Preprints
https://doi.org/10.5194/bg-2022-153
https://doi.org/10.5194/bg-2022-153
 
26 Jul 2022
26 Jul 2022
Status: this preprint is currently under review for the journal BG.

The paradox of assessing greenhouse gases from soils for nature-based solutions

Rodrigo Vargas and Van Huong Le Rodrigo Vargas and Van Huong Le
  • Department of Plant and Soil Science, University of Delaware, Newark, DE, USA

Abstract. Quantifying the role of soils in nature-based solutions require accurate estimates of soil greenhouse gas (GHG) fluxes. Technological advances allow to simultaneously measure multiple GHGs and now is possible to provide complete GHG budgets from soils (i.e., CO2, CH4 and N2O fluxes). We propose that there is a conflict between the convenience of simultaneously measuring multiple soil GHG fluxes at fixed time intervals (e.g., once, or twice per month) and the intrinsic temporal variability and patterns of different GHG fluxes. Information derived from fixed time intervals -as is commonly done during manual field campaigns- had limitations to reproduce statistical properties, temporal dependence, annual budgets, and associated uncertainty, when compared with information derived from continuous measurements (i.e., automated hourly measurements) for all soil GHG fluxes. We present a novel approach (i.e., temporal univariate Latin Hypercube sampling) that can be applied to optimize monitoring efforts of GHG fluxes across time. We suggest that multiple GHG fluxes should not be simultaneously measured at few fixed time intervals (especially once a month), but an optimized sampling approach can be used to reduce bias and uncertainty. These results have implications for assessing GHG fluxes from soils and consequently reduce uncertainty on the role of soils in nature-based solutions.

Rodrigo Vargas and Van Huong Le

Status: open (until 06 Sep 2022)

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Rodrigo Vargas and Van Huong Le

Rodrigo Vargas and Van Huong Le

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Short summary
Quantifying the role of soils in nature-based solutions require accurate estimates of soil greenhouse gas (GHG) fluxes. We propose a novel optimization approach (i.e., temporal univariate Latin Hypercube sampling) that can be applied across ecosystems to improve monitoring efforts and reduce biased estimates across time. Our results have implications for assessing GHG fluxes from soils and consequently reduce uncertainty on the role of soils in nature-based solutions.
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