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Mineral stabilization of soil organic matter is an important regulator of the global carbon (C) cycle. However, the vulnerability of mineral-stabilized organic matter (OM) to climate change is currently unknown. We examined soil profiles from 34 sites across the conterminous USA to investigate how the abundance and persistence of mineral-associated organic C varied with climate at the continental scale. Using a novel combination of radiocarbon and molecular composition measurements, we show that the relationship between the abundance and persistence of mineral-associated organic matter (MAOM) appears to be driven by moisture availability. In wetter climates where precipitation exceeds evapotranspiration, excess moisture leads to deeper and more prolonged periods of wetness, creating conditions which favor greater root abundance and also allow for greater diffusion and interaction of inputs with MAOM. In these humid soils, mineral-associated soil organic C concentration and persistence are strongly linked, whereas this relationship is absent in drier climates. In arid soils, root abundance is lower, and interaction of inputs with mineral surfaces is limited by shallower and briefer periods of moisture, resulting in a disconnect between concentration and persistence. Data suggest a tipping point in the cycling of mineral-associated C at a climate threshold where precipitation equals evaporation. As climate patterns shift, our findings emphasize that divergence in the mechanisms of OM persistence associated with historical climate legacies need to be considered in process-based models. 

Abstract Soil organic matter (SOM) is the largest terrestrial pool of organic carbon, and potential carbon-climate feedbacks involving SOM decomposition could exacerbate anthropogenic climate change. However, our understanding of the controls on SOM mineralization is still incomplete, and as such, our ability to predict carbon-climate feedbacks is limited. To improve our understanding of controls on SOM decomposition, A and upper B horizon soil samples from 26 National Ecological Observatory Network (NEON) sites spanning the conterminous U.S. were incubated for 52 weeks under conditions representing site-specific mean summer temperature and sample-specific field capacity (−33 kPa) water potential. Cumulative carbon dioxide respired was periodically measured and normalized by soil organic C content to calculate cumulative specific respiration (CSR), a metric of SOM vulnerability to mineralization. The Boruta algorithm, a feature selection algorithm, was used to select important predictors of CSR from 159 variables. A diverse suite of predictors was selected (12 for A horizons, 7 for B horizons) with predictors falling into three categories corresponding to SOM chemistry, reactive Fe and Al phases, and site moisture availability. The relationship between SOM chemistry predictors and CSR was complex, while sites that had greater concentrations of reactive Fe and Al phases or were wetter had lower CSR. Only three predictors were selected for both horizon types, suggesting dominant controls on SOM decomposition differ by horizon. Our findings contribute to the emerging consensus that a broad array of controls regulates SOM decomposition at large scales and highlight the need to consider changing controls with depth. 

Abstract. In the age of big data, soil data are more available and richer than ever, but – outside of a few large soil survey resources – they remain largely unusable for informing soil management and understanding Earth system processes beyond 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 new insight.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: availability, 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 A small imbalance in plant productivity and decomposition accounts for the carbon (C) accumulation capacity of peatlands. As climate changes, the continuity of peatland net C storage relies on rising primary production to offset increasing ecosystem respiration (ER) along with the persistence of older C in waterlogged peat. A lowering in the water table position in peatlands often increases decomposition rates, but concurrent plant community shifts can interactively alter ER and plant productivity responses. The combined effects of water table variation and plant communities on older peat C loss are unknown. We used a full‐factorial 1‐m³mesocosm array with vascular plant functional group manipulations (Unmanipulated Control, Sedge only, and Ericaceous only) and water table depth (natural and lowered) treatments to test the effects of plants and water depth on CO₂fluxes, decomposition, and older C loss. We used Δ¹⁴C and δ¹³C of ecosystem CO₂respiration, bulk peat, plants, and porewater dissolved inorganic C to construct mixing models partitioning ER among potential sources. We found that the lowered water table treatments were respiring C fixed before the bomb spike (1955) from deep waterlogged peat. Lowered water table Sedge treatments had the oldest dissolved inorganic¹⁴C signature and the highest proportional peat contribution to ER. Decomposition assays corroborated sustained high rates of decomposition with lowered water tables down to 40 cm below the peat surface. Heterotrophic respiration exceeded plant respiration at the height of the growing season in lowered water table treatments. Rates of gross primary production were only impacted by vegetation, whereas ER was affected by vegetation and water table depth treatments. The decoupling of respiration and primary production with lowered water tables combined with older C losses suggests that climate and land‐use‐induced changes in peatland hydrology can increase the vulnerability of peatland C stores. 

Summary Dead fungal mycelium (necromass) represents a critical component of soil carbon (C) and nutrient cycles. Assessing how the microbial communities associated with decomposing fungal necromass change as global temperatures rise will help in determining how these belowground organic matter inputs contribute to ecosystem responses.In this study, we characterized the structure of bacterial and fungal communities associated with multiple types of decaying mycorrhizal fungal necromass incubated within mesh bags across a 9°C whole ecosystem temperature enhancement in a boreal peatland.We found major taxonomic and functional shifts in the microbial communities present on decaying mycorrhizal fungal necromass in response to warming. These changes were most pronounced in hollow microsites, which showed convergence towards the necromass‐associated microbial communities present in unwarmed hummocks. We also observed a high colonization of ericoid mycorrhizal fungal necromass by fungi from the same genera as the necromass.These results indicate that microbial communities associated with mycorrhizal fungal necromass decomposition are likely to change significantly with future climate warming, which may have strong impacts on soil biogeochemical cycles in peatlands. Additionally, the high enrichment of congeneric fungal decomposers on ericoid mycorrhizal necromass may help to explain the increase in ericoid shrub dominance in warming peatlands.