Stable Isotope Analysis RevealsLower-Order River DissolvedInorganic Carbon Pools Are HighlyDynamicS U S A N W A L D R O N , * , † , §

E . M A R I A N S C O T T , ‡ A N DC H R I S S O U L S B Y ⊥

Scottish Universities Environmental Research Centre, EastKilbride 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 considereda source of atmospheric CO2, thus understanding the behaviorof the dissolved inorganic carbon pool (DIC) is valuable.The carbon isotopic composition, δ13CDIC, and concentration,[DIC], of fluvial samples collected diurnally, over 14months, reveal the DIC pools to be dynamic in range(-22 to -4.9‰, 0.012 to 0.468 mmol L-1 C), respondingpredictably to environmental influences such as changinghydrologic conditions or increased levels of primaryproduction. δ18O of dissolved oxygen (DO) corroboratesthe δ13CDIC interpretation. A nested catchment samplingmatrix reveals that similar processes affect the DIC pool andthus δ13CDIC across catchment sizes. Not so with [DIC]:at high flow, the DIC export converges across catchmentsize, but at low flow catchments diverge in their DICload. Contextualizing δ13C with discharge reveals thatorganic soil-waters and groundwaters comprise end-member sources, which in varying proportions constitutethe fluvial DIC pool. Discharge and pH describe well [DIC]and δ13CDIC, allowing carbon to be apportioned to each end-member from continuous profiles, demonstrated here for thehydrological year 2003-2004. This approach is powerfulfor assessing whether the dynamic response exhibited hereis ubiquitous in other fluvial systems at the terrestrial-aquatic interface or in larger catchments.

IntroductionThe carbon isotopic composition of dissolved inorganiccarbon (δ13CDIC) traces the source of DIC and the bio-geochemical processes that amend pool composition. Forexample, δ13CDIC measurements have identified heterotrophicDIC 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 NorthPacific (3). Increasing focus on the carbon cycle enhances

the significance of direct measures of water body DICconcentration, [DIC]. For example, lakes and river systemsare usually saturated with respect to the atmosphericequilibrium concentration and thus predominantly a sourceof atmospheric CO2 (4).

Fluvial dissolved oxygen (DO) and DIC are linked viaphotosynthesis and respiration: 18O and 13C are discriminatedagainst, respectively, during DIC and DO consumption; theproduct CO2 and oxygen are 16O and 12C-enriched, respec-tively (5, 6). Thus it is advantageous to measure pairedδ13CDIC-δ18ODO to understand carbon cycling. Although notnew (e.g., ref 7), paired δ13CDIC-δ18ODO measurements arenot commonplace with studies (8, 9) yet published. Ad-ditionally, δ13CDIC-δ18ODO measurements generally representspot sampling (e.g., ref 10), yet the strength of their interactionis controlled by day-length and temperature, which impactsphotosynthesis and respiration, and additionally, gas-exchange and groundwater contributions.

DIC systematics in higher-order rivers (7, 11) and largelotic systems (1, 12) have been studied more extensively thanin lower-order rivers. Such studies rarely include pairedδ13CDIC-δ18ODO measurements, beneficial in revealing pro-ductivity-driven diel cycling of DIC (13). The Big Hole River(13), although of lower-order, drains 7200 km2 and base-flow irrigation withdrawal reduces the width (50 m atsampling) relative to flow (Parker, Personal Communication).Observations in this catchment size may not describe DICbehavior in the smaller upper-catchment drainage systemswhich interface terrestrial to aquatic carbon export. Thesetend to be hydrologically more responsive, and chemicallyless-well buffered. Rivers are conduits for terrestrial DICexport to oceans, but knowledge of whether pool compositionand reprocessing changes with catchment size is limited. Toconstrain what processes control fluvial DIC, and to assesswhether these change with catchment size, we measuredfluvial δ13CDIC-δ18ODO and [DIC] from three nested upper-catchments over 14 months and sampled throughout 12 dielcycles.

Materials and MethodsStudy Site and Sampling Strategy. Glen Dye in NE Scotland(56°56′27N, 2°36′00W) is a headwater subcatchment of theRiver Dee, a high-order river draining into the North Sea.Samples were collected at 1.3 km2 from Brocky Burn, asecond-order river system draining the hillslopes; at 41.7km2 at Charr gauging flume on the Water of Dye, and at 90km2 at the Bridge of Bogendreip, Water of Dye (Figure S1a,Supporting Information (SI)). Glen Dye is predominantlyupland in character, and the altitude ranges from 100-776m (Figure SI-S1a). The climate is cool, with mean annualprecipitation of 1130 mm of which <10% is snow. Waterbalance 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 byextensive peats (e5 m deep) and peaty podzols (<1 m) (FigureSI-S1c). In some places peat is eroded to the mineral interface.Incised catchment slopes have the most freely draininghumus iron podzols (<1 m deep); the main river valleybottoms generally have freely draining alluvial deposits.

Discharge at 1.3 km2 was measured using a flume andpressure transducer. The Scottish Environment ProtectionAgency 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 every5 h over a 24 hour period and 12 times during June 2003 to

* Corresponding author phone: 00 44 1413302413; fax: 00 441413304894; e-mail: Susan.Waldron@ges.gla.ac.uk.

† Scottish Universities Environmental Research Centre.‡ University of Glasgow.⊥ University of Aberdeen.§ Current address: Department of Geographical and Earth Sci-

ences, University of Glasgow, Glasgow G12 8QQ, United Kingdom.

Environ. Sci. Technol. 2007, 41, 6156-6162

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August 2004. The flow conditions at time of sampling aredetailed in Figure SI-S2, Table SI-S1).

Isotopic Analyses, Estimation of EpCO2, and StatisticalTreatment of Data. Samples for [DIC] (mmol L-1 C) andδ13CDIC were analyzed using a headspace analysis approach(e.g., ref 15). Underwater, 10 mL of sample was injected intoan acid-washed pre-evacuated exetainer containing 150 µLof degassed phosphoric acid. Sucking in of the syringe barrelduring sample transfer was used as a quality control measureto indicate the exetainers had retained vacuum and con-tamination from atmospheric CO2 was minimal. The shakenexetainer was stored upside-down with the liquid in contactwith the septa, thus minimizing headspace CO2 ingressionor egression and transported in this manner to the laboratoryto 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 (0.03mmol L-1 C.

DO samples were collected in 12 mL exetainers, poisonedwith a small amount of HgCl2 and refrigerated until analysis(16). Standard deviation on a known sample is (0.3‰. Ourrationale that spot samples are representative of reachestimates is outlined in the SI.

Troll 9000EXP data loggers (In-Situ, Inc.) at the 1.3 and41.7 km2 catchment sizes recorded temperature, pH, andatmospheric pressure every 15 min, allowing the excess partialpressure of carbon dioxide in the streamwater, EpCO2, to becalculated (12).

Statistical modeling was carried out using Minitab V 14,under a general linear modeling framework which includeslinear regression and analysis of covariance, incorporatingboth continuous and categorical environmental variables.Assumptions of normality and constant variance were tested.

Results and DiscussionDuring the dry summer, peatland evapotranspiration likelylowered the water table, creating moisture deficits whichrendered precipitation ineffective in initiating a streamflowresponse until November 2003 (Figure SI-S2). With anteced-

ent soil moisture levels now generally high, streamflow isresponsive to precipitation, generating event flow as rapidhydrological pathways route water through and over the peatysoils (17). We sampled two rising limbs (Figure SI-S3,November 13, 2003; Figure 1, April 1 2004) and one fallinglimb (Figure 1, June 24, 2003) of event flow. Summer 2004was wetter, with generally higher flow conditions.

Figure 1 shows δ13CDIC, δ18ODO, and [DIC] most importantto our discussion. The full data set is in Figure SI-S3. Therange in δ13CDIC is large, 17‰ at 41.7 km2 and similarly largeat 1.3 km2 and 90 km2 (15.6 and 16.2‰ respectively).Comparatively, maximum range in δ18ODO is small: 3.1‰ at90 km2, and similar but >41.7km2 > 1.3 km2. During the 24hour light-dark-light cycle (commencing at 12:00), δ13CDIC

becomes more 13C-depleted during darkness, then 13C-enriched with returning light. δ18ODO exhibits the oppositepattern in time. Diel variation is prevalent at all catchmentsizes, and cycle amplitude is largest during the summermonths, e.g., July-October 2003.

The maximum range in [DIC] was 0.4 mmol L-1 (41.7km2), and 0.3 mmol L-1 for the 1.3 and 90 km2 catchments,respectively. [DIC] was highest in summer 2003. Except forDecember 11 2003 and June 24 2004, [DIC] at 41.7 km2 > 90km2 > 1.3 km2. Diel variation in [DIC] generally accompaniesdiel 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? Formeasured field pH of 3.8-8.1, DIC will comprise varyingproportions of CO2(aq) and bicarbonate, HCO3

-. The hydrationof CO2(aq) to HCO3

- causes 7-10‰ 13C-enrichment, depend-ing on temperature (18), a fractionation assumed reversibleas HCO3

- dehydrates. Consequently, some δ13CDIC variationwill 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 end-members (19): a 13C-depleted, low-[DIC] component and a13C-enriched, high-[DIC] component. As the former is

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 thethree nested catchments are shown on each chart. Samples from 41.7 km2 when EpCO2 < 1 are circled. The full data set can be foundin the Supporting Information.

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associated with low flow and the latter is associated withhigh flow, these are hereafter termed low-flow and high-flow end members.

Consider first the interaction of flow on [DIC]. Figure 3documents significant linear relationships between inversespecific discharge and [DIC] for all catchment sizes, i.e., asdischarge increases [DIC] decreases. With increased runoff,increased export of soil-derived organic acids (e.g., on April1 2004, at 1.3 km2, [DOC] increased from 0.0070 g C L-1 pre-event to 0.0138 g C L-1 peak event) decreases stream pH to3.8-4.2 during peak event discharge, (20). DIC is present asCO2(aq), and degassing during turbulent flow or passively mayreduce concentrations close to atmosphere-equilibratedvalues. Fluvial CO2(aq) concentration during event flow (Figure1) surpasses atmosphere-equilibrated concentrations, 0.013-0.027 mmol L-1 for 23 to 0 °C, respectively. Dependent onlevels of soil respiration and the extent to which this pool hasbeen previously flushed, for some events total soil-DIC exportmay remain constant but dilution reduces concentration.For the events sampled here, [DIC] decreases but total DICexport increases and lower [DIC] is not simply dilution of theexisting pool.

During the dry 2003 summer, [DIC] increased as baseflow decreased (Figures 1, SI-S3). Discharge decreased at 1.3km2 i.e., peatland seepage was reduced, and hence the relative

contribution of groundwater increased. Highest [DIC] duringgroundwater-dominated flow suggests groundwater [DIC]is greater than [DIC] from shallow surface runoff. Thus fluvial[DIC] increased as the groundwater component was lessdiluted.

These interpretations are supported by δ13C. Considerfirst the low-flow end-member where δ13CDIC ∼ -22‰ (e.g.,June 24 2004 and the end of April 1 2004, Figure 1). The pHdecrease is insufficient to accommodate the depletion ofδ13CDIC (SI). Use of Gran alkalinity to delineate soil-derivedsurface water versus deeper-soil and groundwater (20),suggests that while the groundwater flux increases duringevents, proportionally more flow originates from shallow soilsand 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 duringanaerobic fermentation, (∼ -14 to 10‰, ref 22)) to renderδ13CDIC similar to event flow waters. Alternatively, soil-respiredCO2 may become 13C-enriched due to degassing (18).Regardless, δ13CDIC supports the interpretation that the high-flow end-member represents dominantly peatland-exportedinorganic carbon.

The low-flow end-member occurs when groundwater ismore prevalent. Groundwater δ13CDIC can be estimated fromwhere regression of δ13CDIC upon inverse concentration

FIGURE 2. (A) The relationship between δ13CDIC and mmL-1 [DIC] for all three catchments; (B) a schematic of the vector influence of physicaland biological processes on the initial DIC composition that arises from mixing of the low-flow and high-flow end members, LFEM andHFEM, 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‰ andmmol 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 highflow [DIC] converges across stream orders, but at low flow the different catchments diverge in [DIC].

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intercepts the y-axis (e.g., ref 18), here estimated to be -10.4to -6.1‰ (Figure 4). This is considerably more 13C-enrichedthan 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 soilrespiration; carbonic acid produced by the dissolution ofatmospheric CO2 yields δ13CDIC more enriched, approaching1.4‰ (e.g., ref 23). Thus, mass balance suggests that for such13C-enrichment in groundwater, approximately 50% of DICis from atmospheric CO2 involved in weathering silicateminerals.

Nested catchment sampling reveals the groundwaterinfluence on fluvial δ13CDIC: at 1.3 km2 where groundwaterinput is less (20) and more 13C-depleted, low-flow δ13CDIC isgenerally more 13C-depleted (Figure 1). Additionally, samplescollected on October 3 2003 are most 13C-enriched, but unlikeearlier in this dry period, they were not collected when theriver was CO2 under-saturated (samples from 41.7 km2 whereEpCO2 < 1 are circled, Figure 1, SI-S3), and draw-down ofatmospheric CO2 would be expected to drive δ13CDIC toward∼ 0‰ (24). Rather, these enriched signatures may reflect themost groundwater-dominated samples, subsequently en-riched by photosynthesis.

Thus fluvial DIC primarily reflects mixing of composi-tionally distinct groundwater and soil-water pools whoserapidly changing dominance quickly alters DIC composition.For example, on April 1 2004 (Figure 1) over approximately10 h, δ13CDIC in the two smallest catchments decreases by8-12‰ as more soil-derived water constitutes runoff inresponse to prolonged, heavy precipitation.

Considerable scatter in the data (Figure 2) indicates thatthe end-members were not compositionally constant and/or the pool DIC has been altered by physical or biologicalprocesses. Otherwise the field data would fall on a mixingline defined by the relative proportional differences of theend-members. As end-member waters were not sampled wecannot assess compositional homogeneity, but 24 hoursampling confirms that both biological and physical processalter the mixed source composition.

Diel variation in [DIC] and δ13CDIC (e.g., summer 2003,May and July 2004) suggests photosynthesis and respirationare reworking the fluvial DIC. Contemporaneous diel varia-tion in δ18ODO confirms this. During winter low-flow, day-length is short and low-temperature regulates peaks inbiological activity. δ13CDIC is little reworked by photosynthesisand dominance of respiration induces isotopic fractionation,shifting δ13CDIC from the mixing line. Respiration-dominatedlow 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 isotopicallydepleted and enriched end of their ranges, respectively. At41.7 and 90 km2, generally the most 13C-depleted and 18O-enriched diel compositions are similar to the proposedrespiration-dominated signatures. At 1.3 km2, δ18ODO duringrespiration-dominated periods is similar to maximum valuesduring diel variation, but δ13CDIC is more 13C-depleted.Primary production in the source headwaters may have beeninsufficient to cause 13C-enrichment. Alternatively, peatlandwinter DIC export may be more 13C-depleted, e.g., throughreduced input of 13C-enriched CO2 associated with metha-nogenesis (22). These controls are not mutually exclusive.

The physical processes that alter DIC composition can bebiologically mediated. Photosynthetic activity may renderEpCO2 < 1, and thus through draw-down of atmosphericCO2, cause 13C-enrichment, toward ∼0‰ (24) (Figure 1, SI-S3). Calculation of EpCO2 alone may not reveal that δ13CDIC

has been influenced by atmospheric draw-down. If con-sumption is balanced by atmospheric CO2 draw-down, EpCO2

) 1, but part of the DIC pool may be atmosphere-derivedand move δ13CDIC from the mixing line.

Degassing of the DIC pool, proposed to be manifest by13C-enrichment (18) and reduction in [DIC], could causescatter around the mixing line, and is likely important givenEpCO2 is generally >1. δ13CDIC at 90 km2, when distinct from41.7 km2, is generally more 13C-enriched. Similarly δ13CDIC at41.7 km2 is more 13C-enriched than at 1.3 km2. [DIC] reductionat 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 asfollows. Mixing takes place between ground- and surface-water sources, the relative proportion of each may vary.Subsequently, competing physical and biological processesmaintain 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 watersdominate; (ii) light penetration is lowered (as turbidity and/or water color increase) and thus photosynthetic 13C-enrichment is inhibited, but degassing may be enhanced. Asδ13CDIC on April 1, 2004 trends toward soil-derived DICsignatures as flow increases without a similar response in[DIC], δ13CDIC may be more sensitive than [DIC] to hydro-logical change. As discharge falls after an event, biologicalmediation 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 inthe summer, likely due to higher respiration rates withincreased water temperatures (25) or greater periphytonbiomass. At high flow 18O-enrichment occurs (cf. the April1, 2004 rising limb vs June 24, 2004 falling limb where δ18ODO

is returning to more-depleted values), which we attribute toturbulent mixing with the atmosphere, and degassing anddisplacement of oxygen-poor soil waters, where respirationhas caused 18O-enrichment.

Is There a Change in Carbon Cycling with CatchmentSize? In our study, all soils are C3-derived, so little differencein soil-derived δ13CDIC is expected. Figure 4 suggests that therelationship between δ13CDIC and [DIC] is the same forcatchment sizes 41.7 and 90 km2, but different to 1.3 km2.The more 13C-depleted groundwater at 1.3 km2 suggestsgreater DIC input from soil-derived organic acids to silicate-weathering than at 41.7 and 90 km2. The shallower slope for1.3 km2 suggests the low-flow end-member influences lessfluvial DIC composition. Similar slopes and intercepts for41.7 and 90 km2 suggest similarity in DIC systematics. Formal

FIGURE 4. The significant linear relationships between the inverseof [DIC] and δ13CDIC allow δ13CDIC of groundwater to be estimatedfrom where the relationships intercept the y-axis (e.g., ref 18). Thisis estimated to be -10.4, -7.5, and -6.1‰ for the 1.3, 41.7, and 90km2 catchments, respectively.

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general linear model analysis, with [DIC] and catchment ascontrolling variables in δ13CDIC, supports interpretation thatcatchments are not all the same. However, scatter in thedata causes insufficient statistical power to identify whichintracatchment 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 withδ18ODO, although after the dry 2003 summer δ18ODO at 1.3km2 is generally more 18O-enriched, perhaps reflecting morerespiration. During event flow, intercatchment differencesare reduced, and [DIC] and δ13CDIC trend toward soil-respiration composition. Homogeneity 24 h after peak flow(June 24, 2004) suggests that DIC export in lower-order riversystems continues after peak flow, and may even lag behindmaximum discharge. This phenomenon, previously notedwith DOC export (26), is likely due to the delayed responseof deeper subsurface flow paths displacing hillslope ground-water, as surface and near-surface contributions to flowdecline once precipitation stops (20).

Fluvial DIC sampled in summer (which broadly equateswith base flow) at different catchment sizes in temperatewatersheds (∼ -11‰, ref 18) is more 13C-depleted thancomparable catchments here, ∼ -7‰, (Table SI-S2), likelyreflecting a greater soil-derived DIC contribution to ground-water. This comparison (Table SI-S2) suggests that ascatchment size increases, δ13CDIC increases. In South ForkEel river, midsummer 1998, 13C-enrichment is observed withincreasing catchment size, attributed to loss of CO2(aq) (18).However, δ13CDIC of summer flow from Big Hole River inMontana, 7200 km2 is ∼ -11.5 to -10 ‰ (13), more 13C-depleted than comparable catchment sizes, ∼ -7 ‰ (18).Clearly, size-related relationships may occur with δ13CDIC

during base flow, due to changing proportional input ofδ13CDIC homogeneous sources, or loss of CO2(aq). However, asunderlying geology changes the mineral-weathering derived

FIGURE 5. A significant relationship exists between pH and δ13CDIC.The 1.3 and 41.7 km2 catchments are identified, but the linearrelationship shown is for pooled data as the catchment specificrelationships are not significantly different. Data does not exist forthe 90 km2 catchment.

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 missingfor 16 days, mid-July 2004. Mass balance allows end-member compositions (Figure 2A, Table SI-S3) to generate a profile for %C in dischargefrom a given end-member, here low-flow (D).

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DIC signature (e.g., ref 23), or soil cover changes from C3- toC4-derived soils, both groundwater and surface water δ13CDIC

will change over larger scales. Intra-, and possibly inter-catchment differences will occur and scale-related responseswill be lost. Additionally primary production may respondto significant channel-altering flow events, and thus scale-related relationships may exhibit temporal variation due todifferences in fluvial recycling.

The dynamic DIC response to environmental influencesmay render detecting a “catchment signature” impossiblewhen spot sampling is employed (commonly so). Withrepeated sampling under the full range of environmentalconditions, cumulative data sets may allow the removal ofreworking, and define catchment-specific signatures. How-ever, resource requirement, or field access logistics, mayrender intensive sample collection prohibitive. Other ap-proaches are required that both aid assessment of fluvialDIC variability, and allow an understanding of compositionalcontrols. We suggest the following parameters may be useful.

Statistically significant relationships between [DIC] andinverse specific discharge which allow [DIC] to be recon-structed may be key in up-scaling fluvial [DIC] systematics.At high flow DIC export converges across stream orders, butat low flow the different catchments diverge in their DICfluxes. The gradient of the slope steepens with increasingcatchment size (Figure 3), which suggests in larger rivers[DIC] may be less sensitive to flow changes.

Continuously logged pH reveals that baseflow conditionsare dominated by circum-neutral groundwater. Diel cyclingof pH occurs, with greatest amplitude in low flow and duringlong daylight. As flow increases, pH rapidly decreases butreturns to circum-neutral values as flow decreases (20). Inessence flow and process-related changes in δ13CDIC areparalleled by pH changes, such that linear and highlysignificant relationships exist between δ13CDIC and pH (Figure5). Both 1.3 and 41.7 km2 relationships are statistically similar,thus pooling the data provides a generic relationship wherepH describes 71% of the variation in δ13CDIC (Figure 5),powerful in predicting δ13CDIC when unknown.

Continuous high-frequency monitoring reveals the “fullsymphony of catchment hydrochemical behavior” (27). Todemonstrate this we have used the relationships withcontinuously logged flow and pH to generate [DIC] andδ13CDIC for the 41.7 km2 catchment for the hydrological year2003-2004 (Figure 6a-c). From these profiles we canapportion fluvial DIC into the % predominantly associatedwith weathering (low-flow end member) (Figure 6d, SI).Without δ13CDIC, we cannot ascertain that soil-derived DICdominates event flow, reduction in concentration could bedilution of the groundwater DIC. Without [DIC], we cannotdelineate that δ13CDIC more 13C-enriched than soil-respirationalso occurs when the high-flow end-member contributesmore DIC. When both parameters are available, continuous-profiling offers greater insight to catchment carbon balance.For example, from these continuous-profiles we estimatethat DIC export, generated during silicate-weathering byatmospheric CO2-derived organic acids, is 19.9 ( 23% of total202.17 kg DIC-C export at 41.7 km2 (SI). [DIC] of the low-flowend-member is unknown, and for the above, it is estimatedto be 1 mmol L-1 C (SI). However, calculations of % exportare not particularly sensitive to this concentration: low-flowend-member [DIC] estimated to be 0.5 mmol L-1 C changesthe % DIC to 24.4%. However, as the error on the concentra-tion term is now proportionally greater, uncertainty in thisestimate increases to 56%. Thus while isolation of end-members is not required to reveal catchment functioning,to increase the value of the output it is beneficial tocharacterize 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 allowtesting of variability between samples. Time of samplingshould be published. Nested catchment studies like this aidupscaling process understanding gleaned in small experi-mental studies (28), but are, unfortunately, insufficientlycommon in studies of the aquatic carbon cycle. To com-pensate, use of a geographic information system to describelandscape controls (e.g., % hydrology of soil types), may proveas incisive in understanding fluvial DIC loads as when appliedto other aspects of riverine chemistry (e.g., ref 28). However,linking the study of fluvial DIC composition with continuouslyrecorded parameters generates detail that allows assessmentof whether the dynamic responses here are catchment-specific or more generic. Ultimately defining other descriptorsallows reconstruction of “continuous” DIC profiles, withwhich we can address key scientific question, such as whetherprojected changes in global temperature and precipitation(29) will influence fluvial export of inorganic carbon fromterrestrial stores.

AcknowledgmentsS.W. is funded by a NERC Advanced Fellowship, NER/J/S/2001/00793. The SUERC is funded by a consortium of ScottishUniversities. We thank Terry Donnelly, Andrew Tait, andJohannes Barth for technical support; Stephanie Evers, MarkWaldron, Liz Bingham, Sally Alexander, and Pauline Langfor field assistance; four anonymous referees, Simon Drew,and particularly Fin Stuart for comments on earlier versionsof the manuscript; Derek Fraser for providing dischargerecords. We are grateful to the Fasque Estate, particularlyArchie Dykes, for site access and accommodation.

Supporting Information AvailableThis contains diagrammatic representation of the full fielddata set, further detail on the field area, study periodhydrological conditions, detail of statistically significantrelationships, a discussion of the influence of intracarbonateequilibria isotopic fractionation on the field data, a com-parison with earlier nonisotopic study of inorganic carboncycling in the same field area and with others using pairedδ13CDIC-δ18ODO measurements in other areas, and detail onthe calculation and processing of the continuous profiles.This material is available free of charge via the Internet athttp://pubs.acs.org.

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Received for review March 11, 2007. Revised manuscriptreceived June 8, 2007. Accepted June 20, 2007.

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