This data repository contains (1) yearly global autotrophic respiration (RA) dataset from 1980 to 2012 with a spatial resolution of 0.5°; (2) original field observations to develop Random Forest (RF) model; (3) main R codes to produce RA database.Model description:The globally gridded RA database was developed by Random Forest (RF) with 449 field observations (see “dataset.csv” in this repository, updated from Bond-Lamberty and Thomson, 2018) using 11 global variables, including gridded temperature, precipitation, diurnal temperature range, potential evapotranspiration, Palmer Drought Severity Index, nitrogen deposition, downward shortwave radiation, soil carbon content, soil nitrogen density, soil water content, land cover.
Dataset information:Dataset name: “Respiration_autotrophic_belowgroud_glob_1980_2012_yr_half_dgree.nc”Which means globally belowground autotrophic respiration from 1980 to 2012 with a spatial resolution of 0.5° at a yearly step.Units: g C m^-2 yr^-1Format: network Common Data Form (netCDF)Spatial coverage: 90S-90N, 180W-180EThe “dataset.csv” file is the field observation from peer review publications combining Global Soil Respiration Database (SRDB v4, Bond-Lamberty and Thomson, 2018), which is publicly available at https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1578. Besides, The database was further updated using observations collected from the China Knowledge Resource Integrated Database (www.cnki.net) up to November 2018 according to the criteria of SRDB. This dataset is provided in format of “.csv”.
R codes:10fold_CV_RA.txt: 10-fold CV for RAAnnual_variability_RA.txt: annual variability for global RACMP_RA.txt: comparing RF-RA and Hashimoto2015-RA using CMP approachRa_DD_CC_plot.txt: plotting the comparing results from CMPRA_MAT_MAP_anomaly.txt: plotting and modelling the relationship between temperature/precipitation anomalies and RA RGB_plot.txt: deriving RGB plot to detecting the relative importance of temperature, precipitation and shortwave radiation.

The netcdf file represent the global belowground autotrophic respiration from 1980 to 2012 with a resolution of half degree. The unit is g C m^-2 a^-1.
The product was produced by global published observations with the linkage of global climate, soil and other environmental variables using random forest.

The netcdf file represent the global belowground autotrophic respiration from 1980 to 2012 with a resolution of half degree. The unit is g C m^-2 a^-1.
The product was produced by global published observations with the linkage of global climate, soil and other environmental variables using random forest.

The netcdf file represent the global belowground autotrophic respiration from 1980 to 2012 with a resolution of half degree. The unit is g C m^-2 a^-1.
The product was produced by global published observations with the linkage of global climate, soil and other environmental variables using random forest.

There are two datasets in this data repository: the first one, named “RH.RF.720.360.1980.2016.Yearly.nc”, is a global heterotrophic respiration (RH) product with a spatial resolution of with 0.5 degree and a time resolution of one year. The global RH product is modelled by Random Forest algorithm with field observations and environmental variables. The environmental variables include temperature, precipitation, diurnal temperature range from CRU TS v.4.01 from 1901 to 2016; shortwave radiation; soil organic carbon content from soil grid data (Hengl et al., 2017); soil nitrogen content from ORNL DAAC; nitrogen deposition data from the Earth System Models of GISS-E2-R, CCSM-CAM3.5 and GFDL-AM3 from the 1850s to 2000s; Palmer Drought Severity Index (PDSI); and soil water content.The RH product is provided in network Common Data Form, version 4 (netCDF-4, short name: nc) data format (https://www.unidata.ucar.edu/software/netcdf/). The RH product is named using the following regulation:"RH.modelling approaches.spatial resolution.start YYYY. end YYYY.temporal resolution.nc"“RH.RF.720.360.1980.2016.Yearly.nc” means modelled RH flux (g C m^-2 yr^-1) by Random Forest (RF) with a 0.5° spatial resolution (size 720 along longitude and 360 along latitude) from start year 1980 to end year 2016 with a yearly temporal resolution.The second file, named “dataset.xlsx”, is the field observation from peer review publications combining Global Soil Respiration Database (SRDB), (version 3, Bond-Lamberty and Thomson, 2014), which is publicly available at https://github.com/bpbond/srdb. Besides, the database was further updated using observations collected from the China Knowledge Resource Integrated Database (www.cnki.net) up to March 2018 according to the criteria of SRDB. This dataset is provided in Microsoft Excel in format of “.xlsx”.R codes to produce main results and land area (named land.area.nc, km^2) are available.

This is a global RH product with 0.5 degree based on the observations and global enviormental variables predicted by Random Forest.

There are two datasets in this data repository: the first one, named “RH.RF.720.360.1980.2016.Yearly.nc”, is a global heterotrophic respiration (RH) product with a spatial resolution of with 0.5 degree and a time resolution of one year. The global RH product is modelled by Random Forest algorithm with field observations and environmental variables. The environmental variables include temperature, precipitation, diurnal temperature range from CRU TS v.4.01 from 1901 to 2016; shortwave radiation; soil organic carbon content from soil grid data (Hengl et al., 2017); soil nitrogen content from ORNL DAAC; nitrogen deposition data from the Earth System Models of GISS-E2-R, CCSM-CAM3.5 and GFDL-AM3 from the 1850s to 2000s; Palmer Drought Severity Index (PDSI); and soil water content.The RH product is provided in network Common Data Form, version 4 (netCDF-4, short name: nc) data format (https://www.unidata.ucar.edu/software/netcdf/). The RH product is named using the following regulation:"RH.modelling approaches.spatial resolution.start YYYY. end YYYY.temporal resolution.nc"“RH.RF.720.360.1980.2016.Yearly.nc” means modelled RH flux by Random Forest (RF) with a 0.5° spatial resolution (size 720 along longitude and 360 along latitude) from start year 1980 to end year 2016 with a yearly temporal resolution.The second file, named “dataset.xlsx”, is the field observation from peer review publications combining Global Soil Respiration Database (SRDB), (version 3, Bond-Lamberty and Thomson, 2014), which is publicly available at https://github.com/bpbond/srdb. Besides, The database was further updated using observations collected from the China Knowledge Resource Integrated Database (www.cnki.net) up to March 2018 according to the criteria of SRDB. This dataset is provided in Microsoft Excel in format of “.xlsx”.

There are two datasets in this data repository: the first one, named “RH.RF.720.360.1980.2016.Yearly.nc”, is a global heterotrophic respiration (RH) product with a spatial resolution of with 0.5 degree and a time resolution of one year. The global RH product is modelled by Random Forest algorithm with field observations and environmental variables. The environmental variables include temperature, precipitation, diurnal temperature range from CRU TS v.4.01 from 1901 to 2016; shortwave radiation; soil organic carbon content from soil grid data (Hengl et al., 2017); soil nitrogen content from ORNL DAAC; nitrogen deposition data from the Earth System Models of GISS-E2-R, CCSM-CAM3.5 and GFDL-AM3 from the 1850s to 2000s; Palmer Drought Severity Index (PDSI); and soil water content.The RH product is provided in network Common Data Form, version 4 (netCDF-4, short name: nc) data format (https://www.unidata.ucar.edu/software/netcdf/). The RH product is named using the following regulation:"RH.modelling approaches.spatial resolution.start YYYY. end YYYY.temporal resolution.nc"“RH.RF.720.360.1980.2016.Yearly.nc” means modelled RH flux by Random Forest (RF) with a 0.5° spatial resolution (size 720 along longitude and 360 along latitude) from start year 1980 to end year 2016 with a yearly temporal resolution.The second file, named “dataset.xlsx”, is the field observation from peer review publications combining Global Soil Respiration Database (SRDB), (version 3, Bond-Lamberty and Thomson, 2014), which is publicly available at https://github.com/bpbond/srdb. Besides, The database was further updated using observations collected from the China Knowledge Resource Integrated Database (www.cnki.net) up to March 2018 according to the criteria of SRDB. This dataset is provided in Microsoft Excel in format of “.xlsx”.

The netcdf file represent the global belowground autotrophic respiration from 1980 to 2012 with a resolution of half degree. The unit is g C m^-2 a^-1.
The product was produced by global published observations with the linkage of global climate, soil and other environmental variables using random forest.

This data repository contains (1) yearly global autotrophic respiration (RA) dataset from 1980 to 2012 with a spatial resolution of 0.5°; (2) original field observations to develop Random Forest (RF) model; (3) main R codes to produce RA database.Model description:The globally gridded RA database was developed by Random Forest (RF) with 449 field observations (see “dataset.csv” in this repository, updated from Bond-Lamberty and Thomson, 2018) using 11 global variables, including gridded temperature, precipitation, diurnal temperature range, potential evapotranspiration, Palmer Drought Severity Index, nitrogen deposition, downward shortwave radiation, soil carbon content, soil nitrogen density, soil water content, land cover.
Dataset information:Dataset name: “Respiration_autotrophic_belowgroud_glob_1980_2012_yr_half_dgree.nc”Which means globally belowground autotrophic respiration from 1980 to 2012 with a spatial resolution of 0.5° at a yearly step.Units: g C m^-2 yr^-1Format: network Common Data Form (netCDF)Spatial coverage: 90S-90N, 180W-180EThe “dataset.csv” file is the field observation from peer review publications combining Global Soil Respiration Database (SRDB v4, Bond-Lamberty and Thomson, 2018), which is publicly available at https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1578. Besides, The database was further updated using observations collected from the China Knowledge Resource Integrated Database (www.cnki.net) up to November 2018 according to the criteria of SRDB. This dataset is provided in format of “.csv”.
R codes:10fold_CV_RA.txt: 10-fold CV for RAAnnual_variability_RA.txt: annual variability for global RACMP_RA.txt: comparing RF-RA and Hashimoto2015-RA using CMP approachRa_DD_CC_plot.txt: plotting the comparing results from CMPRA_MAT_MAP_anomaly.txt: plotting and modelling the relationship between temperature/precipitation anomalies and RA RGB_plot.txt: deriving RGB plot to detecting the relative importance of temperature, precipitation and shortwave radiation.