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Article

Linking Remotely Sensed Carbon and Water Use Efficiencies with In Situ Soil Properties

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Department of Earth and Environmental Science, Murray State University, Murray, KY 42071, USA
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Watershed Studies Institute, Murray State University, Murray, KY 42071, USA
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Department of Natural Resources, Ecology, and Management, Oklahoma State University, Stillwater, OK 74078, USA
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Department of Life and Environmental Sciences, University of California Merced, Merced, CA 95343, USA
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Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA
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Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91125, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Rasmus Fensholt
Remote Sens. 2021, 13(13), 2593; https://doi.org/10.3390/rs13132593
Received: 29 April 2021 / Revised: 28 June 2021 / Accepted: 28 June 2021 / Published: 2 July 2021
(This article belongs to the Special Issue Remote Sensing of Carbon Fluxes and Stocks)
The capacity of terrestrial ecosystems to sequester carbon dioxide (CO2) from the atmosphere is expected to be altered by climate change and CO2 fertilization, but this projection is limited by our understanding of how the soil system interacts with plants. Understanding the soil–vegetation interactions is essential to assess the magnitude and response of terrestrial ecosystems to the changing climate. Here, we used soil profile and satellite data to explore the role that soil properties play in regulating water and carbon use by plants. Data obtained for 19 terrestrial ecosystem sites in a warm temperate and humid climate were used to investigate the relationship between remotely sensed data and soil physical and chemical properties. Classification and regression tree results showed that in situ soil carbon isotope (δ13C), and soil order were significant predictors (r2 = 0.39, mean absolute error (MAE) = 0 of 0.175 gC/KgH2O) of remotely sensed water use efficiency (WUE) based on the Moderate Resolution Imaging Spectroradiometer (MODIS). Soil extractable calcium (Ca), and land cover type were significant predictors of remotely sensed carbon use efficiency (CUE) based on MODIS and Landsat data-(r2 = 0.64–0.78, MAE = 0.04–0.06). We used gross primary productivity (GPP) derived from solar-induced fluorescence (SIF) data, based on the Orbiting Carbon Observatory-2 (OCO-2), to calculate WUE and CUE (referred to as WUESIF and CUESIF, respectively) for our study sites. The regression tree analysis revealed that soil organic matter and soil extractable magnesium (Mg), δ13C, and soil silt content were the important predictors of both WUESIF (r2 = 0.19, MAE = 0.64 gC/KgH2O) and CUESIF (r2 = 0.45, MAE = 0.1), respectively. Our results revealed the importance of soil extractable Ca, soil carbon (S13C is a facet of soil carbon content), and soil organic matter predicting CUE and WUE. Insights gained from this study highlighted the importance of biotic and abiotic factors regulating plant and soil interactions. These types of data are timely and critical for accurate predictions of how terrestrial ecosystems respond to climate change. View Full-Text
Keywords: MODIS; carbon use efficiency; water use efficiency; solar-induced chlorophyll fluorescence; soil properties MODIS; carbon use efficiency; water use efficiency; solar-induced chlorophyll fluorescence; soil properties
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MDPI and ACS Style

El Masri, B.; Stinchcomb, G.E.; Cetin, H.; Ferguson, B.; Kim, S.L.; Xiao, J.; Fisher, J.B. Linking Remotely Sensed Carbon and Water Use Efficiencies with In Situ Soil Properties. Remote Sens. 2021, 13, 2593. https://doi.org/10.3390/rs13132593

AMA Style

El Masri B, Stinchcomb GE, Cetin H, Ferguson B, Kim SL, Xiao J, Fisher JB. Linking Remotely Sensed Carbon and Water Use Efficiencies with In Situ Soil Properties. Remote Sensing. 2021; 13(13):2593. https://doi.org/10.3390/rs13132593

Chicago/Turabian Style

El Masri, Bassil, Gary E. Stinchcomb, Haluk Cetin, Benedict Ferguson, Sora L. Kim, Jingfeng Xiao, and Joshua B. Fisher 2021. "Linking Remotely Sensed Carbon and Water Use Efficiencies with In Situ Soil Properties" Remote Sensing 13, no. 13: 2593. https://doi.org/10.3390/rs13132593

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