Site-specific biogeochemical response to livestock grazing and climate change differs across four continents
Data files
Nov 19, 2025 version files 166.73 MB
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africaprcp.csv
5.27 MB
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africatemp.csv
8.92 MB
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asiaprcp.csv
5.25 MB
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asiatemp.csv
9.08 MB
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cn.csv
25.79 MB
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flux.csv
1.46 MB
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Initial_Model_Runs.zip
1.22 MB
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naprcp.csv
5.54 MB
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natemp.csv
9.34 MB
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npp.csv
13.71 MB
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README.md
16.23 KB
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saprcp.csv
5.09 MB
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satemp.csv
7.63 MB
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Simulation_Runs.zip
68.37 MB
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soc.csv
38.98 KB
Abstract
Drylands make up 40% of terrestrial ecosystems and hold up to 20% of the global soil organic carbon pool. Most semi-arid drylands are, to some extent, grazed by livestock. However, the impact of livestock grazing on carbon cycle dynamics over large spatial and temporal scales remains uncertain, especially as the effects of climate change become more pronounced. Thus far, there has been little work, which has explored how site-specific land management may interact with localized shifts in climate to affect biogeochemical processes in dryland ecosystems globally, particularly in the tropics. We explored, using simulation modeling, how grazing intensity and projected climate change may impact biogeochemical dynamics in dryland regions in North America, South America, Asia, and Africa. Our simulation results showed a site-specific biogeochemical response to livestock grazing and climate change, even across ecologically similar dryland systems. In sites that had smaller projected shifts in climate (i.e., North and South America), heavy grazing decreased soil carbon inputs, outputs, and storage. In the other two sites, particularly in the African site, shifts in climate had the largest impact on simulated biogeochemical processes, with a projected 20% decrease in the soil organic carbon pool in the African site by the end of the century. Our study highlights the importance of considering how localized shifts in climate may affect dryland ecosystem function as this may overwhelm land management effects over longer time scales. Our work also suggests that more research is needed to better understand how small-scale, site-specific sensitivity to climate change and land use may influence dryland carbon cycle dynamics at the global scale, particularly in tropical regions.
Simulation model files for DAYCENT for four dryland sites located in North America, South America, Asia, and Africa. Files in Initial Model Runs used observed data for the model to reach equilibrium and are the base input files used for further simulations. Files in Simulation Runs were the simulations through the end of the century, altering grazing intensity and SSP scenario. Climate data (precipitation and temperature datasheets) were compiled using observed historical data from nearby weather stations and downscaled CMIP6 climate data for three SSP scenarios provided by Predictia Solutions. Simulated soil organic carbon and nitrogen, net primary productivity, and greenhouse gas fluxes are model output from DAYCENT.
Description of the data and file structure
africaprcp.csv
-ssp: shared socio-economic pathway representing downscaled output from 3 climate models from CMIP6 (observed, 1-2.6, 2-4.5, 5-8.5)
-yr: year (1950 - 2100)
-dayofyr: day of year (1-365/366)
-prcp: precipitation (centimeters)
africatemp.csv
-ssp: shared socio-economic pathway representing downscaled output from 3 climate models from CMIP6 (observed, 1-2.6, 2-4.5, 5-8.5)
-yr: year (1950-2100)
-dayofyr: day of year (1-365/366)
-tmax: maximum daily temperature (degrees celsius)
-tmin: minimum daily temperature (degrees celsius)
asiaprcp.csv
-ssp: shared socio-economic pathway representing downscaled output from 3 climate models from CMIP6 (observed, 1-2.6, 2-4.5, 5-8.5)
-yr: year (1950 - 2100)
-dayofyr: day of year (1-365/366)
-prcp: precipitation (centimeters)
asiatemp.csv
-ssp: shared socio-economic pathway representing downscaled output from 3 climate models from CMIP6 (observed, 1-2.6, 2-4.5, 5-8.5)
-yr: year (1950-2100)
-dayofyr: day of year (1-365/366)
-tmax: maximum daily temperature (degrees celsius)
-tmin: minimum daily temperature (degrees celsius)
cn.csv:
-time: year (1, 1901 - 2100)
-site: site name (Shortgrass Steppe is North America, Pilcaniyeu is South America, Inner Mongolia is Asia, and Mpala is Africa)
-graz: grazing intensity (heavy, moderate, or light)
-ssp: shared socio-economic pathway representing downscaled output from 3 climate models from CMIP6 (1-2.6, 2-4.5, 5-8.5)
-soc: simulated total soil organic carbon to 20 centimeters depth (grams carbon meter-2)
-fast_c: simulated fast soil organic carbon fraction to 20 centimeters depth (grams carbon meter-2)
-int_c: simulated intermediate soil organic carbon fraction to 20 centimeters depth (grams carbon meter-2)
-slow_c: simulated slow soil organic carbon fraction to 20 centimeters depth (grams carbon meter-2)
-son: simulated total soil organic nitrogen to 20 centimeters depth (grams nitrogen meter-2)
-fast_n: simulated fast soil organic nitrogen fraction to 20 centimeters depth (grams nitrogen meter-2)
-int_n: simulated intermediate soil organic nitrogen fraction to 20 centimeters depth (grams nitrogen meter-2)
-slow_n: simulated slow soil organic nitrogen fraction to 20 centimeters depth (grams nitrogen meter-2)
flux.csv:
-site: site name (Shortgrass Steppe is North America, Pilcaniyeu is South America, Inner Mongolia is Asia, and Mpala is Africa)
-ssp: shared socio-economic pathway representing downscaled output from 3 climate models from CMIP6 (1-2.6, 2-4.5, 5-8.5)
-graz: grazing intensity (heavy, moderate, or light)
-time: year (1901 - 2100)
-co2ann: annual heterotrophic carbon dioxide respiration flux (grams carbon hectare-1 year-1)
-ch4ann: annual methane oxidation flux (grams carbon hectare-1 year-1)
-n2oann: annual nitrous oxide flux (grams nitrogen hectare-1 year-1)
naprcp.csv:
-ssp: shared socio-economic pathway representing downscaled output from 3 climate models from CMIP6 (observed, 1-2.6, 2-4.5, 5-8.5)
-yr: year (1950 - 2100)
-dayofyr: day of year (1-365/366)
-prcp: precipitation (centimeters)
natemp.csv:
-ssp: shared socio-economic pathway representing downscaled output from 3 climate models from CMIP6 (observed, 1-2.6, 2-4.5, 5-8.5)
-yr: year (1950-2100)
-dayofyr: day of year (1-365/366)
-tmax: maximum daily temperature (degrees celsius)
-tmin: minimum daily temperature (degrees celsius)
npp.csv:
-time: year and month (1 - 1911, 1912.xx - 2100.xx; each decimal increment represents a month of the year starting with .00 which represents January)
-site: site name (Shortgrass Steppe is North America, Pilcaniyeu is South America, Inner Mongolia is Asia, and Mpala is Africa)
-graz: grazing intensity (heavy, moderate, or light)
-ssp: shared socio-economic pathway representing downscaled output from 3 climate models from CMIP6 (1-2.6, 2-4.5, 5-8.5)
-agcacc: growing season accumulator for aboveground carbon production (grams carbon meter-2 year-1)
-bgjcacc: growing season accumulator for juvenile fine root carbon production (grams carbon meter-2 year-1)
-bgmcacc: growing season accumulator for mature fine root carbon production (grams carbon meter-2 year-1) \
saprcp.csv:
-ssp: shared socio-economic pathway representing downscaled output from 3 climate models from CMIP6 (observed, 1-2.6, 2-4.5, 5-8.5)
-yr: year (1950 - 2100)
-dayofyr: day of year (1-365/366)
-prcp: precipitation (centimeters)
satemp.csv:
-ssp: shared socio-economic pathway representing downscaled output from 3 climate models from CMIP6 (observed, 1-2.6, 2-4.5, 5-8.5)
-yr: year (1950-2100)
-dayofyr: day of year (1-365/366)
-tmax: maximum daily temperature (degrees celsius)
-tmin: minimum daily temperature (degrees celsius)
soc.csv:
-site: site name (Shortgrass Steppe is North America, Pilcaniyeu is South America, Inner Mongolia is Asia, and Mpala is Africa)
-graz: grazing intensity (heavy, moderate, or light)
-ssp: shared socio-economic pathway representing downscaled output from 3 climate models from CMIP6 (1-2.6, 2-4.5, 5-8.5)
-soc_1901: simulated total soil organic carbon to 20 centimeters depth in 1901 (grams carbon meter-2)
-fast_1901: simulated fast soil organic carbon fraction to 20 centimeters depth in 1901 (grams carbon meter-2)
-int_1901: simulated intermediate soil organic carbon fraction to 20 centimeters depth in 1901 (grams carbon meter-2)
-slow_1901: simulated slow soil organic carbon fraction to 20 centimeters depth in 1901 (grams carbon meter-2)
-soc_1951: simulated total soil organic carbon to 20 centimeters depth in 1951 (grams carbon meter-2)
-fast_1951: simulated fast soil organic carbon fraction to 20 centimeters depth in 1951 (grams carbon meter-2)
-int_1951: simulated intermediate soil organic carbon fraction to 20 centimeters depth in 1951 (grams carbon meter-2)
-slow_1951: simulated slow soil organic carbon fraction to 20 centimeters depth in 1951 (grams carbon meter-2)
-soc_2000: simulated total soil organic carbon to 20 centimeters depth in 2000 (grams carbon meter-2)
-fast_2000: simulated fast soil organic carbon fraction to 20 centimeters depth in 2000 (grams carbon meter-2)
-int_2000: simulated intermediate soil organic carbon fraction to 20 centimeters depth in 2000 (grams carbon meter-2)
-slow_2000: simulated slow soil organic carbon fraction to 20 centimeters depth in 2000 (grams carbon meter-2)
-soc_2050: simulated total soil organic carbon to 20 centimeters depth in 2050 (grams carbon meter-2)
-fast_2050: simulated fast soil organic carbon fraction to 20 centimeters depth in 2050 (grams carbon meter-2)
-int_2050: simulated intermediate soil organic carbon fraction to 20 centimeters depth in 2050 (grams carbon meter-2)
-slow_2050: simulated slow soil organic carbon fraction to 20 centimeters depth in 2050 (grams carbon meter-2)
-soc_2100: simulated total soil organic carbon to 20 centimeters depth in 2100 (grams carbon meter-2)
-fast_2100: simulated fast soil organic carbon fraction to 20 centimeters depth in 2100 (grams carbon meter-2)
-int_2100: simulated intermediate soil organic carbon fraction to 20 centimeters depth in 2100 (grams carbon meter-2)
-slow_2100: simulated slow soil organic carbon fraction to 20 centimeters depth in 2100 (grams carbon meter-2)
-dsoc_200: change in simulated total soil organic carbon from 1901-2100 (grams carbon meter-2)
-dfast_200: change in simulated fast soil organic carbon fraction from 1901-2100 (grams carbon meter-2)
-dint_200: change in simulated intermediate soil organic carbon fraction from 1901-2100 (grams carbon meter-2)
-dslow_200: change in simulated slow soil organic carbon fraction from 1901-2100 (grams carbon meter-2)
-dsoc_150: change in simulated total soil organic carbon from 1951-2100 (grams carbon meter-2)
-dfast_150: change in simulated fast soil organic carbon fraction from 1951-2100 (grams carbon meter-2)
-dint_150: change in simulated intermediate soil organic carbon fraction from 1951-2100 (grams carbon meter-2)
-dslow_150: change in simulated slow soil organic carbon fraction from 1951-2100 (grams carbon meter-2)
-dsoc_100: change in simulated total soil organic carbon from 2000-2100 (grams carbon meter-2)
-dfast_100: change in simulated fast soil organic carbon fraction from 2000-2100 (grams carbon meter-2)
-dint_100: change in simulated intermediate soil organic carbon fraction from 2000-2100 (grams carbon meter-2)
-dslow_100: change in simulated slow soil organic carbon fraction from 2000-2100 (grams carbon meter-2)
-dsoc_50: change in simulated total soil organic carbon from 2050-2100 (grams carbon meter-2)
-dfast_50: change in simulated fast soil organic carbon fraction from 2050-2100 (grams carbon meter-2)
-dint_50: change in simulated intermediate soil organic carbon fraction from 2050-2100 (grams carbon meter-2)
-dslow_50: change in simulated slow soil organic carbon fraction from 2050-2100 (grams carbon meter-2)
Initial_Model_Runs.zip:
Site Name (Africa, Asia, North America, South America) Initial:
-crop.100: input file to parameterize vegetation dynamics within the model. Specific descriptions of each parameter can be found in crop.def.
-crop.def: File used to describe the measurement and units for a given parameter within crop.100.
-cult.100: input file to parameterize the effect of a cultivation event within the model. Specific descriptions of each parameter can be found in cult.def
-cult.def: File used to describe the measurement and units for a given parameter within cult.100.
-fix.100: input file of fixed parameters that control core pool and flow rates within the model. Specific descriptions of each parameter can be found in fix.def.
-fix.def: File used to describe the measurement and units for a given parameter within fix.100.
-graz.100: input file to parameterize the effect of a grazing event within the model. Specific descriptions of each parameter can be found in graz.def.
-graz.def: File used to describe the measurement and units for a given parameter within graz.100.
-site.100 (i.e., sgs.100 for North America, pilc.100 for South America, im.100 for Asia, mpala.100 for Africa): input file of site-specific characteristics and initial pool amounts within the model. Name before the .100 refers to the site name for each continent. Specific descriptions of each parameter can be found in site.def.
-site.def: File used to describe the measurement and units for a given parameter within site.100.
-site.sch (i.e., sgs.sch for North America, pilc.sch for South America, im.sch for Asia, and mpala.sch for Africa): input file used to establish simulation time and schedule events to occur during the simulation. Name before the .sch refers to the site name for each continent.
-site.wth (i.e., sgs.wth for North America, pilc.wth for South America, im.wth for Asia, mpala.wth for Africa): input file of daily precipitation, minimum temperature, and maximum temperature. Name before the .wth refers to the site name for each continent. -outfiles.in: input file that lists which .out and .csv output files to generate from the simulation. 1 generates the file, 0 does not.
-outvars.txt: input file that lists specific output variables to generate from simulation. -sitepar.in: input file of DAYCENT specific parameters to adjust using site-specific characteristics.
-soils.in: input file to parameterize soil mineralogic and hydrologic characteristics within the model. -tree.100: input file to parameterize tree characteristics if present at site.
Simulation_Runs.zip:
Site Name (Africa, Asia, North America, South America)
- grazingintensityssp: Name of folder represents the simulated grazing intensity (hg: heavy grazing, mg: moderate grazing, lg: light grazing) and shared socio-economic pathway scenario (126: SSP1-2.6, 245: SSP2-4.5, 585: SSP5-8.5)
- grazingintensityssprep: Name of folder represents the simulated grazing intensity (HG: heavy grazing, MG: moderate grazing, LG: light grazing) and shared socio-economic pathway scenario (2.6: SSP1-2.6, 4.5: SSP2-4.5, 8.5: SSP5-8.5) and global circulation model used for
weather simulation (1,2,3)
-crop.100: input file to parameterize vegetation dynamics within the model. Specific descriptions of each parameter can be found in crop.def.
-crop.def: File used to describe the measurement and units for a given parameter within crop.100.
-cult.100: input file to parameterize the effect of a cultivation event within the model. Specific descriptions of each parameter can be found in cult.def.
-cult.def: File used to describe the measurement and units for a given parameter within cult.100
-fix.100: input file of fixed parameters that control core pool and flow rates within the model. Specific descriptions of each parameter can be found in fix.def.
-fix.def: File used to describe the measurement and units for a given parameter within fix.100.
-graz.100: input file to parameterize the effect of a grazing event within the model. Specific descriptions of each parameter can be found in graz.def.
-graz.def: File used to describe the measurement and units for a given parameter within graz.100.
-site.100 (i.e., sgs.100 for North America, pilc.100 for South America, im.100 for Asia, mpala.100 for Africa): input file of site-specific characteristics and initial pool amounts within the model. Specific descriptions of each parameter can be found in site.def.
Name before the .100 refers to the site name for each continent. -site.def: File used to describe the measurement and units for a given parameter within site.100.
-site.sch (i.e., sgs.sch for North America, pilc.sch for South America, im.sch for Asia, mpala.sch for Africa): input file used to establish simulation time and schedule events to occur during the simulation. Name before the .sch refers to the site name for each continent.
-site.wth (i.e., sgs.wth for North America, pilc.wth for South America, im.wth for Asia, mpala.wth for Africa): input file of daily precipitation, minimum temperature, and maximum temperature. Name before the .wth refers to the site name for each continent.
-sitessp.wth (e.g., sgs2.61.wth for North America SSP1-2.6, GCM 1, pilc2.61.wth for South America SSP1-2.6, GCM 1, im2.61.wth for Asia SSP1-2.6, GCM 1, mpala2.61.wth for Africa SSP1-2.6, GCM 1): input file of projected daily precipitation, minimum temperature, and maximum temperature for a given shared socioeconomic pathway scenario. Naming scheme (before. wth) represents name of the site on a given continent, SSP scenario (2.6 for 1-2.6, 4.5 for 2-4.5, and 8.5 for 5-8.5), and GCM (1, 2, or 3).
-outfiles.in: input file that lists which .out and .csv output files to generate from the simulation. 1 generates the file, 0 does not.
-outvars.txt: input file that lists specific output variables to generate from simulation.
-sitepar.in: input file of DAYCENT specific parameters to adjust using site-specific characteristics.
-soils.in: input file to parameterize soil mineralogic and hydrologic characteristics within the model.
-tree.100: input file to parameterize tree characteristics if present at site.
Code/Software
daycentfigsandtables.R:
- used to make the primary tables and figures for the manuscript and appendix figures\
- Completed in R (version 4.4.2)
- Packages: 'ggplot2', 'wesanderson', 'stringr', 'zoo', 'tidyverse', 'scales', 'ggpubr', 'cowplot', 'gt', 'climatol', 'TRAMPR', 'lubridate'
Simulation model files for DAYCENT for four dryland sites located in North America, South America, Asia, and Africa. Files in ‘Initial Model Runs’ used observed data for the model to reach equilibrium and are the base input files used for further simulations. Files in ‘Simulation Runs’ were the simulations through the end of the century, altering grazing intensity and SSP scenario. Climate data (precipitation and temperature datasheets) were compiled using observed historical data from nearby weather stations and downscaled CMIP6 climate data for three SSP scenarios provided by Predictia Solutions. Simulated soil organic carbon and nitrogen, net primary productivity, and greenhouse gas fluxes are model output from DAYCENT.
