Introduction
Freshwater ecosystems cover less than 10 % of global ice-free land area
(Lehner and Doll, 2004) and have been typically overlooked as substantial
contributors to, or sinks of, atmospheric carbon greenhouse gases (GHGs;
Bastviken et al., 2011). However, recent studies suggest inland lakes
collectively receive and process carbon at magnitudes similar to oceanic
uptake and sediment burial, making them important systems within the global
carbon cycle (Cole et al., 2007; Battin et al., 2009; Tranvik et al., 2009;
Maberly et al., 2013; Raymond et al., 2013). Northern latitudes, between
approximately 45 and 75∘ N, contain the highest abundance of
lakes, ponds, and wetlands on the planet (Lehner and Doll, 2004) due to
historical glaciations and moderate annual precipitation. These regions also
contain the world's largest below-ground stores of organic carbon (Tarnocai
et al., 2009). These carbon- and lake-rich northern ecosystems, therefore,
have been critically important sinks historically and will potentially be strong
emitters of this legacy carbon moving forward (ACIA, 2004).
Most northern lakes are net sources of the GHG carbon dioxide (CO2) to
the atmosphere (Jonsson et al., 2003; Tranvik et al., 2009, Laurion et al.,
2010). Cold climates, short growing seasons, and light limitation in
carbon-rich waters can inhibit CO2 uptake by aquatic primary producers
(Karlsson et al., 2009). Conversely, heterotrophic respiration by microbes
continues perennially in most lake waters and sediments, therefore
continuously releasing CO2 to the water column. Turbulence, water
temperature, degree of ice cover, and other factors may then influence the
intensity of CO2 emissions to the atmosphere. Lakes in carbon-rich low
Arctic regions (∼ 60–70∘ N, AMAP, 1998) can account
for more than three-quarters of a landscape's net CO2 emissions to the
atmosphere (Abnizova et al., 2012). At the same time, saturated peatlands
and shallow ponds and lakes throughout much of the low Arctic can also be
robust emitters of the potent GHG methane (CH4) to the atmosphere.
Anoxic conditions in saturated, shallow, organic-rich soils have strong
potential for methanogenic production and release of CH4 into water
(Tagesson et al., 2012). Due to its poor solubility, CH4 can then be
effectively released to the atmosphere from these ecosystems by ebullition
and wind turbulence, perhaps contributing up to 12 % of all global
emissions (Lai, 2009; Walter et al., 2006). These dynamic and carbon-rich
environments, though, are not ubiquitous across the north, particularly
towards the highest-latitude regions.
In the high Arctic (> ∼ 70∘ N; AMAP,
1998), lake abundance and area are dramatically reduced in the landscape.
The prevalence of cold and dry high-pressure air masses results in a
semi-arid climate with relatively well-drained and unproductive inorganic
soils (Campbell and Claridge, 1992). This environment, therefore,
discourages surface water retention, with often less than 5 % of the
landscape being covered by aquatic systems. These conditions, in most cases,
restrict primary production and accumulation of organic matter across these
landscapes compared to the low Arctic, with mostly unknown implications for
carbon GHG exchange in high Arctic lakes and ponds. Considering these
challenging climatic conditions, it may be easy to overlook the high Arctic,
and its freshwater systems, as important contributors to global carbon
cycling (Soegaard et al., 2000; Lloyd, 2001; Lund et al., 2012, Lafleur et
al., 2012). However, recent studies have shown that, where conditions are
favourable (e.g. moist, organic-rich lowlands), high Arctic ecosystems
exchange GHGs at rates similar to ecosystems at more southerly latitudes
(Emmerton et al., 2016). Lack of a broad understanding of carbon cycling in
high Arctic freshwater systems is further complicated by rapidly changing
climate and landscapes across these latitudes due to human-induced warming.
High Arctic ecosystem productivity is currently changing as a warming
climate substantially alters polar watersheds (IPCC, 2007a). Some climate
models predict that, in the Canadian Arctic, autumn and winter temperatures
may rise 3–5 ∘C by 2100, and up to 9 ∘C in the high
Arctic (ACIA, 2004; IPCC, 2007b). Mean annual precipitation is projected to
increase ∼ 12 % for the Arctic as a whole over the same
period, and up to 35 % in localized regions where the most warming will
occur (ACIA, 2004; IPCC, 2007b). Such warming and wetting are already
modifying Arctic landscape energy balances (Euskirchen et al., 2007),
resulting in glacial melt (Pfeffer et al., 2008), permafrost thaw (Froese et
al., 2008), reorganized hydrological regimes (i.e. drying or wetting; Smith
et al., 2005) and extended growing seasons (Myneni et al., 1997). These
changes are also perturbing watershed carbon cycling through, for example,
the liberation of carbon from thawing permafrost and increases in
biological productivity on landscapes and in lakes, ponds, and wetlands (Mack
et al., 2004; Smol et al., 2005; Walker et al., 2006; Smol and Douglas,
2007). However, the net impact of these processes on high-latitude
freshwater carbon GHG exchange is not well delineated, nor is the relative
contribution of freshwater systems to total landscape CO2 and CH4
exchange. This information, from a rapidly changing and extensive biome
(> 106 km2), is critical for improved global carbon
models and budgeting.
The primary objective of this study was to measure the net atmospheric
exchange of CO2 and CH4 with common high Arctic freshwater
ecosystems and to place these findings in context with similar terrestrial
studies from the same high Arctic location. Using these sources together, we
aim to delineate a clearer watershed-scale understanding of high Arctic
exchange of CO2 and CH4.
Map of the Lake Hazen base camp in Quttinirpaaq National Park,
Nunavut, Canada. Ponds and lakes investigated in this study are indicated on
the map, and selected sites are shown in photographs. Inset shows the
general locators of the Lake Hazen watershed.
Methods
Location and sampling overview
We conducted our research at the Lake Hazen base camp in central
Quttinirpaaq National Park, Ellesmere Island, Nunavut (81.8∘ N, 71.4∘ W), Canada's
most northerly protected area (Fig. 1). Lake Hazen (area: 542 km2; max depth: 267 m) is the world's
largest high Arctic lake and is surrounded by a substantial watershed
(6901 km2) composed of carbonate, evaporite, and dolomite rock
(Trettin, 1994) and cryosolic soils. About 38 % of the Lake Hazen
watershed is glaciated, with the balance of area covered by a polar
semidesert (> 80 % of ice-free area; Edlund, 1994), small
lakes, ponds, and meadow wetlands. The lower Lake Hazen watershed is a high
Arctic thermal oasis (France, 1993) as it experiences anomalously warm
growing season (June–August) conditions because it is protected from cold
coastal weather by the Grant Land Mountains and Hazen Plateau (Table S1 in the Supplement).
For example, mean July air temperature is typically 8–9 ∘C
at the base camp, compared to July 1981–2010 climate normals of 6.1 and 3.4 ∘C at the coastal Eureka and
Alert weather stations on Ellesmere Island, respectively (Environment and Climate Change Canada, 2016a). Soils in the region are also atypically warm during the
summer because of low moisture content and efficient radiative heating due
to an abundance of clear-sky days. These conditions, coupled with continuous
daylight during the growing season, have resulted in a greater diversity and
abundance of vegetation and wildlife in the Lake Hazen watershed than
surrounding areas (France, 1993), despite receiving only ∼ 34 mm of precipitation during the growing season (Table S1). Ultra-oligotrophic
Lake Hazen itself dominates the freshwater area of the watershed (Keatley et
al., 2007) and receives most of its water annually from rivers discharging
meltwater from glaciers. Water exits Lake Hazen via the Ruggles River.
Ice cover can remain on Lake Hazen throughout the growing season, though in
recent years the lake has gone ice-free more frequently, usually by late
July. Ponds and a few small lakes are scattered throughout the lower
watershed and are mostly shallow and small in area (∼ 70 %
are < 1 ha) and typically go ice-free by mid- to late June each
year.
To quantify net GHG exchange of typical high Arctic freshwater bodies, we
identified several permanent ponds or small lakes to sample within walking
distance of base camp to the northwest of Lake Hazen (Fig. 1). These
systems were chosen systematically to incorporate a gradient of watershed
position, surface area, mean depth, emergent vegetation productivity, and
hydrological connectivity (Table 1). We also sampled shoreline water of Lake
Hazen, which potentially interacted with ponds located adjacent to its
shoreline. Due to logistical issues related to accessing this remote area
over consistent time periods each year, and due to the distances of some
ponds from base camp, we completed an overall unbalanced sampling program in
space and time. As a result, we focused on delineating biogeochemical
differences between different types of high Arctic freshwaters, rather than
on inter-annual biogeochemical trends within each system. Regardless, all
sampling occurred during the summer growing seasons of 2005 to 2012 (except
for 2006), between mid-June and early August (Tables 2, S2).
Morphometry and hydrology of ponds and lakes sampled for dissolved
greenhouse gas concentrations and general chemistry in the Lake Hazen (LH)
watershed during the growing seasons (June–August) of 2005 and 2007–2012.
Surface
Mean
Max
area
depth
depth
Elevation
Primary water
Lake or pond (location)
(ha)
(m)
(m)
(m a.s.l.)
sources
Pond 01 (N 81.822 W 71.352)
0.1–0.7
0.2–0.6
0.5–1.3
166
LH, snowmelt
Pond 02 (N 81.811 W 71.453)
0.2–3.4
0.1–0.4
0.3–1.2
165
LH, snowmelt
Pond 03 (N 81.829 W 71.462)
0.04
0.3
0.8
338
Snowmelt
Pond 07 (N 81.835 W 71.305)
0.4
0.1
0.3
184
Snowmelt
Pond 10 (N 81.838 W 71.343)
2.5
1.1
2.4
222
Snowmelt
Pond 11 (N 81.832 W 71.466)
0.2
1.1
2.5
291
Snowmelt, ground ice
Pond 12 (N 81.831 W 71.529)
0.2
0.8
1.9
370
Snowmelt
Pond 16 (N 81.850 W 71.392)
0.7
1.1
2.1
434
Snowmelt, ground ice
Skeleton L. (N 81.829 W 71.480)
1.9
1.9
4.7
299
Snowmelt, ground ice
LH shore (N 81.821 W 71.352)
54 200
95a
267a
158
Glacial, snowmelt
a Kock et al., 2012.
Number of samples collected for both dissolved greenhouse gases and
general chemical analyses within freshwater systems of the Lake Hazen
watershed during the growing seasons (June–August) of 2005 and 2007–2012.
All calculated gas fluxes were based on samples collected for
concentration analyses.
Water body
2005
2007
2008
2009
2010
2011
2012
CO2, CH4 (chemistry)
Pond 01
16
25
30 (5)
24 (5)
35 (5)
3
–
Pond 02
16
1
5 (5)
–
2 (2)
3
–
Pond 03
1
1
1
–
1 (1)
3
–
Pond 07
1
1
1
–
2 (2)
3
–
Pond 10
1
–
–
–
2 (2)
3
–
Pond 11
1
–
–
–
2 (2)
6
3
Pond 12
1
1
1
–
2 (2)
–
–
Pond 16
–
–
–
–
2 (2)
3
–
Skeleton Lake
–
19
16 (5)
23 (5)
29 (4)
6
3
Lake Hazen shoreline
17
27
30 (6)
24 (5)
29 (4)
3
–
Dissolved CO2 and CH4 concentrations of high Arctic
freshwaters
Two approaches were used to quantify concentrations of dissolved CO2
and CH4 in surface waters. The first approach was employed at all sites
and used the common method of collecting water directly into evacuated
160 mL Wheaton glass serum bottles capped with butyl rubber stoppers
(Hamilton et al., 1994; Kelly et al., 1997). Each bottle contained 8.9 g of
potassium chloride (KCl) preservative to kill all microbial communities
(Kelly et al., 2001) and 10 mL of ultra-high-purity dinitrogen (N2) as
a gas headspace. To collect a sample, a bottle was submersed ∼ 5 cm below the water surface and punctured with an 18-gauge needle.
Barometric pressure and water temperature were recorded. Dissolved gas
samples were stored in the dark at ∼ 5 ∘C until
return to the University of Alberta, where they were analysed in the
accredited Biogeochemical Analytical Service Laboratory (BASL). There,
samples were placed in a wrist-action shaker for 20 min to equilibrate
dissolved CO2 and CH4 with the N2 headspace. Headspace
CO2 and CH4 concentrations were quantified on a Varian 3800 gas
chromatograph (GC) using a flame ionization detector at 250 ∘C
with ultra-high-purity helium (He) as a carrier gas passing through a
HayeSep D column at 80 ∘C. A ruthenium methanizer converted
CO2 to CH4. Four gas standards (Praxair, Linde-Union Carbide),
ranging from 75 to 6000 parts per million for both CO2 and CH4,
were used to calibrate the GC. A Varian Star Workstation program integrated
peak areas, and only calibration curves with an r2 > 0.99
were accepted for analyses. A standard was re-analysed every 10 samples to
reconfirm the calibration, and duplicate injections were performed on all
samples. Headspace CO2 and CH4 concentrations were converted to
dissolved molar concentrations using Henry's law and corrected for
temperature and barometric pressure differences between sample collection
and analysis. To quantify dissolved inorganic carbon (DIC) concentrations,
samples were acidified with 0.5 mL H3PO4 to convert all DIC to
CO2 and then immediately re-analysed on the GC. DIC concentrations were
calculated as above.
The second approach involved two automated systems to determine detailed
diel changes in surface water dissolved CO2 concentrations at two
different sites (Skeleton Lake and pond 01; Fig. 1; Table S2). Dissolved
CO2 concentrations were measured every 3 h during several
summers. These systems functioned by equilibrating, over a 20 min period,
dissolved CO2 from pumped surface waters with a gas cell in a Celgard
MiniModule Liqui-Cel. The equilibrated gas was then analysed for CO2
concentration by a LI-COR (Lincoln, NE) 820 infrared gas analyzer. The
systems also measured dissolved oxygen (O2) concentrations using a
Qubit™ flow-through sensor. Concentrations were then converted to
aqueous molar concentrations using Henry's law, and water temperature
quantified with a Campbell Scientific (Logan, UT) 107-L thermistor. The
systems were housed in watertight cases along the shore from which a sample
line extended out into the surface waters and upon which a CS
014A anemometer (1 m height) and a Kipp & Zonen (Delft, the Netherlands)
photosynthetically active radiation (PAR) LITE quantum sensor were mounted. All data were
recorded on Campbell Scientific CR10X dataloggers.
Net atmospheric exchange of CO2 and CH4 with high Arctic freshwaters
Though several models exist for quantifying turbulent gas fluxes of lakes
(e.g. MacIntyre et al., 2010), we decided to use the stagnant film model
described by Liss and Slater (1974) to quantify net CO2 and CH4
mass fluxes between surface waters and the atmosphere at our remote
location. This decision was made because 24 h daylight at our
high-latitude location dampened diurnal surface temperature changes to less
than 1 ∘C, and because of the general shallowness of the systems and the steady,
sometimes gusty, wind conditions on site. The stagnant film model assumes
that gas concentrations in both surface waters and the atmosphere are well mixed
and that gas transfer between the phases occurs via diffusion across a
diminutive stagnant boundary layer. Diffusive gas transfer across the
boundary layer is assumed to follow Fick's first law:
Gasfluxµmolm-2h-1=kCSUR-CEQL,
where CSUR (µmol L-1) is the concentration of the gas in
surface waters, CEQL (µmol L-1) is the atmospheric
equilibrium concentration, and k is the gas exchange coefficient or the
depth of water per unit time at which the concentration of the gas equalizes
with the atmosphere (i.e. piston velocity). Values of k (cm h-1) were
calculated using the automated system's wind measurements and occasionally
from nearby (within 2 km) eddy covariance towers (Campbell Scientific CSAT3
Sonic Anemometers; 30 min means), and published empirical
relationships (Table S3; Hamilton et al., 1994). To determine the
direction of the flux, atmospheric equilibrium CO2 and CH4
concentrations were quantified using Henry's law, in situ barometric
pressure and air temperature, and mean annual CO2 and CH4
concentrations in the atmosphere during the year of sampling (Environment and Climate Change Canada, 2016b). If dissolved CO2 and CH4 concentrations in surface
waters were above or below their corresponding calculated atmospheric
equilibrium concentrations, the freshwater systems were considered a source
(+) or sink (-) relative to the atmosphere, respectively.
We also measured ebullition fluxes of CO2 and CH4 to the
atmosphere from two freshwater systems (Skeleton Lake, pond 01) during two
growing seasons using manual bubble collection and GC analysis (see the
Supplement).
Supporting measurements
We quantified additional physical and chemical parameters in surface waters
at the same sites where we collected our GHG samples, albeit at reduced
sampling frequencies (Tables 2, S2). At each site, temperature, pH, specific
conductivity, and dissolved O2 were measured in situ using a YSI (Yellow
Springs, OH) 556 Multiprobe System (MPS). Water samples were also collected for
general chemical analyses (total dissolved nitrogen (TDN), particulate nitrogen (PN),
nitrate + nitrite (NO3-+ NO2-), ammonium (NH4+), total phosphorus (TP),
total dissolved phosphorus (TDP), alkalinity, dissolved organic carbon
(DOC), total dissolved solids (TDS), major cations/anions, dissolved iron,
chlorophyll a (chl a)) into pre-cleaned HDPE bottles. These samples were
immediately processed in the Lake Hazen/Quttinirpaaq Field Laboratory clean
room after water collection and stored in the dark at ∼ 5 ∘C or frozen until analysed at the BASL.
Numerical analysis
We used hierarchical clustering analysis (IBM SPSS Statistics 23) to
organize ponds and lakes into type categories based on concurrent GHG and
chemical analyses (10 sites; n= 62; Table 2). Because sampling was
unbalanced in frequency and time between sites due to logistical challenges
(Table 2; see Sect. 2.1), potential overlap of chemistries between
individual lakes was high, therefore setting a conservative standard for
classifying distinct freshwater types. We used between-group linkage and
squared Euclidean distances to group similar sites together and delineate
distinct high Arctic freshwater classes. We then used linear mixed models
(SPSS) to quantify differences in GHG concentrations and fluxes between
these different high Arctic freshwater types. Linear mixed models are ideal
for analysing non-independent and repeated-measures data as they integrate
inherent errors in repeated sampling designs to more clearly distinguish
statistical differences between groups. These models also can efficiently
handle unbalanced designs by standardizing results from each site within
groups. Linear mixed model details included use of an auto-regressive
moving average (1,1) repeated covariance model, use of a maximum-likelihood
estimation method, and variables organized by freshwater type (fixed) and
year (random).
Mean (±1 SD) water temperature and general chemistry of
different freshwater types, and other selected locations and periods in the
Lake Hazen watershed during the growing seasons (June–August) of 2005 and
2007–2012. All measurements are in µmol L-1 except for water
temperature (∘C), total dissolved solids (mg L-1), and
chlorophyll a (µg L-1).
WT
TDS
PC
DIC
DOC
NO3-+ NO2-
NH4+
TDN
TDP
Fe
SO42-
Chl a
Evaporative
Pond 03
8
485
44
2308
1848
0.01
0.1
113
0.4
0.9
1720
0.9
Pond 07
12 ± 6
1336 ± 32
62 ± 6
2574 ± 93
3859 ± 88
0.01 ± 0.00
1.1 ± 1.0
125 ± 40
0.4 ± 0.0
3.2 ± 1.0
6628 ± 186
0.5 ± 0.2
Pond 10
12 ± 6
934 ± 32
47 ± 15
2248 ± 4
1982 ± 106
0.01 ± 0.00
0.5 ± 0.6
121 ± 35
0.2 ± 0.0
0.0 ± 0.0
4676 ± 113
2.4 ± 0.8
Pond 12
11 ± 3
1060 ± 15
41 ± 3
1450 ± 97
1544 ± 29
0.03 ± 0.02
0.1 ± 0.1
86 ± 1
0.3 ± 0.0
0.2 ± 0.1
6454 ± 118
1.1 ± 0.1
Mean ± SD
10 ± 2
953 ± 355
49 ± 9
2145 ± 484
2308 ± 1050
0.01 ± 0.01
0.5 ± 0.5
111 ± 18
0.3 ± 0.1
1.1 ± 1.5
4870 ± 2278
1.2 ± 0.8
Meltwater
Pond 11
12 ± 2
451 ± 24
29 ± 11
1453 ± 30
383 ± 12
0.03 ± 0.02
0.3 ± 0.4
20 ± 2
0.2 ± 0.0
0.0 ± 0.0
2232 ± 52
0.6 ± 0.2
Pond 16
11 ± 5
328 ± 12
18 ± 3
939 ± 4
554 ± 18
0.01 ± 0.00
0.3 ± 0.3
24 ± 0
0.2 ± 0.0
0.1 ± 0.1
1885 ± 49
0.3 ± 0.1
Skeleton L.
11 ± 4
317 ± 115
23 ± 9
1533 ± 241
447 ± 63
0.02 ± 0.01
2.4 ± 2.3
22 ± 2
0.2 ± 0.0
0.0 ± 0.0
1669 ± 392
0.5 ± 0.4
Mean ± SD
11 ± 0
365 ± 75
24 ± 6
1308 ± 323
461 ± 86
0.02 ± 0.01
1.0 ± 1.2
22 ± 2
0.2 ± 0.0
0.1 ± 0.0
1928 ± 284
0.5 ± 0.1
Melt. streams
3
653
–
769
67
7.70
0.1
35
0.0
0.6
3318
2.1
Shoreline
Pond 01
12 ± 3
192 ± 31
34 ± 17
1848 ± 443
409 ± 124
0.11 ± 0.18
2.8 ± 2.8
24 ± 11
0.2 ± 0.1
2.1 ± 1.6
407 ± 129
0.5 ± 1.1
Pond 02
10 ± 2
131 ± 26
27 ± 15
1356 ± 198
103 ± 25
0.11 ± 0.19
0.5 ± 0.7
6 ± 1
0.1 ± 0.0
0.3 ± 0.3
273 ± 107
0.2 ± 0.1
Mean ± SD
11 ± 2
162 ± 43
31 ± 5
1602 ± 348
256 ± 216
0.11 ± 0.00
1.6 ± 1.6
15 ± 13
0.2 ± 0.1
1.2 ± 1.3
340 ± 95
0.4 ± 0.3
Pre-flood
14 ± 3
216 ± 56
34 ± 4
1740 ± 243
497 ± 115
0.01 ± 0.00
2.2 ± 2.8
27 ± 4
0.3 ± 0.0
1.7 ± 0.7
608 ± 231
0.4 ± 0.2
Post-flood
11 ± 2
164 ± 40
32 ± 18
1681 ± 470
270 ± 172
0.13 ± 0.19
2.0 ± 2.5
16 ± 13
0.2 ± 0.1
1.5 ± 1.7
311 ± 102
0.5 ± 1.0
Lake Hazen shoreline
Mean ± SD
5 ± 3
59 ± 68
10 ± 5
524 ± 301
51 ± 123
0.24 ± 0.18
1.8 ± 2.3
2 ± 1
0.1 ± 0.0
0.0 ± 0.0
69 ± 42
0.1 ± 0.1
WT: water temperature; TDS: total dissolved solids; PC:
particulate carbon; DIC: dissolved inorganic carbon; DOC: dissolved organic carbon;
NO3-+ NO2-: dissolved nitrate + nitrite; NH4+: dissolved ammonium;
TDN: total dissolved nitrogen; TDP: total dissolved phosphorus; Fe:
dissolved iron; SO42-: dissolved sulfate; chl a: chlorophyll a.
Net atmospheric exchange of CO2 and CH4 with a large high
Arctic watershed
To better understand the role of freshwater ecosystems in regional fluxes of
carbon GHGs, freshwater CO2 and CH4 fluxes measured in this study
were coupled with terrestrial fluxes measured in the watershed during the
2008–2012 growing seasons (Emmerton et al., 2014, 2016). The authors measured,
using eddy covariance flux towers (CO2, CH4) and static chambers
(CH4), growing season carbon GHG exchange with terrestrial polar
semidesert and meadow wetland landscapes. Areal coverage of the
different ecosystem types in the watershed was isolated from a previous
classification of Quttinirpaaq National Park (Edlund, 1994) using a
geographical information system (ArcGIS v.10.3; ESRI, Redlands, USA). Mean
growing season fluxes from each measured ecosystem were then weighted to
matching coverage area in the watershed to estimate the total carbon gas
exchange with the atmosphere. Glacial ice was assumed to be a net-zero
contributor of total watershed gas exchange in this scaling
exercise. Ecosystem data were compared using a linear mixed model
similar to that used in the freshwater classification (see Section 2.5).
Results
Biogeochemical classification of high Arctic freshwaters
Four distinct types of freshwater systems were evident from our sampling in
the Lake Hazen watershed (Table 3; Fig. S1 in the Supplement; hierarchical cluster analysis;
see Methods). “Evaporative” ponds (ponds 07, 10, 12) occurred in the
upland of the Lake Hazen catchment and were hydrologically isolated from
their surrounding basins post-snowmelt. These ponds were relatively high in
concentrations of total dissolved solids, most measured ions, DIC, DOC,
organic particles, TDP, and chl a. Pond 03, though not technically clustered
with others, was forced to the evaporative pond category based on lack of
consistent inflowing water and high concentrations of most dissolved ions.
This delegation was further consistent with isotopic measurements of oxygen
(δ18O-H2O) in water taken from each aquatic system in July
2010 (Fig. S2). “Meltwater” systems, including ponds 11 and 16 and Skeleton
Lake, also occurred in the upland of the Lake Hazen watershed but received
consistent water supply through the growing season primarily from snowmelt,
permafrost/ground ice thaw water, or upstream lake drainage. The general
chemistry of these systems was therefore consistent and without extremes
during the growing season (see Sect. 3.2). Typical meltwater streams
draining to these ponds were high in TDN and sulfate (SO42-) but
low in DOC (Table 3), though streams drained through marginal wetlands
surrounding the lakes and ponds downstream of our sampling sites.
“Shoreline” ponds (ponds 01, 02) occurred along the margin of Lake Hazen
and were typically physically isolated from the large lake by porous gravel
berms, and surrounded by wetland soils and flora during spring low-water
conditions. As glacial melt accelerated throughout the growing season,
though, the water level of Lake Hazen rose and could seep through the berms
to incrementally flood the ponds and surrounding wetlands (Fig. S3).
Shoreline ponds changed chemically during the onset of flooding as
indicated, for example, by an increase in the concentration of
NO3-+ NO2- (Table 3). A separate smaller cluster of
pond 01 samples occurred during particularly high-water periods when Lake
Hazen breached the berms (Fig. S1). The flooding water from the “Lake
Hazen shoreline” was cold and dilute in dissolved ions, organic matter, TDN,
and chl a but considerably higher in NO3-+ NO2-
than other water bodies.
Dissolved carbon dioxide (CO2) and methane (CH4)
concentrations during the 2005 and 2007–2012 growing seasons (June–August)
of different types of high Arctic freshwater systems in the Lake Hazen
watershed. Inset text shows site names within each freshwater type. Grey
areas indicate the range of atmospheric equilibrium concentrations CO2
and CH4 during the sampling period.
Mean (±SE) dissolved carbon dioxide (CO2) and methane
(CH4) concentrations and fluxes during the 2005 and 2007–2012 growing
seasons (June–August) from four different freshwater types in the Lake Hazen
watershed. Letters denote statistical differences between ecosystem types
for each gas (linear mixed model; α= 0.05; see Methods).
Dissolved concentrations and net atmospheric exchange of CO2 and
CH4
CO2
Growing season concentrations of dissolved CO2 in sampled high Arctic
freshwaters from 2005 to 2012 varied substantially within and between the
freshwater types, and therefore resulted overall in non-significant
differences between them (Figs. 2, 3, S4, S5).
Mean (±SE) of 3 h diel dissolved carbon dioxide
(CO2) concentration, oxygen (O2) concentration, water temperature,
and photosynthetically active radiation (PAR) data measured by automated
systems deployed at the shorelines of Skeleton Lake (2008–2010) and pond 01
(2008–2010) during the high Arctic growing season (June–August) in the Lake
Hazen watershed.
On average, evaporative ponds had the highest mean CO2 concentrations
(mean ± SE; 27.9 ± 4.9 µmol L-1) compared to other
freshwater types (Fig. 3), primarily due to conditions in pond 03 and pond
07. These ponds were the shallowest of the four sampled and were rich in
dissolved iron, DIC, and TDP. CO2 concentrations were above atmospheric
equilibrium concentration (Fig. 2), and therefore these ponds were sources
of the gas to the atmosphere (+177 ± 66 µmol CO2 m-2 h-1;
Fig. 3). The other evaporative ponds (ponds 10, 12) were deeper
and had CO2 concentrations that were typically near those of the
atmosphere. This contributed to their near-zero exchange of CO2 with
the atmosphere (-5 ± 17 µmol CO2 m-2 h-1).
Together, dissolved CO2 concentrations correlated closely and
positively with DOC and dissolved iron concentrations in evaporative ponds
(Table S4). When combining all evaporative ponds together, they were net
sources of CO2 to the atmosphere (+73 ± 93 µmol CO2 m-2 h-1; Fig. 3).
Meltwater systems had lower, but insignificantly different, CO2
concentrations (26.2 ± 3.9 µmol L-1) than evaporative ponds
(Fig. 3). Meltwater systems showed only gradual declines of CO2
concentrations through the summer, with strong consistency between sampling
times and sites (Fig. 2). However, they emitted higher, though not
significantly different, fluxes of CO2 to the atmosphere overall
(+160 ± 66 µmol CO2 m-2 h-1; Fig. 3) than the
other freshwater classes. CO2 concentrations of meltwater systems
correlated strongly and positively with CH4 concentrations but
negatively with DOC concentrations and measurements that were of high
abundances in meltwater streams draining into the systems (e.g.
SO42-, TDN; Table 3, S4). Mean diurnal trends in CO2
concentrations across all sampling years, as measured by the automated
system at Skeleton Lake, showed that CO2 and O2 concentrations had
little association together (Pearson correlation: r= -0.18, df= 7;
p= 0.67), but CO2 concentrations varied strongly and negatively with
water temperature (r= -0.97, df= 7, p < 0.001; Fig. 4).
Mean CO2 concentrations of shoreline ponds (22.5 ± 3.7 µmol L-1; Fig. 3) were similar to the other freshwater types, which
obscured their considerable seasonal changes within and between growing
seasons. In 2005 and 2007, both pond 01 and pond 02 received little
floodwater from Lake Hazen due to lower lake water levels (Fig. 2). These
conditions resulted in dense wetland vegetation growth surrounding the ponds
and low mean daily dissolved CO2 concentrations (6.5 ± 0.4 µmol L-1) and strong uptake of atmospheric CO2
(-329 ± 59 µmol m-2 h-1). The drier wetland state of these ponds
changed in following summers when Lake Hazen rose substantially upon greater
inputs of glacial meltwaters (WSC, 2015), causing the rising waters to seep
through porous berms into the ponds through July. In concert with flooding,
concentrations of CO2 from 2008 to 2011 of each pond together increased
substantially (30.1 ± 1.5 µmol L-1), resulting in strong net
emissions of CO2 to the atmosphere (+228 ± 44 µmol m-2 h-1). Changing dissolved CO2 concentrations correlated positively
with dissolved nutrients and ions (Table S4). Diurnal trends of CO2 and
O2 concentration measured by the automated system at pond 01 over
several growing seasons showed opposite diel patterns of the gases, with
greater O2 concentrations during the warmest and brightest parts of the
day (r= -0.98, df= 7, p < 0.001; Fig. 4). However, the net result
of strong seasonality in these ponds was slight net emission of CO2 to
the atmosphere (+42 ± 60 µmol m-2 h-1; Fig. 3) that was
not statistically different from other types of freshwaters.
Lake Hazen shoreline water, though not necessarily representative of the
entire lake itself, was characteristic of its moat occurring early each
growing season, and of water that intruded shoreline ponds in July. This
water was generally near atmospheric equilibrium concentrations of CO2
(21.0 ± 7.8 µmol L-1; Fig. 2) with stable and low CO2
uptake throughout the season (-44 ± 66 µmol m-2 h-1;
Fig. 3). CO2 concentrations of this shoreline water
correlated positively and most strongly with DIC, NO3-+ NO2-, major ions, and wind
speed (Table S4).
CH4
Each of the evaporative, meltwater, and Lake Hazen shoreline freshwaters had
statistically similar and low CH4 concentrations (0.06–0.14 µmol L-1) and fluxes (0 to +3 µmol m-2 h-1) across all
growing seasons (Figs. 2, 3, S4, S5). Evaporative ponds had generally flat
seasonal CH4 concentration and flux trends (Figs. 2, S5), except for an
outlier sample from pond 10 in mid-July 2011. CH4 concentrations
correlated strongest with NO3-+ NO2- and alkalinity
(Table S4). Meltwater systems were also generally low in CH4
concentrations and fluxes through the summers and associated positively and
closely with CO2 concentrations, and strongly but negatively with
SO42-, alkalinity, and other ions (Table S4). Notable flux
emissions from these systems only occurred during episodic wind events, also
similar to CO2 (Fig. S5). However, unlike CO2, higher CH4
concentrations were sustained into July in Skeleton Lake in 2010 (Fig. 2).
Lake Hazen shoreline water showed low and stable CH4 concentrations and
fluxes each growing season with infrequent and small releases of the gas to
the atmosphere. CH4 concentrations in this water correlated positively
only with particulate carbon concentrations (Table S4).
Shoreline ponds, alternatively, had significantly higher CH4
concentrations relative to the other systems (1.18 ± 0.16 µmol L-1; Fig. 3) and showed a dynamic seasonal pattern dominated by the
timing of flooding (Fig. 2). In 2005 and 2007 before substantial seasonal
flooding started to occur, CH4 concentrations (0.29 ± 0.03 µmol L-1) and fluxes to the atmosphere
(+8 ± 2 µmol m-2 h-1) were low. As the shoreline ponds began to receive
NO3-+ NO2--rich flood water from Lake Hazen by
mid-summer in subsequent years (2008–2011; Table 3), CH4 concentrations
and fluxes increased substantially (1.70 ± 0.13 µmol L-1;
+41 ± 10 µmol m-2 h-1) and correlated closely with
dissolved organic and inorganic nitrogen (Table S4). This significant
increase in CH4 flux emissions from shoreline ponds during flooding
(> 5 times higher than during dry periods) was coupled with
large increases in pond surface areas, effectively producing even higher
total CH4 emissions to the atmosphere. Towards the end of July during
flooding conditions, full berm breach of the shoreline ponds by rising Lake
Hazen waters occurred, resulting in rapid dilution of CH4
concentrations, but logistical constraints prevented later summer sampling
to investigate if concentrations rebounded thereafter. Overall, aided by
poor solubility of CH4 in water and episodic wind events (Fig. S5),
the flooding of shoreline ponds drove significantly larger CH4
emissions to the atmosphere than other freshwater
types (+28 ± 5 µmol m-2 h-1; Fig. 3).
Comparison of the daily net exchange of carbon dioxide (CO2)
and methane (CH4) between high Arctic terrestrial and freshwater
ecosystems and the atmosphere in the Lake Hazen watershed during the growing
seasons (June–August) of 2005 and 2007–2012. Positive values represent net
emission of a gas to the atmosphere. Underlined values denote statistical
differences of daily fluxes from other ecosystem types for each gas (linear
mixed model; α= 0.05; see Methods). The total and percent growing
season exchange of each gas and ecosystem is also shown, as is the surface
area of each ecosystem. Measurements that were not available were assumed to be zero and are denoted by NA.
CO2 flux
CH4 flux
Area
g C–CO2
Mg C–CO2
g C–CH4
Mg C–CH4
Ecosystem
m-2 day-1
season-1
%
m-2 day-1
season-1
%
km2
%
Aquatic
Upland
+0.045 ± 0.180
+598
4
+0.001 ± 0.001
+11
2
144
2
Shoreline
+0.031 ± 0.218
+2
0
+0.008 ± 0.001
+0
0
1
0
Lake Hazen
-0.014 ± 0.269
-721
5
+0.000 ± 0.002
+6
1
542
7
Terrestriala
Polar semidesert
+0.004 ± 0.223
+1253
9
-0.001 ± 0.003
-412
94
3819
51
Meadow wetland
-0.955 ± 0.291
-11 368
82
+0.001 ± 0.002
+10
2
129
2
Glacial ice
NA
NA
NA
NA
NA
NA
2809
38
Totals
–
-10 236
100
–
-385
100
7443
100
a From Emmerton et al. (2014, 2016); slight discrepancies in values exist here compared to original publications due to data handling in the mixed model; see Methods.
Net atmospheric exchange of CO2 and CH4 with a large high
Arctic watershed
When scaled to total watershed area including Lake Hazen (7443 km2),
polar semidesert landscapes were inconsequential to total CO2 exchange
(+1253 Mg C–CO2; 9 % of total exchange) despite comprising a
substantial proportion of the catchment (3819 km2; 51 %; Table 4).
All types of standing freshwaters sampled in the watershed from this study
showed statistically similar CO2 fluxes compared to the polar
semidesert. When assuming its shoreline waters were representative of the
entire lake area as recent evidence suggests (unpublished data, 2015), the
expansive Lake Hazen (542 km2; 7 %) exchanged relatively little
CO2 with the atmosphere (-721 Mg C–CO2; 5 %), as did smaller
freshwater systems (144 km2; 2 %) in the watershed (+600 Mg C–CO2; 4 %). In clear contrast, during the growing season, moist and
vegetated meadow wetland ecosystems were found to consume CO2 at rates
similar to wetlands in the southern Arctic (-0.96 g C–CO2 m-2 day-1; Emmerton et al., 2016). Consequently, meadow wetlands exchanged an
estimated 82 % (-11 368 Mg C–CO2) of total CO2 with the
atmosphere despite occupying only 2 % (129 km2) of the area in the
Lake Hazen watershed. Total CO2 exchange of the watershed was -10 236 Mg C–CO2 (-1.38 g C–CO2 m-2) during the growing season.
The high Arctic polar semidesert has recently gained attention as a notable
atmospheric sink of CH4 (-0.001 g C–CH4 m-2 day-1;
Emmerton et al., 2014), which has since been observed in studies at other
high Arctic locations (e.g. Jorgensen et al., 2015). These uptake fluxes
coupled with the expansive coverage made the polar semidesert the key
landscape controlling net CH4 exchange throughout the Lake Hazen
watershed (-412 Mg C–CH4; 94 % of total exchange; Table 4).
Surprisingly, a productive meadow wetland in the watershed was a weaker
emitter of CH4 to the atmosphere (+0.001 g C–CH4 m-2 day-1)
than other high Arctic wetlands (Emmerton et al., 2014),
releasing only 10 Mg C–CH4 (2 %) to the atmosphere during the growing
season. All upland freshwater systems (evaporative and meltwater systems)
had low emissions of CH4 to the atmosphere (11 Mg C–CH4; 2 %),
as did Lake Hazen itself (+6 Mg C–CH4; 1 %). All measured
ecosystems had statistically similar CH4 fluxes except for the strong
CH4-producing shoreline ponds (Table 4). However, poor areal coverage
of these dynamic systems in the watershed (0.6 km2; < 1 %)
resulted in contributions of ≪ 1 % (+0.4 Mg C–CH4) of all CH4
exchange in the Lake Hazen watershed (-385 Mg C–CH4; -0.052 g C–CH4 m-2).
Discussion
Dissolved concentrations and net atmospheric exchange of CO2 and
CH4
CO2
Dissolved CO2 was likely being produced effectively in all evaporative
ponds by ecosystem metabolism because of their high concentrations of DOC.
These, and other, isolated systems concentrate many solutes in their waters,
including degraded allochthonous and fresh autochthonous DOC (Tank et al.,
2009), which would be available as a source of energy to heterotrophs.
Accumulation and dissociation of weathered carbonates and evaporates in
these moderately warm, high-alkalinity environments (2–5 mEq L-1) may
have also contributed towards observed dissolved CO2 concentrations in
evaporative ponds (Trettin, 1994; Marcé et al., 2015). However,
differences in pond volumes likely controlled the ultimate concentrations of
CO2 found in evaporative ponds. Small and shallow evaporative ponds
(ponds 03, 07) showed much higher concentrations compared with those that
were larger and deeper (ponds 10, 12) and were therefore more susceptible to
wind-related turbulence and gas exchange with the atmosphere.
The biogeochemistry of meltwater systems was steady and similar between
sites, possibly related to stream flushing, but they ultimately had similar
CO2 concentrations and fluxes to other freshwater types. This occurred
despite inclusion of early summer sampling at Skeleton Lake (2007, 2010)
when CO2 concentrations were higher as post-ice-covered waters were
re-equilibrating with the atmosphere (Kling et al., 1992; Karlsson et al.,
2013). However, fluxes of CO2 to the atmosphere from these systems did
not correspond closely to early season venting, but rather to the
frequency of episodic releases of CO2 to the atmosphere (Fig. S5).
This may have been related to their greater mean depths, which promoted
stratification in at least one of our sampled meltwater systems (Skeleton
Lake; Fig. S6). Stratification would confine decomposition products (e.g.
CO2, CH4) to near their sites of origin in bottom sediments and
extensive benthic mat communities, which would then be released most readily
during and just after wind mixing events. We observed evidence of this
process via strong positive correlations between CO2 and CH4
concentrations in surface waters (Table S4). Results from our automated
systems supported this argument as mean diurnal CO2 and O2
concentrations in surface waters of Skeleton Lake associated poorly and
positively together, rather than negatively when metabolic processes (i.e.
primary productivity or decomposition of organic matter; see pond 01 below)
were dominant drivers in surface waters. Meltwater streams flushing through
marginal wetlands before entry into the meltwater systems, but then not
mixing with the entire lake, may explain the negative correlation observed
between CO2 and DOC concentrations.
Shoreline ponds changed drastically in size and chemistry in response to
seasonal flooding by Lake Hazen shoreline water (Tables 1, 3). During
pre-flooding conditions, CO2 concentrations were low, which could be
attributed to DIC use by autotrophic plankton (pre-flooding: 1.2 µg L-1
chl a; post-flooding: 0.4 µg L-1 chl a), but more likely by
observed dense benthic and macrophytic communities along the margins of the
ponds (Tank et al., 2009). When inundated by flood waters, CO2
concentrations rose sharply, which is typically observed in flooded wetlands
(Kelly et al., 1997). This occurs because widespread inundation of plants
and soils typically prompts rapid decomposition (Table S4). Although
negatively correlated diurnal CO2 and O2 concentrations suggest
that primary productivity was consistently occurring in shoreline pond
surface waters, flooding of the ponds was ultimately the more important
process controlling seasonal CO2 concentrations.
CO2 concentrations in Lake Hazen shoreline water were near atmospheric
equilibrium and only weakly consumed atmospheric CO2. These results
along the shoreline appear to be similar to other locations offshore
(unpublished, 2015) and were reflective of most deep lakes with extremely
low nutrient, organic matter, and chl a concentrations (0.20 µg L-1;
Keatley et al., 2007; Babaluk et al., 2009). CO2 gas exchange between
the lake and the atmosphere correlated well with DIC, alkalinity, and other
ions which are considerable in glacial rivers draining to the lake (Babaluk
et al., 2009). These rivers were also strongly undersaturated in CO2,
as observed elsewhere in glacial environments (Meire et al., 2015), and may
explain the slight CO2 uptake observed by the lake, especially later in
summer.
CH4
Evaporative and meltwater systems were typically weak producers and emitters
of CH4, which was possibly related to concurrently high SO42-
concentrations in these systems due to additions of water-draining evaporite
geologies (Table 3; Trettin, 1994). This may have given competitive
advantage to SO42--reducing bacterial communities in sediments,
which typically outcompete methanogenic bacteria for hydrogen. This
hypothesis was supported by the prevalence of H2S gas in collected
sediment cores from Skeleton Lake (unpublished, 2013) and by the trivial
fluxes of CH4 in bubbles measured emerging from sediments (+0.00 to
+0.01 mg m-2 day-1; Table S5; see the Supplement).
Stratification in meltwater systems likely also limited CH4 emissions
(Table S4). Low production and exchange of CH4 in Lake Hazen,
alternatively, were most likely associated with the lake's ultra-oligotrophic
standing (Keatley et al., 2007), well-oxygenated water, and little
accumulation of littoral organic matter where anoxia could prevail and
CH4 be produced. Only during periods of strong wind mixing of surface
waters, or when shoreline ponds breached and mixed organic particles (Table S4)
across its shoreline, did the nearshore waters of Lake Hazen release
CH4 to the atmosphere above near-zero values.
Shoreline ponds were regional “hotspots” of CH4 exchange, which was
clearly driven by seasonal flooding (Table S4). Pre-flooding conditions in
the ponds were characterized by dry and oxygenated wetland soils, which were
exposed to the atmosphere and not connected to the central pond where we
sampled. Flooding induced saturation of organic soils surrounding the
wetland and perhaps provided advantageous conditions for anaerobic
metabolism, including methanogenesis. Methanogenesis may have been further
enhanced by the flushing of shoreline ponds with SO42--poor Lake
Hazen water, thus possibly favouring methanogenesis over SO42-
reduction in flooded soils.
Net atmospheric exchange of CO2 and CH4 with a large high
Arctic watershed
Studies from the southern Arctic have estimated that fluxes of CO2
(e.g. -1.55 to +1.10 g C–CO2 m-2 day-1; Tank et al.,
2009; Abnizova 2012) and CH4 (+0.01 to +0.09 g C–CH4 m-2 day-1; Walter, 2006; Sachs, 2010) from ponds and lakes can contribute a
strong majority of a region's total exchange of CO2 and CH4 with
the atmosphere (Sachs et al., 2010; Abnizova et al., 2012). Carbon- and
nutrient-rich soils, longer growing seasons, and high densities of aquatic
and wetland ecosystems are likely key characteristics responsible for these
strong signals. To our knowledge, concurrent measurement of freshwater and
terrestrial carbon GHG exchange at a high Arctic location has not been
reported prior to this study. We found that, in a large high Arctic
watershed, a size range from small ponds up to one of the world's largest
high-latitude lakes together contributed only an estimated 9 % of the
CO2 (-0.01 to +0.05 g C–CO2 m-2 day-1) and 3 % of the
CH4 (+0.00 to +0.01 g C–CH4 m-2 day-1) total watershed
exchange of these two GHGs (Table 4). Several reasons may explain the
limited role of freshwater systems there. First, pond and lake coverage in
the high Arctic is typically very low (< 10 % of Lake Hazen
watershed; Table 4) compared to the southern Arctic (Lehner and Doll, 2004).
Well-drained soils, a semi-arid climate, and continuous evaporation
throughout a 24 h daylight growing season all contribute to negative pond
and lake water balances often observed across the high Arctic (Woo and Guan,
2006). Second, growing seasons of high Arctic freshwaters are very short as
ice cover can remain perennially on some lakes, or may vacate for only 3
months (Rautio et al., 2011). Though ponds in the Lake Hazen watershed can
warm to moderate levels compared to other Arctic locations (Table 3, Rautio et al.,
2011), exposure to these temperatures is short-lived and likely limits
growing season autotrophic and heterotrophic activity and their
contributions to freshwater carbon gas exchange. Geochemical production of
CO2 in high-alkalinity ponds and lakes is also lessened in only
moderately warm environments (Marcé et al., 2015). Third, runoff
delivered to high Arctic freshwaters is typically dilute, nutrient-poor, and
low in quality organic matter because it drains through the most
unproductive and desiccated soils anywhere on Earth (ACIA, 2004). Therefore,
neither important nutrients key for aquatic photosynthesis (Markager et al.,
1999) nor labile carbon for heterotrophic activities are supplied to many
high Arctic lakes in great quantities, thus limiting potential biological
carbon GHG uptake or emission. These constraints on aquatic productivity
were visible at our sites as few were dominated by productive emergent
plants, but rather by barren lakebeds or submerged benthic mats of weaker
productivity.
Despite a harsh climate and poor-quality substrates, our results suggest
that the degree of moisture availability in high Arctic ecosystems was an
overarching control on CO2 exchanges. Running-water environments are
the most productive landscapes in the Lake Hazen watershed (Table 4) because
they are consistently wet but not starved of (e.g. polar semidesert) or
inundated by (e.g. ponds, lakes) water. These ideal conditions support
productive emergent plant communities, which typically outgrow other
vegetation types along the terrestrial–aquatic watershed gradient (Wetzel,
2001). This occurred despite low soil temperatures in these wetlands because
of shallow active layers above permafrost. Productive standing-water
environments were rare in the Lake Hazen watershed, except for shoreline
ponds during their drier wetland phase. However, the occasional late season
flooding of these shoreline ponds with Lake Hazen waters promoted a near
balance of net autotrophy and heterotrophy in these systems. For CH4,
the spatial coverage of ecosystem types was the most important factor
controlling its exchange at the watershed scale. Only shoreline ponds, due
to the flooding of their wetland vegetation, were substantially higher in
per-unit CH4 gas exchange than other ecosystems (Table 4). However, net
uptake of CH4 by methanotrophs in polar semidesert soils was ultimately
of greatest importance at the watershed scale because of the landscape's
extensive spatial coverage relative to other ecosystem types. This finding
supports other recent studies which highlight the potential global
importance of this substantial high Arctic CH4 sink (Jorgensen et al.,
2015).
Modification of moisture availability in high Arctic regions is likely to
occur in a changing climate. High Arctic latitudes are expected to endure
considerable warming and increased precipitation, resulting in shifting snow
and ice phonologies, greater contributions to runoff from subsurface ice and
glaciers, and greater evaporation rates (ACIA, 2004). These changes will
affect the distribution and sustainability of water across high Arctic
landscapes. Smol and Douglas (2007) have suggested that negative water
balances and the drying of small and shallow aquatic systems will become a
more frequent response to rapidly increasing temperatures and enhanced
evaporation. Others have suggested that site-specific hydrological
conditions have important controls on the ultimate sustainability of high
Arctic waters (Abnizova and Young, 2010). In the Lake Hazen watershed,
expected increases in nearby coastal evaporation and landward precipitation
(Bintanja and Selten, 2014) may deliver larger snowpacks, recharges to
subsurface ice or water storage, and increases in summertime runoff to
aquatic systems. Increased temperatures, however, should also work to
sustain wet areas in the watershed. For example, increased glacial melt
would deliver more water to Lake Hazen and flood shoreline Lakes for longer
periods. Higher temperatures should also improve water delivery to meltwater
systems and meadow wetlands supplied by thawing subsurface ice. Only shallow
evaporative ponds, which endure a precarious existence based on net balances
in snowmelt and evaporation, have a less certain future. We suspect that
these evaporative systems may be susceptible to drying over the shorter term
as air temperatures increase and the weak water storage capacity of
well-drained polar semidesert soils continues. Only until long-term
improvements in productivity and organic matter content in soils occur
would we expect more consistent sources of runoff to these shallow systems.
Well-drained polar semideserts, similarly, may also be expected to remain
relatively dry until water holding capacity of the soils improves (Emmerton
et al., 2016).
With expected sustainability of water delivery to most wet systems in the
Lake Hazen watershed over the longer term, future carbon GHG exchange there
and across other high Arctic regions is likely dependent on the trajectory
of landscape change of polar semideserts (Sitch et al., 2007). Low CO2
and CH4 exchange in upland freshwater systems and Lake Hazen will
likely continue until water and nutrient conditions in polar semidesert
soils draining to them improves over the longer term. Shoreline ponds may be
flooded earlier and for longer periods as Lake Hazen receives increased
glacial meltwater, possibly amplifying carbon GHG emissions over the short
term. However, supply of decomposable organic carbon may decrease as periods
when these systems are in a productive wetland state become less frequent.
Regardless, shoreline ponds likely have little role in regional carbon GHG
exchange due to their minimal existence. Consequently, changes in the
terrestrial ecosystems, over the longer term, should continue to define the
direction and intensity of GHG exchanges in the high Arctic. Meadow wetlands
are key high Arctic regions due to substantial growing season productivity
and CO2 consumption, despite their low abundance. Notable spatial
expansion of these very productive systems, though, is unlikely due to
topographical constraints. The potential of dry polar semideserts to change,
however, is great over the long term (ACIA, 2004). As plant growth, organic
matter production, and soil water retention improve as expected in the polar
semidesert, its CO2 sink strength during the growing season should also
improve. However, this may also work to perturb atmospheric oxygen and
methane infiltration into polar semidesert soils and perhaps decrease the
magnitude of this globally important atmospheric CH4 sink (Jorgensen et
al., 2015). Ultimately, terrestrial ecosystems and their future
climate-related changes, rather than those in lakes and ponds, will likely
control future carbon cycling at high Arctic latitudes.