Abstract: As ecosystems are being ever-more-deeply characterized, the ‘black box’ modeling of microbiome roles in ecosystems has been replaced by a rainbow. Various models explicitly and implicitly represent microbial guilds, parameterized in a range of ways. Model representations of climate-microbe interconnections now exist for both directions of those connections - microbial impacts on climate and vice versa - at a range of time scales. While it is neither practical nor desirable for a single model to represent all relevant elements of multi-scale genes-to-ecosystems interactions, the community has increasingly demonstrated that some of those details - such as microbial adaptation to changing temperatures - matter profoundly to predicted system-level outcomes. At a thawing Arctic peatland at the leading edge of climate change, we apply an ecosystem of models to distill over a decade of multi-omics ecosystem characterization into a predictive framework. Through these analytical, numerical, and statistical models, we work to identify processes and linkages that are consequential to system outputs but insufficiently represented in predictive ecosystem models, and the minimum features required to do so.