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Relative Sequestration Rate Potential (v3.1g)

SOCSPOT 3.1g helps assess long-term soil organic carbon sequestration potential, guiding land management, climate change mitigation, sustainable agriculture, and carbon offset initiatives globally.

SOCSPOT is the relative long-term (30 year) annual carbon sequestration rate that is possible under similar climate and landuse/landcover as has occurred over the most recent five years, expressed in tonnes C ha-1 yr-1. A higher value indicates a greater potential for durable storage of carbon under the same or similar conditions as have been found in recent years.

To access high-resolution data for your area(s) of interest, contact our team.

High-Level Description

SOCSPOT 3.1g is a gridded data product that captures long-term (20-30 year) relative soil organic carbon (SOC) sequestration potentials globally across rangelands and croplands. This product harmonizes well-established principles of biogeochemical cycling with emerging insights in microbial community adaptation to historical climate to project long-term potential sequestration for stable forms of SOC.

Technical Specifications

Native Resolution: 10-30m

Spatial extent: Global

Domain: Croplands and rangelands (annual and perennial grasslands, trees, shrub and scrub)

Units: tonnes C / ha / yr

  • Note: While SOCSPOT was developed as a biogeochemical model with output units of tonnes C / ha / yr, we emphasize that the use of SOCSPOT should be constrained to relative values, rather than absolute, until long-term localized validations are available.

Inputs: 30-year historical climate averages, annual vegetation cover, type, and net primary productivity, daily soil moisture, 8-day soil temperature, carbon saturation, along with soil texture, bulk density, field capacity, and pH.

Temporal projection range: 2022-2052

Algorithm Theoretical Basis

SOCSPOT 3.1g incorporates emerging insights from fields of microbial evolution and contemporary soil biogeochemistry to forecast the relative sequestration potential of stable forms of SOC (mineral-associated organic carbon, MAOC). Dynamic and static properties of soil (e.g., soil moisture, pH, temperature, texture, bulk density, and carbon content) and climate (e.g., mean annual temperature and precipitation) are used to estimate the degree of microbial assimilation and respiration of incoming carbon from above and belowground sources. SOCSPOT applies the concepts of microbial community adaptation theory (Maynard et al. 2019; Lustenhouwer et al. 2020; Geisen et al. 2020; Bradford et al., 2021, Evans, Allison, & Hawkes, 2022; Averill et al., 2023), which has shown that microbial communities adapt to their local climate regime (temperature and moisture availability). As such, microbial communities in areas with differing climatic regimes (e.g., Arid vs. Mediterranean) will exhibit distinct responses to the same contemporary weather conditions. These distinctions are captured in SOCSPOT through the development of microbial response curves that are continuous functions of historical 30-year climate averages alongside contemporary weather conditions.

Model Assumptions & Constraints

A number of assumptions and methodological choices are important to consider when using outputs of SOCSPOT3.1g.

  • While the model was built to have absolute units (tonnes C ha-1 yr-1), we emphasize that the relative SOC sequestration potentials are the intended outputs. Thus, using SOCSPOT3.1g outputs to estimate absolute carbon accrual and/or subsequent economic returns is discouraged.

  • Global crop-type identification only exists for one year (2021) and does not include distinctions beyond corn, wheat, and ‘other crop’. As such, generic crop coefficients are used for ‘other crop’, and we assume that land parcels are consistently growing the same crop.

  • While vegetation and land cover can change throughout the year, SOCSPOT models use the vegetation cover that exists most commonly within a pixel throughout a given year.

  • Forms of erosion (e.g., fluvial, eolian, surficial, mass movement) are not accounted for in the model framework

Known Issues

  • Within-year crop rotations and/or interspersed multi-cropping systems are modeled as a single crop due to constraints on satellite identification of such land parcels and limited understanding of carbon cycling within such systems.

What’s New?

With the introduction of SOCSPOT 3.1g, we add:

  • Global coverage of relative sequestration rate potential scores.

  • A novel globally-gridded landcover dataset that reflects a fusion of multiple landcover data sources.

  • Multiple data products that were used as model inputs for SOCSPOT3.0c were changed due to constraints on availability within/outside of the Continental United States (CONUS).

  • An update to the biomass input that better resembles the interactions between land cover type, residuals, and root to shoot ratios over croplands, resulting in higher biomass values.

Data Partners, Providers, and References

  • Oregon State University : PRISM Gridded Climate Data. 30-Year Normals (1991–2020).

  • University of California, Davis : Fick, S.E., and R.J. Hijmans. 2017. WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 37(12), 4302-4315. DOI: 10.1002/joc.5086

  • SoilGrids + : Poggio, L., de Sousa, L.M., Batjes, N.H., et al. 2021. SoilGrids 2.0: Producing soil information for the globe with quantified spatial uncertainty. SOIL, 7(1), 217–240. DOI: 10.5194/soil-7-217-2021

  • NASA National Snow and Ice Data Center : O'Neill, P.E., Chan, S., Njoku, E.G., Jackson, T., & Bindlish, R. 2015. SMAP L3 Radiometer Global Daily 8 km EASE-Grid Soil Moisture. Version. Boulder, Colorado USA: NASA National Snow and Ice Data Center Distributed Active Archive Center. DOI: 10.5067/3FS28LMYXAKG

  • NASA Land Processes Distributed Active Archive Center (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Center : Wan, Z., Hook, S., & Hulley, G. 2015. MOD11A1 MODIS/Terra Land Surface Temperature/Emissivity Daily L3 Global 1km SIN Grid V006. NASA EOSDIS Land Processes DAAC. DOI: 10.5067/MODIS/MOD11A1.006

  • NCEP/NCAR + NOAA PSL (Physical Sciences Laboratory) : Kalnay, E., Kanamitsu, M., Kistler, R., et al. 1996. The NCEP/NCAR 40-Year Reanalysis Project. Bulletin of the American Meteorological Society, 77(3), 437–471. DOI: 10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

  • Pasture Watch, Land and Carbon Lab, Satelligence. 2023. Global Pasture Watch: Pasture Monitoring Platform.

Accessing Data

Contact our team to request high-resolution data for your area(s) of interest.