Collar Properties and Measurement Time Confer Minimal Bias Overall on Annual Soil Respiration Estimates in a Global Database

Jian, Jinshi; Gough, Christopher; Sihi, Debjani; Hopple, Anya M.; Bond‐Lamberty, Ben

doi:10.1029/2020JG006066

Collar Properties and Measurement Time Confer Minimal Bias Overall on Annual Soil Respiration Estimates in a Global Database

Journal Article · Sat Dec 05 00:00:00 EST 2020 · Journal of Geophysical Research. Biogeosciences

DOI:https://doi.org/10.1029/2020JG006066· OSTI ID:1786723

^[1]; ^[2]; Sihi, Debjani ^[3]; Hopple, Anya M. ^[4]; ^[1]

Pacific Northwest National Laboratory Joint Global Change Research Institute at the University of Maryland College Park MD USA
Department of Biology Virginia Commonwealth University Richmond VA USA
Department of Environmental Sciences Emory University Atlanta GA USA
Pacific Northwest National Laboratory Richland WA USA, Smithsonian Environmental Research Center Edgewater MD USA

Abstract

Measuring the soil‐to‐atmosphere carbon dioxide (CO ₂ ) flux (soil respiration, R _S ) is important to understanding terrestrial carbon balance and to forecasting climate change. Such measurements are frequently made using measurement collars permanently inserted into the soil surface. However, differences in measurement duration and frequency, as well as collar properties, may lead to biases in the estimation of annual R _S . Using a newly updated global R _S database (SRDB‐V5), we investigated the annual R _S bias associated with five methodological factors: collar height, collar coverage area, collar insertion depth, measurement duration, and measurement frequency. We found that annual R _S was negatively correlated with collar insertion depth, consistent with the idea that collar insertion cuts roots and thus reduces R _S . Annual R _S was also negatively related with collar height and collar coverage area, perhaps because uniform head‐space mixing is difficult to achieve in larger volume chambers; however, these effects were quantitatively small (bias of ~2% to 10% of mean R _S ). We found no correlation of measurement duration or measurement frequency with annual R _S . These findings suggest that variation in R _S methodology generally introduces minimal bias overall. Therefore, compilations of minimally adjusted annual R _S measurements provide a reliable resource for synthesis studies, global annual R _S modeling, and investigation of how soil carbon responds to climate change.

View Accepted Manuscript (Publisher)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-76RL01830

OSTI ID:: 1786723

Alternate ID(s):: OSTI ID: 1734648

Journal Information:: Journal of Geophysical Research. Biogeosciences, Journal Name: Journal of Geophysical Research. Biogeosciences Journal Issue: 12 Vol. 125; ISSN 2169-8953

Publisher:: American Geophysical Union (AGU)Copyright Statement

Country of Publication:: United States

Language:: English

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