Estimating the attainable soil organic carbon deficit in the soil fine fraction to inform feasible storage targets and de-risk carbon farming decisions
Senani Karunaratne
A * , Christina Asanopoulos B , Huidong Jin C , Jeff Baldock B , Ross Searle D , Ben Macdonald A and Lynne M. Macdonald B
A
B
C
D
Abstract
Defining soil organic carbon (SOC) ‘potential’ storage, underpins the economic feasibility of carbon sequestration; however, ‘potential’ storage is not quantifiable using historical and current empirical data. We propose a framework to define ‘attainable’ SOC storage that varies with soil properties, environmental conditions and management practices.
Within the soil fine fraction, we quantified additional storage capacity of the fine fraction SOC attainable deficit (FFSOC_Attainable_Def) by the difference between attainable (FFSOC_Attainable) and actual fine fraction SOC.
Using three analyses, we developed a framework to: (1) estimate the FFSOC_Attainable_Def of the fine fraction of Australian agricultural soils within broad mean annual precipitation ranges and soil depth classes; (2) establish rapid prediction capability for the FFSOC_Attainable_Def using infrared/partial least square regression modelling; and (3) generate spatial FFSOC_Attainable_Def estimates for agricultural regions with ensemble Random Forest modelling.
Global analyses of FFSOC_Attainable_Def do not consider key environmental drivers of carbon inflows and outflows nor soil depth. Separate analyses of soils derived from different combinations of precipitation and soil depth need to include variations in environmental conditions and soil properties to accurately define FFSOC_Attainable and FFSOC_Attainable_Def within the fine fraction. Spatially estimated FFSOC_Attainable_Def stocks revealed an opportunity to increase current fine fraction SOC stock by 3.47 GT (0–0.10 m depth) and 3.24 GT (0.10–0.30 m depth).
Our findings suggests that FFSOC_Attainable_Def is dynamic, not static. Caution is needed when interpreting the results from this analysis.
Deriving estimates of FFSOC_Attainable_Def will reduce risks in decision making on carbon farming in national policies.
Keywords: attainable soil organic carbon, mid-infrared spectroscopy, mineral associated organic carbon, soil carbon storage, soil organic carbon deficit, soil organic carbon potential, soil organic carbon saturation, spatial machine learning modelling.
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