratified
outlet glacier fjords simply because inorganic nutrient concentrations are
also low (e.g. Fig. 3). Refractory DON in rivers that is not directly
degraded by bacteria can be subsequently broken down by photoammonification
processes releasing ammonium (Xie et al., 2012). In large
Arctic rivers, this nitrogen supply is greater than that supplied from
inorganic sources (Le Fouest et al., 2013). For glacier
discharge, processing of refractory DOM could potentially produce a
comparable nitrogen flux to inorganic sources (Table 2, Wadham et al.,
2016). Similarly, in environments where inorganic PO4 concentrations
are low, DOP may be a relatively more important source of phosphorous for
both bacteria and phytoplankton. Many freshwater and marine phytoplankton
species are able to synthesize the enzyme alkaline phosphatase in order to
efficiently utilize DOP (Hoppe, 2003;
Štrojsová et al., 2005). In the context of stratified, low-salinity
inner-fjord environments, where inorganic PO4 concentrations are
potentially low enough to limit primary production (Prado-Fiedler,
2009), this process may be particularly important – yet DOP dynamics are
understudied in glaciated catchments with limited data available
(Stibal et al., 2009, Hawkings et al., 2016).
Finally, whilst DOC concentrations in glacier discharge are low, POC
concentrations, which may also impact microbial productivity in the marine
environment and contribute to the C sink within fjords, are less well
characterized. Downstream of Leverett Glacier, mean runoff POC
concentrations are reported to be 43–346 µM – 5 times higher than DOC (Lawson
et al., 2014b). However, the opposite is reported for Young Sound, where DOC
concentrations in three glacier-fed streams were found to be 7–13 times
higher than POC concentrations (Paulsen et al., 2017). Similarly,
low POC concentrations of only 5 µM were found in supraglacial
discharge at Bowdoin glacier (Kanna et al., 2018). In summary,
relatively little is presently known about the distribution, fate and
bioavailability of POC in glaciated catchments.
Insights into the long-term effects of glacier retreat
Much of the present interest in Arctic ice–ocean interactions arises because
of the accelerating increase in discharge from the Greenland Ice Sheet,
captured by multi-annual to multi-decadal time series (Bamber et al., 2018).
This trend is attributed to atmospheric and oceanic warming due to
anthropogenic forcing, at times enhanced by persistent shifts in atmospheric
circulation (Box, 2002; Ahlström et al., 2017). From existing
observations, it is clear that strong climate variability patterns are at
play, such as the North Atlantic Oscillation/Arctic Oscillation, and that, in
order to place recent change in context, time series exceeding the satellite
era are required. Insight can be potentially gained from research into past
sedimentary records of productivity from high-latitude marine and fjord
environments. Records of productivity and the dominance of different taxa as
inferred by microfossils, biogeochemical proxies and genetic records from
those species that preserve well in sediment cores can help establish
long-term spatial and temporal patterns around the present-day ice sheet
periphery (Ribeiro
et al., 2012). Around Greenland and Svalbard, sediment cores largely
corroborate recent fjord-scale surveys suggesting that inner-fjord water
column environments are generally low-productivity systems (Kumar et al., 2018), with protist taxonomic
diversity and overall productivity normally higher in shelf waters than in
inner-fjord environments (Ribeiro et al., 2017).
Several paleoclimate archives and numerical simulations suggest that the
Arctic was warmer than today during the early to mid-Holocene thermal
maximum (∼8000 years ago), which was registered by
∼1 km thinning of the Greenland Ice Sheet (Lecavalier et al., 2017). Multiproxy
analyses performed on high-resolution and well-dated Holocene marine
sediment records from contrasting fjord systems are therefore one approach
to understand the nature of such past events, as these sediments
simultaneously record climate and some long-term biotic changes representing
a unique window into the past. However, while glacial–interglacial
changes can provide insights into large-scale ice–ocean interactions and the
long-term impact of glaciers on primary production, these timescales are of
limited use to understanding more recent variability at the ice–ocean
interface of fjord systems such as those mentioned in this review. The five
well-characterized Arctic fjords used as case studies here (Fig. 1; Bowdoin,
Kongsfjorden, Sermilik, Godthåbsfjord and Young Sound), for example, did
not exist during the Last Glacial Maximum ∼19 000 years ago (Knutz et al., 2011).
On long timescales, glacier–ocean interactions are subject to marked
temporal changes associated with glacial–interglacial cycles. In the
short term, the position of glacier termini shifts inland during ice sheet
retreat or outwards during ice sheet expansion, and in the long-term
proglacial regions respond to isostatic uplift and delta progradation. The
uplift of fine-grained glaciomarine and deltaic sediments is a notable
feature of landscape development in fjord environments following the retreat
of continental-scale ice sheets (Cable et al., 2018;
Gilbert et al., 2018). This results in the gradual exposure and subsequent
erosion of these sediment infills and their upstream floodplains, releasing
labile organic matter to coastal ecosystems. Whilst the direct
biogeochemical significance of such chemical fluxes may be limited in the
marine environment on interannual timescales (Table 2), potentially more
important is the Fe fertilization following wind erosion and dust emittance
from glacial floodplains.
Ice core records from Greenland and Antarctica, spanning several climatic
cycles, suggest that aeolian deposition rates at high latitudes were as much
as 20 times greater during glacial than interglacial periods (Kohfeld and Harrison, 2001).
Elevated input of terrigenous Fe during windy glacial episodes, and
associated continental drying, has therefore been hypothesized to stimulate
oceanic productivity through time and thus modify the oceanic and
atmospheric CO2 balance (Martin, 1990). While there seems to
be a pervasive dust–climate feedback on a glacial–interglacial planetary
scale (Shaffer and Lambert, 2018), glacier retreat
also exposes new areas of unconsolidated glacial sediments leading to an
increase in both dust storm events and sediment yields from glacial basins
locally. The spatial scale over which this glacially derived dust can be
transported (100–500 km) far exceeds that of discharge-carried nutrients (Crusius et
al., 2011; Prospero et al., 2012; Bullard, 2013).
A need for new approaches?
The pronounced temporal and spatial variations evident in the properties of
glacially modified waters emphasize the need for high-resolution data on
both short (hourly to daily) and long (seasonal to interannual) timescales
in order to understand glacial processes and their downstream effects. In
Godthåbsfjord, Juul-Pedersen et al. (2015) provide a
detailed study of seasonal primary production dynamics. This monthly
monitoring programme captures seasonal, annual and interannual trends in the
magnitude of primary production. Whilst such a time series clearly highlights
a strong interannual stability in both seasonal and annual primary
production (103.7±17.8 g C m-2 yr-1; Juul-Pedersen et al.,
2015), it is unable to fully characterize shorter (i.e. days
to weeks) timescale events such as the spring bloom period. Yet higher data
resolution cannot feasibly be sustained by shipboard campaigns.
Low-frequency, high-discharge events are known to occur in
Godthåbsfjord, and other glacier fjords (Kjeldsen et al., 2014), but are
challenging to observe from monthly resolution data, and thus there is sparse
data available to quantify their occurrence and effects or to quantify the
short-term variation in discharge rates at large, dynamic marine-terminating
glaciers. Consequently, modelled subglacial discharge rates and glacier
discharge derived from regional models (e.g. RACMO, Noël et al., 2015), which underpin our best-available
estimates of the subglacial nutrient pump (e.g. Carroll et al., 2016),
do not yet consider such variability. Time lapse imagery shows that the
lifetimes and spatial extents of subglacial discharge plumes can vary
considerably (Schild et al., 2016; Fried et al.,
2018). While buoyant plume theory has offered important insights into the
role of subglacial plumes in the nutrient pump, buoyant plume theory does
not characterize the lateral expansion of plume waters. Furthermore,
determining the influence of discharge, beyond the immediate vicinity of
glacial outflows, is a Lagrangian exercise, yet the majority of existing
observational and modelling studies have been conducted primarily in the
Eulerian reference frame (e.g. ship-based profiles and moored observations
that describe the water column at a fixed location). Moving towards an
observational Lagrangian framework will require the deployment of new
technology such as the recent development of low-cost GPS trackers which,
especially when combined with in situ sensors, may improve our understanding of the
transport and mixing of heat, freshwater, sediment and nutrients downstream
of glaciers (Carlson et
al., 2017; Carlson and Rysgaard, 2018). For example, GPS trackers deployed
on “bergy bits” have revealed evidence of small-scale, retentive eddies in
Godthåbsfjord (Carlson et al., 2017) and
characterized the surface flow variability in Sermilik Fjord (Sutherland et al., 2014).
Unmanned aerial vehicles and autonomous surface/underwater vehicles can also
be used to observe the spatio-temporal variability of subglacial plumes at
high resolution (Mankoff et
al., 2016; Jouvet et al., 2018). Complementing these approaches are
developments in the rapidly maturing field of miniaturized chemical sensors
suitable for use in cryosphere environments (Beaton et al., 2012).
Such technology will ultimately reduce much of the uncertainty associated
with glacier–ocean interactions by facilitating more comprehensive, more
sustainable field campaigns (Straneo et al.,
2019), with reduced costs and environmental footprints (Nightingale
et al., 2015; Grand et al., 2017, 2019). This is evidenced by a successful
prolonged mooring deployment in the Santa Inés Glacier fjord system
(Fig. 9).
Winter–spring dynamics of salinity, pH and pCO2 at the Santa
Inés Glacier fjord, Ballena (Patagonia). High-resolution pCO2 and pH
measurements (every three hours) were taken in situ using autonomous SAMI-CO2
and SAMI-pH sensors (as per Vergara‐Jara et al., 2019)
(Sunburst Sensors, LLC) starting in the austral autumn
(March 2018). All sensors were moored at 10 m depth.
The Santa Inés Glacier fjord sits adjacent to the open water of the
Straits of Magellan in southwest Patagonia. Moored high-resolution
measurements are now collected in situ using sensor technology and a mooring within
the fjord. Measurements include the carbonate system parameters pCO2 and
pH. The 2018 winter to spring time series (Fig. 9) demonstrates a sharp
decline in pCO2 and corresponding increase in pH, associated with the
onset of the spring bloom in early October. Such a pronounced event,
occurring over ∼2 weeks, would be impossible to characterize
fully with monthly sampling of the fjord. Over winter, pH and pCO2 were
more stable, but sensor salinity data still reveal short-term dynamics
within the fjords' surface waters (Fig. 9). A general decline in salinity is
evident moving from winter into spring. Short-term changes on diurnal
timescales – presumably linked to tidal forcing – and also on daily–weekly
timescales – possibly linked to weather patterns – are also evident (Fig. 9).
Much work remains to be done to deduce the role of these short-term drivers
on primary production.
Finally, we note that the different scales over which the processes
discussed herein operate raises the critical question of how importantly the
different effects of glacial discharge on the marine environment are
perceived in different research fields. Herein we have largely focused on
local- to regional-scale processes operating on seasonal to inter-annual
timescales in the marine environment at individual field sites (Fig. 1). A
very different emphasis may have been placed on the relative importance of
different processes if a different spatial/temporal perspective had been
adopted, for example considering the decadal–centennial effects of increasing
meltwater addition to the Atlantic Ocean, or conversely the seasonal effect
of meltwater solely within terrestrial systems. One conceptual way of
comparing some of the different processes and effects occurring as a result of
glacial discharge is to consider a single biogeochemical cycle on a global
scale, for example the carbon drawdown associated with marine primary
production (Fig. 10).
A scale comparison of the significance of different
chemical/physical processes driven by glacial discharge in terms of the
resulting effects on annual marine primary production (PP) or CO2
drawdown (units Tg C yr-1). Bold lines indicate mean estimates based on
multiple independent studies; dashed lines are based on only one. Green–blue
colours are positive; grey colours are negative. Calculated changes
(largest–smallest) are determined from glacial discharge superimposed on a
modelled global RCP8.5 scenario (Kwiatkowski et
al., 2019), pCO2 uptake due to meltwater-induced undersaturation scaled
to the Greenland Ice Sheet (Meire et al., 2015), computed upwelled NO3
fluxes (assuming 100 % utilization at Redfield ratio, Hopwood et al.,
2018), mean freshwater NO3 (Greenland) inventory (Table 3), NO3
anomaly due to upwelling in Sermilik Fjord (Cape et al., 2019), and
contrasting the mean PP for groups II and IV (Table 1) for a fjord the size
of Young Sound.
A net decrease in primary production is predicted over the 21st century at
the Atlantic scale on the order of >60 Tg C yr-1 mm-1
of annual sea-level rise from Greenland due solely to the physical effects
of freshwater addition (Kwiatkowski et al.,
2019). An example of a potential negative effect on primary production
operating on a much smaller scale would be the retreat of marine-terminating
glaciers and the associated loss of NO3 upwelling (Torsvik et al., 2019). The effect of switching
a modest glacier fjord the size of Young Sound from being a higher-productivity marine-terminating glacier fjord environment to a low-productivity glacier fjord environment receiving runoff only from
land-terminating glaciers (using mean primary production values from Table 1) would be a change of ∼0.01 Tg C yr-1. Conversely,
potential positive effects of glacier discharge on primary production can be
estimated using the Redfield ratio (Redfield, 1934) to
approximate how much primary production could be supported by NO3
supplied to near-surface waters from meltwater-associated processes. Adding
all the NO3 in freshwater around Greenland (Table 3) into the ocean, in the absence of any confounding physical effects from stratification, would
be equivalent to primary production of ∼0.09 Tg C yr-1.
Using the same arbitrary conversion to scale other fluxes, the primary
production potentially supported by upwelling of NO3 at Sermilik (Cape et al., 2019) is approximately 0.13 Tg C yr-1 and that supported by upwelling of NO3 at 12 large
Greenlandic marine-terminating systems (Hopwood et al.,
2018) is approximately 1.3 Tg C yr-1. Finally the inorganic CO2
drawdown due to pCO2 undersaturation in glacier estuaries around
Greenland is approximately 1.8 Tg C yr-1 (Meire et al., 2015).
These values provide a rough conceptual framework for evaluating the
relative importance of different processes operating in parallel but on
different spatial scales (Fig. 10). Whilst a discussion of glacial
weathering processes is beyond the scope of this review, we note that these
estimates of annual C fluxes (Fig. 10) are comparable to, or larger than,
upper estimates of the CO2 drawdown/release associated with weathering
of carbonate, silicate and sulfide minerals in glaciated catchments
globally (Jones et al., 2002; Tranter et al., 2002; Torres et al., 2017).
The implication of this is that shifts in glacier–ocean inter-connectivity
could be important compared to changes in weathering rates in glaciated
catchments in terms of feedbacks in the C cycle on inter-annual timescales.
A link between retreating glaciers and harmful algal blooms?
Shifts between different microbial groups in the ocean can have profound
implications for ecosystem services. For example, addition of DOM can induce
shifts in the microbial loop to favour bacteria in their competition with
phytoplankton for macronutrient resources, which directly affects the
magnitude of CO2 uptake by primary producers (Thingstad et al., 2008;
Larsen et al., 2015). Similarly, changing the availability of Si relative to
other macronutrients affects the viability of diatom growth and thus, due to
the efficiency with which diatom frustules sink, potentially the efficiency
of the biological carbon pump (Honjo and
Manganini, 1993; Dugdale et al., 1995).
A particularly concerning hypothesis, recently proposed from work across
Patagonian fjord systems and the first evaluations of harmful algal bloom
(HAB)-associated species around Greenland, is that changes in glacier
discharge and associated shifts in stratification and temperature could
affect HAB occurrence (Richlen et al., 2016;
León-Muñoz et al., 2018; Joli et al., 2018). In the Arctic, very
little work has been done to specifically investigate HAB occurrence and
drivers in glacier-discharge-affected regions. Yet HAB-associated species
are known to be present in Arctic waters (Lefebvre
et al., 2016; Richlen et al., 2016), including Alexandrium tamarense, which has been implicated as
the cause of toxin levels exceeding regulatory limits in scallops from west
Greenland (Baggesen et al., 2012), and Alexandrium fundyense, cysts of which have been found at
low concentrations in Disko Bay (Richlen et al., 2016). Around Greenland,
low temperatures are presently thought to be a major constraint on HAB
development (Richlen et al., 2016). Yet increasing meltwater discharge into
coastal regions drives enhanced stratification and thus directly facilitates
the development of warm surface waters through summer. This meltwater-driven
stratification has been linked to the occurrence of HAB species including
the diatoms Pseudo-nitzschia spp. (Joli et al., 2018). Thus, increasing freshwater discharge
from Greenland could increase HAB viability in downstream stratified marine
environments (Richlen et al., 2016; Joli et al., 2018; Vandersea et al.,
2018), potentially with negative impacts on inshore fisheries.
Given the ongoing intensification of climate change and the interacting
effects of different environmental drivers of primary production in
glacier fjord systems (e.g. surface warming, carbonate chemistry, light
availability, stratification, nutrient availability and zooplankton
distribution), it is however very challenging to predict future
changes on HAB event frequency and intensity. Furthermore, different HAB-associated groups (e.g. toxin-producing diatom and flagellate species) may
show opposite responses to the same environmental perturbation (Wells et al., 2015). Moreover, many known
toxin-producing species in the Arctic are mixotrophic, further complicating
their interactions with other microbial groups (Stoecker and Lavrentyev, 2018). Fundamental knowledge gaps clearly remain concerning the mechanisms of HAB development,
and there are practically no time series or studies to date investigating
changes specifically in glaciated Arctic catchments. Given the
socio-economic importance of glacier-fjord-scale subsistence fisheries,
especially around Greenland, one priority for future research in the Arctic
is to establish to what extent HAB-associated species are likely to benefit
from future climate scenarios in regions where freshwater runoff is likely
to be subject to pronounced ongoing changes (Baggesen et al., 2012; Richlen et al., 2016; Joli et al., 2018).
Understanding the role of glaciers alongside other manifestations of
climate change
The approximate spatial scale over which glaciers directly affect
different drivers of marine primary production (PP) compared to the likely
limiting resources constraining primary production.
In order to comprehensively address the questions posed in this review, it
is evident that a broader perspective than a narrow focus on freshwater
discharge alone, and its regional biogeochemical effects, is required (Fig. 10). Freshwater discharge is not the sole biogeochemical connection between
the glaciers and the ocean (Fig. 11). Dust plumes from proglacial terrain
supply glacial flour to the ocean on scales of >100 km and thus
act as an important source of Fe to the ocean at high latitudes, where other
atmospheric dust sources are scarce (Prospero et
al., 2012; Bullard, 2013). Similarly, icebergs have long been speculated to
act as an important source of Fe to the offshore ocean (Hart, 1934;
Raiswell et al., 2008; Lin et al., 2011) and induce mixing of the surface
ocean (Helly
et al., 2011; Carlson et al., 2017). Whilst freshwater discharge is a driver
of biogeochemical changes in nearshore and fjord environments downstream of
glaciers (Arimitsu et al., 2016), the distant
(>100 km scale) biogeochemical effects of glaciers on the marine
environment are likely dominated by these alternative mechanisms (Fig. 11).
Furthermore, the distal physical effects of adding increasingly large
volumes of glacier discharge into the Atlantic may have biogeochemical
feedbacks which, whilst poorly studied, are potentially far larger than
individual regional-scale processes discussed herein (Fig. 10) (Kwiatkowski
et al., 2019).
Discharge-derived effects must also be interpreted in the context of other
controls on primary production in the high-latitude marine environment.
Sea-ice properties, and particularly the timing of its breakup and the
duration of the ice-free season, are a key constraint on the seasonal trend
in primary production in the Arctic (Rysgaard et
al., 1999; Rysgaard and Glud, 2007). Similarly, whilst discharge affects
multiple aspects of the three-dimensional water column including fjord-scale
circulation and mixing (Kjeldsen et
al., 2014; Carroll et al., 2017), stratification (Meire et al., 2016b; Oliver
et al., 2018), and boundary current properties (Sutherland et al., 2009), other changes in
the Earth system including wind patterns (Spall
et al., 2017; Sundfjord et al., 2017; Le Bras et al., 2018), sea-ice
dynamics, regional temperature increases (Cook et al., 2016),
and other freshwater sources (Benetti et al., 2019) are driving changes in
these parameters on similar spatial and temporal scales (Stocker et al., 2013;
Hop et al., 2019).
Several key uncertainties remain in constraining the role of glaciers in the
marine biogeochemical system. Outlet glacier fjords are challenging
environments in which to gather data, and there is a persistent deficiency of
both physical and biogeochemical data within kilometres of large
marine-terminating glacier systems, where glacier discharge first mixes with
ocean properties. Subglacial discharge plume modelling and available data
from further downstream can to some extent evade this deficiency for
conservative physical (e.g. salinity and temperature) and chemical (e.g.
noble gases, NO3 and PO4) parameters in order to understand mixing
processes (Mortensen
et al., 2014; Carroll et al., 2017; Beaird et al., 2018). However, the
mixing behaviour of non-conservative chemical parameters (e.g. pH, Si, and
Fe) is more challenging to deduce from idealized models. Furthermore, the
biogeochemical effects of low-frequency, high-discharge events and
small-scale mixing, such as that induced around icebergs, remain largely
unknown. There is a critical need to address this deficiency by the
deployment of new technology to study marine-terminating glacier mixing
zones and downstream environments.
The uniqueness of individual glacier fjord systems, due to highly variable
fjord circulation and geometry, is itself a formidable challenge in
scaling up results from Arctic field studies to produce a process-based
understanding of glacier–ocean interactions. A proposed solution, which
works equally well for physical, chemical and biological perspectives, is to
focus intensively on a select number of key field sites at the land–ocean
interface rather than mainly on large numbers of broadscale,
summertime-only surveys (Straneo et al.,
2019). In addition to facilitating long-term time series, focusing in detail
on fewer systems facilitates greater seasonal coverage to understand the
changes in circulation and productivity that occur before, during and after
the melt season. However, the driving rationale for the selection of key
glacier field sites to date was in many cases their contribution to sea-level
rise. Thus, well-studied sites account for a large fraction of total Arctic
glacier discharge into the ocean but only represent a small fraction of the
glaciated coastline. For example, around the Greenland coastline, the
properties of over 200 marine-terminating glaciers are characterized (Morlighem
et al., 2017). Yet just 5 glaciers (including Helheim in Sermilik Fjord)
account for 30 % of annual combined meltwater and ice discharge from
Greenland, and 15 account for >50 % (year 2000 data,
Enderlin et al., 2014). The relative importance of
individual glaciers changes when considering longer time periods (e.g.
1972–2018, Mouginot
et al., 2019), yet, irrespective of the timescale considered, a limited
number of glaciers account for a large fraction of annual discharge.
Jakobshavn Isbræ and Kangerlussuaq, for example, are among the largest four
contributors to ice discharge around Greenland over both historical
(1972–2018) and recent (2000–2012) time periods (Enderlin
et al., 2014; Mouginot et al., 2019). Whilst small glaciated catchments,
such as Kongsfjorden and Young Sound, are far less important for sea-level
rise, similar “small” glaciers occupy a far larger fraction of the high-latitude coastline and are thus more representative of glaciated coastline habitat.
ConclusionsWhere and when does glacial freshwater discharge promote or reduce marine primary production?
In the Arctic, marine-terminating glaciers are associated with the enhanced
vertical fluxes of macronutrients, which can drive summertime phytoplankton
blooms throughout the meltwater season.
In the Arctic, land-terminating glaciers are generally associated with the
local suppression of primary production, due to light limitation and
stratification impeding vertical nutrient supply from mixing. Primary
production in Arctic glacier fjords without marine-terminating glaciers is
generally low compared to other coastal environments.
In contrast to the Arctic, input of Fe from glaciers around the Southern
Ocean is anticipated to have a positive effect on marine primary production,
due to the extensive limitation of primary production by Fe.
In some brackish, inshore waters, DOM from glaciated catchments could
enhance bacterial activity at the expense of phytoplankton, but a
widespread effect is unlikely due to the low DOM concentration in
freshwater.
Glacier discharge reduces the buffering capacity of glacially modified
waters and amplifies the negative effects of ocean acidification, especially
in low-productivity systems, which negatively affects calcifying organisms.
How does spatio-temporal variability in glacial discharge affect marine primary production?
Glacier retreat associated with a transition from marine- to land-terminating systems is expected to negatively affect downstream productivity
in the Arctic, with long-term inland retreat also changing the
biogeochemical composition of freshwater.
Low-frequency, high-discharge events are speculated to be important drivers
of physical and biogeochemical processes in the marine environment, but
their occurrence and effects are poorly constrained.
HAB viability may increase in future Arctic glacier fjords in response to
increasing discharge driving enhanced stratification, but there are very
limited data available to test this hypothesis.
A time series in Godthåbsfjord suggests that, on inter-annual timescales,
fjord-scale primary production is relatively stable despite sustained
increases in glacier discharge.
How far-reaching are the effects of glacial discharge on marine
biogeochemistry?
Local effects of glaciers (within a few kilometres of the terminus, or within glacier fjords) include light suppression,
impediment of filter-feeding organisms and influencing the foraging habits
of higher organisms.
Mesoscale effects of glaciers (extending tens to hundreds of kilometres from the terminus) include nutrient upwelling, Fe
enrichment of seawater, modification of the carbonate system (both by
physical and biological drivers) and enhanced stratification.
Remote effects are less certain. Beyond the 10–100 km scale over which
discharge plumes can be evident, other mechanisms of material transfer
between glaciers and the ocean, such as atmospheric deposition of glacial
flour and icebergs, are likely more important than meltwater (Fig. 11). Fully
coupled biogeochemical and physical global models will be required to fully
assess the impacts of increasing discharge into the ocean on a pan-Atlantic
scale (Fig. 10).
Data availability
Data sources are cited within the text. For primary production data, see Andersen (1977), Nielsen and Hansen (1995), Jensen et al. (1999), Nielsen (1999), Levinsen and Nielsen (2002), Juul-Pedersen et al. (2015), Meire et al. (2017), Lund-Hansen et al. (2018), Hop et al. (2002), Iversen and Seuthe (2011), Hodal et al. (2012), van de Poll et al. (2018), Seifert et al. (2019), Smoła et al. (2017), Rysgaard et al. (1999), Holding et al. (2019), Harrison et al. (1982), and Reisdorph and Mathis (2015). For chemical data and associated fluxes, see Fransson et al. (2016), van de Poll et al. (2018), Cantoni et al. (2019), Cauwet and Sidorov (1996), Emmerton et al. (2008), Hessen et al. (2010), Hopwood et al. (2016, 2017, 2018), Kanna et al. (2018), Cape et al. (2019), Hawkings et al. (2014, 2017), Lund-Hansen et al. (2018), Meire et al. (2015, 2016a), Brown et al. (2010), Paulsen et al. (2017), Stevenson et al. (2017), Statham et al. (2008), Bhatia et al. (2010, 2013a, 2013b), Lawson et al. (2014b), Hood et al. (2015), Csank et al. (2019), Wadham et al. (2016), Achterberg et al. (2018), Marsay et al. (2017), Annett et al. (2017), Ducklow et al. (2017), Tonnard et al. (2020), Lippiatt et al. (2010), Fransson and Chierici (2019), Vergara-Jara et al. (2019), and Kwiatkowski et al. (2019). For discharge plume properties, see Carroll et al. (2016), Halbach et al. (2019), Kanna et al. (2018), Mankoff et al. (2016), Meire et al. (2016b), Jackson et al. (2017), Bendtsen et al. (2015), Beaird et al. (2018), and Schaffer et al. (2020).
The supplement related to this article is available online at: https://doi.org/10.5194/tc-14-1347-2020-supplement.
Author contributions
TD coordinated workshop activities and designed questions to structure the review paper. MJH coordinated manuscript writing. All authors contributed to writing at least one section of the review and assisted with the revision of other sections. DC edited all figures.
Competing interests
The authors declare that they have no conflict of interest.
Acknowledgements
The authors thank all conveners and participants of the IASC cross-cutting
activity “The importance of Arctic glaciers for the Arctic marine ecosystem”
hosted by the Cryosphere Working Group/Network on Arctic Glaciology and the
Marine Working Group. IASC funding to support early career scientist
attendance is gratefully acknowledged. Figure 7 and all
linear regressions were produced in SigmaPlot.
Financial support
Mark Hopwood was financed by the DFG (award number HO 6321/1-1). Andy Hodson was supported by Joint Programming Initiative (JPI-Climate Topic 2: Russian Arctic and Boreal Systems) award 71126 and Research Council of Norway grant 294764. Johnna Holding was supported by Marie Curie grant GrIS-Melt (752325). Lorenz Meire was supported by the VENI program from the Dutch Research Council (NWO grant 016.Veni.192.150). José L. Iriarte received support from the FONDECYT 1170174 project. Sofia Ribeiro received support from Geocenter Denmark (project GreenShift). Thorben Dunse was supported by the Nordforsk-funded project (GreenMAR).The article processing charges for this open-access publication were covered by a Research Centre of the Helmholtz Association.
Review statement
This paper was edited by Evgeny A. Podolskiy and reviewed by Jon Hawkings and Kiefer Forsch.
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