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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.

Despite the importance of microbial soil organic matter (SOM) respiration in regulating the flux of carbon between soils and the atmosphere, soil carbon cycling models remain primarily based on climate and soil properties, leading to large uncertainty in predictions. To address this knowledge gap, we analyzed high‐resolution water‐extractable SOM profiles from soil cores collected across the United States by the 1,000 Soils Pilot of the Molecular Observation Network. Our innovation lies in using machine learning to distill thousands of SOM formula into tractable units; and it enables integrating data from molecular measurements into soil respiration models. In surface soils, SOM chemistry provided better estimates of potential soil respiration than soil physicochemistry, and using them combined yielded the best prediction. Overall, we identify specific subsets of organic molecules that may improve predictions of global soil respiration and create a strong basis for developing new representations in process‐based models. Plain Language Summary Soil organic carbon is one of the largest and most active pools in the global carbon cycle. Microbial decomposition of soil organic matter (SOM) releases large amounts of carbon dioxide (CO2) to the atmosphere. This process is soil microbial respiration. To evaluate if SOM composition can improve predictions of soil respiration, we collected soils from across the continental US, and analyzed both soil physicochemistry and molecular SOM composition, as part of the Molecular Observation Network. We developed machine learning based workflow to extract key SOM signatures and used the SOM signatures to predict potential rate of soil respiration, compared to standard soil physicochemistry. The results suggested that SOM composition improved the prediction of potential soil respiration in surface soils, where most soil carbon is actively cycled. In deeper soils, model performance was not improved by SOM chemistry, possibly due to the greater importance of mineral‐associated SOM. Our results identified key SOM molecules in predicting potential soil respiration and supported the significance of SOM dynamics in future development of soil carbon models. Key Points Molecular measurements of dissolved soil organic matter (SOM) are critical to accurately predict soil respiration at the continental scale Machine learning extracts key molecules from complex high‐resolution SOM profiles to explain differences in potential soil respiration Dissolved SOM profiles provide more power in predicting potential respiration in surface soils than subsoils

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.

Many streams originate in forested watersheds at risk of wildfires. Wildfires can introduce thermally altered organic compounds to terrestrial and aquatic systems. Understanding the degradation of leachates from these burned organic materials, referred to as dissolved pyrogenic organic material (PyDOM), is critical in determining water quality impacts in forested watersheds. This study used fluorescence spectroscopy to examine photochemical alterations of PyDOM generated by leaching organic matter burned at various temperatures. The PyDOM was exposed to natural sunlight for 25 days and the photochemical formation of hydrogen peroxide was monitored. PyDOM was characterized using ultraviolet–visible absorption, excitation–emission matrix (EEM) fluorescence spectroscopy, and fluorescence indices. Throughout the experiment, the emission intensity of the humic peak for all light-exposed leachates decreased while dark leachates exhibited no significant change in their fluorescence spectra. Additionally, hydrogen peroxide concentrations and UV absorbance decreased progressively over time, providing direct evidence that PyDOM concentrations can be significantly reduced by photodegradation. A characteristically low emission peak was observed in the EEMs of the fresh PyDOM, which could help in detecting fresh PyDOM. These results demonstrate that PyDOM derived from burned leachates is susceptible to photodegradation and that fluorescence measurements could be used as proxies for detecting PyDOM immediately post-wildfire.

Fire affects the quantity and quality of soil organic matter (SOM). While combustion of the O-horizon causes direct losses of SOM, fire also transforms the remaining SOM into a spectrum of thermally altered organic matter. Pyrogenic carbon (PyC) can resist degradation and may have important effects on soil carbon cycling. The objectives of this study are to examine the mobility of PyC. Studying the effects of wildfire is challenging due to the rapid post-fire changes in the ecosystem and lack of robust controls. We overcame those limitations by examining the Chimney Tops 2 Fire which burned 4,617 ha of the Great Smoky Mountains National Park (GRSMNP), including a National Ecological Observatory Network (NEON) site, in November 2016. We examined PyC in soils from three time points from an area burned at low-severity (pre-, immediate post-, and 11 months post-fire) and two time points from areas burned at lower to higher severity (immediate post- and 11 months post-fire). At locations with pre-fire soil samples we found that PyC increased in the O-horizon (2.22 g BPCA/kg soil) after low severity fire, which resulted in higher PyC concentrations at 5–10 cm (0.73 g BPCA/kg soil and 17.79 g BPCA/kg C) and 10–20 cm (12.19 g BPCA/kg C) of depth in the mineral soil. Sites burned at higher severity had more PyC in the O horizon relative to sites burned at lower severity (10.29 g BPCA/kg soil and 29.89 g BPCA/kg C). As a result of higher concentrations of PyC in the O-horizons burned at higher severity, statistically more PyC moved from the O-horizon to the 0–10 cm horizon from immediate to 1-year post-fire (1.37 g BPCA/kg soil and 16.10 g BPCA/kg C). Lastly, the depth profile of C and BPCA suggest a shift in the source and amount of PyC in these soil profiles over time—possibly as a result of fire suppression. Results indicate that low severity fire may be an important mechanism by which PyC is produced and transported into mineral soils.

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 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.

While significant progress has been made in understanding global carbon (C) cycling, the mechanisms regulating belowground C fluxes and storage are still uncertain. New molecular technologies have the power to elucidate these processes, yet we have no widespread standardized implementation of molecular techniques. To help address this gap, we have developed a crowdsourced soil core research program for analyzing molecular and microstructural data that describe soil structure, soil organic matter (SOM) chemistry, and soil microbiology. Known as the 1,000 Soils Pilot and based at the Environmental Molecular Sciences Laboratory (EMSL), we use Fourier-transform ion cyclotron resonance- (FTICR) and liquid chromatography- (LC) mass spectrometry (MS); X-ray Computed Tomography (XCT), water retention curves; metagenomic sequencing; and standard biogeochemical measurements to enable new insights into soil C cycles. To emphasize cross-site comparability, we provide standardized sampling materials and protocols, and all data are generated on dedicated instruments with optimized settings. Here, we describe the 1000 Soils Pilot and present a use case describing differences in SOM chemistry, soil structure, and chemical and biological properties across forest soils exposed to differing wildfire regimes. Data and analytic workflows from the 1000 Soils Pilot will populate a unique continental-scale database of soil molecular properties, as part of the EMSL Molecular Observation Network (MONet) user program.Competing Interest StatementThe authors have declared no competing interest.

Hilton juggles two full-time jobs, and he returns home at night to the one-car garage he calls home in the heart of Silicon Valley. Jose and Elizabeth try to qualify for a mortgage, Emilia reveals a troubling part of her past, and DJ and Takita try to start over in a new neighborhood.

DJ steps up his union activity, Jose and Elizabeth put everything on the line to improve their living situation and Emilia gets an unexpected call about a job opportunity. Percy gets a $1.50/hour raise at a new custodial position and Takita prepares for a celebration at church.