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1. A global meta‐analysis of cover crop response on soil carbon storage within a corn production system

   https://doi.org/10.1002/AGJ2.21340  

   Joshi, Deepak R.; Sieverding, Heidi L.; Xu, Hui; Kwon, Hoyoung; Wang, Michael; Clay, Sharon A; Johnson, Jane M.; Thapa, Resham; Westhoff, Shaina; Clay, David E. (July 2023, Agronomy Journal)

   Michael Kaiser (Ed.)

   By influencing soil organic carbon (SOC), cover crops play a key role in shaping soil health and hence the system's long‐term sustainability. However, the magnitude by which cover crops impacts SOC depends on multiple factors, including soil type, climate, crop rotation, tillage type, cover crop growth, and years under management. To elucidate how these multiple factors influence the relative impact of cover crops on SOC, we conducted a meta‐analysis on the impacts of cover crops within rotations that included corn (Zea maysL.) on SOC accumulation. Information on climatic conditions, soil characteristics, management, and cover crop performance was extracted, resulting in 198 paired comparisons from 61 peer‐reviewed studies. Over the course of each study, cover crops on average increased SOC by 7.3% (95% CI, 4.9%–9.6%). Furthermore, the impact of cover crop–induced increases in percent change SOC was evaluated across soil textures, cover crop types, crop rotations, biomass amounts, cover crop durations, tillage practices, and climatic zones. Our results suggest that current cover crop–based corn production systems are sequestering 5.5 million Mg of SOC per year in the United States and have the potential to sequester 175 million Mg SOC per year globally. These findings can be used to improve carbon footprint calculations and develop science‐based policy recommendations. Taken altogether, cover cropping is a promising strategy to sequester atmospheric C and hence make corn production systems more resilient to changing climates. 

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2. Remotely detected aboveground plant function predicts belowground processes in two prairie diversity experiments

   https://doi.org/10.1002/ecm.1488  

   Cavender‐Bares, Jeannine; Schweiger, Anna K.; Gamon, John A.; Gholizadeh, Hamed; Helzer, Kimberly; Lapadat, Cathleen; Madritch, Michael D.; Townsend, Philip A.; Wang, Zhihui; Hobbie, Sarah E. (November 2021, Ecological Monographs)

   Abstract Imaging spectroscopy provides the opportunity to incorporate leaf and canopy optical data into ecological studies, but the extent to which remote sensing of vegetation can enhance the study of belowground processes is not well understood. In terrestrial systems, aboveground and belowground vegetation quantity and quality are coupled, and both influence belowground microbial processes and nutrient cycling. We hypothesized that ecosystem productivity, and the chemical, structural and phylogenetic‐functional composition of plant communities would be detectable with remote sensing and could be used to predict belowground plant and soil processes in two grassland biodiversity experiments: the BioDIV experiment at Cedar Creek Ecosystem Science Reserve in Minnesota and the Wood River Nature Conservancy experiment in Nebraska. We tested whether aboveground vegetation chemistry and productivity, as detected from airborne sensors, predict soil properties, microbial processes and community composition. Imaging spectroscopy data were used to map aboveground biomass, green vegetation cover, functional traits and phylogenetic‐functional community composition of vegetation. We examined the relationships between the image‐derived variables and soil carbon and nitrogen concentration, microbial community composition, biomass and extracellular enzyme activity, and soil processes, including net nitrogen mineralization. In the BioDIV experiment—which has low overall diversity and productivity despite high variation in each—belowground processes were driven mainly by variation in the amount of organic matter inputs to soils. As a consequence, soil respiration, microbial biomass and enzyme activity, and fungal and bacterial composition and diversity were significantly predicted by remotely sensed vegetation cover and biomass. In contrast, at Wood River—where plant diversity and productivity were consistently higher—belowground processes were driven mainly by variation in the quality of aboveground inputs to soils. Consequently, remotely sensed functional, chemical and phylogenetic composition of vegetation predicted belowground extracellular enzyme activity, microbial biomass, and net nitrogen mineralization rates but aboveground biomass (or cover) did not. The contrasting associations between the quantity (productivity) and quality (composition) of aboveground inputs with belowground soil attributes provide a basis for using imaging spectroscopy to understand belowground processes across productivity gradients in grassland systems. However, a mechanistic understanding of how above and belowground components interact among different ecosystems remains critical to extending these results broadly. 

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3. Optimizing process-based models to predict current and future soil organic carbon stocks at high-resolution

   https://doi.org/10.1038/s41598-022-14224-8  

   Pierson, Derek; Lohse, Kathleen A.; Wieder, William R.; Patton, Nicholas R.; Facer, Jeremy; de Graaff, Marie-Anne; Georgiou, Katerina; Seyfried, Mark S.; Flerchinger, Gerald; Will, Ryan (December 2022, Scientific Reports)

   Abstract From hillslope to small catchment scales (< 50 km 2 ), soil carbon management and mitigation policies rely on estimates and projections of soil organic carbon (SOC) stocks. Here we apply a process-based modeling approach that parameterizes the MIcrobial-MIneral Carbon Stabilization (MIMICS) model with SOC measurements and remotely sensed environmental data from the Reynolds Creek Experimental Watershed in SW Idaho, USA. Calibrating model parameters reduced error between simulated and observed SOC stocks by 25%, relative to the initial parameter estimates and better captured local gradients in climate and productivity. The calibrated parameter ensemble was used to produce spatially continuous, high-resolution (10 m 2 ) estimates of stocks and associated uncertainties of litter, microbial biomass, particulate, and protected SOC pools across the complex landscape. Subsequent projections of SOC response to idealized environmental disturbances illustrate the spatial complexity of potential SOC vulnerabilities across the watershed. Parametric uncertainty generated physicochemically protected soil C stocks that varied by a mean factor of 4.4 × across individual locations in the watershed and a − 14.9 to + 20.4% range in potential SOC stock response to idealized disturbances, illustrating the need for additional measurements of soil carbon fractions and their turnover time to improve confidence in the MIMICS simulations of SOC dynamics. 

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4. Alleviating Nitrogen and Phosphorus Limitation Does Not Amplify Potassium‐Induced Increase in Terrestrial Biomass

   https://doi.org/10.1111/gcb.70193  

   Liang, Guopeng; Sun, Pengyan; Waring, Bonnie G; Fu, Zheng; Reich, Peter B (April 2025, Global Change Biology)

   ABSTRACT Potassium (K) is the second most abundant nutrient element in plants after nitrogen (N), and has been shown to limit aboveground production in some contexts. However, the role of N and phosphorus (P) availability in mediating K limitation in terrestrial production remains poorly understood; and it is unknown whether K also limits belowground carbon (C) stocks, which contain at least three times more C than those aboveground stocks. By synthesizing 779 global paired observations (528, 125, and 126 for aboveground productivity, root biomass, and soil organic C [SOC], respectively), we found that K addition significantly increased aboveground production and SOC by 8% and 5%, respectively, but did not significantly affect root biomass (+9%). Moreover, enhanced N and/or P availability (through N and P addition) did not further amplify the positive effect of K on aboveground productivity. In other words, K had a positive effect on aboveground productivity only when N and/or P were limiting, indicating that K could somehow substitute for N or P when they were limiting. Climate variables mostly explained the variations in K effects; specifically, stronger positive responses of aboveground productivity and SOC to K were found in regions with high mean annual temperature and wetness. Our results suggest that K addition enhances C sequestration by increasing both aboveground productivity and SOC, contributing to climate mitigation, but the positive effects of K on terrestrial C stocks are not further amplified when N and P limitations are alleviated. 

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5. Agricultural Management Legacy Effects on Switchgrass Growth and Soil Carbon Gains

   https://doi.org/10.1111/gcbb.70051  

   Chakraborty, Poulamee; Falvo, Grant; Robertson, G Philip; Kravchenko, Alexandra (July 2025, GCB Bioenergy)

   ABSTRACT Switchgrass (Panicum virgatumL.) is a native North American grass currently considered a high‐potential bioenergy feedstock crop. However, previous reports questioned its effectiveness in generating soil organic carbon (SOC) gains, with resultant uncertainty regarding the monoculture switchgrass's impact on the environmental sustainability of bioenergy agriculture. We hypothesize that the inconsistencies in past SOC accrual results might be due, in part, to differences in prior land management among the systems subsequently planted to switchgrass. To test this hypothesis, we measured SOC and other soil properties, root biomass, and switchgrass growth in an experimental site with a 30‐year history of contrasting tillage and N‐fertilization treatments, 7 years after switchgrass establishment. We determined switchgrass' monthly gross primary production (GPP) for six consecutive years and conducted deep soil sampling. Nitrogen fertilization expectedly stimulated switchgrass growth; however, a tendency for better plant growth was also observed under unfertilized settings in the former no‐till soil. In topsoil, SOC significantly increased from 2007 to 2023 in fertilized treatments of both tillage histories, with the greatest increase observed in fertilized no‐till. Fertilized no‐till also had the highest particulate organic matter content in the topsoil, with no differences among the treatments observed in deeper soil layers. However, regardless of fertilization, the tillage history had a strong effect on stratification with depth of SOC, total N, and microbial biomass C. Results suggested that historic and ongoing N fertilization had a substantial impact on switchgrass growth and soil characteristics, while tillage legacy had a much weaker, but still discernible, effect. 

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