regional and global patterns in carbon export from land to water
TRANSCRIPT
UNIVERSITÉ DU QUÉBEC À MONTRÉAL
REGIONAL AND GLOBAL PATTERNS IN CARBON EXPORT
FROM LAND TO WATER
THESIS
PRESENTED
IN PARTrAL FULFILLMENT OF
THE DOCTORAL DEGREE IN BIOLOGY
BY
MINGFENG LI
JANUARY2016
UNIVERSITÉ DU QUÉBEC À MONTRÉAL Service des bibliothèques
Avertissement
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UNIVERSITÉ DU QUÉBEC À MONTRÉAL
PATRONS RÉG IONAUX ET MONDIAUX DE L'EXPORTATION DE CARBONE DE LA TERRE À L'EAU
THÈSE PRÉSENTÉE
COMME EXIG ENCE PARTIELLE DU DOCTORAT EN BIOLOGIE
PAR MJNGFENG LI
JANVI ER 20 I6
iii
ACKNOWLEDGEMENTS
1 wo uld like to express my deep and sincere gratitude to the many peo ple who he lped
me to bring this research project to fruition, directly or indirectly. First of a li , 1. wo uld
like to thank my PhD supervisors, Professer Paul A. del Giorgio and Professe r Yves T.
Prairie, for providing me the opportunity of PhD in aquatic biogeochemistry. 1 am
deeply grateful for their warm-hearted help, insightful profess ionalism, valuable
guidance and tinancial support throughout the project and my entire PhD program.
Their patience, understanding and encouragement carried me on through these
important years of my !ife and let me learn how to shape myse lf a good scientist in
future. Without them, this dissertation wo uld not have been possible. ln a word , my
gratitude to them is rea lly unutterable !
1 would like to thank the committee members, Ors Changhui Peng, Jonathan J. Cole
and Jean-Franço is Hélie, for their very helpful , va luable comments and suggestions to
improve the quality of thi s thesis.
1 am also deeply indebted to a li my colleagues, the lab members of the the lndustrial
Research Chair in Carbon Biogeochemistry in Boreal Aquatic Systems (CarBBAS)
and the UN ESCO Cha ir in Global Environmental Change, held respective ly by Paul
del Giorgio and Yves T. Prairie, fo r their help in the fie ld , in the lab, and in my daily
!ife : Thanks to Jean- Franço is Lapierre, Dominic Yachon, Audrey Campeau, Matthew
Bagard , Marie-Ève Ferland , Franço is Guillemette, Lisa Fauteux, Véronique
Ducharme Riel, Nico las Fortin-St-Gelais, Jerome Comte, Lennie Boutet, Marilyne
Robidoux, Juan-Pablo Nina -Garcia, Caro lina Garcia-Chavez, Cynthia Soued, Ryan
Hutchins, Shoji Thottathil , Roy Nahas and Sara Mercier Bla is. Thanks to postdoctoral
fellows, Mart in Berggren, Cristian Teodoru, Tehri Ras ilo, Clara Ruiz-Gonza lez,
iv
Tonya DelSontro and Adam Heathcote for va luab le experience and new ideas they
gave us. Special thanks to Ali ce Parkes and Annick St-Pierre, as strong pillars of our
research team, who are be able to run fieldwork, laboratory, logistics, financial and
human resources, easily and smooth ly, thus guaranteeing an excellent environment
for our work and study. 1 also greatly thank Profs. Alison Derry and Beatrix Beisner
for their kind help with my PhD study. 1 wou Id also like to extend my appreciat ions to
the funds that materialize our research group of multiculturalism because nothing
would have been possible without the significant financial support. Thanks to Fonds
de recherche du Québec - Nature et technologies (FRQNT), Natural Sc iences and
Engineering Research Counci l of Canada (NSERC) and Hydro-Quebec, and Groupe
de Recherche Interuniversitaire en Limnologie et en Environnement Aquatique
(GRJL) .
Finally, 1 wo uld like to thank my family, espec ially my wife, Jinxia Wang, who
always understands, encourages and supports me to finish my PhD study, and my
little son, Alexander, and my daughter, Blair, who bring a lot of laughter and energy
to my life, further strengthening my confidence in my PhD study. Thanks to my
parents for their giving me encourages and blessings over telephone, rnaking my life
sunny and full of love.
v
CONTENTS
LIST OF FIGURES ................. .. .... ..... .... ............ .. .. .. .... .... ......... ................................ .. ix
LIST OF TABLES .. ........................... .. ..... ... .... ................ ........... ... ................... ....... ... . x ii
ABBREV IATIONS AND ACRONYMS ..... .......... .............................. ... .................... xiv
ABSTRACT ............ ........ ...................... .. ..... .. .. ... ... ......... ... .... ...................................... xv
R ÉSU MÉ .. .. ............................................ ............................. ............ .. .................... .... xvii
INTRODUCTION ...................................... ...... .. ...... .... ...... ..................... ............... .. .... . !
0. 1 T he ro le and importance of river system in carbon cyc lin g ................ .................... l
0 .2 Environmenta l contra is on riverine carbon export from watersheds at landscape
scale .............................................. ..... ........ ..... ... ............ ..... ....... .. ... ... ..... ................ ....... 3
0.3 Tota l carbon export from watersheds to r iver systems ...................... ... ................. ! 0
0.4 Objectives of the thesis .. ..................... ............... ... ............... ......... .... ... .. ...... ... ...... . ll
0.5 Genera l scopes and approaches ... ....... .... ... ....... .. ...... .. ............................. ........... ... 12
0.5.1 Regional riverin e carbon export fi·om notthern catchments ... ...................... 13
0 .5.2 A meta-analysis up-scaling to g loba l r iver in e carbon export to the oceans .. l 4
CHAPTER 1
THE RELATIVE INFLUENCE OF TOPOGRAPHY AND LAND COYER ON
JNORGANIC AND ORGAN IC CARBON EXPORT FROM CATCHMENTS IN
SOUTHERN QUEBEC, CANADA ... .. ... .... .... ... ................ ..... ..... ... ... ........................ . !?
1. 1 Abstract. ... ............ ... ..... .... .. ....... ........ ........ ..... ............. ........ .......... ............ .. .. ... .. .. .. 17
1.2 lntroduction .............................. ........ .. .............. ... ... .. ... ...... .. .... ..... .... ....... .. ........ ..... l 8
1 .3 Materials and methods ................................................... .... ...................... .... .... ...... 21
1.3. 1 Study area ................................................................................. .................... 2 1
1.3.2 Samp1ing, ana lyses and ca lcu lations ..... .... ...... ... ....... ................... ... .... ...... .. . 23
1.3.3 Catchment topography and land cover .......... ........... .. .............. ...... ........ ... ... 27
vi
1.3.4 Statistical ana lyses ... .. .... ....... .... .................................................................... 28
1.4 Results ...... ... ........... ............. ............................... ........................................... ........ 29
1 .4.1 Carbon export. ..... ...................................... ................................................... 29
1.4.2 Factors intluencing carbon export .................................................... .......... .32
1.4.3 lnter-annual variation in carbon export .... .. .... ............................................. .36
1.5 Discussion ......................................... ...... .. .. ....... .. ....... ..... . .. .... ..... ... ...... .... .... .... .. .. . 38
1.5.1 Drivers of terrestrial carbon expo rt to aquatic systems ...................... .. ....... .40
1.5.1. 1 Drivers of DfC Export... ................... .. ........... .... .......... ... .. ......... ... .... .. .4 1
1.5. 1.2 Drivers of DOC Export... .................................................................... .43
1.5.1.3 Drivers ofTC Export. ................ ................. .. ... .. ......... ...... ... ............... .44
1.5.2 Influence of land cover on the fonns of carbon exported ................... .. ....... .46
1.5.3 Inter-annual variatio n in carbon export... ....................................... .... ...... ... .48
CHAPTER 11
MAGNITUDE AND COMPOS IT ION OF CARBON EXPORT D FROM BOREAL
CATCHMENTS TO RIVER SYSTEMS IN NORTHERN QUÉBEC,
CANADA ................... ... ............ .................... ... ........ ...... ................ ... ............ .............. 5 1
2 .1 Abstract. .. ....... ....... ......... .......... ............ .. ... ..... ....... ... ........ ................ .... ... ...... .. .... .. . 5 1
2.2 Introductio n .. ..... .. ..... .......... ... .... ... .. .... .... ... .......... ... .............. ... ... ..... ............. .......... 52
2.3 Materials and methods ............. ......................... .. ... ..... ........ .. ................................. 55
2.3. 1 Study area ..... ...... ......... ....... .... ............. ... .............................................. ........ 55
2.3.2 Samplin g and chem ica l ana lyses .................. ........... ......... ....... .......... ........... 57
2.3.3 Discharge and DOC and DIC flux calculat ions ................... .......... ............... 57
2 .3.4 Aquatic gas emiss ions ................................................... ... .... ......................... 60
2 .3.5 Watershed properties ...... ........................................ ..... ............................. .. ... 60
vii
2.3.6 Statist ica l Ana lyses .............. .......... .... ........ ...... .... ......................................... 6 1
2.4 Resul ts .......... ... .... ... ...... ....... .... ........... .................. ................... ............................... 6 1
2.4. 1 Riverine DOC and DI C expo rts .................................. .. ..... .... .... .... ... .... .... .... 6 1
2.4.2 Watershed aquatic C02 and CH4 emissions ........... ............................ ... .. ...... 63
2.4.3 Tota l C export from borea l catchments ....... .... ........... ... ..... ........................... 64
2.5 DI SCUSSIONS .............. .................................. ...... ............................................... 69
2.5. 1 River-mediated DOC, DIC and C02 loss from landscapes ............. ...... ....... 69
2.5.2 Magn itude and composit ion of tota l C export .................. ... ................. .... .... 73
2.5.3 Cross-regio na l d ifferences in the magnitude and compos itio n of C
export ...................................................... ..................................................................... 75
2.5.4 Im pli cat io ns to terrestr ia l C budgets ...................................... ...... ........ ... ...... 76
CHAPTER Ill
A GLOBAL ANALYS IS OF RI V ERINE CARBON EXPORTTO THE OCEANS
3. 1 Abstract .. .. .. ........................................ ...... ...... ....... ... .... ............ .......................... ... 81
3.2 lntroductio n ..... ... ... ....... ...... .. ... .. .. .... ... ....................... .... ........................................ 82
3.3 Resul ts and discuss ions ................... ................... .... .................................... ........... 84
3.3 .1 Dri vers of riverine C expo lt ...... ............... ...... ......... .... ...... ...... .. .. .. .. ..... ... ...... 84
3.3.2 A new estimate of g loba l riverine C export to the oceans ...... ...................... 89
3.3.3 Past and future effects ofanthropogenic disturbances on g loba l riverine C
export ........................................................ .......................................................... 93
3.4 Methods ................. ... ......... .. .... .......... ....................... .. ......... ..... .... .... .... .... ... .......... 95
CHAPTER IV
CONCLUSION S .. .............. .................... ................ ..... .............. .. ....... ........................ 97
4. 1 Main co ntributio ns .............................. .................. ... ..... ... ...... ...... ... ........ ............. 97
4.2 Main innovatio ns ................................................ ...................... ..... ...... ............... 1 0 1
vi ii
4.3 lm portant implications ... .... ....... ... ... .. .. .... ............ .. ... .... ..... ..... .... .. ........... .. ... ....... ! 03
REFERENCES ...... ...................... ... ..... .... .... ...... ..... ..... .... .... .............. ... ........ ....... ..... ] 07
ix
LIST OF FIGURES
Figure O. 1 The biogeochemistry of carbon in rivers .............. ... ..... .. .............. ..... ... .... 6
Figure O. 2 The research areas for the regional studies on riverine carbon export (ET:
Eastern Townships; JB: James Bay; AB: Abitibi. JB and AB are closely
neighbored in northern lowland ofQuebec) ... .......... .. ....................... ..... l4
Figure O. 3 The distributional map of the catchments (in brown) for the
meta-analysis, covering 56% of global terrestrial area and 74% of global
exorheic area (exc lud ing Antarctica) ........... .. ............ ......... ... ..... ... ......... l5
Figure 1. 1 DOC export versus DlC export for the 83 catchments. Exports are
expressed as the average of 2004 and 2005 measurements in grams of C
per square meter of total catchment area per year. ........ .... ........... .. ........ 30
Figure 1. 2 Carbon expotted as DIC (solid squares) and DOC (open circles) in g m·2
yr·' for the 83 catchments, average of 2004 and 2005 measurements, as a
function of total catchment area. Significant correlations with catchment
area are shawn for DIC export (thin tine) , DOC export (thick tine) and
TC (dashed tine, points not shown) ................................................ ..... ... 31
Figure 1. 3 Principal component analysis of DIC, DOC and TC exports (average of
2004 and 2005 values) and key topographie and land caver variab les for
the 83 catchrnents .................................. ....... ................... .......... ... .. ..... .. . .33
Figure 1. 4 Variance partitioning in the multiple linear regression models of DlC
and DOC export, showing the percentage of variability explained by
each component variable and the remaining variabi li ty, unexplained by
the rnodels ..... .. ......... ..................... ............................. ... ............... .. ..... .... 35
Figure 1. 5 lnter-annual variation in DIC and DOC exports for 32 basins. For each
site, export is reported as the difference between the export in the given
x
year and the 3-year average export for that site (in g m-2 yr-1). The mean
di ffe rence is the small square within the larger 751h percentile box, with
9Yh percentile whiskers, a median line, and asterisks for maximum and
minimum va lues. Diffe rent letters within a panel indicate significant
diffe rences among yea rs (one-way ANOVA and Tukey-Kramer post-hoc
test) ... ... .. .. ..... .. ....... ... .. ...... ... ... .... .. ... .... ................ ....... .. ............ ... ........ .... 3 7
Fi gure 1. 6 Carbon export as the sum of DIC expott and DOC export in g m-2 yr-1
and the DIC/DOC export ratio versus %vegetation fo r two example
watersheds, an in fl ow to Lac d' Argent (panels A and C) and an in fl ow to
Roxton Pond (panels B and 0 ). The current vegetation cove rage of the
catchment is indicated by an "X" in each pane1... .................... .... ......... .48
Figure 2. 1 Figure. 1 a. Reg ional daily runoff (mm d-1) for the sampling year (201 0),
with the error bars (SE), averaged (from the daily discharges of six
streams and rivers during the water year of our observation (J une 1 st,
2010 through May 3 JS1, 2011 ). b. Relationships between estimated and
measured discharge for the 44 studied rivers .. .. .. ............ .. ........ .. .. .. .. .. .. . 59
Figur e 2. 2 TC export (a) and contribution of different carbon species to TC (b) for
each month in the water year. TC export is expressed in g C per m2
catchment a rea fo r each month .... .. .... .... ........ .... .... .. .............................. 65
Fi gur e 2. 3 a. The average contribution of the various C species in the an nuai total
C export from these borea l watersheds; b. The contribution of DOC
export and of aquatic co2 emiss ions to total c export from these borea l
catchments, as a fun ction of the proportion of water in each catchment
(% water). The latter is mostly driven by the presence of lakes. The
xi
catchments of rivers of order 1 and zero co ntained no la kes and were
aggregated as o/owater = 0 ...... .. ......... .. .. ....... ........... ... ...... ............. ........ . 66
Figure 2. 4 Co mpariso n of the average contribution of di ffe rent C fonns in the
annua l tota l C export be tween South Abitibi and James Bay regions ... 69
Figure 3. 1 The Maps of Global Distributions of DIC and DOC Expotts ... .. ...... 89-90
xii
LIST OF TABLES
Ta bl e 1. 1. Stream and catchment characteristics of the 83 study sites. Statistics for
discharge and water chemistry were determined by first averaging a li
measured va lu es from 2004 and 2005 for each of the 83 streams, then
calcu lating the minimum, maximum, mean and standard deviation of
these values (n=83). Stat ist ics for topography, land · cover, geo logy and
soil were obtained from digital elevation models, and maps of
topography, land cover, rock type, surficia l deposits, and soi l order,
using GIS (n=83) ... .. .... .. ..... ....... ................... ...... ... ..... ................ .. .......... 24
Ta bl e 1. 2. Tab le 2. Multiple linear regressio n models predicting DIC, DOC, and
TC export in g m·2 yr· 1 (n=83 for each). Estimates of coefficients and
corresponding p va lues are given for a li variab les offered during the
step-wise selection process. Variables were included in the mode! if
p<0.05 (in bold) and the corresponding R2 values are shown .... .... .. ..... 34
Ta bl e 1. 3. Local climate, gauged daily discharge, as weil as discharge and ore and
DOC concentrations measured in situ at the 32 s ites in 2003, 2004 and
2005 ............................... .......................... .. ................................... .. .... .. . 36
Ta bl e 2. 1. The physical , hydro logica l and chemical characteristics of the 44
catchments and rivers samp led .............................................................. 62
Ta bl e 2. 2. The ranges, means and medians of the flu xes of DOC, ore, POC, C02,
CH4 and TC exported annually from the 44 catchments (units: g C m·2
yr- 1 on catchment area basis) ....... .... ...... .... .. ......... ....... ........................... 63
Ta bl e 2. 3. The comparisons of physical, chemical and biolog ical factors between
James Bay and Abitibi du ring the measurement per iod (June 1 st, 2010
xiii
to May 3 Pt, 20 1 1 ). The va lues were annua lly averaged fro m the 44
streams and ri vers we observed ...................................... .. .. .......... ....... .. 68
Table 2. 4. Co mpariso n of latera l and gaseo us carbon expo rts fro m watersheds in
the previous studies .. .. .... .............. ... ...... ... ........ .... .. .. .. ........... .... ........... .. 70
Tabl e 3. 1. Multip le linear regress ion mode ls pred ict ing DOC, DI C and POC
export in g m·2 yr·1• Est imates of coeffic ients and corresponding p
va lu es a re g iven fo r all var iables offered d uring the step-w ise select ion
process. Variables were inc luded in the mode! if p<O.OOO 1 and the
correspo nding R2 va lu es are shown ........................... ..... .. ....... ... ... .. .. .... 88
Ta bl e 3. 2. T he co mpar isons of our estimates of g lo ba l ri verine carbo n expo rt to the
oceans w ith those in prev io us studies ........ ... ... ... ........... ..... ......... .. ... .. ... 92
xiv
BIC
BSI
CarBBAS
CH4
CID
co2 COD
DIC
DOC
ETC
GES
GHG
PI C
POC
Pg
TC
TIC
TOC
ABBREVIATIONS AND ACRONYMS
Bayesian Information Criterion
Bas in shape index
Carbon Biogeochemistry in Boreal Aquatic systems
Methane
Carbone inorganique dissous
Carbon diox ide
Carbone organique dissous
Disso lved inorganic carbon
Disso lved organic carbon
Exports totaux de carbone
Gaz à effet de serre
Greenhouse gases
Particulate inorganic carbon
Particulate organic carbon
Petagram
Total carbon
Tota l inorganic carbon
Total inorganic carbon
xv
ABSTRACT
Carbo n ex po rted fro m terrestria l ecosystems to river systems is a cri t ical co mpo nent
of the g lo ba l carbo n cyc le. How much carbo n is ex po rted fro m watersheds, in what
fo rm , and when the ex ports occur, as weil as the future respo nse of riverine carbon
export to c limatic change driven natu ra lly and anthro pogenica ll y, a re major issues of
biogeochem.istry. However, few studies in the past s imulta neo usly explored ri verine
carbo n expo rted in di ffe rent forms and thu s we still do no t have an integrated
perspective of magnitude and regulatio n of tota l riverine carbon expo rt at the regional
and g lo ba l sca les. T he research presented in thi s dissertatio n a ims to explore the
co mpositio n and drivers of tota l carbon export from land to ri ve rs, from watersheds to
no rthern reg ions to the g lo ba l sca le, and to identify the natura l and anthro pogenic
contro ls on the g lo ba l riverine carbon export to the oceans in the context of c limat ic
change. In the thes is project, we used the data co llected by the CarBBAS group over
the past 5 years fro m 127 rivers and streams in Q uebec, and have com bined these
w ith a newly co llated g lo ba l data set of publi shed carbo n co ncentratio ns and/or
ex ports fo r 566 ri vers dra ining a to ta l of 74% of g lo ba l exorheic area .
We fi rst explo red the influ ence of topography and land cover on the co mbin ed
ino rganic and organic carbon export from temperate catchments in so uthern Q uébec
(Chapter 1). O ur resul ts show that whereas both are primar ily driven by regio nal
runoff, to pography is s light ly mo re important than land cover in expla ining the
va riance in DI C export across watersheds, whereas la nd cover is much mo re
important than to pography in determining DOC expo rt. T he inter-annual di ffe rences
in C expo rt are driven mostly by shi f'ts in annual precipitat io n and reg io na l runoff.
Further, the proportion of the catch ment covered by natura l vegetatio n had a negative
effect on DI C export but a pos itive effect on DOC expo rt, sugges ting that a change in
land cover that reduces vegetation (e.g. defo restatio n) wo uld lead to modest decreases
in TC expo rt, but la rge inc reases in the DIC/DOC export ratio. As a fo llow up of
these stud ies in temperate regions, we furthe r quant ifi ed river-mediated expo rt of
disso lved organic and ino rganic C (DOC and DIC), as we il as the in tegrated aquat ic
emiss io ns of both C02 and C H4, fro m 44 borea l catchments that range wide ly in s ize,
to pography and land cover (C hapter 2) . The resulting tota l C export was seaso na lly
ve ry varia ble, dri ven mostly by the annu al runoff cyc le, and averaged 15.5±5.3 g C
m-2 (watershed) yr-1• DOC dom ina ted, on average, this tota l C export over the annua l
cyc le (5 8%), but aquatic C02 emiss ions were a majo r co mpo nent of export in a li
catchments (average 20%). Ou r results confi rm that DOC and DI C exports are most ly
driven by runoff but further regulated by fundamenta lly di ffe rent env iro nmenta l
xvi
fac tors, and that wetlands are a majo r so urce of DOC expo rted to rivers, but further
demo nstrate that lakes w ithin the catchment are a strong DOC sink, such that the net
expo rt of DOC results fro m the ba lance between the two. T he total an nua i C ex ported
via rivers is within the range of net ecosystem prod uction, and has the potentia l to
fu ndamenta lly a lte r our perception of the ro te of these boreal landscapes as so urces or
s inks of atmospheric C02.
The meta-analys is of g loba l river ine carbon export to the oceans has shown that
beyond the expected hydro logie contro l over mate ria l flow, DOC export is mostly
dri ven by a co mbina tion of natural var iables, such the extent of wetlands and the
average organic carbo n content of the catchment so ils, as weil as by anthro pogenic
a lteratio ns of the landscape, such as the extent of cro pland s and, to a lesser degree,
the presence or la rge reservo irs. ln contrast, DIC export was ma inly contro lled by the
extent of carbo nate rocks (positive) and of water bodies (negat ive). ln additio n, the
extent of cropland expla ined a substantia l amount of va riab ili ty. T hese mode ls were
then used to estimate carbon export for a li exo rheic watersheds not present in our
database to derive a new g lobal est imate of carbo n export to the oceans of 0.68±0.05 Pg yr·1, a substantia l revis ion of the often-cited va lu e of 0.9 Pg yr·1• A retrospective
analys is suggests that as much as 40% of the current C export is associated w ith the
extent of agriculture on the planet.
1 n co nclu sion, this thes is has shown that in di ffe rent landscapes and at diffe rent
spatia l sca les, carbon export is driven by a co mbinat ion of natu ra l features of the
landscape and hu man activities. tt a lso high li g hts the d ifferentia i regulatio n of the
inorganic and organic fractio ns of C export. Anthro pogenic impacts due to land
use/cover change may be replac ing the natura l driving forces as the primary
determinants of the magnitud e and co mposit io n of both current and future transfe rs of
carbo n fro m land, thro ugh the hydro logie network, and ultim ate ly reachin g to sea,
imply ing the impo rtance of land use and management in contro lling riverine carbon
export fro m terrestria l ecosystems in the context of human- induced enviro nmenta l
changes, both regio na lly and globa lly.
Key words: ri ver carbon export ; carbon cyc le; greenhouse gases (GHG); d isso lved
organic carbon; disso lved inorganic carbo n.
xvi i
RÉSUMÉ
L' expor1ation du carbone (C) des écosystèmes terrestres vers les systèmes flu viaux
est une composante fondamentale du cycle g lo ba l du carbo ne. Co mbien de ca rbo ne
est exporté des bass ins versants, sous que lle fo rme, quand les expo rtations se
produisent-e lles et qu 'e lle sera la ré ponse de l'expo rtatio n du carbo ne ri ve ra in face
aux changeme nts c limatiques nature ls et anthro piques so nt toutes des qu estio ns
biogéochimiques d'intérêt majeur. Peu d'études cependant ont explorées
simultanément l' ex po r1ation des différentes formes du carbone riverain et no us ne
disposons donc pas enco re une perspective in tégrée de la magnitude et du co ntrô le
des expor1atio ns tota les de carbone flu v ia le à l'éche lle régio nale et g lo bale. La
recherche présentée dans cette thèse vise à explo rer la co mpos itio n et les facte urs qui
contrôlent l'expo rtation tota le de carbo ne des riv ières, des bass in s ve rsants des
régions no rdiques jusqu 'à l' éche ll e glo ba le et d'id entifi er les co ntrô les nature ls et
anthropiques de l'exportatio n de carbo ne flu via le g lo ba le vers les océans le co ntexte
des changeme nts c limatiques . Dans cette thèse, no us avo ns utili sé les do nn ées
recue illies par le groupe CarBBAS au cours des c inq derni ères ann ées provenant de
127 rivières et ruisseaux au Québec co mbinées avec un ensembl e no uvellement
rassembl ées de donn ées mondia les publi ées des co ncentratio ns et/ou des ex portatio ns
de carbone de 566 riviè res dra inant un tota l de 74% de la superfic ie exo ré ique
mondia le .
Nous avo ns d'abo rd explo ré l'influence de la topographie et la co uverture te rrestre sur
l'exportatio n combin ée de carbo ne inorganique et organique provenant de bass in s
ve rsants tempérées du sud du Québec (chapitre 1 ). Nos résultats mo ntrent que la
topographie est plus impo rtante que la co uverture terrestre po ur expliquer la
variabilité du carbo ne inorganique dissous (C ID) expo rtée des bass ins ve rsants, bien
que les deux so ient essentie llement co ntrôlées par le ruisse llement régio na l, a lo rs que
la co uverture terrestre est beauco up plus impo r1ante que la topographie dan s la
déterminatio n de l' exportation de carbo ne organique di sso us (COD). Les diffé rences
interannue lles de l' expo rtation du C sont princ ipa lement rég ies par des cha ngements
dans les précipitatio ns annue lles et le ruisse llement régio na l. De plus, la proportion
du bass in versant couvert par la végétation nature lle a eu un effet négatif sur
l'exportation du CID, mais un effet positif sur l'exportatio n du COD, ce qui suggère
qu'un changement de la co uverture terrestre qui diminu e la végétatio n (par exemple ,
la déforestatio n) co nduira it à des diminutio ns modérées de l' exportatio n du C total,
ma is de fortes augmentatio ns du ratio C l D/COD des expo rtat io ns. Pour poursuivre
cette étude dans les régions tempérées, no us avo ns qu antifi é en o utre l'expo rtation par
xviii
les rivi ères du COD et C ID, a ins i que les émiss ions aquatiques de C02 et de CH4 de
44 bass ins versants bo réaux de diffé rentes ta illes, topographie et de co uvertures
terrestres (chapitre 2). L'exportatio n de C total éta it très va riable entre les sa iso ns et
notamment contrô lé par le cycle annuel du ruisse llement, avec une moyenne de
15.5±5.3 g C m·2 (bass in versant) an·1• Le COD domine en moyenne cette expo rtatio n
tota le de C sur un cyc le annue l (58%), mais les émiss ions de C0 2 aquatiques éta ient
une composante maje ure de l'expo rtatio n dans tous les bass ins versants (moyenne
20%). Nos résultats confirment que les exportations de COD et CID so nt
principalement co ntrô lés par les eaux de ruisse ll ement, mais auss i par des facteurs
environnementaux fo ndamentalement différents et que les zo nes humides so nt une
so urce majeure de COD expo rtés vers les riv ières. Nos résultats démo ntrent aussi que
les lacs situés dans le bass in versant constituent un puits de COD, de te lle sorte que
l'expo rtatio n nette de COD résulte de l'équilibre entre les deux. Le C tota l expo rté
annue llement par les rivières est comparable à la productio n nette de l' écosystème et a
le potentie l de modifie r fo ndamentalement notre perception du rô le des paysages
boréaux comme so urces ou puits de C0 2 atmosphérique.
La méta-analyse des exportatio ns fluviales g lo bales de carbo ne vers les océans a
montré qu'au-de là du contrô le hydro logique attendue sur le transpo rt de la matière,
1 'exportatio n du COD est principalement entraîné par une co mbina iso n de variables
nature lles, te ls l'étendue des zo nes humides et de la teneur en carbo ne organique
moyenne des so ls du bassin versant , a in si que par des modificatio ns anthropiques du
paysage, te ls que l'étendue des terres cult ivées et, dans une mo indre mes ure, de la
présence de grands réservo irs. En reva nche, l' exportation de CID est princ ipa lement
co ntrôlée par l' étendue de roches carbonatées (positif) et des plans d'eau (négati f) . De
plus, l' étendue de te rres cultivées expliqua it une quantité impo t1ante de variabilité.
Ces modèles ont ensuite été utilisées pour estimer l'exportatio n de carbo ne pour tous
les bass in s exoré iques absents de notre base de donn ées pour établir une no uve lle
estimatio n g lobale de l'expo t1atio n de carbo ne vers les océans de 0.68±0.05 Pg an·1,
une révis io n substantie lle de la valeur so uvent c itée de 0.9 Pg an·1• Une analyse
rétrospective suggère que jusqu'à 40% de l'expo rtatio n actue lle est associée à
l' étendue de l'agriculture sur la planète.
En co nclu sio n, cette thèse a montré que, dans des paysages di ffé rents et à di fférentes
éche lles spatia les, l'exportatio n de carbone est entraîné par une co mbina iso n des
caractéristiques nature lles du paysage et les activ ités huma ines . Elle so uligne
également la régulatio n di ffé rentie lle de 1 ' exportatio n des fractio ns organiques et
inorganiques d u C. Les impacts anthropogéniques en ra iso n des changements de
l'utili satio n des terres et des co uvertures terrestres peuvent remplacer les press io ns
xix
nature lles comm e princ ipaux déterminants de l'a mpleur et la compos itio n des
transfe rts actuels et futurs de carbo ne provenant de la terre, par le réseau
hydro log ique pour fin a leme nt atte indre la mer. Ce la implique l'impo rtance de
l'utili sa tio n et de la gestion des terres dans le contrô le de l'expo rtatio n de carbone
n verames des écosystèmes terrestresde dans le co ntexte des changements
env iro nneme ntaux induits par l'ho mme, rég io na lement et mo ndia lement.
Mots clés : exportatio n de carbone, cycle du carbo ne, gaz à effet de serre (G ES),
carbo ne organique disso us, carbo ne inorganique disso us
INTRODUCTION
0. 1 The ro te and importance of river system in carbon cyc ling
Carbo n, as the bu ilding block of li fe , plays an im po rtant ro le in a ser ies of processes
that prov ide food, c lothing and fuel for us, and thus we are unavo idably entw ined
with its biogeochemical cyc le. Part icular ly in the past 50 years, human activ ity has
gradua lly beco me a cruc ia l driving fo rce in g loba l warming du e to the anthropogenic
impacts o n reg iona l and g lo bal carbo n cyc ling (V itousek et a l. , 1997; Ver et a l. , 1999).
Actua lly, carbo n cycling has been w idely regarded as the key to our understanding of
the earth surface system and globa l env iro nmenta l change (e.g. c limate change, land
degradat io n and biodiversity loss) because it acts as an essentia l co mpo nent linking
abiot ic to biot ic co mponents of the earth system through photosynthes is and
decomposit ion, and a lso regulates biogeochemica l cyc ling of other e lements (e.g. N, P,
S) (H imes, 1997; C hame ides and Perd ue, 1997; Falkowski et a l. , 2000; He imann &
Reichstein, 2008).
To date, numerous studies have focused on terrestria l and/or aquatic carbo n cyc le
from di ffe rent perspectives using var io us approaches and methods, a iming to have a
better understandin g of w hat are driv ing the co upling between g lo ba l change and
carbon cyc ling , how it is contro lled or intl uenced natura lly and anthropogenica lly,
and the future response of terrestrial and aquat ic eco systems to it ( e .g . Cao and
Woodward, 1998; Cox et al. 2000; Betts, 2000; Feeman et a l. , 2004; Ca llaghan et a l. ,
201 0; Grosse et a l. , 20 Il ; Neigh et a l. 20 13). Part icular ly, eco systems at northern
latitudes have beco me the focus of recent resea rch (e.g. Call aghan et a l. , 201 0 ; Tank
et a l. 20 12; Neigh et a l. 20 13). T his is not only because these eco systems are large
potentia l si nks of carbo n in the atmosphere but a lso because they are very sens itive to
2
c limate change (Priee and Apps, 1996; Betts, 2000; Callaghan et a l. , 201 0). Therefo re,
understanding the ro le and importance of bo rea l ecosystems in g lo ba l carbo n cyc le is
cruc ia l to o ur assessment of future globa l env ironmenta l change . Unfo rtunate ly,
however, in most cases riverine carbo n expo rted from terrestria l systems, which plays
a key part in linking terrestria l, aquat ic and atmospheric carbo n cyc les, is rare ly
mentio ned when discuss ing terrestria l or g lo ba l carbo n budgets. ln rea lity, inland
waters ( inc luding streams, ri vers, lakes and wetlands) occupy less than 1% of the
Earth 's surface, but the ir co llective co ntribution to the g loba l carbon flu xes is
disproportionate ly important, co mpared w ith te rrestria l and oceanic ecosystems
(Battin et al., 2009) . Espec ia lly in recent years, the re lative contributio n of inland
waters to the glo ba l carbon budget has been further highlighted (Co le et a l. , 2007;
Battin et a l. , 2009; Benstead and Leigh, 20 12; Raymond et a l. , 20 13). How mu ch
carbon is expo rted fro m watersheds, in what form, and when the expo rts occur, as
weil as the future response of riverine carbon export to g lo ba l warming have thus
become hot iss ues of majo r biogeochemical inte rest. A ltho ugh the re are aspects of the
ro le and im portance of river system in regional carbo n budgets that are re lat ive ly we il
understood, there are still many uncerta inties, particula rly in terms of the magnitude
of so me of the key processes in vo lved . Fo r example, the estim ates of g lo ba l C0 2
evasion fro m inland waters range fro m 0.26 to 3 Pg C (Co le et a l. , 2007;
Aufdenkampe et a l. , 2011 ; Raymo nd et a l. , 201 3; Lauerwald et a l. , 2015). Although
the estima tes of organic carbo n transported from land to sea ranging w ide ly from 0.03
to 1 Pg C yr·1 (Williams, 1971 ; Re ine rs, 1973; Richey et a l. , 1980; Meybeck, 1982;
Ludw ig et a l. , 1996; Schlunz and Schne id er, 2000; Aitkenhead and McDowell , 2000)
have been co nverged to a va lue of around 0.4 Pg C yr·1, the exact quantity still
remains e lus ive because previo us studies were based on the limi ted data, g iven
3
similar assumptio ns, and/or co mmonly biased to sorne big rivers, especia lly tropica l
and temperate (Likens et a l. , 1981 ; Meybeck, 1993 ; Ludw ig et a l. , 1996; Cauwet,
. 2002; Da i et a l. , 201 2). As for g lo ba l particulate carbo n ex po rt, the re may be mo re
uncerta inties in the estimates becau se almost a li the previo us estimatio ns were merely
based on an assumed percentage of particulate organic or inorganic carbo n (POC or
PI C) in suspended matter, lacking strong supporting data (Garre! et a l. , 1973;
Likens et a l. , 1981 ; Meybeck, 1982; Ludw ig et a l. , 1996; Cauwet, 2002) , although
Meybeck ( 1982) and Gal y et a l. (20 1 5) estimated g lo ba l riverin e POC expo rt based
on the POC and sedim ent data of 100 and 70 rivers, respective ly. It is thus necessary
to deve lo p a better understanding of the ro le and importance of river systems or
inland waters in linking atmospheric , terrestria l and aquatic carbo n cyc ling , both
regio na lly and g lo ba lly, in the context of g lo bal warming.
0 .2 Enviro nmenta l co ntra is on riverine carbo n expo rt fro m watersheds at landscape
scale
River systems co nnect the atmosphere, hydrosphere, geosphere and bios phere, so
export of carbo n fro m watersheds to river systems is wide ly regarded as an essentia l
compo nent of regio na l and g lobal carbo n cyc ling . Espec ia ll y, headwater streams, the
so urces of river networks, have tight carbon linkages to the ir surrounding terrestrial
environments fro m hill slo pes to stream channels, and are shaped substantia lly by
interactions amo ng hydro logica l, geo morphica l and bio logica l processes that are
associated c losely with the biogeochemica l cyc ling of carbo n. Hence, they are
co ntro lled greatly by land scape va riables and regulate the cyc ling of nutrients (e.g. N,
P, Fe, S) that potentia ll y subsidize the aquatic communities in the downstream
reaches or w ithin the entire watershed (Gomi et a l. , 2002; Wipfli et a l. , 2007).
4
Therefo re, the study on land scape co ntra is on carbon expo rt fro m watersheds scaling
fro m a headwater catchment to the glo be is necessary to integrate inland waters into
the terrestria l and g lo ba l carbon budgets, undo ubtedly benefi cia i to better
understanding of biogeochemi cal cyc les of carbon and nutrients in the backgro und of
g loba l change.
However, landscapes di ffe rentiate at diffe rent spatia l and tempo ral sca les due to the
heterogeneo us combinat io ns of c limate, so i! , vegetation, litho logy, la ndfo rm and land
use/cover, th us resu !ting in diffe rent riverine carbon expo rt patterns that are
characterized by di ffe rent composit ion of carbon species that are exported fro m the
watersheds and then transfo rmed a long the river. ln additio n, human activity has
beco me an impo rtant driv ing fo rce fo r g lobal change and this fu rther compli ca tes the
study of the contro lling effects of landscape on riverine carbo n expo rt fro m the
land scapes due to anthro pogenic impacts on the earth surface and regio nal and glo ba l
carbo n ba lances (e.g. defo restat ion, fa rming , damming and urbanization) (e.g. Meyer
& Tate, 1983; Carig nan et a l. , 2000; Westerhoff and Anning, 2000; Danie l et a l. 2002;
Royer and Dav id 2005 ; Laudo n et al. , 2009; Wilson and Xeno poulos, 2009; Hudo n
and Carignan, 2008; Barn es & Raymond, 2009; Alvarez-Co be las et a l. , 20 12; Bau er
et a l. , 20 13). T herefo re, mo re attentio n sho uld be focused on na tura! and
anthropogenic effects on carbon expo rt fro m catchme nts to rive rs, mechanistica lly
and quantitative ly, at di ffe rent temporal and spatia l scales, and on integrating of
riverin e carbon into terrestria l and g loba l carbon cyc les.
The carbon exported from catchments to river sys tems can genera lly be c lass ified into
disso lved organic carbo n (DOC) (<0.45!-!m), resulting fro m leaching and
deco mposition of organic carbo n in plants and so ils, disso lved inorganic carbo n
5
(DIC), such as HC03-, C03-2 and H2C03 (or dissolved C02), POC (>0.45!lm),
including litter, wood debris, insects and so il organics, and PIC, debris of carbonate
minerais. Ultimately, the C that is loaded from land into river networks will in part
evade as C02 and CH4 to the atmosphere, in part wi ll flow downstream to the
receiving water bodies or oceans, and the rest will enter aquatic food webs or be
stored in sedi ments in streams, rivers, lakes and/or coasta l oceans. On a catchment
basis, the carbon from landscapes is finally transported out of the catchment in
dissolved (DOC, DJC and dissolved CH4), gaseous (C02 and CH4) and particulate
(POC and PIC) forms. Accord ing to Meybeck ( 1982 & 1 993), abo ut 0.9 petagrams
(Pg) C is annual ly delivered to the oceans via rivers, of which 0.4 Pg of organic
carbon (DOC and POC) is from so il organic carbon, 0.3 Pg of ino rganic carbon (D IC
and PIC) is from erosion of carbo nate rocks in cont inenta l crust, and the other 0.2 Pg
is DIC from soil inorganic carbon. ln reality, the main carbon forms in the river are
DOC, DIC and POC since PIC and dissolved CH4 account for a very smal l fraction of
riverine carbon exported (Aucour et al. , 1 999; Billett & Moore, 2008 ; Li et al. , 20 15)
and few studies were/are focused on them for their re lat ively less importance in
ecology and environmental science. Fig ure 1 shows the biogeochemistry of carbon in
rivers, indicating the sources and fates of riverine carbon from terrestrial organic
carbon may be respired, ingested , stored, exported and flocculated , while DIC may be
lost through C02 evasio n. Recently, the g lobal C02 evasion from inland waters is
est imated from 0.26 to 3 Pg C (Co le et a l. , 2007; Aufdenkampe et a l. , 20 Il ; Raymond
et al. , 201 3; Lauerwald et al. , 201 5), while the globa l CH4 evasion is estimated as 0_ 1
Pg (Bastviken et al. 201 1 ). Moreover, due to the landscape heterogeneity, carbon
export fi-om different landscapes to river systems varies widely arOLmd the
world----for examp le, DOC export ranges from 0.5 (Mulho lland and Watts, 1 982) to
6
416 g m·2 yr·1 (Charzanowski et a l. , 1983) whi te riverine DIC export varies from 0.03
(Stets & Strieg l, 2012) to 11 5. 12 g m·2 yr·1 (Tript et a l. , 20 13 ; Sarma et a l. , 20 12).
Precipitation 1 1 Atm
SOURCE
MATERIALS:
Labile Organic
Particulates
Stem flow
Throughflow
Refractory
Particu lates
/
+
' -~ ,, .1'
ALLOCHTHONOUS ' / v v
1 1
Organi~
Acids : 1 1 1
1 .1'
/ 1 1 1
~ v INPUTS:
POC: Litter, Debris,
Trees, lnsects, Pollen
DOC
+
1 1
W\V
DIC
Rock
+CaCOJ
1-jCOJ", co3-2
.1'
' / ,, Weathering ' v
PIC
TRACERSAND
SIGNATURES: --------------~-----
RIVERINE
ENVIRONMENT
Storage
!::.. 13C, !::..
14C chemistry
Entra inment, Mobi 1 ization ( overland, groundwater),
Direct litterfall , slump, and erosion
Ingestion
Export to Downriver nd Marine Environments
J
Figure 1 The biogeochemistry of riverine carbon (modified from Likens (1981))
7
Over the past 30 yea rs, great effo rt has been, to vary ing degrees, made to better
understand and quantify riverine TOC (tota l organic carbo n), DOC, POC, DI C (e.g.
Schlesinger and Me lack, 198 1; Mulho lland & Watts, 1982; Hope et a l. , 1994; L udw ig
et a l. , 1996; Stets and Strieg l 20 12; Tank et a l. , 20 12; La pierre et a l. , 20 13;
Dornblaser & Striegl, 20 15; Ga ly et a l. , 20 15), and evasion of C02 and CH4 (e.g.
Kling et a l. , 199 1; Battin et a l. , 2009; Aufdenkam pe et a l. , 20 11 ; Butman & Raymo nd,
20 11 ; Lapierre et al. , 2013; Raymond et al. , 20 13; Campeau et a l. , 20 14 ; Lauerwald et
a l. , 20 15). ln part icular, the export of te rrestr ia l organic carbon (DOC or TOC) to
river systems has been the focus of attention, because it may influence aquat ic
metabo lism and nutrient cyc li ng, is lin ked to carbo n emiss io ns to the atmos phere, and
c losely re lates to water qua lity (e.g. infl uence on the mo bili ty and ava ilab ili ty of
metals and co ntaminants) (e.g . Sch lesinger and Me lack, 198 1; Mulho lland & Watts,
1982 ; Ho pe et a l. , 1994; Ludw ig et a l. , 1996; M ulho lland, 1997; La i, 2003 ;
A lvarez-Co be las et a l. , 20 12; Lapierre et a l. , 20 13; Laro uche et a l. , 20 15). The
influence of landscape var iab les on riverine DOC export a lso has been add ressed
w ide ly fro m diffe rent perspect ives, such as c limate (e.g. Proku shkin et a l. , 2005 ;
Raymo nd & Oh, 2007; Tetzlaff et a l. , 2007; Kéihle r et a l. , 2008; Lepisto et a l, 20 14),
hydro logy (e.g . Ho rnberger et a l. , 1994; He in et a l. , 2003 ; John so n et a l. , 2006;
Dawson et a l. , 2008 ; Kawasak i et a l. , 2008), geo logy (e. g. Telmer and Yeizer, 1999;
Liu et al. , 2000; lnamdar & Mitche ll , 2006; Ca i et a l. , 2008; Llo ret et a l. , 20 11 ),
topography (e.g. D' Arcy and Carignan, 1997;· Jo hnson et a l. , 2000; Pacifie et a l. ,
20 1 0), so il (e.g. Aitkenhead and McDowe ll , 2000; Palmer et a l. , 200 1; Hae i et a l. ,
20 1 0), w ild fi re (e. g . Marchand et a l. ,2009; Laro uche et a l. , 20 15) , and land use/cover
(e.g. Carignan et al. , 2000; France et al., 2000; Wilso n and Xeno poulos, 2009;
Laudon et a l. , 2009; Regnier et al. , 20 15). T he export of DIC from watersheds to
- ··-- --· -----------------------
8
aquatic ecosystems, on the other hand , appears to be linked to regional geo logy,
especia lly underlying carbonate and siliceous rocks, as we il as land-use/cover plays
important roles in contro lling riverine DLC export (e.g. Liu et a l. , 2000; Raymond &
Co le, 2003 ; Zhang et a l. , 2009; Li et a l. , 20 1 0 ; Regn ier et al. , 20 15). Dornblaser &
Striegl (20 15) a Iso fou nd that DIC export great ly depends on subsurface flow in
boreal regions whi le in tropical region ore is mainly flushed from surface so il layers
(Markewitz et al. , 2001 ). The effects of other landscape variables on riverine DIC
export are not c lear or less explored . Overall , at a regional sca le, it would appear that
catchment topography and hydrology (D ' Arcy et al. , 1 997; lnamdar & Mitchell , 2006;
Mengistu et a l. 20 14), climate (Schindler et a l. , 1997) and catchment vegetat ion
(France et al. , 2000; Lepisto et a l, 20 1 4) are the most important drivers of DOC
export, whereas geo logy is mo re dominant than land-use in contro lling riverine DIC
export (e.g. Liu et al., 2000; Zhang et al. , 20 1 1; Tank et a l. , 20 1 2). Given that the
controls of c limate and hydrology on carbo n export from catchments have weil
understood relatively, topography and land-use/cover inevitably become the main
determinants of the regional differentiation of carbon exports from catchments. ln
particular, few studies have simultaneously addressed the contro ls of topography and
land-use/cover on DOC, DIC and TC exports from watersheds to aquatic ecosystems
and explored the functiona l and mechanical differences ofthe variab les in contro lling
the magnitude and composition of the carbon exported from the landscape.
Furthermore, previous studies on topographical controls on DOC export have shown
that the DOC export has strong negative relat ionships with catchment s lope ( e.g.
Eckhardt et al. , 1990; D'Arcy et al. , 1997; Hazlett et a l. , 2008) and catchment area
(Âgren et al. , 2007). However, the opposite fi nd ings that Wolock et al. ( 1 997)
reported a strong negative relationship between DOC concentration and catchment
9
area while Inamdar & Mitchell (2006) separate ly reported a positive one between
them have further blurred the catchment size effect on DOC export, but indicated that
the relationship is site-specifie. As for the studies on the re lationsh ip between DIC
export and topography, it was mainly limited to the influence of topographical
position on DIC concentration (e.g. Gburek and Fo lmar, 1999; Kling et a l. , 2000;
McGlynn and McDonnell , 2003) , according ly affecting riverine DIC export. With
respect to land-use/caver effect on carbon export, it has been found that the reduction
of natural vegetation due to loggi ng, farming, pasturing o r urbaniz ing co uld
pronouncedly increase riverine DIC exp01t (e.g. Daniel et a l. 2002; Raymond & Co le,
2003; Baker et a l. , 2008; Barnes & Raymond , 2009; Regnier et al. , 20 15) but had
varyi ng influence on DOC export to aquatic ecosystems. For examp le, most studies
fo und that forest-harvesting in catchments cou ld significant ly increase DOC export to
receiving waters (e.g. Carignan et al. , 2000; France et a l. 2000; Lamontagne et a l. ,
2000; Nieminen , 2004; O ' Driscoll et al. , 2006; Laudon et al. , 2009; Winkler et a l. ,
2009). However, sorne noted that c lear-cutting caused little change in DOC export
(Hobbie & Likens, 1973; McDowell & Likens, 1988; Moore & Jackson, 1989;
Piirainen et a l. 2002), and severa! even found that clear-cutting co uld significant ly
reduce DOC export from forested watersheds (Meyer & Tate, 1983; McLaughlin and
Phillips, 2006). As for farming effects on DOC expott, sorne reported that agricu ltural
streams (affected by crops and livestock grazing) were often of lower DOC expott
than streams in forest -, wet land- and heath land-dom in ated catchments (e.g. Cronan et
al. 1999; Royer and David 2005; Alvarez-Cobe las et al. , 20 1 0), wh ile sorne others
addressed that agricultural land use had no pronounced influence on DOC export
from the watersheds (Vidon et al. , 2008; Wilson and Xenopoulos, 2009). Reverse ly, a
significant positive relationship between agricultural use and catchment DOC export
1 0
was co llective ly supported by the 24-year sur.vey of cropping effect on organic
discharge from the Rhone river watershed in US A (Corre li et a l. , 2001 ), the statistica l
analys is of va ried bo rea l catchments in F in la nd (Rantakari & Ko rte la inen, 2008) and
th e fi e ld measureme nts in Zhu jiang River, China (Sun et a l. , 201 0; Zhang et al. , 20 Il) .
Nevertheless, the re lative importance of topography and land-use/cover on DOC, DIC
or TC export and the effects of landscape va riables on compositio n of tota l riverine
carbo n exported from the landscape have been rare ly repo rted . Espec ia lly in the
backgro und of glo ba l environmental change driven largely by anthro pogenic
d isturbances, it is thu s necessary to further exp lo re the re lative effects of topography
and land-use/cover change on the magnitude and co mpos ition of the carbo n expo rted
fro m watersheds to aquatic ecosystems, thus better understanding the ro le and
importance of the rive r carbon exported from the watershed in terrestria l and g lo ba l
carbo n cyc les.
0.3 Tota l carbon expo rt from watersheds to river sys tems
As mentioned above, most previo us studies have foc used separate ly o n exploring the
loading of indiv idual C components (TOC, DOC, POC and DIC) and degass ing of the
tota l carbon expo rted fro m the watersheds (Mulho lland and Watts, 1982; Hope et a l. ,
1994; A lvarez-Co belas et a l. , 20 12; Hoss le r and Bauer, 20 13). A ltho ugh a
considerable in s ight into the dynamics of spec ifi e carbon fo rms has been ga ined w ith
this approach, it neverthe less has yie ld ed a rather fragme nted view of the magnitude
and regulation of TC expo rt from watersheds, and of the re lative importance of
di ffe rent indiv idual carbo n spec ies and potentia l interactio ns between them. ln
addition, the few studies that have quantified TC expo rt and co mpared disso lved
carbon expo rt and degassed C0 2 and CH4, most of these, were limited to one or
l l
severa! small catchment(s) (Hope et a l. , 2001 ; Billett et a l. , 2008 ; Dinsmore et a l. ,
201 3; Wallin et a l,. 2013). lt is currently still diffi cult to produce an integrated view
of TC exported fro m landscapes to river systems and to characterize the
spatial -tempo ral diffe rences of TC and its compositio n. To develo p a better
understanding o f the expo1t of terrestrial carbo n to river systems requ 1res
simultaneo us observation of the main components of riverine carbon fro m the
landscape across a range of land scape types, watershed s izes and c limate, ba th
theo retica lly and practica lly. Only in this way, can the magnitude and co mposition of
total carbon expo 1ted to ri ver sys tems be quantified at di ffe rent space/time scales, and
hence a better understanding of carbon expo rt from watersheds be rea lized fro m the
integrated perspective.
0.4 Objectives of the thes is
The general objective of this thesis is to explore the magnitude and co ntra is of carbon
export fro m watersheds to rivers, scaling from reg io nal to g lo ba l leve ls . lt has been
divided into 3 sub-objectives: 1) to better understand natura l and anthro pogenic
effects on carbo n export from temperate watersheds and the response o f rive rine
carbon expo rt to human activities in the co ntext of g lo bal warming; 2) to identi fy the
magnitude of TC expo rt from boreal landscape, characterize the spatia l-tempo ral
a lteratio n of carbo n co mposit io n of the TC exported (DOC, DI C, POC, PI C, C0 2 and
CH4), and explo re the regional TC expo1t pattern in Quebec; 3) to upsca le the
reg ional studies on riverine carbo n expo rt to the glo bal sca le so as to cla ri fy the major
natural and anthro pogenic drivers on g lo bal riverine carbo n to the oceans thro ugh a
meta-analys is. T he reg io nal studies in the thesis are based on 127 ri ve r catchments
(83 and 44 in temperate and bo rea l reg ions, respeçtively) in Quebec for which the
1 2
Aquatic group at Université du Québec à Mo ntréal had made direct measurements
over the co urse of past 10 years, and whic h were used to explore the regio na l TC
export patterns . In addition, a g lo ba l dataset of publi shed data co mpris ing 566 rivers
was assembled to revis it the g lo ba l TC expo rt patterns in the context of g lo ba l
warming and re-estimate the g lo ba l ri ve rine carbo n budget fi·o m the land to the ocean
and to explo re natura l and anthropogenic drive rs on g lobal riverine carbo n expo tt at
the g loba l sca le.
The three sub-objecti ves of this thesis have been presented as the three chapters,
which are separate ly written in the fo rm of scientific artic le:
Chapter 1 The re lative influence of topography and land caver on inorganic and
organic carbon expo rt from catchments in so uthern Quebec, Canada.
Chapter 2 Magnitude and compos ition of ca rbo n expo rted fi·o m bo rea l catchments to
river systems in northern Quebec, Canada.
Chapter 3 A g lo ba l ana lys is of riverin e carbo n expo rt to the oceans.
T hro ugh these regio na l and g loba l studies, the expo tt of carbo n from watersheds to
aquatic ecosystems w ill be better understood and so rne benefici a i bases fo r the further
study on g lobal carbon cyc le and c limate change could be provid ed .
0.5 Genera l scopes and approaches
This thesis a ims at explo ring the carbo n export fro m watersheds to aquatic
ecosystems and integrating river systems into reg io na l and g lo ba l carbo n cyc les or
budgets. T he sco pe of the studies is foc used on carbo n export fro m land to river
systems, its main c limatic, hydro logie, geo morphic and bio log ical drivers, and the
potent ia l influence of hUJna n activities at the sca les va rying fro m a catchment to the
globe. Therefo re, a series of mixed approaches ( e.g. co llecting data, cha racteriz ing
catchments, making mode ls) are applied to ex plo re the regional spatia l-temporal
patterns of carbon ex port from watersheds to aquatic ecosystem in the natural
environment so as to upsca le this study from a catchm ent to the g lobe.
0.5.1 Regional riverin e carbon export from northern catchments
ln this thes is, 1 used the data of 127 rivers and streams in Quebec, ofwhich 83 and 44
are respective ly in temperate and borea l regions (see Figure 2), that had been
intens ive ly sampled, respective ly, fo r 1 to 3 years. For each sampled system, a series
of phys ica l (temperature, discharge, pC0 2 etc.) and chemica l (pH va lue,
concent rations of DOC, DI C and nutrients, and flu xes of C0 2 and C H4) were
measured or calculated, so as to link them to ri verine carbon exported fi·om the
landscapes. Topographie (e.g. slope, e levation, shape and area of a catchrnent) and
land use/cover (e.g. fo rest% , vegetation% , pasture%, wetland%, lake%) variables
were extracted from the dig itized maps using A reG IS 10 and used to characterize
each catchment. Then r iverine carbon exported tfom each catchment was calcu lated
as the product of discharge and DOC and DIC co ncentrations. T he evas io n of C0 2
and CH4 fro m surface waters was adjusted to the flu xes from the entire catchment
area . Fina lly , TC export ffo m watersheds to rivers was estimated from the sum of
these components, and 1 ex plo red the relative contribution of the various C
co mponents (DOC, DIC, C0 2) to TC ex port, and its drivers using a series sing le or
multiple linear regress ion mode ls.
l 4
Af·J•II ( ; 1
lm\•nriLI1":'
JB
r
Ot-:owo c•
QUCCEC
~'J~rvc- hur•.rve .4 J:>t!\.ll, 'irJC'.i
•
~·~,~(]
""" \
• •
f'RlN,"" [ Cr. ~~~:~~en oLWAI!L l'l14'JO
~ r tl ir.,<c$'1
Figure 2 T he research areas for the reg ional studies on riverine carbon expo rt (ET :
Eastern Townships; JB : James Bay; AB: Abitibi . JB and AB, two sub-regio ns of this
study area, are c lose ly ne ighbo red in no rthern lowland of Quebec)
0 .5.2 A meta-ana lys is up-sca ling to g lo ba l riverine carbo n expo ri to the oceans
1 carried out the meta-analys is of publi shed data on river C co ncentration and expo rt
that were co llected fro m publi cations and technica l reports publi shed mostly after
year 2000, covering 566 rivers wo rldw id e, dra ining 74% of glo bal exoreic area. The
catchments fo r w hic.h 1 co llected data are shawn in the map (F igure. 3 & Appendix
A). The data on catchment area and mult i-year average river discharge were taken
mostly from Meybeck and Ragu ( 1996) (www.unep.org), while others based on the
specifi e references. A li the river mo uth coordinates have been identified w ith Google
Maps. River length and e levat io n in watersheds were mostly co llected from
.1
Figure 3 The total sam pied catchment area (in brown) is 56% of the global terrestrial area, covering 74% of the global exorheic area (excluding Antarctica)
1 5
http ://www. waterfootprint.org . So il organic carbo n, percent land cove r/use and
percent carbonate in the catchments were extracted respectively fi·om the g lo ba l land
use/cover and geo logica l map using ArcG IS 1 O. We only inc luded studies tha t had
fo llowed ri verine DOC, DI C, POC or PI C concent ratio ns and expo rts fo r at least one
full annua l cyc le. Sorne big rivers studied by d ifferent groups, in which case we used
the average of the river carbo n concentrat io ns or exports reported in the va rious
studies. Multiple linear regress io n model is used to explore the re lat io nships of
nvenne DOC, DI C, POC and PIC exports to env ironmental va riables and human
activ ities . T he carbo n export mode ls we made are used to estimate the riverine carbon
export of the other watersheds to the oceans and the mi ss ing C data of the 566 ri vers,
and predict the future trend of g lo bal ri verine carbon expo rt fi·om land to sea in the
co ntext of g loba l warming and under the pressure of cropland expansion.
1 6
0.5.3 Stati stica l ana lys is
Simple and multiple linear regressio ns and covariance ana lyses (AN COV A) were
used to identi fy the re latio nship s between carbo n expo rt/concentratio n and
environmenta l variables and test s ig niti ca nt diffe rences in the reg io na l and g loba l
patterns of riverine carbon export. Data were log 1 0 transfo rmed so metimes so as to
satisfy the co nditions of ho moscedastic ity and normality. In a li the stat istical ana lyses,
the thresho ld for signitica nce is P<0.05 . Statistical ana lyses were carried out on JMP
9.3 (SAS in stitute) .
N.B. Refe rences cited in the introductio n a re presented at the end of the thes is.
C HA PTER 1
T HE RELATIV E IN FL UENCE OF TOPOGRAPHY AND LAND COYER ON
INORG ANI C AND ORG ANl C CA RBON EX PORT FROM CATCHM ENTS IN
SO UTH ERN Q UE BEC, CANADA
Mingfeng Li , Paul A. de l Giorg io, A lice H. Pa rkes and Yves T. Pra irie
l 7
Published in Journal of Geophysical Research: Biogeosciences, (2 01 5), 120,
doi: 10. 1 00212015JG003073.
Département des sc iences bio logiques, Université du Québec à Mo ntréa l, C. P. 8888,
suce. Centre-vill e , Mo ntréa l, Q uébec, H3C 3P8 Canada
N.B. References cited in this chapter are presented at the end of the thesis.
I. I Abstract
Expo rt of carbo n (C) fro m wate rsheds represents a key co mponent of local and
regio na l C budgets. We ex plo red the magnitude, variability and drivers of inorganic,
organic and tota l C expo rt fro m 83 temperate catchments in so uthern Qu ébec, Canada.
The average dissolved inorganic (DI C), disso lved organic (DOC) and tota l C (TC)
expor1s from these catchments were 4 .6, 5. 1 and I 0.2 g m-2 yr-1, respective ly.
Multiple regressio n models, us ing a co mbination of topographica l va riables
(catchment area, shape and slo pe), a long w ith land-caver va riab les (%vegetation,
%wetland , % lake and building density) , expla ined 34%, 62% a nd 53% of the
variability in the DI C, DOC, and TC expe rts, respective ly. An examinatio n of
va riance partitio ning in the models revea led that topography is s lightly more
impo rtant than land co ver in expla ining the variance in DIC ex port ( 19% vs 15%),
1 8
whereas land caver is much more important than topography in determining DOC
export (44% vs 18%). lnterestingly, %vegetation had a negative etfect on DIC export
but a positive effect on DOC export, suggesting that a change in land caver that
reduces vegetation (e.g. deforestation) would lead to modest decreases in TC export,
but large increases in the DIC/DOC export ratio. We conclude that topography and
land caver together determine DIC, DOC and TC exports. While topography is stat ic,
land caver can be altered, which will determine the quantity, form and by extension
the fate of C expo rted from these catchments. Fina lly, ann ual differences in export
values that are related to temperature and precipitation suggest that climate change
a lso have an impact on C export.
Key words: riverine carbon expo rt; DOC; DIC; topography; land caver; carbon cyc le
1.2 Introduction
The export of materials from land to fluvial networks and eventua lly to the ~cean has
been a major focus of research for decades (Likens and Bormann, 1974; Dillon and
Malot, 2005; Hassler and Bauer, 20 13). Not only are these land-derived materials
transported and transformed during transport, they also influ ence the functioning of
the receiving aquatic eco systems (Cole and Caraco, 2001; Aufdenkampe et al. , 20 Il).
More recently, latera l inputs of C from watersheds have been recognized as important
not just to in land and coastal waters, but a lso to our understanding of the terrestrial C
budget as we il (Cole et al., 200 7; Ballin et al., 2009; Buffam et al. , 201 1; Stets and
Striegl, 20 12; Dornblaser and Striegl, 20 15). Most of the d issa lved and parti cu la te
organic C expo rted from watersheds originates from terrestrial prirnary production
(Kardjilov et al. , 2006 ; Wilkinson et al., 20 13; Ga/y et al., 20 15). Sirnilar ly, most of
the DIC is ultirnately of biological origin because bicarbonate and carbonate ions are
1 9
derived from the interaction between respiratory so i! co2 and so i! minera is th ro ugh
the process of chemica l weathering (Liu et al., 2000; Zhang et al., 2009; Tank et al.,
20 12; Wang et al., 20 12). Regardless of its orig in , C expo•t ultimate ly represents a
loss of terrestriEtl primary production that needs to be acco unted fo r in regional C
budgets. How much C is !ost fro m watersheds, in what fo rm, and w hen these expo rts
occu r, a re issues of majo r biogeochemica l interest .
The fo rm in w hich C is exported is of c ritica l impo rtance in determining its fa te. It
large ly dictates the extent to whic h the C w ill e ither be reta ined in the local aquatic
system, re leased to the atmosphere, stored in sediments, or transpo rted downstream,
because di fferent fonns are not regulated by the same bio logica l, chemica l, and
phys ical processes. For exa mple, a significant portio n of the DOC entering aquatic
systems is transfo rmed by micro-organisms, such that it is e ither inco rporated into
bio mass or respired as an energy source (Tranvik, 1992; Ne.ff and Asner, 2001 ). DOC
is a lso affected by photo-chemica l processes that may minera lize into C0 2 (Lapierre
et al. , 201 3), render it more susceptible to micro bia l processes, or even tlocculate in to
POC (von Wachenfeldt et al., 2008, 2009). In contrast, the io nie fract io n of DIC (i.e.
C0 32- and HC0 3-) is like ly to be have in a mo re co nservat ive manner (Zhai et al. ,
2007; MacPherson et al., 2008), whereas the disso lved C02 fractio n will be largely
!ost to the atmosphere, w ith sorne be ing ass imilated during photosynthesis (Striegl et
al., 20 12; Wall in et al., 20 13) . Because DOC and DJ C are processed differently in
aquatic systems, the two C spec ies w ill impact C budgets in di ffe rent ways and thu s
sho uld be examined indi vidua lly. lt fo llows fro m this that the expo rt of these two
general fo rms of C (DI C and DOC) w ill like ly not be driven by the same fac tors .
2 0
A review of the literature shows that DOC export is at !east partly dependent on
aspects of catchment topography, su ch as si ope (Eckhardt and Moore , 1990; D'Arcy
and Carignan, 1997; Hazlett et al. , 2008), area (Mu/ho/land, 1997; France et al.,
2000; Agren et al. , 2007), or e levation (Johnson et al. 2000; Hazlett and Foster,
2002). However, land caver changes, such as deforestation, a lso have an influence on
DOC expo r1 (Meyer and Tate , 1983; Carignan et al., 2000; McLaughlin and Phillips,
2006; France et al. , 1996 ; Wilson and Xenopoulos, 2008) . Although wetlands are
wide ly regarded as sources of DOC, wet land loss due to human activities can have
varying effects on DOC export, depending on land use and management practices
(Royer and David, 2005; Armstrong et al., 201 0; Stanley et al. , 20 12). External
forcing, such as hydrology (Eckhardt and Moore, 1990; D 'Arcy and Carignan, 1997)
and c limate (Freeman et al., 200 1; Raymond and Ho , 2007; Raike et al. , 2012;
Lepisto et al., 2014) also strongly modulate DOC export.
Dissolved inorganic carbon export, on the ether hand , is influenced by catchment
geology, in particular by the presence of carbonate deposits in the catchment (Liu et
al. , 2000; Zhang et al. , 2009; Tank et al. , 20 12). Sorne studies have noted that
topographical position and basin e levat ion have a marked effect on concentration and
export of DIC from watersheds (Soranno et al., 1999; Kling et al., 2000; Finlay et al. ,
20 1 0). Others have shawn that changes in land caver affect DIC export, for example,
through logging, farming, pasturing or urbanization (Daniel et al. , 2002; Raymond
and Cole , 2003 ; Baker et al., 2008; Barnes and Raymond, 2009; Regnier et al., 20 13).
Topographical position and land caver likely interact with geology, and collectively
determine the degree of weathering of the underlying rocks, the principal source of
carbonate and bicarbo nate ions. This interaction between topography and land caver
underscores the need for an integrated approach .
2 l
Most studies to date have explored DlC and DOC export separately (Hope et al.,
1994; Wall in et al. , 20 1 0) , and a lthough there is considerab le insight to be ga ined
with this form-specific approach, it nevertheless yields a rather fragmented view of
the magnitude and regulation of total C export from watersheds. Since the relative
influence of topography and land cover may be different for D!C and DOC export,
chan ges in land cover may lead to shi fts not only in total C export, but a lso in the
DlC/DOC export ratio . Here we exp lore topographie and land cover predictors of
DIC, DOC, and TC exports in a set of 83 diverse catchm ents, located in the temperate
landscape of southern Québec. T he main objectives of this research were three-fold:
(1) to identify the relative importance of topography and land caver on DlC, DOC,
and TC export from temperate watersheds, (2) to exp lore the effect of potential land
cover changes on the DIC/DOC export ratio, and (3) to compare DlC and DOC
exports across 3 co nsecutive years ofvaryi ng hydrologie regimes.
1.3 Materials and methods
1.3.1 Study area
Est imat ing carbon export from a large number of catchments over severa! years
requires a cons id erable samplin g effort and necessar ily invo lves a compromise
between capturing the temporal (within streams) and spat ia l (amo ng streams)
components of variabi lity. As our focus centered on identifying the landscape drivers
most c losely associated with export rates, we opted to maximize landscape variability
while ensuring a sufficient temporal coverage to obta in robust estimates of annua l
export of the various carbo n form s. We therefore se lected 83 catchments in southern
Québec, Canada, abo ut 100 km east of Montreal (45° 12 ' 17''N - 45°49 '22"N,
71 °49 ' 34" W - 72°39 ' 50" W), ranging in area from 0. 13 to 520 km2 (Table 1 ). The
2 2
streams and rivers draining these catchments were sampled in 2004 and 2005 , and a
subset (32) were also sampled in 2003. The rivers sampled range from first arder
streams to fo urth arder ri vers. Vegetation in the watersheds is characterized by mixed
temperate fo rest, dominated by native sugar maple trees, mixed with basswood, red
oak, eastern white pine, eastern hemlock, and ye llow birch. Land use va ried greatly
among catchments, so rn e bein g largely forested, others dominated by agriculture or
pasturelands (Table 1 ). Geo logicall y, the study area is located in the transition region
between the Humber and Dunnage Zones of the Appa lachian Uplands striking
northeastwards; bas rolling topography, controlled by a series of we ll-developed
fa ults and fo lds, is underlain by carbonate-rich and non-ca lcareous sil iceous
sedimentary rocks, imbedded with mudstone and sandstone, and is dotted with
outcrops of metamorph ic and igneous rocks (Tremblay and St-Julien, 1990; Robinson
and Fyson, 1976; Paradis and Lavoie, 1996). The geo logy is thus quite diverse across
the 83 catchments, with the dominant rock type being sedimentary in 56 catchments,
vo lcanic in 18, and intrusive in the remaining 9. The surface depos its in the reg ion
consist mostly of glac ial ti ll and so rne glac io- lacustrine fin e sediment (Prairie et al.,
2002), such that the dominant general formation is till in 19 of the catchments studied,
mud in 6, although rock is the dominant formation in the majority of the catchments
in this study (58). a ils are mainly humo-fe rric podzo lic and dystric bruniso lic, with a
loamy to sandy loam texture and moderate to good internai drainage, such that the
dominant sai l arder is podzo lic in 49 catchments and bruniso lic in 23 catchments.
Gleyso lic so ils dominate in 10 catchments and only 1 catchment is dominated by
yo unger regoso lic so ils. Mean annual prec ipitation in the region is about 1000 mm, of
which 500-600 mm runs off (Natural Resources Canada, 2009), and mean daily
2 3
temperature in July is about l 8°C , while in January it is about -10°C (Environment
Canada, 1981-2010) .
1.3.2 Sampling , ana lyses and ca lculatio ns
The 83 sites were vis ited 4-6 times each in 2004 and 2005, at a bo ut 5-week intervals
during the ice-free period between March and N ovember (tota ling around 400 s ite
vis its per year) , and a subset of 32 sites were vis ited an add it io na l 6-7 times in 2003,
at abo ut 4-week in te rva ls between March and October (totaling around 200 site vis its) .
At each ofthese s ites, water samples were co llected and fil tered in s itu using 0.45 J.lm
syringe filters and transported to the lab in 40 mL g lass via ls w ith s ili co ne septa
(1-C HE M). DJC and DOC co ncentrations were determined fo llowin g ac idification
and oxid atio n w ith phosphoric ac id and sodium persul fa te, respective ly, using a
TOC IOJO tota l carbo n ana lyze r, equipped w ith an infrared C02 detector (01
Analytical, 2% precis io n of2 replicates per vial , 3% accuracy at 5mg L-1 standard) .
The carbon export (g m-2 yr-1) at any g iven s ite is defin ed as the produ ct of discharge
and C concentrati o n per unit catchment area, and it is the refo re essentia l to determine
the first two co mpo nents accurate ly. We determined discharge (m3 s-1) at each site fo r
each sampling date as the product of the measured stream cross-sectio nal area and
water ve locity (sampled at 0 .6 x stream depth at severa! stat io ns across the stream
w id th using the two-dimens iona l FlowTracker aco ust ic Doppler ve locimeter, SonTek).
These po int measurements are however, inadequate to capture the seasonal var iatio n
in discharge, and because the vast majo rity of these rivers are not gauged it was
necessary to deve lop a lternat ive approaches to reconstruct the fu ll annual discharge
pattern for each river. We deve lo ped an empirica l ca librat io n that wo uld a llow us to
estimate the discharge for any given river at any given poi nt in tim e, that is based on
2 4
Table 1. Stream and catch ment characteristics of the 83 study sites. Statistics for discharge and water chemistry were determined by first averaging ali measured values from 2004 and 2005 for each of the 83 streams, theo calculating the minimum, maximum, mean and standard deviation of these values (n=83). Statistics for topography, land cover, geology and soi! were obtained from digital elevation models, and maps of topography, land cover, rock type, surficial deposits, and soi! order, using GIS (n=83).
Varia bl e Min M ea n (SD) M :ax
Strea m c h aracter i st i cs
Dischar·ge (m 3 - 1 ) 0 .002 1 0.48 ( 1.0) 6. 1
Dl concentrat io n (mg L"') 1. 5 8.0 (4. 1) 28
DO con centrat io n (mg L -1) 1.9 7.7 (4.0) 19
pH 6 .0 7.2 (0.38) 8.1
A lka l in ity (J.leq L - 1) 80 530 (280) 1800
TN con centrat io n ( m g L · ') 0.14 OA6 (0. 19) 1 . 1
TP concentration (1-lg L - 1) 4. 1 26 ( 19) 1 10
Catchment topograp h y
Catchme nt area (km 2 ) 0 . 13 28 (79) 520
Average e levation (m) 150 3 10(57) 430
Average s lope ( ) 1.2 5. 1 (2 .8) 12
B 1 1.2 1. 6 (0.22) 2.4
Catchm ent la nd cover
% vegetation 42 83 ( 15) 100
%forest 27 77 ( 18) 100
% pasture 0 2 1 ( 19) 73
o/o wetla nd 0 1.1 (1.9) 9
o/o lake 0 3 .9 (5 .9) 25
B uildings perkm 2 0 9.9( 12) 56
Ca t c hm e nt geo logy a nd so il
o/o intrusive 0 1 1 (27) 100
% sed ime ntary 0 66 (4 1) 100
% volcanic 0 23 (37) 100
o/o rock 0 69 (4 1) 100
o/o ti ll 0 23 (38) 100
% mud 0 7 . 7 (24) 100
% bruniso l ic 0 22 (23) 9 1
o/o g leyso l ic 0 15 (22) 83
o/o organic 0 2.4 (4. 1) 23
o/o podzolic 0 42 (30) 100
o/o regoso 1 i c 0 0.95 (2.5) 17
------------------
2 5
the relationship between our point discharge measurements and discharge data from a
continuous gauging station located in one of our study watersheds, Trois-Lacs (TR)
(hyd rolog ic station 030101 : 45°4 7'30"N, 71 °58 '5" W operated by the Centre
d'expertise hydrique du Québec. The gauging station reports an error of ±5% when in
the stage-discharge relationship ). Our 612 instantaneous discharge measurements
divided by 1 58 the corresponding catch ment a reas were expressed as runoff (mm d-1 ),
and regressed against daily runoff at the TR gauging station, along with other
site-specifie attributes that modulate local discharge. Fo r this reg ion, the best
predictive model of daily runoff at any given site included elevation and catchment,
in addition to the measured daily runoff at the TR station:
log1oSEM = -0.629 + 0.892* 1ogSm + 0.00 188*E + 0.150*1ogJOAo ( 1)
where SEM is the estimated runoff at a given site (mm d·1), STR is the measured va lue
at the T R gauging station, E is the elevation of the sampling si te (m), and Ao is the
total catchment area upstream of the sampling site (km2). These est imates of daily
discharge generated by the empirical model correlated we il with our in stantaneous
discharge measurements, explaining 81 % of the variability (R2=0.8 1, p<O.OOO 1,
n=6 12). We used this relationship to extrapolate discharge to the entire year, including
winter months, for which we had no samples. White the re lationships that we built
between concentration and discharge were based on measurements taken during the
ice-free period, we have no reason to beli eve that these relationships wo uld not hold
for flows under ice-cover. At the gauged site, where discharge was monitored
year-round , the range of discharges recorded during the sampling season
encompassed the range of discharges seen in winter. Furthermore, on the spec ifie
dates when discharge was measured at va rious sites and compared to the gauged
discharge at Trois-Lacs on those same dates, the gauged discharges cover nearly the
2 6
full range of discharges seen throughout the year. This allowed us to derive annual
export and to compare our results with the literature, which overwhelmingly reports
annual expott .
Daily C expott was calculated as the product of daily discharge, estimated as
described above, and DIC and DOC concentrations measured at each site, divided by
catchment area . Applying an average DIC or DOC concentration derived from the 7
to Il point measurements assumes that discharge and concentration are independent,
wh ich is not al ways the case ( Wallin et al., 20 1 0; Birgand et al., 20 Il ). We tested this
ass umption by exploring the relationship between measured DIC and DOC
concentrat ion and measured discharge for each of our 83 sites using the data from ali
years combined. Fo r DI C, significant (p<O. OS) negative (dilution) relationships were
fou nd for 31 sites (p<O.OS), and no sites showed a positive (concentration)
relationship . For DOC, a significant dilution effect was found for only 2 sites
(p<O.OS), whereas 5 sites showed a significant concentration effect. For sites with
significant co rrelation between concentration and discharge, we used the
co rresponding site-spec ifie regression to estimate daily concentrat ion from daily
discharge. For sites with no signifi cant relationship between discharge and DOC or
DIC concentration, we applied the average concentration with the estimated daily
discharge in our calculation of DOC or DI C expott . An nuai DIC and DOC experts (g
m·2 yr·1) were then calculated as the sum of daily export va lues.
Particulate organic carbon (POC) export from a catchment was not measured but
rather estimated assuming a POC to DOC ratio of 0.1 , typica l fo r lotie systems in the
temperate forest (Schlesinger and Melack, 1981 ; Hope et al., 1994). Particulate
inorganic carbon (PIC) export was not included in TC export because prev ious
studies have shown that it acco unted fo r a very small fract ion of inorganic C (Aucour
2 7
et al., 1999) . T hus, in this study, TC expot1 was defin ed as the sum of DI C, DOC and
POC exports.
1. 3.3 Catchment to pography and land caver
The varia bles used to characterize the 83 catchments are listed in Table 1. Values fo r
topography and land caver were extracted from 1 :50,000 dig ita l topographie maps
(Natural Resources Canada, 2006) as we il as 1 :5 0,000 and 1 :250,000 land caver
maps (Natural Resources Canada, 1999) . Geo logica l data (surfic ia l geo logy and
surfic ia l materia ls) were obta ined fro m 1 :5 ,000,000 dig ita l maps (Natural Resources
Canada , 1995) and so i! data tram an ama lgamatio n of 4 sma lle r reg io nal ma ps
rang ing in sca le fro m 1 :20000 to 1: 126720 (!RDA, 2006). Statistics were extracted
fro m the ma ps us ing ArcMap 1 0 (ESRl). Here, average si o pe (0) was derived fro m the
digita l e levatio n ma del w ith 1 Om x 1 Om reso lution. Bas in shape index (BSI ), a
measure of watershed roundn ess, is defin ed as the ratio of the perimeter of the
catchment to that of a c irc le w ith the same area (Miller, 1953) :
BSl = P/(2-Y(n*(Ao))) (2)
where P and Ao are the catchment perimeter and catchment area, respectively.
Geo logica l va riables are ex pressed as a percent of tota l catchment area (Ao).
However, land caver and so it va riables are expressed as a percent of tota l catchment
area (Ao) minu s the area of the catchment covered by waterbodies (Aw), leav in g only
the terrestrial catchme nt area (Ao-Aw). We used two di ffe rent ma p laye rs of different
categorical reso lution to characterize the land caver pro perties of our catchments. In
the fir st land co ver c lass ification, the land scape was broad ly defin ed as vegetated,
un-vegetated, and water (BNDT, Natura l Reso urces Canada). The percent vegetated
derived from this laye r is a broad catego ry that inc ludes wooded areas and shrubland s,
2 8
but excludes pastures and agricultura l land s, and wet lands. The non-vegetated land
inc ludes pastures and agricultura l lands, as weil as bare rock (which is rare in our
landscape ), and therefore these two categories roughly correspond to " natura l" versus
" managed" land scapes . We further characterized the land scape usin g another
landcover layer that prov id ed a finer c lass ificatio n (Canada Land lnvento ry, Natural
Reso urces Canada, http://sis.agr.gc.ca/cansis/publica tions/maps/ index. html), and we
derived percent forest, pasture, wetlands and mines fo r each of our catchment. T he
areas co nsidered as forest inc luded the zo nes on land caver maps c lass ifi ed as
" product ive woodland", " no n-productive woodland", and "outdoor recreat io n", which
co nsisted of fo rested parks in these catchm ents. T he areas cons idered as pasture were
the zo nes on land caver maps c lass ified as " improved pasture and fo rage crops" and
" unimproved pastu re and range land" . To calculate percent wet land s, regio ns on land
caver maps that were coded as " swamp, marsh or bog" were merged w ith "wetland s".
Land caver categorized as cropland or urban was not present in the stud ied
catchments. Building dens ity is expressed as the number of buildings per square
kilo meter of te rrestria l catchment area. Ali the above land caver categories are
expressed as % of the terrestria l area in each catchment, whereas percent la kes is
the water area over the tota l catchment area.
1.3.4 Statistica l analyses
A princ ipal compo nent analys is was perfo rmed on the variables describing
topography, land ca ver, geo logy and sa il in Table 1 to explo re the multiple
re lationships among variab les. T hey were then offered fo r inc lu sio n in multiple linear
regressio n models predict ing D!C, DOC and TC export. T he models were buil t using
a mixed step-w ise se lectio n process, w ith p<0.05 as the conditio n fo r inc luding a
var iab le in the madel. Bath %fo rest and %pastu re from land caver maps were
2 9
excluded fro m these analyses as they were strong ly corre lated w ith the broader
category of %vegetation from to pographie maps (%forest: positive, R2=0 .73, n=83,
p<O.OOO 1; % pasture : negative, R2=0.72, n= 83, p<O.OOO 1 ), and were therefo re
co nsidered redundant. The inter-annu al va riability in DI C and DOC expo rt was
examined fo r a subset of 32 catchme nts usin g a one-way ana lys is of variance and the
Tukey- Kramer post-hoc test to ftnd significa nt di ffe rences amo ng three sequentia l
years (p<0.05) . Exports for the 32 sites were centered by express ing the expo rt fro m
each site in a given year as the di ffe rence re lative to that site's average expo rt over
the 3 years (2003, 2004, and 2005). This procedure a llowed us to examin e more
robustly inter-annua l diffe rences for streams w ith very di ffe rent average ex port.
1.4 Results
1.4.1 Carbo n expo rt
We observed a w ide range m export rates of both DI C and DOC across the 83
catchments studied . DIC export was 4.6 g m·2 yr·1 (average of 2004 and 2005 va lu es),
and ranged an o rd er of magnitude, fro m 1. 1 to Il g m·2 yr·1 (Fig ure 1 ) . Simila rly,
DOC export averaged 5. 1 g m·2 yr·1 over the same period, and ranged fro m 1. 1 to 13 g
m·2 yr·1 (Fig ure 1 ). As a result, TC expo rt averaged 10 g m·2 yr·1, and ranged fro m 2.5
to 18 g m·2 yr·1• Co mbining the uncerta inty of both di scharge and co ncentratio n
estimates, e rror propagatio n ca lculatio ns suggest that the ex port va lues have an
associated erro r o f abo ut 25%.
3 0
14
12
•,_ 10 >-
8 .9 t 0 ~ 6 (])
0 0 4 0
2 •
• 0
• • • •
•
•
• •
• • • • ~-- -... . - .
•
• . · .. ' ·f-• • • • •• • 1 . ...... . .. .- . . . . . .., .
.. •
••
2 4 6 8
DIC export (g m-2 y(
1)
•
10 12
Figure 1. DOC export versus DIC export for the 83 catchments . Exports are
expressed as the average of 2004 and 2005 measurements in g of C pe r square
meter of total catchment area per year.
14 ~ c 0
12
• 0 0
0 ~ 10 ~
>- / e B "! 0 E
8 • -9 • t 0 0.. x 0 Q) 6 • c
0 0 -e co u
4 0
• 2 0 •
~ • 0
0.1 10 100
catchment area (km2)
Figure 2. Carbon exported as DIC (solid squares) and DOC (open circles) in g m·2 yr" ' for the 83 catchments , average of 2004 and 2005 measurements, as a fun ction of total catch ment area . Significant correlations with catchment area are shawn for DIC export (thin line}, DOC export (thick line) and TC (dashed line , points not shawn).
3 1
Despite the similar range and magnitude of Dl C and DOC exports, there was no
sig nifica nt corre lation between the export of these two C spec ies. T he re lati ve
co ntributio n of the two disso lved constituents to TC expo rt thus varied cons iderably
among the catchments, w ith expo rt from some sites be ing overwhelm ing ly dominated
by inorganic C, and others by its organic co unterpart. T he rat io of DI C to DOC expo rt
ranged 20-fo ld , from 0 . 19 and 3.9, averag ing 1.1 , w ith 56 of the 83 catchments fa lling
in the range between 0.5 and 2.0. ln additio n, the range and magnitude of DI C and
3 2
DOC concentrations (in mg L· ') across the 83 s ites were s imilar (average of 2004 and
2005 va lues, Table 1 ), yet the re was no re lationship between co ncentratio ns of these
inorganic and o rganic co mponents for the region.
Overa ll , there was a s ignifi cant pos it ive spatia l scale effect on C expo rt (Fig ure 2),
such that DIC, DOC and TC exports inc reased w ith catchment s ize (log10(DICexport)
= 0.54 + 0. 11 *log10(Ao), R2=0. 19, p<O. OOOl , n=83; log,o(DOCexpo rt) = 0.56 +
0.12* 1og ,o(Ao), R2=0.1 6, p=0.0002, n= 83; log10(TCexport) = 0.90 + O. ll *logiO(Ao),
R2=0.33, p<O.OOOI , n= 83).
1.4.2 Factors influenci ng carbon expo1t
A principa l compo nent ana lys is of DIC, DOC and TC exports (average of 2004 and
2005 va lues) as weil as topographie and land cover variables demonstrates the large
degree of unco upling between DIC and DOC export, as these two variables· are
orthogonal to each othe r on the summ ary plot of the fir st 2 compo nents (F ig ure 3).
T he fir st two co mponents expla ined mo re tha n 50% of the variance in the data, w ith
co mpo nent 1 a ligning strong ly w ith topographica l va riables, such as catchment area,
s lope and e levation (34%), and component 2 a lig ning mo re with land cover variables,
su ch as %vegetatio n and %wetlands ( 18% ).
1.0
0.5
N 0.0 +-' c Q.) c 0 o._
E 8 -0 .5
%vegetation
TC export
buildings km·•
-1 .0 +---..------,-----r----;----.----.-----.----, -1 .0 -0.5 0.0
Component 1 (33.8 %)
0.5 1.0
3 3
Figure 3. Principal co mpo nent analys is of DIC, DOC and TC expe rts (average of
2004 and 2005 va lues) and key to pographie and land-cover va riables for the 83
catchments.
T he positio n of DIC and DOC exports at 45° to the axes revea ls tha t the export of
e ither C co mpo nent is re lated to a co mbinat io n of the topographica l va riables of
com ponent 1 and the land cover va riables of co mpo nent 2 . Not surpris ing ly, TC
expo rt was intermediate between DIC and DOC expo rts. T he multiple linear
regress io n mode ls presented in Table 2 th us incorporate a combinat ion of topography
and land cover variables, and expla in 34%, 62% and 53% of the variance in DIC,
DOC and TC expo rts, respect ively. Both DI C and DOC expo rts were posit ive ly
3 4
related to total catchment area (as shawn in Figure 2) . BSl and %vegetation both had
a significant negative effect on DIC export, but a sign ifi cant positive effect on DOC
export. ln addition, building density (a measure of human in fluence) was positively
related to DIC export, whereas wet lands were positively related to DOC export.
Fina lly, the presence of lakes in the catchment had a negative effect on DOC export
but none on DJC export. Variables describing geo logy (as e ither genera l rock
formation or surface material type) and so it type did not contribu te significant ly to
predicting C export. As mentioned in Section 2.4, %fo rest and % pasture were not
offered in the step-wise madel-building process, because of their strong correlation
with %vegetation .
Table 2. Multiple linear regression models predicting DIC, DOC, and TC export in g
m-2 yr1 (n=83 for each). Estimates of coefficients and corresponding p values are
given for ali variables offered during the step-wise selection process. Variables were
included in the mode! if p<0.05 (in bold) and the corresponding R2 values are shown.
DIC DOC TC Parame ter
Estimatc p value Estimatc P value Estima tc
Catchmenl area (lcm2)" 1.069 <0.0001 0.672 0.0323 1.412
Average elevation (rn) 0.7584 0.2181 Topography
Average slope (0) 0.2418 - 0.271 0.0041 -0.266
BSJ -2.088 0.0201 2.705 0.0068
%vegetation - 0.038 0.0017 0.061 0.0003
Land cover %wetland 0.8931 0.530 <0.0001 0.690
%lake 0.3783 -0.139 0.0002
Buildings per km2 0.036 0.0116 0.4498
Intercept 9.914 <0.0001 -3.423 0.1072 9.731
p value
0.0002
0.6454
0.0066
0.8220
0.5486
<0.0001
0.0601
0.8632
<0.0001
Rz 0.34 0.62 0.53
* Ca!chment area is log JO lransformod.
DIC Export
8.8%
- % welland [:=::J % vegetation
- build ings km-2
!:=::J % lake -BSI c=J Catchment area ~Slope
- unexplainedJ
"12%
3 5
DOC Export
6.2% 3.7%
Figure 4. Variance partit ioning in the multiple linear regression models of DIC and DOC export , showing the percentage of variability explained by each compone nt variable and the remaining variability, unexplained by the models.
Figure 4. Variance pa rtitio nin g in the multiple linear regress ion mode ls of DI C and DOC
export, showing the pe rcentage of va riabili ty expla ined by each compo nent varia ble and the
remaining va ria bil ity, unex pla ined by the mode ls.
An examina tio n of the sums of squares assoc iated to each va ri a ble in the multiple
regress io n mode ls a llows us to determine the re lati ve influence of topogra phica l and
land cover varia bles on C expo rt (Figure 4). T he topographica l variables (catchment
area and BSI) were s lig htly mo re important than the land cover varia bles
(%vegetatio n and building density) in predicting DI C expo rt, w ith topogra phy and
land cover expla ining 19% and 15% of the va riability, respecti ve ly. ln co ntrast, land
cover varia bles (%vegetatio n, % wetland and % lake) were more impo rtant than the
topographica l va ria bles (catchment area, BSl and slo pe) in predicting DOC export,
land cover and topography explaining 44% and only 18% of the variability in the
DOC mode !, respective ly. ln terms of TC expo rt, the topographica l var ia bles
(catchment area and s lo pe) and land cover (%wetland) expla ined roughly the same
amount of va riatio n (24% versus 29%, respective ly) .
3 6
The positive re latio nship of catchment s ize w ith both ore and DOC expo rts resulted
in an overa ll pos itive effect of catchment size on TC expo rt (Table 2) . ln contrast, the
oppos ing effects of BSI and %vegetation on DIC and DOC expo rt cance led each
othe r out and as a result, these variables had no overa ll impact on TC expo rt. The
pos itive effect of %wetland and the negat ive effect of s lope o n DOC export were
strong eno ugh to influence overa ll TC export, despite the ir lack of influence on DIC
export.
1.4.3 Inter-annual va riatio n in carbon export
The precedin g results were based on the average C expo rt fo r 83 bas in s in 2004 and
2005 ; howeve r, we a lso examined inter-annual va riation in C expott fro m 2003 to
2005 fo r a subset of 32 bas ins . Co ntinuo us measurements fro m 13 weathe r statio ns in
the study area revea l that 2005 was the warmest and wettest year, w ith 1 oc hig her
respective ly (ANOVA, R2 = 0.59, p<O.OOO 1, n = 96, Tukey- Kramer p<O.OOO 1)
(Fig ure 5). DOC expo rts were a lso s ig nificantly hig he r in 2005 than in 2004 and 2003,
w ith average DOC exports fo r the 32 bas ins of 6.1 , 5.0, and 5.2 g m·2 yr·1 in 2005,
2004, and 2003, respective ly (A NOVA, R2 = 0.3 1, p<O.OOO 1, n = 96, Tukey-Kramer
p<O.OOO 1) (F ig ure 5). As a consequence, TC exports were also s ig nificantly highe r in
2005 than in 2004 and in 2003, w ith average T C exports fo r the 32 bas ins of 13.6,
1 0.7, and 11.0 g m·2 yr· 1 in 2005, 2004, and 2003, respective ly (ANOVA, R2 = 0 .67,
p<O.OOO 1, n = 96, Tukey-Kramer p<O.OOO 1 ). T here was no inter-annua l di ffe rence
between exports in 2003 and 2004 for any C species .
3 7
Table 3. Loca l climate, gauged da ily discharge, as weil as discharge and DIC and
DOC concentrations measured in situ at the 32 sites in 2003, 2004 and 2005.
2003 2004 2005
Annual mean air temperature ("C) a 5.0 5.1 6.0
Annual precipitation (mm) a 1245 1026 1316
Mean (SD) of mean daily discharges at 13.4 (1 8.7) 12.7 (15 .9) 15.6 (23 .9) Trois-Lacs (m3 s·') b
Mean (SD) of mean daily discharges al 0.57 (0.77) 0.62 (0.8 1) 0.68 (0.97) Waterloo (m3 s-') c
Mean (SD) measured in situ discharge (m3 s·•) NA 0.30 (0.59) 0.59 (1.4)
Mean (SD) DIC concentration (mg L·') 8.7 (4.0) 8.9 (4.7) 9.8 (5.4)
Mean (SD) DOC concentration (mg L-1) 8.3 (3 .7) 8.2 (4.0) 8.7 (4.7)
a Data from http://cl imate. weatheroffi ce.gc.ca
b Data from https://www.cehq. go uv. qc.ca/sui vihydro/graphique.asp?NoStation=030 101
c Data from https://www.cehq. go uv.qc.ca/sui vi hydro/graphique.as p?NoStation=030343
1 .5 Discussion
The C exports and DI C/DOC export ratios that we measured for these 83 bas ins in
so uthern Québec are weil within the range ofvalues found in the literature. Our range
of DOC export (1 .1 to 13 g m·2 yr-1) is in very good agreement with that estimated by
Eckhardt and Moore ( 1990) in roughly the sa me area ( 1 to 18 g m·2 yr·1 ). The average
DOC export of 5.1 g m·2 yr·1 co rresponds to the mid-range of DOC exports reported
for Atlantic Canada (1.6 to 12.4 g m·2 yr-1) (Clair et al., 1994), fo r fo rested landscapes
in southeastern Canada (0.9 to 13.7 g m·2 yr-1) (Creed et al., 2008), or for forested
watersheds in other temperate regions of North America (0.3 to 4 1.7 g m·2 yr-1) (Hope
3 8
et al., 1994), and very similar to the average DOC export of the 6 g m-2 yr-1 reported
for wet temperate regions by Meybeck (1993). Similarly, our DIC export range of 1.1
to Il g m-2 yr- 1, and average of 4.6 g m-2 yr-1, were weil within the range of riverine
exports found in Europe (0.5 to 67.8 g m-2 yr-1) (Hope et al. , 1994), although they
~ere slightly higher than those fou nd in Atlantic Canada (0.04 to 4.19 g m-2 yr- 1,
average 0.71 g m-2 yr- 1) (Clair et al. , 1994) and were much higher than those found in
central Ontario (0.81 to 1.69 g m-2 yr- 1, average 1.12 g m-2 yr-1) (Dillon and Molot,
1997). As for TC export, our range of 2.5 to 18 g m-2 yr- 1 and average of 10 g m-2 yr-1
agree weil with TC export from north Atlantic rivers in the United States (3.7 to 15 g
m-2 yr- 1, average of 7.2 g m-2 yr-1) (Stets and Striegl, 2012), but is lower than TC
exports from European rivers at similar latitudes (e.g. TC exports for the Adige,
Danube and Po Rivers, which were 16.7, 12.4 and 30.1 g m-2 yr- 1, respectively)
(UNEF, 2003) .
The decoupling between DIC and DOC exports that we observed in our systems (Fig
1) has also been observed in other regions, leading to variations in DJC/DOC export
ratios bath within and across regions . In this regard , our DIC/DOC export ratio varied
widely across catchments (from 0.2 to 3.9), and the overall mean of 1.14 was much
higher than published DIC/DOC ratios in Atlantic Canada (0.0 1 to 0.86, average 0.13)
(Clair et al., 1994) and central Ontario (0.13 to 0.32, average 0.27) (Dillon and Molot,
1997). This inter-regional difference is largely attributable to differences in the
amount of wetlands and carbonate rocks, which relate to the production of sail DOC
and DIC, respectively. Atlantic Canada and central Ontario are lithologically
dominated by volcanic and granitic rocks, respectively, whereas most of our study
area, is underlain by carbonaceous sedimentary rocks (Paradis and Lavoie, 1996),
which contribute more DIC by weathering. ln addit ion, most of the catchments
3 9
studied in Atlantic Canada, are located on islands, where the soils are poorly
developed, thereby producing less DIC from soit respiration. Furthermore, the study
area in central Ontario has more wetlands (up to 25%) than ours (up to 9%), which
contribute more DOC and further lower the DJC/DOC ratio.
We designed this study to maximize spatial coverage and environmenta l gradients,
wh ile st ill capturing at least so me of the seasona l var iabi 1 ity in riverine d ischarge and
C concentration. Discharge is without doubt the most variable of these two
components, but we were able to reconstruct the annual discharge pattern by relating
our point measurements to a cont inuous discharge record in one of study streams
(n>600 point measurements). This approach is effective to capture both the total
runoff fi·om each st ream and the main features of the annua l hydrographs. With
regard to the temporal var iab ility in C concentrations, we examined the
mean-variance relationship for DIC and DOC concentrations, by plotting the variance
of ali co ncentrat io n measurements at a given site in a given year, V, versus the mean
concentration for that s ite in that year, X. Combining the 32 sites samp led in 2003
with the 83 sites samp led in 2004 and 2005 , there were a total of 198 site-years for
which we could compare the variance to the mean. Applying the resulting
mean-variance equations (Vo,c=0.032*Xo,c249 , R2=0.51 , p<O.OOO 1, n= 198;
Yooc=O.O 19*Xooc2·62, R2=0.67, p<O.OOO 1, n= 198) following Cattaneo and Prairie
( 1995) a llowed us to determine that no more than 4 samp les per year were req uired to
obtai n a mean concentration for a given site with a precision of 20%. As we visited
each s ite 4-7 times per year, the mean concentration calculated for any site shou ld
have an error of 20% or less , thereby confirming the adequacy of our sampling
strategy. Carbon concentrations are less temporally variable than nutrients such as N
and P (Moatar and Meybeck, 2007; Birgand et al. , 20 Il ), and a si milar precision was
4 0
obtained by Birgand et al. (2011 ) fo r tota l disso lved carbon sampled mo nthly in a
fo rested catchment. With our experimenta l des ign, we found mo re va riability in
carbo n expo rt amo ng sites than w ithin a year at a s ing le s ite, which a llowed us to
explore the drivers of carbon export across catchments of di ffe ring topographica l and
land cover character ist ics.
1.5. 1 Drivers ofTerrestrial Carbon Export to Aquatic Systems
While topography and land cover together expla ined only 34% of the va riability m
DIC expo rt, they expla ined 62% of the varia bi! ity in DOC expo rt, c learly illu strating
that DI C and DOC export are co ntro lled by diffe rent biogeochemica l processes.
Furthermore, whereas land cover and to pography were equa lly impo rtant in
determining DI C ex po rt (expla ining 15% and 19% of the va riability, respective ly),
land cover was c learly a stronge r driver of DOC expo rt than was topography
(expla ining 44% and 18% of the va riabil ity, respect ive ly). These results suppo rt our
hypothes is that a combinatio n of underlyin g topographical fea tu res and potentia lly
more dynamic land cover features are in vo lved in determining the va rio us fo rrns of C
exported .
Despite these di fferences, there was one dri ve r that was co mmo n to a li fo rms of C
export, whether DIC, DOC, or TC: catchment area was pos itive ly re lated to a li fo rms
of C expo rt, e ither a lone (F igure 2), o r in co mbinat io n w ith other etfects in multiple
linear regressio n models, exp la ini ng 15%, 4% and 16% of the va riab il ity in DIC,
DOC, and TC export, re pect ive ly (Table 2, Fig ure 4) . T his is in contrast to the
finding of Agren et al. (2007) that sma ll headwater catchments expo rt the most
terrestria l DOC, in a co mpari so n of 15 sub-catchments in Sweden rang ing in s ize
fro m 0.03 to 22 km2 • lt is di ffi cult to expla in why catchment area sho uld play a ro le in
4 l
how much C is exp01ted per sq uare kilo meter. We fo und no sig ni fica nt re lat io nship
between carbon concentratio n (D!C, DOC, or TC) and catchment area (p>0.05, n=83,
usin g the average of 2004 and 2005 co ncentrations for each site and using e ither
terrestr ial or tota l catchment area). T his is inco nsistent w ith the posit ive re lationship
with DOC co ncentration reported by Jnamdar and Mitchell (2006) and the negat ive
re lat io nship w ith DOC concentratio n reported by Wolock et al. ( 1997). T h us, the
ultimate driver is like ly hydro logy, and in this regard , we fi nd a relat ive ly strong
positive re lat io nship between catchm ent s ize and runoff (parameters), and a lso w ith
catchment e levat io n. T he reaso ns unde rly ing this pos it ive re lart io nship are not c lear,
but could be re lated to shifts in la nd cover patterns w ith catchment s ize. ln pa rticular,
the re was a trend fo r larger catchments to have less fo rest and vegetat ion cover and
highe r proportion of agricultura l land s, and it has been suggested that runoff actu a lly
inc reases with defo restation and human-induced landscape a lternat io ns (A llan, 2004;
Maetens et al., 20 12).
1.5. 1.1 Drivers of DI C Expo tt
A fte r catchment a rea, %vegetatio n in the watershed was the seco nd most important
facto r determ ining D!C export, w ith less vegetated bas in s export in g mo re DI C. This
agrees with prev ious work that has shown that defo restat io n or co nvers ion of natura l
vegetat ion into pasture inc reases DI C expo rt fro m the landscape, eithe r when
co mparing DIC export across bas in s (Baker et al. , 2008; Rantakari and Kortelainen,
2008; Regnier et al. , 20 13) or when fo llow ing DI C export within a bas in as its land
co ver changes over ti me (Raymond and Cole, 2003 ; Yan et al., 20 13). T here are
severa! processes that can exp la in the observed pattern between %vegetat io n and DI C
ex port. ln o ur study regio n, unvegeta ted areas often co rrespo nded to pasture lands
which, in co mpar ison w ith forest so ils, tend to have hig he r so it respi rat ion rates
4 2
(Smith and Johnson, 2004; Kellman et al. 2007), leading to elevated soil C02 and
greater weathering potential (Likens, 201 0; Bayon et al. , 2012) . Previous studies have
shown that replacing forest species with forage or farm crops results in a decrease in
the soil C/N ratio , leading to a more rapid mineralization of soil organic matter and
litterfall , thus increasing groundwater DIC and soil C02 (Marland et al. , 2004;
Hedley et al. , 2009). Moreover, deforestation, due to agriculture or pasture, can
intensify weathering (Likens, 201 0; Bayon et al., 20 12), th us releasin g more
bicarbonate and carbonate ions into river water. Therefore reducing the vegetation
coverage and/or shifting land uses to agricultural or residential may increase DIC
export by increasing so il respiration rates and weathering.
In addition, C geochemistry and water chemistry in river systems are dependent
largely on lithological variability m carbonate/silicate-dominated terrains
(Amiotte-Suchet et al. , 2003 ; Zhang et al. , 2009). Our study area is located in the
transition region between the Humber and Dunnage Zones, underlain by
carbonate-rich and non-calcareous s il iceo us sedimentary rocks and ma fic volcanic
rocks associated marine sed im ents, respectively. Particularly, in the Humber zone
there are the world 's largest asbestos mine, and severa! talc mines (Castonguay and
Tremblay, i003), both of which are hydrous magnesium silicates that are often
associated with carbonates and easily hydrolyzed to release HCOJ·. The fact that 9 of
the 10 catchments with DI C export of more than 6.6 g m·2 yr· 1 are in the Humber
Zone (except the stream outflowing Lake Nick), further highlights the importance of
carbonate and silicate rocks in controlling riverine DIC export from the catchment.
DIC export also increased with building density. Buildings and their residents are not
point sources of DIC but higher building density usually results in land clearing and
road construction, causing an anthropogenic increase in erosion and therefore DIC
4 3
export from so ils. This pos itive effect is strong ly suppo rted by previo us studies
(Daniel et al. , 2002; Bornes and Raymond, 2009; Zeng et al., 201 1 ).
Bas in shape index, BSI , a lso played a s ig nificant role in co ntro lling DlC export. The
greater the departure fro m a c ircular bas in (BSl> 1.0), the less DI C that is exported .
T hi s negative re latio nship may be due to hydro logica l pathways be in g more
co nvo luted in bas in s w ith mo re complex shapes. Fo r example, c ircular catchments are
mo re prone to fl ooding than e longated ones (Waugh, 1995 ; Rasool et al., 20 Il ),
leading to hig her erosio n and flu shing out ofva rio us fo nns of terrestria l DIC.
1.5. 1.2 Drivers of DOC Export
The two variables that expla ined most of the va riatio n in DOC expo rt were % lake and
% wetland . Bas in s co nta ining mo re lakes expo rted less DOC, w hich highli ghts the
ro le of lakes as s inks of terrestria ll y-derived organic matter (Larson et al., 2007) .
Temperate and borea l lakes accumulate large amo unts of terrestria l C in the ir
sedim ents (Fer/and et al. 20 12; Tranvik et al. 2009), and a lso deco mpose and emit a
portio n of this te rrestria l DOC as C0 2 and CH4 (Larson et al., 2007; Dinsmo re et al.,
20 13). A ltho ugh the catchments in this study did no t co nta in many wetlands
(max imum 9% coverage) , wetlands still played a role in sha pin g DOC expo rt , as has
been reported fo r othe r reg io ns (Eckhardt and Moore, 1990 ; Dillon and Malot, 1997;
Huntington and Aiken, 20 13). T hese two land co ver va ria bles are susceptible to
anthro pogenic and c lim ate change through dra inage, damming, and changes in the
hydro logie reg ime . T herefo re changes to the amo u nt and extent of wetlands and lakes
in a watershed w ill affect two impo rtant so urces and s inks of DOC and thu s the
moveme nt of te rrestria l C into the aquatic system and the atmosphere.
4 4
We fo und that DOC export was a lso co rre lated w ith %vegetation and BSI, but the
direction of the corre lation was opposite of that fo r DI C export, hig hli ghting the
independent nature of DOC and DIC expo rts (F igures 1 and 3) . Altho ugh the
presence of vegetation lowered DI C expo rt, it increased DOC expo rt in these bas ins,
which agrees with previo us work (Meyer and Tate, 1983; France et al., 1996) . T he
positive re lationship between DOC expo r1 and %vegetatio n refl ects the fact that most
riverine DOC is ultimate ly deri ved from land vegetatio n (via direct litter input and
leaching) and so il s (v ia micro bia l activ ity, root exudation, leaching and eros io n of
organic matter) (Spitzy and Leenheer, 199 1 ). T he in fl uence of BSI on DOC export
was oppos ite to that on DI C expo r1, w ith e longated mo re complex hig h BSI bas ins
exporting more DOC than ro und, less complex low BSI bas ins. Simil a rly, Pacifie et
al. (20 1 0) showed that a mo re e lo ngated bas in oft:en has a highe r ratio of ri parian to
upland area and can export mo re DOC to river systems. As mentio ned above, that
larger catchments expo rted more C, but in this reg ion, la rger watersheds were a lso
characteri zed as hav ing a lower average slo pe (R2=0. 17, p=O.OOO 1, n= 83) and lower
average e levatio n (R2=0.08, p=0.0080, n=83), a ltho ugh these co rre lations are weak.
Once entered into a multiple regress io n with catchment area as a factor, e levation had
no effect on C expo rt; however, watersheds w ith a fl atter average slo pe expo rted
more DOC and TC, independent of the effect of catchment size. Gentler slopes
fac ilitate wetland fo rmation, leading to mo re DOC productio n and ex po rt (D 'A rcy
and Carignan, 1997), and a Iso have lo nger wate r res idence times, a llowing more time
for so il DOC to leach into so il water and ne ighboring waterways (Hazlett et al., 2008;
deCatanzaro and Chow-Fraser, 20 Il ).
1.5.1.3 Drivers of TC Export
4 5
We were able to expla in 53% of the variatio n in tota l C export using two
topographica l variables, catchme nt area and slope, and one land cover variable ,
%wetland . T he pos it ive effect of catchment area on both DI C and DOC exports
results in a s imil ar influence on TC export, like ly thro ugh its effect on d ischarge, as
discussed above. T he negat ive effect of slo pe on DOC was strong eno ugh to result in
a negat ive effect on TC expo rt, expla ining 8% of its va riability, desp ite the lack of a
re lat ionshi p between slo pe and DI C export. Similarly, the effect of inc reas ing TC
expo rt w ith inc reasing wetland coverage arose so le ly because of the important ro te of
wet land s in co ntro lling DOC export, as wetland s did not play a ro te in DlC expo rt.
This land cover featu re of the catchment ex pla ined 29% of the va riability in TC
expo rt. ln co ntrast, a ltho ugh BS I and %vegetatio n played impo rtant ro tes in both DlC
and DOC exports, they acted in o ppos ite directions on the two C spec ies, and as a
result, had no overa ll impact on TC export. As we observed fo r DI C and DOC export,
TC export is influenced by a co mbinat ion of topographie and land cove r effects,
expla in ing 24% and 29% of its varia bility, respect ive ly. Because the drivers of DI C
export and DOC export are qui te di ffe rent, the model of TC export prov ides a
simplified summ ary of what influences the move ment of terrestria l C to aquatic
sys tems, white hiding the complex ity of what influences the movement of indi vidua l
C spec ies.
Despite the re be ing ev idence in the literature fo r the effect of so it ty pe and geo logy
on C expo rt, these fac tors did not emerge as s ig ni fica nt drivers in our watersheds. We
used ma ps of geo logy and so it to div id e the catchments, based on area l percentages
(Table 1 ), in to 3 mutua lly exc lu sive categories of rock type ( in trusive, sedim entary
and vo lcanic) as we il as 3 mutua lly exclu sive categories of surfic ia l deposits (rock,
t ill and mud) and 5 mutua lly exc lus ive categories of so it (bruniso lic, g leyso lic,
4 6
regoso lic, podzo lic and organic). We fo und one potentia l mode! of DTC expo rt that
inco rporated the percent coverage of sedim entary rocks and rocky surfic ia l depos its
but it is unclear why DI C expo rt would dec line w ith increas ing presence of
sedimentary rocks and rocky surfic ia l depos its. ln additio n to expla ining only a
marg ina l 4% mo re of the variabili ty in DI C export tha n the mode! in Table 2, it
required removing BSI as an effect and remov in g one outlie r s ite, and so this mode!
was co nsidered less appropriate fo r these catchments. There were no potentia l mode ls
for DOC or TC expo rt that inco rporated geo logy or so il. ln summary, we did not find
that geo logy or so il type played very important ro les in co ntro lling OTC, DOC and TC
ex port from the landscape.
1 .5.2 Influence of Land Cover on the Forms of Carbon Expo rted
A lthough vegetatio n coverage did not play a s ig nifica nt ro le in tota l C expo rt, it did
have an impact on the actua l nature of this export . We used the models in Table 2 to
project tota l C expo rt and its partition into DI C and DOC expo rts, under scenarios of
changing land use in term s of %vegetat io n, fo r two of o ur bas ins (Fig ure 6). ln the
case of the bas in that dra in s in to Lac d ' Argent, which currently has 92% vegetatio n
coverage, reducing the vegetatio n coverage to 40%, fo r example due to agricul ture or
urbaniza tion, wo uld result in an Il % decrease in C expo rt fro m the bas in (as
DI C+DOC) (our test using DIC+DOC, in stead of DIC+ I .1 *DOC, as TC expo rt
showed the same result a ltho ugh the coeffic ients are s li ghtly diffe rent), but a 3-fo ld
inc rease in the DI C/DOC expo rt ratio, fro m 0.8 to 2.2. The reductio n in vegetatio n
coverage would thus cause a shi ft in this bas in from a system that expo rts most of its
terrestria l Cas DOC, to a bas in that exports mostly DI C. Co nversely, for an inflow of
Roxton Pond, which current ly dra in s a watershed that is 57% vegetated, increas ing
the vegetatio n coverage to 100% would result in only a 9% inc rease in C export,
----------------------------------------------------------------------------------------------
4 7
while the DIC/DOC export ratio wou ld be reduced to half, from 1. 1 to 0.5 (F igure 6).
ln this case the watershed wou ld shi ft from exporting equal amounts of D1C and
DOC to exporting mainly DOC. Land use change that modifies vegetation coverage,
such as deforestation or reforestation, wou ld therefore have a modest effect on total C
export, but wou ld greatly alter the form of C exported. Although deforestation is
widely regarded as one of the most common anthropogenica lly-dr iven land cover
changes, especially in developing countries (Nagendra, 2007) , many of the temperate
regions in Eastern North America and Western Eu rope have been undergoing
reforestation due to a decline in agriculture (Rudel, 1998; !PCC, 20 13). As DOC and
ore are processed differently in aquatic systems, changes in the form of terrestrial c
exported will lead to changes in the fate of this C , w ith DOC being mo re likely to be
mineralized and released to the atmosphere as C02 and CH4 than DIC, w hich may be
transported downstream in a more conservative manner. To summarize, reductions in
vegetation coverage wi ll shift the C export to favor the inorganic rather than the
organic forms of C, potentially leading to the terrestrial C being transported further
downstream, rather th an being re leased to the atmosphere through bio logical
processes in the aquatic system.
4 8
11 .0 11 .0 A B
..-- 10.5 10 .5 · ..... >-N 10.0 10 .0 'E g t::
9.5 9.5
0 0.. x Q)
9.0 9 .0
u 8.5 8 .5
0 20 40 60 80 100 0 20 40 60 80 100 20 20
c D
t:: 15 15 g_ x Q)
10 10 u 0 0 ü 5 5 0
0 0 0 20 40 60 80 100 0 40 60 80 100
% vegetation % vegetation
Figure 6. Carbo n expo rt as the sum of DIC export and DOC export in g m-2 yr-1 and the
DI C/DOC expo rt ratio ve rsus %vegetation fo r two examp le watersheds, an inflow to
Lac d ' Argent (pane ls A and C) and an in fl ow to Roxton Pond (pane ls B and D) . The
current vegetatio n coverage of the catchment is ind icated by an "X" in each pane l.
1.5.3 Inter-annual Var iation in Carbo n Export
The diffe rences in C expo rt observed in 32 bas ins over 3 consecutive years were
like ly driven by inter-annual va riations in temperature and prec ipitat io n, causing
in ter-annua l va riations in stream discharge (Table 3). Expo rt of both DI C and DOC
was about 25% hig her in 2005 (at 6.8 and 6 .1 g m-2 yr-1, respective ly) re lat ive to 2003
and 2004 exports (Figure 5) . In term s of temperature and precipitation, 2005 was a
wann , wet year and 2004 a dry yea r, as co mpared to a re lative ly average 2003. T his
resu lted in the mean dai ly discharge at the Tro is-Lacs gauged s ite be ing highe r and
more variable in 2005 than in the two preceding years (ANOVA p=0.0063 , n= I 096,
2003=A, 2004= AB, 2005= 8). Sim ilarly, at the Waterloo gauged site, mean dai ly
4 9
discharge was hig her and mo re va riable in 2005 (A NOVA p=0.0004, n= 1096,
2003=A, 2004=8 , 2005=8 ) . Discharge was therefo re sig nifi cantly higher in 2005
than in 2003, and this like ly drove the diffe rences in C expo rt, a pattern that has been
prev io usly repo1ted (Dillon and Malot, 2005; Dinsmore et al., 201 3). As C export is
the product of discharge and C concentration per unit catchment area, we a lso
examined inte r-annua l variability in concentratio n. Average DJC and DOC
co ncentratio ns were highest in 2005 (Table 3), yet there were no signifi cant
diffe rences in co ncentration among years. 1 n other words, va riatio n in C
co ncentratio n across the 32 sites was more important than va riat io n across the 3 years.
lnteresting ly, at the sca le of the individual site, we found a negative effect of
discharge on DI C concentratio n w ithin 3 1 of our 83 sites (dilution effects, outlined in
Sectio n 2 .2), yet at the regio na l sca le, the highest discharge year (2005) was
associated to the highest average DI C co ncentrations, and the hig hest average DI C
ex port fro m a li s ites co mbined. We suggest that trans ient increases in runoff and
discharge w ithin a catchment may not necessarily lead to increased DTC re lease rro m
so ils, and this may expla in the local dilution effects that we so metimes observed.
However, a systematic increase in overa ll prec ipitatio n and temperature, and the
assoc iated sustained increased in runoff and discharge, may act to increase overa ll
DLC and DOC export on an annual scale.
Acknowledgemen ts
Ali the data used in this study are ava il able fo r co llaborati ve use; contact Alice Parkes
(parkes.a lice@ uqam.ca) fo r in formatio n regarding access and handlin g. T his study
was jo intly funded by the Nationa l Science and Eng ineerin g Research Counc il of
5 0
Canada (NSERC) Strategie Projects Grant Program (SPG) and the Program for aiding
developmental and environmental research (PARDE), awarded to Y. Prairie, as wei l
as the NSERC Hydro-Québec lndustrial Research Chair in Carbon Biogeochemistry
in Boreal Aquat ic Systems (CarBBAS Chair), held by P. del Giorgio, and by a
scholarship from the Fonds québécois de la recherche sur la nature et les technologies
(FQRNT), given to M. Li . Thanks to Jean-François Lap ierre, Marie-Eve Ferland,
François Guillemette, Dominic Vachon and Martin Berggreri for their va lu able
statistical and academie assistance.
5 1
CHAPTER Il
MAGNITUD E AND COMPOSITION OF CA RB ON EX PORTED FROM BOREAL
CATC HM ENTS TO RIVE R SYSTEMS IN NORT HE RN QU ÉBEC, CANA DA
Mingfeng Li, Yves T. Prairie, and Paul A. de l G io rg io
Being preparedfor Global Biogeochemical Cycles
Gro upe de Recherche Interuniversitaire en Limno logie et en Enviro nnement
Aquatique, Département des sc iences bio logiques, Université du Québec à Mo ntréa l,
C. P. 8888, suce. Centre Ville, Mo ntréal, Québec, H3 C 3P8 Canada
N.B. Refe rences c ited in this cha pte r are presented at the end of the thesis.
2. 1 Abstract
Rivers play a major ro le in regio nal and g lo ba l carbo n (C) cyc ling by channelin g and
processing la rge amount of C that is de rived fro m land . T he form of the C exported
fro m watersheds to flu via l systems determines the biogeochemi ca l ro le and fate of
this C, yet few studies have simultaneo usly assessed the majo r fo nns of C ex ported
fro m land to rivers. Here we have quantified ri ver-mediated ex port of disso lved
organic and ino rganic C (DOC and DIC), as we il as the integrated aquatic emiss ions
of both C02 and CH4, fro m 44 bo rea l catchments that range w idely in size,
topography and land cover. Our results show that DOC and DIC expo rts averaged
9. 1± .3 and 2 .8± 1.9 g c m-2 (catchment) yr-1, respect ive ly, whereas tota l aquat ic co2
and C H4 emiss io ns averaged 3. 1±3.6 and 0.1 ±0. 1 g C yr·1 per m2 catchment,
respect ive ly. The resulting tota l C (TC) export was seasona lly very variable, driven
5 2
mostly by the annua l runoff cyc le , and ave raged 15 .6±5.3 g C m·2 yr·1• DOC
dominated on ave rage this TC export over the annua l cyc le (59%), but aquatic C0 2
emiss ions were a majo r co mponent of TC expo rt in a li catchments (average 20%).
Our results confi rm that DOC and DIC exports are mostly driven by runoff but
further regulated by fu ndamenta lly di ffe rent env ironmenta l fac to rs, and that wetlands
are a majo r so urce of DOC expo rted to rivers, but further demo nstrate that lakes
within the catchment are a strong DOC s in k, such that the net expo rt of DOC results
fro m the ba lance between them. C02 emiss ions replace DOC expo rt as the ma in
latera l C export w ith increasing vvate r coverage in the catchment. T he annua! TC
exported via rivers is w ithin the range of net ecosystem productio n (NEP) that has
been estimated fo r these boreal landscapes, but it is it still unc lear w hat co mponents
of this to ta l ri ver ine export, if any, may be inc luded in these N EP estimates.
Regardless, this river-med iated lateral loss of C has the potentia l to fund amenta lly
a lter our perception of the ro le of these bo rea l land scapes as so urces or s inks of
atmospheric co2.
Key words Riverine carbo n; DOC; DI C; greenhouse gases ; bo rea l catchm ents;
carbon cyc le.
2.2 Introductio n
Rive rs are a fundamenta l compo nent of the g lo ba l C cyc le, processing C that
o rig inates in the terrestri a l biosphere, transporting it to the oceans and returning it to
the atmosphere. lt is now recognized that a s izable fractio n of watershed terrestria l
net primary producti vity (NPP) is channe led to ri vers, but whereas there is a
re lat ively strong consensus that the tota l amo unt of C de livered to the oceans by
rive rs wor ldw ide is in the range of 0.9 Pg C y- 1 (Meybeck, 1982 ; Cole et al., 2007);
5 3
the re is still much uncerta inty regarding how much C is actua lly exported fro m land
to rivers. lt is now recognized that the re is a s ignificant but va riable amo unt of
processing of ino rganic and espec ia lly organic C of te rrestria l o rig in during trans it
within river ne tworks (Cole et al., 2007), such that the amo unts of C reaching the
ocean do not necessarily reflect the C that was orig in a lly exported fi·om land . ln fact ,
the estimates of C export fro m land to rive rs have systematically increased over the
past decade, to current estimates that are in the order 2.5 to 3. 1 Pg C annua lly
(Tranvik et al., 2009; Battin et al., 2009), and so have the estim ates of the portion of
this c that is buried in aquatic sedim ents, and returned to the atmosphere as c o 2. lt is
c lear that there is still much uncerta inty concernin g not only the magnitud e but a lso
the regulatio n of these compo nents of the g lo ba l C cyc le.
T he fo rm of the C exported from watersheds to flu vial systems is key not only. to the
fun ctio ning of these aquatic aquatic ecosystems, but to the actua l biogeochemica l fa te
of this C in the land scape. Fo r exa mple, whereas D!C expo rted fro m so ils tends to
trans it thro ugh aquatic networks w ith re lative ly little a lteratio n, DOC tend s to be
transfo rmed and degraded thro ugh bio logica l and photochemi ca l processes, fue ling in
s itu metabo lism in the rece iving systems, and further fu e ling C0 2 and CH4 emiss io ns
from these ecosystems. So il-deri ved C0 2 and C H4, on the o the r hand , will tend to
flu x o ut to the atm osphere, a lthough a portio n w ill a lso be transpo rted downstream
togethe r with the DOC and DIC. Over the past decade, there has been inc reas ing
interest and research seeking to establi sh the magnitude and the regulatio n of each of
these compo nents of river C dynami cs. For example, studies have identi fied the ma in
fac tors driving DOC export to ri vers, inc lud ing regional prec ipitatio n (Clair et al.,
1994; Dinsmore et al. , 201 3), runoff (Brinson, 1976; Raymond et al., 2007), land use
(Barnes and Raymond, 2009; Regnier et al., 201 3), catchme nt s lo pe (Eckhardt and
5 4
Moore, 1990; Dosskey and Bertsch, 1994; Hazlett et al. , 2008; Li et al., 20 15), sail
C:N ratio (Aitkenhead and McDowell , 2000), pH (Brooks et al. , 1999), and the
density of lake and wetland systems in the catchments (Koprivnjak and Moore, 1992;
Dillon and Malot, 1997; Fer/and et al. , 20 12).
Dissolved inorganic C (DlC), on the other hand , appears to be strongly influenced by
catchment geology, in particular by the presence of carbonate deposits in the
catchment (Liu et al., 2000; Zhang et al. , 2009; Tank et al. , 20 12), and topographical
position and basin e levation (Soranno et al. , 1999; Kling et al. , 2000; Finlay et al.,
20 i 0; Li et ai., 20 i 5). Others have shown that land co ver change affects DIC export.
For example, the reduction of natural vegetation due to logging, farming , pasturing or
urbanizing are ali believed to increase riverine DIC export (Daniel et al. , 2002;
Raymond and Cole, 2003 ; Baker et al., 2008; Barnes and Raymond, 2009; Regnier et
al., 20 13 ; Li et al. , 2015). Further, it has been known for decades that most streams
and rivers are supersaturated with C02 (Kiing et al., 1991 ; Cole et al. , 1994), and CH4
(Billett and Moore, 2008; Bastviken et al. , 2011; Campeau et al., 2014), but the
evasion of C02 and CH4 from river systems ha.s only recently been recognized as an
important regional source of atmospheric greenhouse gases (GHG) (Butman &
Raymond, 2011 ; Bastviken et al., 2011; Raymond et al. , 2013 ; Campeau et al. , 2014),
and the number of studies focusing on river C gas evasion has increased
exponentially in recent years.
One of the main patterns to emerge from this collective body of work is the fact that
the various forms of riverine C (DIC and DOC export, C02 and CH4 transport and
emission) are regulated very differently from each other, and that therefore the
contrais of total C export from land to ri vers, and the fa te of this C are more complex
5 5
than what were o rig ina lly thought. One of the ma in cha llenges that still remains in
arder to reso lve thi s co mplex ity is tha t the data on C export is still fragmented and
lacking integratio n, s ince most studies to date have focused on a spec ifie C species
(Mu/ho/land and Watts, 1982; Hope et al., 1994; Alvarez-Cobelas et al. , 20 12;
Hossler and Bauer, 201 3), and in a limited range ofwatershed types. Very few studies
to date have simultaneo usly qu antified ali the ma in compo nents that make up the tota l
poo l of C that is expo rted from la nd to rivers (Bille tt and Moore, 2008; Polsenaere et
al., 20 13; Striegl et al., 20 12; Abri! et al., 2000), and fewer still have do ne thi s ac ross
a range of enviro nmenta l, geographie and c lim atic gradients (Butman and Raymond,
20 Il ; Stets and Striegl, 20 12).
ln this study we have explic itly assessed the magnitude, composition and regulation
of tota l C ex po rt from a w ide range of catchm ents that are located in the bo rea l reg ion
of Québec. The borea l biome represents one of the largest C poo l on the earth , where
a large proportio n of a li terrestria l organic C is stored in so ils and in peat lands (Molot
and Dillon, 1996). lt is a lso a landscape w ith among the highest dens ity of surface
waters in the world , and where freshwaters are mo re like ly to play a key ro le in te rm s
of regiona l C processing and transport. The spec ifie objectives of this study were: 1)
to quantify the dynamics of DOC, DI C, C0 2 and CH4 across a w ide range of rivers in
the boreal regio n of Québec; 2) to reconstruct the magnitude of tota l C export fro m
these borea l watersheds; and 3) to explo re how the magnitud e and compos itio n of this
tota l C expo rt to rivers varies across catchments and a lo ng enviro nmenta l, geograph ie
and c lima tic gradients.
2. 3 Mate ria ls and methods
2 .3. 1 Study area
5 6
Our general study area is located in the lowland reg io n of northe rn Québec, Canada,
w ithin the No r1hern C lay Be lt, which was created by lacustrine deposits from the
proglac ia l lakes Barlow and Ojibway. T he rivers we sampled and the ir respective
catchments are located in two dist inct sub-regio ns: South Abitibi (47-48°N, 78- 79°W)
and James Bay (48-49°N, 78- 79°W). Geo logica lly, this area is located in the Abitibi
sub-province of Canadian Shie ld. T he bedrock is composed of granitoid (50%),
vo lcanic (40%), and sedim entary ( 1 0%) rocks fo rmed ca. 2.7 billio n years ago and
covered by a thin layer of so il (Asselin et a l. 2006). The James Bay regio n is located
w ithin the black spruce - feath r mos bioc !imat ic domain, and is characterized by
extensive peat bogs and fens, whereas South Abitibi is w ithin the ba lsam fir (A bies
balsamea L. Mill.) - paper birch (Betula papyrifera Marsh) bioclimatic doma in , and
has much Jess coverage of peat bogs (Bergeron et a l. , 2004). Fro m south to north
across the study area, mean an nua i temperature va ries from 0 to 1. 7 °C, and mean
annual precipitatio n from 880 to 975 mm (Asse lin et a l. 2006). Beaver dams are
ubiquito us thro ugho ut South Abitibi , especia lly alo ng 151 to 3'd order streams, wh ile
they are pract ica lly absent in James Bay, which is dominated by peatlands. Further
details of the s ites and of the sampling regime can be fo u nd in Cam peau et al. , (20 14) .
T he C0 2 and C H4 dynamics and flu xes to the atmosphere in these bo real rivers have
been previo us ly reported by Campeau et a l. (20 14) and Campeau and de l Gio rgio
(20 14). Here we combine these previo us results on gas dynamics with additio na l data
on DOC and DIC concentrations and river discharge to assess the magnitude of C
ex port fro m these bo rea l catchments, and in particula r to derive est imates of tota l
watershed C export that inc lude not only DI C and DOC transpo rt by rivers, but a lso C
gas emiss ions by both rivers and lakes w ithin these catchments.
5 7
2.3.2 Sampling and chemical analyses
In this study we use data collected from 44 sites, 30 located in South Abitibi and 14
located in James Bay, ranging from Strahler Order 1 to 7. Thirteen of these rivers
were visited 8 times each from May 2010 to May 20 Il , at around 5 week intervals,
20 were visited three times between May and October 20 1 0, and 11 were visited once
in mid-summer 2010. Water was sampled approximately 10 cm below the water
surface and filtered in situ using 0.45 ~-tm syringe filters and then sealed, refrigerated
and transported to the lab in 40 mL glass vials (1-CHEM) for chemical analyses.
Concentrations of DIC and DOC were determined following acidification and
oxidation with phosphoric acid and sodium persulfate, respectively, using a TOCI010
total carbon analyzer, equipped with an infrared C02 detector (OI Analytical, 2%
precision of2 replicates per vial, 3% accuracy at 5 mg L-1 standard).
2.3.3 Discharge and DOC and DIC flux calculations
Carbon expo11 of each stream was calculated as the product of the water loading and
the water C concentration (mg L-1), and therefore it is essential to accurately
determine both components. During the study period, we had pressure sensors
(True-Tracks) installed in four additional rivers and streams for continuous
monitoring of river water levet. For each of these streams we developed an empirical
discharge/water levet relationship based on the channel morphometry, which we used
to estimate the daily discharge of each of these 4 rivers. ln addition, the daily
discharges of Harricana and Kinojévis rivers were obtained directly from the
government-operated continuous gauging stations (hydrologie stations: 043012 and
080101) (http://www.mddelcc.gouv.qc.ca). Based these 6 sam pied streams and rivers,
we obtained an average daily runoff (mm d- 1) curve for the entire water year (Figure
5 8
1 a), and this average regional curve was then used as the local runoff pattern to
estimate daily discharge of a li the sampled rivers based on their respective watershed
areas. There was good overall agreement between the discharge est imated this way,
and the actual measured discharge in our point samp ling across a li of our rivers
(R2=0.84, n= 113, p<O.OOOJ) (Figure 1 b).
We measured DOC and DIC concentrations at each samp ling date, and these
concentrations need to be extrapo lated in time in arder to calculate da.ily export.
Previous studies have shawn that there may be both concentrat ion and dilution effects
reiated to shifts in discharge (Li et al. , 20 15). We explored this possibility by
assessing the concentration versus discharge relationships of ali the individual
streams using ANCOYA, and testing the significance of the resulting s lopes. The
results show that the daily runoff had a significant overall negative (di lution) effect
on DJC concentration (R2=0.62, RMSE=0.2481 , n= 165 , p<O.OOOl), and a sign ificant
positive (concentration) effect on DOC concentration (R2= 0.68, RMSE=0.151, n= 169,
p<O.OOOl). We used the resulting s lopes and the river-specifie DOC or DIC intercept
offset to correct for discharge-related shifts in DOC and DIC concentration for each
river. Daily C export was then calculated as the product of daily runoff and daily C
(DOC and DIC) concentration, and annual DIC and DOC export was calculated as
the sum of daily export values for the whole water year. River POC concentrations
were not measured and therefore POC flux had to be approximated, which we did by
assuming POC roughly equal to 5% TOC for boreal forest eco-region (Ivarsson and
Janssen 1994; Hope et al. 1994). PIC flux was not included in the TC exported from
the catchments because previous studies have shawn that it accounts for a very sma ll
fraction of inorganic C (Aucour et al. 1999; Hassler and Bau er 20 13).
c, 6 %i Dat
e (J
une
1, 2
010
to M
ay 3
1, 2
011)
0.1
0.1 5
9
10
100
1000
Mod
ele
d 0
(L s
·')
Fig
ure
1 a.
Reg
iona
l da
ily
run
off
(m
m d
·') f
or t
he s
ampl
ing
year
(20
1 0)
, w
ith
the
erro
r ba
rs (
SD
), a
vera
ged
(fro
m t
he d
aily
disc
harg
es o
f si
x st
ream
s an
d ri
vers
dur
ing
the
wat
er y
ear
of
our
obse
rvat
ion
(Jun
e JS
t, 20
10 t
hrou
gh M
ay 3
Pt,
2011
). b
.
Rel
atio
nshi
ps b
etw
een
esti
mat
ed a
nd m
easu
red
disc
harg
e fo
r th
e 44
stu
died
riv
ers
(R2 =
0.8
4, n
=ll
3,
p<O.
OOO
1 ).
1000
0
6 0
2.3.4 Aquatic gas emissions
During the study period, C02 and CH4 concentrations (ppm) and fluxes (mmol m·2 d·1)
across the air-water interface were measured in ali the rivers (as reported in Campeau
et al. (2014) and Campeau and del Giorgio (2014)). C02 and CH4 concentrations
were determined in situ using the headspace technique, and fluxes (mmol C m·2 d· 1)
across the air-water interface were determined using the floating chamber technique,
as described and reported in Camp eau and del Giorgio (20 14). Measurements were
not made from December to March, when most of these rivers are frozen . The C
fluxes of December 201 0 were assumed to be 1/2 of those measured in November
201 0, because most ri vers and streams were ice-covered for approximately half of the
month, and we assumed zero fluxes for January to March. We a lso used the average
C02 and CH4 fluxes measured in over 40 lakes in the same study region and reported
by Rasilo et al. (20 15) to estimate the average monthly C02 and CH4 emission from
lakes across the study catchments. Measurements were available for May, June, July
and October 2010, so we linearly extrapolated the measured fluxes to August,
September, November and December, and further used the average lake C02 and CH4
evasion measured in May 2010 to estimate fluxes for April and May 2011. Average
monthly lake C02 and CH4 emissions within each catchment were estimated by
multiplying the average measured gas fluxes by the total lake area within the
catchment; likewise, average monthly total stream gas emissions were calculated as
the average monthly C02 and CH4 fluxes multiplied by the total stream area within
catchment. Tota l aquatic C02 and CH4 emissions are the sum of the estimated lake
and stream emissions within each catchment.
2 .3.5 Watershed properties
6 1
For each sampled site, the catchment area was delineated from digital maps with a
resolution of 1 :50,000 scale (available at Natural Resources Canada (National
Topographie Data Base) and average catchment slope, lake area as weil as stream
length of each river order within this catchment on the maps were calculated using
ArcGIS 9.3. The stream area for different stream order within the catchment was
calculated separately as the product of total stream length and the average stream
width of the corresponding stream order, the latter derived from the measured width
for 328 across notthern Quebec; total stream surface in the catchment is the sum of
the total areas for each stream order existing within the catchment.
2.3.6 Statistical Analyses
ln most cases, data input for modeling were log 1 0 transformed for normality. A series
of simple linear regressions were performed to explore the correlations between
variables. Significance is determined at p<0.05 and results reported as non-significant
have p values >0.05 . We used JMP 9.3 (SAS institute) to do the statistical analyses.
2.4 Results
2.4.1 Riverine DOC and DIC exports
The rivers sampled in this study, as weil as their respective catchments, span much of
the range in physical, hydrological and chemical characteristics found in the Boreal
region of Québec, summarized in Table 1. The estimated annual DOC export varied
by one order of magnitude across watersheds, fi·om 1.8 to 21.4 g C m·2 yr·1, averaging
9.1 g C m·2 yr·1 (Table 2). The annual DlC export was systematically lower than
that of DOC, averaging 2.8 g C m·2 y- 1, also ranging an order of magnitude across
watersheds (from 0.5 to 7.7 g C m·2 yr·1, Table 2).
6 2
Table 1 The physical , hydrological and chemical characteristics of the 44 catchments
and the rivers sampled.
Variable Max Min Mean (SD)
Catchment arca (km2 ) 6013 .2 0 .03 401 .3(1261.2)
Catchment average slope (") 5.9 0.3 2 .0( 1.5)
Total stream length (km) 10207.7 0 . 1 694.3(2210.8)
Forest coverage (%) 100 0 72.0(41.1)
Wetland coverage (%) 100 0 27.0(42. 1)
Lake coverage (%) 10.0 0 1.4(2 .6)
DOC concentration (mg L ' 1) 35 .2 8.7 16.9(6 .2)
DIC concentration (mg L-1) 32.6 1.9 11.3(7 .3)
Total P concentration (J.tg L· 1) 170.5 2 .2 35.4(26.7)
Total N concentration (mg L ·1) 1.6 0.2 0.6(0.2)
pH value 9 .9 5.0 7.1(0.6)
COz evasion flux (mmol m·2 d· ') 727.6 -1.6 126.3(156.8)
en. evasion flux (mmol m -2 d-1) 214.5 0.03 7.5(27 .2)
Average CHL a (1-lg L ' 1) 39.0 0 . 1 3 .2(4.7)
DOC and DIC export were both significantly related, albeit in opposite directions, to
average catchment slope (logDOCexp = 2.2 -0.5* log-slope, R2=0.69, n=44, p<O.OOO 1;
logDICexp = 0.61 + 0.45*1og-slope, R2=0.31 , n=44, p<O.OOOl) and wetlands%
(logDOCexp = 2.7+0.21 *log-wetland%, R2=0.71, n=21 , p<O.OOOl; logDICexp = -0.03
- 0.19*1og-wetland%, R2=0.37, n=21 , p=0.0003). It is clear that DOC and DIC
export fluxes are regulated very differently in these catchments, and interestingly,
there was a strong negative relationship between both (logDICexp
0.67*logDOCexp, R2 = 0.25, n = 44, p=0.0005).
6 3
2.13 -
Since DOC and DIC exp01t are both driven by the same discharge, the factors
identifted above appear to be mostly acting the concentrations of DOC and DIC. ln
particular, there was a strong negative relationship between river DOC concentration
and the percentage of water in the catchment (o/owater), the latter mostly driven by the
density of lakes within the catchment (logDOC = 1.41 - 0.16* logo/owater, R2 = 0.24, n
= 25, p=0.01) .
Table 2 The ranges, means and medians of the fluxes of DOC, DlC, POC, C02, CH4
and TC exported annually from the 44 catchments (units : g C m-2 yr-1 on catchment
area basis).
C species DOC DIC POC co2 CH4 TC
Max 21.4 7.7 1.1 14.7 0.4 27.3
Min 1.8 0.5 0.1 0.3 0.01 4.7
Mean (SD) 9.1 (5.3) 2.8 (1.9) 0.5 (0.3) 3.1 (3.6) 0.1 (0.1) 15.6 (5.3)
Median 6.29 2.0 0.4 1.3 0.1 14.8
2.4.2 Watershed aquatic C02 and CH4 emissions
6 4
Watershed aquatic gas emissions from ali aquatic surfaces within the watersheds
averaged 3.1 g C m·2 yr-1 for C02 and 0.1 g C m-2 yr-1 for CH4, and ranged two orders
of magnitude across watersheds for both (Table 2) . C02 and CH4 were significantly
positively related to each other (C02em = -0.70 + 31 .4*CH4em, R2=0.88, n=44,
p<O.OOO 1) and bath had significant positive relationships with catchment area (C02:
R2=0.39, n=44, p<O.OOOI; CH4: R2=0. 14, n=44, p=O.OI), total stream length (C02:
R2=0.44, n=44, p<O.OOOI ; CH4: R2=0.18, n=44, p<O.OOOI), stream arder (C02:
R2=0.49, n=44, p<O.OOOl ; CH4: R2=0.24, n=44, p=0.0007). In particular, C02 and
CH4 were both strong ly positive ly correlated to the %water in the catchment (C02em =
1.07 + 137.2*%water, R2=0.97, n=44, p<O.OOOI ; CH4em = 0.07 + 3.65*%water,
R2=0.77, n=44, p<O.OOOI).
2.4.3 Total C export from boreal catchments
Table 2 shows the average and range of total C export (TCexp) from these boreal
catchments, estimated as the sum of DOC, DIC and POC export and C02 and CH4
fluxes. There was a strong seasonal variation in the magnitude of the average regional
TC export (Figure 2a). TCexp peaked in the early spring, and May and April fluxes
accounting for 38% of the annual TCexp, corresponding to a peak in annual discharge
driven mostly by snowmelt (Figure 1 a). There was a secondary peak in export in the
fait , this associated to increased discharge driven by precipitation. Export was lowest
in both mid-summer and mid-winter, both periods of base flow (Figure 2a). The
relative contribution of C form to total C export from boreal catchments also varied
greatly along the annual cycle (Figure 2b) . DOC dominated TCexp in the fait , winter
and spring, whereas the combined C02 and CH4 emissions dominated TCexp during
6 5
summer (Figure 2b). The contribution of DIC to TCexp was relatively constant
throughout the annual cycle .
................................................................................................................................... a
100•.
so•. ..
40~.
20~o ··
o•.
b
• CH4 O C02 OPOC .. •roc • ore
Figure 2. Total C expott (a) and contribution of each C form to total C export (b) for
each month in the water year. Total C export is expressed in g C per m2 catchment
area for each month, whereas the latter is expressed as percentage of each C form in
total C export.
The cumulative annual TCexp averaged 15.6 g C m·2 yr·1 (Table 2) across ali
catchments, with most values concentrating within a narrow range of 12 to 17 g C m·2
yr·1 (SE around the mean 0.8 g C m·2 yr-1). There were significant positive
relationships between TC export and catchment slope, the proportion of wetlands and
of water in the catchment, and the three combined resulted in the best predictive
6 6
mode! of annual total C expo tt : TCexp = 15.4 - 1.35*Siope + 116.5*%water +
4.03*%wetlands (R2=0.64, n=44, p<0.0001 .
a b ~ . DOC QOntribution -
t: . C02 contribution -0 ..... a. >< <ll:;J "' ü
•mc § . ~. .. !2
• noe _g:il • c:
DPOC .2 :5 . . .o o
OC02 ·= ..... ë 0
OCH4 u
~:1 ..
•• • 1 1
• " " water%
Figure 3. a. The average contribution of the various C species in the annual total C
export from these boreal watersheds; b. The contribution of DOC export and of
aquatic C02 emissions to total C export from these boreal catchments, as a function
of the proportion of water in each catchment (% water). The latter is mostly driven by
the presence of lakes. The catchments of ri vers of arder 1 and zero contained no lakes
and were aggregated as %water = O.
DOC dominated the average annual TCexp (58 .5%), whereas DIC contributed on
average < 18% (Figure 3). Gaseous emissions as C02 and CH4 together accounted for
an average of 20.5% of the annual TC exported from these boreal catchments,
overwhelmingly driven by C02 emissions. The estimated contribution of POC to the
average annual TCexp was small , in the arder of around 3% (Figure 3a). The
contribution of the various C species to the annual TCexp varied systematically across
the studied watersheds. In particu lar, there was strong decline in the contribution of
DOC to TCexp with increasing water surface in the catchment, which was mirrored
6 7
roughly by a proportion increase in the contribution of C02 along the same gradient
(Figure 3b).
We further explored whether there were systematic differences in the magnitude and
composition of TCexp between the two distinct sub-regions that we covered in our
study (South Abitibi and James Bay) , which are characterized by very different land
cover, particularly in terms of the extent of peatland cover (data summarized in Table
3). The average DOCexp was 2.4-fold higher in James Bay (15 g m·2 yr-1) compared to
South Abitibi (6.3 g m·2 yr-1), whereas the average DIC export was 2.6-fold higher in
South Abitibi; the average C02 and CH4 in South Abitibi were 2.5 and 3.9 times
higher than those in James Bay, respectively. Interestingly, CH4 was low in James Bay
(< 0.2%), but was a significant component of TCexp in South Abitibi (> 1%). As a
result, not only was the average magnitude of the TCex p different between the two
sub-regions (18.6 g m·2 yr·' versus 14.0 g m·2 yr·1, James Bay and South Abitibi,
respectively) , but also actual composition of the TCexp differed substantially: Whereas
in James Bay DOC overwhelmingly dominated TCexp (80%), and DIC contributed
very little (7%), in South Abitibi the TCexp was more equally distributed between
DOC (45%), DIC (25%), and C gas emissions (27% and 1%, C02 and CH4,
respectively) (Figure 4).
6 8
Table 3 The comparisons of physical, chemical and biological factors between James
Bay and South Abitibi during the measurement period (June 1 5', 2010 to May 31 5',
2011 ). The values were annually averaged from the 14 and 30 streams and rivers we
observed in James Bay and South Abitibi , respectively.
Variable James Bay South Abitibi
A vera ge air temperature eq 0.6* 2.7*
Average catchment slope e) 1.3 2.3
Average elevation (rn) 296 304
Forest coverage (%) 20.8 97.5
Peatland coverage (%) 84.3 0.3
Lake coverage (%) 0.5 1.9
DOC concentration (mg L·') 31.3 16.8
DIC concentration (mg L-1) 6.0 12.0
Total P concentration (J.Lg L-1) 24.1 37.8
Total N concentration (mg L-1) 0.6 0.5
pH value 7.1 7.2
Alkalinity (Jleq L·') 330.2 1177.1
COz evasion flux (mmol m·2 d·1) 70.6 89.6
CH1 evasion flux (mmol m·2 d·') 3.1 9.1
Average CHLa (Jlg/L) 1.2 3.4
South Abitibi
ODI C
• ooc OPOC O C02 OCH4
6 9
James Bay
Figure 4. Comparison of the average contribution of di ffe rent C fo rm s in the annual
total C export between South Abitibi and James Bay reg ions.
2.5 DISCUSSION
2.5.1. River-mediated DOC, DIC and C0 2 loss from landscapes
The loss of C fro m land to aquat ic ecosystems is increasing ly recognized as a
significant component of the reg ional C budgets (Co le et a l. 2007; Tranvik et a l. 2009;
Raymond et a l. , 20 13). T here is an extensive literature on river-mediated C loss from
terrestrial systems, but re latively few studies to date have g iven a complete acco unt of
riverine disso lved, particulate and gaseo us C exports fo r regional C budgets of borea l
biomes yet. Our study of 44 rivers was explicit ly designed to quanti fy C loss in
diffe rent fo rm s, i. e. DOC, DIC, C02 and CH4, so as to obtain an integrated view of
TC export from the landscape.
The ranges for the export of TC and of the diffe rent C species from these boreal
catchments in Q ué bec lie weil within the range of va lu es in the literatu re. Table 4
7 0
Tab
le 4
Com
pari
son
of
late
ral
and
gase
ous
carb
on
expo
rts
from
the
wat
ersh
eds
in p
revi
ous
stud
ies
wit
h ou
rs.
Exp
ort
of
each
C f
orm
fro
the
cat
chm
ents
is e
xpre
ssed
in
g C
m·2
yr·1 •
W:;
ti!ir;
he-d
E
ca-r
egio
!il
co!
GH
., T
C
Ref
erem
:e
}\.:r
cadw
n ~~:mp€!3Œ
2 7
.9
Pois
!Oll.a
.e:re
e<
aL
_o 1:.
.
Sdr
elè.
t Temp~
;n:
l}_g
11.8
A
'b.ri
l e· .
:ù ..
_00
0
1\fu
.;ou
ri
Te:
lllpe
mtE<
!-
L9
2.5
Ohi
o Te
mpe
o.at
e:
-~
1 • .
<.
~,>fi ;
.;i;
;iFJ p
i. T
empe
oaŒ
A
S
.5
F .. .ry
d:l:.
;.u.
Bom
.-~1
67
3.9
0.7
5.0
9.
6 W
allm
et
aL, 2
013
Yuk
on
Bar
eaJ
638-
ôO
4_
-L
9 -.
8 0.
9 0 .
.. 6
9.0
. 0.
06
1.8.
3 ~trieg
et 3
1.,
10
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vs..:
.tra b
acke
-n
Bor
&l
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,
2.9
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qLli;
y et
ru.,
200
9 ~
--
1fl
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~empe..-aœ-
6401
} fi
.;
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Jo
ll6.:.
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: L
, ~007
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eal
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14.3
3
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0.0
3 .B
ill-
e~ &
~-oote, _
Oll&
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... A
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i}
40.5
B
ille
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31 .
. 200
4
Bro
ckyB
UI:'
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T~.::raœ
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3 .L
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1 1.
2 H
op
e et
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ntei
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-
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1.~
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o.:
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S
teis;
&
trieg
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1}1:
:!; H
ossl
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Ban
er,
t:S
20B
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m.l.
3ll&
Ray
mon
d, 2
..
Z
lm_1
3llg
9u
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pic
a.
Ci üO
OO
L ~
2.6
8A
.-
0 -~ ~
O.ô
_8
_7
Yao
e:ta
l., 2
7·
Tha
ng e
t l!.l
. ... 0
13
·-·
.v
__
;::
(ha~gj
i:.;.ug
'Snt
rmop
ir::al
. 8
000
00
0.9
•• .3
0.
8 o.
_ 8.
5 2
l.J
Wan
g et
a·.
, :ocn
~ Wan
g et
:11.,
20
2 H
llii
llgh
e 75
000
0
1}:
03
o .
. 1
.1
2.1
-u
a, 2
C•07
; Zhl
œg
e: a
l. _
009
Aur
...he
:nco
rth
.4
l'!U
.....
.. 9
0.0
0.0
_ 34
.3
Dir
u.m
ore
e;ra
L 2
013
Est
rie
Cii...
"'PŒ
T l
of f
uis
the-
-.;is
A
bit
t 0.
5 3
.1
0.1
15.6
Th
:i.:-
>àJ d
y
~Tot
~:
CA
. c:m
.hm
ema:
12::.
.
7 1
summarizes published results on lateral (dissolved) and vertical (gaseous) Joss of C
from different landscapes. Our range in DOC export (1.8 to 21.4 g m-2 yr-1) agrees
weil with the range between 2.3 and 14.8 g m-2 yr-1 for boreal watersheds in Finland
(Rantakari et al. 201 0), and our average regional DOC export of9.1 g m-2 yr- 1 is close
to the upper limit of the range between 3.1 and 8.4 g m-2 yr-1 for Northeast Canada
given by Mulholland and Watts (1982), but somewhat higher than the mean value of
6.1 g m-2 yr-1 reported by Huotari et al. (20 13) for boreal watersheds in southern
Finland. On the other hand, our average DIC export of 2.8 g m-2 yr-1, ranging from 0.5
to 7.7 g m-2 yr-1, was significantly higher than that in Sweden (0.3-1.4 g m-2 yr- 1,
averaging O. 7 g m-2 yr-1) (Wall in et al. 20 13) and Fin land (TJC: 0.9-1.4 g m-2 yr-1,
averaging 1.1 g m-2 yr-1) (Rantakari et al. 2010), but lower than that found in the
Yukon River (5.8 g m-2 yr-1) (Table 4). These regional differences in DIC export
most likely reflect local geology (Tank et al. 2012), and to sorne extent, variations in
terrestrial primary production, sin ce a sign ificant portion of the DIC exported actually
originates from chemical weathering of rock that is mostly mediated by respiratory
soil co2.
Our results confirm the key role of wetlands as sources of DOC to ri vers (Houtari et
al. 20 13), but further highlight the rote of surface waters, and particularly lakes, as
important sinks of DOC in the landscape (Gergel et al. 1999; Xenopoulos et al. 2003),
such that the balance between the relative coverage of wetlands and lakes appears to
be one of the key determinants of the net DOC export from these northern watersheds.
Our study provides further evidence for a differentiai regulation of DOC and DIC
export from these boreal catchments. Whereas the export of both species is primarily
driven by runoff, as has been reported before (Hou tari et al. 20 13), the re are
7 2
differences in the drivers that determine their respective concentrations, and in
particular, DOC and DIC exports significantly related to catchment slope and percent
wetland, but in opposite directions. This is consistent with previous findings of our
group (Li et al. , 20 15) and others (Hou tari et al. 20 13), wh ich demonstrated a
differentiai control DOC and DIC export in temperate and boreal watersheds. The
resulting strong negative relationship between DOC and DIC export that we report
here is interesting, because it is to sorne extent compensatory and may contributes to
constraining TC export within a narrower range.
The average emissions of C02 and CH4, on a catchment area basis were 3.1 and 0.1 g
m·2 y 1, respective( y, and both ranged widely (see Table 2). There are only a handful
of reports of total aquatic C02 fluxes scaled to the en tire watershed, which range from
a minimum of 2 g C m·2 y· ' in sub-arctic Sweden (Christensen et al. 2007) to a high 9
g C m·2 y 1 for the Yukon watershed (Striegl et al. 20 12); our own average estima te of
C02 emission (lies weil within this range and close to previous boreal studies
(Jonsson et al. 2007). The CH4 value, on the other hand, is within the upper ranges of
emission reported for other river systems (listed in Table 3), and over 3 times more
than the CH4 emissions from a boreal landscape located only 400 km south of our
study area (Billet and Moore, 2008). One of the main reasons underlying these higher
CH4 is the widespread damming of rivers by beavers, especially in South Abibiti,
which generates aquatic habitats that are particularly conducive to the production and
emission of CH4 (Ford and Naiman 1988). C02 significantiy and positively related to
CH4 in this regions, as had been previously shown by Campeau and del Giorgio
(20 14), who reported a strong positive correlation between the partial pressures of
C02 and CH4 (pC02 and pCH4 ) in surface water in the same study area. This positive
7 3
correlation is not surprising since C02 and CH4 are bath strongly driven not only by
the average water surface C fluxes but mostly by the relative coverage of water in the
catchment, which in turn is a function of the catchment size and slope, larger
catchments having lower slopes and generally larger lakes, and thus the positive
relationship of bath with catchment area as weil.
2.5.2 Magnitude and composition oftotal C export
On the who le, the magnitude of TC export from the landscape was characterized by
spring>fall>winter>summer. This seasonal variation in TC tightly followed the
average daily d ischarge curve (Figure 1 ), suggesting that TC export was mostly
driven by the seasonal variation in discharge and therefore runoff. In particular, the
TC export from April to May accounted for 38% of the annual TC export, resulting
from a combination of the degass ing of C02 accumulated under the ice, and also of
high spring discharge and associated loads of DOC and DlC. Previous studies have
also reported runoff as explaining 60 to over 80% of the variation in DOC and DlC
export from temperate and boreal catchments (Âgren et al. 2007; Raymond and Oh
2007; Pumpanen et al. 20 14; Li et al. , 20 15), with concentrations explaining the
remainder of bath the cross-system and seasonal variability in dissolved C export.
On average, the contribution of the various C species to annual TC export was
DOC>C02> DIC>POC>CH4, and over 90% of the TCexp accounted for by the first
three, in agreements with previous studies (Striegl et al. 2012; Wall in et al. 20 13;
Dinsmore et al. 2013 , and see Table 3). On the who le, the gaseous C loss as C02 and
CH4, accounted for an average of 20% of the an nuai TC export in our study area, in
agreement with the values reported for other boreal (Hope et al. 2001 ; Oquist et al.
2009; Koprivnjak et al. 2010; Striegl et al. 2012; Wallin et al. 2013), but signiftcantly
7 4
higher than the 13% and 6% from temperate watersheds reported by Billett et al.,
(2004) and Abri l et al. , (2000), respectively. Our results, together with these previous
studies, collectively confirm that gaseous C export is a major component of
river-driven C loss from boreal landscapes.
Although DOC dominates the average regional annua l TCexp, its contribution within
individual watersheds declines as a function of increasing water coverage in these
watersheds, reaching a minimum of around 20% at the highest water densities in the
landscape, whereas the contribution of C02 tends to peak at around 65% in these
water rich watersheds. lt is interesting to note that these opposing trends in DOC
export and C02 emissions, as weil as with DIC discussed above, confers a certain
stabi lity to the tota l C export from these boreal catchments, and helps explain why
most of the estimates of TCexp ho ver around a relatively narrow range ( 12 to 17 g C
m·2 y·1), in spite of the large environmental, topographie and morphometric
heterogeneity th at exists among the se catchments. The best predictive model of TCexp
actually retlects the net balance in the regulation of its main components: The
positive re lationship with the proportion of wetlands retlects their strong positive
influence on DOC export, whereas the positive etfect of the proportion of water
suggests that the enhancement of C gas emiss ions w ith increasing water surface is not
offset by the decline in DOC that occurs along the same gradient; the positive effect
of catchment area on TCexp further retlects increases in runotf as a function of
catchment ize, a weil as in total gas emis ion and DIC export. We should note that
in this study POC was not measured and was rather assumed to be a fixed proportion
of DOC, so no actual conclusions can be drawn for this particular C species, but
existing evidence suggests that its contribution to TCexp in these mostly
7 5
non-agricultural watersheds should be minor (lvarsson and Jansson 1994; Hope et al.
1994).
The interplay between the average contribution of DOC and C02 along a gradient of
water density among catchments occurs to sorne extent within a given catchment in
time. We have shown that there is a clear temporal succession in the relative
contribution of the main C species along an an nuai cycle, with a peak contribution of
DOC during periods of high discharge, and dominance of C02 during summer low
flow periods. The mechanisms underlying this replacement are probably different:
Whereas the replacement of DOC for C02 across catchments likely reflects the
increased photochemical and biological degradation of terrestrially derived DOC that
occurs with increasing water coverage and thus water residence time, the temporal
succession reflects seasona l shifts in discharge and aquatic metabolism (Vachon and
del Giorgio 20 14). The increase in the relative contribution of C02 du ring these low
flow periods results from a combination of declines in the loading of DOC, and
increases in the actual aquatic co2 fluxes, likely driven by temperature- and
light-enhanced DOC degradation within lakes. The seasonal pattern in both C02 and
CH4, with marked peaks in mid-summer, also likely reflects a temperature effect,
consistent with Billett et al. (2004), Koprivnjak et al. (20 1 0) and Kosten et al. (20 1 0)
who reported a strong positive correlation between temperature and co2 evasion .
2.5 .3 Cross-regional differences in the magnitude and composition ofC export
It is interesting to note that there are major differences in both the magnitude and the
actual composition of TCexp between the two sub-regions, James Bay and South
Abitibi , that coexist with our general study area but which are very distinct in terms
of land cover and to sorne extent climate (see table 4 for a summary) . The total C02
7 6
and CH4 emissions in James Bay were 2.5-fo ld lower those in South Abitibi, to sorne
degree, reflecting the effects of regional temperature and water coverage, whereas
DIC export was substantially higher on average in South Abitibi , possibly related to
differences in both underlying geo logy as we il as in temperature-driven soi t
respiration and the resulting chem ica l rock weathering. The largest difference that we
found between the regions, however, was in the DOC export, which was 2.4-fold
higher in James Bay, driven by a 2-fold higher average river DOC concentration there
(Table 3) . These elevated DOC concentrations in James Bay are likely related to the
much higher peatland coverage (12.6- 1 00% vs . 0-4% of the total ar a) and smaller
catchment slope (1.3 vs 2.3 on average) , and reinforce the importance ofthese factors
in determining DOC concentration and export from land (Eckhardt and Moore, 1990;
Dillon and Molot, 1997).
2.5.4 Implications to terrestrial C budgets
The lateral C export from land to water that we report here must be placed in the
context of the who le C budget of this boreal landscape. Much of the recent empirical
and modeling work has focused on better constraining the net C02 exchange between
various landscapes and the atmosphere (i.e., Net Ecosystem Production, NEP), in
order to determine the role of these eco systems as sources or sinks of atmospheric C.
NEP varies greatly with geographie location and climate, but a lso within a given site
as a function of stand age, fire history and clear cutting (Bergeron et al. 2008;
Goulden et al. 20 Il), and also as a function of inter-annual differences m
precipitation and temperature (Litvak et al. 2003). Moreover, there is evidence of
long term shifts in the net C balance of landscapes with in the boreal biome. For
example, Dunn et al. (2007) reported a decade-long shift in net C uptake in a boreal
7 7
landscape dominated by black spruce, from being small source of C ( -41 g C m-2 y- 1)
to more recently become a sma ll sink (+21 g C m-2 y- 1). Not surprising ly, there is a
very large range in net C02 exchange reported for boreal forests, from - l 00 to
250 g C m-2 yr- 1 (Ryan et al. 1997; Hyvonen et al. 2007).
ln this regard, very few current models of terrestrial primary production and C
storage include lateral C !osses ( i.e. Hayes et al. 20 12; Regnier et al. 20 13; Wu et al.
2013), and even fewer incorporate aq ueous C emissions, although there is ample
evidence that these fluxes are regionally significant, particularly in boreal landscapes
(Battin et al. 2009; Wallin et al. 2013). A key issue is then to what extent current
approaches to estimating NEP include this TCexp, and if they do, what components of
TCexp are included (Fied ler et al. 2006; Hyvonen et al. 2007). Estimates based on
eddy covariance towers may incorporate sorne of the aquatic C emissions, depending
on the locatio n of the tower, but certainly do not include a li the C components !ost to
the aq uatic network (Kij un et a l. 2006). For example, recent studies have reported
that unexpectedly high lasses of soi l C had to be invoked in order to mass balance the
apparent net C02 uptake with the observed long-term ecosystem C accumu lation, and
these were attributed to increased respiration (Lindroth et al. 2008), but it is likely
that at !east a portion of this soi t C loss resulted from the lateral export soit DOC and
DIC to the aquatic network. T he few previous studies that have explicitly attempted
to integrate the main components of the lateral C export to water a li converge to point
out that TCexp is a significant component of regional C flu xes and consistently within
the arder of magnitude as the NEP in for their respective regions (5% to over 80% of
the local NEP, Buffam et a l. 2011; Field 1er et al. 2006; Christensen et al. 2007;
Jonsson et al. 2007; Striegl et al. 20 12).
----------------------------------------
7 8
ln this regard, although there is an extensive literature on boreal terrestrial primary
production net C exchange, there are few direct est imates of NEP for this region in
particular. G irardin et al. (2011) report an average NEP ofaround 150 g C m-2 y- 1 for
the southern portion of the Abitibi region of boreal Québec, whereas Bergeron et al.
(2007) report a much lower NEP, in the order of 4 g C m-2 y-1 in the nearby region of
Chibaugamau. Sorne of this difference may be methodological , because the former
was based on estimates of C stocks and tree productivity, whereas the latter is based
on eddie covariance data. This large range in reported NEP for this region also likely
reflects the large degree of heterogeneity that exists in this boreal la ndscape, driven
by local climate, fire history and more recently, forestry. Regardless, the estimated
TCexp in the Abitibi region that we report here is like ly to play a key role in
determining wh at portions of this vast boreal landscape act as either a so urce or a sink
of atmospheric c_ This is particularly true for the James Bay region, which is drier
and colder than the adjacent South Abitibi and thus likely approaches the lower
reported range of NEP, and which is nevertheless characterized by a higher estimated
TCexp (18.6 g m-2 yr-1 vs 14 g m-2 yr-1, James Bay and South Abitibi , respectively).
This implies that the relative contribution ofTCexp to the whole landscape C budget is
likely to be even larger in the James Bay region than it is for Abitibi in general.
Interestingly, these TCexp areîn the same range of estimated fire-driven C02 fluxes to
the atmosphere (Van Bell en et al. 20 1 0), yet whereas the latter are incorporated into
most terrestrial C models for these regions, the former are not. More generally, the
large degree of uncertainty that still characterizes most estimates of net tenestrial C
si nk or sources may be at least in part related to the non-inclusion of this lateral loss
to the aquatic components of the regional C budget.
7 9
ACKNOWLEDGEMENTS
Ali the data used in this study are available for collaborative use; contact Paul A. del
Giorgio ([email protected]) for information regarding access and handling.
This study was funded by the NSERC Hydra-Québec lndustrial Research Chair in
Carbon Biogeochemistry in Boreal Aquatic Systems (CarBBAS Chairwhich is jointly
funded by the National Science and Engineering Research Council of Canada
(NSERC) and Hydra-Québec. Thanks to Audrey Campeau, who generously shared
her data with us, and ali the current and former members of the CarBBAS team who
participated in the collection and analysis ofthe data used in this study.
0 00
CHA PTER III
A GLOBAL ANALYSIS OF RlVERJNE CARBON EX PO RT TO TH E OCEANS
Mingfe ng Li, Yves T. Pra irie, and Paul A. de l G io rg io
Be ing prepared for Nature Geosciences
Département des sc iences bio logiques, Univers ité du Québec à Mo nt réa l, C P 8888,
Suce Centre Ville, Mo ntréa l, Québec, H3C 3P8 Canada
N.B. References c ited in this chapter are presented at the end of the thesis
3. 1 Abstract
8 1
Rive rine carbo n (C) expo rt to the oceans is a key co mpo nent in the g lo ba l C cyc le,
yet it is still poorly co nstra ined . T his is large ly the resul t of the limi ted data base used
to der ive a g lo bal flu x and because most studies assessed the ino rganic or organic
fractio n separate ly, thus yie lding a fragmentary perspecti ve of C exported to oceans.
Here we rev is it the g lo bal rive rine C expo rt, based on the meta-ana lys is of publi shed
data covering 566 rivers dra ining 74% of the g lo ba l exorheic area. This analys is
yie ld s a new g lo bal annual riverine C expo rt of 0.68±0.05 Pg yr-1, substantia lly lower
than the w ide ly-c ited 0 .9 Pg yr-1• Our results show that, at a g lobal scale, the organic
and in organic co mponents of C export are driven by diffe rent combinat ions of natura l
and human-derived features of the land scape. Beyo nd the expected hydro logie co ntro l
on materia l transpo rt, DOC expo rt was ma inly co ntro lled by natural characteristics
su ch as the presence of wet lands as we il as the organic carbon content of the surface
so i! layer. O n the other hand , the natura l drivers of DJC export were the extents of
carbo nate rocks and water surface in the watersheds. However, a li fonns of carbon
8 2
were also shawn to be dependent on the extent of croplands within the catchments,
and strongly so for the inorganic fraction. A retrospective analysis suggests that 40%
of the current C delivery to the oceans is associated with agricu lture. Our multiple
regression models demonstrate that cropland expansion may be a primary driver of
future riverine C export not on ly in magnitude but also in its composition. This study
further highlights the differentiai regulation of global inorganic and organic C exports
and can serve as a strong· basis for identifying the implications of future c limate and
human-induced environmental changes on this important component of the global
carbon cycle.
3.2 Introduction
Riverine transport of C to the oceans is the ultimate leachate of terrestrial carbon.
Fo llowing the pioneering assessment of Meybeck and coworkers, it is a significant
component of the global C cycling and quantifying it is essentia l to a better
understanding ofthe Earth 's biogeochemical and climatic systems, particularly in the
context of g loba l change (Lai, 2003; Aufdenkampe et al. , 2011 ; Cole et al., 2007;
Battin et al. 2009). How much and in what form continental C is lost to oceans have
thus been of major biogeochemical interests for severa! decades . Regionally, the main
drivers of carbon export are relatively c lear. The combined etfects of topography,
hydrology, climate and land use/caver change on riverine C export from landscapes
are weil known(D' Arcy and Carignan, 1997; Hazlett et a l. , 2002; DeCatanzaro and
Chow-Fraser, 2011; Freemanet al., 2004) and the importance of the in land aquatic
processing of this terrestrially-derived carbon is an active research area (Cole et al.
2007; Tranvik et al. 2009; Raymond et al. , 20 13). A lthough g lobal estima tes of
riverine C export to the oceans have been periodically re-assessed (Richey et al. , 1980;
8 3
Meybeck, 1982; Schlünz & Schneider, 2000; Dai et al; 20 12; Seitzinge r et al. ,
20 1 0), the ir acco unting is surprisingly poorly constrained (SchiUnz & Schneider,
2000) because of either di ffe rences in approaches or of the limited riverine C data
compilations. Nevertheless, published estimates tend to converge around 0.9 Pg yr·1,
a va lue that has been widely cited as the global total riverine C flu x (Co le et al. 2007;
Battin et a l. 2009; Tranvik et al. 2009; Bauer et al. , 201 3).
Most prev ious estimates considered only so rne of the four C components (disso lved
and particulate, organic and inorganic carbon species; DOC, POC, DlC and PI C,
respectively), thus yie lding a fragmented perspecti ve of riverine C exported to the
oceans and contributing to the uncertain ty of the estimate of global C expo11ed in
di ffe rent fonns from the terrestrial biosphere. Moreover, these globa l estimates are
generally derived from a few to a few dozen large rivers and extrapolated to the rest
of the globe, thereby ass uming an untested representati veness. Considering that there
are about 740 ri vers draining into the oceans that have individual catchments > 10,000
km 2, arriving at a more ace urate estima te of the global riverine C ex po11 to the oceans
will necessarily require a better or complete geographie coverage but will also benefi t
fro m the ident ifi cation of the main dr ivers determining the export of the various
carbon fonns at the planetary scale.
ln this synthesis, we campi led literature C data of fi e ld measurements from 566 ri vers
worldwid e, draining a total of 74% of the global exorheic area (Antarctica is exc luded
from this study) and combined it with land caver and other catchment info rmation to
identity the large sca le determinants of C expo11. The resul ting models were then
applied to the remaining (unsampled) rivers of the wo rld to better constra in the globa l
riverine export of di fferent C species to the coastal oceans. ln addition, we explored
8 4
the relative roles of natural and human-altered la ndscape features on the delivery of
various forms of carbon and their potential implications in the context of globa l
enviro nmental change.
3.3 Results and discussions
3.3 .1 Drivers of riverine C export
A review of the literature reveals that riverine C export differs wide ly among ·
individual rivers due to the large variat ion in catchment topography, vegetat ion,
geology, climate and hydrology (Hope et al. 1994; Pacifie, 2009; Tank et al., 20 12).
To assess their relative importance at the globa l scale, we developed multivariate
models to test specifica lly the importance of catchment characteristics, such as land
caver (ama lgamated into broad categories: forests, crop lands, wetlands and water, see
Supp lementa l Information S2), soi l organic carbon, mean annual runoff, mean annua l
temperature, carbonate rock outcrops, and catchment s lope and area. ln add ition, we
examined the potential influence ofsome specifie human a lterat ions to the landscapes,
such as the increased water residence time and river segmentat ion induced by the
creation of large dams (S f3) . Average population density was also a candid ate
var iab le and was assumed to be a good proxy of hu man disturbance. T he models were
developed using the e last ic net variab le select ion procedure combined with BIC
va lidat ion, as implemented in JMP Pro vers ion 12 . Variables retained in the final
models each bring independent information useful to the description and prediction of
carbon export.
Without surprise, we found li ke many regional studies (Hope et al. 1994; Pacifie,
2009; Tank et al. , 20 12) that a li forms of carbon export were ultimately constrained
8 5
by the amount of water flushing through the catchments (as runoff, mm yr-1).
However, beyond this simple hydrologie contro l, each form of carbon exported was
determined by different sets of landscape features . At this globa l sca le, the
non-hydrological var iations in DOC expo1t was best exp lained by edaphic
characterist ics of their catchments, such as the soi l organic carbon (SOC 0-30cm, kg
C m-2) and the extent of wetlands in the catchment. We were also ab le to detect the
signifi cant influence of two important human alterations to the landscape on DOC
export: the extent of croplands and the presence of large reservoirs within the
catchment (expressed as the additiona l residence time of water, AWRT, within the
catchment; DOC vs A WRT: R2=0.11 , n=442, p<O.OOO 1 ). Last ly, we fou nd that large
catchments tended to export less somewhat carbon per unit area, suggesting that a
greater mineralization and loss of DOC during the transit through the hydro logica l
network. At the globa l scale, the relative importance of the various influences ranked
as fo llows: Hydrology > Soil organic carbon > % Wetlands > %Croplands ::::
Catchment size > A WRT.
Variations in DIC export were also best exp lained by a combinat ion of natural and
human-altered features of the landscape. Like DOC, DIC export is tightly contro lled
by the regiona l hydrology (runoff). However, and not surprisingly, it is also strongly
and positively modulated by the presence of carbonate rocks within its catchment.
Moreover, it is negative ly modulated by the fraction of the landscape covered by
water. The mechanisms behind both of these natural drivers are eas il y understood. ln
the former, the chemical weathering of carbonate rocks by soi l respiratory C02 is a
primary source of alkalinity (i.e. HC03- and C032-) , which constitutes the bulk of DlC
in most cases. Rivers draining catchments with a large proportion underlain by
8 6
carbonate rocks naturally yield more DI C. Similarly, the negati ve influence of water
coverage likely refl ects the converse mechanism: catchments with a lot of water
surface simple have a sma ller surface over which this chemica l weathering of so i!
minerais can occur. In this respect, inland waters largely act as passive transport pipes
fo r these conservative ions (HC0 3- and COJ2-). Beyo nd these natural contra is
however, our analys is revea led the important influence of the extent of agricultural
activ ities on DIC export. Co llective ly, they explain about 57% of the global variation
in DI C export, including a small but significant positive effect of catchment size.
Their re lative importance fo llows Hyd rology > %Croplands ::::: %Carbonates >
% Water > Catchment size.
Always in much smaller amounts than its disso lved co unterpart, the particulate
fraction of organic carbon (POC) was also a significant multivariate function
(R2=0.4 7) combining hydrology and bath na tura! (% Water) and human-altered
(%Croplands) features of the catch ment landscapes. The inverse relationship between
POC export and water coverage can probably be ascribed to POC deposition and
bu rial in the sediments, and/or the greater POC potent ia l degradation because of
longer res idence time in lakes or reservo irs. Conversely, the positive association
between %Cropland and POC export can result fro m the greater eros ional so i! !osses
of croplands relative to fo rests. Table 1 summarizes the globa l models for the
di fferent fo rms of carbon. For PIC export, the limited number of observat ions (n=36
rivers) precluded the development of a spec ifi e mult ivariate mode!. lnstead, we used
the median ratio of 10% between PIC and DI C export observed in the 36 rivers and
applied it to ali the other catchments. This approach, while necessar ily coarser, best
captured the observed variab ility in PIC export.
8 7
While the importance ofwetlands and so i! o rganic carbo n co ntent to DOC yie ld is not
new to the lite rature ( Dillon and Ma lot 1997, Aitkenhead and McDowe ll 2000), our
g lo bal mode ! can be so lved (fi g. S l4. 1) to assess how DOC expo rt varies in different
regio ns of the world depending on loca l hydro log ie regimes (runoff, mm yr-1) and so i!
organic carbon content (SOC, kg C m-2) when a li other va riables rema ining equal at
the ir mean va lues. Fo r SOC> 10 kg m-2, the re latio nships are nearly linear, suggesting
DOC expot1 can be viewed as a fir st-ord er reactio n w ith the so i! o rganic C reservo ir
e luted w ith di ffe rent e ffi c iencies depending on the annual runoff. As a genera l rule,
DOC expo rt correspo nd s to a rate va rying narrowly between 0.02 and 0.07% of the
SOC per year per mm of runoff. So lv ing the mode! furthe r fo r units of pure
cropland , this removal rate inc reases only s lightly to 0 .03-0.1 % yr-1 per unit runoff
(mm ) whil e a pure wetland unit wo uld remove abo ut 0.3-0.5% yr-1 per unit runoff
(mm), indicating a much greater removal rate ofwetland organic carbo n.
To our know ledge, our study is the fir st to detect a s ig nificant influence of large
reservo irs (>0. 1 Mm 3 capac ity) on DOC yie ld . Altho ugh large ly explo ratory in sco pe,
our ana lys is sugges ts tha t the lo nger water res id ence time induced by the creatio n of
large reservo irs for a va riety of purposes (fl ood co nt ro l, irr igatio n, hydroe lectric ity)
may favor a mo re complete degradatio n of the DOC, bio logica lly or photochemica lly,
into DI C (Lapie rre et a l. , 201 3 ; Spencer et a l. , 2009) during its transit.
8 8
Table 1 Multiple linear regression models predicting DOC, D!C and POC export in g
m·2 yr· 1. Estimates of coefficients and corresponding p values are given for ali
variables offered during the e lastic net selection process. Variab les were included in
the mode] if p<O.OO 1 and the corresponding R2 values are shown.
DOC export DIC expo11 POC export
Parameter
Estima te p Estima te p Estima te p
Annual runoff (mm) 0.744 <0.0001 0.781 <0.0001 0.899 <0.0001
Catchment area (km2) -0 .070 <0.0001 0.102 0.0003
Soit organic carbon (kg m·2) 0.326 <0.0001
o/ocrop lands 0.022 <0.0001 0.055 <0.0001 0.049 <0.0001
o/owetlands 0.202 <0.0001
o/owater body -0.114 <0.0001 -0.155 <0.0001
%carbonates 0.058 <0.0001
lntercept - 1.863 -2 .117 -2.652
R2 0.70 0.57 0.47
n 427 404 339
Notes: ln the models , C export, annual runoff, catchment area and soit organic carbon
are log 10 transformed , o/ocroplands, o/owater surface and %carbonates are square root
transformed, and o/owetlands is 0 .25-power transformed.
8 9
3.3.2 A néw estima te of g lo ba l riverine C expo1t to the oceans
The deve lo pment of the statistica ll y robust mode ls at this g lo ba l scale has not only
further cla rifi ed the re lative importance of di ffe rent contro ls on riverine C export to
the oceans, they a lso a llow us to estimate carbon expo rt to the oceans from the rest
(26%) of the g lo bal exo re ic area whe re no measurements of carbo n expo rt have been
found in our data co mpilatio n. T hese represent 5098 watersheds of mo re than 3 km 2.
Co mbining the measured va lu es of the 566 rivers with the mode led estimates fo r the
unmeasured catchments yie ld ed a new estimate of the g lo ba l riverin e C ex po rt to the
oceans. Fig ure 1 shows the g lo ba l distributio n of measured (so lid co lors) and
modeled (hatched) DIC and DOC expo rts (F ig ure 1 a and 1 b, respective ly) .
a Global Distribution of DIC export
,/ :::-. /
/
"'"·- -/·--- j-'§!l-~ ) // /
1 1 1 1
1 1
,.,..,. . ~ ! 1 ~JI'---.f...---l
\
""a'~~ /
~/ / / , ,/"".,.'
,.,,·"
( / .-...-· -~ . . ( , ~# ,-· ,--- r · )l"X'i! ëC":: •''! 97:-::Jt: ,~ -:~'! ,~.~:::-: '! 11:)~
DIC (glm2/yr)
c· .. J oo - so c:::::J oo - 123 - 123-24 5-24 5-452- 452 . 94 9
DI C according to the model (gl m2/yr)
CJ oo-27 CJ 27 - 7.4 [ZJ 7.4-1A9 ~ 149-319 ~319-831
9 0
b Global Distribution of DIC export
DO C (g/m2Jyr}
D oo-16 ~ 1.6-33 .3.3-58.5.8- 96 .9 .6 - 38 ~ DOC accordlng to the m odel(g/m2Jyr}
Oo.o-2s o 2.s-7.si2Zà7.s-16.9 ~ 169-31 0 RJ31.o -6o .s
Projection lo >dmuthal Datum . World Geodetic System 1984 (WGS 84}
Fig ure 1 Maps of G lo ba l Distributions of D1 C and DOC Exports
Our assessment yie lded a tota l g lo ba l C export of 0 .68±0.05 Pg yr-1, of w hich DOC,
POC, DI C and PI C exports represent 0.18±0.01 , 0.07±0.01 , 0 .39±0.02 and 0.04±0.01
Pg yr-1, respectively. Our new estimate thus co nstitutes a significant downward
revision of the wide ly used glo ba l C expo rt va lue of 0.9 Pg yr-1• For compariso n,
Table 2 compiles our new estimates w ith those previously published and it hig hli g hts
that the largest diffe rences are in the POC and PI C export. Our POC expo rt estimate
of 0.07 Pg yr-1 is much lower than the va lu e of around 0. 18 Pg yr-1 reported in
previous studies (Meybeck, 1982; Galy et a l. , 20 15 ; Ludw id et a l. , 1996) altho ugh
consistent with the va lu e of Garre! et a l. ( 1973). We suggest that the glo ba l POC
9 1
export may have been overestimated in the past primarily because of limited data.
The largest data co mpilatio n of g lo ba l POC expo rt previo us ly publi shed was based on
only 70 ri ve rs, in compar iso n to the 359 watersheds used in th is study, covering a
tota l of 64% of the g lo ba l exo re ic area. Even our own estimate may be so mewhat
inflated. ln o ur data set, 63 POC ex port va lu es from catchments located in Sweden
and Canada were based on the assumptio n that POC corresponded to 5% of TOC
tho ugh the studies indicated tha t POC is genera lly less tha n 5% of TOC in
concentratio n (C la ir et a l. , 1994 ; C la ir et a l. , 20 13; Laudo n et a l. , 2004). Furthermore,
it is often reported that small mo unta ino us ri vers (bas in a rea: < 10,000 km2 and
headwater e levation: 1000 to 3000 m) have an extreme ly high POC fl ux (Mill iman &
Syvitski , 1992; Lyo ns et a l. , 2002; Ko mada et al. , 2004), espec ia lly in the so uthwest
Pac ifi e. Our study included 23 4 sma ll ri vers, of which 54 ri ve rs are in the southwest
Pac ifi e, only showed a very weak re latio nship between POC expott and e levation
(R2=0.03, n=254, p=0.007), and this va riable was not reta ined in the POC mode!
using the elast ic net variable se lection procedure.
9 2
Table 2 The compariso ns of our est ima tes of g loba l riverine carbon export to the
oceans with those in previous studies
Rivers DOC DIC POC PIC TOC TIC TC
used
This study 0 .18 0.39 0 .07 0 .04 0.25 0 .43 0 .68 566
Mcybock, 1982 0 .22 0.38 0 . 18 0 . 17 0.4 0 .55 0 .95 27
Mcybock, 1993 0 .20 0 .38 0 . 18 0 . 17 0 .3 8 0 .55 0 .93 60
Mackenzie et al .• 1996 0 .61 0 .72 1.33
Aitkeohead & McDowe11, 2000 0 .36 164
Cuuwet. 2002 0 .25
Dai el al., 2012 0 . 17 11 8
Degens et al.. 1 9 9 1 0 .33
Duce and Duursma. 1977 0 .13
Galy el al .• 2015 0 .20 70
Garre) et al. . 1 973 0 . 13 0 .07 0 .20
Haoda, 1977 0 .30
Harrison et al., 2005 0 . 17 68
Kcmpe, 1979 0 .44 0 .19
Kcmpe, 1985 0 .2 8
Ludwig e l al ., 1996a 0 .2 1 0 .32 0.19 0.40
Ludwig e l al ., 1996b 0 .21 0 . 17 0 .3 8 48
Manloura & Woodward, 1983 0 .78
Michaelis et al , 1986 0 .53
Rciners, 1 973 0 .2 - 1
Richcy el al , 1980 1.00
S chJesinger & M elack, 1981 0 .39 12
Schlunz & Schneider, 2000 0.43 18
Smith & Holhbaugh, 1993 0 .2 0
Spitzy & Iuekkol, 1 99 1 0 .50
Stewart e l al. , 1978 0 .52
Williams, 1971 0 .03
9 3
For PIC export, significant uncertainty remains given the Iimited data we were able to
compile (only 36 rivers) and their geographie coverage (about 16% of the global
exoreic area). However, we argue that our estimate of the global PIC export of 0.04
Pg yr·1 is nevertheless reasonably constrained from the ratio DlC:TIC observed 111
rivers, (median: 0 .95 ; average: 0.96) suggesting that, on average, PIC represent only
about 5% of the TIC export, lower than the fraction we used to estimate it. Our
resulting estimate can therefore be considered an upper limit but is much lower than
the previous reported value of0.17 Pg yr· 1 (Meybeck, 1982), which was itself derived
by assuming that PIC is a constant I% fraction of total suspended matter (Meybeck,
1982; Huang et al. , 20 12).
3.3.3 Past and future effects ofanthropogenic disturbances on global river C export
Human activity is widely regarded as an important driver of global environmental
change, especially in the past five decades, during which the rapid development of
world 's economies is characterized by the expansions of agriculture, industry and
urbanization . Our models ali include the fraction of the catch ment used as croplands
as a major driver of C export. They can therefore be used to estimate how much of
the current global export may be attributed to agriculture. Recalculating the export of
ali 5664 catchments wh ile imposing 0% cropland results in a global estimate of 0.40
Pg yr·1, suggesting that the cur-rent extent of agriculture worldwide accounts for 0.28
Pg yr· 1 (about 40%) of the present global carbon export to the oceans . According to
our models , the bulk (nearly two thirds) of this carbon associated with agriculture is
inorganic, consistent with the results from the Mississippi basin where the extent of
croplands within various sub-basins was directly related to alkalinity export
(Raymond and Cole 2003) . Projections from the FAO of agricultural requirements to
9 4
feed the world's growing populatio n (Alexandratos and Bruinsma 20 12) suggest that
cropland s will expand at a rate of abo ut 0.1 % per year over the 2050 ho rizon. T his
va lue is the net result offo recasted reductio n in croplands in develo ped co untries (at a
rate of -0 .14% per year) but a much faster increase in the deve lo ping wo rld (+0.24%
per year), particula rly in Latin America (+0.49% per year). Depending on the carbon
export profil e of agricultura l land abandoned because of severe land degradation and
a lso on the geographical location of this future expansion, our models suggest that
tota l carbon export co uld increase by up to 15 % by 2050. Much greate r changes can
be expected at loca l scales. Taking the Changj iang catchment as an 'example,
if %cropland increases fi·om the cur-rent 34% to 80%, and assumin g other variables
remain co nstant, the tota l C exported to the coasta l ocean by th is river w ill inc rease
by 45%. As a genera l rule, it is the DlC and POC exports that are the most sens itive
carbon fo rms to a convers ion to cropland . T his therefo re implies that g lo bal cropland
expansio n w ill modify riverine C expo rt not only in its magnitude but a lso in its
co mpos itio n. The potentia l co nsequences of such co mpos it iona l changes on the
oceanic carbo n processing are currently unknown but may a lter sig nificantly the
fun ctioning of the coasta l eco systems rece iv ing these carbo n loads.
S imila rly we can co nsid er the potentia l effects of chang ing c limatic regimes on
carbon expo rt. Using the scenario proposed by Cao et a l. (20 1 0) that a doubling in
atmospheric C0 2 would results in a 15% increase in runoff, o ur mode l would suggest
a commensurate increase of about 12% in tota l carbon expo rt. Wh ile this conc lusion
depend s strong ly on the geographie distribution of the predicted increases in runoff,
such predictio ns co uld nevertheless be integrated to our modeling approach to y ie ld
better predictions of c limate induced effects on C expo rt . Regardless of the exact
9 5
magnitude of chan ges, our study highli ghted that anthropogenic disturbances, past
and future, may have become the most impo rtant factors modify ing the magnitude
and compos ition of ri verin e C export from terrestria l to aquatic ecosys tems,
particula rly in the co ntext of g lo ba l env iro nmenta l change.
3.4 M ETHODS
ln this study, a li the data on C co ncentratio ns and expe rts to the oceans are co llected
fro m jo urnal papers, technica l reports and books published after 2000 . T he co mplete
data co mpila tio n is provid ed in SI-Table 5.1. A li the riverine C concentratio ns and
expe rts were fi e ld observed for at least 1 year w ith a frequency of at !east 3-4 times .
Some big rivers were measured severa! times fo r di ffe rent studies. ln this case, we
use the average of the va lues fo r that river. Ri verine C expo rt, when not provid ed
directly, was calculated as C export (g m-2 yr-1) == C concentration (mg L-1) X
annual discharge (m3)/catchment area (m2). A il the data on river discharge and
catchment a rea are based on Mey beek and Ra gu ( 1996) or the specifie references,
while river mo uth coordinates are corrected by Google .Maps. The catchment
de lineatio n for each river bas in was o bta in ed fro m the Hydro Bas in s product
(http ://www.hydrosheds .org/page/hydro bas ins) matching the river mo uth locations.
The basin po lygons were then used to extract the catchment characteri stics using the
g lo ba l raster fil es fo r annua l runoff(mm yr-1) , catchment s lo pe and area.
The same process was then applied to a li other exo rhe ic catchments dra inin g into the
oceans thereby a llowing the applica tio n of the multiva riate mode ls to a li catchments
that had not been sampled in our database. A li stati stical ana lyses were perfo rmed in
JMP Pro 12. Variable selectio n for the multiva riate regress ion models was carried out
usin g the e last ic net a lgo rithm co upled with the Bayes ia n Information C rite rio n (BI C)
9 6
validation procedure, as implemented in JMP Pro 12. Although this procedure does
not necessarily rely on probability levels for variable retention, ali the variables
retained in the models were statistical ly significant (p<O.OO 1 in ali cases) .
9 7
CHAPTERlY
CONCLUSIONS
4.1 Main contributions:
The co mmon theme of this thes is is to explore the natura l and anthro pogenic dri vers
of carbo n expo tt fro m watersheds to aquatic ecosystems, as we il as the re lative
impo rtance of indiv idua l drivers in co ntro l ling the magnitude and co mpos itio n of the
tota l carbo n expo rted in di fferent fo rms to the rece iving waters, through
systematica lly ana lyz in g the carbo n database of 127 rivers and streams in Q uebec that
had been sampled for 1-3 years by the Aquatic group of UQAM, and then shifts the
study from a catchment and reg iona l sca le to the g lo ba l sca le fo r a further ex plo ration
of them based on the g lo ba l carbo n dataset that were poo led and integrated fro m the
prev io us ly-scattered knowledge and data in the literature regarding riverine carbon
export to the oceans. On the bas is of the co mbinat ion of the large amo unts of regio nal
and g lo ba l C data, this thes is has (re)assessed and predicted the magnitude,
co mpositio n and trend of the tota l carbon expotted fro m watersheds to the receiving
waters at di ffe rent spatia l and tempora l scales, and deve lo ped a better understanding
of the ro te and importance of riverine carbon export in regio na l and glo ba l carbon
cyc les, quant itative ly and qua litat ive ly.
9 8
Specifically, the following key points emerge from the different chapters:
4.1.1 T he study on the re lative influence of topography and land cover on inorganic
and organic carbo n export from temperate catchments has s imultaneo usly explo red
DOC and DI C expo rt to river systems, based on a la rge amo unt of regiona l
observatio ns that max imize the spat ia l coverage and env iro nmenta l gradients and that
captures some of the seaso nal variabili ty in river d ischarge and C concentratio n. This
study has c lar ified the ro le and importance of d ifferent ind iv id ua l drivers of DOC and
DI C exports fro m the watersheds, in particular, that topography is more important
than land cover in expla ining the va riance in D!C expo rt, whereas land cover is much
more impo rtant than topography in terrns of DOC export. T his furthe r hig hli ghts
hum an activ it ies that lead to land use/cover change, such as urbanizat io n,
defo restat ion and wet land c learance, can potentia ll y modify the magnitude and
co mposit io n of the tota l C expo rt from watersheds. The explorat ion of the
inter-annual va riation of DI C and DOC expo rt fro m these temperate catchments
demonstrates that the flu ctuations in precipitatio n and temperature due to climate
change or g lobal warming wo uld to some extent mod ify TC e port and DIC/DOC
ratio, because of the di ffe rent responses of DOC and DI C exports to prec ipitation and
9 9
temperature , w hich could prov id e sorne bases fo r the predictio n of C export and
wate r qua lity changes triggered by regiona l or glo ba l c limate shi fts.
4.1.2 As a fo llow up of the patterns observed in the fi rst chapter and m order to
further understand environmenta l drivers of carbon export to rive r systems m the
bo real bio me, the seco nd chapter foc used on the expo rt of disso lved (DOC and DI C),
and gaseous (C0 2 and C H4), so as to quantify the spatia l and tempo ra l va riations in
the magnitude and co mpos itio n of the to ta l carbo n expo rted fro m a w ide range of
bo rea l watersheds.Total ex po rt peaked in spr ing and var ied w ide ly in its magnitude
and co mpos ition seaso na lly, but was dominated by DOC on an annual bas is . T he
integrated aquat ic C02 emiss io ns were a lso a majo r co nt ributor to the tota l C expo rt
fro m these watersheds, and replaced DOC as the dominant C spec ies in watersheds
with hig h water dens ities.
4.1.3 On the bas is of Chapters 1 and 2 that addressed the natura l and anthro pogenic
drivers of carbon expo rt fro m e ither temperate and borea l watersheds to river systems
and the compositio n and magnitude of tota l carbo n exported in di ffe rent fo rms at a
regio na l scale, the third chapter shi fts from a catchme nt and regional sca le to the
g lo be to explore the natura l and anthro pogenic drivers of g lo ba l riverine carbo n
export to the oceans, and to reassess the g lo ba l ri verine carbo n export rate based on a
l 0 0
synthesis and meta-analysis of the most extensive river carbon dataset assembled to
date. We produce a new an nuai globa l riverine carbon export rate of 0.68 Pg C yr·1,
24% less than the wide ly-accepted va lu e of0.9 Pg C yr· 1 (e.g. Battin et al. , 2009; Co le
et al. , 2007; Tranvik et al. , 2009). Our revised estimates of g loba l DOC and DlC
export, O. 1 8 and 0.39 Pg C yr· 1, respectively, are sim i !ar to the wide ly-used va lu es of
around 0.2 (e.g. Meybeck, 1982&1993; Ludwig et a l, 1996; Harrison et al. , 2005 ; Dai
et al. , 20 12) and 0 .38 (Meybeck, 1982& 1993) Pg C yr·1, respectively. However, we
narrowed the uncertainties of the previous est imations of POC and PIC exports and
obtained the an nuai global riverine POC and PIC exports of 0.07 and 0.04 Pg C yr· 1,
respectively, using the most extensive POC data coverage to date. T his g loba l study
a lso has further clarified the relative importance of different drivers of riverine carbon
export from terrestrial ecosystems at a g loba l scale. Our multiple regression analyses
have further shown that human activities, especially crop land expansion, may become
a main regulator of the magnitude and compos ition of total riverine carbon export to
the oceans in the future. Our models predict that a 15% increase in runoff, predicted
under a doubling of atmospheric C02 (Cao et al. , 201 0) cou ld lead to an increase of
12% in total carbon export to the oceans, whereas increases in the cropland area w ill
result in proportionately larger shifts in the magnitude and composition of total C
l 0 1
export. Fo r example , an increase in cro pland coverage in the Changj iang catchment
fro m the current 34% to 80% of the tota l surface would result in an inc rease in the
export of DOC, Dl C and POC by 17%, 48% and 42%, respect ive ly, w ith a resulting
inc rease in tota l C export fro m this catchment of 45%.
4.2 Main innovations
4.2.1 Whereas prev ious studies on watersheds to rivers have focused mainly on
spec ifi e C species and on individua l drive rs of carbo n expo rt, this thesis has
co mparative ly explored the re lative influence of the ensembl e of topography and land
co ver variables on tota l riverine carbon expo rt and its ma in co mpo ne nts, scaling fro m
individua l watersheds to the g lo be. At the reg io na l scale, an examinatio n of va riance
partitio ning in our mode ls revea led that topography is s lig htly mo re impo rtant than
land-cover in explaining the va riance in DIC export ( 19% vs 15%), whereas
land-cover is much mo re important tha n topography in determining DOC expo rt
(44% vs 18%). This di ffe rence between topography and land cover in co ntro lling
DOC and DIC expo rts to rivers wo uld lead to the changes in magnitude and/o r
compositio n of tota l carbo n expo rt beca use of the di ffe rence in anthro pogenic impacts
on the two categories of driv ing fo rces. Acco rding ly, the trend s in tota l carbo n and its
l 0 2
components exported from watersheds could be predicted based on the degree of
anthropogen ic disturbances.
4.2.2 This thesis has sketched an integrated view of total carbon export from boreal
watersheds to river systems through exploring the spat ia l and tempora l var iations in
total carbon and its components (DOC, DIC, POC, C02 and CH4) exported from the
boreal landscape. This st udy not on ly explored the intra-annual variation in the
magnitude and composit io n of total carbon exported from the boreal watersheds also
compared the tota l carbon between the neighboring sub-reg ions that are characterized
by different landscapes (James Bay is dominated by peatlands, while in Abitibi
beaver damming is ubiquitous a lo ng streams), and thus developed a better
understand ing of the spat ial and temporal variations in carbon export to ri ver systems
at a regional scale.
4.2.3 This thesis reports a re-estimate of globa l riverine carbon expo rt to the oceans
based on the most extensive global C dataset to date. Thi s g lobal study yie ld s a new
global riverine carbon export rate of 0.68±0.05 Pg C yr·1 to the oceans, 24% lower
than the widely-accepted va lu e of 0.9 yr· 1 through narrowing the uncertainties in the
previous estimat ions. Through a series of multiple linear regression ana lyses, the
relative importance of different natural and anthropogenic drivers of riverine carbon
l 0 3
expo rted in di ffe rent fonns fro m land to sea has been fu rthe r c larified . Especia ll y, we
fo und that %croplands in the watershed like runoff (though runoff can expla in
40-58% variance in riveerine carbon export) is an impo rtant varia ble intluenc ing a li
the different carbon forms (DOC, DIC and POC). ln particular, the current cropland
coverage of the g lo ba l terrestria l area is aro und Il %, hav ing huge potentia l of
cropland expans ion, white the g lo ba l runoff has inc reased less than 4% since 1880
(Labat et a l. , 2004; Da i et a l. , 2009), hig hli g hting huma n activ ities, espec ia lly
cropland expans io n around the world , wo uld become a ve ry important va riable
influencing the g loba l riverine carbon ex po rt to the oceans in the future.
4.3 Important implications
The findin g that to pography is s lig htly more important than land-caver in expla ining
the va riance in DI C export (1 9% vs 15%), wh ereas land-ca ver is much mo re
impo rtant than topography in detennining DOC expo1t (44% vs 18%) fro m the
watershed to rivers impli es that how to effective ly and ratio na lly use and manage land
reso urces wo uld be very important to direct the trend of riverine carbon export fi·om
watersheds to aquatic ecosystems scaling from a catchme nt to the glo be . T he average
of tota l carbon exported fro m the boreal watersheds to the rive r systems ( 15.6 gC m·2
yr·1) is in the a rder of 5 to 1 1% of the reg iona l NPP, but of the sa me magnitude of the
l 0 4
Net Ecosystem Production that has been estimated for this type of landscape
highlighting the need to integrate carbon export from watersheds to river systems into
terrestrial carbon budgets in order to improve our understanding of landscape C
sources and sinks within the boreal biome. Further, our re-ana lys is of the g lobal
export dataset resulted in a new estimate of annua l g loba l riverine carbon export to
the oceans of 0.68 Pg yr· 1, which is signifi cantly lower than current accepted figure of
0.9 Pg yr·1, of which DOC, POC, DIC and PIC exports are 0 . 18, 0.07, 0.39 and 0.04
Pg yr·1, respectively, imply that it is necessary to reassess the role and importance of
carbon export from watershed to river systems in terrestrial and g lobal carbo n. The
thesis has a lso contributed to narrowing down the uncertainties in the estimations of
other C reservoirs, which is essentia l to better constrain the regiona l and global
carbon budget. T he finding that o/ocropland in the watershed is c losely related to the
riverine carbon export through the globa l ana lysis of riverine carbon export to the
oceans further implies that human activities , espec ia lly crop land expansio n, may be
replacing the natural driving forces as the primary determinants of the magnitude and
composition of both current and future transfers of carbon from land, through the
hydro logie network, and ultimate ly reaching to sea, further indicating the importance
of land use and management in co ntro lling riverine carbon export from terrestrial to
1 0 5
aquat ic ecosystems m the co ntext of c limate and human-induced envi ronmenta l
changes.
N.B. References c ited in this chapter are presented at the end of the thes is .
CD
0
l 0 7
REFERENCES
Abri! , G., Etcheber, H., Borges, A. V. , and Frankignoulle, M. (2000). Excess
atmospheric carbon dioxide transported by rivers into the Scheldt estuary. Earth and Planetary Sciences, 330:76 1- 768.
Âgren, A. , Buffam, 1., Berggren , M. , Bishop, K. , Jansson, M. , and Laudon, H. (2008).
Dissolved organic carbo n characterist ics in boreal streams in a forest-wetland
gradient during the transition between winter and summ er. Journal of Geophysical
Research, 11 3: 1- 11 , doi:IO.I029/2007JG000674.
Âgren, A., Buffam, 1., Jansson, M. , and Laudon, H. (2007). Importance of seaso na lity
and sma ll st reams for the land scape regulation of dissolved organic carbon export.
Journal of Geophysica/ Research, 11 2, doi: 1 0.1 029/2006JG000381.
Âgren, A. , Janssen, M., lvarsson, H. , Bishop, K. , and Seibert, J. (2007). Seasonal and
runoff-related changes in total organic carbon concentrat ions in the River Ore,
Northern Sweden. Aquatic Sciences, 70:21 - 29, doi: 10. 1 007/s00027-007-0943-9.
Ahlstrom, A. , Schurgers, G. , Arneth, A. , and Sm ith , B. (2012). Robustness and
uncertainty in terrestrial ecosystem carbon respo nse to CM IP5 climate change
projections. Environmental Research Letters 7(4):044008.
A itken head , J. A. and McDowell , W. H. (2000). Soi! C:N ratio as a predictor of
annua l riverine DOC flux at loca l and g lobal sca les. Global Biogeochemical Cycles ,
14(1):127- 138.
Alexandratos, N. and Bruinsma, J. (20 12) . World agricu lture towards 2030/2050: the
20 12 revision. ESA Working paper no. 12-03. Rome, FAO.
Allan, J . D. (2004). Landscapes and riverscapes: the influence of land use on stream
ecosystems. Annal Review of Ecology, Evolution, and Systematics , 35:257- 284,
doi: 1 0.1146/ann urev.eco lsys.35. 120202. 11 0122.
A lvarez-Co belas , M. , Angeler, G . D., Sanchez-Carrillo, S ., and Almendros, G. (20 12).
A worldw id e view of organic carbo n export fi·om catchments. Biogeochemistry,
107:275-293, do i: 10. 1 007/s 10533-0 1 0-9553-z.
Amiotte-Suchet P. , Probst, J.-L. , and Ludwig, W. (2003). Worldwide distribution of
continental rock lithology: impli cations for the atmospher ic/soi l co2 uptake by
l 0 8
continenta l weather ing and alkalinity river transport to the oceans. Global
Biogeochemical Cycles, 17, doi: 10.1 029/2002GBOO 189 1.
Armstrong, A., Holden, J., Kay, P. , Francis, B., Fo ulger, M. , G ledh ill , S., McDonald ,
A. T., and Walker, A. (20 1 0) . The impact of peatland drain-blocking on dissolved
organ ic carbon loss and discolouration of water: results from a national survey.
Journal of Hydrology, 3 81 : 1 12- 120.
Aselmann, 1. and Crutzen , P. J. (1989). Globa l distribution of natural freshwater wetlands and rice paddies, their net primary productivity, seasonality and possible
methane emissions. Journal of Atmospheric Chemistry, 8:307-358.
Asselin , H. , Belleau, A., and Bergeron, Y. (2006). Factors responsible fo r the
co-occurrence of forested and unforested rock outcrops in the boreal forest. Landscape Eco /ogy, 2 1 :271 - 280, doi: 10 .1 007/s 10980-005-1393-1 .
Aucour, A., Sheppard, S., Guyomar, 0., and Wattelet, J. ( 1999). Use of 13C to trace
origin and cyc ling of inorgan ic carbon in the Rhône river system. Chemical Geology, 159:87-105.
Aufdenkampe, A. K. , Mayorga, E. , Raymond, P. A., Melack, J. M., Doney, S. C., Alin, S. R. , .. . Yoo, K. (20 Il ). Riverine coup ling of biogeochemical cycles between land,
oceans, and atmosphere. Frontiers in Eco/ogy and the Environment, 9( 1 ):53- 60, doi: 10.1890/ 100014.
Baker, A. , Cumberland, S., and Hudson, N. (2008). Disso lved and total organic and inorganic carbon in sorne British rivers. A rea, 40(1 ): 117-127.
Barnes, R. T. , and Raymond , P. A. (2009). The contribution of agricultural and urban
activ ities to inorganic carbo n fluxes within temperate watersheds. Chemical Geology, 266:318-327.
Bastviken, D., Tranvik, L. J. , Downing, J. A., Cri ll , P. M. , and Enrich-Prast, A. (2011).
Freshwater Methane Em iss ions Offset the Continenta l Carbon Sink. Science, 33 1 (60 13):50.
Battin, T. J., Luyssaert, S. , Kaplan , L. A., Aufdenkampe, A. K., Richter, A., and Tranvik, L. J. (2009). The boundless carbon cyc le. Nature Geoscience, 2:598-600, doi : 10. 1 038/ngeo618 .
1 0 9
Bauer, J. E., Ca i, W.-J ., Raymond , P. A., Bianchi , T. S. , Hopkinso n, C. S. , and Regnier,
P. A. G. (20 13). The changing carbon cyc le of the coasta1 ocean. Nature, 504:61-70,
doi : 10. 1 038/nature 12857.
Bayon, G. , Dennielou, B., Etoubleau , J., Ponzevera, E., Toucanne, S. , and Bermell , S.
(20 12) . lntens ify ing weathering and land use in iron age central Arr ica. Science, 335: 1219-1 222.
Benstead, J. P. and Leig h, D. S. (20 12). An expanded ro te for river networks. Nature Geoscience , 5(1 0):678-679, doi: 10.1 038/ngeo 1593.
Bergeron Y., Gauthier S. , Flannigan M., and Kafka V. (2004). Fire regimes at the
transition between mixed wood and coniferous boreal forest in no rthwestern Quebec.
Ecolo gy, 85: 191 6- 1 932.
Bergeron, 0 ., Margo lis, H. A. , Coursolle, C., and Giasson, M.-A . (2008). How does
forest harvest influence carbon dioxide fluxes of black spruce ecosystems in eastern
North America? Agricultural and Forest Meteorology, 148(4):537-548.
Bergeron, 0 ., Margo lis, H. A. , Black, T. A. , Co urso lle, C., Dunn , A. L., Barr, A. G.,
and Wofsy, S. C. (2007). Co mpari so n of carbon dioxide flu xes over three bo rea l black
spruce forests in Canada. Global Change Bio/ogy, 13( 1):89-1 07 .
Betts, R. A. (2000) . Offset of the potential carbo n sink from boreal forestation by
decreases in surface a lbedo . Nature, 408:187-190.
Billett, M. F. and Moore, T. R. (2008). Supersaturation and evas ion of C02 and CH4
in surface waters at Mer Bleue peatland, Canada. Hydrological Processes, 22 :2044-2054, doi: 10.1 002/hyp .
Bille tt, M. F. , Palmer, S. M., Hope, D., Deaco n, C., Hargreaves, K . J ., Flechard, C.,
and Fowler, D. (2004). Linking land-atmosphere-st ream carbon flu xes in a lowland
peatland system. Global Biogeochemical Cycles, 18:1-12,
doi : 1 O. 1 029/2003GB002058.
Birgand, F. , Appelboom, T. W. , Chescheir, G. M., and Skaggs, R. W. (20 1 1 ).
Estimating nitrogen, phosphorus, and carbon fluxes in forested and mixed-use
watershed s of the lower coastal plain of North Caro l ina: uncerta inties associated with
in frequent sampling. Trans. ASABE. , 54(6):2099-2 11 O.
Brin son, M. M . ( 1976). Organic matter !osses from four watersheds 111 the hu mid
tropics . Limnol. Oceanogr. 21 :572-582 .
l 1 0
Brooks, P. D ., McKnight, O. M. , Bencala, K. E. ( 1 999). The re latio nship between so il
heterotrophic activity, so i! disso lved organic carbo n (DOC) leachate, and
catchment-scale DOC expo rt in headwater catchments. Water Resour. Res. 35:1895- 1902.
Buffam, 1., Galloway, J. N ., Blum, L. K ., and McG iathery, K . J . (2001 ) . A
stormfl ow/baseflow co mpariso n of disso lved organic matter concentratio ns and
bioava ilability in an Appalachian stream, Biogeochemistry, 53:269- 306.
Buffam, 1. , Turner, M. G ., Desai, A. R. , Hanso n, P.C. , Ru sak, J . A ., Lottig, N . R. , ...
Carpenter, S. R. (2011 ) . Integrating aquat ic and terrestrial co mpo nents to co nstruct a
complete carbon budget for a no rth temperate lake district. Global Change Bio/ogy, 17(2) : 11 93- 12 11. do i: 10. 111 llj .1365-2486.20 1 0.023 13.x.
Butman, O. and Raymond , P. A. (20 Il ) . Significa nt eftl ux of carbo n dioxide from
streams and rivers tn the United States. Nature Geoscience, 4: 1-4,
doi: 10. 1 038/ngeo 1294.
Ca i, W., Guo, X. , Chen, C., Dai, M ., Zhang, L. , Zhai, W., Lo hrenz, S., et a l. (2008). A
co mparative overview of weathering intens ity and HC0 3- flu x in the wo rld 's major
rivers w ith emphas is on the Changj iang, Hu anghe, Zhuji ang (Pearl) and Miss iss ippi
Rivers. Continental She(f Research, 28, 1538-1 549.
Callaghan, T. V., Bergho lm, F. , Christensen, T. R., Jonasso n, C., Ko kfe lt, U ., &
Johansso n, M. (20 1 0). A new climate. era in the sub-A rctic : Accele rating c limate
changes and multiple impacts. Geophysical Research Letters, 37, 1- 6.
do i: 10. 1 029/2009GL042064
Cam peau, A. , & Del Giorg io, P. A. (20 14). Patterns in CH4 and C02 co ncentrations
across borea l rivers: Major drivers and impli cat io ns fo r flu v ia l greenho use emiss ions
under c limate change scenarios. Global Change Bio/ogy, 20, 1075- 1088.
do i: 1 0. 1111 /gcb. l 2479.
Campeau, A. , Lapierre, J.-F., Vachon, D., & de l Gio rg io, P. A. (20 14) . Regional
contribution of C02 and CH4 fl uxes from the fl uvia l network in a lowland boreal
landscape of Québec. Global and Planetary Change, 28, 57-69.
do i: 10. 1002/20 13G B004685 .
Cao, Lo ng, Govindasamy Baia, Ken Calde ira, Ramakri shna Nemani , and Geo rge
Ban-Weiss. 201 O. 1 mportance of carbo n diox id e phys io logica l fo rc ing to future
l 1 1
climate change. Proc Natl Acad Sei U S A., 1 07(21 ), 95 13- 9518. doi:
10.1 073/pnas.0913000 107
Cao, M., & Woodward, F. (1998). Dynamic responses of terrestrial ecosystem carbon
cyc ling to globa l c limate change. Nature , 393, 249-252.
Carig nan, R. , D'Arcy, P. , & Lamontagne, S. (2000). Comparat ive impacts of tire and
forest harvesting on water quality in Boreal Shield lakes. Canadian Journal of
Fisheries and Aquatic Sciences, 57(S2), 105-117.
Castonguay, Sébastien and Alain Tremblay (2003), Tectonic evo lution and
significance of Silu rian - Early Devonian hinterland-directed deformation in the
interna i Humber zone of the southern Quebec Appalachians. Can. J Earth Sei. 40,
255-268 .
Cattaneo, A. , and Y. T. Prairie ( 1995), Temporal variabi lity in the chemical
characteristics a long the Riviere de l' Achigan: How many samp les are necessary to
describe stream chem istry? Can. J Fish. Aquat. Sei., 52, 828- 835 .
Chameides, W.L. and Perdue, E.M . (1997). Biogeochemical Cycles (p. 11 5- 136).
Oxford University Press, London.
Charzanowski, T., Stevenson, L. and Spu rrier, D. ( 1983) . Transport of Dissolved
Organic Carbon Through A Major Creek of the North lnlet Ecosystem. Marine
Eco/ogy Progress Series, 13: 167- 174.
Christensen JH , Hewitson B, Busuioc A et a l. (2008). Regional c limate projections. ln:
Solomon S, Ciais, P., A. V. Borges, Gwenaël Abri! , M. Meybeck, G. Folbe1th, Didier
Hauglustaine, and 1. A. Janssens. The impact of lateral carbon fluxes on the European
carbon balance. Biogeosciences 5(5), 1259-1271 .
C lair, T. A. , Pollock, T. L. , & Ehrman, J. M. ( 1994). Exports of carbon and nitrogen
from river basins in Canada's At lantic Provinces. Global Biogeochemical Cycles, 8(4),
441-450. doi: 10. 1 029/94GB02311
Cole, J . J ., and Caraco , N. F. (200 1 ), Carbon in catchments: connecting terrestrial
carbon !osses with aquatic metabolism, Mar. Freshwater Res., 52, 101 - 110.
Cole, J. J. , Caraco, N. F., Kling, G. W., & Kratz, T. K. (1994). Carbon dioxide
supersaturation in the surface waters of lakes. Science, 265, 1568- 1570.
doi: 1 0.1126/sc ience.265.5178.1568
1 1 2
Co le, J. J., Prairie, Y. T. , Caraco, N. F. , Mcdowell, W. H. , Tranvik, L. J. , Striegl, R.
G. , . . . Daniel , M. H. B. , A. A. Montebelo , M. C. Bernardes, J. P. H. B. Ometto, P. B.
D. E. Camargo, A. Y. Krusche, M. V. Ballester et a l. (2002). Effects of urban sewage
on dissolved oxygen , dissolved inorgan ic and organic carbon, and electrical
co nductivity of sma ll streams a long a gradient of urban izat ion in the Piracicaba river
basin, Water Air Soi/ Pol/., 136, 189-206.
Cole, JJ , YT Prairie, NF Caraco, WH McDowell , LJ Tranvik, RG Striegl, CM Duarte,
P Korte la inen, and JA Down ing. 2007. Plumbing the globa l carbon cycle: Integrating
in land waters into the terrestrial carbon budget. Ecosy tems, 1 0, 171-184.
Corre!!, D. L., Jo rdan, T. E. , & Weiler, D. E. (200 1 ). Effects of precipitation, a ir
temperature, and land use on organic carbo n di scharges fi·o m Rhode river watersheds.
Water, A ir, and Soif Pollution, 128, 139-159.
Cox, P. M. , Betts, R. a, Jones, C. 0., Spa ll , S. a, & Totterde ll , 1. J . (2000).
Acceleration of g loba l warming due to carbon-cyc le feedbacks in a coupled c limate
mode!. Nature, 408, 184- 187. doi : 10.1038/3504 1539
Creed, 1. F., F. D. Beai! , T. A. C lai r, ., P. J . Dillon, and R. H. Hesslein (2008),
Predicting export of dissolved organic carbon from forested catchments in g lac iated
landscapes with sha llow so ils, Global Biogeochem. Cycles, 22, n/a- n/a.
doi: 10.1 029/2008GB003294.
Curtin , D. , M. H. Beare, and G. Hernandez-Ramirez (20 12), Temperature and
Moisture Effects on Microbial Biomass and Soi l Organic Matter Mineralization, Soi/
Sei. Soc. Am. J. , 76(6), 2055- 2067, do i: 1 0.2136/sssaj20 12.00 1 1.
D' Arcy, P., & Carignan, R. ( 1997). Influence of catchment topography on water
chemist ry in southeastern Québec Shield lakes. Canadian Journal of Fisheries and
Aquatic Sciences, 54, 22 15-2227.
Dai, A. (20 12). Jncreasing drought under g loba l warming in observat ions and models.
Nature Climate Cha nge, 3( 1 ), 52- 58. do i: 10.1 038/nclimate 1633
Dai, A. , T. Qian, K. E. Trenberth, and J. D Milliman. (2009) . C hanges in continental
freshwater discharge from 1948-2004. Journal ofC/imate, 22, 2773-279 1.
Dai, M., Yin , Z. , Meng, F., Liu , Q., & Cai, W.-J . (20 12) . Spatia l dist ribution of
riverine DOC inputs to the ocean: an updated global synthesis. Current Opinion in
Environmenta/ Sustainability, 4(2), 170- 178. doi: 10.10 16/j.cosust.20 12.03.003.
1 1 3
Danie l, M. H. B., Montebelo , A. A. , Bernardes, M. C., Ometto, J. P. H. B. , Camargo,
P. B. D. E., Krusche, A. V., Ballester, M. V. , et al. (2002). Effects of urban sewage on
dissolved oxygen, dissolved inorganic and organic carbon, and electrical conductivity
of sma ll streams along a gradient of urbanization in the Piracicaba river basin. Water, Air, and Sail Pollution, 136, 189-206.
Dawson, J. J. C., Soulsby, C., Tetzlaff, D. , Hrachowitz, M. , Dunn , S. M. , & Malcolm,
1. A. (2008). Jnfuence of hydrology and seasonal ity on DOC exports from three
contrasting upland catchments. Biogeochemistry, 90, 93 -11 3.
DeCatanzaro, R. , and P. Chow-Fraser (201 1 ), Effects of landscape variables and
season on reference water chemistry of coasta l marshes in eastern Georgian Bay, Can.
J. Fish. Aquat. Sei. , 68, 1009- 1023, doi: 10.1 1 39/F20 11-035.
Dillon, P.J. , & Malot, L. A. (1997). Effect of landscape fo nn on export of dissolved
o rgani c carbon, iron, and phosphorus from forested stream catchments. Water Resources Research, 33( 11 ), 259 1- 2600.
Dillon, P.J. , & Malot, L. A. (2010). Importance of C02 evas ion from sma ll boreal
streams. Global Biogeochemical Cycles, 24, 1- 9. doi: 10. 1 029/2009GB003723
Dillon, P. J., and L. A . Malot (1997) , Dissolved organic and inorganic carbon mass
balances in central Ontario lakes, Biogeochemistry, 36, 29-42.
Dillon , P.J. , and L. A. Malot (2005), Long-term trends in catchment export and lake
retention of dissolved organic carbon, disso lved organ ic nitrogen, total iron, and total
phosphorus: The Dorset, Ontario, study, 1978- 1998, J Geophys. Res. , Il 0,
doi: 10. 1 029/2004JG000003.
Dinsmore, K. J. , Billett, M. F., & Dyson, K. E. (20 13). Temperature and precipitation
drive temporal variab ility in aquat ic carbon and GHG concentrations and fluxes in a
peatland catchment. Global change bio/ogy, 1- 16. doi: 1 0.1111 /gcb. l2209
Dinsmore, K. J., Billett, M.F., & Moore, T. R. (2009). Transfer of carbon dioxide and
methane through the soi l-water-atmosphere system at Mer Bleue peatland , Canada.
Hydrological Processes, 23 , 330- 341. doi: 10.1 002/hyp
Dornblaser, M. M ., & Striegl, R. G. (20 15). Switching predominance of organic
versus inorganic carbon exp01ts from an intermediate-size subarctic watershed.
Geophysical Research Letters, 42(2), 1-9. doi : 10. 1002/20 14GL062349.
1 1 4
Dosskey, M. G ., & Bertsch, P. M. ( 1994). Fo rest Sources and Pathways of Organic
Matter Transport to a Blackwater Stream: A Hydro logie Approach. Biogeochemistry, 24( 1), 1- 19.
Downing, J. A. , Co le, J. J., Middelburg, J. J ., Strieg l, R. G., Ouarte, C. M.,
Korte la inen, P., . . . Laube, K. a. (2008). Sediment organic carbon buria l in
agricultura ll y eutrophie impoundments over the last century. Global Biogeochemical Cycles, 22, 1- 1 O. do i: 10. 1 029/2006GB002854.
Druffe l, E. R. M., J. E. Bauer, and S. Griffin (2005 ), Input of particulate organic and
disso lved ino rganic carbo n from the Amazon to the Atlantic Ocean. Geochem. ,
Geophy. and Geosy. , 6(3), 1-7, do i: 10.1 029/2004GC000842.
Dubo is, K. 0. , Lee, D., & Veizer, J. (201 0). Isotopie constra ints on a lkalini ty ,
disso lved organic carbon , and atmospheric carbon dioxid e flu xes in the Miss iss ippi
Rive r. Journal ofGeophysical Research, 11 5, 1- 11. do i: 10.1 029/2009JG OO Il 02
Dunn AL, Barfo rd CC, Wofsy SC et a l. (2007). A lo ng-term record of carbon
exchange in a bo real black spruce fo rest: means, responses to in terannua l va riability,
and decada l trends. Global Change Bio/ogy, 13(3), 577-590.
EC 1981-20 1 O. Enviro nment Canada. Mean an nuai temperatures from 198 1-2010 at
the fo llowing 13 weather stations: Bonseco urs, Magog, Bromptonvill e, Richmo nd,
Georgeville, St-Camill e Wolfe, Danville, Sherbrooke A, Granby, St-Hyac inthe 2,
Brome, Arthabaska, Sutton.
Eckhardt, B. W., & Moore, T. R. ( 1990). Contra is on Disso lved Organic Carbon
Co ncentrations in Streams, Southern Quebec. Canadian Journal of Fisheries and Aquatic Sciences, 47, 153 7- 1544.
Fa lkowski , P. , Scho les, R. J., Boyle, E. , Canade l! , J., Canfie ld , 0 ., E lser, J., . . . Steffen,
W. (2000). T he G lo ba l Carbon Cyc le : A Test of Our Knowledge of Earth as a System. Science , 290, 29 1- 296.
Ferland, M.- E., P. A. Del G io rg io, C. R. Teodoru , and Y. T. Prairie. (20 12), Lo ng-term
C accumula tio n and tota l C stocks in bo real lakes in no rthern Q uébec. Global Biogeochem. Cycles , 26(4). doi: I0 .1029/2011GB00424 1.
Fiedle r, Sabine, Bett ina S. Hë ll , and Hermann F. Jungkunst. (2006) . Discovering the
importance of late ra l C02 transport fi·om a temperate spruce fo rest. Science of the total Environment, 368(2), 909-9 15.
l l 5
Finlay, K., P. R. Leav itt, A. Patoine, and B. Wissel (20 1 0), Magnitudes and contro ls
of organic and inorganic carbon
northern Great Plains, doi: 1 0.43 19/ lo.20 1 0.55.4 .1 55 1.
flu x through a chain of hard-water lakes on the
Limnol. Oceanogr., 55(4), 155 1- 1564,
Ford, T. E. , & Nai man, R. J. ( 1988). Alteration of carbon cyc ling by beaver: methane
evas ion rates fro m borea l fo rest streams and ri vers. Canadian Journal of Zoo/ogy, 66, 529- 533 . do i: 1 0. 11 39/z88-076
France, R. , H. Culbe1i , and R. Peters (1996), Decreased carbon and nutrient in put to
borea l lakes fro m part iculate organic matter fo llowing riparia n clear-cutting, Environ. Manage., 20(4), 579-583 .
France , R. , R. Steedman, R. Lehmann , and R. Peters (2000), Landscape
Modificatio n of DOC Concentrat ion in Borea l Lakes, Water Air Soif Poli., 122, 153- 162.
France, R. , Steedman, R., Lehmann , R. , & Peters, R. (2000). Landscape Modification of DOC Concentrat ion in Borea l Lakes. Water, Air, and Soif Pollution, 122, 153-1 62.
Freeman, C. , C. D. Evans, D. T. Monte ith, B. Reyno lds, and N. Fenner (200 1 ), Export of organic carbon from peat so il s, Nature, 412, 785.
Freeman , C. , Fenner, N., Ost ie, N. J., Kang, H., Dowrick, D. J., Reyno lds, B. , .. .
Hudson, J. (2004) . Export of disso lved organic carbon fro m peatlands under e levated carbon d ioxid e leve ls. Nature, 430, 1 95- 198.
Ga ly, V. , B. Peucker-Ehrenbrink, and T. Eglinton (20 15), G lobai carbon ex poli fro m the terrestria l biosphere controlled by erosion, Nature, 52 1, 204- 207.
do i: 1 O. 1 038/nature 14400
Gergel, Sarah E., Monica G. Turner, and Timothy K. Kratz. ( 1999). Disso lved organic carbon as an indicator of the scale of watershed in fl uence on lakes and rivers.
Ecological Applications, 9(4) , 1377-1390 .
Girardin, M. P. , P. Y. Bernier, and S. Gauth ie r. (20 Il ). Jncreasing potential NEP of
eastern bo real North American forests constrained by decreasin g wildfire act ivity.
Ecosphere, 2(3), art25 .
Go mi, T. , Sid le, R. C. , & Richardson, J. S. (2002). Understanding Processes and Downstream Linkages of Headwater Systems. BioScience, 52( 1 0), 905- 916.
l l 6
Go ulden, M . L., A. M. S. McMill an, G. C . Winston, A. V. Rocha, K. L. Manies, J. W.
Hard en, and B. P. Bo nd-Lamberty. (20 Il ). Patterns of NPP, GPP, respiratio n, and
NEP du ring bo real forest succession. Global Change Bio/ogy, 17, 855-871 .
G rosse, G. , Harden, J. , Turetsky, M., McG ui re, A. 0 ., Camill , P. , Tarnocai, C. , et a l.
(20 Il ). Vulnerability of high-lati tude so i! o rganic carbon in N orth America to
disturbance. Journal ofGeophysical Research - Biogeosciences, 11 6.
Haei, M., Oquist, M . G. , Buffa m, l. , Âgren, A., Blomk vist, P., Bisho p, K ., ... Laudo n,
H. (20 1 0). Co ld w in ter so ils enhance disso lved organic carbon co ncentratio ns in so i!
and stream water. Geophysical Research Letters , 37, 1-5.
do i: 10. 1029/20 1 OGL04282 1
Hartmann , J ., Jansen, N ., Durr, H. H., Kempe, S. & Ka hle r, P. G lobal
C02-consumptio n by chemical weathering : what is the contributio n of highly act ive
weathering reg io ns? G lo ba l Planet Change 69, 185- 194 (2009).
Hayes, Danie l J ., Dav id P. T urner, G raham Stinso n, A. David McG ui re , Yaxing Wei,
Trist ram O. West, Linda S. Heath et a l. (2012). Reco nc iling est imates of the
co ntempo rary No rth America n carbo n ba lance amo ng terrestria l biosphere models,
atmospheric invers ions, and a new approach fo r estimating net ecosys tem exchange
fro m in ve ntory- based data . Global Change Bio/ogy, 1 8( 4 ), 1282-1 299.
Hazlett, P. W., and N . W. Foster (2002), Topograph ie co ntra is of nitrogen, sul fur and
carbo n transport fro m a to lerant hardwood hills lo pe, Water Air Soif Pol!., 2, 63- 80.
Hazlett, P., K.Broad, A. Gordon, P. Si bley, J. Butt le, and O. Larme r (2008), The
importance of catchment slope to so i! water N and C concent ratio ns in riparian zo nes:
implicat io ns for riparian buffe r w idth. Can. J. Forest Res. , 38, 16- 30,
do i: 1 0. 11 39/X07- 146.
Hedley, C . B., B. 1-1 . Kusumo, M. J. Hedley, M. P. T uohy, and M. Hawke (2009), So i!
C and N seques tration and fe rtili ty development under land recently co nverted fro m
plantat io n fo rest to pastora l fa rming, New Zeal. J. Agr. Res., 52(4), 443-453,
do i: 1 O. 1 080/002882309095105 26.
He im ann , M. and Re ichste in , M. (2008) . Terrestria l ecosystem carbo n dynamics and
e lima te feedbacks. Nature, 45 1, 289-292.
He in, T. , Barany i, C ., Herndl , G . J .. , Wanek, W., & Schiemer, F. (2003) .
A lloc htho no us and autochthono us part icu late organ ic matter in tloodpla ins of the
l l 7
River Danube: the importance of hydrological connectivity. Freshwater Bio/ogy, 48,
220-232 .
Hilto n, R. G . et a l. Tro pica l-cyc lone-driven erosion of the terrestrial bios phere from mounta ins. Nature Geosc i. 1, 759- 762 (2008).
Himes, F.L. , 1997. Nitrogen, Sul fur, and Phosphorus and the Sequestering of Carbon.
ln : Lai, R. , Kimble, J.M. , Fo llett, R. F. , and Stewart, B.A. (Eds.), Soi! Processes and the Carbon Cycle. (p. 3 15-320), CRC Press, New York.
Ho bbie, J. E. & Likens, G. E. ( 1973). Output of phosphoru s, di sso lved organic carbon
and fine particulate carbon fro m Hubbard Brook watersheds. Limnology and Oceanography, 18, 734-742.
Hope D, Billett M F, and Cresser MS. (1994). A Rev iew of the Exp011 of Carbon in
Rive r Water: Fluxes and Processes. Environmental Pollution, 84, 30 1-324.
Hope, D. , Palmer, S. M., Billett, M. F., & Dawso n, J. J. C. (200 1). Carbon dioxide
and methane evasio n from a temperate peatland stream. Limnology and Oceanography , 46(4), 847- 857.
Hornberger, G. M. , Benca la, K. E ., & Mcknight, D. M. ( 1994). Hydro logica l controls
on disso lved organic carbon during snowmelt in the Snake River near Montezuma,
Co lorado . Biogeochemistry, 25, 147- 165.
Hoss ler, K. , & Bau er, J. E. (20 13). Amounts, isoto pie character, and ages of organic
and inorganic carbon expo tted from rivers to ocean margins: 1. Estimates of
terrestrial losses and inputs to the Middle Atlantic Bight. Global Biogeochemical Cycles, 27, l - 16. doi: l O. 1 002/gbc.20033
Hoss ler, K., and J. E. Bauer (20 13), Amounts, isotopie character, and ages of organic
and inorganic carbon expotted fro m rivers to ocean margins: 2. Assessment of natural
and anthropogenic controls, Global Biogeochem. Cycles, 27, do i: 10.1 002/gbc.20034.
Huang, T.-H. , Fu, Y.-H ., Pan, P. -Y. , & Chen, C.-T. A. (20 12). Flu via l carbon flu xes in
tropical rivers. Current Opinion in Environm ental Sustainability, 4(2), 162- 169.
doi: 1 0. 10 16/j.cosust.20 12.02.004
Hudo n, C. , & Carignan, R. (2008) . Cumulat ive impacts of hydro logy and hu ma n
act ivities on water qua lity in the St. Lawrence River (Lake Sa in t-Pierre, Quebec,
Canada). Canadian Journal of Fisheries and Aquatic Sciences, 65(6), 11 65-11 80.
1 1 8
Huntington, T. G ., and G . R. Aiken (20 13), Export of dissolved organic carbon from
the Penobscot River basin in north-central Maine, .J Hydrol. , 476, 244-256.
doi: 10. 10 16/j.jhydrol.20 12.1 0 .039.
Huotari , Juss i, Hannu Nykanen, Martin Forsius, and Lauri Arvola . (20 13). Effect of
catchment characteristics on aquat ic carbon export fi·om a boreal catchment and its
importance in regio nal carbon cycling. Global change bio/ogy, 19( 12), 3607-3620.
Hyvonen, Riitta, Goran 1. Âgren, Sune Linder, Tryggve Persso n, M. Francesca
Cotrufo, Alf Ekb lad , Michael Freeman et a l. (2007). The like ly impact of e levated
[C02] nitrogen deposition, increased temperature and management on carbon
sequestration in temperate and borea l forest ecosystems: a literature review. New
Phytologist, 173(3), 463-480.
lnamdar, S. P. & Mitchell , M. J. 2006. Hydro logie and topographie contra ts on
storm-event exports of disso lved organic carbon (DOC) and nitrate across catchment
sca les. Water Resources Research, 42(3), 1- 16. doi: 10.1 029/2005WR004212.
1 PCC (20 13), Climate Change 2013: The Physical Science Basis. Co ntributio n of
Working Group 1 to the Fifth Assessment Report of the lntergovernmenta l Panel on
C1imate Change (Stocker, T.F. , D. Qin , G .-K. Plattner, M. Tignor, S.K. Allen, J.
Boschung, A. Nauels, Y. Xia, V. Bex and P.M . Midgley (eds.)). Cambridge University
Press, Cambridge, United Kingdom and New York, NY, USA, 1535 pp,
doi : 10. 1 017 /CB097811 07415324.
1 RDA , 1 nst itut de rechercher et de déve loppement en agroenvironnement inc. (2006).
lvarsson, H. , & Jansson, M. (1994). Regional variation ofd isso lved organic matter in
running waters in central northern Sweden. Hydrobiologia, 286, 37- 51 .
Johnson, C. E., C. T. Driscoll, T. G. Siccama, and G . E. Likens (2000); E lement
fluxes and landscape in a northern hardwood watershed ecosystem, Ecosystems, 3(2),
159-184.
Johnson, M. S., Lehmann, J ., Co uto, E. G. , Filho, J. P. N ., & Riha, S . J . (2006). DOC
and DIC in Flowpaths of Amazonian Headwater Catchments w ith Hydrolog ically
Co ntrasting Soils . Biogeochemistry, 81 , 45-57.
Jonsson, Anders, Grete A1gesten, A-K. Bergstrom , Kevin Bishop, Sebastian Sobek,
Lars J . Tranvik, and Mats Jansson. (2007). lntegrating aquatic carbon flu xes in a
boreal catch ment carbon budget. Journal of Hydrology, 334( 1 ), 141 - 150.
1 l 9
Kalff, J. (2002), Limnology-inland water ecosystems, pp 2 18-225 , Prentice-Hall lnc. ,
Upper Sadd le River, New Jersey, USA.
Kardjilov, M. 1. , G. Gisladottir, and S. R. Gislason (2006), Land degradation in
northeastern lceland : present and past carbon fluxes, Land Degrad. Dev., 17, 401-417,
doi: 10. 1 002/ ldr.746.
Kawasaki , M. , Ohte, N. , Kabeya, N. , & Katsuyama , M. (2008). Hydrological contro l
of dissolved organic carbo n dynamics in a forested headwater catchment, Kiryu
Experim enta l Watershed, Japan. Hydrological Processes, 22, 429- 442.
Kellman, L. , H. Beltrami, and D. Risk (2007), Changes in seasonal soi l respiration
with pasture conversion to forest in At lant ic Canada, Biogeochemistry, 82( 1 ) ,
1 01 - 109 . doi: 1 O. 1007 /s 1 0533-006-9056-0.
Kempe, S. (1979) Carbon in the fres hwater cyc le. ln: Solin , 8. , Degens, E. T. , Kempe,
S. and Ketner, P. (Eds) The G lobal Carbon Cycle. SCOPE Rep. 13, Wiley, Chichester,
pp. 3 17-42.
Kling, G. W., Kipphut, G. W. , Miller, M. M. , & O ' Brien , W. J. (2000) . Integration of
lakes and streams in a landscape perspective: the importance of material processing
on spatia l patterns and temporal coherence. Freshwater Bio/ogy, 43, 477-497.
doi: 10.1 046/j.l365-2427.2000.00515.x
Kljun, N. , T. A. Black, T. J. Griffis , A. G . Barr, D. Gaumont-Guay, K. Morgenstern, J.
H. McCaughey, and Z. Nesic. (2006). Response of net ecosystem productivity of
three boreal forest stands to drought. Ecosystems, 9(7), 11 28- 11 44.
Kahler, S. J. , Buffam, 1. , Laudon, H., & Bishop, K. H. (2008). C limate's cont ro l of
intra-annual and interannu al variability of total o rganic carbo n concentration and flux
in two contrasting boreal landscape e lements. Journal of Geophysical Research, 1 13,
1-1 2. doi: 10.1 029/2007JG000629.
Komada, T., Druffel , E. R. M. , & Tru mbo re, S. E. (2004). Oceanic expo tt of relict
carbon by sma ll mountainous rivers. Geophysical Research Letters, 3 1, 1-4.
doi: 1 O. 1 029/2004G Lü 19512
Koprivnjak, J., & Moo re, T. R. ( 1992). Sources, Organic and Fluxes of Dissolved
Carbon in Subarctic Fen Catchments. Arctic and Alpine Research, 24(3), 204-2 1 O.
1 2 0
Kesten, S., Roland, F. , Da Motta Marques, D. M. L. , Van Nes, E. H., Mazzeo, N. ,
Sternberg, L. D. S. L. , ... Co le, J. J. (20 1 0). C limate-dependent C02 emiss ions fro m
lakes. Global Biogeochemical Cycles, 24(2) , 1- 7. doi: 10.1 029/2009GB003618
Labat, David and Goddéris, Yves and Probst, Jean-Luc and Guyot, Jean-Loup. 2004.
Evidence for g loba l runoff increase related to c limate warming. Advances in Water
Resources, 2(6), 631-642.
Lai , R. (2003). Soil erosion and the globa l carbon budget. Environment International, 29, 437 - 450. do i:10.1016/SOI60-4120(02)00192-7
Lamontagne, S. , Carignan, R. , D' Arcy, P. , Prairie, Y. T., & Paré, D. (2000). Element
export in runoff from eastern Canadian Boreal Sh ie ld drainage basins fo llow ing forest.
Canadian Journal of Fisheries and Aquatic Sciences , 57(S2), 118-128.
Lap ierre, Jean-François, F. G uillemette, M. Berggren and P. A. del Giorg io (20 13),
lncreases in terrestrially derived carbon st imulate organic carbon processing and co2
em issio ns m boreal aquat ic ecosystems, Nature Communications, 4,
doi : 10.1 038/ncomms3972.
Larouche, J. R. , Abbott, B. W., Bowden, W. B. , & Jones, J. B. (2015). T he role of
watershed characterist ics, permafrost thaw, and wi ld fire on dissolved organic carbon
biodegradability and water chem istry in Arctic headwater streams. Biogeosciences, 12,
4221-4233 . doi : 1 0.5 194/bg-12-422 1-20 15.
Larsen, J. H. , P. C. Frost, Z . Zheng, C . A. Johnston, S. D. Bridgham, D. M. Lodge,
and G. A. Lamberti (2007), Effects of upstream lakes on disso lved organic matter in
streams, Limnol. Oceanogr. , 52( 1 ), 60-69 .
Laudon, H., Hedtjarn, J. , Sche lker, J ., Bishop, K ., S0rensen, R. , & Âgren, A. (2009).
Response of Dissolved Organic Carbon fo llowing Forest Harvesting in a Boreal
Forest. Ambio, 38(7), 381 -386.
Laudon, H. , Këhler, S., & Buffam, 1. (2004). Seasona l TOC export from seven boreal
catchments in northern Sweden . Aquatic Sciences, 66, 223- 230.
doi: 1 0. 1 007 /s00027-004-0700-2.
Laudon, H. , M. Berggren, A. Âgren, 1. Buffam, K. Bishop, T. Grabs, M. Jansson and
S. Këhler (20 11 ), Patterns and Dynamics of Disso lved Organic Carbon (DOC) in
Boreal Streams: The Role of Processes, Connectivity, and Scaling. Ecosystems, 14(6),
880-893. doi: 10. 1 007/s 1002 1-011-9452-8.
1 2 1
Lauerwald , R. , Hartmann, J. , Moosdorf, N., Kempe, S. , & Raym ond , P. a. (20 13).
What contrais the spatial patterns of the riverine carbonate system? - A case study for North America. Chemical Geology, 337-338, 114- 127. doi: 1 O. 1 0 16/j .chemgeo.20 12. 1 1.01 1
Lauerwald , R. , Laruelle, G. G. , Hartmann , J., Ciais, P., & Regnier, P. A. G. (20 15).
Spatial patterns in C02 evasion from the global river network Ronny. Global Biogeochemical Cycles, 1- 2 1. doi: 1 O. 1 002/20 13G B004679.
Lepisto, A. , M. N. Futter and P. Kortelainen (20 14), Almost 50 years of monitoring
shows that climate, not forestry, contrais long-term organic carbon fluxes in a large boreal watershed, Glob. Change Biol., 20, 1225-1237. doi : 1 O.llll /gcb.l2491.
Li, M., P. A. del Giorgio, A. H. Parkes, and Y. T. Prairie (2015), The relative influence of topography and land caver on inorganic and organic carbon experts from
catchments rn southern Que bec, Canada, J. Geophys. Res. Biogeosci. , 120,doi : 10.1002/20 15JG003073.
Li, S.-liang, Liu , C.-qiang, Li , J. , Lang, Y.-chao , Ding, H., & Li, L. (20 1 0).
Geochemistry of disso lved inorganic carbon and carbonate weathering in a small typical karstic catchment of Southwest China: Isotopie and chemical constraints. Chemical Geology, 277, 301-309.
Li kens, G. E. et al. (eds.) , ( 1981 ). Flux of Organic Carbon by Ri vers to the Oceans
CONF-8009140, National Technicallnformation Service, Springfield, pp. 4- 15 .
Likens, G. E., and F. B. Bormann (1974), Linkages between Terrestrial and Aquatic Ecosystems, BioScience, 24(8), 447-456.
Likens, Gene E. (20 1 0), Biogeochemistry of In/and Waters , pp. 591-600, Academie,
San Diego, Calif.
Lindroth, Anders, Leif Klemedtsson, Achim Grelle, Per Weslien, and Ola Langvall.
(2008). Measurement of net ecosystem exchange, productivity and respiration in
three spruce forests in Sweden shows unexpectedly large so i! carbon !osses. Biogeochemistry, 89( 1 ), 43-60.
Litvak, Marcy, Scott Miller, Steve C. Wofsy, and Michael Goulden. (2003) . Effect of
stand age on whole ecosystem C02 exchange in the Canad ian borea l forest. Journal of Geophysical Research: Atmospheres, 108, D3. DOI: 10.1029/2001 JD000854.
1 2 2
Liu , Z. , Weiler, O. E., Corre ll , O. L. , & Jo rdan, T. E . (2000). Effects of land caver and
geo logy on stream chemi stry in watersheds of Chesa peake Bay. Journal of the
American Water Resources Association, 36(6), 1349- 1365.
Lloret, E., Dessert, C., Gai lla rdet, J., A lbéric, P., Crispi, 0., Chaduteau, C., & Benedetti , M. F. (20 Il ). Co mparison of disso lved inorganic and organic carbo n y ie ld s
and flu xes in the watersheds of tro pical vo lcanic is lands, exa mples fro m G uadelo upe
(French West lndies). Chemical Geology, 280, 65-78.
Lottig, N . R., Stanley, E. H., & Maxted, J. T. (2 01 2). Assess ing the influence of
upstream dra inage lakes on flu via l organic carbo n in a wetland-rich reg io n. Jo urna l of
Geophys ica l Research, 11 7(G3), G030 Il . do i: 1 O. 1029/20 1 2JG00 1983
Ludwig, W. , Probst, J. , & Kempe, S. ( 1996) . Predicting the oceanic input of organic
carbo n by co ntinenta l erosio n. Global Biogeochemical Cycles, 1 0( 1 ), 23-4 1.
Ludwig, Wo lfga ng and Ami otte Suchet, Philippe and Probst, Jean-Luc. Rive r
discharges of carbo n to the world's oceans: determining loca l inputs of a lka linity and
of disso lved and particula te organic carbo n. ( 1996) Sc iences de la terre et des
planètes (Comptes rendus de l'Académie des sc iences) , 323: 1007-1 0 14.
Lyo ns, W. B., Nezat, C. A. , Carey, A. E., & Hicks, O. M . (2002). Organic carbon
flu xes to the ocean from hig h-standing is land s. Geo logy, 30(5), 443-446.
do i: 1 0. 11 30/009 1-76 13(2002)030<0443
Mackenz ie FT, Lerma n A, Ver LMB. Ro te of the co nt inenta l marg in in the glo ba l
carbo n ba lance during the past three centuries. Geo logy 1998, 26(5): 423-426.
Macpherso n, G. L. , J. A. Ro berts, J. M. Bla ir, M. A. Townsend, O. A. Fowle, and K.
R. Be isner (2008), lncreas ing sha llow groundwater C02 and limes tone weathering,
Konza Prai rie, USA . Geochim. Cosmochim. AC. , 72, 558 1- 5599.
do i: 10.10 1 6/j.gca.2008.09.004.
Maetens, W., Vanmaercke, M. , Poesen, J., Jankauskas, B. , Jankauskiene, G. , lonita, I.
(20 12).
Marchand , 0 ., Prairie, Y. T., & de l G iorgio, P. A. (2009) . Linking fo rest tires to lake
metabo lism and carbon dioxid e emiss ions in the borea l reg ion of No rthern Q uebec.
G loba l C hange Bio logy, 15( 12), 286 1- 2873. do i: 1 0. 1111 /j .l 365-2486.2009.0 1979.x.
l 2 3
Markewitz , 0 ., Dav id so n, E. A., Figue iredo, R. O. 0., Victo ria, R. L. , & Krusche, A.
V. (200 1 ) . Co nt ro l of cat ion concentrat ions in stream waters by surface so il processes
in an Amazo nian watershed . Nature , 4 10, 802- 805. doi: 10. 1038/35071 052.
Marland , G., C. Garten, W. Post, and T. West (2004), Studies on enhanc in g carbo n
sequestrat io n m so ils , Energy, 29(9- 1 0), 1643- 1650.
do i: 10. 10 16/j.energy.2004.03 .066.
Mattsso n, T. , Fin ér, L. , Korte la inen, P. , & Sa llantaus, T. (2003). Brook water qua lity
and background leaching fro m unmanaged forested catchments in Fin land . Water, Ai r,
and So i! Po llutio n, 147, 275- 297 . doi: IO.I 023/A: 1024525328220
McDowe ll , W. H. & Likens, G. E. ( 1988). O rigin , co mpos it io n, and flu x of disso lved
organic carbo n in the Hubbard Brook Valley. Ecological Monographs, 58, 177-1 95 .
McLaughlin, J . W., & Phillips, S. A. (2006) . So il carbon, nit rogen, and base cation
cyc ling 17 years after who le-tree harvesting in a low-e levat io n red spruce (Picea
rubens) -ba lsam tir (Abies ba lsamea) fo rested watershed in centra l Ma ine, USA.
Forest Eco/ogy and Management , 222, 234-253 .
Mengistu , S . G. , C reed, 1. F. , Webster, K. L. , Enanga, E. , & Beall , F. O. (20 14).
Searching fo r s imila rity in to pographie contro ls on carbo n, nitrogen and phosphorus
ex port from forested headwater catchments. Hydrological Processes, 28(8),
3201 - 32 16. do i: 1 O. 1 002/hyp.
Meybeck, M . ( 1982). Carbon, nit rogen and phosphorus transport by wor ld ri vers.
American Journal of Science, 282, 40 1-450.
Meybeck, M. ( 1993). Riverin e transpo t1 of atmospheric carbon: So urces, globa l
typo logy and budget. Water, Air & Soit Pollution, 70, 443-463 .
Meyer, J . L. , & Tate, C. M. (1983). T he Effects of Watershed Disturbance on
Disso lved Organic Carbon Dynamics of a Stream. Eco/ogy, 64( 1 ), 33-44.
Mille r, V. C. ( 1953), A Quant itative Geo mo rphic Study of Dra inage Basin
Characteri st ics in the C linch Mounta in Area, Virginia and Tennessee. Office ofNava l
Research, Geography Branch. Project No. 389042. Techn ica l Report No . 3, 1-30.
Milliman, J. 0 ., & Syv itski , J. P. M. ( 1992) . Geomorphic/Tectonic Co ntro l of
Sediment Discharge to the Ocean: The Importance of Sma ll Mo unta ino us Rive rs. T he
Journa l ofGeo logy, 1 00(5), 525- 544.
l 2 4
Moatar, F., and M. Meybeck (2007). Riverine fluxes of pollutants: Towards
predictions of uncertaint ies by flux duration indicators. C. R. Geosci., 339, 367- 382.
doi: 10.10 16/j.crte.2007.05.00 1
Molot, L. A. , & Dillon, P.J. ( 1996). Storage of terrestrial carbon m boreal lake
sed iments and evasio n to the atmosphere. Global Biogeochemical Cycles, 1 0(3),
483-492.
Moore, TR & Jackson, RJ ( 1989). Concentrations, fluxes and characteristics of
dissolved organic carbon in forested and disturbed catchments, Westland, New
Zealand. Il. Larry River. Water Resources Research , 25 , 1331-1339.
Mortatti J., and J . L. Probst (2003), Si li cate rock weathering and atmospheric/soi l
C02 uptake in the Amazon basin estimated from river water geochemistry: seasonal
and spatial variations . Chem. Geol., 197, 177-196.
M ulho lland, P. J. ( 1997), Disso lved organic matter concentrat ion and flux in streams,
J. N. Am. Benthol. Soc., 16( 1), 131-141.
Mulholland , P.J.and Watts, J.A. 1982. Transport ofürganic Carbon to the Oceans by
Rivers of North America : A Synthesis of Existing Data. Te/lus, 34, 176-186.
Nagendra, H. (2007), Drivers of reforestation in human-domi nated forests, PNAS, 1 04(39), 152 18- 23 , doi : 1 0.1 073/pnas.07023191 04.
Neff, J . C. , and G. P. Asner (2001), dissolved organic carbon in terrestrial ecosystems:
synthesis and a mode!, Ecosystems, 4( 1 ), 29-48, doi: 10.1 007/s 1002 10000058.
Neigh , C. S. R., Nelson, R. F. , Ranson, K. J. , Margolis, H. a. , Montesano, P. M. , Sun,
G. , ... Andersen, H. E. (20 13). Taking stock of c ircumboreal forest carbon with
ground measurements, airborne and spaceborne LiDAR. Remote Sensing of Environment, 137, 274- 287. doi: 10. 10 16/j.rse.20 13.06.019
Nieminen, M. (2004). Export of Dissolved Organic Carbon, Nitrogen and Phosphorus
Fo llowing Clear-Cutt ing of Three Norway Spruce Forests Growing on Drained
Peatland in Southern Finland . Silva Fennica, 38(2), 123-132.
NRC 1995. Natura l Resources Canada. Geo logical Survey of Canada.
NRC 1999. Natural Resources Canada. Canada Land lnventory circa 1966.
NRC 2006. Natural Resources Canada. National Topographie Data Base.
l 2 5
NRC 2009. Natura l Resources Canada. Atlas of Canada. Prec ipitatio n Ma p 41" ed,
1974, Runoff Ma p 61 11 ed , 2009.
O' Drisco ll , N . J ., S ic ili ano, S. D. , Peak, D., Carignan, R. , & Lean, D. R. S. (2006).
The influence of fo restry activity on the structure of disso lved organic matter in lakes :
Implicatio ns fo r me rcury pho toreactio ns. Science ofThe Total Environment, 366, 880
- 893.
Oqui st , M. G. , Wa llin, M., Seibe rt, J ., Biship, K. , & Laudo n, H . (2009). Disso lved
lnorganic Carbon Export Across the Sa il/Stream Interface and lts Fate in a Boreal
Headwate r Stream. Environmental Science & Technology, 43, 7364- 7369.
Pac ifie, V. J . (2009). Hydro logy and land scape structure contro l suba lpine catchment
carbon expo rt . PhD thes is. Montana State Univers ity.
Pac ifie, V. J ., B . L. McG iynn , D. A. Riveros-lregui , D. L. Welsch, and H. E. Epste in
(2008) , Yariability m so i! respirat io n across riparian-hill s lo pe transit ions,
Biogeochemistry, 9 1, 5 1-70.
Pac ifie, V. J ., Jencso , K. G ., & McG ly nn , B. L. (20 1 0) . Variable flu shing mechanisms
and landscape stru cture contro l stream DOC expo rt during snowme lt in a set of
nested catchments. Biogeochemistry, 99, 193-2 1 1.
Pa lmer, S. M., Ho pe, D., Bille tt, M. F. , Dawso n, J. J. C. , & Bryant , C. L. (200 1 ).
Sources of organic and inorganic carbon in a headwater stream: Evid ence fro m
carbo n iso tope studies. Biogeochemistry, 52(3), 32 1- 338.
Paradis, S. , and D. Lavo ie ( 1996), Mul t iple-stage diagenetic a lteratio n and fluid
histo ry of O rd ov ic ian carbo nate-hosted ba rite mine ra lization, Southern Q uebec
A ppa lachia ns, Sediment. Geol., 107, 12 1-1 39.
Piira inen, S. , Fin , L., Mann erkoski , H., & Starr, M. (2002). Effec ts of forest
c lear-cutt in g on the carbo n and nitrogen flu xes thro ugh podzo lic sa il horizo ns. Plant and So if, 239, 301-3 1 1.
Po lsenaere, Pierre, N ico las Savoye, Henr i Etchebe r, Mathie u Canton, Dominique
Po irie r, Steven Bo uill on, and Gwenaë l Abri!. (20 13). Export and degassing of
terrestria l carbon thro ugh waterco urses dra ining a temperate podzo lized catchme nt .
Aquatic sciences, 75(2) , 299-3 19.
Pra irie , Y. T., D. F. Bi rd , and J. J . Co le (2002), T he summ er metabo lic ba lance in the
epilimnio n of so utheastern Quebec lakes, Limnol. Oceanogr., 47( 1 ), 3 16- 32 1.
1 2 6
Priee, D.T. and Apps, M.J. Boreal forest responses to climate change scenarios along
an ecoclimatic transect in centra l Canada. ( 1 996). Climate Change 34: 179-1 90.
Prokushkin, A. S., Kajimoto, T., Prokushkin, S. G., McDowell, W. H., Abaimov, A. P., & Matsuura, Y. (2005). Climatic factors influencing fluxes of dissolved organic carbon from the forest floor in a continuous-permafrost Siberian watershed. Canadian Journal of Forest Research, 35, 2130-2 140.
Pumpanen, Jukka, Aki Lindén, Heli Miettinen, Pasi Kolari , Hannu llvesniemi, Ivan Mammarella, Pertti Hari et al. (20 14). Precipitation and net eco system exchange are
the most important drivers of DOC flux in upland boreal catchments. Journal of
Geophysical Research: Biogeosciences 11 9(9), 1861-1878.
Raich J. W., and C. S. Potter (1995). Global patterns of carbon dioxide emissions from soi ls, Global Biogeochem. Cycles 9: 23- 36. doi: 10. 1 029/94GB02723.
Raike, A. , P. Kortelainen, T. Mattsson, and O. N. Thomas (20 12), 36 year trends in dissolved organic carbon export from Finnish rivers to the Baltic Sea, Se i. Tot. Environ. , 435-436, 188- 201. doi : 10.1 0 16/j.scitotenv.20 12.06.111
Rantakari , M., & Kortelainen, P. (2008). Contro ls of organic and inorganic carbon in random ly se lected Boreal lakes in varied catchments. Biogeochemistry, 91, 151 - 162.
Rantakari , M., and P. Kortelainen (2008), Controls of organic and inorganic carbon in randomly selected Boreal lakes in varied catchments, Biogeochemist1y, 9 1, 151-162.
Rantakari , M. , Mattsson, T., Korte lainen , P., Piirainen, S., Finér, L., & Ahtiainen, M. (20 1 0) . Organic and inorganic carbon concentrations and fluxes from managed and unmanaged boreal first-o rder catchments. Science of The Total Environment, 408, 1649- 1658 . doi: l 0.1 0 16/j .sc itotenv.2009.12.025
Rasera, D. F. F. L. M., Ballester, V. R. M., Krusche, A. V. , Sa limon, C., Montebelo, L. a. , Alin, Richey, J. E. (2008). Est imat in g the surface area of sma ll rivers in the
southwestern amazon and their ro le in C02 outgassing. Earth Interactions, 12(6), 1- 16. doi :l0.1175/2008EI257.1
Rasilo, T. , Y.T. Prairie and P.A. del Giorgio . (20 15). Large-sca le patterns in summer diffusive CH4 fluxes across boreal lakes, and contribution to diffusive C emissions. Global Change Bio/ogy, 21 (3), 1124-1139.
l 2 7
Rasool , Q. A, V. K. Singh and U. C. Singh (20 11), The eva luation of Morphmetric
characteristics of Upper Subarnarekha Watershed drainage basin using
Geoinformatics as a tool, Ranchi , Jharkhand, !nt. J. Environ. Sei. , 7( 1 ) , 1924- 1930.
Raymond, P. A. , & Co le, J. J. (2003). lncrease in the export of alkalinity from North
America 's largest river. Science , 30 1, 88- 9 1. doi: 1 0.1126/science . l 083788
Raymond, P. A. , & Oh, N. (2007). An empirical study of climatic contrais on riverine
C export from three major U.S. watersheds. Global Biogeochemical Cycles, 21 , 1- 9.
doi: 10.1 029/2006GB002783
Raymond, P. A ., and J. E. Saiers (20 1 0), Event controlled DOC export from forested
watersheds, Biogeochemistry, 1 00, 197- 209, doi: 1 0.1007 /s 10533-01 0-9416-7.
Raymond, P. A. , and J. J. Co le (2003), lncrease in the export of a lka linity from No11h
America 's largest river, Science , 30 1, 88-91.
Raymond, Peter A. , Jens Hartmann, Ronny Lauerwald , Sebastian Sobek, Cory
McDonald , Mark Hoover, David Butman, Robert Striegl, Emilio Mayorga, Christoph
Humborg, Pirkko Kortelainen , Hans Dürr, Michel Meybeck, Philippe Ciais & Peter
Guth . (20 13) . Global carbon dioxide emissions from in land waters. Nature, 503,
355-359.
Regnier, P. , Fried lin gstein, P., Cia is, P. , Mackenzie, F. T. , Gruber, N. , Janssens, 1.
A. , ... Thullner, M. 2013. Anthropogenic perturbation of the carbon fluxes from land
to ocean. Nature Geoscience, 6(8), 597-607. doi: 10.1 038/ngeo 1830
Reiners, WA. 1973. A summary of the world carbon cycle and recommendat ions for
critical research. Brookhaven Symp. Biol. 30: 368-382.
Richey, J. E. , Brock, J. T. , Na iman, R. J ., Wissmar, R. C. , & Stal lard , R. F. ( 1980).
Organic carbon: Oxidation and transport in the Amazon River. Science, 207,
1348- 1351.
Richey, J. E. , Brock, J. T., Na iman, R. J ., Wissmar, R. C. , & Sta llard , R. F. ( 1980).
Organic carbon: Oxidation and transport in the Amazon River. Science, 207,
1348- 135 1.
Robinson, S. D. , and W. K. Fyson (1976), Fo ld structures, southern Stoke Mountain
area, Eastern Townships, Québec: Taconic or Acadian? Can. J. Earth Sei. , 13(1 ),
66-74.
l 2 8
Royer, T. V., & David , M. B. (2005). Export of dissolved organic carbon from
agricultural streams in Illino is, USA. Aquatic Sciences, 67, 465-471.
doi: 10.1007 /s00027-005-0781-6.
Rudel , T. ( 1998), ls The re a Forest Transition? Deforestation, Reforestation, and
Development, Rural Sociology, 63(4), 533-552.
Ryan, M. G., Lavigne, M. B., & Gower, S. T. (1997). Annual carbon cost of
autotrophic respiration in boreal forest ecosystems in relation to species and climate.
Journal o.fGeophysical Research, 1 02(97), 28871. doi : 10.1 029/97JDO 1236
Sarma, V. V. S. S., Viswanadham, R., Rao, G. D. , Prasad, Y. R. , Kumar, B. S. K.,
Naidu, S. a., ... Murty, T. V. R. (20 12). Carbon dioxide emiss io ns from Indian
monsoonal estuaries. Geophysical Research Letters, 39(3), n/a- n/a.
doi : 10. 1029/20 Il GL050709
Schlesinger, W. H. , & Melack, J. M. ( 1981 ). Transport of organic carbon m the
world's rivers. Tel!us, 33, 172- 187. doi : 1 0.1111 /j.2153-3490.1981.tb01742.x
Schlesinger, W. H ., and J. M. Melack ( 1981 ), Transport of organic carbon m the
world ' s ri vers, Te !lus, 33, 1 72-187.
Schli.inz, B., & Schneider, R. R. (2000). Transport of terrestrial organic carbon to the
oceans by rivers: re-est imat ing flu x- and burial rates. International Journal of Earth
Sciences, 88, 599- 606.
Seitzinger, S. P., Mayorga, E., Bouwman, A. F., Kroeze, C. , Beusen, A. H. W., Billen,
G ., ... Harrison, J. A. (20 1 0). Global river nu trient export :A scenario analysis of past
and future trends. Global Biogeochemical Cycles, 24, 1- 16.
doi: 10.1 029/2009GB003587
Smith 0 ., and L. Johnson (2004), Vegetation-mediated changes in microc1imate
reduce so i! respiration as woodland expand into grass land, Eco/ogy, 85, 3348- 3361.
Soranno, P. A ., K. E. Webster, J . L. Riera, T. K. Kratz, J . S. Baron, P. A. Bukaveckas,
G . W. Kling et a l. ( 1999), Spatial Variation amo ng Lakes w ithin Landscapes:
Eco log ical Organization along Lake Chains, Ecosystems, 2, 395-4 1 O.
Soranno, P. A., K. E. Webster, J. L. Riera, T. K. Kratz, J. S. Baron, P. A. Bukaveckas,
G. W. Kling, G. W., Kipphut, G. W., & Miller, M. C. (1991). Arctic lakes and streams
as gas conduits to the atmosphere : implications for tundra carbon budgets. Science, 25 1, 298- 30 1. doi : 10. 1 126/science.251.499 1.298
1 2 9
Spencer, R. G. M. , Stubbins, A. , Hernes, P.J. , Baker, A. , Mopper, K. , Aufdenkampe,
A. K. , ... Six, J. (2009). Photochemical degradation of dissolved organic matter and dissolved lignin phenols from the Congo River. Journal of Geophysical Research, 114(G3), G0301 O. doi: 10.1 029/2009JG000968
Spitzy, A., and J. A. Leenheer ( 1991 ), Disso lved organic carbon in rivers, in
Biogeochemistry of major world rivers edited by E. T. Degens, S. Kempe, and J. E. Richey, pp. 213-232, Wiley, New York.
Stanley, E. H. , S. M. Powers, N. R. Lottig, 1. Buffam, and J. T. Crawford (2012),
Contemporary changes in disso lved organic carbon (DOC) in human-dominated rivers: is there a role for DOC management? Freshwater Biol., 57(Suppl. 1 ), 26-42,
doi : 1 O.llll /j. l365-2427.20 11.02613.x.
Stets, E. G. & R. G. Striegl. (2012), Carbon export by rivers draining the
conterminous United States.Jnland Waters , 2, 177- 184. doi: 1 0.5268/IW-2.4.51 O.
Striegl, R. G. , Dornblaser, M. M. , Aiken , G. R. , Wickland , K. P. , & Raymond , P. A. (2007). Carbon export and cycling by the Yukon, Tanana, and Porcupine rivers,
Alaska, 2001 - 2005. Water Resources Research, 43, 1- 9. doi : 1 0.1 029/2006WR00520 1
Striegl , R. G., M. M. Dornblaser, C. P. McDonald , J. R. Rover, andE. G. Stets (2012),
Carbon dioxide and methane emissions from the Yukon River system, Global
Biogeochem. Cycles, 26, doi: 10.1029/20 12GB004306.
Sun, Chao. 2007. Carbon transportation of Yellow River during water and sediment
regulation period and annua l variation of different carbon species at HuauanKou
hydrlogic station. Master 's Thesis. Ocean University of China.
Sun, H. G. , Han , J. , Lu , X. X. , Zhang, S. R. , & Li, D. (201 0). An assessment of the riverine carbon flux of the Xijiang River during the past 50 years. Quaternary
International, 226, 38-43.
Tank, S. E., Frey, K. E., Striegl, R. G. , Raym ond, P. a. , Holmes, R. M. , McClelland , J. W., & Peterson, B. J. (20 12). Landscape-level contrais on dissolved carbon flux from div erse catchments of the circum boreal. Global Biogeochemical Cycles, 26( 4 ), 1- 15.
doi : 1 O. 1 029/20 12G B004299
Tank, S. E., Raymond , P. a. , Striegl , R. G., McClelland, J. W., Holmes, R. M. , Fiske, G. J ., & Peterson, B. J. (20 12). A land-to-ocean perspective on the magnitude, source
1 3 0
and implication of DIC flu x from majo r Arctic ri vers to the Arctic Ocean. Global
Biogeochemical Cycles, 26(4) . do i: 10. 1029/20 Il G B0041 92
Telmer, K., & Veizer, J. (1 999). Carbon flu xes , pC0 2 and substra te weathe ring in a
large no rthern rive r bas in , Canada: carbon iso tope perspectives. Chemical Geology, 159, 6 1-86.
Tetzlaff, D., Ma lco lm, 1. A. , & Soulsby, C. (2007) . Influ ence of fo restry,
environmenta l change and c limat ic variability on the hydro logy, hydrochemi st ry and
res idence times of upla nd catchme nts. Journal ofHydrology, 346, 93- 111.
Tranvik, L. J. , and M. Jansso n (2002), Terrestria l export of o rganic carbon. Nature, 4 15, 86 1- 862, do i: 10. 1 038/4 1586 1 b
T ranvik, L. J. , D owning, J. A ., Cotne r, J . B., Lo ise lle, S. A ., Striegl, R . G. , Ba lla tore,
T. J., ... Weyhe nmeyer, G. A. (2009). Lakes and reservo irs as regulators of carbon
cyc ling and c lim ate. Limnology and Oceanography, 54(6, part 2) , 2298- 23 14.
T ranvik, Lars J. ( 1992), A llochthono us disso lved organic matter as an ene rgy so urce
fo r pe lag ie bacteria and the co ncept of the micro bia l loop, Hydrobiologia, 229,
107-114.
Tremblay, A. , and P. St julien ( 1990), Structura l style and evo lutio n of a segme nt of
the Dunnage Zo ne fro m the Q uebec A ppa lachians and its tectonic implicatio ns, Geol. Soc. Am. Bull., 102(9), 12 18- 1229.
Tripti , M., Lambs, L. , Otto, T. , G urumurthy, G. P., Teisserenc, R., Mo ussa, 1., .. . Probst, J. L. (20 13) . First assessment of water and carbo n cyc les in two tropical
coasta l rivers of south-west lndia : an isotopie approach. Rapid Communications in Mass Spectrometry, 27( 15), 1- 9 . do i: 10. 1 002/ rcm.66 1
United Nations Enviro nme nt Programme (UN E P)---- Mediterranean Act ion Plan
(M AP) (2003), Technica l Repo rts Series No. 14 1 UN EP/ MAP: Riverine Transport of
Water, Sediments and Pollutants to the Mediterranean Sea (p. 12 1 ).
Van Be lle r1, S. , M. Garnea u, and Y. Bergeron. (20 1 0) . Impact of c limate change on
fo r-est fi re seve rity and co nsequences fo r carbon stocks in bo real Quebec, Canada: a
synthes is . Fire Eco/ogy, 6(3), 16-44.
Ver, L. M. B., Mackenz ie, F. T. , & Lerma n, A . 1999). Biogeochemi cal responses of
the carbo n cyc le to natura l and huma n perturbat io ns: past, present, and future.
American Journal of Science, 299, 762- 80 1.
1 3 l
Yidon, P., Wagner, L. E., & Soyeux, E. (2008) . Changes in the character of DOC in
streams du ring storms in two Mid western watershed s with co ntrastin g land uses.
Biogeochemistry, 88 , 257-270.
Yito.usek, Peter M., Haro ld A. Mooney, Jane Lubchenco, and Jerry M. Me lillo. 1997.
Human Do minatio n of Earth 's Ecosystems. Science 277: 494-499 .
vo n Wachenfe ldt, E., D. Bastviken, and L. J . T ranv ik (2009), Mic ro bia lly induced
flocculatio n of a llochtho no us disso lved o rganic carbo n in lakes, Limnol. Oceanogr. , 54(5), 1811 - 1818, do i:10.431 9/ lo .2009.54.5.1811.
von Wachenfe ldt , E., S. Sobek, D. Bastviken, and L. J. Tranv ik (2008), Linking
a llochtho no us disso lved o rganic matter and bo rea l lake sediment carbo n sequestratio n:
The ro le of lig ht-media ted flocculatio n, Limnol. Oceanogr. , 53(6), 24 16- 2426,
do i: 1 0.43 19/lo .2008 .53 .6.24 16.
Wallin , M. B., G rabs, T. , Buffam, 1. , Laudo n, H. , Âgren, A. , Oquist, M. G. , & Bisho p,
K. (20 13) . Evas io n of C0 2 fro m streams - The dominant co mpo nent of the carbon
export through the aquatic conduit in a bo real landscape . Global Change Bio/ogy, 19,
785- 797. do i: 1 0. 1111 /gcb.l 2083
Wall in , M., 1. Buffam, M. G . Oquist, H. Laudo n, and K. Bisho p (20 1 0), Tempora l and
spatia l va riabil ity of disso lved inorganic carbon in a boreal stream network:
Co ncentratio ns and downstream flu xes, J. Geophys. Res., 1 15, 1- 12,
do i: 1 0. 1 029/2009JGOO Il 00 .
Wang F, Wang Y, Zhang J, X u H, Wei X . 2007. Human impact on the histo rica l
change ofC0 2 degass in g flu x in Ri ver Changj iang . Geochem Trans. A ug 9;8:7.
Wang, S. , K . M . Yeager, G . Wan, C. Liu , Y. Wang, and Y. Lü (20 12) , Carbo n export
and HCOf fa te in carbo nate catchments: A case study in the karst plateau of
so uth western Chin a. Appt. Geochem., 27, 64-72,
do i: 10.1 0 16/j .apgeochem.20 11.09.003.
Wang, X., Ma, H., Li , R., Song, Z., & Wu , J . (20 12). Seaso na l flu xes and so urce
va riatio n of organi c carbo n trans po t1ed by two majo r Chinese Rivers: T he Ye llow
Rive r and Changj iang (Yangtze) Rive r. Global Biogeochemical Cycles, 26(2).
do i: 1 O. 1 029/201 1 GB004 130
Waugh, Dav id ( 1995), Geogra phy, An lntegrated approach. 2"d Ed. Cha pter-3
Mo rphometry of dra inage bas ins . pp. 5 1-62 .
1 3 2
Westerhoff, P., & Annin g, D. (2000). Concentrations and characteristics of organic
carbon in surface water in Arizo na: influence of urbanizatio n. Journal of Hydra/ogy,
23 6, 202- 222.
Wilkinson, G. M., M. L. , Pace, and J. J . Co le (2013), Terrestria l dominance oforganic
matter m no rth temperate lakes, Global Biogeochem. Cycles , 27,
do i: 10. 1029/20 12GB004453 .
Willi ams, P. M. (1971) The distributio n and cyc lin g ofo rganic matter in the ocean. ln:
Faust, S. J . and Hunter, J. V. (eds), Organic Compounds in Aquatic Environments, 145- 163 . Marcel Dekker, New York.
Wilson, H. F. , & Xeno poulos, M. A. (2009) . Effects of agricultura l land use on the
compos it ion of flu via l disso lved organic matter. Nature Geoscience , 2, 37-41 .
Winkle r, G ., Lec lerc, V. , Siro is, P., Archambault, P., & Berube, P. (2009). Sho rt-term
impact of forest harvesting on water quality and zoo plankton communities in
o ligo trophic headwater lakes of the eastern Canadian Boreal Shie ld. Boreal Environment Research, 14, 323-337.
Wipfli , M. S. , Richard son, J . S., & Na iman, R. J. (2007). Eco logica l linkages between
headwaters and downstream ecosystems: Transport of organic matter, in vertebrates,
and wood down headwater channels. Journal of the American Water Reso urces
Associatio n, 43( 1), 72- 85. do i:IO.Illl /j . l752-1 688.2007.00007 .x.
Wohl, E., Dw ire, K. , Sutfi n N. , Po lvi , L. , & Bazan, R. (20 12). Mechanisms of carbon
storage in mo unta ino us headwater rivers. Nature Communications, 3, 1263- 1270.
do i: 10.1 038/nco mms2274
Wolock, D. M., Fan, J., and Lawrence, G . B. ( 1997). Effects of bas in size on
low-flow stream chemistry and subsurface co ntact time in the Neversink river
watershed, New York. Hydra!. Process, 11 , 1273- 1286.
Wu, Haibin, Changhui Peng, T. R. Moore, D. Hua, C. Li, Q. Zhu, M. Pe ichl , M. A.
Ara in , and Z. Guo. (20 13). Mode ling disso lved organic carbon in tempera te fo rest
so ils : T RIPLEX-DOC mode! development and va lidatio n. Geosci Mode / Dev Discuss, 6(2), 3473-3508 .
Xeno poulos, Marguerite A., Dav id M. Lodge, Jaso n Frentress, T imothy A. Kreps,
Scott D. Bridgham, Elizabeth Grossman, and Caryn J. Jackson. (2003). Regional
com pari so ns of watershed determinants of disso lved organic carbo n in tempe rate
1 3 3
lakes from the Upper Great Lakes region and selected reg ions globa lly. Limnology and Oceanography, 48(6), 232 1-2334.
Yan, J ., W. Wang, C. Zhou, K. Li , and S. Wang (20 13), Responses of water yie ld and
disso lved inorganic carbon export to forest recovery in the Houzhai karst bas in , so uthwest China, Hydrol. Process, doi: l 0.1 002/hyp.
Yao, G., Gao , Q. , Wang, Z. , Huang, X. , He, T. , Zhang, Y. , ... Ding, J. (2007).
Dynamics of C0 2 partial pressure and C02 outgass ing in the lower reaches of the Xijiang Ri ver, a subtropica l monsoon river in China. Science of The Total
Environment, 376, 255- 266. do i: 10. 10 16/j .scitotenv.2007.0 1.080
Yoon, B. & Raymond , P. A. Disso lved organic matter ex port fi·om a forested
watershed during Hurricane Irene. Geophys . Res. Lett. 39, Ll8402 (20 12).
Yuste, J. C. , D. D. Bald occhi , A. Gershenson, A. Go ldstein, L. Miss ion, and S. Wong (2007), Micro bial so il respiration and its dependency on carbon inputs, so il
temperatu re and moisture, Glob. Change Biol. , 13, 20 18-2035, doi: 10. 1111 /j . l365-2486.2007.0 141 5.
Zak, O. R., W. E. Ho lmes, N. W. MacDonald , and K. S. Preg itzer ( 1999), So it
temperature, matric potentia l, and the kinetics of microbia l respiration and nitrogen mineralization, Soi! Sei. Soc. Am. J. , 63, 575-5 84.
Zeng, F. , C. A. Mas ie llo, and W. C. Hockaday (20 Il ), Contro ls on the origin and
cyc ling of ri verine disso lved inorganic carbon in the Brazos River, Texas. Biogeochemistry, 104, 275-29 1. doi:IO.I007/s l0533-010-9501-y
Zhai, W. , M. Dai, and X Guo (2007), Carbonate system and C0 2 degass ing flu xes in
the inner estuary of Changj iang (Yangtze) River, China, Mar. Chem. , 107, 342-356.
do i: 1 O. 10 l6/j .marchem.2007 .02.0 Il .
Zhang, S. , Lu , X. X., Sun, H., Han, J., & Laurence, O. (2009) . Major ion chemistry
and disso lved inorganic carbon cyc ling in a human-disturbed mountainous river (the
Luodingj iang River) of the Zhujiang (Pearl River), China. Science of the Total
Environment, 407, 2796-2807.
Zhang, S. , Lu , X. , Sun, H., & Han, J. (20 Il ). Modeling catchment controls on organic
carbon flu xes in a meso-scale mounta inous ri ver (Luodingj iang), China. Quaternary
International, 244(2), 296-303.
1 3 4
Zhang, S. , X. X. Lu, H. Sun, J. Han, and D. Laurence (2009), Major ion chemistry and disso lved inorganic carbon cyc ling in a human-disturbed mountainous ri ver (the
Luodingjiang Ri ver) of the Zhuji ang (Pearl River), China, Sei. Total Environ. , 407, 2796-2807.
Zhang, Xiangshan and Longj un Zhang. 2007. Phenomena of pH instant increas ing and its effect on disso lved inorganic carbon flu x to sea in Yellow River Estuary. Environmental Science, 28(6), 111 6-1 222.
------------------------------- - - ----------
1 3 5
Appendi x A
Supplementary Information For
A Global Analysis of Riverine Carbon Export to the Oceans
Sl -1. List and source of landscape characteristics extracted for each catchment draining into the
oceans
Data Type Citation
Fetke, Balazs M . et al (2000). Global Composite Runoff
Fields Based on
Observed River Discharge and Simulated Water
Runoff Raster Balances . Complex
Systems Research Center, University of New Hampshire .
UNH-GRDC
Composite Runoff Fields vl .O. Available at
http:/ /www.grdc.sr.u nh.edu/.
European Space Agency (ESA)- Climate Change
Initiative (CCl) . The Land Caver CCl Climate Research
Land Caver 2010 Raster Data Package (CRDP). Land Caver Maps- vl.S
(2008-2012 epoch). Available at
http:/ /ma ps . elie. ucl .ac. be/CCI/viewer/down load. php
Harmonized World Soil Database Vl.2 Organic
Soil organic C (Top Raster
Carbon density.
0-30 cm) http :/ /www.fao. org/ so ils-porta 1/soi 1-s u rvey /soi 1-m a ps-a
nd-data bases/ha rmo ni zed-world-soil-d a ta base-v12/ en/
Williams & Ford . World map of carbonate rock
Carbonates Polygon (Shapefile) outcrops v3 .0. SGGES, University of Auckland, New
Zealand . Availab le at
http:/ /web .env.auckland .ac. nz/ou r _research/ka rst/
51 -2. Land Caver categories amalgamation
The land caver classes provided by the ESA CCl land caver product (2010) contains 37 distinct
categories. For the purposes of our carbon export madel development, these were simplified to
only 5 classes using the following amalgamation :
% Forests = Sum of {
Tree caver, broadleaved, deciduous, closed to open {>15%)
1 3 6
Tree cover, broadleaved, deciduous, open (15-40%)
Tree caver, broadleaved, evergreen, closed to open(> 15%)
Tree caver, flooded, fresh or brakish water
Tree caver, flooded, saline water
Tree caver, mixed leaf type (broadleaved and needleleaved)
Tree caver, needleleaved, deciduous, closed (>40%)
Tree caver, needleleaved, deciduous, closed to open (>15%)
Tree caver, needleleaved, deciduous, open (15-40%)
Tree caver, needleleaved, evergreen, closed (>40%)
Tree caver, needleleaved, evergreen, closed to open (> 15%)
Tree caver, needleleaved, evergreen, open (15-40%)
Tree or shrub caver)
%Croplands = Sum of (
Cropland, irrigated or post-flooding
Cropland, rainfed
Mosaic cropland (>50%) 1 natural vegetation (tree, shrub, herbaceous caver) (<50%))
%Wetlands = Sum of (
Tree caver, flooded, fresh or brakish water
Tree caver, flooded, saline water
Shrub or herbaceous caver, flooded, fresh/saline/brakish water)
%Shrublands= Sum of (
Mosaic herbaceous cover (>50%) / tree and shrub (<50%)" ),
Mosaic natural vegetation (tree, shrub, herbaceous caver) (>50%)/
Mosaic tree and shrub (>50%)/ herbaceous caver (<50%)
Shrub or herbaceous caver, flooded, fresh/saline/brakish water"
Shrubland,
Shrubland deciduous,
Shrubland evergreen,
Sparse herbaceous caver (<15%)
Sparse shrub (<15%)
Sparse vegetation (tree, shrub, herbaceous caver) (<15%)
% Water bodies = Water bodies
cropland (<50%)
1 3 7
Sl-3. Additional Water Residence Ti me (AWRTl from large freshwater reservoirs
We developed the metric AWRT to act as a proxy for the a mount of additional ti me water stays
within a catch ment because of the added volumes contained in large freshwater reservoirs. This
was accomplished by summing the reservoir water volume capacities of ali reservoirs within
each catchment and dividing by the average annual runoff over the catchment. We used the
geolocated GRanD (G lobal Reservoir and Dam) database available at
http :/ /www.gwsp.org/products/grand-database.html .
Sl-4. Average DOC export= (Runoff. SOC)
The generalized DOC export from a catchment can derived by solving the multivariate models
presented in Table 1 of the main text as a function of only Runoff and SOC and replacing the
other variables with their mean values in our data set. The resulting equation as illustrated as a
family of curves representing the relationship between DOC export and Soil Organic Carbon for
different runoff values. For SOC>10 kg m·2 , the relationships are approximately linear (Fig. Sl-4.1)
suggesting that DOC yield can be roughly considered as a first-order reaction with the SOC
reservoir.
Figure S4.1 . Relationship between DOC export and Soil Organic Carbon (kg C m·2) for different
levels of annual runoff (mm yr·1 )
~----------------------------------
l 3 8
20
u tl.O
t10 0 0.. >< (1)
u 8 5
0
0 10 20 30 Sail organic carbon (kg C m-2)
Runoff
-1 200 mm yr _
40 50
l 3 9
SI -S. Complete Data set used in this study.
Ri vers A la Baleine Abitibi Abra Adige Adour A~o
A 1211 0 Agu san Aht ava Akheloos Alafia Alazeya Albany Aliakmon Alsea Alsek Altamaha Amazon Ameca Amgerman Amguema A mur Ana bar Anadry Anderson AndroscollS!in Ankobra A palachicola Appomattox Approuague Argens A maud A mo Ashbun on
Reference Rosa et al. , 20 12; Hudon et al. , 1996 Sheehan. 1989; SENES, 20 13 Du lay, 2005 ; EM B-CA R, 20 13 UNEP, 2003 Gueguen et al .. 2002: Point et al .. 2007: Bosser et al. , 20 12 San Diego-M cG ione et al. , 1998 Breward , 1996 Kulinski and Pempkow iak, 20 Il UNEP, 2003; Skoulikidis et al. , 1998 Stets & Striegl , 20 12 Dolman et al. , 20 12; Gordeev et al. , 1996 Mey beek and Ragu, 1996 Skoulikidis et al. . 1998; UNEP, 2003 Stets & St riegl , 20 12 Ministrv of Env.ironmen of BC. 1996: Eckerl ct Stets & St riegl, 20 12 Richcy et al. , 1990; Arauio et al. , 20 14 Mev beek and Ragu, 1996 Kulinski and Pempkowiak. 20 Il Gordeev et al. , 1996 Moon et al. , 2009 Gordeev et al. . 1996 Mey beek and Ragu, 1996 Mev beek and Ragu, 1996 Stets & Striegl, 20 12 Yi dana et al. , 2008 Stets & Striegl, 20 12 Stets & Striegl, 20 12 M cv beek &nd Ragu, 1996 UNEP. 2003 H udon et al. . 1996 UNEP, 2003 URS. 20 14
Atran Kulinski and Pemp kowiak, 20 Il Atrato Res trepo & Kierfve, 2004 Attawapiskat OCWA. 200 1; Des pault & Branfireun, 20 14 Aucilla Stets & Striegl~ 20 12 Aude UNEP, 2003 A uraioki Raike et al., 20 12 Aux Feuilles Hudon et al. , 1996 Aux Outardes 1-1 udon et al. , 1996; Clair et al. , 20 13 Aux Rochers l-Iu don et al. , 1996 Axios UNEP. 2003 : skoulikidis et al.. 1998: Babage Mev beek and Ragu, 1996 Back Chou inard and M ilbum. 1995 Baker Mey beek and Ragu, 1996 Ban Pakong Mey beek and Ragu, 1996 Bandama Mey beek and Ragu, 1996 Barito Mey beek and Ragu, 1996 Barumun Mev beek 1md Ragu, 1996 Berbice Mey beek and Ragu, 1996 Betsiamites Clair et al. , 20 13 Betsiboka Ralison et al. , 2008; M arwick et al. .20 14 Biobio VarMS et al. , 20 13 Blackstone Nixon et al. , 1995; Stets & Striegl, 20 12 Botoross trôml Kulinski and Pemo kowiak, 20 Il
Rivers Reference Bralunani Mey beek and Ragu, 1996 Bralunaputra Mey beek and Ragu, 1996 Brant as Aldrian et al. . 2008 Brazos (Tex) Stets & St riegl , 20 12 Breede N. VAN BINSBERGEN, 20 11 Broadback M undv et al ... 201 0: Rosa et al.. 2012: Clair ct al .. Buffalo BayouStets & Striegl , 201 2 Buller Carey et al. , 2005 Burdekin Mey beek and Ragu, 1996 Bumside Chouinard and M ilbum, 1995 Buvuk Mende Meybeck and Ragu, 1996 Bzy b Meybeck and Ragu, 1996 Cagayan Mey beek and Ragu, 1996 Cape Fear Avery .Ir. et al. , 2003; Stets & Striegl, 20 12 Cauweri Sarma et al. , 20 12 Cavall y Mey beek and Ragu, 1996 Cedar Stets & StrieJl) , 20 12 Cey han (Sey h1Meybeck and Ragu, 1996 ChanJl)lll a Chen&Chen, 1992 Changjiang Cai et al. , 2008; Wang et a1. ,20 12 Chao Phrya Mey beek and Ragu, 1996 Charles Stets & Striegl , 20 12
hehalis Stets & Striegl , 20 12 Chickahominy Stets & Striegl , 20 12 Chico Brunet et al. , 2005 Chikugo Liu et al. , 20 10 Cho Shui Chi Pan, 20 12 Choctawatche< Stets & Striegl, 20 12 Chubut Brunet et al. , 2005 Churchill (A ti)Ciair et al. , 1994,20 13 Churchill (HucG ransko et al. , 2007 Cimanuk Mey beek and Ragu, 1996 Citanduy Mey beek and Ragu, 1996 Cit arum Mey beek and Ragu, 1996 Clarence Mev beek and Ragu, 1996 Clutha Mey beek and Ragu, 1996 Colorado (A q~ Brunet et al. , 2005 Colorado (A ri)Stets & Striegl , 20 12 Colorado (Tex Stets & St riegl, 20 12 Columbia Stets & Stricgl , 20 12 Col ville Gordeev et al. . 1996 Comoe Mey beek and Ragu, 1996 Connecticut Stets & Striegl , 20 12; Hoss ler et al., 20 13 Coosawhatch i< Stets & St riegl , 20 12 Copper Mey beek and Ragu, 1996 Coppennine Rollo, 2003; Chou inard and M ilbum, 1995 Comeille H udon et al. . 1996 Cross Edet et al. , 20 13 Cu nene Mey beek and Ragu, 1996 Cuy uni Tos iani et al. , 2004 Dalalven Mev beek and Ragu, 1996 Daling Xia&Z hang,20 11 Dai y Robson et al. , 20 1 0 Damodar (L-I oc Mey beek and Ragu, 1996 Danu be Mey beek and Ragu, 1996 Daugava Kulinski and Pempkowiak, 20 11 Dee l-I one et al.. 1997: Dawson ct al. . 2009
1 4 0
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}carey et al., 2005 Meybeck and RagY., 1996 Lee et al., 2001 Kim et al., 2007 Mey beek and Ragu, 1996 Rosa et al. , 20 12; Clair et al., 20 13 Bay ram el al., 20 1 1 Chou inard and M ilburn . 1995; Gransko et al. , 2007; Ku linski and Pempkowia~ 20 Il Mey beek and Ragu, 1996 UNEP_, 2003 Along[ et aL, 1 99~ Stets & StriegiJ 20 12 Stets & Striegl, 20 12 Meybeck ru1d Ragu, 1996 Stets & Striegl, 20 12 Pan~ 20 12 Wu et al., 201 1 Pan_,_ 20 12 Gu el ai.J 2009· Ran et al. , 20 1 3~ Wanget at., 20 12 Hoss ler& Bauer, 20 13 Xia & Zhru1 g, 20 11 Hit chcock et al., 20 10
J Kulinski and Pempkowiak, 20 11 Kulinski and Pempkowials, 20 11
i Gordeev et al. , 1996; Lobbes et aL ,. 2000; Dittmar & Mey beek and Ragu, 1996 Mey beek ru1d Ragu, 1996 K ?avi?? et al., 20 1 1 Bird et al., 2008 Jha & M asao, 20 13; A lrun et al. , 2007; Alrun et al., lwata et al. , 20 13 Meybeck ru1d Ragu 1996 Stets & Striegl, 20 12 Cai et al.1 998; Qju and Ye, 20 13 Meybeck ru1d Ragu, 1996 Meybeck and Ragu, 1996 Rllike et al ., 20 12; Ku linsk i and Pempkowiak, 20 11 Pokrovsky & Scholl, 2002 Humborget al. , 2004 ; Kulinski ru1 d Pempkowiak, Pokrovsky & Scholl, 2002 Pan, 20 12 Ansharj et a l ~ 20 10
_ Raike et al .,_l9 12 F ooladv2f!d el &,.10 1 L Chou inard a_nçl M ilburl}, 1995 Mey beek ru1d Ragu, 1996 Pokrovsky & Scholl , 2002 Kulinski and Pempkow iak, 20 11 ; Riiike et al. , 20 12 Cronan, 20 12; Stets & St riegl, 20 12 Pokrovsky & Schott, 2002 Gordeev et al., 1996 Kulinski and PempkowiakJ 20 11~ Rllike et al, 20 12 Meybeck ru1d Ragu, 1996 Harun, 2013 Kulinski and Pempkowialç,20 Il · Raike et &., 20 12 Sugimoto et al. , 2006; Liu et al., 2010
Kit akami Büsser et al_. 20 12 Kizill rmark Mey beek and Ragu, 1996 Klamath Stets & Striegl , 20 12 Kobuk Mey beek and Ragu, 1996 Kodori Mey beek and Ragu, 19.96 Kokemaenjoki Kulinsk.i and l?emokowiak. 201 L: Riiike et aL Ko.ksoak Rosa et al. , 20 12: Clair et al. , 20 13 Kola Pekka et al. , 2008 Kolyma Lobbes et aL. 2000: Gordeev et aL 1996: Konkoure Mey beek and Ragu, 1996 Krishna Sam1a et al. , 20 12 Kuban Mey beek and Ragu, 1996 K uiva joki Kulinski and Pemp .kowiak, 20 1 1 Kushiro Alam et al. , 20 12 Kuskokwim Mey beek and Ragu, 1996 Kuzema Pokrovsky & Schott , 2002 Ky m(ioki "Kulinski and PenJDkowiak, 20 Il Ky roQioki Raike et al. , 20 12 La Grande Schneider-Vieira et aL 1994: Rosa et al .. 20U: Lal!an Kulinski and Pempkowiak, 20 Il Lahave Clair et al. , 1994 Lanyang Kao&Liu, 1996, 1997; Pan, 20 12 Lapuan joki Raike et al. , 20 12 Lapvaiirtin joki Kulinsk.i and Pemokowiak. 201 L: Raike et aL Lavaca Stets & Striegl, 20 12 Leba Niemirvcz et al. , 2006 Leichhardl No lier et al. , 20 12 Lena Gordeev et al .. 1996: Di umar & Kattner. 2003: Les t ijoki Kuliuski and I?emokowiak. 20 I l: Raike et aL Letniya North Pokrovsky & Schott . 2002 Liao Xia & Zhang, 20 11 : Yu et al. , 20 15 Lielup e K ?avi?? et al ., 20 Il Liioki Raike et al. . 20 12 Limp opo Oberholster et al, 20 10 Liungan Ku lins ki and Pempkowiak, 20 Il Liungbyan Kulinski and Pempkowiak. 20 Il Loire Niemi rycz et al. , 2006 Lori li ard Chouinard and M ilbum, 1995 Los Angeles Stets & Striegl, 20 12 Loukkos EL M orhit et al. , 20 13 Louro_s Ovez ikoglou et al. , 2003 Luan xia & Zhang, 20 1 1 Lul!a Mey beek and Ragu, 1996 Lulealven l:iwnbomeLal .. 2004: Kulinski and Lupawa Niemirycz et al. , 2006 Lyckebyan Kulinski and Pe1npkowiak, 20 Il Macdonald il-ludon et al. , 1996 Mackenz ie Clair et al. , 20 13 Mad Stets & Striegl , 20 12 Magdalena Lewis et al. , 1995: J ujnovsky et al., 20 10 Magp ie Hudon et al. , 1996 MahakanJ Mey beek and Ragu, 1996 Mahanadi Maip o M anavj!iil Manicouaj!iln Maroni Matamek
Pan ieralw an.d RavJnahashav. 2005: SarJna et Mey beek and Ragu, 19_96 Mey beek and Ragu, 1996 H udon et al. , 1996: Clair et al. , 20 13 Sondage! al. ,20 10 1-1 udon et al.. 1996
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Mey beek and Ragu, 1996 Mey beek and Ragu, 1996 Clair et al. , 1994 Noh et al. ,20 13 Zhu et al. , 20 12: Yang et al. , 2008 Kulinski and Pempkowiak, 20 11 Stets & Striegl , 20 12 Mev beek and Ragu, 1996
1 4 1
Servais et al. , 1989: Cleven et al. , 2005 Gordeev et al. . 1996: Lobbes et al ... 2000: Dittmar & Mey beck and Ragu, 1996 Stet s & Striegl , 20 12 Mey beek and Ragu, 1996 Stets & Striegl , 20 12 Büsser et al. , 20 12 Hudon et al .. 1996: Naiman and Luli<. 1997: Clair et Sheehan, 1989 Kulinski and Pempkowiak. 20 I l Mey beek and Ragu, 1996 Kulinski and Pemp kowiak, 20 Il lavazzo et al. , 20 12 Cartwriglll , 20 10 K !av ins, 20 13 Mey beck and Ragu, 1996 I-1 udon et al. . 1996 Stets & Striegl , 20 12 Gordeev et al. , 1996: Dittmar & Kattner. 2003 Dolman et al. , 201 2 Sanna et al. , 20 12 Chen&Chen, 1992 Stets & Striegl , 20 12 Shanna&Subramanian, 2008: Sam1a et al. , 20 12 Raike et al., 20 12 Stets & Striegl , 20 12 Kul inski and Pempkowiak, 20 11 Gransgok et al., 2007 Hudon et al. , 1996: Clair el al_, 20 13 Stets & Striegl , 20 12 Stets & Striegl , 20 12 Brunet et al. , 2005 Stets & Striegl , 20 12 Schneider-Vieira et al .. 1994: Rosa et aL 2012: Clair Kulinski and Pempkowiak, 20 11 : Tockner et al. , 2009 Skoulikidis et al. , 1998: Skoulikid is, 1989 Tript et al. , 20 13; Sarmaet al. , 20 12 Davis et aL L978:H ooe et al .. 1994:Bales et al. . Kulinski <md Pempkow iak, 20 1 1 Maya et al. . 20 13 Esser&Kollirnaier. 199 1: Harrison et al .. 2005: A rau io Mey beek and Ragu, 1996 Ku linski and Pempkowiak, 20 I l M und y et al. , 20 1 0: Clair et al._, 20 13 Stets & Striegl , 20 12 Ku linski and Pempkowiak, 20 11 Brunet et al. , 2009 Gordeev et al., 1996: Dittmar & Kattner, 2003 Stels & Striegl, 20 12 Sieoak. 1999
1 4 2
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Stets ljL Striegl, 20 12 Mey beek and Ragu, 1996 Gordeev et al. . 1996; Lobbes et al. ,. 2000; Mey beek and Ra gu, 1996 H udon et al.o 1996 Gordeev et al. 1996; Lobbes et al. ,. 2000 Gordeev et al., 1996 Beusen et al. . 2005 ; Harrison et al. , 2005 ; UNEPO 2003 Ku linski and Pempkow@ls, 20 Il Lewis and Saunders, 1989..; Paolini, J 925; Mey beek and Ragu 1996 Kulit1s.ki and Pempkowiak,20 J L Raike et al. . Sondag et al., 20 1 0 Raike et al., 20 12 Prabhahar et al., 20 12 Hoss ler& Bauer, 20 13 Mey beek and Ra gu, 1996 Jennerjahn et al., 20 1 Q; Araujo et al., 20 14 Depetris & Kempe, 1993 Mey beek and Ra!?J.t, 1996 Niemirycz et al.~ 2006 Stets & Striegl, 20 12 Stets & Striegl, 20 12 Stets & Striegl, 20 12 Nixon et al. , 1995 Stets & S!riegl~ 2012 Duan et a l~ 2007,2006· Stets & Striegl, 20 12 Gordeev et al., 1996; Di_umar & Kattner, 2003 Stets & Striegl, 20 12 Water Resources Division of Canada, 2002 Pan, 20 12 Sanna et aL 20 12 Cronano 20 12; Stets & Striegl, 20 12 Mey beek and Ragu, 1996 Stets & Striegl 20 12 KJt.linski and Pemo..kowiak, 20 J L; Raike et al. , Mey beek and Ra gu, 199§._ _ Hudon el al., 1996; Gransko et al" 200L
J -l udon et al.., !996 Skoulikidis et aL 1998 l:lumborget al. , 2004; K. ulinski and Tockner et al. 2009· Pett ine et al., 1998; Pokrovslsy & Schoq,, 2QQ2 ~rlllitlêt al. 20 12 Rosa et al. 20 12 Kulins.ki.an.d Pempkowjak, 20 Il ; Rllike et al. , Stets & Striegl, 20 12 ; Hossler& Bauer 20 13 Gransko et al, 2007 Meybeck and Raf?l,t, 1996 Meybeck and Ra!?J.J., 199.9 Gordeev et al. 1996 M eybeck and Ragu__,_ 1996 Stets & St riegl, 20 12 Dolman et al., 20 12 K ulinski and Pempkowiak. 20 Il ; Raike et al. , Stets & Striegl, 2012 Stets & Striegl 20 12 Chou inard and M ilbum, 1995
Rambla Del Garcia-P intado et al ., 2007 Ranealven J Humborget al., 2Q04 Rangitikei Carey et al. , 2005 Rappal1annoc Stel~ & Striegl, 2Q 12 Raritan Stets & Striegl, 20 12 Reda Niemirycz et al ., 2006 Re!?f! Niemi rycz et al. , 2006 Rh ine Niemiry cz et al. , 2006 RJ10ne Semp éré et al. , 2000 Rianila Abri! et al., 20 15; Marwick et al" 20 14 RickJean , Kulinski and Pempkowiak, 20 11 Rio Grande Stets & St riegl, 20 12 Rioni !Mey_J?eck and Ra!?J.J, 1996 Roanoke Stets & Striegl, 20 12 ; 1-l ossler& Bauer, 20 13 Ro!?J.te Stets & Striegl, 20 12 Romaine 1-1 udon et al., 1996; Clair et al., 20 13 Ronnea Ku linski and Pempkowiak
0 20 11
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Pokrovsky & Schott , 2002 Baum et al. , 2007 K ulillski and Pemo kowiak. 20 Il : Raike et al .. K u lins ki and Pemokowiak. 20 Il : Raike et al .. Kulinski and Pempkowiak, 20 Il Stets & Striegl, 20 12 Stets & Striegl, 20 12 Clair et al. , 20 13 1-lumborget al .. 2004:Kulinski and Mey beek and Ragu, 1996 Stets & Striegl, 20 12 Niemirvcz et al. . 2006 Stet & St rieg), 20 12 Stets & Strieg) , 20 12 Li et al.. 1995 Skoulikidis et al., 1998: Kom1as 2003&2004 Clair et al. , 1994 Stets & St riegl, 20 12
tets & St riegl, 20 12 Stets & Strieg), 20 12 Clair et al. , 20 13 Skoulikidis et al. , 1998: UNEP, 2003 Mey beek and Ragu, 1996 Sam1a et al. , 20 12 Mey beek and Ragu, 1996 Mey beek and Ragu, 1996 Stets & Striegl, 20 12; Hoss ler and Bauer, 20 13 Petrone, 20 1 0 T ri p t et al. , 20 13 Pan ,20 12 Ncal, 2007 Pan , 20 12 Bouillon et al. , 2007 Sham1a&Subramanian , 2008; Sann a et al. , 20 12 Davis el al.. 1978: Baies el al.. 2000: Lin et al .. Nixon et al. , 1995 UNEP. 2003 Dolman et al.. 20 12 Cochran et al .. 1996: Gordeev et al. . 1996 Meybeckand Ragu, 1996 Bosser et al. . 20 12 Naganuma&Seki, 1987: Alan1 et al. . 20 12 UNEP. 2003 Mey beek and Ragu, 1996 Arauio et al. , 20 14; Neal et al., 1998 Chouinard and M ilbum, 1995 Mey beek and Ragu, 1996 Lewi and Saunders, 1982. Alam et al. , 20 12; Büsser et al. , 20 12 Büsser et al. , 20 12 1-ludon et al. , 1996 Kulinski and Pempkowiak, 20 Il Tipp inget al. , 1997 1-ludon et al. , 1996 Warnken & Santschi 2004 : Stels & Strieg]_ Pan,2012 Dolman et al. . 20 12
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References (for database)
Abril, G., Bouillon, S. , Darchambeau, F., Teodoru, C. R. , Marwick, T. R. , Tamooh, F. ,
and Borges, A. V. (2015). Technical Note: Large overestimation of pC02
calculated from pH and a lkalinity in acidic, organic-rich freshwaters.
Biogeosciences, 12:67- 78, doi:l0.5194/bgd-11-11701-2014.
Abril , G. , Etcheber, H., Borges, A. V. , and Frankignoulle, M. (2000). Excess
atmospheric carbon dioxide transported by rivers into the Scheldt estuary. Earth
and Planetary Sciences, 330:761 - 768.
Alam, M. J. , Nagao , S., Aramaki , T. , Shibata, Y. , and Yoneda, M. (2007). Transpott of
particulate organic matter in the lshikari River, Japan during spring and summer.
Nuclear Instruments and Methods in Physics Research B, 259:513f-517,
doi: 10.10 16/j.nimb.2007.01 .194.
Alam, M. J., Nagao, S. , and Quayum, M. E. (2012) . Transport behavior of particulate
organic matter in river water during snow melting in the Ishikari , Tokachi,
Teshio and Kushiro rivers, Japan. Journal of Asiatic Society of Bangladesh,
Science, 38(2) : 163- 173.
Aldrian, E., Chen, T. A., Adi, S. , Prihartanto, Sudiana, N. , and Nugroho, S. P. (2008).
Spatial and seasonal dynamics of riverine carbon fluxes of the Brantas
catchment in East Java. Journal of Geophysical Research: Biogeosciences,
113:1 - 13, doi:1q.1029/2007JG000626.
Alin, S. R. , Aalto, R. , Goni , M. A. , Richey, J. E., and Dietrich, W. E. (2008).
Biogeochemical characterization of carbon sources in the Strickland and Fly
rivers, Papua New Guinea. Journal of Geophysical Research: Earth Surface,
11 3: 1- 21 , doi: 10.1 029/2006JF000625.
Alkhatib, M. , Jennerjahn , T. C. , and Samiaji , J. (2007). Biogeochemistry of the
Dumai River estuary, Sumatra, Indonesia, a tropical black-water river.
Limnology and Oceanography, 52(6):241 0- 24 17,
doi: 1 0.4319/lo .2007.52.6.241 O.
A longi, O. M. , Ayukai , T. , Brunskill , G. J. , Clough, B. F. , and Wolanski, E. (1998).
Sources, sinks, and export of organic carbon through a tropical, semi-enclosed
delta (Hinchinbrook Channe l, Australia) . Mangroves and Salt Marshes,
2 :237- 242.
1 6 2
Anshari , G., Gusrizal, Setyawati, R. , and Novrita, W. (201 0). Dissolved Organic
Carbon (DOC) Transport from the Kapuas River to South China Sea.
Association for Tropical Biology and Conservation (ATBC) 2010 Meeting. Page
187.
Araujo, M ., Noriega, C., and Lefevre, N. (2014). Nutrients and carbon fluxes in the
estuaries of major rivers flowing into the tropical Atlantic. Frontiers in Marine Science, l(May), 1- 16. doi:10.3389/frnars.2014.00010.
Aselmann, 1., and Crutzen, P. J. (1989). Global distribution of natural freshwater
wetlands and rice paddies, their net primary productivity, seasonality and
possible methane emissions. Journal of Atmospheric Chemistry, 8:307- 358.
doi: 10.1 007/BF00052709.
Baburaj, B. , D. Padma lai , S.I. Remya, K. Maya and Lekshmi, 1. (20 12). "DIN, DIP,
DIC and S04 Fluxes fi'om the Neyyar River (Kerala) into the Receiving Coastal
Waters." Bonfring 1 nternational Journal of Industrial Engineering and
Management Science, 2: 1-7.
Baker, A. , and Spencer, R. G . M. (2004). Characterization of dissolved organic matter
from source to sea using fluorescence and absorbance spectroscopy. Science of
the Total Environment, 333:217- 232. doi: 10.10 16/j.scitotenv.2004.04.013 .
Balakrishna, K. , & Probst, J. L. (2005). Organic Carbon Transport and C/N Ratio
Variations in a Large Tropical River: Godavari as a Case Study, India.
Biogeochemistry, 73(3), 457-473 .
Baies, Jerad D. , Carolyn J. Oblinger, and Asbury H. Sal lenger, Jr. 2000. Two Months
of Flooding in Eastern North Carolina, September October 1999: Hydrologie
Water Quality, and Geologie Effects of Hurricanes Dennis, Floyd, and Irene.
Water Resources Investigations Report 004093 (USGS), North Carolina. Pp 13.
Baum, A. , Rixen, T. , & Samiaji , J. (2007). Relevance of peat draining rivers in central
Sumatra for the riverine input of dissolved organic carbon into the ocean.
Estuarine, Coastal and Shelf cience, 73 , 563- 570.
doi: 10.10 16/j.ecss.2007.02.012
Bayram, A., Onsoy, H., Akinci , G. , & Bulut, V. N. (2011). Variation of total organic
carbon content along the stream Harsit, Eastern Black Sea Basin, Turkey.
Environmental Monitoring and Assessment, 182, 85- 95.
doi: 10. 1007 /s 10661-010-1860-2
1 6 3
Beusen, A. H . W., Dekkers, A. L. M., Bouwman, A. F., Ludwig, W., & Harrison, J. A.
(2005). Estimation of global river transport of sediments and associated
particulate C, N, and P. Global Biogeochemical Cycles, 19(4), n/a- n/a.
doi : 1 0.1 029/2005GB002453
Bird, M. 1. , Robinso n, R. A. J. , Oo, N. W., Aye, M. M. , Lu , X. X. , Higgitt, D. L. , ...
Hoey, T. B. (2008). A preliminary estimate of organic carbon transport by the
Ayeyarwady (Irrawaddy) and Thanlwin (Salween) Rivers of Myanmar.
Quaternarylnternational, 186, 113- 122. doi :10.1016/j.quaint.2007.08 .003
Bizsel, K. C., Suzal, A., Demirdag, A., inanan, B. E. , & Esen, E. (20 Il). Particulate
Organic Matter Contribution of Gediz River to the Aegean Sea. Turkish Journal
of Fisheries and Aquatic Sciences, Il , 377- 383. doi : 1 0.4194/ 1303-2712-v11
Bouillon, S. , Dehairs, F., Schiettecatte, L.-S. , & Borges, A. Y. (2007).
Biogeochemistry of the Tana estuary and delta (northern Kenya). Limnology and
Oceanography, 52(1 ), 46- 59. doi: 1 0.4319/ lo.2007.52.1.0046
Breward, N . 1996. Mercury and other heavy-metal contamination associated with
gold mining in the Agusan river catchment, Mindanao , the Philippines.
Technical Report of British Geological Survey: Overseas Geology series.
Brunet, F. , Gaiero, D. , Probst, J. L. , Depetris, P. J., Lafaye, F. G. , & Stille, P. (2005).
8 13C tracing of disso lved inorganic carbon sources in Patagonian rivers
(Argentina). Hydrological Processes, 19, 3321 - 3344. doi: 10.1 002/hyp .5973
Burns, K. A. , Brunskill , G. , Brinkman, D ., & Zagorskis, l. (2008). Organic carbon
and nutrient fluxes to the coastal zone from the Sepik River outflow. Continental
Shelf Research , 28, 283- 301. doi: 10.10 16/j.csr.2007.08.004
Büsser, Sybille , Rolf Frischknecht, Jun Kono and Kiyotada Hayashi. 2012.
ESU-services Report: Ecological Scarcity Japan. Pp33-37 .
Cai, Agen, Li , W., Chen, Q. and Wang, X. 1998. Studies of Particulate Organic
Carbon in the Xiamen western harbor and the Jiulong River Estuary.
Cai, W. , Guo, X. , Chen, C., Dai, M., Zhang, L., Zhai, W. , . .. Wang, Y. (2008). A
comparative overview of weathering intensity and HC03- flux in the world's
major rivers with emphasis on the Changjiang, Huanghe, Zhujiang (Pearl) and
Miss iss ippi Rivers. Continental Shelf Research, 28, 1538- 1549.
doi: 10.1 0 \6/j.csr.2007.1 0.014
1 6 4
Cai, Yunlong. 2006. Study on Biological Stability of Drinking Water and Pollution
Index in Distribution System . PhD thesis , Tongji University.
Carey, A. E. , Gardner, C. B., Goldsmith, S. T. , Lyons, W. B., & Hicks, D. M. (2005).
Organic carbon yields from small , mountainous rivers, New Zealand .
Geophysical Research Letters, 32, Ll5404. doi: 10.1 029/2005GL023159
Cartwright, 1. (20 1 0). The origins and behaviour of carbon in a major semi-arid river,
the Murray River, Australia, as constrained by carbon isotopes and
hydrochemistry. Applied Geochemistry, 25(11), 1734- 1745.
doi: 10. 10 16/j .apgeochem.20 10.08.020
Celeste A. Journey, Douglas A. Burns, Karen Riva-Murray, MarkE. Brigham, Daniel
T. Button, Toby D. Feaster, Matthew D. Petkewich , and P. M. B. (2012). Fluvial
Transport of Mercury , Dissolved Organic Carbon , Suspended Sediment , and
Selected Major Ions in Contrasting Stream Basins in South Carolina and New
York , October 2004 to September 2009 Scientific f nvestigations Report 2012 -
5173 (pp. 1- 140).
Chen, Jingsheng and Chen, Mei. 1992. Chemical characteristics and genesis of major
ions ofthe rivers in Hainan island. Tropical Geography, 12(3): 272-281.
Chouinard, J., & Milburn, D. (1995). Arctic Environmental Strategy: summary of
recent aquatic ecosystem studies. Northern water resources studies (pp . 69-186).
Clair, T. A. , Pollock, T. L. , & Ehrman, J. M. ( 1994). Exports of carbon and nitrogen
from river basins in Canada 's Atlantic Provinces. Global Biogeochemical Cycles , 8(4), 441-450. doi : 10.1 029/94GB02311
Clair, T. A. , Dennis, l. F., & Bélanger, S. (2013). Riverine nitrogen and carbon
expot1s from the Canadian landmass to estuaries. Biogeochemistry, 115(1-3), 195- 211. doi: 10.1 007/s 10533-013-9828-2
Cleven, R. , Nur, Y. , Krystek, P., & van den Berg, G. (2005). Monitoring Metal
Speciation in The rivers Meuse and Rhine Using DGT. Water, Air & Soil
Pollution, 165, 249- 263.
Cochran, J. Kirk, N. S. Fisher, and S.B. Moran (1996). Transport and fate of
radionuclides in the Ob River estuarine system. FINAL REPORT of ONR Grant
# N000149410: 1-29.
1 6 5
Cronan, C. S. (2012). Biogeochemistry of the Penobscot River watershed, Maine,
USA: nu trient export patterns for carbon, nitrogen, and phosphorus.
Environmental Monitoring and Assessment, 184(7), 4279-88.
doi: 10. 1 007/sl 0661-011-2263-8
Davis, Graham J. , Mark M. Brinson and William A. Burke. 1978 . Organic carbon and
Deoxygenation in the Pamlico River Estuary. Report UNC- WRRI-78-131 ,
Project No. A-088-NC, Water Resources Research lnstitute of the University
ofNorth Carolina.
Dawson, J. J. C. , Soulsby, C., Hrachowitz, M. , Speed , M. , & Tetzlaff, D. (2009).
Seasonality of epC02 at different scales along an integrated river continuum
within the Dee Basin , NE Scotland. Hydrological Processes, 23 , 2929- 2942.
doi: 10.1 002/hyp
Depetris, P. J . & Kempe, S. (1993). Carbon Dynamics and Sources m the Parana
River. Limnology and Oceanography, 38(2), 382-395 .
Despault, T. & Branfireun, B. 2014. Fluorescence fingerprinting of dissolved organic
matter in the Attawapiskat River Watershed - Towards the development of in situ
proxies for mercury in northern waters. Elements, 32(2), 23-26.
Dhillon, G. S. (2012). Comp~rison of Particulate and Dissolved Organic Carbon
Exports From Forested Piedmont Catchments. Master 's Thesis , University of
Delaware.
Dittmar, T. , & Kattner, G. (2003). The biogeochemistry of the river and shelf
ecosystem of the Arctic Ocean: a review. Marine Chemistry, 83(3-4), 103- 120.
doi : 1 O. 1 0 16/S0304-4203(03)00 105-1
Dolman, A. J ., Shvidenko, A. , Schepaschenko, D., Ciais, P. , Tchebakova, N. , Chen,
T., ... Schulze, E.-D. (2012). An estimate of the terrestrial carbon budget of
Russia using inventory-based , eddy covariance and inversion methods.
Biogeosciences, 9(12), 5323- 5340. doi: 1 0.5194/bg-9-5323-2012
Duan, S., & Bianchi, T. S. (2006). Seasonal Changes in the Abundance and
Composition of Plant Pigments in Particulate Organic Carbon in the Lower
Mississ ippi and Pearl Rivers. Estuaries and Coasts, 29(3), 427-442.
Duan, S. , Bianchi, T. S. , & Sampere, T. P. (2007). Temporal variability m the
composition and abundance of terrestrially-derived dissolved organic matter in
1 6 6
the lower Miss iss ippi and Pearl Rivers. Marine Chemistry, 103, 172 - 184.
do i: 10.1 016/j .marchem.2006.07.003
Dulay, Josephine Aries L. 2005 . The Abra River System Water Quality Monitoring.
Natio nal Cordille ra Studies Co nfe rence (U niversity of the Philippines - Baguio,
2005) and the AEESEAP Conference (Kuala Lumpur, Malays ia, 2005) . Pp 1-1 O.
Duran, M., & Çmez, M. S. U. (2007). Utilization of both benthic macro invertebrates
and phys icochemica l parameters fo r evalu ating water quality of the Stream
Çekerek (Tokat, N Turkey). Journal of Environmenta l Bio logy, 28(2), 23 1-236.
Eckert, Ginny, E ran Hood, Sonia Nagorski , and Carrie Talus. 2006. Assessment of
Coastal Water Resources and Watershed Condit ions at Glac ier Bay Nationa l
Park and Preserve, A laska.Techn ica l Report NP S/NRWRD/NRTR-2006/353.
Edet, A., Ukpong, A., & Nganje, T. (20 13). Hydrochemical studies of Cross River
Bas in (southeastern Nigeria) river systems using cross plots, statistics and water
quality index. Environmental Earth Sciences, 70, 3043- 3056.
doi: 1 O. 1 007/s 12665-01 3-2365-4
Elli s, E. E ., Keil , R. G ., lnga lls, A. E. , Richey, J. E., & Alin , S. R. (201 2). Seasonal
va riability in the so urces of particulate organic matter of the Mekong River as
discerned by e lementa l and lignin analyses . Journa l of Geo phys ical Research:
Biogeosciences, 117(January) , 1- 15. do i: 10.1 029/20 11JG00181 6
El Morhit, M ., Fekhao ui, M., Serghini , A., E l Blidi, S., El Abidi, A. , & Yahyao ui , A.
(201 3). Typo logy of Water Quality in the Lo ukkos River Estuary (Morocco).
Larhyss Journal, 12, 7- 24.
Esser, G ., Kohlm a ier, G .H., 199 1. Mode lling terrestria l so urces of nitrogen,
phosphorus, sulphur and organic carbon to rivers. In : Degens, E.T. , Kempe, S.,
Richey, J.E. (Eds.), Biogeochemistry of Majo r World Rivers. John Wiley & sons
Ltd, Chichester, pp. 169- 2 11 .
Ferguson, P. R. , Dubo is, K. D., & Veizer, J. (20 11 ) . Fluvia l carbon flu xes under
extreme rainfa ll co nditions : Infe rences fro m the Fly River, Papua New Guinea.
Chemical Geo logy, 281 , 283- 292. do i: 1 0.10 16/j .chemgeo.20 10 .12.01 5
Foo ladvand, M., Ramavandi , B., Zandi , K., & Ardestani, M. (20 11 ). Investigation of
trihalomethanes fo rmation potentia l in Karoon River water, Iran. Env ironmental
Mo nitoring and Assessment, 178, 63- 7 1. doi: 10. 1 007/s 1 066 1-0 10- 1672-4
1 6 7
Ford, P. , T illman, P. , Ro bson, B. , & Webster, l. T. (2005). Organic carbon deliveries
and their flow related dynamics in the Fitzroy estuary. Marine Pollution Bulletin,
51, 119- 127. doi: 10.10 16/j.marpolbul.2004.1 0.019
Freese, H . M. , Gors, S., Karsten, U., & Schumann, R. (2007). Dissolved inorganic
nutrients and organic substrates in the River Warnow (North-Eastern
Germany) - Utilisation by bacterioplankton. Limnologica, 37(3), 264-277.
doi : 1 0.10 16/j.limno.2007 .03.001
Gallardo, B. , Garcia, M. , Cabezas, A., Gonzalez, E., Ciancarelli, C., Gonzalez, M. , &
Comin, F. A. (2007). F irst approach to understanding riparian wetlands in the
Middle Ebro River floodplain (NE, Spain): Structural characteristics and
functional dynamics. Limnetica, 26(2), 373-386.
Garcfa-Pintado, J. , Martfnez-Mena, M. , Barbera, G. G., Albaladejo, J., & Castillo, V.
M. (2007). Anthropogenic nutrient sources and loads from a Mediterranean
catchment into a coastal lagoon: Mar Menor, Spain. Science of the Total
Environment, 373, 220-239. doi : 10.1 016/j.sc itotenv.2006.1 0.046
Gomez, B. , Trustrum, N. a. , Hicks, D. M. , Rogers, K. M ., Page, M. J. , & Tate, K. R.
(2003). Production, storage, and output of particulate organic carbon: Waipaoa
River basin, New Zealand. Water Reso urces Research , 39(6) , n/a-nla.
doi:l0.1029/2 002WR001619
G6mez-Gutiérrez, A. 1. , Jover, E. , Bodineau, L., Albaigés, J. , & Bayona, J. M. (2006).
Organic contaminant loads into the Western Mediterranean Sea: estimate of Ebro
River inputs. Chemosphere, 65(2), 224- 36.
doi: 10.10 16/j.chemosphere.2006.02.058
Goni, M. A. , Monacci , N. , Gisewhite, R. , Ogston, A. , Crockett, J. , & Nittrouer, C.
(2006). Distribution and sources of particulate organic matter in the water
co lumn and sedim ents of the Fly River De lta, Gulf of Papua (Papua New
Guinea). Estuarine, Coastal and Shelf Science, 69, 225- 245.
doi: 10.1 0 16/j.ecss.2006.04 .0 12
Gordeev, V. Y., Ma1tin, J. M., Sidorov, I. S. , & Sidorova, M. V. (1996). A
reassessment of the Eurasian river input of water, sediment, major elements, and
nutrients to the Arctic Ocean. American Journal of Science, 296: 664-691.
Granskog, M. A., Macdonald , R. W., Mundy, C.-J., & Barber, D. G. (2007).
Distribution, characteristics and potential impacts of chromophoric disso lved
1 6 8
organic matter (CDOM) in Hudson Strait and Hudson Bay, Canada. Continental
Shelf Research, 2 7(15), 2032- 2050. doi: 10.10 16/j.csr.2007.05.00 1
Gu , D., Zhang, L. , & Jiang, L. (2009). The Effects of Estuarine Processes on the
F lu xes of Inorganic and Organic Carbon in the Yellow River Estuary. J Ocean Univ. China, 8( 4), 352- 358. doi: 10.1007 /sll802-009-0352-x
Guéguen, C. , Belin, C. , & Dominik, J. (2002). Organic colloid separation m
contrasting aquatic environments with tangential flow filtration. Water Research,
36, 1677- 1684. doi: 10.1 016/S0043-1354(01 )00374-8
Harrison, J. A. , Caraco, N., & Seitzinger, S. P. (2005) . Global patterns and sources of
dissolved organic matter export to the coastal zone: Results from a spatially
explic it, g lobal mode!. Global Biogeochemical Cyc les, 19(4), n/a- n!a.
doi: 10.1 029/2005GB002480
Harun, S. (2013). Water quality dynamics in a lowland tropical catchment: the
Kinabatangan River, Sabah, Malaysia. PhD Thesis. University ofBirmingham .
Hitchcock, J. N., Mitrovic, S. M., Kobayashi , T., & Westhorpe, D. P. (20 1 0).
Responses of Estuarine Bacterioplankton, Phytoplankton and Zooplankton to
Dissolved Organic Carbon (DOC) and Inorganic Nutrient Additions. Estuaries
and Coasts, 33,78- 91. doi :10.1007/s12237-009-9229-x
Hope, D. , Billett, M. F., & Cresser, M. S. (1997). Exports of organic carbon in two
river systems in NE Scotland. Journal ofHydrology, 193, 61 - 82.
Hassler, K. , & Bau er, J. E. (20 13). Amounts, isotopie character, and ages of organ ic
and inorganic carbon exported from rivers to ocean margins: 1. Estimates of
terrestrial lasses and inputs to the Middle Atlantic Bight. Global Biogeochemical
Cyc les, 27, 1- 16. doi:1 0.1 002/gbc.20033
Hudon, C. , Morin, R. , Bunch, J. , & Harland, R. ( 1996). Carbon and nutrient output
from the Great Whale River (H udson Bay) and a comparison with other rivers
around Quebec. Canadian Journal of Fisheries and Aquatic Sciences, 53, 1513- 1525.
Humborg, C ., Smedberg, E. , Blomqvist, S. , Mërth, C.-M. , Brink, J., Rahm, L.,
Sah lberg, J. (2004). Nutrient variations in boreal and subarct ic Swedish Rivers:
Landscape control of land-sea fluxes. Limnology and Oceanography, 49(5),
1871 - 1883. doi : 1 0.4319/ lo.2004.49.5 .1871
1 6 9
Hung, J.-J., Yeh, Y.-T. , & Huh, C. -A. (2012) . Efficient transport of terrestrial
particulate carbon in a tectonically-active marginal sea off southwestern Taiwan.
Marine Geology, 315-318, 29-43. doi:10.1016/j.margeo.2012.05.006
lavazzo , P. , Ducci, D. , Adamo, P. , Trifuoggi, M., Migliozzi, A., & Boni, M. (2011).
Impact of Past Mining Activity on the Quality of Water and Soil in the High
Moulouya Valley (Morocco). Water, Air, & Soi! Pollution, 223(2), 573- 589.
doi: 10.1007 /s 11270-011-0883-9
Tbanez, C. , Prat, N. , Duran, C. , Pardos, M. , Munne, A., Andreu , R. , ... Trobajo, R.
(2008). Changes in dissolved nutrients in the lower Ebro river: Causes and and
consuqences. Limnetica, 27(1 ), 131- 142.
lwata, T. , Suzuki, T. , Togashi, H., Koiwa, N ., Shibata, H., & Urabe, J. (2013). Fluvial
transport of carbon along the river-to-ocean continuum and its potential impacts
on a brackish water food web in the Iwaki River watershed , northern Japan.
Ecological Research, 28(5), 703- 716. doi: 10.1 007/sl1284-0 13-1047-8
Jennerjahn, Tim C. Bastiaan A . Knoppers, Weber F.L. de Souza, Carlos E.V.
Carvalho, Gesine Mollenhauer, Matthias Hubner and Venugopalan. 201 O. The
Tropical Brazilian Continental Margin. lN: Kon-Kee Liu , Larry Atkinson,
Renato Quinones and Liana Talaue-McManus et al. (eds.), Carbon and Nutrient
Fluxes in Continental Margins, Global Change - The IGBP Series, pp 423-496.
DOl 10.1007/978-3-540-92735-8 8, c Springer-Verlag Berlin Heidelberg 2010
Jha, P. K. , & Masao , M. (2013). Factors Affecting Nutrient Concentration and Stable
Carbon and Nitrogen Isotope Ratio of Particulate Organic Matter in the Ishikari
River System, Japan. Water, Air, & Soit Pollution, 224(5), 1551.
doi: 10.1007 /sll270-013-1551-z
Jin , L. , Whitehead, P. , & Hadjikakou, M. (2013) . A Study of the Yesilirmak River
Catchment in Northern Turkey: Spatial Patterns and Temporal Trends in Water
Quality. Journal of Environmental Protection, 04, 104- 120.
doi: 1 0.4236/jep.20 13.47 AO 13
Jujnovsky, J., L. Almeida-Lefiero, M. Bojorge-Garcia, Y. L. Monges, E.
Cantoral-Uriza and M. Mazari-Hiriart. 201 O. Hydrologie ecosystem services:
water quality and quantity in the Magdalena River, Mexico City. Hidrobiol6gica 20(2) : 113-126.
1 7 0
Kao, S.-J. , & Liu , K.-K. (1996). Particulate organic carbon export from a subtropical
mountainous river (Lanyang Hsi) in Taiwan. Limnology and Oceanography, 41(8), 1749- 1757.
Kao, S. J. , & Liu , K. K. (1997). Fluxes of dissolved and nonfossil particulate organic
carbon from an Oceania small river (Lanyang Hsi) in Taiwan. Biogeochemistry, 39, 255- 269.
Kim, J.-K. , Shin, J. M., Jang, C., Jung, S., & Kim, B. (2007). Comparison of TOC
and DOC Distribution and the Oxidation Efficiency of BOD and COD in
Severa( Reservoirs and Rivers in the Han River System. Journal of Korean Society on Water Quality, 23(1 ), 72- 80.
K!aviçs, M., Kokorïte, 1. , & Rodinovs, V. (2011). Dissolved organic matter
concentration changes in river waters of Latvia. Proceedings of the Latvian
Academy of Sciences. Section B. , 65(1-2), 40-47. doi : 1 0.2478/vl 0046-011-0017-1
Kormas, K. A. , A. Nicolaidou and M. Thessalou-Legaki (2003). Variability of
environmental factors of an eastern Mediterranean Sea river. Mediterranean Marine Science 4(1): 67-77.
Kormas, K. a, & Papaspyrou, S. (2004) . Growth of marine bacterioplankton on river
and seawater dissolved organic carbon in a Mediterranean coastal system. Cahiers de Biologie Marine 45: 55-64.
Kulinski, K. & Pempkowiak, J. (2011). The carbon budget of the Baltic Sea.
Biogeosciences, 8(11 ), 3219-3230. doi: 1 0.5194/bg-8-3219-2011
Kunz, M. J. (2011). Effect of Large Dams in the Zambezi River Basin: Changes in
Sediment, Carbon and Nutrient Fluxes. PhD thesis . ETH ZURICH.
Ledesma, J. L. J. , Kohler, S. J., & Futter, M. N. (2012). Long-term dynamics of
dissolved organic carbon: Implications for drinking water supply. Science of The
Total Environment, 432, 1- 11. doi : 10.1 016/j .scitotenv.2012.05.071
Lee, K. , Ryu , J. , Ahn, K. , Chang, H. , & Lee, D. (2007). Factors contro lling carbon
isotope ratios of dissolved inorganic carbon in two major tributaries of the Han
River, Korea. Hydrological Processes, 21 , 500- 509. doi: 10.1 002/hyp
------~---- -~--------------------
l 7 l
Lesack, L. F. W., Hecky, R. E., & Melack, J. M. (1984). Transport of carbon , nitrogen,
phosphorus and major solutes in the Gambia River, West Africa. Limnology and Oceanography, 29( 4), 816- 830.
Lewis, W. M., & Saunders III, J. F. (1989) . Concentration and transport of dissolved
and suspended substances in the Orinoco River. Biogeochemistry, 7, 203-240.
Lewis, William M., Hamilton, Stephen K. and Saunders, James F. 1995. Rivers of
Northern South America . Pp 219-256. IN: Cushing, C. , K. Cummish and G . W.
Minshall (eds.) River and Stream Ecosystems of the World. Elsevier. New York.
Li , W. , Dagaut, J. , & Saliot, a. (1995). The application of sterol biomarkers to the
study of the sources of particulate organic matter in the Solo River system and
and Serayu River, Java, Indonesia. Biogeochemistry, 31, 139- 154.
doi: 1 0.1007 /BF00004046
Lin, J. , Xie, L., Pietrafesa, L. J. , Ramus, J . S., & Paerl , H. W. (2007). Water Quality
Gradients across Albemarle-Pamlico Estuarine System: Seasonal Variations and
Model Applications. Journal of Coastal Research, 23( 1 ), 213- 229.
doi: 10.2112/05-0507.1
Liu , Kon-Kee, Gwo-Ching Gong, Chau-Ron Wu, and Hung-Jen Lee. 2010. The
Kuroshio and the East China Sea. ln: Liu , Kon-Kee, Larry Atkinson, Renato
Quinones, and Liana Talaue-McManus(ed).Carbon and Nutrient Fluxes in
Continental Margins---A G lobai Synthesis. Springer-Verlag Berlin Heidelberg.
Pp 124-146. DOl 10.1007/978-3-540-92735-8
Lobbes, J. M. , Fitznar, H. P. , & Kattner, G. (2000). Biogeochemical characteristics of
dissolved and particulate organic matter in Russian rivers entering the Arctic
Ocean. Geochimica et Cosmochimica Acta, 64(17), 2973- 2983.
Loh, P. S., Chen, C. T. A., Lou, J. Y., Anshari, G. Z., Chen, H. Y., & Wang, J. T.
(20 12). Comparing Lignin-Derived Phenols, 8 13C Values, OC/N Ratio and 14C
Age Between Sediments in the Kaoping (Taiwan) and the Kapuas (Kalimantan,
Indonesia) Rivers. Aquatic Geochemistry, 18, 141 - 158.
doi: 10.1007 /s 10498-011-9153-0
Magalhaes, C., Teixeira, C. , Teixeira, R., Machado , A, Azevedo, l. , & Bordalo, A A.
(2008). Disso lved organic carbon and nitrogen dynamics in the Douro River
estuary, Portugal. Ciencias Marinas, 34, 271 - 282. Retrieved from <Go to
ISI> ://000260312600002
l 7 2
Mantoura R .F.C. and E.M.S. Woodward. 1983. Conservative behaviour of riverine
disso lved organic carbon in the Severn Estuary : chemical and geochemical
implications. Geochimica et Cosmochimica Acta, 47(7), 1293- 1309.
Martins, Olasumbo and Probst, Jean-Luc. 1991. Biogeochemistry of Major African
Rivers: Carbon and Mineral Transport. IN : E. T. Degens, S. Kempe and J.E.
Richey (eds.). Biogeochemistry of Major World Rivers . SCOPE series, John
Wiley and Sons Ltd. Pp. 127-155.
Marwick, T. R. , Borges, A. Y. , Van Acker, K. , Darchambeau, F. , & Bouillon, S.
(20 14). Disproportionate Contribution of Ri parian Inputs to Organic Carbon
Pools m Freshwater Systems. Ecosystems, 17(6) , 974- 989.
doi : 10.1 007/sl 0021-014-9772-6
Masiello, A. C., & Druffel , E. R. M. (200 1 ). Carbon isotope geochemistry of the
Santa Clara River. Global Biogeochemical Cycles, 15(2), 407-416.
Maya, K. , Remya, S. I. , Baburaj, B. , Baijulal, B., Lekshmi, I. , Nisha, U. R., ...
Padma lai, D. (20 13). Natural and anthropogenic determinants of water quality
changes in a small tropical river basin, SW India. International Journal of
Agricultural Sciences, 3(1), 363- 372.
Meybeck M. and RaguA. (1996) River Discharges to the Oceans. An assessment of
suspended solids, major ions, and nutrients. Environment Information and
Assessment Report. UNEP, Nairobi , 250 p.
Ministry of Water, Land and Air Protection of British Columbia, Environment Canada.
( 1996). State of Water Quality of Alsek River Above Bates River 1992-1994.
Available at: http://www.env.gov.bc.calwat/wq/quality/alsekabv/figures .html# Il
Moon, S. , Huh, Y. , & Zaitsev, A. (2009) . Hydrochemistry of the Amur River:
Weathering in a Northern Temperate Basin. Aquatic Geochemistry, 15, 497- 527.
doi: 1 O. 1007 /s 1 0498-009-9063-6
Moore, S. , Gauci , V., Evans, C. D. , & Page, S. E. (20 11). Fluvial organic carbon
tosses fi·om a Bornean blackwater river. Biogeosciences, 8, 901 - 909.
doi : 1 0.5194/bg-8-90 1-2011
Mulholland, P.J. , & Watts, J. A. (1982). Transport of organic carbon to the oceans by
rivers of North America: a synthesis of existing data. Tell us, 34, 176- 186.
l 7 3
Mundy, C. J. , Gasselin , M. , Starr, M. , & Michel, C. (201 0) . Riverine export and the
effects of circulation on dissolved organic carbon in the Hudson Bay system,
Canada. Limnology and Oceanography, 55(1 ), 315-323.
Naiman , R. J. , & Link, G. L. (1997). Organic Matter Dynamics m 5 Subarctic
Streams, Quebec, Canada. Journal of the North American Benthological Society,
16(1), 33-39.
Neal, Edward G . 2007. Hydrology and Glacier-Lake-Out burst Floods ( 1987-2004)
and Water Quality (1998- 2003) of the Taku River near Juneau, Alaska. USGS
Scientific Investigations Report 2007-5027. Pp . 1-38.
Niemirycz, E., Gozdek, J., & Koszka-Maron , D. (2006). Variability of Organic
Carbon in Water and Sediments of the Odra River and Its Tributaries. Polish J of Environ. Stud., 15(4), 557- 563.
Nixon, S. W., Granger, S. L. , & Nowicki , B . L. (1995). An assessment of the annual
mass balance of carbon, nitrogen, and phosphorus in Narragansett Bay.
Biogeochemistry, 31(1), 15-61.
Noh, S., Choi, M. , Kim , E., Dan , N . P. , Thanh, B. X. , Ha, N . T. Van, ... Han, S.
(20 13). Influence of salinity intrusion on the speciation and partitioning of
mercury in the Mekong River Delta. Geochimica et Cosmochimica Acta, 106,
379-390. doi:l 0.10 16/j.gca.2012.12.018
Noller, B. , Huynh, T., Ng, J. , Zheng, J. , & Harris , H. (2012). Sources and Pathways of Contaminants to the Leichhardt River (pp. 1- 285).
Odemis, B. , & Evrendilek, F. (2007). Monitoring water quality and quantity of
national watersheds in Turkey. Environmental Monitoring and Assessment, 133,
215- 229. doi: 10.1 007/s 1 0661-006-9574-1
Ontario Clean Water Agency (OCWA). 2001. Attawapiskat First Nation (Band No.
143). In : Assessment Study of Water and Wastewater Systems and Associated
Water Management Practices in Ontario First Nation Commun ities. Pp 1-8.
Ontario Clean Water Agency (OCWA). 2001. Fort Severn First Nation (Band No .
89). ln : Assessment Study of Water and Wastewater Systems and Associated
Water Management Practices in Ontario First Nation Communities . Pp 1-9.
1 7 4
Ovezikoglou, V., Ladakis, M., Dassenakis, M., & Skoullos, M. (2003). Nitrogen ,
Phosphorus and Organic Carbon in Main Rivers of the Western Greece.
Global Nest Journal, 5(3), 147-156.
Pan, Pei Yi. 2012. Distributions and variations of dissolved organic carbon in Taiwan
Strait and Taiwanese Rivers. Master Thesis. lnstitute of Marine Geology and
Chemistry, National Sun Yat-sen University.
Panigrahy, B. K., & Raymahashay, B. C. (2005) . River water quality in weathered
limestone: A case study in upper Mahanadi basin, India. Journal of Barth System
Science, 114(5), 533- 543. doi: 10.1 007/BF02702029
Paolini, J. (1995). Particulate organic carbon and nitrogen In the Orinoco river
(Venezuela). Biogeochemistry, 29, 59- 70.
Patsch , J. , & Lenhart, H.-J. (2011). Daily Loads of Nutrients, Total Alkalinity,
Dissolved Inorganic Carbon and Dissolved Organic Carbon of the European
continental rivers for the years 1977-2009 (pp. 1- 1 59).
Pekka, L. , Halmeenpaa, H., Ecke, F., Vuori, K., Mokrotovarova, 0., Ohlander, B., & Ingri , J. (2008). Assessing pollution in the Kola River, northwestern Russia,
using metal concentrations in water and bryophytes. Boreal Environment
Research, 13, 15-30.
Pereira, R. , Bovolo, C. 1., Spencer, R. , Hernes, P. , Tipping, E. , Vieth-Hillebrand, A,
Pedentchouk, N. , ... Wagner, T. (2014). Mobilization of optically invisible
dissolved organic matter in response to rainstorm events in a tropical forest
headwater river. Geophysical Research Letters, 41 ( 4), 1202- 1208.
doi: 10.1002/20 13GL058658.Received
Petrone, K. C. (20 1 0). Catchment expott of carbon, nitrogen, and phosphorus across
an agro-urban land use gradient, Swan-Canning River system, southwestern Australia. Journal of Geophysical Research, 115(G1), GOI016. doi: 1 O. 1 029/2009JGOO 1 051
Petrucio, M. M. (2003) . Produtividade Bacterioplanctônica e Fitoplanctônica nos
Ecossistemas Aquaticos do Trecho Médio da Bacia do Rio Doce - MG .
UNTVERSlDADE FEDERAL DE SÂO CARLOS.
l 7 5
Pettine, M. , Patrolecco, L., Camusso , M., & Crescenzio, S. ( 1998). Transport of
Carbon and Nitrogen to the Northern Adriatic Sea by the Po River. Estuarine,
Coastal and Shelf Science, 46, 127- 142.
Pitta, E. , Zeri, C., Tzortziou, M., Dimitriou , E. , Paraskevopoulou , Y. , & Dassenakis, E.
(2014). Dissolved organic matter cycling in eastern Mediterranean rivers
experiencing multiple pressures . The case of the trans-boundary Evros River.
Mediterranean Marine Science, 15(2), 398-415 .
Point, D., Bareille, G ., Amouroux, D. , Etcheber, H ., & Donard , O. F. X. (2007).
Reactivity, interactions and transport of trace elements, organic carbon and
pa11iculate material in a mountain range river system (Adour River, France).
Journal ofEnvironmental Monitoring, 9, 157- 167. dai: 10.1 039/b616312b
Pokrovsky, O .. , & Schott, J. (2002). lron colloids/organic matter associated transport
of major and trace elements in small boreal rivers and their estuaries (NW
Russia). Chemical Geology, 190(1-4), 141 - 179.
doi: 1 O. 10 16/S0009-2541 (02)00 115-8
Prabhahar, C. , Saleshrani , K. , & Tharmaraj, K. (2012) . Seasonal Variation in
Physico-Chemical Parameters of Palar River in and Around Yaniyambadi
Segment, Vellore District, Tamil Nadu , India . International Journal of
Pharmaceutical & Biological Archives, 3(1 ), 99- 104.
Qiu, Yue and Ye, Yong. 2013. Exchanges of Nutrients and Organic Carbon between
Mangrove Forest and its Adjacent Water Area through Tide Actions in the
Jiulongjiang Estuary. Journal of Xiamen University (Natural Science), 52(5),
718-721 . dai: 1 0.6043/j.issn.0438-0479.2013.05.024
Raike, A. , Kortelainen , P., Mattsson, T. , & Thomas, O . N. (2012). 36 year trends in
dissolved organic carbon expo11 from Finnish rivers to the Baltic Sea. The Science of the Total Environment, 435-436, 188- 201 .
dai : 10.10 16/j.scitotenv.20 12.06. 111
Ralison, O . H., Borges, A. Y. , Dehairs, F., Middelburg, J . J ., & Bouillon , S. (2008).
Carbon biogeochemistry of the Betsiboka estuary (north-western Madagascar) .
Organic Geochemistry, 39(12), 1649- 1658.
dai: 10.1 016/j.orggeochem.2008.0J .Ol 0
1 7 6
Ran, L. , Lu, X. X. , Sun, H. , Han, J. , Li, R. , & Zhang, J. (20 13). Spatial and seasonal
variability of organic carbon transport in the Yellow River, China. Journal of Hydrology, 498, 76- 88. doi: 10.1 016/j.jhydro1.2013.06.018
Raymond, Peter A. and Spencer, Robert G.M. 2014. Chapter Il : Riverine DOM, rN:
Biogeochemistry of Marine Dissolved Organic Matter (Second Edition) (ed.
Hansell , Dennis and Carlson, Craig) . Elsevier AP. London. Pp 509-533.
Ren , M. , Cai, Y., Gao, N. , and Zhu, Y. 2006. Study on Assimilable Organic Carbon in
Raw Water ofYangtze Delta. Water Purification Technology, 25(6), 27-30.
Restrepo,J. D. and Kjerfve B . 2004. Chapter 14: The Pacifie and Caribbean Rivers of
Colombia: Water Discharge, Sediment Transport and Dissolved Loads. In:
Environmental Geochemistry in Tropical and Subtropical Environments,
Env ironmental Science, pp 169-187.
Richey, J. E ., Hedges, J. I. , Devol, A . H., Quay, P. 0 ., Victoria, R. , Martine! li, L. , ...
Richey, E . (1990). Biogeochemistry of Carbon in the Amazon River of carbon in
the Amazon River Biogeochemistry. Limnology and Oceanography, 35(2),
352- 371.
Robson, B. J., Schult, J. , Smith, J. , Burford, M. , & Revill, A . (2010). Towards
understanding the impacts of land management on productivity in the Da/y River. Final Report ofTRaCK (Tropical Rivers and Coastal Knowledge). (pp . 1- 170).
Rollo , Hugh Andrew. 2003. Processed Kimberlite-Water Interactions in Diamond
Mine Waste, Ekati Diamond Mine, N. W.T. , Canada. Master Thesis. Queen 's
University
Rosa, E. , Hillaire-Marcel, C. , Ghaleb, B ., & Dick, T. A. (2012). Environmental and
seasonal controls on riverine dissolved uranium in the Hudson, James, and
Ungava bays region, Canada. Canadian Journal of Earth Science, 49 758-771.
doi : 1 0 .1139/E20 12-025
San Diego-McGione1 , V. Dupra1, and S. V. Smith . 1998. N and P Budget of
Lingayen Gulf, Philippines.
http://nest. su.se/MNODE/Asia/Philippines/ lingayen/Lingayenbud .htm
Santos, 1. R ., Cook, P. L. M. , Rogers, L. , de Weys, J. , & Eyre, B. O. (20 12). The "salt
wedge pump": Convection-driven pore-water exchange as a source of dissolved
1 7 7
organic and inorganic carbon and nitrogen to an estuary. Limnology and
Oceanography, 57(5), 1415- 1426. doi: 1 0.4319/ lo .20 12.57.5.1415
Sarin , M. M. , Sudheer, A. K. , & Balakrishna, K. (2002). Significance of riverine
carbon transport: A case study of a large tropical river, Godavari (lndia). Science in China (Series C), 45(Supp.), 97- 108.
Sarma, Y. Y. S. S. , Yiswanadham, R. , Rao , G. D. , Prasad , Y. R., Kumar, B. S. K. ,
Naidu, S. a., ... Murty, T. Y. R. (2012) . Carbpn dioxide emissions from Indian
monsoonal estuaries. Geophysical Research Letters, 39(3), n/a- n/a.
doi : 1 0.1029/2011 GL050709
Schafer, J. , Blanc, G. , Audry, S. , Cossa, D. , & Bossy, C. (2006). Mercury in the
Lot-Garonne River system ( France ): Sources , fluxes and anthropogenic
component Mercury in the Lot-Garonne river system ( France ): Sources , fluxes
and anthropogenic component Depending on the origin and nature of SPM , HgT
P concentra. Applied Geochemistry, 21 (3) , 515- 527.
Schneider-Vieira, F. , Baker, R. , & Lawrence, M. (1994) . THE ESTUARIES OF
HUDSON BA Y: a case study of the physical and biowgical characteristics of
selected sites (pp. 1- 85) .
SENES (Specialists in Energy, Nuclear and Environmental Sciences). 2013. Proposed
New Post Creek Hydroelectric Project - Aquatic Environment. Technical
Supporting Document, submitted to Coral Rapids Power lnc. and Ontario Power
Generation lnc. and prepared by Jerry Fitchko.
Sempere, R. , Charribere, B., van Wambeke, F. , & Cauwet, G. (2000). Carbon inputs
of the Rhne River to the Mediterranean Sea: Biogeochemical implications.
Global Biogeochemical Cycles, 14(2), 669-<581.
Servais, P. , Anzil , A. , & Yentresque, C. (1989). Simple Method for Determination of
Biodegradable Dissolved Organic Carbon in Water. Applied and Environmental
Microbiology, 55, 2732- 2734. doi:0099-2240/89/ I 02732-03
Sharma, S. K., & Subramanian, Y. (2008) . Hydrochemistry of the Narmada and Tapti
Ri vers, 1ndia. Hydrological Processes, 22, 3444- 3455. doi: 10.1 002/hyp
Sheehan, R. W. 1989. Mattagami River Baseline Biological Study, 1986-1987. Report
No. 89-34-K Ontario Hydro Research Division, Toronto . 127+ p
1 7 8
Siepak, J. ( 1999). Total Organic Carbon (TOC) as a Sum Parameter of Water
Pollution in Selected Polish Rivers (Vistula, Odra, and Warta). Acta Hydrochim.
Hydrobiol., 27(5), 282- 285 .
Skoul ikidis, T. , Bertahas, 1., & Koussouris, N. T. ( 1998). The environmental state of
freshwater resources in Greece (rivers and lakes). Environmental Geology,
36(1-2), 1- 17.
Sondag, Francis, Jean-Loup Guyot, J. S. Moquet, Ala in Laraque, Georges Adele,
Gerard Cochonneau, Jean-Claude Doudou, Christe lle Lagane, and Philippe
Vauchel. Suspended sed iment and dissolved Joad budgets of two Amazonian
rivers from the Guiana Shie ld: Maroni River at Langa Tabiki and Oyapock River
at Saut Mari pa (French Guiana) . Hydrological Processes, 2010, 24 (Il),
1433-1445.
Stets, E. G ., & Striegl, R. G. (20 12). Carbon export by ri vers drain ing the
conterminous United States. In/and Waters , 2, 177- 184. dai: 1 0.5268/IW-2.4.51 0
Stoichev, T., Amouroux, D. , Monperrus, M. , Point, D. , Tessier, E. , Bareille, G., &
Donard, O. F. X. (2006). Mercury in surface waters of a macrotidal urban
estuary (River Adour, south-west France). Chemistry and Eco logy, 22(December
20 13), 137- 148. dai: 10.1080/02757540500526450
Sugimoto, R., Kasai, A., Yamao, S., Fujiwara, T. , & Kimura, T. (2006). Short-term
variation in behavior of a llochthonous particulate organic matter accompanying
changes of river discharge in Lse Bay, Japan. Estuarine, Coastal and Shelf
Science, 66, 267- 279. dai: 10.10 16/j .ecss.2005.08 .014
Teodoru, C. R. , del Giorgio, P. A. , Prairie, Y. T. , & Camire, M. (2009). Patterns in
pC02 in boreal streams and rivers of northern Quebec, Canada. Global
Biogeochemical Cyc les, 23, 1- 11. doi :10.1029/2008GB003404
Tian, L., Wu, Y. , Lin, J., Zhu, Z., and Zhang, J. 2010. Distribution and composit ion of
organic carbon in the northeastern Hainan rivers and coasts during winter.
Journal ofTropical Oceanography, 29(5), 136-141.
Tipping, E. , Marker, A. F. H. , Butterwick, C., Collett, G. D. , Cranwell , P. A. , Ingram,
J. K. G., .. . Simon, B. M. (1997) . Organic carbon in the Humber rivers. Science
ofThe Total Environment, 194/195, 345- 355.
1 7 9
Tockner, Klement , Uehlinger, Urs and Robinson, Christopher T.(Eds.) 2009. Rivers of
Europe. (P' ed.), pp. 1- 35 . London: Elsevier B . V.
Tosiani,T., Loubet,M., Viers,J. , Yalladon,M. , Tapia,J. , Marrero,S. , Yanes,C. ,
Ramirez,A. and Dupre,B.(2004) : Major and trace elements in river-borne
materials from the Cuyuni basin (southern Venezuela) : evidence for
organo-colloidal control on the dissolved Joad and element redistribution
between the suspended and dissolved Joad . Chemical Geology, 211 , 305-334
Tripti , M. , Lambs, L. , Otto, T. , Gurumurthy, G. P. , Teisserenc, R., Moussa, l. ,
Probst, J. L. (20 13). First assessment of water and carbon cycles in two tropical
coastal rivers of south-west lndia: an isotopie approach . Rapid Communications
in Mass Spectrometry, 27(15), 1- 9. doi:l0.1002/rcm .6616
United Nations Environment Programme (UNEP)----Mediterranean Action Plan
(MAP). (2003). Technical Reports Series No. 141 UNEPIMAP: Riverine Transport of Water, Sediments and Pollutants ta the Mediterranean Se a (p. 121 ).
URS Australia Pty Ltd . 2014. Onslow Water fnfrastructure Upgrade Project: Desktop
Risk Assessment on Constituents (excluding NORMs) of the Residual Saline
Stream. Report No.: 42908178/Geo-0739/0
Yan Binsbergen, N . 20 Il. Annual Report of Breede River Valley Municipality.
http://www.breedevallei .gov.zalbvmweb/ images/Annua!ReportsOther/4638 7%
20waters dec1 0-revised .pdf
Vargas, C.A., Arriagada, L., Sobarzo, M. , Contreras, P. Y. , & Saldias, G. (2013).
Bacterial production along a river-to-ocean continuum in central Chile:
implications for organic matter cycling. Aquatic Microbial Eco/ogy, 68,
195- 213 .
Yeyssy, E. , Etcheber, H. , Lin , R. G. , & Maneux, E. (1999). Seasonal variation and
origin of Particulate Organic Carbon in the lower Garonne River at La Reole
(southwestern France) . Hydrobiologia, 391 , 113- 126.
Yoss, B. M. , Peucker-Ehrenbrink, B., Eglinton, T. 1. , Fiske, G. , Wang, Z. A. , Hoering,
K. a., . .. Wiebe, B. (20 14). Tracing river chemistry in space and ti me: Dissolved
inorganic constituents of the Fraser River, Canada. Geochimica et
Cosmochimica Acta, 124, 283- 308. doi: 10. 1 016/j .gca.20 13.09.006
1 8 0
Wang, Jiangtao. 1998. Colloïdal organic carbon in Huanghe, Changjiang and
Qian tang River. Chinese Science Bulletin 43(11 ), 915-917.
Wang, X., Ma, H. , Li , R., Song, Z. , & Wu, J. (2012). Seasonal fluxes and source
variation of organic carbon transported by two major Chinese Rivers: the Yellow
River and Changjiang (Yangtze) River. Global Biogeochemical Cycles, 26(2).
doi : 10.1029/20 Il GB004130
Wang, Z. A. , Bienvenu, D. J. , Mann, P. J. , Hoering, K. a. , Poulsen , J. R., Spencer, R.
G. M., & Holmes, R. M. (2013). lnorganic carbon speciation and fluxes in the
Congo River. Geophysical Research Letters , 40(3), 511-516.
doi: 10.1 002/gr1.50160
Warnken , K . W., & Santschi, P. H. (2004). Biogeochemical behavior of organic
carbon in the Trinity River downstream of a large reservoir lake in Texas, USA.
Science of the Total E nvironment, 329, 131 - 144.
doi :1 0.1 016/j.scitotenv.2004.02.017
Water Resources Division of 1ndian and Northern Affairs, Canada. 2002. Peel River
Basin Water Quality Report. Pp.1-49.
Wu, W., Zheng, H. , Yang, J ., Luo, C. And Zhou, B. 2011 . Chemical weathering of
large river catchments in China and the global carbon cycle. Quaternary
Sciences, 3 1 (3 ), 3 97-407.
Wu, Y. , & Zhang, J. (200 1 ). Carbon isotope geochemistry in the Yalujiang estuary.
Science in China (Series B) , 44(Supp.), 1- 5.
Xia, Bin and Zhang Longjun . (2011) . Carbon distribution and fluxes of 16 rivers
discharging into the Bohai Sea in summer. Acta Oceanologica Sinica, 30(3),
43- 54. doi:10.1007/sl3131-011-0118-3.
Yang, Limin, Ni , Zhixin , Li , Xiaobo, Lin, Zhuguang and Wang, Qiuquan. 2008.
Complexing capacity and soluble complex lability of cadmium in the Minjiang
river. Environmental Chemistry, 27(6), 795-799.
Yao, G. , Gao , Q. , Wang, Z ., Huang, X ., He, T. , Zhang, Y. , ... Ding, J. (2007).
Dynamics of C02 partial pressure and C02 outgassing in the lower reaches of
the Xijiang River, a subtropical monsoon river in China. Science of The Total
Environment, 376, 255- 266. doi: 10.1 016/j.scitotenv.2007.01.080
1 8 1
Yeh, Yi-Ting. 2009. Export of Particulate Carbon and Nitrogen from the Gaoping
River and their Burial in the Associated Coastal Sea. Master's Thesis . National Sun Yat-sen University.
Yidana, S. M ., Ophori, D., & Banoeng-Yakubo, B. (2008). A multivariate statistical
analysis of surface water chemistry data-The Ankobra Basin, Ghana. Journal of
Environmental Management, 86, 80- 87. doi: 10.1 016/j.jenvman.2006.11.023
Yu, W. , Zou, L.;Wen, M., and Zhang, Y. 2015. Distribution of Organic Carbon in the
Estuary of the Shuangtaizi River. Periodical of Ocean University of China, 45(2), 101-108.
Zhang, J. , Yu, Z .. , Liu , S .. , Xu , H. , Wen, Q .. , Shao, B., & Chen, J .. (1997).
Dominance of terrigenous particulate
Shuangtaizihe estuary. Chemical
doi: 1 O. 1 0 16/S0009-2541 (97)000 12-0
organic carbon in the high-turbidity
Geology, 138(3-4), 211 - 219.
Zhang, J. , Liu, S. M. , Xu, H. , Yu, Z. G. , Lai , S. Q. , Zhang, H. , ... Chen, J. F. (1998) .
Riverine Sources and Estuarine Fates of Particulate Organic Carbon from North
China in Late Summer. Estuarine, Coastal and Shelf Science , 46(3) , 439-448. doi: 1 0.1006/ecss.1997.0277
Zhu , X. , Yu, G ., Gao, Y. And Wang, Q. 20 12. Fluxes of Parti cu la te Carbon from
Rivers to the Ocean and their Changing Tendency in China. Progress in
Geography, 31(1): 118-122.