Exploring plant and soil microbial communities as indicators of soil organic carbon in a California rangeland

Soil organic carbon (SOC) is increasingly a focus of land management and policy initiatives, due to the dual role it plays in soil health and climate change mitigation. To manage SOC effectively, land managers would benefit from proxy indicators that can assess SOC concentrations and forecast changes through time. Because inputs and outputs to SOC are driven by plants and soil microorganisms, plant and soil microbial communities may be useful indicators of spatial or temporal SOC changes. To assess and compare the utility of these ecological communities as SOC indicators, we monitored SOC from surface and subsurface soils across a six-year period on a ranch in Central Coastal California, and measured plant, fungal, and bacterial/archaeal community composition. As expected, we observed unique relationships between each candidate indicator and SOC. Most notably, the relative abundance of putative copiotrophic and oligotrophic bacterial phyla allowed us to predict future changes in SOC concentration, as did the relative abundance of saprotrophic fungi and relative cover of perennial grass. Plant and soil microbial community structure was also related to SOC content at the time of sampling. Combining indicators improved our ability to predict SOC concentration and future changes, though we were unable to identify indicators that strongly explained historical changes in SOC concentration that preceded sampling. Our findings suggest that measurements of plant and soil microbial community structure can indicate SOC concentration and future changes, and so may be useful to inform management of healthy soils. •Plant and soil microbial community structure predicted soil organic carbon content.•Functional groups of plant and soil microbes forecasted future changes in soil organic carbon.•Plant and soil microbial community structure failed to explain past changes in soil organic carbon.•Combining measurements from bacterial, fungal, and plant communities improved predictions.