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In the past few decades, there has been an evolution in our understanding of soil organic matter (SOM) dynamics from one of inherent biochemical recalcitrance to one deriving from plant‐microbe‐mineral interactions. This shift in understanding has been driven, in part, by influential conceptual frameworks which put forth hypotheses about SOM dynamics. Here, we summarize several focal conceptual frameworks and derive from them six controls related to SOM formation, (de)stabilization, and loss. These include: (a) physical inaccessibility; (b) organo‐mineral and ‐metal stabilization; (c) biodegradability of plant inputs; (d) abiotic environmental factors; (e) biochemical reactivity and diversity; and (f) microbial physiology and morphology. We then review the empirical evidence for these controls, their model representation, and outstanding knowledge gaps. We find relatively strong empirical support and model representation of abiotic environmental factors but disparities between data and models for biochemical reactivity and diversity, organo‐mineral and ‐metal stabilization, and biodegradability of plant inputs, particularly with respect to SOM destabilization for the latter two controls. More empirical research on physical inaccessibility and microbial physiology and morphology is needed to deepen our understanding of these critical SOM controls and improve their model representation. The SOM controls are highly interactive and also present some inconsistencies which may be reconciled by considering methodological limitations or temporal and spatial variation. Future conceptual frameworks must simultaneously refine our understanding of these six SOM controls at various spatial and temporal scales and within a hierarchical structure, while incorporating emerging insights. This will advance our ability to accurately predict SOM dynamics. Plain Language Summary: Soil organic matter, the remains of plants, animals, and microbes in the soil, performs many important functions for humans and ecosystems, providing habitat for animals, nutrients for plants, climate change buffering, and structure for soil animals and human structures. Thus, it is important to understand how soil organic matter is formed, stabilized, and lost. Here, we review conceptual frameworks that have contributed to our understanding of soil organic matter over the past 20 years. We evaluate their support in experiments and also how well represented they are in computer models. We find the least support and representation for controls of soil organic matter associated with properties of microbes and physical barriers between microbes and soil organic matter. These and novel soil organic matter controls require more research for better understanding of soil organic matter functions. Key Points: Soil organic matter (SOM) research has been advanced by conceptual frameworksConceptual frameworks are associated with different SOM controls with variable empirical support and model representationMicrobial physiology and morphology and physical inaccessibility, as SOM controls, require more empirical work and model representation [ABSTRACT FROM AUTHOR]

Nutrient limitation is widespread in terrestrial ecosystems. Accordingly, representations of nitrogen (N) limitation in land models typically dampen rates of terrestrial carbon (C) accrual, compared with C‐only simulations. These previous findings, however, rely on soil biogeochemical models that implicitly represent microbial activity and physiology. Here we present results from a biogeochemical model testbed that allows us to investigate how an explicit versus implicit representation of soil microbial activity, as represented in the MIcrobial‐MIneral Carbon Stabilization (MIMICS) and Carnegie‐Ames‐Stanford Approach (CASA) soil biogeochemical models, respectively, influence plant productivity, and terrestrial C and N fluxes at initialization and over the historical period. When forced with common boundary conditions, larger soil C pools simulated by the MIMICS model reflect longer inferred soil organic matter (SOM) turnover times than those simulated by CASA. At steady state, terrestrial ecosystems experience greater N limitation when using the MIMICS‐CN model, which also increases the inferred SOM turnover time. Over the historical period, however, warming‐induced acceleration of SOM decomposition over high latitude ecosystems increases rates of N mineralization in MIMICS‐CN. This reduces N limitation and results in faster rates of vegetation C accrual. Moreover, as SOM stoichiometry is an emergent property of MIMICS‐CN, we highlight opportunities to deepen understanding of sources of persistent SOM and explore its potential sensitivity to environmental change. Our findings underscore the need to improve understanding and representation of plant and microbial resource allocation and competition in land models that represent coupled biogeochemical cycles under global change scenarios. Plain Language Summary: Nitrogen limitation of terrestrial ecosystems is common, and crates feedbacks between aboveground and belowground biogeochemical cycles. We present a novel analysis looking at how the explicit versus implicit representation of soil microbial activity influences ecosystem carbon and nitrogen fluxes in a global biogeochemical model. With the microbial explicit model, MIcrobial‐MIneral Carbon Stabilization‐carbon‐nitrogen, we found increases in the inferred turnover time of soil organic matter (SOM) that were caused by plant‐soil feedbacks from nitrogen limitation of plant productivity. Over the historical period, we found that warming‐induced acceleration of SOM decomposition resulted in higher rates of nitrogen mineralization and vegetation biomass accrual. Collectively, these findings present new opportunities to investigate plant‐soil interactions with a model that explicitly represents microbial decomposers. Key Points: We present a global scale soil carbon and nitrogen biogeochemical model that explicitly represents soil microbial activity, MIcrobial‐MIneral Carbon Stabilization‐carbon‐nitrogen (MIMICS‐CN)Nitrogen limitation of plant productivity increases soil organic matter turnover time with MIMICS‐CNSoil texture and litter quality affect prognostic soil carbon to nitrogen ratios that are simulated with MIMICS‐CN [ABSTRACT FROM AUTHOR]

In the age of big data, soil data are more available than ever, but -outside of a few large soil survey resources-remain largely unusable for informing soil management and understanding Earth system processes outside of the original study. Data science has promised a fully reusable research pipeline where data from past studies are used to contextualize new findings and reanalyzed for global relevance. Yet synthesis projects encounter challenges at all steps of the data reuse pipeline, including unavailable data, labor-intensive transcription of datasets, incomplete metadata, and a lack of communication between collaborators. Here, using insights from a diversity of soil, data and climate scientists, we summarize current practices in soil data synthesis across all stages of database creation: data discovery, input, harmonization, curation, and publication. We then suggest new soil-focused semantic tools to improve existing data pipelines, such as ontologies, vocabulary lists, and community practices. Our goal is to provide the soil data community with an overview of current practices in soil data and where we need to go to fully leverage big data to solve soil problems in the next century. [ABSTRACT FROM AUTHOR]