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Journal of Geophysical Research: Biogeosciences
RESEARCH ARTICLE
10.1002/2014JG002861
Key Points:
• High-elevation waterbodies experience
gas limitation
• The lack of carbon sources to waterbodies
should be considered
• Gas exchange is overestimated from
indirect measurements
Correspondence to:
J. T. Crawford,
jtcrawford@usgs.gov
Citation:
Crawford, J. T., M. M. Dornblaser,
E. H. Stanley, D. W. Clow, and R. G. Striegl
(2015), Source limitation of carbon gas
emissions in high-elevation mountain
streams and lakes, J. Geophys. Res.
Biogeosci., 120, doi:10.1002/2014JG002861.
Received 19 NOV 2014
Accepted 22 APR 2015
Accepted article online 5 MAY 2015
Source limitation of carbon gas emissions in high-elevation
mountain streams and lakes
John T. Crawford1,2, Mark M. Dornblaser1, Emily H. Stanley2, David W. Clow3, and Robert G. Striegl1
1
U.S. Geological Survey National Research Program, Boulder, Colorado, USA, 2Center for Limnology, University of WisconsinMadison, Madison, Wisconsin, USA, 3U.S. Geological Survey Colorado Water Science Center, Lakewood, Colorado, USA
Abstract Inland waters are an important component of the global carbon cycle through transport, storage,
and direct emissions of CO2 and CH4 to the atmosphere. Despite predictions of high physical gas exchange
rates due to turbulent ﬂows and ubiquitous supersaturation of CO2—and perhaps also CH4—patterns of gas
emissions are essentially undocumented for high mountain ecosystems. Much like other headwater networks
around the globe, we found that high-elevation streams in Rocky Mountain National Park, USA, were
supersaturated with CO2 during the growing season and were net sources to the atmosphere. CO2
concentrations in lakes, on the other hand, tended to be less than atmospheric equilibrium during the open
water season. CO2 and CH4 emissions from the aquatic conduit were relatively small compared to many parts of
the globe. Irrespective of the physical template for high gas exchange (high k), we found evidence of CO2
source limitation to mountain streams during the growing season, which limits overall CO2 emissions. Our
results suggest a reduced importance of aquatic ecosystems for carbon cycling in high-elevation landscapes
having limited soil development and high CO2 consumption via mineral weathering.
1. Introduction
Lakes, streams, and rivers are important global sources of CO2 to the atmosphere [Cole et al., 2007; Butman
and Raymond, 2011; Raymond et al., 2013], and they might also be important sources of CH4 [Bastviken
et al., 2011; Baulch et al., 2011; Striegl et al., 2012; Crawford et al., 2013]. However, the strength of these
conclusions is challenged by a lack of widespread data. Patterns of aquatic gas emissions are reasonably
well described for some arctic, temperate, boreal, and tropical landscapes [e.g., Kling et al., 1991; Jones and
Mulholland, 1998; Hope et al., 2001; Richey et al., 2002; Dinsmore et al., 2010; Wallin et al., 2013], whereas
CO2 and CH4 emissions from high-elevation aquatic ecosystems are essentially unknown [Tamooh et al.,
2013]. Despite their remote nature and often protected administrative status (e.g., national parks and
forests), mountain landscapes in the western U.S. and elsewhere are already experiencing the effects of
climate change and other anthropogenic impacts such as nitrogen saturation, permafrost thaw, insect
outbreaks, long-term drought, and decreasing winter snowfall [Baron et al., 2009]. These stressors affect
aquatic ecosystem function, including carbon (C) gas exchange [Wickland et al., 2001], but we need a more
complete understanding of the C cycle in these systems before we can make sufﬁcient predictions.
Aquatic gas exchange is regulated both by physical processes and the concentration of gases in water. First,
turbulent energy dissipation (approximated by the gas transfer velocity (k; m d1)) constrains the rate at
which gases can be exchanged across the air-water interface. In very turbulent, high-gradient ﬂuvial
systems such as mountain streams, k is predicted to be very high (e.g., >10 m d1 [Butman and Raymond,
2011; Raymond et al., 2012]). Thus, emission of supersaturated gases is expected to be rapid. High rates of
gas exchange cannot occur simply due to high k, as supersaturated gas conditions are also required.
Preliminary estimates of pCO2 indicate that the partial pressure gradient can be high in mountainous
regions of the western U.S. [Butman and Raymond, 2011], thus leading to a prediction of high annual
aquatic CO2 emissions. However, these conclusions are based on limited and uncertain CO2 values
calculated from dissolved inorganic carbon/alkalinity and pH (which can be challenging to measure in
dilute mountain headwaters).
©2015. American Geophysical Union. All
Rights Reserved.
CRAWFORD ET AL.
In high-gradient mountain streams, gas emissions facilitated by high physical exchange could be limited by
CO2 availability. Aquatic respiration produces CO2, resulting in direct emission to the atmosphere. Dissolved
CO2 could also be derived from soil and groundwater respiration sources. Yet in many high-elevation
MOUNTAIN STREAM EMISSIONS
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Journal of Geophysical Research: Biogeosciences
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Figure 1. Photograph of Black Lake illustrating the high topographic relief and lack of organic matter sources in highelevation catchments.
landscapes having substantial exposed bedrock and poorly developed soils, organic C concentrations are low
(Figure 1). If aquatic and terrestrial respiration is a function of organic carbon availability and reactivity, then
high-elevation catchments lacking in organic C sources may also have limited in situ respiration. Although
soil CO2 can be extremely supersaturated with respect to the atmosphere (10 to 100X equilibrium), a large
fraction of respired (biotic) CO2 can be removed via abiotic weathering reactions [Walker et al., 1981]. If
consumption of CO2 via weathering is substantial, then export and degassing in aquatic systems could
also be limited.
Although there have been previous suggestions that headwater streams are locations of intense C
transformations and CO2 emissions, we predicted that low carbon source availability in high-elevation
catchments would lead to relatively low aquatic emissions. With this in mind, we asked three questions for
a high-elevation landscape in the Central Rocky Mountains of Colorado: (1) Is there evidence of CO2 source
limitations on emissions? (2) How do stream and lake pCO2 compare, and how does stream pCO2 change
over the course of a year in a high-elevation catchment? (3) What is the aquatic contribution to CO2 and
CH4 cycling in a high-elevation aquatic network? Answers to these questions will help constrain the
contribution of streams and lakes to regional and global C balances. We used a U.S. Geological Survey
(USGS) time series of dissolved gases (CO2 and CH4) collected from alpine and subalpine streams and lakes
in Rocky Mountain National Park (RMNP) during 1999 and a spatial upscaling technique to predict basinscale emissions. As a follow up to these data, we measured pCO2, pCH4, and emissions of both gases in a
series of streams in the park during June and July 2013.
2. Methods
2.1. Site Description
We studied high-elevation lakes and streams mostly contained within the boundaries of RMNP (Figure 2),
near Estes Park, Colorado, USA. Site elevations ranged from a low of 2780 m above sea level (asl) in
subalpine forest to a maximum of 3505 m asl, just below the continental divide (4000 m asl) in the high
alpine. In addition to two broad surveys of stream and lake chemistry in 1999 (described in Clow et al.
[2002]), we focused on patterns of CO2 and CH4 in the alpine Loch Vale and Glacier Gorge catchments,
which are part of the USGS Water, Energy, and Biogeochemical Budgets program. In Loch Vale, mean
annual precipitation is 110 cm, with 65–85% falling as snow [Baron and Denning, 1993]; mean annual
CRAWFORD ET AL.
MOUNTAIN STREAM EMISSIONS
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Journal of Geophysical Research: Biogeosciences
10.1002/2014JG002861
Figure 2. (top) Map of study locations from 1999 to 2013 and (bottom) map of transect locations given in Table 1.
temperatures range from 1.7°C at the basin outlet to 5.0°C at upper elevations [Clow et al., 2003a]. Land
cover is dominated by exposed rock (53%), with only 7% forest cover, which is limited to valley bottoms.
Where present, poorly developed soils on hillslopes and in the forest have relatively low organic carbon
content between 0.5 and 2.7% but somewhat higher values in riparian areas [Baron et al., 1992]. The focal
catchment (Loch Vale) is drained by two streams, Andrews Creek and Icy Brook (less than 1% forested
catchments), which merge 0.6 km above The Loch (the lowest elevation alpine lake in the basin; Figure 2).
High elevations are dominated by tundra landscapes including communities of sedges, grasses, and other
herbaceous plants. Engelmann spruce (Picea engelmanii) and subalpine ﬁr (Abies lasiocarpa) populate the few
forested areas in the lower portions of the catchment. Water discharge data were obtained for stream gages
operated by the USGS on Andrews Creek (elevation = 3205 m asl) and Icy Brook (elevation = 3171 m asl).
2.2. pCO2 and pCH4 Measurements (1999)
Partial pressures of CO2 and CH4 were measured at approximately weekly intervals in 1999 (March–December)
along two stream/lake transects in adjacent catchments. The transect data track changes in dissolved gas
concentrations as water ﬂows from the highest elevations, through lakes, and into lower elevations,
and document differences between stream and lake sites as well as longitudinal variability in gas
production/consumption and efﬂux. The transects included the Loch Vale catchment (Andrews Creek ﬂow
path and Icy Brook) and the ﬂow path from Black Lake to Glacier Creek in Glacier Gorge (Figure 2 and
Table 1). An additional 18 streams in the park were sampled less regularly (~8 times each), and 37 lakes were
sampled once during September 1999 [Clow et al., 2002, 2003b]. Surface pCO2 and pCH4 were analyzed
CRAWFORD ET AL.
MOUNTAIN STREAM EMISSIONS
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Journal of Geophysical Research: Biogeosciences
10.1002/2014JG002861
Table 1. Average pCO2 and pCH4 Values for Repeated Longitudinal Sampling Sites in the Andrews Creek and Glacier
Gorge Catchments Corresponding to Sites in Figure 2
Transect
Site Number
on Map Inset
Site Name
Elevation (m)
Mean
pCO2 (SD)
Mean
pCH4 (SD)
1
2
3
4
5
6
7
Andrews Tarn Outﬂow
Andrews Creek, MS5
Andrews Creek
Andrews Creek above Icy Brook
Icy Brook at Loch Inlet
Loch Outlet at gage
Icy Brook
3465
3262
3205
3156
3111
3109
3171
233 (115)
168 (121)
651 (754)
229 (81.6)
201 (150)
323 (271)
401 (329)
34.3 (84.4)
34.7 (87.1)
4.14 (4.85)
3.76 (5.81)
5.45 (7.27)
6.1 (8.77)
2.72 (3.99)
8
9
10
11
12
13
Black Lake
(not measured)
Glacier Creek above Jewel Lake
Mills Lake
Mills Lake Outlet
Glacier Creek below Loch Creek
3238
310 (274)
3.96 (6.52)
3039
3033
3033
2979
463 (411)
513 (476)
387 (134)
387 (169)
5.28 (8.51)
12.1 (29.6)
9.38 (10.2)
18.1 (42.5)
Andrews Creek
Glacier Gorge
using a headspace equilibration method [Striegl et al., 2001], in which a 15 mL water sample obtained 10 cm
below the water surface was preserved in a 30 mL serum bottle that was preevacuated with N2 gas. CO2 was
analyzed using a Li-Cor LI-6262 benchtop infrared gas analyzer (IRGA). Methane concentrations were
measured using a Hewlett Packard model 5890 II gas chromatograph equipped with a ﬂame ionization
detector having a minimum detection limit of 50 ppbv.
2.3. CO2 and CH4 Measurements (2013)
We resampled many of the sites from the 1999 survey in June and July 2013. Stream and lake pCO2 were
measured using handheld Vaisala CO2 probes modiﬁed for submersion in water [Johnson et al., 2010],
which were allowed to equilibrate under water for a minimum of 30 min before measurements were
recorded. The CO2 probes have a manufacturer-reported accuracy equal to 1.5% of the calibrated range
(10,000 ppmv) plus 2% of the reading. This level of accuracy could cause discrepancies between measured
ﬂuxes and opposing pressure gradients under low-concentration conditions. Surface pCH4 was measured
using the headspace equilibration method [Striegl et al., 2001]. In addition to concentration measurements,
we made direct measurements of gas exchange with the atmosphere using a suspended chamber
technique [Crawford et al., 2013]. Air-water CO2 exchange (JCO2; mol m2 time1) was calculated by
monitoring the change in CO2 concentration inside a plastic chamber sealed to the stream or lake surface
using a portable PP Systems EGM IRGA (equation (1)):
J CO2 ¼ dC=dt * h
(1)
3
1
where dC/dt is the CO2 concentration change over time (mol m time ) and h is the height of the plastic
chamber (m). Although measurements spanned an average of 5 min, we report ﬂuxes in units of mol m2 d1
to facilitate comparison with other studies while acknowledging that these rates do not account for potential
diel variability.
In addition to the IRGA measurements of CO2 ﬂux, we made eight ﬂux measurements for CO2 and CH4 using a
Los Gatos Research ultraportable greenhouse gas analyzer (UGGA) connected to the plastic chambers. We
switched from the IRGA to the UGGA because of its higher precision and ability to directly measure CH4
(CH4 precision of 2 ppb), in order to better constrain estimates of k in the ﬁeld. UGGA measurements were
made in streams at elevations between 2240 and 2759 m asl. Gas ﬂuxes were calculated by monitoring
the changes in CO2 and CH4 concentrations in the chamber atmosphere over time identically to the
IRGA + chamber technique.
2.4. Upscaled CO2 and CH4 Emissions
We estimated basin-scale (408.63 km2) CO2 and CH4 emissions from the east side of the continental divide
using an upscaling approach with multiple estimates of k. The area of RMNP is 1075 km2, but we did not
CRAWFORD ET AL.
MOUNTAIN STREAM EMISSIONS
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Journal of Geophysical Research: Biogeosciences
10.1002/2014JG002861
have representative samples for the entire region; therefore, watersheds on the west side of the continental
divide were excluded from our analysis. For each upscaling method, we used a combination of stream and
lake surface area, pCO2 and pCH4 values from the 1999 sampling, and modeled or empirical estimates of k.
Daily total stream CO2 ﬂux (CO2Tot, moles CO2, or equivalently CH4Tot) is a function of the difference
between the gas partial pressure of water (pCO2 or pCH4; mol m3), the atmospheric equilibrium
concentration corrected for temperature (CO2sat or CH4sat; mol m3), the gas transfer velocity (k; m d1),
and total water surface area (SA; m2) (equation (2)).
CO2 Tot ¼ ðpCO2 CO2sat Þ * k * SA
(2)
where CO2sat or CH4sat (equation (3)) was calculated according to temperature-dependent solubility of each
gas (Henry’s law constant, Kh) using data from Plummer and Busenberg [1982] for CO2 and Wilhelm et al. [1977]
for CH4 at atmospheric pressure (Patm)
CO2sat ¼ CO2atm * Kh=Patm
(3)
Total stream SA was calculated based on individual stream segment lengths extracted from the NHDPlus data
set multiplied by average segment width calculated using a hydraulic geometry model developed for RMNP
streams [David et al., 2010] (equation (4)).
Width ¼ 2:854 * Q0:16
(4)
Segment Q (m3 s1) was assumed to be constant (the mean annual ﬂow value computed by the “unit runoff”
method from the NHDPlus data set).
Because k can be highly variable and can have high uncertainty, we used two approaches to estimate stream
k. First, we used an empirical model (equation (5)) from Raymond et al. [2012] to calculate stream k normalized
to a Schmidt number of 600 (K600) based on segment attributes from the NHDPlus and a hydraulic geometry
equation for depth (equation (6) [David et al., 2010]).
K 600 ¼ 4725 * ðV * SÞ0:86 * Q0:14 * D0:66
(5)
Depth ¼ 0:37 * Q0:35
(6)
1
1
The selected model uses stream velocity (V; m s ), slope (S; m m ), Q, and depth (D; m) as inputs, and a
regression of observed against calculated k values has a high r2 (0.76). This model only incorporates average
discharge conditions and will therefore not capture variation in k due to low- and high-ﬂow events. The goal
was to compare average gas transfer conditions with average concentrations in 1999. K600 from equation (5)
was converted to kCO2 corrected for temperature dependence by rearranging equation (7):
K 600 ¼ ð600=ScCO2 Þ0:5 * k CO2
(7)
ScCO2 is the Schmidt number of CO2 corrected for temperature (T; °C) based on the polynomial ﬁts given by
Wanninkhof [1992] (equation (8)):
ScCO2 ¼ 1911:1 118:11 * T þ 3:4527 * T 2 0:04132 * T 3
(8)
K600 was also converted to kCH4 using the same strategy as for CO2 (modiﬁed equations (7) and (8)).
In our second upscaling approach for streams, we populated a distribution of k from our chamber
measurements made in 2013 assuming a normal distribution (discussed further in Results section) and
used the same pCO2 and SA values. Direct estimates of k were calculated from chamber estimates using
concurrent measurements of pCO2 and gas ﬂux (JCO2) and rearranging equation (9):
J CO2 ¼ ðpCO2 CO2 satÞ * k
(9)
Lake ﬂuxes were estimated from a normal distribution of k with a mean of 0.54 m d1 (SD = 0.12), a distribution
that was derived from a large number of temperate lakes [Read et al., 2012], as predictor variables for empirical
lake k models were not available. Lake area was extracted from the NHDPlus data set. All stream and lake ﬂux
estimates were calculated from Monte Carlo model simulations (1000 replications) conservatively assuming
180 days of open water. Fluxes and uncertainty are reported as the mean and the 95% conﬁdence interval of
the simulations calculated using the function quantile in R.
CRAWFORD ET AL.
MOUNTAIN STREAM EMISSIONS
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Journal of Geophysical Research: Biogeosciences
10.1002/2014JG002861
Figure 3. Time series of discharge and pCO2 for three streams (Andrews, Icy Brook, and Glacier) as well as one spring in 1999.
The vertical lines separate periods of persistent snow cover and active snowmelt, the gray lines show stream discharge, and
the dashed horizontal line denotes atmospheric equilibrium (~250 μatm at elevation in 1999).
3. Results
3.1. Q Patterns and Timing of Snowmelt
Andrews Creek had low (but nonzero) ﬂow during winter, but Icy Brook had no measureable ﬂow at that time
(Figure 3). Snowmelt in 1999 began in early May, with increasing ﬂows as melt progressed to its peak around
1 July. After peak snowmelt, streamﬂow declined gradually, with the exception of distinct Q peaks in August–
September, which were the result of summer storms that occur frequently along the Front Range of Colorado.
3.2. Stream and Lake pCO2
In 1999, we observed a pattern of supersaturated pCO2 throughout winter until late May to early June at
Andrews Creek (Figure 3). Stream pCO2 then declined substantially coinciding with snowmelt and
increased Q. We observed a slightly different pattern for the groundwater spring near Andrews Creek,
where CO2 remained much more supersaturated through the summer season relative to streams. Stream
pCO2 peaked at nearly 4000 μatm in Andrews Creek, and then quickly declined to values near 1000 μatm
during early snowmelt, which was similar to values in Andrews Spring. Icy Brook and Glacier Creek appear
to have followed similar patterns to Andrews Creek, with near-saturation values persisting throughout the
summer, but we do not have complete data during winter. Our repeated sampling along two stream
transects showed some variability at individual sites but no consistent downstream pattern (Table 1).
In most of the lakes sampled in RMNP during 1999 (n = 37), surface pCO2 was undersaturated with respect to
the atmosphere. Average lake pCO2 was 191 μatm, ranging from below detection to 592 μatm (Figure 4).
Stream pCO2 was typically greater than in lakes during the summer ice-free period (Figure 4) with stream
pCO2 averaging 470 μatm, although undersaturation was still common. In addition to the strong spatial
CRAWFORD ET AL.
MOUNTAIN STREAM EMISSIONS
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10.1002/2014JG002861
20
40
differences between lakes and streams, we
observed a weak but statistically signiﬁcant
negative relationship between stream pCO2 and
elevation (Figure 5; p < 0.05, r2 = 0.11) with the
highest pCO2 and greatest variability observed
in streams at lower elevations.
0
Frequency
60
Journal of Geophysical Research: Biogeosciences
0
500
1000
1500
2000
3.3. Stream and Lake pCH4
8
4
0
Frequency
12
Methane in the focal streams was consistently
supersaturated with respect to the atmosphere
during 1999. Stream pCH4 was relatively stable
over the year, with distinct elevated periods
that did not necessarily overlap among sites
(high pCH4 in July at all sites except Icy Brook;
high at Andrews Creek and Icy Brook in August
0
100
200
300
400
500
600
but not at Andrews Spring; Figure 6). Spring
pCO2 (µatm)
water pCH4 increased beginning in the fall
reaching values near 20 μatm in the early
Figure 4. Distributions of (top) stream and (bottom) lake pCO2
winter months, but this pattern was not
during the 1999 ice-free season; the dotted lines denote the
evident in other nearby surface waters. There
mean value.
was high spatial variability in pCH4 along the
two stream transects, with no clear relation to elevation or stream order (Table 1). We observed
supersaturated pCH4 in both streams and lakes (Figure 7). Mean stream and lake pCH4 were 7.5 μatm and
3.5 μatm, respectively.
3.4. CO2 and CH4 Emissions
1000
pCO2 (µatm)
1500
In agreement with summertime measurements from 1999, average stream pCO2 in June and July 2013 was
supersaturated with respect to the atmosphere (mean = 417 μatm, SD = 105 μatm, n = 30), and average pCH4
was 6.78 μatm (range = 0.53 to 92.5, SD = 16.1 μatm; data not shown). In 2013, streams ranged from net
sources to sinks of CO2 but on average were net sources (based on instantaneous ﬂux measurements). Mean
CO2 efﬂux was 35.9 mmol CO2 m2 d1, with a maximum of 146 mmol CO2 m2 d1. Three out of 11 ﬂux
measurements made using the IRGA showed net CO2 uptake (up to 40 mmol CO2 m2 d1). Eight
additional ﬂux estimates made using the UGGA supported the CO2 patterns observed with the IRGA. Mean
UGGA CO2 ﬂux was 40.5 mmol CO2 m2 d1 (range = 15.1 to 132 mmol CO2 m2 d1). The UGGA
CH4 measurements showed a large range of
CH4 exchange including net uptake due to CH4
undersaturation (mean = 179 μmol CH4 m2 d1;
range = 21.2 to 642 μmol CH4 m2 d1). We
did not compare UGGA and IRGA methods
directly in this study.
MOUNTAIN STREAM EMISSIONS
7
0
500
Figure 5. Plot of elevation versus pCO2 for Rocky Mountain
National Park streams sampled in 1999; the dashed line is the
least squares regression ﬁt.
Gas transfer velocities estimated from the IRGA
chamber measurements and the pCO2 probes
showed inconsistent reliability due to the
small partial pressure gradients between the
stream and the atmosphere that were not
accurately quantiﬁed by the probes. For
example, on three occasions, we recorded CO2
efﬂux during the chamber deployment but
measured a pCO2 gradient that should result
in CO2 inﬂux from the atmosphere. For the
few chamber measurements that showed
agreement between measured partial pressure
gradients and CO2 exchange (correct sign),
2800
3000
3200
3400
Elevation (m)
CRAWFORD ET AL.
Journal of Geophysical Research: Biogeosciences
10.1002/2014JG002861
Figure 6. pCH4 time series from streams and springs during 1999 in Rocky Mountain National Park. The vertical lines separate
periods of persistent snow cover and active snowmelt, the gray lines show stream discharge, and the dashed horizontal line
denotes atmospheric equilibrium (about 1.1 μatm at elevation in 1999).
60
40
20
0
Frequency
80
we calculated k values between 3.69 and
16.0 m d1 (mean = 9.78 m d1, n = 6). For
comparison, average k from the empirical
model of Raymond et al. [2012] was
68.8 m d1 and was skewed heavily to the
right (discussed later).
−0.5
0.0
0.5
1.0
1.5
2.0
2.5
20
10
0
Frequency
30
log10 pCH4 (µatm)
0
5
10
15
20
25
30
pCH4 (µatm)
Figure 7. (top) Stream (log transformed) and (bottom) lake pCH4
distribution during the 1999 ice-free season; the vertical lines
denote the mean value.
CRAWFORD ET AL.
MOUNTAIN STREAM EMISSIONS
3.5. Upscaled Flux Estimates
We calculated a total stream area of 0.56 km2 and
a total lake area of 3.88 km2 from the NHDPlus
data set covering a total catchment area of
408.63 km2. The total aquatic coverage in the
upscaled region therefore was 1.09% (0.95%
lakes, 0.14% streams). Mean upscaled stream
CO2 emission during the 1999 ice-free season
(assumed to be 180 days) using a k model from
Raymond et al. [2012], the distribution of
summer pCO2 values, and our model of stream
surface area, was 105 × 106 mol CO2 (95%
conﬁdence interval = 169 to 866 × 106 mol
CO2). The second upscaling calculation using
8
Journal of Geophysical Research: Biogeosciences
10.1002/2014JG002861
the distribution of k from our 2013 chamber measurements resulted in a lower mean ﬂux of 24 × 106 mol
CO2 (95% conﬁdence interval = 37.1 to 198 × 106 mol CO2). Yearly ﬂuxes normalized to the catchment
area were 258 and 60.0 mmol CO2 m2 yr1 (3.10 g C m2 yr1 and 0.721 g C m2 yr1) from the two
models, respectively. While streams may still ﬂow during winter, Q during this period was very low or
even unmeasurable (Figure 3), and we assume that CO2 emissions from streams were negligible during
snow cover.
Our estimate of lake CO2 ﬂux using modeled k values was 2.58 × 106 mol CO2 (95% conﬁdence
interval = 13.4 to 14.6 × 106 mol CO2). This indicates that lakes likely exhibit net uptake of atmospheric
CO2 during the ice-free season. Per unit lake surface, CO2 ﬂuxes averaged 4.67 mmol CO2 m2 d1.
Normalized to the catchment area, annual lake ﬂuxes were 8.01 mmol CO2 m2 yr1. The net aquatic
CO2 ﬂux (lakes + streams) for the 1999 open water season therefore was 52.1 mmol CO2 m2 yr1
(625 mg C m2 yr1), indicating that the entire aquatic system was a weak net source of CO2.
Upscaled CH4 emissions were substantially lower (in terms of C) relative to CO2 emissions. The 1999 growing
season ﬂux from streams was 336 × 103 mol CH4 (95% conﬁdence interval = 0.148 to 13200 × 103 mol CH4)
and 215 × 103 mol CH4 (95% conﬁdence interval = 61 to 5210 × 103 mol CH4), using the Raymond et al.’s
[2012] k model and our 2013 k distribution, respectively. Stream CH4 ﬂuxes were substantially less (in terms
of C) relative to CO2 ﬂuxes. Normalized to catchment area, stream CH4 emissions were between 1.30 and
1.93 mmol CH4 m2 yr1. Lake CH4 emissions were much lower than streams with net growing season
ﬂux of 58.9 × 103 mol CH4 to the atmosphere (95% conﬁdence interval = 24.9 to 265 × 103 mol CH4;
catchment normalized = 144 μmol CH4 m2 yr1).
4. Discussion
4.1. Overview
Our data lead to three conclusions regarding dissolved gases in mountain aquatic networks. First, there were
conspicuous differences in concentrations of both CO2 and CH4 between streams and lakes suggesting
different underlying processes for these two aquatic habitats. Second, although observed and modeled k
values in the study area were relatively high (>9 m d1), concentrations of dissolved gases were not high,
indicating that efﬂux is likely supply limited. Third, although streams were typically small sources of CO2
and CH4 to the atmosphere, this total ﬂux was partially offset by lakes in the catchment. Collectively, these
data offer a ﬁrst look into C gas emissions in high-elevation catchments and suggest that in these
relatively C-poor landscapes, exchange of C gases with the atmosphere may be substantially smaller than
previously suggested.
4.2. Comparison of Streams and Lakes
Despite strong connectivity between surface water elements, concentrations of lake and stream pCO2 and
pCH4 were different in this high-elevation landscape, a tendency that has been described for other aquatic
networks [Weyhenmeyer et al., 2012]. While streams were typically weakly supersaturated in both CO2 and
CH4 with respect to the atmosphere, lakes were typically undersaturated with CO2 and only weakly
supersaturated in CH4, which differs from the typical pattern of CO2 supersaturation in North American
lakes [Cole et al., 1994; McDonald et al., 2013]. Most of the lake data were collected during the late growing
season and could bias our upscaled estimates of annual exchange with the atmosphere. High-elevation
lakes in these landscapes are thought to have rates of gross primary productivity that exceed respiration
(net autotrophic) [Seastedt et al., 2004], which should generally result in undersaturated CO2
concentrations. But phytoplankton biomass increases steadily following ice-out [Seastedt et al., 2004];
therefore, late summer pCO2 measurements may reﬂect the period of greatest gross primary production
and least pCO2 in the water column, which could account for the observed differences between streams
and lakes. Future work could address the seasonal patterns of stream and lake CO2 simultaneously.
4.3. CO2 Source Limitation
One explanation for the observed high ks but low pCO2 in these mountain streams could be that gas
exchange was sufﬁciently rapid in upstream reaches that high pCO2 was not sustainable. This
interpretation is problematic because high stream pCO2 was seldom encountered in these watersheds,
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except when snow cover inhibited gas exchange with the atmosphere (Figure 3). Therefore, concluding that
CO2 was degassed “somewhere else” is simply not supported. This phenomenon is analogous to an efﬁcient
transportation system (a municipal bus) that has nothing to transport (no riders). The physical template for
high gas exchange is always present, but CO2 molecules from aquatic and terrestrial respiration generally
are not present in sufﬁcient quantities to yield a high ﬂux to the atmosphere.
To explore the concept of source limitation further, we used a simple model of stream CO2 concentration
under a realistic scenario, where k is 10 m d1, water temperature is 10°C, and initial CO2 was 2X saturated
with respect to the atmosphere (62.8 μmol L1 CO2), similar to the average values from our data set
(pCO2 = 539 μatm). To sustain approximate steady state CO2 concentrations of 2X atmospheric equilibrium
under these boundary conditions would require the constant addition of ~13 μmol L1 CO2 h1. Assuming
a mean water depth of 0.5 m requires an areal production rate of 6.5 mmol CO2 m2 h1. While we do
not have knowledge of metabolic rates in our study streams, we can use published values to establish
plausibility of this source. Metabolism measurements from high-elevation (2524 m asl) streams in
the Sangre de Cristo range of northern New Mexico revealed whole stream respiration rates between
6.7 and 14.7 g O2 m2 d1 [Fellows et al., 2001]. We can translate these values to a hypothetical
stream reach in RMNP and compare with the steady state concentration model. Assuming that a stream
has a respiratory quotient of 1.2, this translates to between 42 and 92 mmol CO2 m2 h1. These
published respiration rates for high-elevation streams can therefore easily support steady state 2X
atmospheric CO2 supersaturation under the physical conditions documented in RMNP streams.
However, primary production will offset some of the daily CO2 production, and we suspect that these
rates are high for RMNP given low C availability. Comparison with net ecosystem production (NEP) from
an interregional comparison of lower-elevation streams (NEP varied from 1 to >6 g O2 m2 d1)
[Bernot et al., 2010] also supports the prediction that stream metabolism is capable of supporting
observed ﬂuxes.
A CO2 source limitation is also suggested by patterns of terrestrial metabolism. For example, greatest
respiration rates in high-elevation terrestrial environments and greatest CO2 partial pressures at the soil
surface occur under maximum snow cover [Monson et al., 2006; Mast et al., 1998; Brooks et al., 2004].
Similarly, we found greatest stream pCO2 during periods of snow and ice cover, whereas during
snowmelt, pCO2 was much less and was even undersaturated with respect to the atmosphere on
multiple occasions. Microbial communities in these high-mountain ecosystems are uniquely adapted to
low temperatures and deep snowpacks during winter and spring months [Monson et al., 2006]. Fungal
biomass peaks under snow-covered soils and can be 15 times higher than summer levels [Schadt et al.,
2003], and winter respiration can reemit the majority of C sequestered during the growing season
[Monson et al., 2006; Hubbard et al., 2005]. This broad pattern of seasonal disconnection between
primary production and decomposition in terrestrial systems may also be driving observed patterns
in streams.
We suggest that after CO2-rich soil water is ﬂushed from high-elevation catchments during the onset of
snowmelt, there is little remaining CO2 to maintain high-stream pCO2 and aquatic emissions as snowmelt
proceeds. The rapid release and subsequent decline of CO2 concentrations appear to be similar to the
“ionic pulse” phenomenon for melting snowpacks in the region [Williams et al., 1996], in this case a highelevation “carbonic pulse.” Decreased pCO2 could also be driven by dilution of high pCO2 groundwater
with direct snowmelt contributions to streamﬂow. As soils warm (and dry), and terrestrially derived waters
have lower pCO2 later in the growing season (as suggested by changes in spring water pCO2; Figure 3),
pCO2 in streams moves closer to equilibrium with the atmosphere. CO2 derived from terrestrial respiration
may become very limited during the growing season because of a specialized high-elevation microbial
community that exhibits low metabolic activity during summer [Schmidt et al., 2009; Schadt et al., 2003].
Patterns of stream and lake metabolism likely also contribute to variability at daily to seasonal scales, but
we do not have sufﬁcient data to explore these relationships at present.
4.4. Aquatic Contribution to CO2 Exchange
Most of the available data from around the globe support a substantial aquatic contribution to C cycling [e.g.,
Raymond et al., 2013], but we found relatively low aquatic CO2 and CH4 ﬂuxes in this high-elevation landscape
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Journal of Geophysical Research: Biogeosciences
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(see literature comparisons in Wallin et al. [2013] and Crawford et al. [2013]). Estimates of total stream CO2 ﬂux
varied widely based on the use of modeled or observed k. As such, we urge that these upscaled estimates be
viewed with some caution given the high uncertainty. However, these estimates are helpful for constraining
the magnitude of aquatic emissions. The most probable estimate of catchment-normalized aquatic CO2 ﬂux
for the ice-free season was 625 mg C m2 yr1 (net emissions) in 1999. On the other hand, CH4 emissions
likely did not contribute substantially to the landscape C balance.
We can compare our estimate of aquatic CO2 ﬂuxes to other carbon ﬂuxes in these high-elevation
landscapes. Previous work in this region has focused on the consumption of CO2 due to mineral
weathering. Using a 15 year time series of solutes, water discharge, and geochemical modeling, Clow and
Mast [2010] were able to estimate CO2 consumption by silicate and carbonate weathering reactions. The
outcome of this work is equivalent to assessing catchment-normalized downstream dissolved inorganic
carbon export but with added information on the underlying physical and chemical controls. In the Loch
Vale catchment, CO2 consumption varied between 1.83 and 3.29 g C m2 yr1 and was estimated at
2.29 g C m2 yr1 for 1999 [Clow and Mast, 2010]. Comparison with our upscaled estimates of CO2 ﬂuxes
indicates that chemical weathering of minerals is an important component of the C budget. Annually,
more C is exported laterally in the form of bicarbonate than is emitted across the air-water interface—
terrestrial respiration is “masquerading” as the bicarbonate ion due to weathering reactions [Cole et al.,
2007]. Although this result may seem surprising, the high exposure of bedrock and high physical
weathering rates of talus ﬁelds and other rock landforms [Mast et al., 1990; Clow and Sueker, 2000], as well
as limited soil development in alpine and subalpine regions, should contribute to a pattern of CO2 cycling
that is different from better studied boreal and temperate environments. While CO2 consumption by
weathering appears to be greater than aquatic CO2 emission in this high-elevation catchment, the longterm fate of exported weathering products depends on mineralogy. In Loch Vale, silicate weathering
accounts for approximately two thirds of CO2 consumption, while one third is consumed by carbonate
weathering [Clow and Mast, 2010]—a weaker net sink of CO2 over long time scales.
This study was limited by our ability to accurately measure pCO2 and k in this mountain environment. First,
although we used a combination of headspace and sensor-based pCO2 measurements which are arguably
more accurate than indirect calculations based on pH and alkalinity [Wallin et al., 2014; Abril et al., 2014],
we found disparities between measured ﬂuxes and the saturation state observed with sensors. These
discrepancies are likely due to the inherent error of the sensors. Although such sensors are becoming
widely adopted as a means of monitoring pCO2 in streams and lakes, we suggest that caution be applied
under low-concentration conditions such as encountered here. Further, selection of a probe with better
accuracy at lower concentrations will be essential. Second, our limited number of direct ﬂux
measurements combined with pCO2 resulted in lower k relative to a predictive model [Raymond et al.,
2012]. One explanation for this disagreement comes from our choice of sampling locations. We were only
able to deploy chambers in lower turbulence environments away from standing waves, waterfalls, and
other high-velocity features in streams. This sampling bias likely leads to lower k estimates. On the other
hand, the predictive model of Raymond et al. [2012] has not been validated in such high-gradient
turbulent channels and therefore may need to be viewed as an upper limit with respect to mountain
stream k. Clearly, estimating k accurately continues to pose a major challenge to this research topic.
4.5. Conclusion
This is one of the ﬁrst studies addressing aquatic CO2 and CH4 ﬂuxes in high-elevation catchments. We show
that the aquatic conduit does contribute to the C cycling of high-elevation catchments but to a very small
extent relative to streams in boreal, temperate, and tropical biomes. Stream CO2 concentrations were
limited during the majority of the open water season. Large-scale estimates of aquatic CO2 and CH4
emissions should therefore consider the availability (or lack thereof) of C sources in high-elevation
ecosystems such as the Rocky Mountains where headwater catchments are dominated by exposed
bedrock, with limited vegetative cover and thin, poorly developed soils (e.g., Loch Vale). Similar patterns
are expected in northern mountain networks with limited vegetation cover and poorly developed soils
such as the Tian Shan, the Alps, the Himalaya, and perhaps others in lower latitudes such as the Andes. We
conclude by suggesting that C emissions from mountainous headwater networks are overestimated in
previous continental and global studies based on indirect estimates of aquatic gas exchange.
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Journal of Geophysical Research: Biogeosciences
Acknowledgments
We thank Nick Gubbins and Doug Halm
for their ﬁeld assistance. This work was
supported by the U.S. Geological Survey’s
National Research Program; Water, Energy
and Biogeochemical Budgets Program;
and the Inland Waters LandCarbon
project. J.T.C. was also supported by the
National Science Foundation under
cooperative agreement DEB-0822700,
NTL LTER. Any use of trade or product
names is for descriptive purposes only
and does not imply endorsement by the
U.S. Government. Users can freely access
the data by contacting the corresponding
author (jtcrawford@usgs.gov).
CRAWFORD ET AL.
10.1002/2014JG002861
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