A Soil Parameters Geodatabase for the Modeling Assessment of Agricultural Conservation Practices Effects in the United States

Soil parameters for hydrology modeling in cropland dominated areas, from the regional to local scale, are part of critical biophysical information whose deficiency may increase the uncertainty of simulated conservation effects and predicting potential. Despite this importance, soil physical and hydraulic parameters lack common, wide-coverage repositories combined to digital maps as required by various hydrology-based agricultural water quality models. This paper describes the construction of a geoprocessing workflow and the resultant hydrology-structured soil hydraulic, physical, and chemical parameters geographic database for the entire United States, named US-SOILM-CEAP. This database is designed to store a-priori values for a suit of models, such as SWAT (Soil and Water Assessment Tool), APEX (Agricultural Policy Environmental EXtender) and ALMANAC (Agricultural Land Management Alternatives with Numerical Assessment Criteria), which are commonly used for the across scale assessment of agricultural hydrology and conservation practice scenarios. The Soil Survey Geographic (SSURGO) database developed by the U.S. Department of Agriculture provided the main source data for this development. Additional spatial information, a geographic information system platform and Python computer programming language code were used to create hydrology-based tile coverage of the areal soil units linked to the specific and detailed attributes required by each model. The created repository adds value to the source soil survey data, while maintaining and extending the detailed information necessary for the across scale and combined application of the models. Ultimately, our multi-model database provides a comprehensive product achieving joined informational-mapping-geoprocessing functionality with the explicit maintenance of the original conceptual links between soil series and composing soil layers, allowing for efficient data retrieval, analysis and service as input for modeling conservation effects

Advancement of a Soil Parameters Geodatabase for the Modeling Assessment of Conservation Practice Outcomes in the United States

US-ModSoilParms-TEMPLE is a database composed of a set of geographic databases functionally storing soil-spatial units and soil hydraulic, physical, and chemical parameters for three agriculture management simulation models, SWAT, APEX, and ALMANAC. This paper introduces the updated US-ModSoilParms-TEMPLE, which covers the entire United States and is organized as a framework of 22 nested and hydrologically-ordered regional geographic databases with internal spatial segmentation drainage-defined at a conveniently manageable tile (Watershed Boundary Dataset’s, WBD, 8-digit Subbasin) level. Spatial features are stored in multiple formats (raster and vector) and resolutions (10-meter and 30-meter), while being in direct relationship with the table of attributes storing the models’ parameters. A significant number of former parameter voids, determined by the local incompleteness of the source datasets, were filled using a methodology leveraging upon the hierarchy of the Soil Taxonomy information and the geographic location of the gaps. The functionality of each geographic database was extended by adding customized tools, which streamline the incorporation into geoprocessing workflows, the aggregation and extraction of data sets, and finally the export to other model support software user environments. These tools are attached and conveniently distributed along with detailed metadata documentation within each of the developed regional geographic databases. The system hosting this framework is developed using a proprietary software format (ESRI® File Geodatabase), however, a companion version of the framework of 8-digit tiles is also developed and provided using openly accessible formats. The experience shared in this paper might help other efforts in developing hydrology-oriented geographical databases

Validation of EPIC for Two Watersheds in Southwest Iowa

The Erosion Productivity Impact Calculator (EPIC) model is validated using long-term data collected for two southwest Iowa watersheds that have been cropped in continuous corn under two different tillage systems. The annual hydrologic balance was calibrated during 1988-94 by adjusting the runoff curve numbers and residue effects on soil evaporation. Model validation was performed for 1976-87 using both summary statistics and parametric and nonparametric statistical tests. Overall, results show that EPIC was able to replicate the long-term relative differences between the two tillage systems

Economic Potential of Greenhouse Gas Emission Reductions: Comparative Role for Soil Sequestration in Agriculture and Forestry

We use the Agricultural Sector Model to analyze the economic potential of soil carbon sequestration as one of several agricultural greenhouse gas emission mitigation strategies, including afforestation. For low incentives on carbon emission savings, agricultural soil carbon sequestration is the most cost-efficient strategy. As incentive levels increase above $50 per ton of carbon equivalent, afforestation and biofuel production become the key strategies, while the role of soil carbon diminishes. If saturating sinks are discounted based on their net present value, the competitive economic equilibrium among agricultural mitigation strategies shifts away from soil carbon sequestration and afforestation and toward more biofuel production. Regardless of the discounting assumption and the carbon savings incentive level, the economic potential of soil carbon sequestration never attains its technical potential as estimated by soil scientists. The study also estimates the impacts of agricultural mitigation policies on welfare, prices, production, and input use in the traditional food and fiber sector and the effects of emission leakage from unregulated agricultural sources

Control of Stereoselectivity in Diverse Hapalindole Metabolites is Mediated by Cofactor‐Induced Combinatorial Pairing of Stig Cyclases

Stereospecific polycyclic core formation of hapalindoles and fischerindoles is controlled by Stig cyclases through a three‐step cascade involving Cope rearrangement, 6‐exo‐trig cyclization, and a final electrophilic aromatic substitution. Reported here is a comprehensive study of all currently annotated Stig cyclases, revealing that these proteins can assemble into heteromeric complexes, induced by Ca2+, to cooperatively control the stereochemistry of hapalindole natural products.Die stereospezifische Bildung des polycyclischen Kerns der Hapalindole und Fischerindole wird durch Stig‐Cyclasen gesteuert, die eine dreistufige Kaskade aus Cope‐Umlagerung, 6‐exo‐trig‐Cyclisierung und elektrophiler aromatischer Substitution vermitteln. Die Proteine können sich induziert durch Ca2+ zu heterotrimeren Komplexen zusammenlagern, um auf kooperative Weise die Stereochemie zu steuern.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155506/1/ange201913686.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155506/2/ange201913686-sup-0001-misc_information.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155506/3/ange201913686_am.pd

Regional scale cropland carbon budgets: Evaluating a geospatial agricultural modeling system using inventory data

Accurate quantification and clear understanding of regional scale cropland carbon (C) cycling is critical for designing effective policies and management practices that can contribute toward stabilizing atmospheric CO2 concentrations. However, extrapolating site-scale observations to regional scales represents a major challenge confronting the agricultural modeling community. This study introduces a novel geospatial agricultural modeling system (GAMS) exploring the integration of the mechanistic Environmental Policy Integrated Climate model, spatially-resolved data, surveyed management data, and supercomputing functions for cropland C budgets estimates. This modeling system creates spatiallyexplicit modeling units at a spatial resolution consistent with remotely-sensed crop identification and assigns cropping systems to each of them by geo-referencing surveyed crop management information at the county or state level. A parallel computing algorithm was also developed to facilitate the computationally intensive model runs and output post-processing and visualization. We evaluated GAMS against National Agricultural Statistics Service (NASS) reported crop yields and inventory estimated county-scale cropland C budgets averaged over 2000e2008. We observed good overall agreement, with spatial correlation of 0.89, 0.90, 0.41, and 0.87, for crop yields, Net Primary Production (NPP), Soil Organic C (SOC) change, and Net Ecosystem Exchange (NEE), respectively. However, we also detected notable differences in the magnitude of NPP and NEE, as well as in the spatial pattern of SOC change. By performing crop-specific annual comparisons, we discuss possible explanations for the discrepancies between GAMS and the inventory method, such as data requirements, representation of agroecosystem processes, completeness and accuracy of crop management data, and accuracy of crop area representation. Based on these analyses, we further discuss strategies to improve GAMS by updating input data and by designing more efficient parallel computing capability to quantitatively assess errors associated with the simulation of C budget components. The modularized design of the GAMS makes it flexible to be updated and adapted for different agricultural models so long as they require similar input data, and to be linked with socio-economic models to understand the effectiveness and implications of diverse C management practices and policies

Simulating Potential Switchgrass Production in the United States

Using results from field trials of switchgrass (Panicum virgatum L.) in the United States, the EPIC (Environmental Policy Integrated Climate) process-level agroecosystem model was calibrated, validated, and applied to simulate potential productivity of switchgrass for use as a biofuel feedstock. The model was calibrated with a regional study of 10-yr switchgrass field trials and subsequently tested against a separate compiled dataset of field trials from across the eastern half of the country. An application of the model in a national database using 8-digit watersheds as the primary modeling unit produces 30-yr average switchgrass yield estimates that can be aggregated to 18 major watersheds. The model projects average annual switchgrass productivity of greater than 7 Mg ha-1 in the Upper Mississippi, Lower Mississippi, and Ohio watersheds. The major factors limiting simulated production vary by region; low precipitation is the primary limiting factor across the western half of the country, while moderately acidic soils limit yields on lands east of the Mississippi River. Average projected switchgrass production on all crop land in the continental US is 5.6 Mg ha-1. At this level of productivity, 28.6 million hectares of crop land would be required to produce the 16 billion gallons of cellulosic ethanol called for by 2022 in the 2007 Energy Independence and Security Act. The model described here can be applied as a tool to inform the land-use and environmental consequences of switchgrass production

Multi-parallel qPCR provides increased sensitivity and diagnostic breadth for gastrointestinal parasites of humans: field-based inferences on the impact of mass deworming

BACKGROUND: Although chronic morbidity in humans from soil transmitted helminth (STH) infections can be reduced by anthelmintic treatment, inconsistent diagnostic tools make it difficult to reliably measure the impact of deworming programs and often miss light helminth infections. METHODS: Cryopreserved stool samples from 796 people (aged 2-81 years) in four villages in Bungoma County, western Kenya, were assessed using multi-parallel qPCR for 8 parasites and compared to point-of-contact assessments of the same stools by the 2-stool 2-slide Kato-Katz (KK) method. All subjects were treated with albendazole and all Ascaris lumbricoides expelled post-treatment were collected. Three months later, samples from 633 of these people were re-assessed by both qPCR and KK, re-treated with albendazole and the expelled worms collected. RESULTS: Baseline prevalence by qPCR (n = 796) was 17 % for A. lumbricoides, 18 % for Necator americanus, 41 % for Giardia lamblia and 15% for Entamoeba histolytica. The prevalence was <1% for Trichuris trichiura, Ancylostoma duodenale, Strongyloides stercoralis and Cryptosporidium parvum. The sensitivity of qPCR was 98% for A. lumbricoides and N. americanus, whereas KK sensitivity was 70% and 32%, respectively. Furthermore, qPCR detected infections with T. trichiura and S. stercoralis that were missed by KK, and infections with G. lamblia and E. histolytica that cannot be detected by KK. Infection intensities measured by qPCR and by KK were correlated for A. lumbricoides (r = 0.83, p < 0.0001) and N. americanus (r = 0.55, p < 0.0001). The number of A. lumbricoides worms expelled was correlated (p < 0.0001) with both the KK (r = 0.63) and qPCR intensity measurements (r = 0.60). CONCLUSIONS: KK may be an inadequate tool for stool-based surveillance in areas where hookworm or Strongyloides are common or where intensity of helminth infection is low after repeated rounds of chemotherapy. Because deworming programs need to distinguish between populations where parasitic infection is controlled and those where further treatment is required, multi-parallel qPCR (or similar high throughput molecular diagnostics) may provide new and important diagnostic information

Biomass production of herbaceous energy crops in the United States: field trial results and yield potential maps from the multiyear regional feedstock partnership

Current knowledge of yield potential and best agronomic management practices for perennial bioenergy grasses is primarily derived from small-scale and short-term studies, yet these studies inform policy at the national scale. In an effort to learn more about how bioenergy grasses perform across multiple locations and years, the U.S. Department of Energy (US DOE)/Sun Grant Initiative Regional Feedstock Partnership was initiated in 2008. The objectives of the Feedstock Partnership were to (1) provide a wide range of information for feedstock selection (species choice) and management practice options for a variety of regions and (2) develop national maps of potential feedstock yield for each of the herbaceous species evaluated. The Feedstock Partnership expands our previous understanding of the bioenergy potential of switchgrass, Miscanthus, sorghum, energycane, and prairie mixtures on Conservation Reserve Program land by conducting long-term, replicated trials of each species at diverse environments in the U.S. Trials were initiated between 2008 and 2010 and completed between 2012 and 2015 depending on species. Field-scale plots were utilized for switchgrass and Conservation Reserve Program trials to use traditional agricultural machinery. This is important as we know that the smaller scale studies often overestimated yield potential of some of these species. Insufficient vegetative propagules of energycane and Miscanthus prohibited farm-scale trials of these species. The Feedstock Partnership studies also confirmed that environmental differences across years and across sites had a large impact on biomass production. Nitrogen application had variable effects across feedstocks, but some nitrogen fertilizer generally had a positive effect. National yield potential maps were developed using PRISM-ELM for each species in the Feedstock Partnership. This manuscript, with the accompanying supplemental data, will be useful in making decisions about feedstock selection as well as agronomic practices across a wide region of the country

Whipworm genome and dual-species transcriptome analyses provide molecular insights into an intimate host-parasite interaction.

Whipworms are common soil-transmitted helminths that cause debilitating chronic infections in man. These nematodes are only distantly related to Caenorhabditis elegans and have evolved to occupy an unusual niche, tunneling through epithelial cells of the large intestine. We report here the whole-genome sequences of the human-infective Trichuris trichiura and the mouse laboratory model Trichuris muris. On the basis of whole-transcriptome analyses, we identify many genes that are expressed in a sex- or life stage-specific manner and characterize the transcriptional landscape of a morphological region with unique biological adaptations, namely, bacillary band and stichosome, found only in whipworms and related parasites. Using RNA sequencing data from whipworm-infected mice, we describe the regulated T helper 1 (TH1)-like immune response of the chronically infected cecum in unprecedented detail. In silico screening identified numerous new potential drug targets against trichuriasis. Together, these genomes and associated functional data elucidate key aspects of the molecular host-parasite interactions that define chronic whipworm infection