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  3. Data release for estimating soil respiration in a subalpine landscape using point, terrain, climate and greenness data

Data release for estimating soil respiration in a subalpine landscape using point, terrain, climate and greenness data

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Citation

Berryman, E., Vanderhoof, M.K., Bradford, J., Hawbaker, T.J., Henne, P.D., Burns, S.P., Frank, J., Birdsey, R., and Ryan, M.G., 2018, Data release for estimating soil respiration in a subalpine landscape using point, terrain, climate and greenness data: U.S. Geological Survey data release, https://doi.org/10.5066/P99TRHPB.

Summary

Landscape carbon (C) flux estimates are necessary for assessing the ability of terrestrial ecosystems to buffer further increases in anthropogenic carbon dioxide (CO2) emissions. Advances in remote sensing have allowed for coarse-scale estimates of gross primary productivity (GPP) (e.g., MODIS 17), yet efforts to assess spatial patterns in respiration lag behind those of GPP. Here, we demonstrate a method to predict growing season soil respiration at a regional scale in a forested ecosystem. We related field measurements (n=144) of growing season soil respiration across subalpine forests in the Southern Rocky Mountains ecoregion to a suite of biophysical predictors with a Random Forest model (30 m pixel size). We found that Landsat [...]

Contacts

Originator :
Melanie K Vanderhoof, John Bradford, Todd J Hawbaker, Paul D Henne, Sean P Burns, John Frank, Richard Birdsey, Michael G Ryan, Erin Berryman
Metadata Contact :
Melanie K Vanderhoof
Publisher :
U.S. Geological Survey
Distributor :
U.S. Geological Survey - ScienceBase
SDC Data Owner :
Geosciences and Environmental Change Science Center
USGS Mission Area :
Land Resources

Attached Files

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Berryman_soilrespiration.xml
Original FGDC Metadata
View 		15.29 KB application/fgdc+xml
datarelease_rasters.zip 51.75 MB application/zip
SRseasonal3.csv 48.98 KB text/csv
Soil_resp_mapping_RFmodels.r 2.33 KB text/x-rsrc

Purpose

Soil respiration returns carbon dioxide back to the atmosphere and is an important part of the carbon cycle, but estimates of soil respiration across large landscapes are hard to pin down. Soil respiration is sensitive to changes in climate and vegetation, which are available as mapped data products, thanks to remote sensing and geospatial technology. We developed a statistical model that mapped soil respiration across three forests and an entire region based on climate and vegetation spatial data. While this work was limited to subalpine forests in the southern Rocky Mountains, our method can be used in other ecosystems to better understand how ecosystems interact with atmospheric carbon dioxide.

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DOI https://www.sciencebase.gov/vocab/category/item/identifier doi:10.5066/P99TRHPB

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