DOI: 10.1002/2017JG004207
Scopus记录号: 2-s2.0-85046015837
论文题名: Temporal Coupling of Subsurface and Surface Soil CO2 Fluxes: Insights From a Nonsteady State Model and Cross-Wavelet Coherence Analysis
作者: Samuels-Crow K.E. ; Ryan E. ; Pendall E. ; Ogle K.
刊名: Journal of Geophysical Research: Biogeosciences
ISSN: 21698953
出版年: 2018
卷: 123, 期: 4 起始页码: 1406
结束页码: 1424
语种: 英语
英文关键词: carbon cycle
; cross-wavelet coherence analysis
; free-air CO2 enrichment
; nonsteady state carbon flux
; soil respiration
; temporal coherence
Scopus关键词: carbon dioxide
; carbon flux
; deconvolution
; grassland
; microbial activity
; numerical model
; regression analysis
; sandy loam
; soil carbon
; soil moisture
; soil respiration
; soil texture
; soil type
; temporal analysis
; wavelet analysis
; United States
; Wyoming
英文摘要: Inferences about subsurface CO2 fluxes often rely on surface soil respiration (Rsoil) estimates because directly measuring subsurface microbial and root respiration (collectively, CO2 production, STotal) is difficult. To evaluate how well Rsoil serves as a proxy for STotal, we applied the nonsteady state DEconvolution of Temporally varying Ecosystem Carbon componenTs model (0.01-m vertical resolution), using 6-hourly data from a Wyoming grassland, in six simulations that cross three soil types (clay, sandy loam, and sandy) with two depth distributions of subsurface biota. We used cross-wavelet coherence analysis to examine temporal coherence (localized linear correlation) and offsets (lags) between STotal and Rsoil and fluxes and drivers (e.g., soil temperature and moisture). Cross-wavelet coherence revealed higher coherence between fluxes and drivers than linear regressions between concurrent variables. Soil texture and moisture exerted the strongest controls over coherence between CO2 fluxes. Coherence between CO2 fluxes in all soil types was strong at short (~1 day) and long periods (>8 days), but soil type controlled lags, and rainfall events decoupled the fluxes at periods of 1–8 days for several days in sandy soil, up to 1 week in sandy loam, and for a month or more in clay soil. Concentrating root and microbial biomass nearer the surface decreased lags in all soil types and increased coherence up to 10% in clay soil. The assumption of high temporal coherence between Rsoil and STotal is likely valid in dry, sandy soil, but may lead to underestimates of short-term STotal in semiarid grasslands with fine-grained and/or wet soil. ©2018. American Geophysical Union. All Rights Reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/114177
Appears in Collections: 气候减缓与适应
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作者单位: School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, United States; Lancaster Environment Centre, Lancaster University, Lancaster, United Kingdom; Hawkesbury Institute for the Environment, Western Sydney University, Penrith, NSW, Australia; Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, United States; Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ, United States
Recommended Citation:
Samuels-Crow K.E.,Ryan E.,Pendall E.,et al. Temporal Coupling of Subsurface and Surface Soil CO2 Fluxes: Insights From a Nonsteady State Model and Cross-Wavelet Coherence Analysis[J]. Journal of Geophysical Research: Biogeosciences,2018-01-01,123(4)