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Creators/Authors contains: "Goel, Ramesh"

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  1. Free, publicly-accessible full text available April 1, 2026
  2. Processes driving nutrient retention in stormwater green infrastructure (SGI) are not well quantified in water-limited biomes. We examined the role of plant diversity and physiochemistry as drivers of microbial community physiology and soil N dynamics post precipitation pulses in a semi-arid region experiencing drought. We conducted our study in bioswales receiving experimental water additions and a montane meadow intercepting natural rainfall. Pulses of water generally elevated soil moisture and pH, stimulated ecoenzyme activity (EEA), and increased the concentration of organic matter, proteins, and N pools in both bioswale and meadow soils. Microbial community growth was static, and N assimilation into biomass was limited across pulse events. Unvegetated plots had greater soil moisture than vegetated plots at the bioswale site, yet we detected no clear effect of plant diversity on microbial C:N ratios, EEAs, organic matter content, and N pools. Differences in soil N concentrations in bioswales and the meadow were most directly correlated to changes in organic matter content mediated by ecoenzyme expression and the balance of C, N, and P resources available to microbial communities. Our results add to growing evidence that SGI ecological function is largely comparable to neighboring natural vegetated systems, particularly when soil media and water availability are similar. 
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  3. Recycling underutilized resources from food waste (FW) to agriculture through hydrothermal carbonization (HTC) has been proposed to promote a circular economy (CE) in food-energy-water (FEW) nexus. However, most HTC studies on FW were conducted at laboratory scale, and little is known on the efficacy and feasibility of field application of HTC products from FW, i.e. the aqueous phrase (AP) and solid hydrochar (HC), to support agriculture production. An integrated pilot-scale HTC system was established to investigate practical HTC reaction conditions treating FW. A peak temperature of 180 â—¦C at a residence time of 60 min with 3 times AP recirculation were recommended as optimal HTC conditions to achieve efficient recovery of nutrients, and desirable AP and HC properties for agriculture application. Dilution of the raw AP and composting of the fresh HC are necessary as post-treatments to eliminate potential phytotoxicity. Applying properly diluted AP and the composted HC significantly improved plant growth and nutrient availability in both greenhouse and field trials, which were comparable to commercial chemical fertilizer and soil amendment. The HTC of FW followed with agricultural application of the products yielded net negative carbon emission of ô€€€ 0.28 t CO2e tô€€€ 1, which was much lower than the other alternatives of FW treatments. Economic profit could be potentially achieved by valorization of the AP as liquid fertilizer and HC as soil amendment. Our study provides solid evidences demonstrating the technical and economic feasibility of recycling FW to agriculture through HTC as a promising CE strategy to sustain the FEW nexus. 
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  4. R code for Hastings, Y. D. (2022). Green Infrastructure Microbial Community Response to Simulated Pulse Precipitation Events in the Semi-Arid Western United States (Master's thesis, The University of Utah). This study was supported by a grant from the US National Science Foundation (DEB 2006308). R code for and Hastings, Y. D., et al. Green Infrastructure Microbial Community Response to Simulated Pulse Precipitation Events in the Semi-Arid Western United States. In review. Abstract: Nutrient retention in urban stormwater green infrastructure (SGI) of water-limited biomes is not well quantified, especially when stormwater inputs are scarce. We examined the role of plant diversity and physiochemistry as drivers of microbial community physiology and soil N pools and fluxes in bioswales subjected to simulated precipitation and a montane meadow experiencing natural rainfall within a semi-arid region during drought. Precipitation generally elevated soil moisture and pH, stimulated ecoenzyme activity, and increased the concentration of organic matter, proteins, and N pools in both bioswale and meadow soils; but the magnitude of change differed between events. Microbial community growth was static and N assimilation into biomass was limited across precipitation events. Unvegetated SGI plots had greater soil moisture, yet effects of plant diversity treatments on microbial C:N ratios, organic matter content, and N pools were inconsistent. Differences in soil N concentrations in bioswales and the meadow were most directly correlated to changes in organic matter content mediated by ecoenzyme expression and the balance of C, N, and P resources available to microbial communities. Our results add to growing evidence that ecological function of SGI is comparable to neighboring natural vegetated systems, particularly when soil media and water availability are similar. The file and R code structure is as follows: Data - Contains all data used for the analysis Results - Contains all figures, RMANOVA, and Piecewise Structural Equation Modeling results. renv - R environment used for project EEA_Vector_Analysis.R - R code used to analyze coenzyme (EEA) responses, including RMANOVA to look for significant differences in EEA response to simulated pulse events and Vector Analysis to determine the nutrient resource acquisition. Gravimetric_soil_moisture_pH.R - R code used for RMANOVA of gravimetric soil moisture and pH responses to simulated pulse events. MicrobialBiomass_EEA.Rproj - Downloaded R project Microbial_biomass.R - R code used for RMANOVA of microbial biomass carbon, nitrogen, and C:N responses to simulated pulse events. OM_protien_N_pools_fluxes.R - R code used for RMANOVA of organic matter content, proteins, and N pools and fluxes responses to simulated pulse events. PSEM_final.R - R code used for Pearson Correlation and Piecewise Structural Equation Modeling. Rclimate.R - R code used to obtain summary statistics of climate data from GIRF and TM climate and soil sensors. 
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