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Abstract Crop N decision support tools are typically based on either empirical relationships that lack mechanistic underpinnings or simulation models that are too complex to use on farms with limited input data. We developed an N mineralization model for corn that lies between these endpoints; it includes a mechanistic model structure reflecting microbial and texture controls on N mineralization but requires just a few simple inputs: soil texture soil C and N concentration and cover crop N content and carbon to nitgrogen ratio (C/N). We evaluated a previous version of the model with an independent dataset to determine the accuracy in predictions of unfertilized corn (Zea maysL.) yield across a wider range of soil texture, cover crop, and growing season precipitation conditions. We tested three assumptions used in the original model: (1) soil C/N is equal to 10, (2) yield does not need to be adjusted for growing season precipitation, and (3) sand content controls humification efficiency (ε). The best new model used measured values for soil C/N, had a summertime precipitation adjustment, and included both sand and clay content as predictors ofε(root mean square error [RMSE] = 1.43 Mg ha⁻¹;r² = 0.69). In the new model, clay has a stronger influence than sand onε, corresponding to lower predicted mineralization rates on fine‐textured soils. The new model had a reasonable validation fit (RMSE = 1.71 Mg ha⁻¹;r² = 0.56) using an independent dataset. Our results indicate the new model is an improvement over the previous version because it predicts unfertilized corn yield for a wider range of conditions. 

Abstract Agricultural fields in drylands are challenged globally by limited freshwater resources for irrigation and also by elevated soil salinity and sodicity. It is well known that pedogenic carbonate is less soluble than evaporate salts and commonly forms in natural drylands. However, few studies have evaluated how irrigation loads dissolved calcium and bicarbonate to agricultural fields, accelerating formation rates of secondary calcite and simultaneously releasing abiotic CO₂to the atmosphere. This study reports one of the first geochemical and isotopic studies of such “anthropogenic” pedogenic carbonates and CO₂from irrigated drylands of southwestern United States. A pecan orchard and an alfalfa field, where flood-irrigation using the Rio Grande river is a common practice, were compared to a nearby natural dryland site. Strontium and carbon isotope ratios show that bulk pedogenic carbonates in irrigated soils at the pecan orchard primarily formed due to flood-irrigation, and that approximately 20–50% of soil CO₂in these irrigated soils is calcite-derived abiotic CO₂instead of soil-respired or atmospheric origins. Multiple variables that control the salt buildup in this region are identified and impact the crop production and soil sustainability regionally and globally. Irrigation intensity and water chemistry (irrigation water quantity and quality) dictate salt loading, and soil texture governs water infiltration and salt leaching. In the study area, agricultural soils have accumulated up to 10 wt% of calcite after just about 100 years of cultivation. These rates will likely increase in the future due to the combined effects of climate variability (reduced rainfall and more intense evaporation), use of more brackish groundwater for irrigation, and reduced porosity in soils. The enhanced accumulation rates of pedogenic carbonate are accompanied by release of large amounts of abiotic CO₂from irrigated drylands to atmosphere. Extensive field studies and modelling approaches are needed to further quantify these effluxes at local, regional and global scales. 

Abstract. Data collected from research networks presentopportunities to test theories and develop models about factors responsiblefor the long-term persistence and vulnerability of soil organic matter(SOM). Synthesizing datasets collected by different research networkspresents opportunities to expand the ecological gradients and scientificbreadth of information available for inquiry. Synthesizing these data ischallenging, especially considering the legacy of soil data that havealready been collected and an expansion of new network science initiatives.To facilitate this effort, here we present the SOils DAta Harmonizationdatabase (SoDaH; https://lter.github.io/som-website, last access: 22 December 2020), a flexible database designed to harmonize diverse SOM datasets frommultiple research networks. SoDaH is built on several network scienceefforts in the United States, but the tools built for SoDaH aim to providean open-access resource to facilitate synthesis of soil carbon data.Moreover, SoDaH allows for individual locations to contribute results fromexperimental manipulations, repeated measurements from long-term studies,and local- to regional-scale gradients across ecosystems or landscapes.Finally, we also provide data visualization and analysis tools that can beused to query and analyze the aggregated database. The SoDaH v1.0 dataset isarchived and availableat https://doi.org/10.6073/pasta/9733f6b6d2ffd12bf126dc36a763e0b4 (Wieder et al., 2020).