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A Global Database of Soil Respiration Data, Version 2.0
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Please note that this version was superseded by Version 3 on 2014/07/24.

Follow this link to the latest version:

Bond-Lamberty, B.P. and A.M. Thomson. 2014. A Global Database of Soil Respiration Data, Version 3.0. Data set. Available on-line [] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, USA

Contact ORNL DAAC User Services ( if you need additional assistance.


This data set provides an updated soil respiration database (SRDB), a near-universal compendium of published soil respiration (RS) data. Soil respiration, the flux of autotrophically- and heterotrophically-generated CO2 from the soil to the atmosphere remains the least well-constrained component of the terrestrial C cycle. The database encompasses all published studies that report at least one of the following data measured in the field (not laboratory): annual RS, mean seasonal RS, a seasonal or annual partitioning of RS into its sources fluxes, RS temperature response (Q10), or RS at 10 degrees C. SRDB's orientation is thus to seasonal and annual fluxes, not shorter-term or chamber-specific measurements, and the database is dominated by temperate, well-drained forest measurement locations. The database includes a file of RS data and a linked file of study bibliographic data. Both files are in comma-separated format.


Figure 1. Location of SRDB database observations (dots), by ecosystem type. A Google Earth data layer (kmz) is included with this data set as a companion file for easy geographic visualization of the included studies.

A Community Database of Soil Respiration Data

The compilers of the SRDB database (Bond-Lamberty and Thomson, 2010) make it available to the scientific community both as a traditional static archive (ORNL DAAC) and as a dynamic community database that will be updated over time by interested users. 

The dynamic version of the database is hosted on Google Code: This site uses version control software (Subversion,, so that researchers can use (check out) current as well as previous versions of the database. It also features online wiki documentation, a mailing list, and other aspects typical of any open source project. Both archives include the database itself, metadata, and usage notes. Initially the two repositories will hold identical copies, but we anticipate that the dynamic version will expand and change with time. Instructions for making a contribution are listed on the Google Code site. For this reason we recommend that citations to this database always include a version number and download date.

The ORNL DAAC released Version 1.0 in 2010, Version 2.0 in 2012, and will update the database on an annual basis to incorporate changes and additions submitted by the RS community via the Google Code site and by Bond-Lamberty and Thomson. Transaction logs for the SRDB-data and SRDB-study files will be maintained.

ORNL DAAC Version Record

SRDB Version ORNL DAAC Release Date Studies Included Records Date Range Date Superseded
Version 2.0 2012/03/01 1,021 4,387 1961-2009 2014/07/24
Version 1.0 2010/04/30 818 3,379 1961-2007 2012/03/01

Version 2.0: Data from 1,021 studies have been entered into the database, constituting 4,387 records. The data span the measurement years 1961-2009 and are dominated by temperate, well-drained forests. The source for version 2.0 is srdb_20110524a from the Google Code website.

Version 1.0: Data from 818 studies have been entered into the database, constituting 3,379 records. The data span the measurement years 1961-2007 and are dominated by temperate, well-drained forests. Note that the Version 1.0 database is no longer available online at the ORNL DAAC. For access to this database, please contact the DAAC as indicated in Section 6 of this document.

Data Citation:

Cite this data set as follows:

Bond-Lamberty, B.P. and A.M. Thomson. 2012. A Global Database of Soil Respiration Data, Version 2.0. Data set. Available on-line [] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A.

Table of Contents:

1. Data Set Overview:

Project: Soil Collections

The investigators are Bond-Lamberty, B. and Thomson, A.M. 

The SRDB was designed to capture and make available for analysis the large number of RS studies published over the last four decades. It will also be one of the first such databases in the earth sciences to leverage open-source software technologies, resulting in a dynamic, shared, and more powerful data resource for interested users. The science community will determine any future changes that may be necessary as well as the uses to which these data will be put. A Google Earth data layer (kmz) is included with the database for easy geographic visualization of the included studies.

Related Data Set:

Raich, J. W., and W. H. Schlesinger. 2001. Global Annual Soil Respiration Data (Raich and Schlesinger 1992). Data set. Available on-line [] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A. doi:10.3334/ORNLDAAC/622

Companion Files:

2. Data Characteristics:

The main data file "global_srdb-data_v2.csv" is a comma-separated file of all the soil respiration data; column names appear in the first row. 

Bibliographic information for the studies that appear in the main data file can be found in the "global_srdb-studies_v2.csv" file;  column names are in the first row and values are comma-separated.

Data file index:  The assigned four-digit study number is common to both files and indexes the srdb-studies to srdb-data. 

Missing values:  In both files, if a value (numeric or text) is missing for a study, that field is left blank.

File Description: global_srdb-data_v2.csv

Column Number Column Name Column Description and Units
1Record_number Record number
2Entry_date Entry date
3Study_number Study number; index into the studies database
4Author Name of first author
5Duplicate_record Is record a known duplicate? (Study number)
6Quality_flag Quality control.

Quality control flags include:

V0  default, no qualification (blank cell)
V01  estimated from figure
V02  data from another study
V03  data estimated--other
V04  potentially useful future data
V10  potential problem with data
V11  suspected problem with data
V12  known problem with data
V13  duplicate?
V14  inconsistency
Further details can generally be found in the notes field (#105 below)
7Contributor Data contributor
8Country Country
9Region State/province/region
10Site_name Name of study site
11Study_midyear Year study was performed (middle year if multiple years)
12YearsOfData Years of data; always _1
13Latitude Latitude, decimal; positive=north, negative=south
14Longitude Longitude, decimal; positive=east, negative=west
15Elevation Elevation, m
16Manipulation Manipulation performed (CO2, fertilization, etc.)
17Manipulation_level Degree of manipulation performed
18Age_ecosystem Time since ecosystem established, years. This is used when, e.g., the time of conversion of forest to agriculture is known
19Age_disturbance Time since disturbance, years
20Species Dominant species
21Biome Biome (boreal, temperate, etc). Subjective
22Ecosystem_type Ecosystem type (grassland, forest, etc). Subjective
23Ecosystem_state Ecosystem state (managed, unmanaged, natural). Subjective. Unmanaged means human management or disturbance in the past, but not currently.
24Leaf_habit Dominant leaf habit (deciduous, evergreen)
25Stage Developmental stage (aggrading, mature). Subjective
26Soil_type Soil description (classification and texture)
27Soil_drainage Soil drainage (dry, wet). Subjective. Dry means well-drained uplands; wet peatlands, swamps, etc.
28Soil_BD Soil bulk density, g cm-3
29Soil_CN Soil C:N ratio
30Soil_sandsiltclay Soil sand:silt:clay ratio
31MAT Reported mean annual temperature, C
32 MAP Reported mean annual precipitation, mm
33 PET Reported potential evapotranspiration, mm
34 Study_temp Annual temperature in year of study, C
35Study_precip Annual precipitation in year study of study, mm
36CO2_method CO2 measurement method
37Partition_method Method used to partition RS source fluxes, following Bond-Lamberty et al. (2004)
38 Rs_annual Annual C flux from soil respiration, g C m-2. This can either be reported directly by the study, calculated from reported mean fluxes, or estimated from a figure (in which case a quality control note is made, field 6)
39 Rs_annual_err Error (typically plot-to-plot) for Rs_annual, g C m-2
40 Rs_interann_err Interannual error reported for Rs_annual, g C m-2. This is occasionally reported by authors, or defined as the standard deviation between year iand year i+1 (N=2)
41 Rs_max Maximum RS flux, µmol m-2 s-1
42Rs_maxday Maximum RS flux day of year
43Rs_min Minimum RS flux, µmol m-2 s-1
44Rs_minday Minimum RS flux day of year
45Rlitter_annual Annual RS flux from litter, g C m-2
46Ra_annual Annual autotrophic RS flux, g C m-2
47Rh_annual Annual heterotrophic RS flux, g C m-2
48RC_annual Root contribution to Rs_annual, annual fraction
49Rs_spring Mean spring RS flux, µmol m-2 s-1. Seasons are defined by authors
50Rs_summer Mean summer RS flux, µmol m-2 s-1
51Rs_autumn Mean autumn RS flux, µmol m-2 s-1
52Rs_winter Mean winter RS flux, µmol m-2 s-1
53Rs_growing Mean growing RS flux, µmol m-2 s-1
54Rs_wet Mean wet season RS flux, µmol m-2 s-1
55Rs_dry Mean dry season RS flux, µmol m-2 s-1
56RC_seasonal Root contribution to seasonal RS, fraction
57RC_season Season of RC_seasonal
58Model_type Type of temperature-response model used
59Temp_effect Temperature effect on RS (none, positive, negative)
60Model_output_units Temperature-response model output units
61Model_temp_range Soil temperature range over which model fitted
62Model_N Model N
63Model_R2 Model r-squared
64T_depth Depth at which soil temperature recorded, cm. A value of -200 (i.e., 2 m above ground) is used for air temperature
65Model_paramA Model parameter A
66Model_paramB Model parameter B
67Model_paramC Model parameter C
68Model_paramD Model parameter D
69Model_paramE Model parameter E
70WC_effect Soil water effect on RS
71R10 RS at 10 C, µmol m-2 s-1
72Q10_0_10 Q10 temperature response, 0-10 C .Q10 values are either reported by authors, calculated from reported RS-temperature regressions, or occasionally estimated from figures (in which case a quality control note is made, field 6)
73Q10_5_15 Q10 temperature response, 5-15 C
74Q10_10_20 Q10 temperature response, 10-20 C
75Q10_0_20 Q10 temperature response, 0-20 C
76Q10_other1 Q10 temperature response, other temp range
77Q10_other1_range Temperature range of Q10_other1, C
78Q10_other2 Q10 temperature response, other temp range
79Q10_other2_range Temperature range of Q10_other2, C
80GPP Annual gross primary production at site, g C m-2
81ER Annual ecosystem respiration at site, g C m-2
82NEP Annual net ecosystem production at site, g C m-2
83NPP Annual net primary production at site, g C m-2
84ANPP Annual aboveground NPP at site, g C m-2
85BNPP Annual belowground NPP at site, g C m-2
86NPP_FR Annual fine root NPP at site, g C m-2
87TBCA Total belowground carbon allocation at site, g C m-2
88Litter_flux Annual aboveground litter flux, g C m-2. This is reported very inconsistently (leaf only, leaf and fine woody material, all material, etc). Generally this should not include large woody material
89Rootlitter_flux Annual belowground litter flux, g C m-2
90TotDet_flux Annual total litter flux, g C m-2. This should be the sum of Litter_fluxand Rootlitter_flux
91Ndep Annual nitrogen deposition, g N m-2
92LAI Leaf area index at site, m2 m-2. Hemispheric (one-sided) if possible
93BA Basal area at site, m2 ha-1
94C_veg_total Total carbon in vegetation, g C m-2. This should be the sum of C_AG and C_BG. For this and all "C_" fields, biomass is converted to carbon using a ratio of 0.5 unless study-specific values are available
95C_AG Total carbon in aboveground vegetation, g C m-2
96C_BG Total carbon in belowground vegetation, g C m-2
97C_CR Total carbon in coarse roots, g C m-2
98C_FR Total carbon in fine roots, g C m-2
99C_litter Total carbon in standing litter, g C m-2
100C_soil Total carbon in soil organic matter, g C m-2
101C_soildepth Depth to which soil C recorded, cm
102Notes Notes

Example Data Records:

Study_midyear,YearsOfData,Latitude,Longitude,Elevation,Manipulation,Manipulation_level, Age_ecosystem,Age_disturbance,Species,
MAT,MAP,PET,Study_temp,Study_precip,CO2_method, Partition_method,Rs_annual,Rs_spatial_err,Rs_interann_err,
Rs_autumn,Rs_winter,Rs_growingseason, Rs_wet,Rs_dry,RC_seasonal,RC_season,Model_type,Temp_effect,Model_output_units,
Model_temp_range,Model_N,Model_R2,T_depth,Model_paramA,Model_paramB,Model_paramC,Model_paramD,Model_paramE, WC_effect,

1,2008-09-26,2534,Bond-Lamberty,,Q02,BBL,Canada,Manitoba,BOREAS NSA-D1998,
2001.5,1.5,56.63,-99.94,,None,,,3,Picea mariana;
Pinus banksiana; Populus tremuloides,Boreal,Forest,Natural,Evergreen,Aggrading,Gray luvisol (Boralf),Medium,,,,
,,1.3,,,-0.05,Growing,"Arrhenius, R=a*exp(-b/c(T-d)), T in K",
0,5,5,,0,0,150,80,120,70,50,,41800,70,LAI from Bond-Lamberty (2002); C from Wang (2003) and Gower (1997)
2151,2009-06-08,3074,Ohashi,,Q01,BBL,Finland,,Koli National Park,
2003,1,63.05,29.78,,None,,,100,Picea abies;
Pinus sylvestris; Betula pendula,Boreal,Forest,Natural,Evergreen,Mature,,Dry,,
,,,,,,,,,,,,,,,,Rs estimated from figure
2008.5,1,32.18333333,118.7,,Fertilized,150 kgN/ha/yr,,,Quercus fabri;Platycarya strobilacea; Broussonetia papyrifera; Symplocos paniculata;
Lindera glauca; Lindera angustifolia; Celtis sinensis; Acer ginnala; Carex spp.; Asparagus cochinchinensis; Stellaria media,
15.5,1020,,,,Gas chromatography,,650,45,
R=a exp(b(T-c))",Positive,mg CO2/m2/hr,"6,26",,0.749,10,39.228,0.107,

File Description: global_srdb-studies_v2.csv

Field_number V1 Field_name V1 Field_description Field_name Field_description
1 Study_number Study number; used as a lookup from srdb-data Study_number Study number; used as a lookup from srdb-data
2 Authors Study authors Authors Study authors
3 Title Study title Title Study title
4 Source Study source (usually journal name) Source Study source (usually journal name)
5 Volume Volume number Volume Volume number
6 Issue Issue number Issue Issue number
7 BP Beginning page BP Beginning page
8 EP Ending page EP Ending page
9 Pub_year Publication year PubYear Publication year
10 Notes Notes Notes Notes
11 Abstract Abstract Abstract Abstract
12 Citations Citations Citations Citations
13 DE Data entry: entered into srdb-data (Y, N)?DE Data entry: entered into srdb-data (Y, N)?
14 DLD Downloaded: study acquired (Y/N)? DLD Downloaded: study acquired (Y/N)?
15 DOI Digital object identifier DOI Digital object identifier
16 nonEnglish Is study in a non-English language (Y/N)? nonEnglish Is study in a non-English language (Y/N)?
17 Rank Rank (1=highly relevant, 4=not relevant) Rank Rank (1=highly relevant, 4=not relevant)
18 Search_date Date search performed SearchDate Date search performed
19 Search_term Web of Science search term used SearchTerm Web of Science search term used

Example Data Records:


14","Maldague, M.E.; Hilger, F.","Observations fauntistique et microbiologiques dans quelques biotopes forestiers equatoriaux",
"Soil organisms (ed: Doeksen, van der Drift)","","","368","374","1963","","","","Valya","Y","Y","",

"17","Monteith","Crop photosynthesis and the flux of carbon dioxide below the canopy",
"Journal of Applied Ecology","1","","321","337","1964","","","","","Y","Y","",
"N","1","9/26/2008","R&S1992; B-L2004","","","",""

N","1","9/26/2008","Topic=(""soil co2 evolution"" not ""soil respiration"")","0012-9658","","WOS:A19668082200018",""

"5849","Lee, Na-Yeon","An evaluation of empirical regression models for predicting temporal variations in soil respiration in a cool-temperate deciduous broad-leaved forest",
"Journal of Ecology and Field Biology","33","2","","","2010","",
"Soil respiration (R-s) is a critical component of the annual carbon balance of forests, but few studies thus far have attempted to evaluate empirical regression models in R-s. The principal objectives of this study were to evaluate the relationship between R-s rates and soil temperature (ST) and soil water content (SWC) in soil from a cool-temperate deciduous broad-leaved forest, and to evaluate empirical regression models for the prediction of R-s using ST and SWC. We have been measuring R-s, using an open-flow gas-exchange system with an infrared gas analyzer during the snow-free season from 1999 to 2001 at the Takayama Forest, Japan. To evaluate the empirical regression models used for the prediction of R-s, we compared a simple exponential regression (flux=ad(bt):Eq. [1]) and two polynomial multiple-regression models (flux = ad(bt) x (theta v - c) x (d - theta v)(f): Eq. [2] and flux = ae(bt) x (1 - (1 - (theta v/c))(2)): Eq. [3]) that included two variables (ST: t and SWC: theta v) and that utilized hourly data for R-s. In general, daily mean R-s rates were positively well-correlated with ST, but no significant correlations were observed with any significant frequency between the ST and R-s rates on periods of a day based on the hourly R-s data. Eq. (2) has many more site-specific parameters than Eq. (3) and resulted in some significant underestimation. The empirical regression, Eq. (3) was best explained by temporal variations, as it provided a more unbiased fit to the data compared to Eq. (2). The Eq. (3) (ST x SWC function) also increased the predictive ability as compared to Eq. (1) (only ST exponential function), increasing the R-2 from 0.71 to 0.78.",
N","3","","Topic=(""soil respiration"" or ""soil surface co2 flux"" or ""soil co2 efflux"") AND Year Published=(2010)","1975-020X(print)|2093-4521(electronic)","","BIOSIS:PREV201100182246",""

Expanded descriptions and usage notes for a number of fields in the soil respiration data file "global_srdb-data_v2.csv"

This file contains expanded descriptions or usage notes for a number of fields in the soil respiration database.
Last updated: 29-Nov-2010

This and a number of the other 'subjective' fields (marked with an asterisk) are highly subjective. Here "natural" means unmodified by humans; "managed" means under active management; and "unmanaged" means human management or disturbance in the past, but not currently.

This is used when, e.g., the time of conversion of forest to agriculture is known. In contrast, age_disturbance records time of last disturbance in general.

See Bond-Lamberty et al. (2004) in Global Change Biology for an explanation of the categories used here.

This is reported error associated with Rs_annual. Typically spatial (plot-to-plot) but can be other sources too.

This is defined simply as the standard deviation between year i and year i+1, so n=2 always, and this field will be blank in at least one observation for each study.

Given in cm; a value of -200 (i.e., 2 m above ground) is used for air temperature.

This is reported very inconsistently--leaf only, leaf and fine woody material, all material, etc. Generally this should not include large woody material.

This should be the sum of Litter_flux and Rootlitter_flux.

This should be the sum of C_AG and C_BG. For this and all "C_" fields, biomass has been converted to carbon using a ratio of 0.5.

Rank    [ in srdb_studies.csv ]
Note this score (1-4, with 1 being "highly relevant" and 4 "not relevant") is not an assessment of the study's scientific merit or validity; it's simply a judgment, based on reading the abstract and title, of how relevant this study is to the database (i.e., is it likely to have appropriate data?).
Last updated: 2010/04/23

Site boundaries: (All latitude and longitude given in degrees and fractions)

Site (Region) Westernmost Longitude Easternmost Longitude Northernmost Latitude Southernmost Latitude Geodetic Datum
Global (point) -162.2 175.5 78.1667 -78.02 Unknown

Time period:

3. Data Application and Derivation:

This is a database compiled from published studies about soil surface CO2 flux (soil respiration) measured in the field and intended to serve as a resource for scientific analysis. 

The primary RS units used were gC/m2/yr (for annual fluxes) and ¼mol/m2/s (for mean seasonal fluxes); values were converted as necessary from those given by study authors. A variety of ancillary data were also entered when reported, including site-related and experimental data, information on ecosystem structure and function, methods used, etc.; we assumed a 12:44 ratio of C to CO2 molecular weights, and that biomass was 50% C (unless specified otherwise in the study).

4. Quality Assessment:

Data were crosschecked against a number of other RS data collections and meta-analyses (Hibbard et al., 2005; Chen and Tian, 2005; Burton et al., 2008; Sottaet al., 2004). Quality flags were assigned based on information provided in a given study and best judgment.

5. Data Acquisition Materials and Methods:

For the compilation of Version 1, investigators collected all available studies in the peer-reviewed scientific literature reporting RS measured in the field; lab incubation studies were not included. The ISI Web of Science constituted the primary source of published studies; search terms used included soil respiration, soil CO2 evolution, etc., and were conducted through the 2008 publication  year. We used each study's title and abstract to decide whether to acquire it; ~40% of the almost 4700 studies were acquired and examined. 

In version 2.0, publications from 2009, 2010 and from the first half of 2011 were included and RS data from 164 studies have been added. The Google Earth.kmz file of site locations was updated. Additionally, a number of corrections have been made. A number of Age_disturbance fields have been corrected and completed. The Partition_method field has been fixed for many records. Finally, three fields have been deleted: Chamber_method, CH4_flux, N2O_flux. These fields were inconsistent or almost never used.

Short term experiments (i.e., RS measurements made over less than 1-2 weeks) were not entered unless the study authors extrapolated their results to seasonal or annual values; the database is in general not designed to accommodate instantaneous or short-term measurements. In general we did not do additional research to find older publications that might not be listed in the Web of Science.  To qualify for inclusion, a study had to report at least one of the following data:

If at least one of these data was reported, or could be calculated with few or no assumptions, e.g., easily estimated from points in a figure, the study was entered into the database. For example, sometimes a study will show monthly soil respiration in a figure but not compute an annual flux, and so estimates were made from the figure. This was noted in a quality flag.

When it was necessary to calculate or estimate annual flux for one of the studies, these calculations and notes were recorded in an Excel spreadsheet which may be opened in MSExcel, OpenOffice, etc. File names start with the assigned four-digit study number that indexes the global_srdb-studies and global_srdb-data files. For example, "0020 WitkampEcology 1966.xlsx" and "4634 Webster JGR 2008.xlsx". These spreadsheets are provided as a companion file and have been compiled and compressed into a single file,

6. Data Access:

This data is available through the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Data Archive Center:

Contact for Data Center Access Information:
Telephone: +1 (865) 241-3952

7. References:

Bond-Lamberty, B. and A.M. Thomson. 2010. A global database of soil respiration measurements, Biogeosciences, 7, 1321-1344, doi:10.5194/bgd-7-1321-2010.

Burton, A. J., Melillo, J. M., and Frey, S. D. 2008.: Adjustment of forest ecosystem root respiration as temperature warms, Journal of Integrative Plant Biology, 50, 1467-1483, doi:10.1111/j.1744-7909.2008.00750.x.

Chen, H., and Tian, H.-Q. 2005. Does a general temperature-dependent Q(10) model of soil respiration exist at biome and global scale?, Journal of Integrative Plant Biology, 47, 1288-1302.

Hibbard, K. A., Law, B. E., and Sulzman, J. 2005. An analysis of soil respiration across northern hemisphere temperate ecosystems, Biogeochemistry, 73, 29-70, doi:10.1007/s10533-004-2946-0.

Sotta, E. D., Meir, P., Malhi, Y., Nobre, A. D., Hodnett, M., and Grace, J. 2004. Soil CO2 efflux in a tropical forest in the central Amazon, Global Change Biol., 10, 601-617, doi:10.1111/j.1529-8817.2003.00761.x.