Soil Respiration Maps for the ABoVE Domain, 2016-2017

Description

This dataset provides gridded estimates of carbon dioxide (CO2) emissions from soil respiration occurring within permafrost-affected tundra and boreal ecosystems of Alaska and Northwest Canada at a 300 m spatial resolution for the period 2016-08-18 to 2018-09-12. The estimates include monthly average CO2 flux (gCO2 C m-2 d-1), daily average CO2 flux and error estimates by season (Autumn, Winter, Spring, Summer), estimates of annual offset of CO2 uptake (i.e., vegetation GPP), annual budgets of vegetation gross primary productivity (GPP; gCO2 C m-2 yr-1), and the fraction of open (non-vegetated) water within each 300 m grid cell. Belowground sources of respiration (i.e., root and microbial) are included. The gridded soil CO2 estimates were obtained using seasonal Random Forest models, information from remote sensing, and a new compilation of in-situ soil CO2 flux from Soil Respiration Stations and eddy covariance towers. The flux tower data are provided along with daily gap-filled flux observations for each Soil Respiration station forced diffusion (FD) chamber record. The data cover the NASA ABoVE Domain.

Resources

Name Format Description Link
The dataset's project home page HTML ABoVE project site Open resource
Download this dataset HTML This link allows direct data access via Earthdata login Open resource
Get a related visualization PNG Seasonal average soil respiration emissions (gCO2 C m-2 d-1) for autumn (September-October), winter (November-March), spring (April-May), and summer (June-August ) at a 300 m spatial resolution. Source: Watts et al. (2021) Open resource
View documentation related to this dataset HTML ORNL DAAC Data Set Documentation Open resource
View documentation related to this dataset PDF Soil Respiration Maps for the ABoVE Domain, 2016-2017: ABoVE_Soil_Respiration_Maps.pdf Open resource
This dataset's landing page HTML Data set Landing Page DOI URL Open resource
Google Scholar search results HTML Search results for publications that cite this dataset by its DOI. Open resource

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