Objectives. Soil organic carbon (SOC) represents the largest terrestrial C pool, yet there is substantial uncertainty surrounding the ecological mechanisms that shape SOC formation and loss. Long-held paradigms about the dominant controls on soil C cycling are changing, calling for a re-evaluation of four major drivers of SOC dynamics: plant tissue traits, microbial community traits, rhizosphere dynamics, and soil mineralogy. To predict changes in SOC cycling in the long term, it is necessary to accurately represent feedbacks among these drivers in ecosystem models. However, reflecting the uncertainty induced by rapidly evolving paradigms of SOC cycling, these models exhibit wide variation in structure and parameterization, placing different emphases on primary mechanisms of SOC stabilization. Thus, the overall goal of the proposed research is to identify the mechanisms by which plant and microbial traits mediate soil C cycling, and leverage this understanding to evaluate and improve microbe-explicit biogeochemical models. To do so, this project will target two linked research aims:
Research Objective 1: assess the independent and interactive effects of plant litter chemistry, microbial community structure, root exudation, and soil mineralogy on the formation and loss of SOC
Research Objective 2: utilize empirical data generated in Objective 1 to evaluate and compare three influential microbially explicit biogeochemical models
Research objectives will be addressed using a new experimental platform: the creation of ‘synthetic root/soil systems.’ This approach allows for independent manipulation of chemical characteristics of plant C inputs (including root exudates), the taxonomic and functional composition of soil microbial communities, and the mineral composition of the soil matrix.
Project Description. To address Research Objective 1, synthetic root/soil systems will be constructed using a range of soil mineral types and microbial inoculum treatments, thereby establishing differences in microbial community-level physiological traits. Subsequently, artificial soils will be exposed to varying C inputs representing a range of chemical recalcitrance, including synthetic root exudates. Isotope tracer techniques will be used to monitor microbial biomass growth, respiratory CO2 losses, and the physicochemical stabilization of C inputs. Shifts in SOC cycling will be evaluated in relation to microbial community structure and functional potential, which will be characterized through shotgun metagenomics sequencing. To address Research Objective 2, data generated during the synthetic soil study will be leveraged to evaluate three ‘microbially explicit’ biogeochemical models that represent soil C cycling as a function of microbial physiology. These models vary in their representation of the relationships among plant traits, microbial traits, and soil C cycling, entraining different hypotheses about the dominant controls on SOC formation and loss. Each model will be run under a suite of scenarios representing the different experimental conditions established in the synthetic soils experiment. Models will be evaluated for their ability to simulate observed C pools and fluxes and their responses to experimental treatments. This exercise will provide insight on the model structures which are necessary to capture C cycle responses to shifts in plant and microbial community traits.
Potential Impact. This work will support the development of a novel artificial soil method to identify directional relationships among plant traits, microbial communities, and key biogeochemical processes that those microbes mediate. The synthetic soils experiments will allow rigorous evaluation of competing hypotheses regarding the effects of plant litter quality and root exudation on the size of the SOC sink. Moreover, these data will directly inform the structure of biogeochemical models with explicit microbial mechanisms of SOC formation and loss. This is a pressing research need, given that current models represent outdated mechanisms of soil carbon cycling and cannot accurately capture the response of the land C sink to global change.
