Environ. Sci. Technol. 2007, 41, 6156-6162
Stable Isotope Analysis Reveals
Lower-Order River Dissolved
Inorganic Carbon Pools Are Highly
Dynamic
S U S A N W A L D R O N , * ,†,§
E. MARIAN SCOTT,‡ AND
CHRIS SOULSBY⊥
Scottish Universities Environmental Research Centre, East
Kilbride G75 0QF, United Kingdom, Department of Statistics,
University of Glasgow, Glasgow G12 8QQ, United Kingdom,
and Department of Geography and the Environment,
School of Geosciences, University of Aberdeen,
Aberdeen AB24 3UF, United Kingdom
River systems draining peaty catchments are considered
a source of atmospheric CO2, thus understanding the behavior
of the dissolved inorganic carbon pool (DIC) is valuable.
The carbon isotopic composition, δ13CDIC, and concentration,
[DIC], of fluvial samples collected diurnally, over 14
months, reveal the DIC pools to be dynamic in range
(-22 to -4.9‰, 0.012 to 0.468 mmol L-1 C), responding
predictably to environmental influences such as changing
hydrologic conditions or increased levels of primary
production. δ18O of dissolved oxygen (DO) corroborates
the δ13CDIC interpretation. A nested catchment sampling
matrix reveals that similar processes affect the DIC pool and
thus δ13CDIC across catchment sizes. Not so with [DIC]:
at high flow, the DIC export converges across catchment
size, but at low flow catchments diverge in their DIC
load. Contextualizing δ13C with discharge reveals that
organic soil-waters and groundwaters comprise endmember sources, which in varying proportions constitute
the fluvial DIC pool. Discharge and pH describe well [DIC]
and δ13CDIC, allowing carbon to be apportioned to each endmember from continuous profiles, demonstrated here for the
hydrological year 2003-2004. This approach is powerful
for assessing whether the dynamic response exhibited here
is ubiquitous in other fluvial systems at the terrestrialaquatic interface or in larger catchments.
Introduction
The carbon isotopic composition of dissolved inorganic
carbon (δ13CDIC) traces the source of DIC and the biogeochemical processes that amend pool composition. For
example, δ13CDIC measurements have identified heterotrophic
DIC production as important in oligotrophic lakes (1),
reconstructed ice shelf loss in Antarctic epishelf lakes (2),
and traced the source of intermediate waters in the North
Pacific (3). Increasing focus on the carbon cycle enhances
* Corresponding author phone: 00 44 1413302413; fax: 00 44
1413304894; e-mail: [email protected].
† Scottish Universities Environmental Research Centre.
‡ University of Glasgow.
⊥ University of Aberdeen.
§ Current address: Department of Geographical and Earth Sciences, University of Glasgow, Glasgow G12 8QQ, United Kingdom.
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the significance of direct measures of water body DIC
concentration, [DIC]. For example, lakes and river systems
are usually saturated with respect to the atmospheric
equilibrium concentration and thus predominantly a source
of atmospheric CO2 (4).
Fluvial dissolved oxygen (DO) and DIC are linked via
photosynthesis and respiration: 18O and 13C are discriminated
against, respectively, during DIC and DO consumption; the
product CO2 and oxygen are 16O and 12C-enriched, respectively (5, 6). Thus it is advantageous to measure paired
δ13CDIC-δ18ODO to understand carbon cycling. Although not
new (e.g., ref 7), paired δ13CDIC-δ18ODO measurements are
not commonplace with studies (8, 9) yet published. Additionally, δ13CDIC-δ18ODO measurements generally represent
spot sampling (e.g., ref 10), yet the strength of their interaction
is controlled by day-length and temperature, which impacts
photosynthesis and respiration, and additionally, gasexchange and groundwater contributions.
DIC systematics in higher-order rivers (7, 11) and large
lotic systems (1, 12) have been studied more extensively than
in lower-order rivers. Such studies rarely include paired
δ13CDIC-δ18ODO measurements, beneficial in revealing productivity-driven diel cycling of DIC (13). The Big Hole River
(13), although of lower-order, drains 7200 km2 and baseflow irrigation withdrawal reduces the width (50 m at
sampling) relative to flow (Parker, Personal Communication).
Observations in this catchment size may not describe DIC
behavior in the smaller upper-catchment drainage systems
which interface terrestrial to aquatic carbon export. These
tend to be hydrologically more responsive, and chemically
less-well buffered. Rivers are conduits for terrestrial DIC
export to oceans, but knowledge of whether pool composition
and reprocessing changes with catchment size is limited. To
constrain what processes control fluvial DIC, and to assess
whether these change with catchment size, we measured
fluvial δ13CDIC-δ18ODO and [DIC] from three nested uppercatchments over 14 months and sampled throughout 12 diel
cycles.
Materials and Methods
Study Site and Sampling Strategy. Glen Dye in NE Scotland
(56°56′27N, 2°36′00W) is a headwater subcatchment of the
River Dee, a high-order river draining into the North Sea.
Samples were collected at 1.3 km2 from Brocky Burn, a
second-order river system draining the hillslopes; at 41.7
km2 at Charr gauging flume on the Water of Dye, and at 90
km2 at the Bridge of Bogendreip, Water of Dye (Figure S1a,
Supporting Information (SI)). Glen Dye is predominantly
upland in character, and the altitude ranges from 100-776
m (Figure SI-S1a). The climate is cool, with mean annual
precipitation of 1130 mm of which <10% is snow. Water
balance estimates suggest annual evaporation of ca. 300 mm.
Underlying geology is granite with a small schist outcrop
(Figure SI-S1b). The interfluves above 450 m are covered by
extensive peats (e5 m deep) and peaty podzols (<1 m) (Figure
SI-S1c). In some places peat is eroded to the mineral interface.
Incised catchment slopes have the most freely draining
humus iron podzols (<1 m deep); the main river valley
bottoms generally have freely draining alluvial deposits.
Discharge at 1.3 km2 was measured using a flume and
pressure transducer. The Scottish Environment Protection
Agency provided discharge data for 41.7 km2 (Figure SI-S2).
By comparison with a third gauging station at 233 km2,
discharge for 90 km2 can be confidently estimated (17).
Samples were collected at each site approximately every
5 h over a 24 hour period and 12 times during June 2003 to
10.1021/es0706089 CCC: $37.00
 2007 American Chemical Society
Published on Web 07/28/2007
FIGURE 1. δ13CDIC, δ18ODO and [DIC] for five of the 12 sampling trips. δ13CDIC, δ18ODO, and [DIC] for each sampling date are stacked vertically,
each column represents a different sampling date. The x-axis represents hours since 12:00 on the date of sampling, and the data for the
three nested catchments are shown on each chart. Samples from 41.7 km2 when EpCO2 < 1 are circled. The full data set can be found
in the Supporting Information.
August 2004. The flow conditions at time of sampling are
detailed in Figure SI-S2, Table SI-S1).
Isotopic Analyses, Estimation of EpCO2, and Statistical
Treatment of Data. Samples for [DIC] (mmol L-1 C) and
δ13CDIC were analyzed using a headspace analysis approach
(e.g., ref 15). Underwater, 10 mL of sample was injected into
an acid-washed pre-evacuated exetainer containing 150 µL
of degassed phosphoric acid. Sucking in of the syringe barrel
during sample transfer was used as a quality control measure
to indicate the exetainers had retained vacuum and contamination from atmospheric CO2 was minimal. The shaken
exetainer was stored upside-down with the liquid in contact
with the septa, thus minimizing headspace CO2 ingression
or egression and transported in this manner to the laboratory
to await analysis, which was usually within one week.
Precision on an unknown sample is concentration dependent,
but here, δ13CDIC is within (1‰. [DIC] precision is (0.03
mmol L-1 C.
DO samples were collected in 12 mL exetainers, poisoned
with a small amount of HgCl2 and refrigerated until analysis
(16). Standard deviation on a known sample is (0.3‰. Our
rationale that spot samples are representative of reach
estimates is outlined in the SI.
Troll 9000EXP data loggers (In-Situ, Inc.) at the 1.3 and
41.7 km2 catchment sizes recorded temperature, pH, and
atmospheric pressure every 15 min, allowing the excess partial
pressure of carbon dioxide in the streamwater, EpCO2, to be
calculated (12).
Statistical modeling was carried out using Minitab V 14,
under a general linear modeling framework which includes
linear regression and analysis of covariance, incorporating
both continuous and categorical environmental variables.
Assumptions of normality and constant variance were tested.
Results and Discussion
During the dry summer, peatland evapotranspiration likely
lowered the water table, creating moisture deficits which
rendered precipitation ineffective in initiating a streamflow
response until November 2003 (Figure SI-S2). With anteced-
ent soil moisture levels now generally high, streamflow is
responsive to precipitation, generating event flow as rapid
hydrological pathways route water through and over the peaty
soils (17). We sampled two rising limbs (Figure SI-S3,
November 13, 2003; Figure 1, April 1 2004) and one falling
limb (Figure 1, June 24, 2003) of event flow. Summer 2004
was wetter, with generally higher flow conditions.
Figure 1 shows δ13CDIC, δ18ODO, and [DIC] most important
to our discussion. The full data set is in Figure SI-S3. The
range in δ13CDIC is large, 17‰ at 41.7 km2 and similarly large
at 1.3 km2 and 90 km2 (15.6 and 16.2‰ respectively).
Comparatively, maximum range in δ18ODO is small: 3.1‰ at
90 km2, and similar but >41.7km2 > 1.3 km2. During the 24
hour light-dark-light cycle (commencing at 12:00), δ13CDIC
becomes more 13C-depleted during darkness, then 13Cenriched with returning light. δ18ODO exhibits the opposite
pattern in time. Diel variation is prevalent at all catchment
sizes, and cycle amplitude is largest during the summer
months, e.g., July-October 2003.
The maximum range in [DIC] was 0.4 mmol L-1 (41.7
km2), and 0.3 mmol L-1 for the 1.3 and 90 km2 catchments,
respectively. [DIC] was highest in summer 2003. Except for
December 11 2003 and June 24 2004, [DIC] at 41.7 km2 > 90
km2 > 1.3 km2. Diel variation in [DIC] generally accompanies
diel cycling of δ13CDIC-δ18ODO, most apparent at 41.7 km2,
with maximum concentrations ca. 06:00-08:00.
What Causes Such Wide Range in Composition? For
measured field pH of 3.8-8.1, DIC will comprise varying
proportions of CO2(aq) and bicarbonate, HCO3-. The hydration
of CO2(aq) to HCO3- causes 7-10‰ 13C-enrichment, depending on temperature (18), a fractionation assumed reversible
as HCO3- dehydrates. Consequently, some δ13CDIC variation
will reflect interspecies isotopic fractionation as pH changes.
However, this mechanism cannot explain the field δ13CDIC
range (evidenced in the Supporting Information).
The hyperbolic relationship between δ13CDIC and [DIC] at
all catchment scales (Figure 2a) reflects mixing of two endmembers (19): a 13C-depleted, low-[DIC] component and a
13C-enriched, high-[DIC] component. As the former is
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FIGURE 2. (A) The relationship between δ13CDIC and mmL-1 [DIC] for all three catchments; (B) a schematic of the vector influence of physical
and biological processes on the initial DIC composition that arises from mixing of the low-flow and high-flow end members, LFEM and
HFEM, respectively. δ13CDIC and [DIC] of the LFEM and HFEM for the mixing-line shown here are -7.5 and 1.0, and -22 and 0.06‰ and
mmol L-1 C, respectively, the end-member compositions chosen for the 41.7 km2 catchment modeling (Figure 6).
FIGURE 3. The significant relationship between inverse of specific discharge and [DIC] for each nested catchment reveals that at high
flow [DIC] converges across stream orders, but at low flow the different catchments diverge in [DIC].
associated with low flow and the latter is associated with
high flow, these are hereafter termed low-flow and highflow end members.
Consider first the interaction of flow on [DIC]. Figure 3
documents significant linear relationships between inverse
specific discharge and [DIC] for all catchment sizes, i.e., as
discharge increases [DIC] decreases. With increased runoff,
increased export of soil-derived organic acids (e.g., on April
1 2004, at 1.3 km2, [DOC] increased from 0.0070 g C L-1 preevent to 0.0138 g C L-1 peak event) decreases stream pH to
3.8-4.2 during peak event discharge, (20). DIC is present as
CO2(aq), and degassing during turbulent flow or passively may
reduce concentrations close to atmosphere-equilibrated
values. Fluvial CO2(aq) concentration during event flow (Figure
1) surpasses atmosphere-equilibrated concentrations, 0.0130.027 mmol L-1 for 23 to 0 °C, respectively. Dependent on
levels of soil respiration and the extent to which this pool has
been previously flushed, for some events total soil-DIC export
may remain constant but dilution reduces concentration.
For the events sampled here, [DIC] decreases but total DIC
export increases and lower [DIC] is not simply dilution of the
existing pool.
During the dry 2003 summer, [DIC] increased as base
flow decreased (Figures 1, SI-S3). Discharge decreased at 1.3
km2 i.e., peatland seepage was reduced, and hence the relative
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contribution of groundwater increased. Highest [DIC] during
groundwater-dominated flow suggests groundwater [DIC]
is greater than [DIC] from shallow surface runoff. Thus fluvial
[DIC] increased as the groundwater component was less
diluted.
These interpretations are supported by δ13C. Consider
first the low-flow end-member where δ13CDIC ∼ -22‰ (e.g.,
June 24 2004 and the end of April 1 2004, Figure 1). The pH
decrease is insufficient to accommodate the depletion of
δ13CDIC (SI). Use of Gran alkalinity to delineate soil-derived
surface water versus deeper-soil and groundwater (20),
suggests that while the groundwater flux increases during
events, proportionally more flow originates from shallow soils
and peak flow is dominated by shallow soil-derived water.
Soil CO2 formed by respiration of C3 vegetation, (∼ -28‰,
ref 21), may mix with peatland CO2 produced during
anaerobic fermentation, (∼ -14 to 10‰, ref 22)) to render
δ13CDIC similar to event flow waters. Alternatively, soil-respired
CO2 may become 13C-enriched due to degassing (18).
Regardless, δ13CDIC supports the interpretation that the highflow end-member represents dominantly peatland-exported
inorganic carbon.
The low-flow end-member occurs when groundwater is
more prevalent. Groundwater δ13CDIC can be estimated from
where regression of δ13CDIC upon inverse concentration
FIGURE 4. The significant linear relationships between the inverse
of [DIC] and δ13CDIC allow δ13CDIC of groundwater to be estimated
from where the relationships intercept the y-axis (e.g., ref 18). This
is estimated to be -10.4, -7.5, and -6.1‰ for the 1.3, 41.7, and 90
km2 catchments, respectively.
intercepts the y-axis (e.g., ref 18), here estimated to be -10.4
to -6.1‰ (Figure 4). This is considerably more 13C-enriched
than some temperate watersheds (e.g., -17 ( 1.5‰, ref 18).
Carbonate rocks when weathered yield 13C-enriched DIC,
but are not present in Glen Dye. In silicate weathering,
organic-derived carbonic acid yields δ13CDIC similar to soil
respiration; carbonic acid produced by the dissolution of
atmospheric CO2 yields δ13CDIC more enriched, approaching
1.4‰ (e.g., ref 23). Thus, mass balance suggests that for such
13C-enrichment in groundwater, approximately 50% of DIC
is from atmospheric CO2 involved in weathering silicate
minerals.
Nested catchment sampling reveals the groundwater
influence on fluvial δ13CDIC: at 1.3 km2 where groundwater
input is less (20) and more 13C-depleted, low-flow δ13CDIC is
generally more 13C-depleted (Figure 1). Additionally, samples
collected on October 3 2003 are most 13C-enriched, but unlike
earlier in this dry period, they were not collected when the
river was CO2 under-saturated (samples from 41.7 km2 where
EpCO2 < 1 are circled, Figure 1, SI-S3), and draw-down of
atmospheric CO2 would be expected to drive δ13CDIC toward
∼ 0‰ (24). Rather, these enriched signatures may reflect the
most groundwater-dominated samples, subsequently enriched by photosynthesis.
Thus fluvial DIC primarily reflects mixing of compositionally distinct groundwater and soil-water pools whose
rapidly changing dominance quickly alters DIC composition.
For example, on April 1 2004 (Figure 1) over approximately
10 h, δ13CDIC in the two smallest catchments decreases by
8-12‰ as more soil-derived water constitutes runoff in
response to prolonged, heavy precipitation.
Considerable scatter in the data (Figure 2) indicates that
the end-members were not compositionally constant and/
or the pool DIC has been altered by physical or biological
processes. Otherwise the field data would fall on a mixing
line defined by the relative proportional differences of the
end-members. As end-member waters were not sampled we
cannot assess compositional homogeneity, but 24 hour
sampling confirms that both biological and physical process
alter the mixed source composition.
Diel variation in [DIC] and δ13CDIC (e.g., summer 2003,
May and July 2004) suggests photosynthesis and respiration
are reworking the fluvial DIC. Contemporaneous diel variation in δ18ODO confirms this. During winter low-flow, daylength is short and low-temperature regulates peaks in
biological activity. δ13CDIC is little reworked by photosynthesis
and dominance of respiration induces isotopic fractionation,
shifting δ13CDIC from the mixing line. Respiration-dominated
low flow is apparent from (i) low variance in δ13CDIC, δ18ODO
and [DIC], e.g., December 11 2003, February 7 2004, and (ii)
δ13CDIC and δ18ODO that tend toward the more isotopically
depleted and enriched end of their ranges, respectively. At
41.7 and 90 km2, generally the most 13C-depleted and 18Oenriched diel compositions are similar to the proposed
respiration-dominated signatures. At 1.3 km2, δ18ODO during
respiration-dominated periods is similar to maximum values
during diel variation, but δ13CDIC is more 13C-depleted.
Primary production in the source headwaters may have been
insufficient to cause 13C-enrichment. Alternatively, peatland
winter DIC export may be more 13C-depleted, e.g., through
reduced input of 13C-enriched CO2 associated with methanogenesis (22). These controls are not mutually exclusive.
The physical processes that alter DIC composition can be
biologically mediated. Photosynthetic activity may render
EpCO2 < 1, and thus through draw-down of atmospheric
CO2, cause 13C-enrichment, toward ∼0‰ (24) (Figure 1, SIS3). Calculation of EpCO2 alone may not reveal that δ13CDIC
has been influenced by atmospheric draw-down. If consumption is balanced by atmospheric CO2 draw-down, EpCO2
) 1, but part of the DIC pool may be atmosphere-derived
and move δ13CDIC from the mixing line.
Degassing of the DIC pool, proposed to be manifest by
13
C-enrichment (18) and reduction in [DIC], could cause
scatter around the mixing line, and is likely important given
EpCO2 is generally >1. δ13CDIC at 90 km2, when distinct from
41.7 km2, is generally more 13C-enriched. Similarly δ13CDIC at
41.7 km2 is more 13C-enriched than at 1.3 km2. [DIC] reduction
at 90 km2 cf. 41.7 km2 is consistent with CO2(aq) degassing.
Benthic respiration of DOM, or greater groundwater input,
appears sufficient to compensate for degassed loss as [DIC]
increases at 41.7 km2 from 1.3 km2.
The dynamic range in fluvial DIC composition arises as
follows. Mixing takes place between ground- and surfacewater sources, the relative proportion of each may vary.
Subsequently, competing physical and biological processes
maintain a dynamic equilibrium changing [DIC] and δ13CDIC
(and δ18ODO) depending on the strength of these interactions
(Figure 2b). These processes are hydrologically responsive.
For example, at high flow (i) δ13CDIC shows soil-derived waters
dominate; (ii) light penetration is lowered (as turbidity and/
or water color increase) and thus photosynthetic 13Cenrichment is inhibited, but degassing may be enhanced. As
δ13CDIC on April 1, 2004 trends toward soil-derived DIC
signatures as flow increases without a similar response in
[DIC], δ13CDIC may be more sensitive than [DIC] to hydrological change. As discharge falls after an event, biological
mediation of DIC begins, e.g., the rise in δ13CDIC at 41.7 km2
on June 24 2004 could be photosynthetically induced.
Similarly, DO appears responsive to flow. Diel δ18ODO
cycling during all periods of low flow is most pronounced in
the summer, likely due to higher respiration rates with
increased water temperatures (25) or greater periphyton
biomass. At high flow 18O-enrichment occurs (cf. the April
1, 2004 rising limb vs June 24, 2004 falling limb where δ18ODO
is returning to more-depleted values), which we attribute to
turbulent mixing with the atmosphere, and degassing and
displacement of oxygen-poor soil waters, where respiration
has caused 18O-enrichment.
Is There a Change in Carbon Cycling with Catchment
Size? In our study, all soils are C3-derived, so little difference
in soil-derived δ13CDIC is expected. Figure 4 suggests that the
relationship between δ13CDIC and [DIC] is the same for
catchment sizes 41.7 and 90 km2, but different to 1.3 km2.
The more 13C-depleted groundwater at 1.3 km2 suggests
greater DIC input from soil-derived organic acids to silicateweathering than at 41.7 and 90 km2. The shallower slope for
1.3 km2 suggests the low-flow end-member influences less
fluvial DIC composition. Similar slopes and intercepts for
41.7 and 90 km2 suggest similarity in DIC systematics. Formal
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FIGURE 5. A significant relationship exists between pH and δ13CDIC.
The 1.3 and 41.7 km2 catchments are identified, but the linear
relationship shown is for pooled data as the catchment specific
relationships are not significantly different. Data does not exist for
the 90 km2 catchment.
general linear model analysis, with [DIC] and catchment as
controlling variables in δ13CDIC, supports interpretation that
catchments are not all the same. However, scatter in the
data causes insufficient statistical power to identify which
intracatchment differences exist.
For individual sampling trips, during non-event flow, [DIC]
and δ13CDIC exhibit site-specific differences, but still respond
similarly to mediating processes. This is less apparent with
δ18ODO, although after the dry 2003 summer δ18ODO at 1.3
km2 is generally more 18O-enriched, perhaps reflecting more
respiration. During event flow, intercatchment differences
are reduced, and [DIC] and δ13CDIC trend toward soilrespiration composition. Homogeneity 24 h after peak flow
(June 24, 2004) suggests that DIC export in lower-order river
systems continues after peak flow, and may even lag behind
maximum discharge. This phenomenon, previously noted
with DOC export (26), is likely due to the delayed response
of deeper subsurface flow paths displacing hillslope groundwater, as surface and near-surface contributions to flow
decline once precipitation stops (20).
Fluvial DIC sampled in summer (which broadly equates
with base flow) at different catchment sizes in temperate
watersheds (∼ -11‰, ref 18) is more 13C-depleted than
comparable catchments here, ∼ -7‰, (Table SI-S2), likely
reflecting a greater soil-derived DIC contribution to groundwater. This comparison (Table SI-S2) suggests that as
catchment size increases, δ13CDIC increases. In South Fork
Eel river, midsummer 1998, 13C-enrichment is observed with
increasing catchment size, attributed to loss of CO2(aq) (18).
However, δ13CDIC of summer flow from Big Hole River in
Montana, 7200 km2 is ∼ -11.5 to -10 ‰ (13), more 13Cdepleted than comparable catchment sizes, ∼ -7 ‰ (18).
Clearly, size-related relationships may occur with δ13CDIC
during base flow, due to changing proportional input of
δ13CDIC homogeneous sources, or loss of CO2(aq). However, as
underlying geology changes the mineral-weathering derived
FIGURE 6. Continuous time series of pH (A), [DIC] (B), and δ13CDIC (C) for the 41.7 km2 catchment scale. pH, and thus δ13CDIC, data are missing
for 16 days, mid-July 2004. Mass balance allows end-member compositions (Figure 2A, Table SI-S3) to generate a profile for %C in discharge
from a given end-member, here low-flow (D).
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DIC signature (e.g., ref 23), or soil cover changes from C3- to
C4-derived soils, both groundwater and surface water δ13CDIC
will change over larger scales. Intra-, and possibly intercatchment differences will occur and scale-related responses
will be lost. Additionally primary production may respond
to significant channel-altering flow events, and thus scalerelated relationships may exhibit temporal variation due to
differences in fluvial recycling.
The dynamic DIC response to environmental influences
may render detecting a “catchment signature” impossible
when spot sampling is employed (commonly so). With
repeated sampling under the full range of environmental
conditions, cumulative data sets may allow the removal of
reworking, and define catchment-specific signatures. However, resource requirement, or field access logistics, may
render intensive sample collection prohibitive. Other approaches are required that both aid assessment of fluvial
DIC variability, and allow an understanding of compositional
controls. We suggest the following parameters may be useful.
Statistically significant relationships between [DIC] and
inverse specific discharge which allow [DIC] to be reconstructed may be key in up-scaling fluvial [DIC] systematics.
At high flow DIC export converges across stream orders, but
at low flow the different catchments diverge in their DIC
fluxes. The gradient of the slope steepens with increasing
catchment size (Figure 3), which suggests in larger rivers
[DIC] may be less sensitive to flow changes.
Continuously logged pH reveals that baseflow conditions
are dominated by circum-neutral groundwater. Diel cycling
of pH occurs, with greatest amplitude in low flow and during
long daylight. As flow increases, pH rapidly decreases but
returns to circum-neutral values as flow decreases (20). In
essence flow and process-related changes in δ13CDIC are
paralleled by pH changes, such that linear and highly
significant relationships exist between δ13CDIC and pH (Figure
5). Both 1.3 and 41.7 km2 relationships are statistically similar,
thus pooling the data provides a generic relationship where
pH describes 71% of the variation in δ13CDIC (Figure 5),
powerful in predicting δ13CDIC when unknown.
Continuous high-frequency monitoring reveals the “full
symphony of catchment hydrochemical behavior” (27). To
demonstrate this we have used the relationships with
continuously logged flow and pH to generate [DIC] and
δ13CDIC for the 41.7 km2 catchment for the hydrological year
2003-2004 (Figure 6a-c). From these profiles we can
apportion fluvial DIC into the % predominantly associated
with weathering (low-flow end member) (Figure 6d, SI).
Without δ13CDIC, we cannot ascertain that soil-derived DIC
dominates event flow, reduction in concentration could be
dilution of the groundwater DIC. Without [DIC], we cannot
delineate that δ13CDIC more 13C-enriched than soil-respiration
also occurs when the high-flow end-member contributes
more DIC. When both parameters are available, continuousprofiling offers greater insight to catchment carbon balance.
For example, from these continuous-profiles we estimate
that DIC export, generated during silicate-weathering by
atmospheric CO2-derived organic acids, is 19.9 ( 23% of total
202.17 kg DIC-C export at 41.7 km2 (SI). [DIC] of the low-flow
end-member is unknown, and for the above, it is estimated
to be 1 mmol L-1 C (SI). However, calculations of % export
are not particularly sensitive to this concentration: low-flow
end-member [DIC] estimated to be 0.5 mmol L-1 C changes
the % DIC to 24.4%. However, as the error on the concentration term is now proportionally greater, uncertainty in this
estimate increases to 56%. Thus while isolation of endmembers is not required to reveal catchment functioning,
to increase the value of the output it is beneficial to
characterize end-members.
That physical and biological processes shape DIC is clear,
but interpretations are rarely contextualized with the con-
sideration that composition changes within the same day.
Field programs should incorporate temporal controls, e.g.,
sites sampled contemporaneously, at the same time of day,
or environmental measurements, e.g., discharge, that allow
testing of variability between samples. Time of sampling
should be published. Nested catchment studies like this aid
upscaling process understanding gleaned in small experimental studies (28), but are, unfortunately, insufficiently
common in studies of the aquatic carbon cycle. To compensate, use of a geographic information system to describe
landscape controls (e.g., % hydrology of soil types), may prove
as incisive in understanding fluvial DIC loads as when applied
to other aspects of riverine chemistry (e.g., ref 28). However,
linking the study of fluvial DIC composition with continuously
recorded parameters generates detail that allows assessment
of whether the dynamic responses here are catchmentspecific or more generic. Ultimately defining other descriptors
allows reconstruction of “continuous” DIC profiles, with
which we can address key scientific question, such as whether
projected changes in global temperature and precipitation
(29) will influence fluvial export of inorganic carbon from
terrestrial stores.
Acknowledgments
S.W. is funded by a NERC Advanced Fellowship, NER/J/S/
2001/00793. The SUERC is funded by a consortium of Scottish
Universities. We thank Terry Donnelly, Andrew Tait, and
Johannes Barth for technical support; Stephanie Evers, Mark
Waldron, Liz Bingham, Sally Alexander, and Pauline Lang
for field assistance; four anonymous referees, Simon Drew,
and particularly Fin Stuart for comments on earlier versions
of the manuscript; Derek Fraser for providing discharge
records. We are grateful to the Fasque Estate, particularly
Archie Dykes, for site access and accommodation.
Supporting Information Available
This contains diagrammatic representation of the full field
data set, further detail on the field area, study period
hydrological conditions, detail of statistically significant
relationships, a discussion of the influence of intracarbonate
equilibria isotopic fractionation on the field data, a comparison with earlier nonisotopic study of inorganic carbon
cycling in the same field area and with others using paired
δ13CDIC-δ18ODO measurements in other areas, and detail on
the calculation and processing of the continuous profiles.
This material is available free of charge via the Internet at
http://pubs.acs.org.
Literature Cited
(1) Jones, R. I.; Grey, J.; Quarmby, C.; Sleep, D. Sources and fluxes
of inorganic carbon in a deep, oligotrophic lake (Loch Ness,
Scotland). Global Biogeochem. Cycles 2001, 15, 863-870.
(2) Smith, J. A.; Hodgson, D. A.; Bentley, M. J.; Verleyen, E.; Leng,
M. J.; Roberts, S. J. Limnology of two Antarctic epishelf lakes
and their potential to record periods of ice shelf loss. J.
Paleolimnol. 2006, 35, 373 -394.
(3) Itou, M.; Ono, T.; Noriki, S. Provenance of intermediate waters
in the western North Pacific deduced from thermodynamic
imprint on δ13C of DIC. J. Geophys. Res., [Oceans] 2003, 10, 3347.
(4) Cole, J. J.; Caraco, N. F.; Kling, G. W.; Krat, T. K. Carbon dioxide
supersaturation in the surface waters of lakes. Science 1994,
265, 1568-1570.
(5) Falkowski, P. G.; Raven, J. A. Aquatic Photosynthesis; Blackwell
Sciences: Malden, MA, 1997.
(6) Nagel, O. W.; Waldron, S.; Jones, H. G. An off-line implementation
of the stable isotope technique for measurements of alternative
respiratory pathway activities. Plant Physiol. 2001, 127, 12791286.
(7) Quay, P. D.; Wilbur, D. O.; Richey, J. E.; Devol, A. H. The 18O:16O
of dissolved oxygen in rivers and lakes in the Amazon Basin:
Determining the ratio of respiration to photosynthesis rates in
freshwaters. Limnol. Oceanogr. 1995, 40, 718-729.
VOL. 41, NO. 17, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
9
6161
(8) Jamieson, T. S.; Schiff, S. L.; Taylor, W. D. Implementation of
a new isotopic tool (18O/16O in dissolved O2) for the management
of oxygen in the Grand River, an impacted watershed in S.
Ontario. EOS Trans., AGU, 2004, 85 (17), Abstract B41B-04.
(9) Tobias, C. R.; Bohlke J. Diel variation of oxygen and inorganic
carbon in a high productivity, high alkalinity stream: biological
and geochemical controls. EOS Trans., AGU, 2004, 85 (47),
Abstract H41F-0344.
(10) Wang, X. F.; Veizer, J. Respiration-photosynthesis balance of
terrestrial aquatic ecosystems, Ottawa area, Canada. Geochim.
Cosmochim. Acta 2000, 64, 3775-3786.
(11) Barth, J. A. C.; Veizer, J. Carbon cycle in St. Lawrence aquatic
ecosystems at Cornwall (Ontario): seasonal and spatial variations. Chem. Geol. 1999, 159, 107-128.
(12) Maberly, S. C. Diel episodic and seasonal changes in pH and
concentrations of inorganic carbon in a productive lake. Fresh.
Biol. 1996, 35, 579-598.
(13) Parker, S. R.; Poulson, S. R.; Gammons, C. H.; Degrandpre, M.
D. Biogeochemical controls on diel cycling of stable isotopes
of dissolved O2 and dissolved inorganic carbon in the Big Hole
River, Montana. Environ. Sci. Technol. 2005, 39, 7134-7140.
(14) Soulsby, C.; Rodgers, P. J.; Petry, J.; Hannah, D. M.; Malcolm,
I. A.; Dunn, S. M. Using tracers to upscale flow path understanding in mesoscale mountainous catchments: two examples
from Scotland. J. Hydrol. 2004, 291, 174-196.
(15) Torres, M. E.; Mix, A. C.; Rugh, W. D. Precise δ13C analysis of
dissolved inorganic carbon in natural waters using automated
headspace sampling and continuous-flow mass spectrometry.
Limnol. Oceanogr. 2005, 3, 349-360.
(16) Barth, J. A. C.; Tait, A.; Bolshaw, K. Automated analyses of 18O/
16O ratios in dissolved oxygen from12-mL water samples. Limnol.
Oceanogr. 2004, 2, 5-41.
(17) Soulsby, C.; Rodgers, P.; Smart, R.; Dawson, J. J. C.; Dunn, S. A
tracer-based assessment of hydrological pathways at different
spatial scales in a mesoscale Scottish catchment. Hydrol. Process
2003, 17, 759-777.
(18) Finlay, J. C. Controls of streamwater dissolved inorganic carbon
dynamics in a forested watershed. Biogeochemistry 2003, 62,
231-252.
6162
9
ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 41, NO. 17, 2007
(19) Criss, R. E. Principles of Stable Isotope Distribution; Oxford
University Press: Oxford, 1999.
(20) Tetzlaff, D.; Waldron, S.; Brewer, M.; Soulsby, C. Assessing nested
hydrological and hydrochemical behaviour of a mesoscale
catchment using continuous tracer data. J. Hydrol. 2007, 336,
430-443.
(21) Cerling, T. E.; Solomon, D. K.; Quade, J.; Bowman, J. R. On the
isotopic composition of carbon in soil carbon-dioxide. Geochim
Cosmochim. Acta 1991, 55, 3403-3405.
(22) Waldron, S.; Hall, A. J.; Fallick, A. E. Enigmatic stable isotope
dynamics of deep peat methane. Global Biogeochem. Cycles
1999, 13, 93-100.
(23) Telmer, K; Veizer J. Carbon fluxes, pCO2 and substrate weathering
in a large northern river basin, Canada: carbon isotope
perspectives. Chem. Geol. 1999, 159, 61-86.
(24) Deuser, W. G.; Degens, E. T. Carbon isotope fraction in the
system CO2(gas)-CO2(aqueous)-HCO3-(aqueous). Nature 1967,
215, 1033-1035.
(25) del Giorgio, P. A.; Williams, P. J. le B. Respiration in Aquatic
Ecosystems; Oxford University Press Inc., New York, 2005.
(26) Worrall, F.; Burt, T. P.; Jaeban, R. Y.; Warburton, J.; Shedden,
R. Release of dissolved organic carbon from upland peat. Hydrol.
Process 2002, 16, 3487-3504.
(27) Kirchner, J. W.; Feng, X.; Neal, C; Robson, A. J. The fine structure
of water-quality dynamics: the (high-frequency) wave of the
future Hydrol. Process 2004, 18, 1353-1359 (29)
(28) Soulsby, C.; Tetzlaff, D.; Dunn, S. M.; Waldron, S. Scaling up
and out in runoff process understanding: insights gained from
nested experimental catchment studies. Hydrol. Process 2006,
20, 2461-2465.
(29) International Panel on Climate Change, Third Assessment
Report. Climate Change 2001: Synthesis Report. 2001, http://
www.ipcc.ch (accessed March 2007).
Received for review March 11, 2007. Revised manuscript
received June 8, 2007. Accepted June 20, 2007.
ES0706089