effect of catchment characteristics on aquatic carbon export from a boreal catchment and its...

Effect of catchment characteristics on aquatic carbonexport from a boreal catchment and its importance inregional carbon cyclingJ U S S I HUOTAR I * , HANNU NYKÄNEN † , MART IN FORS IUS ‡ and LAURI ARVOLA*

*Lammi Biological Station, University of Helsinki, Paajarventie 320, Lammi FI-16900, Finland, †Department of Biological and

Environmental Science, University of Jyvaskyla, P.O. Box 35, Jyvaskyla FI-40014, Finland, ‡Finnish Environment Institute, P.O.

Box 140, Helsinki FI-00251, Finland

Abstract

Inland waters transport and emit into the atmosphere large amounts of carbon (C), which originates from terrestrial

ecosystems. The effect of land cover and land-use practises on C export from terrestrial ecosystems to inland waters

is not fully understood, especially in heterogeneous landscapes under human influence. We sampled for dissolved C

species in five tributaries with well-determined subcatchments (total size 174.5 km2), as well as in various points of

two of the subcatchments draining to a boreal lake in southern Finland over a full year. Our aim was to find out how

land cover and land-use affect C export from the catchments, as well as CH4 and CO2 concentrations of the streams,

and if the origin of C in stream water can be determined from proxies for quality of dissolved organic matter (DOM).

We further estimated the gas evasion from stream surfaces and the role of aquatic fluxes in regional C cycling. The

export rate of C from the terrestrial system through an aquatic conduit was 19.3 g C m�2(catchment) yr�1, which cor-

responds to 19% of the estimated terrestrial net ecosystem exchange of the catchment. Most of the C load to the recipi-

ent lake consisted of dissolved organic carbon (DOC, 6.1 � 1.0 g C m�2 yr�1); the share of dissolved inorganic

carbon (DIC) was much smaller (1.0 � 0.2 g C m�2 yr�1). CO2 and CH4 emissions from stream and ditch surfaces

were 7.0 � 2.4 g C m�2 yr�1 and 0.1 � 0.04 g C m�2 yr�1, respectively, C emissions being thus equal with C load to

the lake. The proportion of peatland in the catchment and the drainage density of peatland increased DOC in streams,

whereas the proportion of agricultural land in the catchment decreased it. The opposite was true for DIC. Drained

peatlands were an important CH4 source for streams.

Keywords: boreal catchment, CH4, CO2, dissolved inorganic carbon, dissolved organic carbon, flux

Received 12 December 2012 and accepted 5 July 2013

Introduction

Carbon (C) transport from land to sea with en route

processing and degassing into the atmosphere has

recently been emphasized to be of central importance

in estimates for regional and global C cycling (Cole

et al., 2007; Battin et al., 2008; Aufdenkampe et al., 2011;

Butman & Raymond, 2011). The carbon dioxide (CO2)

emissions from inland waters, for example, have shown

to be in the range 1–50% of net ecosystem production

or C accumulation rates of the surrounding catchments

(Kling et al., 1991; Hanson et al., 2004; Jonsson et al.,

2007; Huotari et al., 2011; Ojala et al., 2011). When all

transported C species have been considered, terrestrial

C transport to streams and subsequent emissions to the

atmosphere have been shown to possibly reverse the

terrestrial CO2 sink of a temperate peatland to become

neutral or a source (Billett et al., 2004).

Northern soils store large quantities of C, however,

the susceptibility of C to be released due to changes in

land-use, as well as in hydrology and temperature as

climate changes, is uncertain and poses a potential

threat to further increase the concentrations of atmo-

spheric CO2 and CH4. Butman & Raymond (2011) have

highlighted the importance of the smallest streams in C

cycling due to their contribution to the out-gassing of

CO2. In C cycling, the role of CH4 emissions may be

small but due to its high radiative forcing (Forster et al.,

2007), freshwater CH4 emissions as CO2 equivalents

has been estimated to offset 25% of the terrestrial green-

house gas sink (Bastviken et al., 2011). Some previous C

budget studies in northern areas have incorporated sur-

face waters in larger watersheds and mostly in remote

regions with minimal human disturbance (Christensen

et al., 2007; Jonsson et al., 2007; Buffam et al., 2011; Stri-

egl et al., 2012), while less is known about aquatic

export of terrestrial C from heterogeneous boreal catch-

ments under human disturbance, including agriculture.

Human induced perturbations within the catchments

affect C export into aquatic systems and may also haveCorrespondence: Jussi Huotari, tel. +358 40 576 2675,

fax +358 91 91 40746, e-mail: [email protected]

© 2013 John Wiley & Sons Ltd 3607

Global Change Biology (2013) 19, 3607–3620, doi: 10.1111/gcb.12333

large implications in regional C cycling by changing the

terrestrial net ecosystem exchange (NEE). Contempo-

rary forestry practises with harvesting and site prepara-

tion initially enhances the C export followed by

effective C storing in fast growing stand biomass and

finally declining productivity in the maturing forests

(Ryan et al., 1997; Kolari et al., 2008; Schelker et al.,

2012). Peatland drainages for forestry purposes, most of

which are situated in Nordic countries and Russia

(Minkkinen et al., 2008), trigger the same kind of suc-

cession in C cycling and C export to aquatic systems

(Armentano & Menges, 1986; Minkkinen et al., 2002).

Clearing a forest or peatland for agriculture enhances

the export of C and reduces C accumulation in the soil

(Armentano & Menges, 1986). In the Mississippi River

catchment, for example, increase in agriculture over the

last century has enhanced inorganic C transport from

soils, which, however, may act as a CO2 sink due to

sequestration in carbonate weathering (Raymond et al.,

2008). Changes in land cover affect water retention in

the system, whether it is lost by evapotranspiration or

flushed through in near surface or ground water runoff,

subsequently affecting C escape rates (Mayorga, 2008).

As the quality of dissolved organic matter (DOM)

varies depending on the source, it serves as a tool to

estimate the origin of stream water C (Battin, 1998;

Helms et al., 2008) and may reveal the effect of human

disturbance on the C transport as well. The quality of

DOM can be estimated by absorption spectrum of the

water sample, which varies depending on the molecu-

lar weight and the degree of aromaticity of DOM (e.g.

Hernes et al., 2008). Knowing the source of C would

help to improve the assessments of the role of inland

waters in large scale estimates of C cycling (Cole et al.,

2007; Tranvik et al., 2009).

Our goal was to find out how heterogeneous land-

scapes, which include forests, peatlands (mostly

drained), agriculture and lakes, affect terrestrial C loss

as well as the CO2 and CH4 concentrations of streams

in a boreal catchment. We sampled the main tributaries

of Lake P€a€aj€arvi, southern Finland, for dissolved C spe-

cies as well as in several sites along two of the tributar-

ies with varied land cover/land-use types. Data over a

full year allows us to estimate the total dissolved C

export as well as the CH4 and CO2 evasion from

streams of the whole catchment. Furthermore, we dis-

cuss the importance of aquatic C fluxes in regional C

cycling including lakes in the region, of which CO2 and

CH4 emissions have recently been estimated (Kankaala

et al., 2013). The specific research questions we wanted

to answer were: (i) How does peatland and agricultural

land affect C export from the catchment, i.e. the lateral

transport and gas emissions from inland water sur-

faces? (ii) What is the role of the streams and lakes in

regional C budget within this well determined and rep-

resentative boreal catchment with heterogeneous land-

use?

Material and methods

Data were gathered from five main subcatchments of Lake

P€a€aj€arvi (61°04′N, 25°08′E; Fig. 1; Fig. S1 in colour) that

together make up 174.5 km2 and cover 83% of the whole

catchment area (210.1 km2). Two of the subcatchments are

rather small in area: 12 L€oytynoja (8.2 km2) and 13 Ko-

iransuolenoja (6.5 km2), two are larger 6 Mustajoki (79.3 km2)

and 14 Haarajoki (57.8 km2) and one is intermediate: 7 Luh-

danjoki (22.8 km2). There is a higher percentage of agricultural

land in 13 Koiransuolenoja and 7 Luhdanjoki subcatchments,

while the Mustajoki subcatchment has a higher proportion of

peatland relative to others (Table 1). Practically all peatlands

in the area are drained for forestry with only small areas of

undrained natural peatland remaining.

To better understand the effect of peatland and agricultural

land on stream water chemistry, two of the subcatchments

were sampled additionally at different locations along the

main stream channel: the Mustajoki subcatchment (sample

points 1–6) was sampled at six locations of which one (no. 5)

was a tributary to Mustajoki; the L€oytynoja subcatchment (9–

12), which originates from a groundwater spring, had four

sampling points, one of which is a tributary to L€oytynoja from

a periodically overflowing drained peatland (no. 11) (Fig. 1).

Currently, there are only small scale restocking of forests, no

large scale clearing for agriculture, and peatland drainages

were excavated mainly in 1960–1970s with some drainages

reopened in 1990–2000s. The outlet of Lake P€a€aj€arvi (8

P€a€aj€arvi) was sampled 3 km downstream from the lake. The

study area with the demarcated subcatchments as well as all

the sample points is shown in Fig. 1. Tables 1 and 2 give the

characteristics of the subcatchments. Definitions of subcatch-

ment areas as well as land-cover proportions used are based

on Topographic Database of National Land Survey of Finland

(2010) and analysis with ArcMap 10. The bedrock of the catch-

ment belongs to “the Proterozoic Svecokarelidic mountain

range and consists of mica gneisses, amphibolites, granites,

granodiorites and minor bodies of basic plutonic rocks” (Lai-

takari, 1980). Mean annual temperature and precipitation in

the area measured over the period of 1981–2010 are 4.2 °C and

645 mm, respectively (Pirinen et al., 2012), while our study

year was slightly warmer (5.7 °C) and wetter (694 mm) (May

2011–April 2012).

Weekly sampling began on 4 May 2011 in the five main trib-

utaries and the outlet stream, and ended on 30 May 2012. The

streams were sampled for pH, specific conductance, dissolved

organic carbon (DOC) concentration and absorbance measure-

ments as well as for dissolved CH4 and CO2 concentrations.

At the same time water temperature was recorded in situ. The

sampling for CO2 and CH4 was conducted every second week

in September and October and monthly from December to

March. We started additional sampling in Mustajoki and L€oyt-

ynoja subcatchments on 10 June 2011 and ended on 23 May

2012 with the same intensity except for that monthly sampling

© 2013 John Wiley & Sons Ltd, Global Change Biology, 19, 3607–3620

3608 J . HUOTARI et al.

continued from December until May. The main tributaries

were sampled during 1 day and additional sampling was con-

ducted during the next day. Altogether 57 samples were taken

from the main tributaries except for CH4 and CO2 (N = 38).

Additional points were sampled 26 times (N = 20 for gases)

except for sample points 11, because it dried out during sum-

mer, and 1, 5 and 11 because of ice cover during the winter.

Samples for DIC, CO2 and CH4 were taken into 60-ml poly-

propylene syringes closed with three-way stopcocks. Below

the stream surface triplicate 30 ml samples were drawn into

the syringes avoiding air bubbles. The samples were kept in

crushed ice until the measurements were made in the labora-

tory within 24 h. pH of the samples were lowered with 3.0 ml

of 1% HNO3 to transform all DIC to CO2. Headspace of 30 ml

N2 was then added into syringes followed by a gas chromato-

graphic determination of CO2 and CH4 concentrations of well-

equilibrated headspace at 20 °C as explained by Ojala et al.

(2011). CO2 concentration was calculated from DIC, pH and

temperature as described by Butler (1982).

The samples for pH (Thermo Scientific Orion 3-star pH

Benchtop) and specific conductance (YSI 3200) were mea-

sured in the laboratory. Duplicate DOC samples from fil-

trated water (Millex-HA 0.45 lm) were stored at �22 °C in

plastic vials until determinations. They were measured with

Pt-catalysed high-temperature combustion, using a Shimadzu

TOC-5000 total carbon analyser. Absorbance measurements

were conducted between 200 and 750 nm with 0.5 nm inter-

vals using a 0.01 m quartz cuvette (Shimadzu UV-1800) and

sample absorbance spectra were referenced to a blank

spectrum of MQ-water. For DOM quality proxies, we used

wavelength specific UV-absorbance at 254 nm (SUVA254) cal-

culated as the absorbance divided by DOC concentration,

which correlates with the aromaticity of the DOM and it is

inversely related to its biodegradability (Weishaar et al.,

2003; Wickland et al., 2012). We used the ratio of the absor-

bances at 254 and 365 nm (A254/365) for the proxy of molecu-

lar weight of DOM, which is negatively correlated with

molecular weight and biodegradability of DOM (�Agren et al.,

2008). We did not verify the molecular weight or biodegrad-

ability of DOM with further analyses and thus these

measures should be considered as suggestive.

Discharge (Q) data for 6 Mustajoki, 12 L€oytynoja and 14 Ha-

arajoki as well as for the outlet stream of Lake P€a€aj€arvi (no. 8)

were taken from a database of the Finnish Environment Insti-

tute (OIVA service on environment and geographic informa-

tion, 1 June 2012). Instantaneous values of Q based on our own

measurements of the cross-section area of the stream channel

and water velocity (MiniAir�2; Schiltknecht Messtechnik AG,

Gossau, Switzerland) for 13 Koiransuolenoja were plotted

against the respective daily Q values of Mustajoki, Haarajoki

Fig. 1 Lake P€a€aj€arvi and the studied subcatchments. Numbered circles represent the sample points of which catchment characteristics

are given in Table 1 and stream water characteristics given in Table 2.


AQUATIC C EXPORT FROM A BOREAL CATCHMENT 3609

and L€oytynoja and the best attained regression was used to

produce a continuous Q time series. The daily Q of Haarajoki

best explained the variation of the measured instantaneous

Q of Koiransuolenoja and the form of the regression was a

second-order polynomial function (r2 = 0.822, N = 47). For

the four subcatchments of the tributaries, we had continuous

discharge data which covered 72.2% of the whole catchment

area of Lake P€a€aj€arvi. For 7 Luhdanjoki we do not have data

on Q. Flow velocity for sample points 1–5 and 9–11 were mea-

sured at every sampling occasion and for other sample points

it was calculated from Q and the measured cross-section area

of the stream channel.

Table 2 Stream water characteristics (mean � SD) measured at the sample points shown in Fig. 1

t, °C pH DIC, g m�3

Specific

conductance,

lS cm�1 (25 °C) Total N, mg m�3 Total P, mg m�3

1 8.4 � 7.0 5.5 � 0.4 2.5 � 1.0 36 � 4.4 ND ND

2 5.6 � 5.7 6.2 � 0.6 2.6 � 1.0 57 � 5.1 ND ND

3 5.9 � 6.1 6.3 � 0.6 2.7 � 1.1 65 � 6.2 ND ND

4 6.2 � 6.3 6.4 � 0.5 3.1 � 1.4 71 � 8.5 ND ND

5 7.1 � 5.8 6.7 � 0.4 4.0 � 1.1 105 � 17 ND ND

6 Mustajoki 7.0 � 6.6 6.6 � 0.3 3.8 � 1.7 91 � 10 1610 � 800 30 � 5

7 Luhdanjoki 6.8 � 5.9 7.1 � 0.3 7.8 � 1.4 156 � 18 3710 � 1930 35 � 15

8 P€a€aj€arvi 8.9 � 8.3 7.1 � 0.1 4.0 � 0.4 94 � 2.8 1400 � 180 13 � 4

9 5.4 � 2.2 6.6 � 0.2 4.3 � 0.3 90 � 6.9 ND ND

10 5.7 � 3.1 6.7 � 0.2 4.5 � 0.4 105 � 7.1 ND ND

11 7.4 � 5.5 3.9 � 0.3 5.0 � 4.1 73 � 29 ND ND

12 L€oytynoja 6.1 � 4.0 6.9 � 0.3 3.8 � 1.6 98 � 8.8 1120 � 400 20 � 8

13 Koiransuolenoja 7.5 � 6.5 7.2 � 0.2 6.1 � 1.2 214 � 16 3240 � 1850 40 � 89

14 Haarajoki 7.6 � 6.6 6.6 � 0.2 5.2 � 1.8 95 � 17 1360 � 890 35 � 12

ND, not determined.

Table 1 Characteristics of the studied subcatchments. Most important mineral soil and peat types of the subcatchments are

according to Quaternary deposits 1 : 20 000 of Geological Survey of Finland (2008)

Forest% Peatland% Agriculture% Lake%

Total

Area,

km2

Discharge,

m3 s�1

Ditch m/

Peatland ha Mineral soil Peat type

1 83.5 13.9 0 2.5 5.1 – 273

2 70.1 28.3 0.8 0.8 20.8 – 262

3 57.6 26.7 2.7 1.1 40.9 – 255

4 67.6 25.4 6.1 1.0 45.5 – 254

5 63.0 15.6 21.1 0.3 21.5 – 276

6 Mustajoki 65.0 21.3 13.1 0.7 79.3 0.5 255 Moraine,

fine sand

Sedge

peat 68%

7 Luhdanjoki 50.4 12.9 35.7 1.1 22.8 – 191 Silt, moraine Sedge

peat 77%

8 P€a€aj€arvi 62.5 13.5 16.2 7.8 231.7 1.9 ND

9 87.4 3.3 9.3 0 1.2 – 66

10 76.8 2.7 20.5 0 2.1 – 131

11 60.6 37.8 1.7 0 2.8 – 254

12 L€oytynoja 70.4 16.3 13.4 0 8.2 0.07 243 Sand, fine

sand, gravel

Sphagnum

peat 66%

13 Koiransuolenoja 67.4 4.7 27.9 0.01 6.5 0.07 222 Fine sand,

moraine

Sedge

peat 100%

14 Haarajoki 69.8 13.1 11.6 5.4 57.8 0.7 240 Moraine,

fine sand,

silt

Sedge

peat 76%

ND, not determined.



C export was calculated from discharge and concentration

data using the Load Estimator (LOADEST) program (Runkel

et al., 2004). CH4 and CO2 exchange between stream water and

the atmosphere was calculated as a product of gas exchange

coefficient and the gas concentration difference between the

surface water and the equilibrium concentration. The gas

exchange coefficient at 20 °C (k600) was calculated according to

the equation by Raymond et al. (2012), where the empirically

determined k600 was approximated from the slope of the

stream segment (S) and the flow velocity (V, m s�1), i.e. k600(m d�1) = S 9 V 9 2841.6 + 2.03. The gas exchange (Fc) was

then calculated as Fc = k (Caq-Ceq), where Caq and Ceq are gas

concentrations of the surface water and that which the surface

water would have if it was in equilibriumwith the atmosphere,

respectively. Gas transfer coefficient was calculated from k600as k = k600 (Sc/600)�0.5 using gas specific Schmidt numbers

(Sc) taken from J€ahne et al. (1987). To attain area specific

annual efflux rates for streams with daily V values we assumed

linear change in gas concentrations and integrated the attained

daily exchange rates over the year, whereas for streams with

sporadic V data we calculated monthly average efflux rates

and multiplied them with the respective number of open water

days in a month and further summed them up. No gas efflux

was assumed during ice cover. The attained efflux rates were

grouped according to the stream width classes used in the

Topographic Database of National Land Survey of Finland and

based on field determination, i.e. stream width <2 m, 2–5 m

and >5 m. N for efflux estimates of each class were 1, 9 and 2,

respectively. Stream surface areas were estimated by assuming

mean widths of 0.5 m and 3.5 m for classes of <2 m and 2–

5 m, respectively, while the stream areas for class >5 m were

given in the database, and multiplying the mean widths by

lengths of the streams of the respective width classes. Effluxes

were extrapolated over the whole stream surface area of the

catchment assuming attained stream width specific evasion

rates and multiplying by the respective surface area of the

stream width classes. For the estimate of the CH4 and CO2

fluxes from all water surfaces of the study area, we adopted

the areal gas flux estimates from Kankaala et al. (2013), esti-

mated for different sized lakes especially for this area.

Possible relationships between measured values were tested

with correlation analysis for each sampling point individually.

We calculated monthly averages, which were further averaged

to attain a single yearly average for all variables. These num-

bers were analysed against land cover information. In addi-

tional sampling points variables had only a single value

during winter months that represented the respective month.

If some point could not be sampled each month due to drought

or ice cover, we did not use any gap filling to attain the

monthly value, except for gas effluxes which were assumed as

zero, but only months with measured information were used

for yearly averages. All variables were log10-transformed

prior to analysis. We used Spearman’s correlation because all

the variables were not normally distributed (Shapiro–Wilk,

P < 0.05). All analyses were performed with PASW Statistics

20 (IBM Corp., Armonk, NY, USA). Uncertainties of the

estimated loads and fluxes as well as the choice of the gas

exchange model are discussed in Supporting Information.

Results

Time series for load estimates and dissolved C concen-

trations are shown in Figs S2–11.

Stream discharge

Discharge patterns of the streams followed each other

and only the discharge of the regulated outlet stream (8

P€a€aj€arvi) diverged from the other streams (Fig. 2). The

discharge was highest in late April at the time of snow

melt, and the second highest peak was found in late

December. Smaller peaks were recorded in November,

September and June. Concurrent discharge peaks con-

firmed the uniform climate of the study area. Winter

base flow was higher than summer base flow except in

12 L€oytynoja.

CH4 and CO2 concentrations and fluxes

Gas concentrations were always above atmospheric

equilibrium (Fig. 3a and b). CH4 concentrations were

highest in the summer and in September. The highest

concentrations in general were in 8 P€a€aj€arvi and 14

Haarajoki, i.e. 9.3 � 7.6 (mean � SD; range 1.6–27.7)and 7.8 � 4.9 (1.5–19.4) mg C m�3, respectively, but

there was an exceptionally high CH4 concentration of

Fig. 2 Discharge (mm d�1) of the studied tributaries draining

to Lake P€a€aj€arvi and of its outlet stream.



232 mg C m�3 in 6 Mustajoki in early August (Fig. 3a).

CH4 concentrations were low during the winter and

they slightly increased in late winter or early spring

except in 7 Luhdanjoki and in 12 L€oytynoja, of which

concentration remained relatively low all the time, i.e.

1.3 � 0.5 (0.6–2.8) mg C m�3. CH4 concentration corre-

lated negatively with Q in 6 Mustajoki, 8 P€a€aj€arvi and

14 Haarajoki (Table 3).

CO2 concentration was close to equilibrium

(<2 9 equilibrium) only twice in 7 Luhdanjoki in June

and once in 13 Koiransuolenoja in July (Fig. 3b). In 6

Mustajoki and 14 Haarajoki there was a clear two-

peaked pattern with the first peak occurring in late

summer–autumn with the highest concentration in

Haarajoki of 6.3 g C m�3, and a second peak in the

winter. The winter peak was distinct also in the other

streams except in 8 P€a€aj€arvi, which had rather stable

CO2 concentration throughout the study, i.e. 0.8 � 0.2

(0.4–1.3) g C m�3. CO2 correlated with Q in 12 L€oyt-

ynoja and 13 Koiransuolenoja (Table 3).

Within theMustajoki subcatchment (1–6) CH4 concen-

trations were almost constantly highest in its topmost

sample point 1 (Fig. 3a), which peaked in late summer–early autumn. CH4 concentration in general decreased

downstream, but there was a CH4 source to the stream

between the sample points 3 and 4, in an area with peat-

land, agriculture and forest cover of 13%, 36% and 51%,

respectively. As with CH4, the lowest CO2 concentra-

tions were often measured in sample point 3 after which

the concentrations increased, i.e. 4.0 � 1.3 (2.7–8.2) mg

C m�3 as CH4 and 1.2 � 0.7 (0.6–3.4) g C m�3 as CO2

vs. 5.8 � 3.0 (2.0–11.2) mg C m�3 and 1.4 � 0.7 (0.8–3.8) g C m�3 in sample points 3 and 4, respectively.

In the L€oytynoja subcatchment the effect of the

groundwater spring was clear in gas concentrations.

The uppermost sample point (no. 9) always had low

CH4 concentrations, i.e. 0.6 � 0.3 (0.3–1.6) mg C m�3,

as it is situated 560 m downstream from the spring and

with only minor effects from small areas of peatland

and agriculture. The pattern in both gases between the

sample points 9 and 10 was similar and although the

CO2 concentrations were always almost identical, the

area between the sample points (distance ca. 800 m)

was a clear source of CH4 (Fig. 3a). The area (0.9 km2)

has peatland, agriculture and forest cover of 2%, 37%

and 61%, respectively. Sample point 11, discharging the

drained peatland to L€oytynoja showed high concentra-

tions of both CH4 and CO2 in the summer but its influ-

ence on gas concentrations had already disappeared at

the sample point 12. CO2 concentration decreased along

the 3.6 km route from sample point 9 to 12 L€oytynoja,

whereas CH4 increased (Fig. 3a and b), i.e. more CH4 was

produced to the stream water en route than was evaded.

Areal effluxes of CH4 were highest in the smallest

stream width class reflecting high CH4 concentration

from drained peatlands, whereas the highest areal CO2

emissions occurred in the stream width class of 2–5 m

(Table 4). This was due to high gas transfer velocity

(k600) of the width class, i.e. 7.7 � 5.4 m d�1, compared

with that of 1.3 m d�1 of the smallest width class and

2.3 � 0.8 m d�1 of the width class of >5 m. The surface

area of the smallest width class was almost double that

of class 2–5 m, resulting in an order of magnitude

higher CH4 emission and 67% higher CO2 emission. C

gas emissions from streams were 65% higher than that

of lakes and ponds (Table 4).

DOC concentration and DOM quality

Stream discharge and DOC concentrations were posi-

tively correlated (Table 3). The highest concentrations

(a)

(b)

(c)

Fig. 3 CH4 concentration (mg C m�3) (a), CO2 concentration (g

C m�3) (b), and DOC (g C m�3) (c) for each sample points

shown in Fig. 1. Dashed lines represent the atmospheric equilib-

rium concentration of CH4 (a) and CO2 (b) at 20 °C.



were recorded in November–December while the

peak during the highest Q in April–May was slightly

lower. The lowest DOC concentrations occurred in

August–September and February–March. All of the

main tributaries had a similar pattern in DOC,

whereas outlet stream 8 P€a€aj€arvi had a rather constant

DOC concentration throughout the study (range 8.9–13.5 g m�3). The range in DOC was quite large in all

other sample points and e.g. in 6 Mustajoki and 12

L€oytynoja the concentrations fluctuated between 6.3–34.5 g m�3 and 2.7–26.9 g m�3, respectively (Fig. 3c).

In the Mustajoki subcatchment (1–6), DOC concen-

tration was the most stable, i.e.15.5 � 3.1 (11.9–22.5) g m�3 in sample point 1. DOC concentrations

correlated with Q and the correlations were much

stronger downstream, i.e. concentrations were higher

during high discharge and lower during low discharge

conditions than in the uppermost sample point (no. 1).

However, on average DOC concentration increased

downstream, although in the late winter–spring the

main-stem DOC concentration was diluted by the

waters from tributary (no. 5).

In the L€oytynoja subcatchment (9–12) DOC concen-

tration did not correlate with Q in sample point 9, and

DOC was low (<5 g m�3) all the time in sample points

9 and 10, closest to the spring. The only exception was

the snow melt peak when the DOC concentrations rose

close to 10 g m�3. DOC concentration in sample point

11 varied between 33 and 108 g m�3 and was lowest

during snow melt and highest in September right after

the summer drought. DOC concentration was clearly

higher in sample point 12 than in 9 and 10 except dur-

ing summer drought and in midwinter when sample

point 11 was frozen solid, implying that there was no

stream connection between the peatland area (no. 11)

and the 12 L€oytynoja stream.

Also dissolved organic matter (DOM) quality seemed

to be related to discharge. However, the relationship

varied between the streams, i.e. there was a negative

correlation between Q and aromaticity of DOM in 6

Mustajoki and 13 Koiransuolenoja, while in other

streams the correlation was positive (Table 3). Since

DOC positively correlated with Q in all streams, it indi-

cated that 6 Mustajoki and 13 Koiransuolenoja received

a large amount of less aromatic DOM during high flow

compared with low flow, while in the other streams the

DOM during the high flow was probably more aro-

matic than during low flow. However, there was no

connection between changes in SUVA254 and DOC in

13 Koiransuolenoja, but we found SUVA254 on average

to decrease with increasing DOC consistently in sample

points most influenced by peatlands (>15%), except in

12 L€oytynoja (16.3%), which is groundwater influenced

and where SUVA254 increased together with DOC.

SUVA254 increased together with DOC also in sample

points 9 and 10, as well as in 7 Luhdanjoki. Proxy for

Table 3 Spearman’s correlation coefficients and p-values (2-tailed) for stream log10-transformed discharge (log Q) and log10-trans-

formed DOC, SUVA254, A254/365, CH4 and CO2

6 Mustajoki 8 P€a€aj€arvi 12 L€oytynoja 13 Koiransuolenoja 14 Haarajoki

DOC

r 0.789 0.437 0.813 0.592 0.673

P 0.000 0.001 0.000 0.000 0.000

N 57 57 57 54 54

SUVA254

r �0.663 0.347 0.619 �0.503 0.379

P 0.000 0.009 0.000 0.000 0.005

N 56 56 56 53 53

A254/365

r 0.848 �0.579 0.071 0.847 0.194

P 0.000 0.000 0.605 0.000 0.163

N 56 56 56 53 53

CH4

r �0.791 �0.922 0.003 �0.049 �0.836

P 0.000 0.000 0.984 0.779 0.000

N 38 38 38 35 35

CO2

r 0.001 �0.163 0.582 0.826 �0.175

P 0.994 0.329 0.000 0.000 0.319

N 38 38 38 35 35

Statistically significant correlations are highlighted by italics.



molecular weight of DOM was negatively correlated

with Q in 6 Mustajoki whereas the correlation was posi-

tive in 8 P€a€aj€arvi (Table 3). When monthly averages of

SUVA254 and A254/365 were plotted against each other,

streams formed distinct but slightly overlapping

groups implying the most biodegradable DOM in the

outlet stream of Lake P€a€aj€arvi while DOM from Mustaj-

oki catchment with 21% of peatland coverage appar-

ently had the lowest biodegradability (Fig. 4).

DOM quality was rather stable within the Mustajoki

subcatchment with the aromaticity of DOM slightly

decreasing along the water course (Fig. 5). Instead, in

the L€oytynoja subcatchment DOM quality proxies var-

ied a lot and reflected the influence of the groundwater,

as well as of the drained peatland into stream water

DOM, as aromaticity of DOM was always much lower

in sample points 9 and 10 than in 12 (Fig. 5a). This was

even during the drought and the midwinter when the

connection of the drained peatland through the sample

point 11 to the L€oytynoja stream was ceased based on

the DOC data. The variation of DOM quality was great-

est close to the spring (sample point 9) and lowest in

the peatland site (sample point 11) (Fig. 5). The rela-

tionship between the proxy for molecular weight and

DOC in sample point 11 diverged that from other sites

with moderate peatland coverage possibly implying

differences due to sphagnum peat when other sites

consisted mainly of sedge peat (Table 1).

Land-cover effect

Peatland proportion correlated with DOC concentra-

tion and the quality of DOM of the streams (Table 5).

Moreover, the extent of which the peatlands were

drained within the catchment, measured as ditch length

per peatland area, was a good predictor of the DOM

quality and it was related to DOC concentrations as

well (Table 5). Peatland proportion and drainage den-

Table

4W

ater

surfaceareasan

dsp

ecificeffluxes.Areal

CH

4an

dCO

2fluxes

forlakes

aread

optedfrom

Kan

kaa

laet

al.(20

13)

Streams/

ditch

esLak

es

Totalarea

or

flux(km

2ortC

yr�

1)

<2m

2–5m

>5m

Total

(t)

<0.01

km

2

0.01–0.1

km

2

0.1–1

km

2

1–10

km

2

>10

km

2Total(t)

Stream

length

(m)/N

lakes

9917

0475

143

ND

3321

81

1

Areaha

49.6

26.3

8.7

8.5

72.2

174.5

199.7

1348

.818

.8

CO

2flux

(gC

m�2yr�

1)

1710

1929

849

159

7761

4146

CH

4flux

(gC

m�2yr�

1)

40.1

7.17

4.9

2.96

1.11

0.33

0.25

0.11

TotalCO

2flux(kgC

yr�

1)

8479

0750

7297

7348

514

28.7

1350

155

613

1064

4281

897

6204

5287

7.9

2306

.6

TotalCH

4flux(kgC

yr�

1)

1988

418

85.7

424.0

22.2

251.3

801.7

575.8

499.4

1483

.73.6

25.8

ND,notdetermined

.

Fig. 4 Monthly means of A254/365 vs. SUVA254 [l (mg C)�1 m�1]

for the five main tributaries of Lake P€a€aj€arvi and its outlet

stream.



sity both correlated with CH4 concentration, although

the relationship with peatland proportion and CH4 was

only close to significant (P = 0.051). Agricultural land

proportion positively correlated with pH and specific

conductance as expected, and it positively correlated

with DIC as well. The correlation of agricultural land

proportion with CH4 was negative, although there was

an indication of a summertime source of CH4 from agri-

cultural land in sample points 4 and 10. However, their

CH4 concentrations correlated differently with Q, i.e.

negatively in 4 and positively in 10. DOC/DIC ratio

was highly dependent on peatland proportion in the

catchment, also the ratio decreased together with a pro-

portion of agricultural land. However, DOC/DIC ratio

was below unity only due to high groundwater

influence in sample points 9 and 10.

Dissolved C load to Lake P€a€aj€arvi and regional CH4 andCO2 effluxes

The load of dissolved carbon, including DOC, DIC and

CH4 to Lake P€a€aj€arvi from the four main subcatchments

with continuous Q records and covering 72.2% of the

catchment of P€a€aj€arvi summed up to 1050 � 168

t C yr�1. Assuming the same load per area from the

whole catchment, the total load estimate is 1455 � 233 t

C yr�1 [7.1 � 1.1 g C m�2(catchment) yr�1]. DOC

dominated the load at 86.5% and DIC made up practi-

(a) (b)

Fig. 5 SUVA254 [l (mg C)�1 m�1] (a), and A254/365 (b) for each sample points shown in Fig. 1.

Table 5 Spearman’s correlation coefficients between log10-transformed land cover proportions and measured log10-transformed

variables

DOC SUVA254 A254/365 CO2 CH4 DIC Cond pH

Peatland%

r 0.873 0.736 �0.754 �0.055 0.530 �0.556 �0.640 �0.670

P 0.000 0.003 0.002 0.852 0.051 0.039 0.014 0.009

N 14 14 14 14 14 14 14 14

Forest%

r �0.367 0.024 �0.029 0.226 �0.327 �0.424 �0.323 �0.244

P 0.197 0.935 0.923 0.436 0.253 0.131 0.260 0.401

N 14 14 14 14 14 14 14 14

Agriculture%

r �0.609 �0.591 0.371 �0.420 �0.530 0.675 0.952 0.925

P 0.021 0.026 0.191 0.135 0.051 0.008 0.000 0.000

N 14 14 14 14 14 14 14 14

Lake%

r �0.082 �0.242 0.422 0.240 0.358 0.000 �0.182 �0.067

P 0.780 0.404 0.133 0.409 0.209 1.000 0.533 0.821

N 14 14 14 14 14 14 14 14

Drainage density

r 0.692 0.918 �0.692 �0.143 0.577 �0.670 �0.560 �0.538

P 0.009 0.000 0.009 0.642 0.039 0.012 0.046 0.058

N 13 13 13 13 13 13 13 13

Statistically significant correlations are highlighted by italics.



cally the entire remainder 13.5%. CH4 load in terms of

C was negligible (0.19 � 0.03 t C yr�1, 0.01%).

Total CO2 and CH4 evasion from streams to the

atmosphere in the catchment was estimated at

1429 � 586 and 22 � 9.8 t C yr�1, respectively

(Table 4). Including both CH4 and CO2 effluxes of

all the water surfaces in the whole study area the ef-

fluxes summed up to 2332 t C yr�1. This is 60%

higher than dissolved C transported to lake P€a€aj€arvi

and together make up to 3787 t C yr�1, i.e. 18.5 g

C m�2 of the catchment, which can be regarded as

terrestrial loss without including sedimentation and

particulate organic carbon (POC) transport.

Discussion

Streams and ditches cover only 4.4% of the water sur-

faces of the study area but their C gas emissions were

65% higher than that of lakes and ponds, which cover

7.8% of the whole study area. The emission vs. lateral

transport ratio of the streams was 1 : 1 without POC

included in our estimate for transport. For comparison,

it is same with the Yukon River basin (Striegl et al.,

2012) whereas in Sweden emissions were much lower

in relation with lateral transport, i.e. 0.2 : 1 (Humborg

et al., 2010).

Our mean CO2 and CH4 efflux estimates of

1690 � 575 g C m�2 (stream surface) yr�1 and

26 � 10 g C m�2 yr�1, respectively, fall well within the

range of fluxes measured from a Scottish peatland

stream; 259–45878 and 0–345 mg C m�2 d�1 for CO2

and CH4, respectively (Hope et al., 2001). Our CO2

fluxes are also comparable to estimates for Swedish riv-

ers of 473–3032 g C m�2 yr�1 (Humborg et al., 2010),

and a little less than the estimated mean for streams

and rivers in the USA (i.e. 2370 � 800 g C m�2 yr�1;

Butman & Raymond, 2011), as well as that used by

Jonsson et al. (2007) for 1st to 5th order streams in their

C budget for boreal catchment in Sweden, i.e. 7686 mg

C m�2 d�1. The highest uncertainty in our flux esti-

mates remains in the estimate for peatland ditches. In

Finland, CH4 fluxes from ditches of peatlands drained

for forestry have been measured to be in autumn on

average 229 and 66 mg CH4 m�2 d�1 for minerotrophic

and ombrotrophic mires, respectively (Minkkinen et al.,

1997), with the annual average CH4 emissions ranging

7–164 g CH4 m�2 yr�1 (Minkkinen & Laine, 2006).

These are comparable with our estimate of 110 mg

C m�2 d�1 (40 g C m�2 yr�1) for our sample site 11 of

ombrotrophic peatland. Our estimate is also close to

that of Dinsmore et al. (2010) who measured an average

evasion rate at 107 mg C m�2 d�1 for Black Burn,

Scotland, the stream draining an ombrotrophic peat-

land affected by peat extraction area and overgrown

drainage ditches. Minkkinen & Laine (2006) measured

high CH4 fluxes from peatland drainage ditches even

through the ice cover in winter and thus, assuming zero

flux during ice cover may underestimate actual CH4

fluxes from streams. The role of the effluxes from

narrowest stream width class is large and prone to pro-

duce significant error if not taken into account (Butman

& Raymond, 2011; Wallin et al., 2013). Although the

role of CH4 was minor in C cycling, its radiative forcing

was 12% of the total GWP when calculated as CO2

equivalents (Forster et al., 2007).

Peatlands are considered as important sources for

CO2 and CH4 in streams and they have shown to corre-

late with stream water organic carbon concentrations

(Hope et al., 2001; Teodoru et al., 2009). We did not find

such a correlation either with peatland coverage and

CO2 or DOC and CO2 concentration, a finding similar

to Finnish lakes, where CO2 concentrations correlated

negatively with peatland coverage in the catchment

(Kortelainen et al., 2006). The difference may stem from

a high proportion of drained peatlands in Finnish

catchments. However, our most peatland affected

sample point showed very high CO2 concentrations in

the summer and it is possible that the effect of peatland

in stream CO2 concentration is diminished if sampling

takes place at a distance from the peatland from where

the CO2 is effectively emitted. €Oquist et al. (2009) esti-

mated that 90% of the groundwater DIC export to bor-

eal headwater streams is emitted as CO2 into the

atmosphere within 200 m of the water entering the

stream. However, peatlands were an important CH4

source and especially the drainage density correlated

with CH4 concentration, which is consistent with Dy-

son et al. (2011) who found stream water CH4 concen-

trations to be an order of magnitude higher in a

drained peatland site than in their undrained control

site in eastern Finland. This is counterbalancing the

decrease in CH4 fluxes from drained peatland surfaces

compared with natural ones (Nyk€anen et al., 1998).

Lake sediments are also hot spots for CH4 production

(e.g. Kankaala et al., 2006) from where it is released to

streams as well as to the atmosphere especially during

spring and autumn turnover periods. In our study area,

the increase in CH4 in streams in late summer–earlyautumn could be associated with turnover of lakes and

ponds. There was a clear summer time CH4 source

from agricultural land in both intensively studied

catchments, although in the annual scale the effect of

agricultural land on CH4 concentrations was negative.

It might be that agricultural soils were not the source

per se but easily degradable DOM was probably turned

into CH4 in anoxic sediments of the stream during low

flow (no. 4) or in a connected pond from where it was

released with increasing flow (no. 10). Otherwise, the



better degradability of DOM from agriculture could not

be seen in the gas concentrations.

In contrast, agricultural land clearly increased DIC

concentrations in streams. The water fluxes can be very

different between agricultural land and forests since in

agricultural land a larger amount of water leaves

through ground water runoff enabling DOC to be

absorbed by mineral soils, while in nonagricultural

land water flows in near surface runoff where DOC

concentrations are higher (Mayorga, 2008; Dalzell et al.,

2011). Furthermore, water and bicarbonate fluxes have

shown to be increased due to the runoff changes by

agriculture, which has led to increased weathering of

silicate and carbonate rocks and the consequent seques-

tering of CO2 (Raymond et al., 2008). Thus, runoff from

agricultural land dilutes the DOC in streams while DIC

is higher, which was also evident in our data set

(Table 5). Some of the increase in DIC may be due to

liming of agricultural land. In Sweden, Humborg et al.

(2010) estimated that 4% of the carbonate and bicarbon-

ate export to the sea in Sweden was from pollution,

mainly from liming of agricultural land, which covers

8% of Sweden. Liming probably increases stream water

DIC more in small agriculture-intensive catchments

discharging to lakes. However, it is difficult to assess

from our data the extent of how much liming of agri-

cultural land increases stream water pH and thus retain

more inorganic C dissolved in the water.

Positive correlations between DOC and Q, and rela-

tions between DOC quality and season and Q are well-

established in the literature (e.g. Striegl et al., 2007;

Spencer et al., 2008; Wickland et al., 2012). DOC concen-

tration showed a similar pattern in all streams draining

into Lake P€a€aj€arvi, reflecting the mixture of peatland

and forest in the catchments and diverging C source

from peatlands to forest soils with increasing runoff, as

suggested by Laudon et al. (2011). However, different

land cover and land-use properties clearly affected the

quality of DOM when the flow regime diverged. For

the Mustajoki catchment with moderate peatland cov-

erage, the decreasing aromaticity and molecular weight

with increasing DOC suggest the source of more biode-

gradable DOM during high flow, i.e. diverging source

from peatlands to forest soil (Laudon et al., 2011), as the

peatland DOM can be regarded as less biodegradable

(Tipping et al., 1999; Kalbitz et al., 2003). Also, that the

agricultural land produced DOM of lower aromaticity,

supposedly more labile to microbial degradation, is

consistent with the findings of Williams et al. (2010) in

southern Ontario, Canada. Opposite to the Mustajoki

catchment, in 7 Luhdanjoki and in the L€oytynoja catch-

ment excluding sample point 11, increasing DOC was

associated with the increase in aromaticity of DOM,

implying the higher influence of ground water during

the base flow. DOC concentrations from agricultural

land are usually low and tend to be diluted with

increasing flow (e.g. Ruark et al., 2009; Dalzell et al.,

2011). Thus, the effect of agriculture may be difficult to

discern from stream water chemistry data with even

moderate agricultural land cover. The data also suggest

that different peat types, i.e. sphagnum vs. sedge peat

may give the different DOM quality signature.

Although the processes behind the observed temporal

and spatial changes in DOM quality are not fully

understood, the data suggest that DOM quality proxies

can be useful in interpretation of C sources (Battin,

1998; Helms et al., 2008) and warrant further investiga-

tions.

Although the coverage of the peatlands in the catch-

ment was the most important factor affecting stream

water DOC concentrations, also the extent of anthropo-

logical disturbance on peatlands, i.e. the drainage den-

sity, clearly affected the DOC concentration and DOM

quality. The positive correlation between peatland/

wetland coverage and stream water DOC concentration

have been shown in various studies in the Northern

Hemisphere (e.g. Dillon & Molot, 1997; Aitkenhead

et al., 1999; Arvola et al., 2004; Mattsson et al., 2009;

Laudon et al., 2011). Studies on the effects of peatland

drainages on water DOC concentration have shown

contradictory results (Holden et al., 2004 and references

therein), but e.g. Mitchell & McDonald (1995) have

shown, consistent with our results, that drainage den-

sity, determined as total channel length of 1st, 2nd and

3rd order stream per area, correlates with DOC concen-

tration in runoff. Also DOC concentration in the soil

water of a drained peatland was twice as high as in a

natural peatland within the same peat-complex (Laine

MPP, Str€ommer R & Arvola L, unpublished manu-

script).

The peatland coverage in boreal forest region is 24%

(Wieder et al., 2006), which is similar to the average

peatland percentage of the catchments in Finland, i.e.

22%, determined in a study that covered 88% of total

area of Finland (Mattsson et al., 2005). This emphasizes

the important role of peatlands in DOC export, espe-

cially in Finland where a large portion (55%) of peat-

lands are drained for forestry (Turunen, 2008). For

comparison, agricultural land forms about 8% of the

land area in Finland and e.g. in Canada, where one-

third of the world’s boreal forests are situated, at least

6% of the former boreal forests have been cleared for

farmland and settlements (Smith et al., 2000). C export

from catchments is largely controlled by water runoff

of which human induced disturbance in catchments

may increase. The climate change scenarios for Finland

predict warming and increase in precipitation espe-

cially in winter (Jylh€a et al., 2009) resulting in an



increase in winter time Q. This has already shown to be

taken place in many catchments in Finland during the

period of 1912–2004 (Korhonen & Kuusisto, 2010). We

measured similar or higher DOC concentrations in late

autumn/early winter than during spring snow melt Q

peak (Figs S6–11). This, connected with projected

increase in Q would imply enhanced C loss from catch-

ments in winter. The increase in DOC export from Mus-

tajoki catchment has been predicted for future winters

while the spring load decreases (Naden et al., 2010).

Similar results were predicted for the nearby Valkea-

Kotinen catchment using the INCA-C model (Futter

et al., 2009),

In concordance with Wallin et al. (2013) CO2 evasion

from streams was a dominant component of the C

export and constituted 49% of the total lateral dissolved

C and evasive C flux of the streams. Our measurements

did not include sedimentation or transport of POC, but

the emission per accumulation ratio has been estimated

on average as 21 : 1 for Finnish lakes (Kortelainen et al.,

2006) and the DOC:POC ratio was 10 : 1 e.g. in a humic

river in northern Finland (Heikkinen, 1989). Adding

estimates according to these ratios for C accumulation

in lakes and POC transport in streams to our estimates

of emission and transport of dissolved C, together they

make up to 3955 t C yr�1, which is 19.3 g C m�2 that

can be estimated to escape from the terrestrial system.

This is 0.15% of the estimated mean soil C stock (132.1

Mg ha�1) and 0.28% of the mean standing forest bio-

mass (68.9 Mg ha�1) in the catchment of Lake P€a€aj€arvi

(Hartman et al., 2012). We do not have measurements

of the terrestrial net ecosystem exchange (NEE) of CO2

of the catchment, but when we use average values from

the literature for different aged forest from a clear-cut

to 75-year old pine forest (Kolari et al., 2004), for peat-

land drained for forestry (Lohila et al., 2011) and for

agricultural land (Lohila et al., 2004) in Finland and

take account of their areal extent, we end up with an

estimate of 100 g C m�2 for the whole catchment. Thus,

our estimated C export from the terrestrial system

would be 19% of the terrestrial NEE. For comparison,

Humborg et al. (2010) estimated that in Sweden aquatic

DIC fluxes alone would correspond to 10% of the NEE.

Our results clearly indicate the importance of consid-

ering different land-use patterns and both streams/

ditches and lake surface areas when determining areal

budgets of different C species. High peatland propor-

tion in the catchment as well as high drainage density

of the peatlands clearly increased the DOC in streams

whereas agricultural land increased DIC. Aquatic trans-

port of terrestrial C is regionally important and espe-

cially the gas evasion from the smallest streams must

be taken into account in C budgets. The ultimate fate

of terrestrial C transported by streams, whether it is

sedimented or returned to the atmosphere en route to

the sea, determines the net effect of the terrestrial

system to the global atmospheric C budget. Whatever

the fate is, the aquatic C escape from terrestrial system

is regionally and globally important and should be

taken into account as an integral part of the terrestrial

C cycle.

Acknowledgements

This study was supported by the Academy of Finland throughprojects Pro-DOC and CLIMES (Grants 127922 and 256231 toMartin Forsius) and Academy Research Fellow Post to HannuNyk€anen (Grants 136455, 140964), and by the Lammi BiologicalStation of University of Helsinki. Leena Vitie, Aki Virtanen andMartti Yl€atupa are acknowledged for their efforts in the fieldsampling and in the laboratory, as well as Jaakko Vainionp€a€aand Riitta Ilola for measurements and laboratory analyses. Wethank John Loehr for correction of the language of themanuscript.

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Supporting Information

Additional Supporting Information may be found in theonline version of this article:

Figure S1. Lake P€a€aj€arvi and the studied subcatchments.Figure S2. Modelled and measured load of DOC and DIC toLake P€a€aj€arvi from 6 Mustajoki catchment.Figure S3. Modelled and measured load of DOC and DIC toLake P€a€aj€arvi from 11 L€oytynoja catchment.Figure S4. Modelled and measured load of DOC and DIC toLake P€a€aj€arvi from 12 Koiransuolenoja catchment.Figure S5. Modelled and measured load of DOC and DIC toLake P€a€aj€arvi from 6 Haarajoki catchment.Figure S6. CH4 (mg C m�3), DIC (g C m�3) and DOC (gC m�3) concentrations within Mustajoki catchment, samplepoints 1–6.Figure S7. CH4 (mg C m�3), DIC (g C m�3) and DOC (gC m�3) concentrations in 7 Luhdanjoki.Figure S8. CH4 (mg C m�3), DIC (g C m�3) and DOC (gC m�3) concentrations in 8 P€a€aj€arvi.Figure S9. CH4 (mg C m�3), DIC (g C m�3) and DOC (gC m�3) concentrations within L€oytynoja catchment, samplepoints 9–12.Figure S10. CH4 (mg C m�3), DIC (g C m�3) and DOC (gC m�3) concentrations in 13 Koiransuolenoja.Figure S11. CH4 (mg C m�3), DIC (g C m�3) and DOC (gC m�3) concentrations in 14 Haarajoki.Table S1. Comparison of k600 values (mean of monthly val-ues � SE, m d�1) determined with different models fromRaymond et al. (2012).



effect of catchment characteristics on aquatic carbon export from a boreal catchment and its...

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