TY - JOUR
T1 - Topography Mediates the Response of Soil CO2 Efflux to Precipitation Over Days, Seasons, and Years
AU - Kopp, Marissa
AU - Kaye, Jason
AU - Smeglin, Yuting He
AU - Adams, Thomas
AU - Primka, Edward J.
AU - Bradley, Brosi
AU - Shi, Yuning
AU - Eissenstat, David
N1 - Funding Information:
This manuscript was improved by feedback from Drs. Elise Pendall, Ben Bond-Lamberty, and three anonymous peer reviewers. Financial support was provided by National Science Foundation Grant (award EAR—1331726) for the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO), by the US Department of Energy, Office of Science, Office of Biological & Environmental Research (award DE—SC0012003), and by Hatch Appropriations under Project PEN04571 and Accession 1003346. Manual soil CO2 efflux samples were collected by Alexandra Buck and Jeremy Harper. All data were collected from the SSHCZO field site, which is managed by Brandon Forsythe, within Penn State’s Stone Valley Forest, which is managed by staff of the Forestlands Management Office and funded by the Penn State College of Agricultural Sciences and Department of Ecosystem Science and Management. PhenoCam data are funded by the Northeastern States Research Cooperative, NSF’s Macrosystems Biology program (Awards EF–1065029 and EF–1702697), and DOE’s Regional and Global Climate Modeling program (Award DE–SC0016011). MK was funded by a USDA National Needs Fellowship from NIFA (Grant 2019–38420–28979) and trained on an NSF Research Traineeship (NSF-DGE NRT-INFEWS # 1828822).
Funding Information:
This manuscript was improved by feedback from Drs. Elise Pendall, Ben Bond-Lamberty, and three anonymous peer reviewers. Financial support was provided by National Science Foundation Grant (award EAR—1331726) for the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO), by the US Department of Energy, Office of Science, Office of Biological & Environmental Research (award DE—SC0012003), and by Hatch Appropriations under Project PEN04571 and Accession 1003346. Manual soil CO efflux samples were collected by Alexandra Buck and Jeremy Harper. All data were collected from the SSHCZO field site, which is managed by Brandon Forsythe, within Penn State’s Stone Valley Forest, which is managed by staff of the Forestlands Management Office and funded by the Penn State College of Agricultural Sciences and Department of Ecosystem Science and Management. PhenoCam data are funded by the Northeastern States Research Cooperative, NSF’s Macrosystems Biology program (Awards EF–1065029 and EF–1702697), and DOE’s Regional and Global Climate Modeling program (Award DE–SC0016011). MK was funded by a USDA National Needs Fellowship from NIFA (Grant 2019–38420–28979) and trained on an NSF Research Traineeship (NSF-DGE NRT-INFEWS # 1828822). 2
Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2023/6
Y1 - 2023/6
N2 - Spatiotemporal heterogeneity in soil CO2 efflux (FS) underlies one of our greatest gaps in understanding global carbon (C) cycles. Though scientists recognize this heterogeneity, FS sampling schemes often average across spatial heterogeneity or fail to capture fine temporal heterogeneity, and many ecosystem models assume flat terrain. Here, we test the idea that simple, remotely sensible terrain variables improve regression models of spatiotemporal variation in FS. We used automatic chambers that, for the first time, capture FS in complex temperate forest terrain at fine temporal resolution with 177,477 hourly FS measurements at 8 locations from ridgetop to valley along planar and swale hillslopes, across three years ranging from dry to record wet precipitation. In two of these years, we measured FS weekly at 50 additional locations distributed across the 8-ha catchment. Growing season Fs estimates were 1.25 times greater when sampling hourly versus weekly. At ridgetops, growing season FS increased by an average of 463 gC m−2 180 day−1 (75.9%) from dry to wet years, while valleys decreased by 208 gC m−2 180 day−1 (− 20.1%). This bidirectional response to interannual moisture was identified in distinct Random Forest models of Fs for convergent (water accumulating) or non-convergent (water shedding) hillslope positions. We hypothesize that different FS constraints drive these opposing responses—water availably to biota limits FS from ridgetops while slow oxygen diffusion limits FS from wet valleys. Accounting for hillslope position and shape reduces variance of FS estimates in complex terrain, which could improve FS sampling, C budgets, and modeling.
AB - Spatiotemporal heterogeneity in soil CO2 efflux (FS) underlies one of our greatest gaps in understanding global carbon (C) cycles. Though scientists recognize this heterogeneity, FS sampling schemes often average across spatial heterogeneity or fail to capture fine temporal heterogeneity, and many ecosystem models assume flat terrain. Here, we test the idea that simple, remotely sensible terrain variables improve regression models of spatiotemporal variation in FS. We used automatic chambers that, for the first time, capture FS in complex temperate forest terrain at fine temporal resolution with 177,477 hourly FS measurements at 8 locations from ridgetop to valley along planar and swale hillslopes, across three years ranging from dry to record wet precipitation. In two of these years, we measured FS weekly at 50 additional locations distributed across the 8-ha catchment. Growing season Fs estimates were 1.25 times greater when sampling hourly versus weekly. At ridgetops, growing season FS increased by an average of 463 gC m−2 180 day−1 (75.9%) from dry to wet years, while valleys decreased by 208 gC m−2 180 day−1 (− 20.1%). This bidirectional response to interannual moisture was identified in distinct Random Forest models of Fs for convergent (water accumulating) or non-convergent (water shedding) hillslope positions. We hypothesize that different FS constraints drive these opposing responses—water availably to biota limits FS from ridgetops while slow oxygen diffusion limits FS from wet valleys. Accounting for hillslope position and shape reduces variance of FS estimates in complex terrain, which could improve FS sampling, C budgets, and modeling.
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U2 - 10.1007/s10021-022-00786-1
DO - 10.1007/s10021-022-00786-1
M3 - Article
AN - SCOPUS:85138151705
SN - 1432-9840
VL - 26
SP - 687
EP - 705
JO - Ecosystems
JF - Ecosystems
IS - 4
ER -