Global soil organic carbon–climate interactions: Why scales matter. (2nd June 2022) - Jungkunst, Hermann F.; Göpel, Jan; Horvath, Thomas; Ott, Simone; Brunn, Melanie
Abstract: Soil organic carbon (SOC) holds the largest terrestrial carbon stock because of soil conditions and processes that favor soil carbon persistence. Vulnerable to climate change, SOC may cross a tipping point toward liberating carbon‐based greenhouse gases, implying massive self‐amplifying SOC‐ climate interactions. Estimates of SOC persistence are challenging as we still lack broad mechanistic insights. Upscaling mechanistic details from small to larger scales is challenging because the driving factors are not available at the needed resolution. Downscaling is problematic as many modeling studies point to the highest uncertainties deriving from the SOC response to climate change, while models themselves have difficulties in replicating contemporary soil properties and dynamics. To bridge the problems of scaling, strict process orientation seems adequate. Holdridge Life Zones (HLZ) classification, as one example, is a climate classification framework at a mesoscale that provides a descriptive approach to facilitate the identification of potential hotspots and coldspots of SOC‐climate interaction. Establishing coordinated experiments across all HLZ, but also including multiple global change drivers, has the potential to advance our understanding of general principles regulating SOC‐climate interaction and SOC persistence. Therefore, regionally tailored solutions for both experiments and modeling are urgently needed and can lead to better management of soil and the ecosystem services provided. Improving "translations" from the scales relevant for process understanding to the scales of decision‐making is key to good management and to predict the fate of our largest terrestrial carbon stock. This article is categorized under: Integrated Assessment of Climate Change > Integrated Scenario Development Abstract : Global soil organic carbon (SOC)–climate interactions are highly relevant to predict future climate change, but need to be unravelled regionally by scaling up detailed mechanistic processes and downscaling global models.