NOTICE -- The LBA-ECO Project website is no longer being supported.  This archive is a snapshot, as it existed in 2013, of the LBA-ECO website, maintained by NASA Goddard Space Flight Center, and now archived at the ORNL DAAC.  Links to external websites may be inactive. Final data products from the LBA project can be found at the ORNL DAAC.
banner banner banner banner banner banner
banner banner banner banner banner banner banner
home aboutlibrarynews archivecontacts banner

Abstracts & Profiles
Research Sites
Synthesis Groups
Field Support
Find LBA Data
Investigator Checklist
Process & Policy
Documentation & Archive
Training & Education
Activities Summary
T&E Goals
Student Opportunities
  Folha Amazônica


CD-06 (Richey / Victoria)

LBA Dataset ID:



1. ELLIS, E.E.
      5. QUAY, P.D.

Point(s) of Contact:

ORNL DAAC User Services Office Oak Ridge National Laboratory Oak Ridge, Tennessee 37 (

Dataset Abstract:

Our objectives were to determine the relationship between respiration rates and the in situ concentrations of the size classes of organic carbon (OC), and the biological source (C3 and C4 plants and phytoplankton) of organic matter (OM) supporting respiration. Respiration was measured along with OC size fractions and dissolved oxygen isotopes (delta18O-O2) in rivers of the central and southwestern Amazon Basin. Rates ranged from 0.034 umol O2 L-1 h-1 to 1.78 umol O2 L-1 h-1, and were four-fold higher in rivers with evidence of photosynthetic production (demonstrated by delta 18O-O2,24.2 per mil) as compared to rivers lacking such evidence (delta 18O-O2.24.2 per mil; 1.35 plus or minus 0.22 vs.0.30 plus or minus 0.29 mmol L-1 h-1). Rates were likely elevated in the former rivers, which were all sampled during low water, due to the stimulation of heterotrophic respiration via the supply of a labile, algal-derived substrate and/or the occurrence of autotrophic respiration. The organic composition of fine particulate OM (FPOM) of these rivers is consistent with a phytoplankton origin.

Beginning Date:


Ending Date:


Metadata Last Updated on:


Data Status:


Access Constraints:


Data Center URL:

Distribution Contact(s):

ORNL DAAC User Services Office Oak Ridge National Laboratory Oak Ridge, Tennessee 37 (

Access Instructions:


Data Access:

IMPORTANT: The LBA-ECO Project website is no longer being supported. Links to external websites may be inactive. Final data products from the LBA project can be found at the ORNL DAAC. Please follow the fair use guidelines found in the dataset documentation when using or citing LBA data.

LBA-ECO CD-06 Carbon Cycling in Rivers in Amazonas and Acre, Brazil: 2005-2006 :

Documentation/Other Supporting Documents:

LBA-ECO CD-06 Carbon Cycling in Rivers in Amazonas and Acre, Brazil: 2005-2006 :

Citation Information - Other Details:

Ellis, E.E, J.E. Richey, A.K. Aufdenkampe, A.V. Krusche, P.D. Quay, C. Salimon and H. Brandao da Cunha. 2012. LBA-ECO CD06 Carbon Sources and Respiration Rates in Rivers in Amazonas and Acre: 2005-2006. Data set. Available on-line [] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A.

Keywords - Theme:

Parameter Topic Term Source Sensor


Keywords - Place (with associated coordinates):

(click to view profile)
(click to view profile)
North South East West
  BRAZILIAN AMAZON -2.58900 -10.07300 -58.74600 -72.70000

Related Publication(s):

Ellis, E.E., J.E. Richey, A.K. Aufdenkampe, P.D. Quay, A.V. Krusche, C. Salimon, and H.B. da Cunha. 2012. Factors controlling aquatic respiration and its role in fueling CO2 gas evasion in rivers of the central and southwestern Amazon Basin. Limnol. Oceangr. 57(2), 2012, 527-540. doi: 10.4319/lo.2012.57.2.0527

Data Characteristics (Entity and Attribute Overview):

Data Characteristics:

Data are presented in one ASCII comma separated file titled CD06_River_respiration_survey.csv and are organized as follows:

File name:,River_respiration_survey.csv,

File date,29-Jun-12,

Associated LME:,CD06_Respiration,


1,Site Name,(River or Stream),Name of the river of stream sampled,

2,Sampling Year,YYYY,Year in which samples were collected,

3,Date,YYYMMDD,Date on which samples were collected,

4,Latitude,degrees S,Geographic coordinates for the sampling site reported in degrees latitude,

5,Longitude,degrees W,Geographic coordinates for the sampling site reported in degrees longitude,

6,Area_watershed,km2,Area of the watershed for the river sampled reported in square kilometers,

7,Hydrograph_stage,,Hydrograph stage indicating if the river level was falling, at a minimum, rising or at a maximum,

8,Water_type,,River water type: clear, black or white,

9,Depth ,m,Sampling depth reported in meters,

10,DO,micromoles per liter,Dissolved oxygen concentration reported in micromoles of oxygen per liter of water,

11,pCO2,Pascals,Partial pressure of CO2 gas in water reported in pascals,

12,DIC,micromoles per liter,Dissolved inorganic carbon concentration reported in micromoles of C per liter of water,

13,delta_13C _DIC,per mil,delta 13C of the dissolved inorganic carbon component reported in per mil relative to the PDB standard,

14,pH,,pH of the river water,

15,Temp,degrees C,Temperature of the river water at the time of sampling reported in degrees Celcius,

16,Respiration,umol CO2 per m^2 *s,Depth integrated respiration rate (flux of CO2 reported in micromoles of CO2 per square meter per second),

17,SE_Respiration,umol CO2 per m^2 *s,Standard error of the calculated respiration flux (N=3),

18,Evasion_CO2,umol CO2 per m^2 *s,Evasion flux of CO2 reported in micromoles of CO2 per square meter per second,

19,SE_Evasion,umol CO2 per m^2 *s,Standard error of the calculated evasion flux of CO2. Error was propagated using Monte Carlo boot strapping procedures,

20,Resp/Evas,percent,Percent of CO2 evasion flux attributed to respiration calculated as respiration/ evasion *100. Reported in percent,

21,SE_R/E,percent,Standard error of the calculated fraction of evasion represented by respiration,

22,WC_Respir_Rate,umol O2 per L* h,Water-column respiration rate reported in micromoles of oxygen per liter per hour.,

23,O2_Sat,,The concentration of oxygen measured in the river water relative to the concentration that would be expected if the water-column was 100% saturated with oxygen at that temperature.,

24,delta_18O_DO,per mil,delta 18O of the dissolved oxygen in the riverwater reported in per mil relative to the SMOW (standard mean ocean water) standard,

25,TSS,mg per L,Concentration of total (CSS + FSS) suspended sediment reported in milligrams per liter,

26,CSS,mg per L,Concentration of coarse suspended sediment (> 63 micrograms) reported in milligrams per liter,

27,FSS,ng per L,Concentration of fine suspended sediment (between 0.7 micrograms and 63 micrograms) reported in milligrams per liter.,

28,TOC,mg per L,Concentration of total organic carbon reported in milligrams per liter,

29,CPOC,mg per L,Concentration of coarse particulate organic carbon reported in milligrams per liter,

30,FPOC,mg per L,Concentration of fine particulate organic carbon reported in milligrams per liter,

31,DOC,mg per L,Concentration of dissolved organic carbon reported in milligrams per liter,

32,DOC_high_MW,mg per L,Concentration of high molecular weight dissolved organic carbon defined as greater than 100 kDa in size and reported in milligrams per liter,

33,DOC_med_MW,mg per L,Concentration of medium molecular weight dissolved organic carbon defined as less than 100 kDa but greater than 5 kDa in size and reported in milligrams per liter,

34,DOC_low_MW,mg per L,Concentration of low molecular weight dissolved organic carbon defined as less than 5 kDa in size and reported in milligrams per liter,

35,C:N_CPOC,,The atomic carbon to nitrogen ratio of the coarse particulate organic carbon. ,

36,C:N_FPOC,,The atomic carbon to nitrogen ratio of the fine particulate organic carbon.,

37,delta_13C_CPOC,per mil,delta 13C of the dissolved coarse particulate organic carbon component reported in per mil relative to the PDB standard.,

38,delta_13C_FPOC,per mil,delta 13C of the dissolved fine particulate organic carbon component reported in per mil relative to the PDB standard.,

39,delta_13C_DOC,per mil,delta 13C of the dissolved organic carbon component reported in per mil relative to the PDB standard.,

40,delta_13C_CO2resp,per mil,delta 13C of the carbon dioxide resulting from respiration reported in per mil relative to the PDB standard.,

41,Conc_bacteria,cells/mL,Concentration of bacterial cells reported in number of cells per milliliter of water,


,missing data are represented by -9999,


Site Name,Sampling Year,Date,Latitude,Longitude,Area_watershed,Hydrograph_stage,Water_type,Depth ,DO,pCO2,DIC,delta_13C _DIC,pH,Temp,Respiration,SE_Respiration,Evasion_CO2, SE_Evasion,Resp/Evas,SE_R/E,WC_Respir_Rate,DO_Sat ,delta_18O_DO,TSS,CSS,FSS,TOC,CPOC,FPOC,DOC,DOC_high_MW,DOC_med_MW,DOC_low_MW,C:N_CPOC,C:N_FPOC,delta_13C_CPOC,delta_13C_FPOC,delta_13C_DOC,delta_13C_CO2resp,Conc_bacteria

Campina,2006,20060817,2.589,60.033,< 10,falling,black,0.3,102.6,1308,344.7,-26.6,4,25.1,-9999,-9999,-9999,-9999,-9999,-9999,-9999,-9999,-9999,4,3.1,0.9, 32.8,1.3,0.18,31.3,3.6,21.1,6.6,29.6,23.6,-29,-29.2,-9999,-9999,-9999

Barro Branco,2005,20050716,2.93,59.974,< 10,falling,clear,0.4,186.9,970,327.4,-22.4,4.6,25.6,0.014,0.007,12.41,-9999,0.11,0.05,0.13,0.76,25.7,0.5,0.5,-9999,3.4,0.17,0.08,3.2,-9999,-9999,2.2,23.8,10.7,-29.9,-28.2,-9999,-9999,-9999

Barro Branco,2006,20060829,2.93,59.974,< 10,falling,clear,0.4,196.1,731,279.9,-24.3,4.7,25.8,-9999,-9999,-9999,-9999,-9999,-9999,0.03,0.83,25.2,0.3,0.1,0.2, 2.4,0.03,0.07,2.2,0.1,1.3,0.9,23.5,16,-29.7,-27,-29.8,-9999,164355

Negro,2005,20050802,3.062,60.285,716770,falling,black,34,101.3,659,208.5,-25.2, 5.1,29.2,1,0.4,12.7,0.8,8,3,0.11,0.55,27,0.4,0,0.4,9.6,0,0.56,9,2.9,3,3.1,11.6,11.7,-31.5,-29.6,-9999,-9999,-9999


Catuaba,2005,20050830,10.073,67.614,< 10,Low,clear,0.5,207.7,201,121,-16.9,6.2, 23.5,0,0.008,2.87,-9999,1,0,0.17,0.88,24.7,4.2,0.2,4,2.1,0.01,0.5,1.6,0.8,0.2, 0.5,18,11.4,-30,-28.6,-9999,-9999,-9999

Catuaba,2006,20060925,10.073,67.614,< 10,Low,clear,0.5,217.9,163,108.5,-20.2,5.1,24,-9999,-9999,-9999,-9999,-9999,-9999,0.36,0.86,25.3,9.3,0.3,9,2.6, 0.03,1.05,1.5,0.8,0,0.7,20.7,9.9,-29.5,-29.1,-28.7,-28.3,2208262

Humaita,2005,20050826,9.751,67.672,< 10,Low,white,0.3,156.5,281,104.9,-17.1,5.6,27.9,0.1,0.03,1.13,-9999,6,2,0.76,0.62,27,4.6,0.6,4,4.2,0.05,0.48,3.7, 1.1,-9999,-9999,18.4,8.5,-29.7,-27.4,-9999,-9999,-9999

Data Application and Derivation:

The purpose of this work was to understand the factors that control the range of water-column respiration rates observed in rivers and streams across the Amazon Basin. Accordingly, we sampled rivers with a range of water chemistry types and respiration rates to determine how in situ concentrations of various parameters affected respiration rates. We then performed a series of statistical analyses, including partial correlation, step-wise backward multiple linear regression, and standard linear regression. To be considered a candidate for the multiple linear regression, input variables were excluded if they were highly correlated with each other (i.e. had a value of r that exceeded 0.7), or if there was more than one missing datum per variable.

Much of the details on the derivitization of the data is reported in the methods section below and users are encouraged to view the publication for full details. Many parameters were processed minimally post field collection. Additional information is provided here for the calculation of the depth-integrated respiration rate, and the CO2 gas evasion flux. The depth-integrated respiration rate for a given site was calculated from the respiration rate (i.e. measurements of oxygen consumption (in umols L-1 h-1). This rate was converted to CO2 production by using a respiratory coefficient of 1. It was then multiplied by the depth of the river to yield a depth-integrated respiration rate in terms of umols CO2 m-2 s-1.

The error was then determined using Monte Carlo error propagation techniques.

Most of the gas evasion rates reported here were also published in Alin et al. (2010) and were determined using a floating chamber equipped with a fan. However, not all sites were analyzed by Alin et al. (2010). Thus, for these sites, the gas evasion flux (in umol/(m2*s)) was determined by using the difference between the pCO2 measurements of the atmosphere and the water (as described in detail in Ellis et al. (2012)) using the following equation:

F= kCO2 * gamma* (PCO2_atm- PCO2_s)

where F is the outgassing flux of CO2 in (umol m-2 s-1) kCO2 is the temperature-dependent gas exchange coefficient for CO2 (m d-1), gamma is CO2 solubility (umolm-3*uPa-1;Weiss 1974), and PCO2_atm and PCO2_s are the partial pressures of CO2 in the atmosphere and solution, respectively. kCO2 was determined as a function of wind speed (Alin et al. 2010). A value of k600, the gas transfer velocity for freshwater at 20 degrees C, was selected for each wind speed based on the relationship between k600 and u10 values presented in Alin et al. (2010). Monte Carlo error-propagation techniques were used to determine the error of our calculated gas evasion flux.

Quality Assessment (Data Quality Attribute Accuracy Report):

Quality Assessment:

We list the precision below for the following variables analyzed in this study:

delta_13C: 0.3 per mil

pH: 0.1 pH unit.

DIC concentration: 1 percent of DIC value.

Respiration rate: 0.01 umol O2 L-1 hr-1

delta_18O of dissolved O2: 0.2 per mil

All measures of organic carbon concentration (DOC, DOC > 100 kDa, DOC between 5-100 kDa, DOC < 5 kda) FPOC, CPOC)= 0.1 mg L-1

All measures of suspended sediment concentration (TSS, FSS, CSS) = 0.1 mg L-1

Bacterial concentration: 0.1 x 10^6 cells mL-1

Process Description:

Data Acquisition Materials and Methods:

Study area: Samples were collected during 2005 and 2006 in the Brazilian states of Acre and Amazonas, which are located in southwestern and central Amazonia. Locations were chosen to represent a range of water types and conditions found in these regions. Due to the predominance of whitewater rivers in both Amazonas and Acre and the logistical challenges of reaching a variety of river types in this large region, we sampled 10 whitewater rivers of varying sizes. We also sampled two clear water streams (one each in Amazonas and Acre), and two blackwater rivers in Amazonas. Watershed areas ranged from less than 10 km2 to 2,910,510 km2, which were calculated as in Mayorga et al. (2005). Not all sites were in the same stage of the hydrograph at the time of sampling. All rivers in Acre were in the low water stage, whereas rivers draining Amazonas were in the falling-water stage. We collected samples from 14 sites from July to September 2005, which coincided with a severe drought in the western and southern regions of the Amazon Basin (Zeng et al. 2008). Eight of these sites were resampled during August through September 2006 of the following year (no drought).

Sample collection: Samples were collected from the thalweg of rivers using a submersible pump placed at six-tenths of the total river depth. pH, conductivity, and dissolved oxygen were measured by immersing field probes (Thermo Orion 290 A+ pH meter, a Chek Mite CD-30 conductivity meter, and a 55 YSI dissolved oxygen probe) in a continuously overflowing graduated cylinder. For small streams, samples were taken directly below the water surface to minimize disturbance. PCO2 was analyzed via headspace equilibration following the methods of Cole et al. (1994) and modified as in Alin et al. (2010). PCO2 samples were either measured immediately using infra-red gas analysis via a Li-Cor LI-820 (Alin et al. 2010) or stored in glass bottles until analysis with a Shimadzu gas chromatograph (GC-17A equipped with flame ionization and electron capture detectors and a methanizer).

Lab methods:

Size fractionation

Bulk size fractions (CPOC [greater than 63 um], FPOC [0.7 to 63 um], and DOC [less than 0.7 um]) were filtered in the field, whereas size fractionation of DOC was processed in the laboratory. Coarse suspended sediment (CSS) concentrations were measured by first passing a known volume of river water through a 63-um sieve, and then later drying and weighing the sieved material. The material collected from a plankton net was preserved with HgCl2 for later analyses of weight percentages (percent by weight) of C, N, and delta13C of CPOC. CSS concentrations were multiplied by percent by weight C to determine CPOC concentrations. Sieved river water was homogenized with a churn splitter (Wilde and Radtke 2003) and then filtered, providing the fine suspended sediment concentration (FSS) by mass difference (Aufdenkampe et al. 2001). Sieved water was also passed through precombusted glass fiber filters (GF/F), which were then analyzed for d13C, percent by weight of C and N, and FPOC concentrations. The filtrate of the GF/F filter (defined as DOC) was stored in precombusted glass vials and immediately preserved with HgCl2 pending no further analysis. Centrifuge ultrafiltration was used to size-fractionate DOC into the following categories: high molecular weight (HMW; greater than 100 kDa), medium molecular weight (MMW; between 5 and 100 kDa), and low molecular weight (LMW; less than 5 kDa) DOC, using a method modified from Burdige and Gardner (1998). Water was filtered through two GF/F filters in the field, placed on ice in the dark, transported back to the laboratory, and refrigerated until analyzed (within 48 h). Centrifuge tubes (Amicon Ultra-15 Centrifugal Filter Units) were precleaned by sonication with two 10% HCl rinses, followed by an Alconex rinse, and five C-free Milli-Q water rinses for an hour each. The 5-kDa filters were cleaned by centrifuging 15 mL of 0.1 mol per L NaOH through the filter unit, at 4,000 x g for 20 min twice, followed by a third NaOH rinse for 10 min, and two Milli-Q water rinses for 10 min. Fifteen milliliters of sample was then centrifuged for 40 min. The 100-kDa filters were cleaned as follows: three 15-mL NaOH rinses for 15 min, followed by one Milli-Q water rinse, and two Milli-Q water rinses for 30 min. The sample was then centrifuged for 30 min. Controls were run using albumin to ensure that the filter was not affected by the cleaning process. The concentration factors for the retentate of the 5-kDa and 100-kDa centrifugal filter units were 104.39 and 53.39, respectively (Millipore Corporation). However, we opted to analyze the filtrate, rather than the retentate, because it was of adequate volume for DOC analyses (greater than 180 microliters). To calculate the percentage of DOC that is less than size X we used equation 1 (see accompanying documentation)). To determine the concentration of DOC (less than 5 kDa or less than 100 kDa) the unfiltered DOC concentration was multiplied by the percentage of DOC in the given size category. The concentration of the size fractions of DOC was obtained by subtracting the appropriate value(s) from the original DOC concentration. DOC concentrations were measured after acidification and sparging with high-temperature combustion using a Shimadzu TOC500A carbon analyzer (2005 samples) and a Shimadzu TOC-V CPH carbon and nitrogen analyzer (2006 samples). Those samples with high DIC concentrations were acidified and sparged for an additional 20 min to ensure DIC removal.

Carbon isotopic analyses and C:N ratios

Stable isotopes (13:12C) of carbon were measured in both the inorganic and organic size fractions to aid in partitioning OM among end-member sources. Results are given in delta notation with units of per mil, and were normalized relative to Vienna Peedee Belemnite. After drying coarse and fine materials in a 60 degree C oven, the samples were analyzed for delta13C and C:N ratios using a Finnigan Delta Plus mass spectrometer coupled to a Fissions EA 1110 CHN analyzer with a precision of 0.3 per mil for the mass spectrometer. For 2005 samples, the C:N ratio was obtained directly from a model 440 CHN analyzer made by Exeter Analytical. The d13C of DOC was analyzed using an automated method in which DIC was sparged from the sample after adding phosphoric acid, followed by sodium persulfate oxidation of DOC to CO2. The CO2 gas was carried to an infra-red gas analyzer and then to a PDZ Europa-Hydra 20-20 isotope ratio mass spectrometer. Only the 2006 samples were analyzed. DIC field collections and isotopic measurements (delta13C of DIC) were conducted as in Quay et al. (1992), with a precision of 0.03 per mil for the 2006 samples. DIC concentrations were calculated from pH and PCO2 for the 2005 samples. We used temperature-dependent equilibrium constant values (K1, K2, and KH) as reported in Clark and Fritz (1997). To estimate the delta13C of phytoplankton, we used an isotopic fractionation factor of 12 to 17 per mil between the delta13C of H2CO3 (calculated from the delta13C of DIC [as in Mayorga 2004, using the equilibrium fractionation factors from Zhang et al. 1995]) and phytoplankton. This fractionation factor is derived from the relationship between H2CO3 and POM (predominantly phytoplankton) in the surface ocean (Goericke and Fry 1994).

In situ respiration rates

Respiration rates were calculated at all sites by measuring the consumption of oxygen over a 24-h period. Five initial and final replicate samples were incubated in 60-mL acid-washed Biological Oxygen Demand bottles in the dark in river water held at ambient temperatures. Bottles were agitated twice daily by gently inverting them several times to reduce aggregate formation. Oxygen concentrations were measured by Winkler Titrations (Wetzel and Likens 1991) using a Hach titrator. Dissolved oxygen consumption was determined as the rate of change between the initial and final replicates over the incubation period.

Bacterial abundance measurements

Bacterial abundance measurements were made by epifluorescence microscopy using 4,6-diamidino-2-phenylindole (DAPI) optical filters in 2006. Forty-milliliter samples were collected, preserved with formaldehyde to a final concentration of 2%, and analyzed within 2 to 4 months of collection. A surfactant (0.5% solution of Triton X-100 in distilled water) was added dropwise to particle-rich samples, which were then sonicated for 10 min. Next, the sample solution was stained with Acridine Orange for 3 min. Samples were then filtered using 0.22 µm black polycarbonate-membrane filters, and then stained with DAPI for 10 min. Because these samples had high sediment concentrations, this dual-stain technique was necessary to illuminate the bacterial cells against the particle-rich background for counting purposes (Schmidt et al. 1998). Between 250 mL and 5 mL of sample were used, such that 200 cells were counted in 20 fields.

Measurements of delta18O-O2 and delta18O-H2O

Stable isotopes of oxygen dissolved in water (delta18O-O2) were measured to assess the origin of O2 (Holtgrieve et al. 2010). Samples were analyzed within 3 months using a Finnigan Delta XL continuous-flow mass spectrometer (Thermo Electron Corp). Masses 32, 34, and 40 (16O : 16O, 18O : 16O, and 40Ar) were simultaneously measured (Barth et al. 2004; Holtgrieve et al. 2010). Water isotopes (delta18O-H2O), which came from a separate sample of river water, were analyzed on a Micromass Isoprime mass spectrometer. Results are given relative to Standard Mean Ocean Water in delta notation with units of per mil.


Alin, S.R., M.F.F.L. Rasera, C.I. Salimon, J.E. Richey, G.W. Holtgrieve, A.V. Krusche and A. Snidvongs. 2010. Physical controls on carbon dioxide transfer velocity and flux in low-gradient river systems and implications for regional

carbon budgets. J. Geophys. Res.-Biogeosci. 116: GO1009, doi:10.1029/2010JG001398

Aufdenkampe, A.K., J.I. Hedges, J.E. Richey, A.V. Krusche and C.A. Llerena. 2001. Sorptive fractionation of dissolved organic nitrogen and amino acids onto fine sediments within the Amazon Basin. Limnol. Oceanogr. 46: 1921�1935,


Barth, J.A., C.A. Tait, and M. Bolshaw. 2004. Automated analyses of 18O/16O ratios in dissolved oxygen from 12-mL water samples. Limnol. Oceanogr.: Methods 2: 35�41, doi:10.4319/lom.2004.2.35

Burdige, D.J., and K.G. Gardner. 1998. Molecular weight distribution of dissolved organic carbon in marine sediment pore waters. Mar. Chem. 62: 45�64, doi:10.1016/S0304-4203(98)00035-8

Clark,I., and P. Fritz. 1997. Environmental isotopes in hydrogeology. Lewis.

Cole, J.J., N.F. Caraco, G.W. Kling, and T.K. Kratz. 1994. Carbon dioxide supersaturation in the surface waters of lakes. Science 265: 1568�1570, doi:10.1126/science.265.5178.1568

Goericke, R., and B. Fry. 1994. Variations of marine plankton d13C with latitude, temperature, and dissolved CO2 in the world ocean. Glob. Biogeochem. Cycles 8: 85�90, doi:10.1029/93GB03272

Holtgrieve, G.W., D.E. Schindler, T.A. Branch and Z. Teresa A�mar. 2010. Simultaneous quantification of aquatic ecosystem metabolism and reaeration using a Bayesian statistical model of oxygen dynamics. Limnol. Oceanogr. 53:

1047�1063, doi:10.4319/lo.2010.55.3.1047

Mayorga, E. 2004. Isotopic constraints on sources and cycling of riverine dissolved inorganic carbon in the Amazon Basin. Ph.D. thesis. Univ. of Washington,

Mayorga, E., M.G. Logsdon, M.V. Ballester and J.E. Richey. 2005. Estimating cell-to-cell land surface drainage paths from digital channel networks, with an application to the Amazon basin. J. Hydrol. 315: 167�182, doi:10.1016/j.jhydrol.2005.03.023

Quay, P.D., D.O. Wilbur, J.E.Richey, J.I. Hedges, A.H. Devol and R. Victoria. 1992. Carbon cycling in the Amazon River: Implications from the 13C compositions of particles and solutes. Limnol.Oceanogr. 37: 857�871, doi:10.4319/lo.1992.37.4.0857

Schmidt, J.L., J.W. Deming, P.A. Jumars and R.G. Keil. 1998. Constancy of bacterial abundance in surficial marine sediments. Limnol. Oceanogr. 43: 976�982, doi:10.4319/lo.1998.43.5.0976

Sioli, H. 1984. The Amazon: Limnology and landscape ecology of a mighty tropical river and its basin. Kluwer Academic

Wetzel, R.G., AND G.E. Likens. 1991. Limnological analyses, 2nd ed. Springer-Verlag.

Wilde F.D. and D.B. Radtke. 2003. National field manual for the collection of water-quality data, U.S. Geological Survey.

Zeng, N., J.-H. Yoon, J.A. Marengo, A. Subramaniam, C.A. Nobre, A. Mariotti and J.D. Neelin. 2008. Causes and impacts of the 2005 Amazon drought. Environ. Res. Lett. 3:014002. , doi:10.1088/1748-9326/3/1/014002

Zhang, J., P.D. Quay and D.O. Wilbur. 1995. Carbon isotope fractionation during gas-water exchange and dissolution of CO2. Geochim. Cosmochim. Acta 59: 107�114, doi:10.1016/0016-7037(95)91550-D


NASA logo
Get Acrobat Reader