Introduction
Inland waters represent an important component of the global carbon cycle by
transporting, storing and processing significant amounts of organic and
inorganic carbon (C) and by emitting substantial amounts of carbon dioxide
(CO2) to the atmosphere (Cole et al., 2007; Aufdenkampe et al.,
2011). Globally about 0.32 to 0.8 Pg C is emitted per year as CO2 from
lakes and reservoirs (Raymond et al., 2013; Barros et al., 2011). For
streams and rivers, the global estimates range from 0.35 to 1.8 Pg C yr-1
(Raymond et al., 2013; Cole et al., 2007), where the lower
estimates can be considered as conservative because they omit CO2
emissions from small headwater streams. In 2015 global CO2 evasion from
rivers and streams was estimated at 0.65 Pg C yr-1 (Lauerwald et
al., 2015). Comparable amounts of C are discharged into the oceans by
the world's rivers (0.9 Pg C yr-1) and stored in aquatic sediments
(0.6 Pg C yr-1) (Tranvik et al., 2009). In total, evasion, discharge and
storage of C in inland waters have been estimated to account for about 4 %
of global terrestrial net primary production (NPP; Raymond
et al., 2013) or 50–70 % of the total terrestrial net ecosystem
production (NEP; Cole et al., 2007). A recent
continental-scale analysis, which combined terrestrial productivity
estimates from a suite of biogeochemical models with estimates of the total
aquatic C yield for the conterminous United States (Butman et
al., 2015), resulted in mean C export rates from terrestrial into freshwater
systems of corresponding to 4 % of NPP and 27 % of NEP. These estimates varied by a
factor of 4 across 18 hydrological units with surface areas between
105 and 106 km2.
The substantial lateral and vertical transport of terrestrial-derived C in
inland waters is currently not accounted for in most bottom-up estimates of
the terrestrial uptake rate of atmospheric CO2 (Battin
et al., 2009) and results in high uncertainties in regional-scale C budgets
and predictions of their response to climate change, land use and water
management. Only few studies have quantified C fluxes and pools including
inland waters at the regional scale (103–104 km2)
(Christensen et al., 2007; Buffam et al., 2011; Jonsson et al.,
2007; Maberly et al., 2013) or for small (1–10 km2) catchments
(Leach et al., 2016; Shibata et al., 2005; Billett et al., 2004). The
majority of existing regional-scale studies on terrestrial–aquatic C fluxes
are from the boreal zone and are characterized by a relatively large
fractional surface area covered by inland waters, a high abundance of lakes
and high fluvial loads of dissolved organic carbon (DOC). Landscapes in the
temperate zone can differ in all these aspects, potentially resulting in
differences in the relative importance of aquatic C-fluxes and flux paths
(storage, evasion and discharge) in regional-scale C budgets. In this study,
we provide a representative investigation of a temperate watershed to
improve the understanding of the role of temperate inland water bodies in
the regional and global C-cycles. We analyzed the relationship between
terrestrial NPP and CO2 evasion and C discharge for more than 200
catchments in southwest Germany. The stream-dominated catchments range in
size from 0.8 to 889 km2 and are characterized by a relatively small
fraction of surface water coverage (< 0.5 % of the land surface
area). In contrast to studies from the boreal zone, the fluvial C load is
dominated by dissolved inorganic carbon (DIC). Estimates of aquatic C-export
from the catchments were obtained from water quality and hydrological
monitoring data and were related to terrestrial NPP derived from MODIS
satellite data. The scale dependence of aquatic C-fluxes in relation to
NPP is analyzed by grouping the data according to Strahler stream order (Strahler, 1957). By comparing our results to a variety of published
studies, we finally discuss the magnitude and the relative importance
of different fluvial flux paths in regional-scale C budgets in different
landscapes and climatic zones.
Map of the stream network (black lines) within the state
borders of Rhineland-Palatinate in southwest Germany. The inset map in the
upper left corner indicates the location of the study region in central
Europe. Filled circles mark the positions of sampling sites with color
indicating stream order (SO1–SO4; the numbers in brackets in the legend
are the respective number of sampling sites). The catchment areas of the
sampling sites are marked in grey.
Materials and Methods
Study area and hydrological characteristics
The study area encompasses large parts of the federal state of
Rhineland-Palatinate (RLP) in southwest Germany (Fig. 1). The average
altitude is 323 m (48–803 m) and the mean annual temperature and
precipitation varied between 5.8 and 12.2 ∘C and 244 and 1576 mm,
respectively, during the time period between 1991 and 2011 at the 37 meteorological
stations operated by the state of RLP (http://www.wetter.rlp.de/).
The dominant land covers in the study area are woodland (41 %, mainly
mixed and broad-leaved forest), tilled land (37 %, mainly arable land and
vineyards) and grassland (13 %, mainly pastures) (Corine land cover; EEA, 2006).
The fraction of peatland in the study area is small
(0.95 km2; 0.009 % of the study area) and 16 % of the study area
contains carbonate bedrock.
Most of the rivers in RLP are part of the catchment area of the Rhine River.
Other large rivers in the state are the Mosel, Lahn, Saar and Nahe. The upland
regions of RLP are the sources of many small, steep and highly turbulent streams
with gravel beds (MULEWF, 2015). Lakes in RLP are small with a
total area of approximately 40 km2 (Statistisches Landesamt
Rheinland-Pfalz, 2014) and were omitted from the analysis. The river network
has a total length of 15 800 km and consists of stream orders (Strahler,
1957) between 1 and 7. A catchment map of RLP, consisting of subcatchments
of 7729 river segments was provided by the state ministry (MULEWF,
2013), where a river segment refers to the section between a source and the
first junction with another river or between two junctions with other
rivers. All subsequent analyses were conducted separately for each stream
order and streams of Strahler order greater than 4 were omitted from the
analysis because of the limited sample size with only few catchments
available. Moreover, we omitted streams for which parts of the catchment
area were outside of the study area. Overall, 3377, 1619, 861 and 453 stream
segments were retained for the analysis for Strahler orders of 1 to 4,
respectively. Annual mean discharge and length of the river segments were
obtained from digital maps provided by the state ministry (MULEWF,
2013).
Aquatic C concentrations
DIC concentrations and partial pressure of dissolved CO2 (pCO2) in
stream water were estimated from governmental water quality monitoring data
which were acquired according to DIN EN ISO norms (DIN EN ISO
10523:2012-04; DIN EN ISO 9963-1:1996-02; DIN EN ISO 9963-2:1996-02). The
data include measurements of alkalinity, pH and temperature which were
conducted between 1977 and 2011 (MULEWF, 2013). Sampling intervals
differed between the sites and water sampling was conducted irregularly with
respect to year and season. To exclude a potential bias resulting from the
seasonality of DIC concentrations on the analysis, we only considered river
segments for which at least one measurement was available for each season
(spring, summer, autumn and winter). From these measurements, pCO2 and DIC
concentrations were estimated using chemical equilibrium calculations with
the software PHREEQC (version 2) (Parkhurst and Appelo, 1999). For 201
river segments with seasonally resolved measurements, we first computed
seasonal mean pCO2 and DIC concentrations, which subsequently
were aggregated to annual mean values averaged over the entire sampling
period:
pCO2annual‾=(pCO2spring‾+pCO2summer‾+pCO2autumn‾+pCO2winter‾)/4.
Measurements of dissolved and total organic C (TOC) were available only
for 64 of these sampling sites.
Estimation of lateral DIC export and catchment scale
CO2 evasion
The lateral export of DIC and the total CO2 evasion from the upstream
network were calculated for each of the 201 sampling sites
with seasonally averaged concentration estimates. The lateral DIC export from
the corresponding catchments was calculated as the product of the mean DIC
concentration and discharge. CO2 evasion from the stream network
upstream of each sampling site was estimated by interpolating pCO2 for
all river segments without direct measurements by averaging the mean
concentrations by stream order and assigning them to all stream segments of
the river network (Butman and Raymond, 2011). Stream width
(w, in m), depth (d, in m) and flow velocity (v, in m s-1) were estimated
from the discharge (Q, in m3 s-1) using the following empirical
equations (Leopold and Maddock Jr, 1953):
w=a⋅Qb,d=c⋅Qd,v=e⋅Qf.
For the hydraulic geometry exponents and coefficients, the values from
Raymond et al. (2012) were used (b=0.42, d=0.29, f=0.29, a=12.88,
c=0.4 and e=0.19).
The water surface area (A, in m2) was calculated as the product of
length and width of the river segments. The average slope for each segment
was estimated from a digital elevation map (resolution 10 m) provided by the
federal state of RLP (LVermGeoRP, 2012).
Zhang and Montgomery (1994) investigated the effect of digital
elevation model (DEM) resolution on the slope calculation and performance in
hydrological models for spatial resolutions between 2 and 90 m. They found
that while a 10 m grid is a significant improvement over 30 m or coarser
grid sizes, finer grid sizes provide relatively little additional
resolution. Thus, a 10 m grid size represents a reasonable tradeoff between
increasing spatial resolution and data handling requirements for modeling
surface processes in many landscapes. The gas transfer velocity of CO2
at 20 ∘C (k600, in m d-1) was calculated from slope (S)
and flow velocity (v, in m s-1) (Raymond et al., 2012).
k600=S⋅v⋅2841.6+2.03
This gas transfer velocity was adjusted to the in situ temperature
(kT, in m d-1) using the following equation:
kT=k600⋅ScT600-0.5.
where ScT is the Schmidt number (ratio of the kinematic viscosity of
water and the diffusion coefficient of dissolved CO2) at the in situ
temperature (Raymond et al., 2012). Finally the CO2 flux
(FD, in g C m-2 yr-1) for each stream segment was calculated
as
FD=kT⋅KHpCO2-pCO2,a⋅MC.
The partial pressure of CO2 in the atmosphere (pCO2,a) was
considered as constant (390 ppm) and the Henry coefficient of CO2 at
in situ temperature (KH, in mol L-1 atm-1) was estimated
using the relationship provided in Stumm and Morgan (1996). MC is the molar mass of C (12 g mol-1). Finally, the total CO2
evasion was estimated by summing up the product of FD with the
corresponding water surface area for all stream segments located upstream of
each individual sampling point.
Estimation of the catchment NPP
Average NPP in the catchment areas of the study sites were obtained from a
global data set derived from the moderate resolution imaging spectroradiometer
(MODIS) observations of the earth observing system (EOS) satellites, which
is available for the time period 2000 to 2013 with a spatial resolution of
30 arcsec (∼ 1 km2; Zhao et al.,
2005). In this data set, NPP was estimated based on remote sensing
observations of spectral reflectance, land cover and surface meteorology as
described in detail by Running et al. (2004). We used mean
NPP data (2000–2013) averaged over the catchment areas of the individual
sampling sites.
Statistical analysis
Linear regressions (F test) were used to analyze the data. Group differences
or correlations with p<0.05 were considered statistically
significant. For the regression of total aquatic C-export rate and annual
catchment NPP, data were log-transformed to correct for normal distribution.
All statistical analyses were performed with R (R Development Core Team,
2011).
Major hydrological characteristics, pCO2, DIC and DOC
concentrations averaged over stream orders (SO) and for all sampling sites
(Total). All values are provided as mean ± SD (standard deviation) of
the annual mean observations, ranges are given in brackets and n is the number
of observations.
SO 1
SO 2
SO 3
SO 4
Total
n
29
53
60
59
201
Catchment size
9 ± 7
16 ± 9
87 ± 54
243 ± 140
103 ± 126
(km2)
(1–35)
(4–37)
(9–298)
(48–889)
(1–889)
Water coverage
0.24 ± 0.11
0.26 ± 0.09
0.36 ± 0.11
0.42 ± 0.13
0.33 ± 0.13
(%)
(0.05–0.43)
(0.1–0.45)
(0.09–0.6)
(0.18–0.7)
(0.05–0.7)
Discharge
0.06 ± 0.05
0.15 ± 0.10
0.73 ± 0.63
2.20 ± 1.95
0.91 ± 1.41
(m3 s-1)
(0.003–0.19)
(0.01–0.36)
(0.02–3.41)
(0.22–12.22)
(0.003–12.22)
Drainage rate
0.26 ± 0.17
0.29 ± 0.16
0.27 ± 0.17
0.30 ± 0.21
0.28 ± 0.18
(m yr-1)
(0.05–0.67)
(0.06–0.66)
(0.05–0.74)
(0.06–1.20)
(0.05–1.20)
pH
7.58 ± 0.61
7.70 ± 0.46
7.81 ± 0.37
7.75 ± 0.29
7.73 ± 0.42
(6.20–8.97)
(6.30–8.60)
(6.60–8.30)
(6.91–8.30)
(6.20–8.97)
Alkalinity
3.08 ± 2.50
2.74 ± 2.58
2.77 ± 1.85
2.58 ± 1.73
2.75 ± 2.12
(mmol L-1)
(0.08–7.58)
(0.08–8.55)
(0.14–9.88)
(0.32–7.22)
(0.08–9.88)
pCO2
2597 ± 1496
1819 ± 1095
1992 ± 1327
2162 ± 1302
2083 ± 1303
(ppm)
(145–6706)
(681–5338)
(573–7627)
(366–7759)
(145–7759)
DIC
38.8 ± 30.3
34.2 ± 31.1
34.6 ± 22.4
32.4 ± 21.0
34.5 ± 25.7
(g m-3)
(3.4–93.1)
(3.5–104.5)
(3.1–119.6)
(4.1–89.3)
(3.1–119.6)
DOC
3.54 ± 1.86
4.11 ± 0.73
4.17 ± 1.08
4.10 ± 1.24
4.08 ± 1.20
(g m-3)
(2.2–6.7)
(3.1–4.8)
(2.6–7.1)
(2.0–7.7)
(2.0–7.7)
(n=5)
(n=4)
(n=22)
(n=33)
(n=64)
Results
Catchment characteristics and aquatic C load
The size of the analyzed catchment areas varied over 3 orders of
magnitude (0.8 to 889 km2) and the mean size increased from 9 km2
for 1st order streams to 243 km2 for streams of the order 4 (Table 1). Mean discharge and catchment area were linearly correlated
(r2=0.74, p<0.001). The runoff depth, i.e., the stream
discharge divided by the catchment area, was relatively constant across
stream orders with a mean value of 0.28 m yr-1, corresponding to 35 % of the annual mean precipitation rate in the study area. The mean discharge
increased more than 30-fold from 0.06 to 2.2 m3 s-1 for 1st to 4th order streams, respectively. Similarly, the estimated water
surface area increased with increasing stream order from 0.24 to 0.42 % of the corresponding catchment size (Table 1).
Individual estimates of the CO2 partial pressure at the sampling sites
varied between 145 and 7759 ppm. Only 1 % of the pCO2 values were
below the mean atmospheric value (390 ppm), indicating that the majority of
the stream network was a source of atmospheric CO2 in all seasons. The
pCO2 was higher in summer (mean ± SD: 2780 ± 2098 ppm) and
autumn (mean ± SD: 2848 ± 2019 ppm) than in winter (mean ± SD: 2287 ± 1716 ppm) and spring (mean ± SD: 2172 ± 2343 ppm).
The total mean value of pCO2 was 2083 ppm and pCO2 and DIC did not
differ significantly among the different stream orders (pCO2 : p=0.35, DIC: p=0.56). On average, DIC in the stream water was composed
of 91.2 % bicarbonate, 0.4 % carbonate and 8.4 % CO2.
TOC versus DIC concentration. Different colors
indicate sampling sites from different stream orders. The solid line shows
the fitted linear regression model with TOC = 0.04 ⋅ DIC
(r2=0.33, p<0.001).
The few available samples of DOC and TOC indicate that the organic C
concentration was about 1 order of magnitude smaller than the inorganic C
concentration (Table 1). There were no pronounced regional or temporal
differences in organic C. Only a small fraction of TOC was in
particulate form (on average 8.6 %) and TOC was linearly related to DIC,
indicating that the organic load made up only 4 % of the total C
load at the sampling sites (Fig. 2). The data are provided in the Supplement.
Aquatic C-fluxes and terrestrial NPP in catchments drained by
streams of different stream orders (SO) and for all sampling sites (Total).
All values are mean ± standard deviation and ranges are given in
brackets. The CO2 flux from the water surface (first row) is expressed
per square meter water surface area, while the remaining fluxes are
expressed per square meter catchment area.
SO 1
SO 2
SO 3
SO 4
Total
CO2 flux from water
2415 ± 2335
1975 ± 1364
1998 ± 1671
1928 ± 903
2032 ± 1528
surface (g C m-2 yr-1)
(-335–12 915)
(418–7143)
(704–11 016)
(851–5093)
(-335–12 915)
Gas transfer velocity
7.04 ± 4.52
7.74 ± 3.78
5.86 ± 2.81
4.23 ± 0.96
6.05 ± 3.32
k600 (m d-1)
(2.16–20.57)
(2.03–20.50)
(2.03–15.55)
(2.03–6.50)
(2.03–20.57)
CO2 evasion per catchment
5.9 ± 6.3
5.2 ± 4.1
7.0 ± 6.6
8.0 ± 4.6
6.6 ± 5.5
area (g C m-2 yr-1)
(-1.0–30.0)
(0.7–19.2)
(1.6–43.8)
(3.0–23.0)
(-1.0–43.8)
DIC discharge per catchment
6.2 ± 4.5
7.1 ± 6.1
7.7 ± 5.7
7.5 ± 4.7
7.3 ± 5.4
area (g C m-2 yr-1)
(1.6–25.8)
(0.6–27.2)
(1.6–35.5)
(1.2–24.5)
(0.6–35.5)
Total aquatic C-export per catchment
12.1 ± 6.9
12.3 ± 6.9
14.7 ± 10.8
15.5 ± 6.7
13.9 ± 8.3
area (g C m-2 yr-1)
(4.7–34.5)
(1.5–29.6)
(5.3–66.8)
(7.0–33.8)
(1.5–66.8)
NPP
466 ± 127
536 ± 66
527 ± 57
508 ± 69
515 ± 79
(g C m-2 yr-1)
(106–661)
(251–644)
(364–627)
(330–618)
(106–661)
Catchment NPP and C budget
NPP increased linearly with catchment size (r2=0.98, p<0.001),
but the specific NPP, i.e., the total NPP within a catchment divided by
catchment area, did not differ significantly (p=0.24) among catchments of
different stream orders. The smallest mean value and the largest variability
of specific NPP (mean ± SD: 466 ± 127 g C m-2 yr-1,
range: 106 to 661 g C m-2 yr-1) was observed among the small
catchments of 1st order streams, while the variability was consistently
smaller for higher stream orders (Table 2). The total average of terrestrial
NPP in the study area was 515 ± 79 g C m-2 yr-1 (mean ± SD).
In a simplified catchment-scale C balance, we consider the sum of the DIC
discharge (DIC concentration multiplied by discharge) measured at each
sampling site and the total CO2 evasion from the upstream network as the total amount of C that is exported from the catchment
area through the aquatic conduit. The total evasion was estimated by
interpolation with stream-order specific pCO2 values assigned to the
complete stream network. Given the small number of available measurements,
we neglect the fraction of organic C which is exported with stream
discharge. As demonstrated above, TOC load is small in comparison to the DIC
load (Fig. 2), resulting in a comparably small (< 4 %) error.
The resulting CO2 evasion rates decreased slightly, but not
significantly (p=0.26) for increasing stream orders with a total mean
evasion rate of 2032 g C m-2 yr-1 (expressed as per unit water
surface area; Table 2). The total aquatic evasion rate within catchments
normalized by the size of the catchment increased significantly with stream
order with a mean value of 6.6 g C m-2 yr-1 (Table 2).
Annual rate of C export through the stream network versus
terrestrial NPP in the catchment area. Different colors indicate sampling
sites from different stream orders. The solid line shows the fitted linear
regression model for the log-transformed data with C_export = 0.005 ⋅ NPP1.06 (r2=0.89, p<0.001).
The total aquatic C-export rate, i.e., the sum of evasion and DIC discharge,
was strongly correlated with annual mean NPP averaged over the corresponding
catchment area. Linear regression of the log-transformed data results in a
power-law exponent of 1.06, indicating a nearly linear relationship (Fig. 3). As small streams of low stream order can be directly influenced by local
peculiarities, the relationship is more variable for streams of Strahler
order 1 and 2, while larger streams represent more average conditions over
larger spatial scales with less variability. However, most of the correlation between
the total aquatic C-export rate and the annual mean NPP can be
attributed to their common linear-scale dependence.
(a) Box plots of C export (sum of evasion and discharge) normalized by
catchment area. (b) Box plots of the ratio of the total exported C and
terrestrial NPP for different stream orders. (c) Box plots of the fraction of
the total exported C which is emitted to the atmosphere from the stream
network for each stream order. The boxes demarcate the 25th and 75th
percentiles and the whiskers demarcate the 95 % confidence intervals. Median
and mean values are marked as horizontal lines and square symbols,
respectively. The sample numbers (n) provided in (a) apply to all panels.
After normalization with catchment area, the total aquatic C-export rate
increased slightly with stream order (Fig. 4a). Also, the ratio of the C
exported through the aquatic network (i.e., the sum of evasion and discharge)
to the terrestrial NPP increased slightly, though not significantly
(p=0.32), from 2.18 % for 1st order streams to 2.72 % for stream
order 4 (Fig. 4b). This increase was related to increasing rates of CO2
evasion in streams of higher order and the contribution of evasion to the
total C-export rate increased from 39 to 53 % (Fig. 4c). The increasing
evasion is mainly caused by the increasing fractional water surface area for
increasing stream orders (Table 1), because the CO2 fluxes per water
surface showed a rather opposing trend with decreasing fluxes for increasing
stream orders (Table 2). On average, 1.31 % of the catchment NPP is
emitted as CO2 from the stream network and 1.49 % is discharged
downstream (Table 2).
Map of 3rd and 4th order catchments showing (a) mean NPP
(g C m-2 yr-1), (b)
aquatic export (g C m-2 yr-1) and (c) ratio
aquatic export/NPP (%).
No regional (large-scale) pattern or gradients were observed in the spatial
variation in catchment-scale NPP nor aquatic C-export (Fig. 5).
Discussion
Uncertainty analysis
Our estimates are subject to a number of uncertainties associated with
sampling, interpolation and systematic errors including the neglect of
C burial in sediments, C export and evasion as methane, and
unresolved spatial and temporal variability.
According to Abril et al. (2015), high uncertainties of pCO2
estimates from pH and alkalinity measurements occur at pH values < 7. In our study, only 7 % of the pH values were < 7. For
pH > 7 the median and mean relative errors are 1 and 15%,
respectively (Abril et al., 2015). Raymond et al. (2013)
estimated uncertainties from comparisons of estimates obtained using
approaches comparable to the present study with direct measurements of
CO2 concentration on streams. For a density of sampling locations of
0.02 sites per km2 (corresponding to this study) they derived an
uncertainty of 30 %. Similarly, Butman and Raymond (2011)
estimated uncertainties of overall flux estimates of 33 %, based on Monte
Carlo simulation of similar data for hydrographic units in the United
States. However, we expect that these unbiased, i.e., randomly distributed,
uncertainties did not affect the general results of our model.
While the riverine C concentrations were obtained from measurements
that covered a time period from 1977 to 2011, the NPP data were available
for the time period from 2000 to 2013. In boreal and subtropical rivers, an
increasing per decade DIC export due to climate change and anthropogenic
activities has been observed (Walvoord and Striegl, 2007; Raymond et al.,
2008); therefore the different time periods covered by the two data sets
might pose a problem. However, comparisons of DIC measurements in the study area
between 1977–1999 and 2000–2011 did not show significant changes.
Furthermore, the sampling frequency for DIC increased so that the majority
of DIC measurements originated from the same time period as the NPP data.
The hydraulic geometry exponents and coefficients used in this study were
derived from various data sets obtained in North America, not for central
Europe. Unfortunately, we are not aware of a comparably extensive data set
of hydraulic geometry data derived for European rivers. The coefficients
have been applied in global studies before, e.g., Raymond et al. (2013). A comparison of hydraulic geometry coefficients derived from various
data sets, including data from England, Australia and New Zealand, is
presented in Butman and Raymond (2011), who estimated that the
error associated with uncertainties of hydraulic geometry coefficients is
rather small compared to uncertainties derived for C fluxes.
C burial in sediments was neglected in this study but can make a
significant contribution to catchment-scale C balances. Estimates vary
between 22 % at a global scale (Aufdenkampe et al., 2011), 14 % for
the conterminous US (Butman et al., 2015) and 39 % for the
Yellow River network (Ran et al., 2015). However, C storage in
aquatic systems occurs mainly in lakes and reservoirs, which are virtually
absent in the study area. Therefore we consider the bias caused by
neglecting storage to be small in comparison to remaining uncertainties
(30 %).
Similarly, the transport of C as methane was neglected because
measurements of methane concentration or fluxes were not available for the
study area. According to a recent meta-analysis, the dissolved methane
concentration in headwater streams varies mainly between 0.1 and
1 µmol L-1, with streams in temperate forests being at the lower end
(Stanley et al., 2016). As the methane makes up only a small fraction of
total C in comparison to the mean DIC concentration in the present
study (500 µmol L-1), it can be assumed that methane makes a rather
small contribution to the catchment-scale C balance.
Since no time-resolved discharge data were available for the sampling sites,
we cannot account for extreme events. Moreover, no information was
available if the governmental monitoring included sampling during floods.
Given the stochastic nature and short duration, we expect that such samples
are at least underrepresented. Since it has been observed that
high-discharge events can make a disproportionally high contribution to
annual mean C export from catchments, we consider our estimates as a
lower bound.
An average study region
The average C fluxes in the catchments of the study area resemble
global and large-scale zonal mean estimates in many aspects. The mean
atmospheric flux of CO2 from the stream network of
2031 ± 1527 g C m-2 yr-1 is in close agreement with bulk estimates for streams
and rivers in the temperate zone of 2630 g C m-2 yr-1 (Aufdenkampe et al., 2011) and
2370 g C m-2 yr-1 (Butman and Raymond, 2011). The
fractional surface coverage of streams and rivers (0.42 % for stream
order 4) corresponds to the global average of 0.47 % (Raymond
et al., 2013) and also mean terrestrial NPP in the catchments (515 g C m-2 yr-1)
was in close correspondence to recent global mean
estimates (495 g C m-2 yr-1; Zhao et al., 2005).
By combining CO2 evasion and downstream C-export by stream discharge,
we estimated that 13.9 g C m-2 yr-1, corresponding to 2.7 % of
terrestrial NPP, are exported from the catchments by streams and rivers, in
which both evasion and discharge contributed equally to this flux. Also,
these findings are in close agreement with global and continental-scale
estimates of 16 and 13.5 g C m-2 yr-1, respectively (Table 3).
Summary of estimates of aquatic C-export in relation to terrestrial
production in the watershed across different spatial scales (spatial scale
decreases from top to bottom). Aquatic C-export is the sum of C-discharge
and evasion (numbers in parentheses also include the change in C storage in
the aquatic systems by sedimentation) normalized by the area of the
terrestrial watershed. Aquatic C fate refers to the percentage of the total
exported C which is emitted to the atmosphere (evasion) and transported
downstream (discharge). The missing percentage is the fraction which is
stored in the aquatic systems by sedimentation (if considered). Terrestrial
production is expressed as NPP or as net ecosystem exchange (NEE). n.c. indicates that this compartment/flux was not considered in the respective
study.
Study area
Fractional water
Aquatic C
Aquatic C
Aquatic C-export/
Reference
(catchment size
coverage (%)
export
fate (%):
terrestrial
in km2)
rivers: R
(g C m-2 yr-1)
evasion: E
production (%)
lakes: L
discharge: D
NPP
NEE
Global
R: 0.2–0.3
16
E: 44
3.71
21–642
Aufdenkampe et al. (2011)
(1.3 × 108)
L: 2.1–3.4
(20)
D: 34
Conterminous US
R: 0.52
13.5
E: 58
3.6
273
Butman et al. (2015)
(7.8 × 106)
L: 1.6
(18.8)
D: 28
Central Amazon
4–16
138
E: 87
6.84
n.c.
Richey et al. (2002)
(1.8 × 106)
D: 13
Yellow River network
R: 0.3–0.4
18.5
E: 35
n.c.
96
Ran et al. (2015)
(7.5 × 105)
L: n.c.
(30)
D: 26
(62)
North temperate
R: 0.5
11.8
E: 33
n.c.
7
Buffam et al. (2011)
lake district (6400)
L: 13
(16)
D: 41
Northern Sweden
R: 0.33
9
E: 50 (4.5)
n.c.
6
Jonsson et al. (2007)
(peat) (3025)
L: 3.5
D: 50 (4.5)
Temperate streams
R: 0.33
13.9
E: 47
2.7
n.c.
This study
(0.7–1227)
L: n.c.
D: 53
English Lake district
R: n.c.
5.4
E: 100
1.6
n.c.
Maberly et al. (2013)
(1–360)
L: 2.2
D: n.c.
Forested stream
R: 0.1–0.7
9.4
E: 53
n.c.
8–17
Wallin et al. (2013)
catchments in Sweden
L: n.c.
D: 47
(0.46–67)
(<0.7)
Forest catchment
R: –
4
E: n.c.
n.c.
2
Shibata et al. (2005)
in Japan (9.4)
L: n.c.
D: 100
Peatland catchment
R: 0.05
30.4
E: 13
n.c.
160
Billett et al. (2004)
(3.35)
L: n.c.
D: 87
Peatland catchment
R: n.c.
12.2
E: –
n.c.
12–50
Leach et al. (2016)
(2.7)
L: 2.2
D: –
1 For a value of 56 Pg C yr-1 for global NPP (Zhao
et al., 2005).2 Global mean NEE was estimated as the difference of gross primary production (GPP) and ecosystem
respiration, which was assumed to be 91–97 % of GPP
(Randerson et al., 2002).3 This percentage refers to NEP instead of NEE.4 For a global mean value of NPP in tropical forests of 1148 g C m-2 yr-1 (Sabine et al., 2004).
Aquatic C-export across spatial scales
Although not exhaustive, Table 3 provides data from a large share of existing
studies relating the aquatic C-export to terrestrial production in the
corresponding catchments, which cover a broad range of spatial scales and
different landscapes. Except for the tropical forest of the Amazon basin,
the aquatic C-export normalized to catchment area estimated for
temperate streams in our study is surprisingly similar to those estimated
at comparable and at larger spatial scale. In the Amazon, the fraction of
terrestrial production that is exported by the fluvial network is more than
2-fold higher (nearly 7 % of NPP; Richey et al., 2002).
However, it must be noted that a large fraction of the regional NPP in the Amazon is
supported by aquatic primary production by macrophytes and C export is
predominantly controlled by wetland connectivity, with wetlands covering up
to 14 % of the land surface area (Abril et al., 2013). An
additional peculiarity of the Amazon is that, in contrast to the remaining
systems, the vast majority (87 %) of the total C-export is governed by
CO2 evasion (Table 3), whereas lateral export constitutes a much
smaller component. An exceptionally low fraction of NPP that is exported
from aquatic systems at larger scale was estimated for the English Lake
District (1.6 %; Maberly et al., 2013), though only
CO2 evasion from lake surfaces was considered, i.e., downstream
discharge by rivers was ignored. Their estimate agrees reasonably well with
the fraction of catchment NPP that was emitted to the atmosphere from the
stream network in the present study (1.3 %). If a similar share of
catchment NPP was also exported with river discharge in the Lake District,
the average mass of C exported from the aquatic systems per unit catchment
area would be in close agreement with our and other larger-scale estimates
(Table 3).
In more detailed studies at smaller scales and for individual catchments,
aquatic C-export was exclusively related to net ecosystem exchange (NEE)
measured by eddy covariance. Here, the estimated fractions of aquatic export
range between 2 % of NEE in a temperate forest catchment (only discharge,
evasion not considered; Shibata et al., 2005) and 160 % of NEE
in a boreal peatland catchment (Billett et al., 2004).
Analysis of interannual variations in stream export from a small peatland
catchment in Sweden (Leach et al., 2016) resulted in
estimates of C export by the fluvial network between 5.9 and 18.1 g C m-2 yr-1 over 12 years.
The total mean value of 12.2 g C m-2 yr-1, however, is in close agreement with the present and other
larger-scale estimates (Table 3). In contrast to the present study, C export
from the peatland catchments was dominated by stream discharge of DIC.
Controlling factors for aquatic C-export
We found a significant linear relationship between total catchment NPP and
the C export from the catchment in the stream network across 4 Strahler
orders. The relationship was mainly caused by a strong correlation between
catchment size and water surface area. As expected for temperate zones,
large streams and rivers with large surface area have larger catchments. A
study analyzing aquatic C-fluxes for 18 hydrological units in the
conterminous US (Butman et al., 2015) observed a significant
correlation between catchment-specific aquatic C yield and specific
catchment NEP, which in turn was linearly correlated to NPP. We did not
observe such a correlation at smaller scale, which could be related to the
rather narrow range of variability in NPP among the considered catchments.
Nevertheless, the linear correlation observed by Butman et
al. (2015) indicates that a constant fraction of terrestrial NPP is exported
by aquatic systems if averaged over larger spatial scales.
The relatively narrow range of variability in C export per catchment area
(between 9 and 18 g C m-2 yr-1, with the two exceptions discussed
above) in different landscapes (Table 3) is rather surprising. Although this
range of variation is most likely within the uncertainty of the various
estimates, the variability across different landscapes is certainly small in
comparison to the order of magnitude differences in potential controlling
factors like catchment NPP, fractional water coverage as well as size and
climatic zone of the study area. In lake-rich regions, evasion from inland
waters was observed to be dominated by lakes (Buffam et al., 2011; Jonsson
et al., 2007), which cover up to 13 % of the surface area of those
regions. In the present study, as well as in other studies on catchments where
lakes are virtually absent (Wallin et al., 2013) and the
fractional water coverage was smaller than 0.5 % of the terrestrial
surface area, an almost identical catchment-specific C export and evasion
rate has been observed (Table 3). CO2 emissions from water surfaces
depend on the partial pressure of CO2 in water and are therefore
related to DIC, which was the dominant form of dissolved C in the present
study. Studies in the boreal zone, where dissolved C in the aquatic systems
is mainly in the form of DOC, however, found comparable catchment-specific C
export and evasion rates (Leach et al., 2016; Jonsson et al., 2007; Wallin
et al., 2013; cf. Table 3). The difference in the speciation of the
exported C indicates that a larger fraction of the terrestrial NPP is
respired by heterotrophic respiration in soils and exported to the stream
network as DIC in the present study, in contrast to export as DOC and
predominantly aquatic respiration. Observations and modeling of
terrestrial–aquatic C fluxes across the US suggested a transition in the
source of aquatic CO2 from direct terrestrial input to aquatic CO2
production by degradation of terrestrial organic C with increasing
stream size (Hotchkiss et al., 2015). Such a transition
was not observed in the present study, where organic C made a small
contribution to the fluvial C-load across all investigated stream
orders. In addition to soil respiration, mineral weathering also contributes
to DIC in stream water. The relative importance of soil respiration and
weathering varies depending on geology and the presence of wetlands in the
area (Hotchkiss et al., 2015; Lauerwald et al., 2013; Jones et al., 2003).
In the present study, 16 % of the catchment areas contained carbonate
bedrock. The DIC concentration in the water increased with the proportion of
carbonate containing bedrock in the catchment (R2=0.33, p<0.001).
Despite the small number of observations in the meta-analysis, the narrow
range of variability in C export per catchment area may indicate that
neither water surface area nor the location of mineralization of terrestrial
derived C (soil respiration and export of DIC versus export of DOC and
mineralization in the aquatic environment) are important drivers for the
total C-export from catchments by inland waters at larger spatial scales.
This rather unexpected finding deserves further attention, as it suggests
that other, currently poorly explored, processes control the
aquatic–terrestrial coupling and the role of inland waters in regional C-cycling.
Given the significant contribution of inland waters to regional and
global-scale greenhouse gas emissions, the mechanistic understanding of
these processes is urgently required to assess their vulnerability to
ongoing climatic and land use changes, as well as to the extensive
anthropogenic influences on freshwater ecosystems. Recent developments of
process-based models, which are capable of resolving the boundless
biogeochemical cycle in the terrestrial–aquatic continuum from catchment to
continental scales (Nakayama, 2016), are certainly an important
tool for these future studies.