GAMEchange

Current soil carbon models used by the Intergovernmental Panel on Climate Change (IPCC) lack sophistication, leading to uncertainty about soils’ roles as carbon sinks or sources. Microbe-explicit models hold promise for improving predictions, yet challenges arise from limited data and high microbial variability, which is influenced by eco-evolutionary processes. The ERC-funded GAMEchange project aims to address this by using recent microbial genomic data to develop advanced biogeochemical models that reflect microbial adaptation impacts on soil organic carbon (SOC). Through an innovative emulation method, GAMEchange will integrate a genome-parameterised microbial model with a vegetation land model, enabling comparison of SOC predictions for 2100 with and without microbial adaptation. This project will set the foundation for more precise microbial modelling in future IPCC climate forecasts.

The representation of soil carbon in models used by the Intergovernmental Panel on Climate Change (IPCC) remains significantly underdeveloped, leading to uncertainty concerning some models predicting soils as carbon sinks and others as sources of carbon dioxide. The development of microbe-explicit models is a very promising avenue for avoiding such inconsistencies and obtaining more accurate soil organic carbon (SOC) predictions. However, these models still suffer from uncertain parameterisation due to the lack of data and the high variability in microbial responses at the ecosystem scale. These issues are especially true in carbon-rich northern high-latitude soils that are most vulnerable to large SOC loss with global change. The variability in microbial response at the ecosystem scale is rooted in intricate microscale eco-evolutionary adaptive processes, namely evolution, dispersal, and filtering of community diversity. The diversity in microbiomes, resulting from past selection, influences present adaptive capacity and is referred to as the contingency effect. 

The GAMEchange project will harness a recent surge of novel microbial genomic data in order to parameterise a new generation of biogeochemical model that accounts for the effect of microbial adaptation on SOC, including contingency effects. GAMEchange will couple the genome-parameterized microscale microbial model with a vegetation land model using a novel emulation approach. This novel coupled model will allow us to compare the 2100 SOC predictions with and without microbial adaptation. This project will produce the first coupled soil microbe-land model parameterised with genomic data, laying the foundation for more realistic microbial models for IPCC climate projections.