Examining Antimicrobial Resistance in Escherichia coli: A Case Study in Central Virginia's Environment.

While environmental factors may contribute to antimicrobial resistance (AMR) in bacteria, many aspects of environmental antibiotic pollution and resistance remain unknown. Furthermore, the level of AMR in Escherichia coli is considered a reliable indicator of the selection pressure exerted by antimicrobial use in the environment. This study aimed to assess AMR variance in E. coli isolated from diverse environmental samples, such as animal feces and water from wastewater treatment plants (WWTPs) and drainage areas of different land use systems in Central Virginia. In total, 450 E. coli isolates obtained between August 2020 and February 2021 were subjected to susceptibility testing against 12 antimicrobial agents approved for clinical use by the U.S. Food and Drug Administration. Approximately 87.8% of the tested isolates were resistant to at least one antimicrobial agent, with 3.1% showing multi-drug resistance. Streptomycin resistance was the most common (73.1%), while susceptibility to chloramphenicol was the highest (97.6%). One isolate obtained from WWTPs exhibited resistance to seven antimicrobials. AMR prevalence was the highest in WWTP isolates, followed by isolates from drainage areas, wild avians, and livestock. Among livestock, horses had the highest AMR prevalence, while cattle had the lowest. No significant AMR difference was found across land use systems. This study identifies potential AMR hotspots, emphasizing the environmental risk for antimicrobial resistant E. coli. The findings will aid policymakers and researchers, highlighting knowledge gaps in AMR-environment links. This nationally relevant research offers a scalable AMR model for understanding E. coli ecology. Further large-scale research is crucial to confirm the environmental impacts on AMR prevalence in bacteria.

Quantitative Representativeness and Constituency of the Long-Term Agroecosystem Research Network and Analysis of Complementarity with Existing Ecological Networks.

Studies conducted at sites across ecological research networks usually strive to scale their results to larger areas, trying to reach conclusions that are valid throughout larger enclosing regions. Network representativeness and constituency can show how well conditions at sampling locations represent conditions also found elsewhere and can be used to help scale-up results over larger regions. Multivariate statistical methods have been used to design networks and select sites that optimize regional representation, thereby maximizing the value of datasets and research. However, in networks created from already established sites, an immediate challenge is to understand how well existing sites represent the range of environments in the whole area of interest. We performed an analysis to show how well sites in the USDA Long-Term Agroecosystem Research (LTAR) Network represent all agricultural working lands within the conterminous United States (CONUS). Our analysis of 18 LTAR sites, based on 15 climatic and edaphic characteristics, produced maps of representativeness and constituency. Representativeness of the LTAR sites was quantified through an exhaustive pairwise Euclidean distance calculation in multivariate space, between the locations of experiments within each LTAR site and every 1 km cell across the CONUS. Network representativeness is from the perspective of all CONUS locations, but we also considered the perspective from each LTAR site. For every LTAR site, we identified the region that is best represented by that particular site-its constituency-as the set of 1 km grid locations best represented by the environmental drivers at that particular LTAR site. Representativeness shows how well the combination of characteristics at each CONUS location was represented by the LTAR sites' environments, while constituency shows which LTAR site was the closest match for each location. LTAR representativeness was good across most of the CONUS. Representativeness for croplands was higher than for grazinglands, probably because croplands have more specific environmental criteria. Constituencies resemble ecoregions but have their environmental conditions "centered" on those at particular existing LTAR sites. Constituency of LTAR sites can be used to prioritize the locations of experimental research at or even within particular sites, or to identify the extents that can likely be included when generalizing knowledge across larger regions of the CONUS. Sites with a large constituency have generalist environments, while those with smaller constituency areas have more specialized environmental combinations. These "specialist" sites are the best representatives for smaller, more unusual areas. The potential of sharing complementary sites from the Long-Term Ecological Research (LTER) Network and the National Ecological Observatory Network (NEON) to boost representativeness was also explored. LTAR network representativeness would benefit from borrowing several NEON sites and the Sevilleta LTER site. Later network additions must include such specialist sites that are targeted to represent unique missing environments. While this analysis exhaustively considered principal environmental characteristics related to production on working lands, we did not consider the focal agronomic systems under study, or their socio-economic context.

Uncertainty in phosphorus fluxes and budgets across the US long-term agroecosystem research network.

Phosphorus (P) budgets can be useful tools for understanding nutrient cycling and quantifying the effectiveness of nutrient management planning and policies; however, uncertainties in agricultural nutrient budgets are not often quantitatively assessed. The objective of this study was to evaluate uncertainty in P fluxes (fertilizer/manure application, atmospheric deposition, irrigation, crop removal, surface runoff, and leachate) and the propagation of these uncertainties to annual P budgets. Data from 56 cropping systems in the P-FLUX database, which spans diverse rotations and landscapes across the United States and Canada, were evaluated. Results showed that across cropping systems, average annual P budget was 22.4 kg P ha-1 (range = -32.7 to 340.6 kg P ha-1 ), with an average uncertainty of 13.1 kg P ha-1 (range = 1.0-87.1 kg P ha-1 ). Fertilizer/manure application and crop removal were the largest P fluxes across cropping systems and, as a result, accounted for the largest fraction of uncertainty in annual budgets (61% and 37%, respectively). Remaining fluxes individually accounted for <2% of the budget uncertainty. Uncertainties were large enough that determining whether P was increasing, decreasing, or not changing was inconclusive in 39% of the budgets evaluated. Findings indicate that more careful and/or direct measurements of inputs, outputs, and stocks are needed. Recommendations for minimizing uncertainty in P budgets based on the results of the study were developed. Quantifying, communicating, and constraining uncertainty in budgets among production systems and multiple geographies is critical for engaging stakeholders, developing local and national strategies for P reduction, and informing policy.

Indicators of water use efficiency across diverse agroecosystems and spatiotemporal scales.

Understanding the relationship between water and production within and across agroecosystems is essential for addressing several agricultural challenges of the 21st century: providing food, fuel, and fiber to a growing human population, reducing the environmental impacts of agricultural production, and adapting food systems to climate change. Of all human activities, agriculture has the highest demand for water globally. Therefore, increasing water use efficiency (WUE), or producing 'more crop per drop', has been a long-term goal of agricultural management, engineering, and crop breeding. WUE is a widely used term applied across a diverse array of spatial scales, spanning from the leaf to the globe, and over temporal scales ranging from seconds to months to years. The measurement, interpretation, and complexity of WUE varies enormously across these spatial and temporal scales, challenging comparisons within and across diverse agroecosystems. The goals of this review are to evaluate common indicators of WUE in agricultural production and assess tradeoffs when applying these indicators within and across agroecosystems amidst a changing climate. We examine three questions: (1) what are the uses and limitations of common WUE indicators, (2) how can WUE indicators be applied within and across agroecosystems, and (3) how can WUE indicators help adapt agriculture to climate change? Addressing these agricultural challenges will require land managers, producers, policy makers, researchers, and consumers to evaluate costs and benefits of practices and innovations of water use in agricultural production. Clearly defining and interpreting WUE in the most scale-appropriate way is crucial for advancing agroecosystem sustainability.

Escherichia cryptic clade II through clade VIII: Rapid detection and prevalence in feces and surface water.

Bacteria of the cryptic lineage of genus Escherichia, or Escherichia cryptic clades (cryptic clades), are phenotypically indistinguishable from Escherichia coli (E. coli) using standard biochemical tests. Except for clade I (C-I), cryptic clades were hypothetically believed to be environmental but not enteric. If so, they would hinder the interpretation of current E. coli-based water quality (fecal pollution) monitoring in the United States because environmental bacteria do not indicate the presence of harmful fecal material. This study was performed to develop a rapid method for the detection of cryptic clades and to investigate their potential impact on water quality monitoring. By whole-genome comparison, one gene, named ecc (Escherichiacryptic clades), was identified to be unique to C-II through C-VIII. An end-point polymerase chain reaction (PCR) method, eccPCR, was developed by targeting the ecc. The results of in-silico and wet tests demonstrated 100 % sensitivity and specificity of the eccPCR to detect C-II through C-VIII. Based on the EPA Method 1603, 519 presumptive E. coli isolates were obtained from the fecal samples of 13 different host species and 192 isolates from surface water samples taken at four locations in a watershed of mid-Missouri. As indicated by the eccPCR amplification, the overall prevalence of C-II through C-VIII in the presumptive E. coli isolates was estimated to be about 0.6 % in the fecal samples and about 1.6 % in the water samples. Therefore, the potential impact of cryptic clades on water quality monitoring may be limited if EPA Method 1603 is used. Furthermore, clades C-II through C-VIII in stream water samples were found repeatedly only at a single sampling site, but neither at the upstream sites nor five kilometers downstream of the site. The data do not support nor reject the environmental hypothesis about cryptic clades. Further study is needed to determine the implication of the observation.

Development of PLEAD: A Database Containing Event-based Runoff Phosphorus Loadings from Agricultural Fields.

Computer models are commonly used for predicting risks of runoff P loss from agricultural fields by enabling simulation of various management practices and climatic scenarios. For P loss models to be useful tools, however, they must accurately predict P loss for a wide range of climatic, physiographic, and land management conditions. A complicating factor in developing and evaluating P loss models is the relative scarcity of available measured field data that adequately capture P losses before and after implementing management practices in a variety of physiographic settings. Here, we describe the development of the P Loss in runoff Events from Agricultural fields Database (PLEAD)-a compilation of event-based, field-scale dissolved and/or total P loss runoff loadings from agricultural fields collected at various research sites located in the US Heartland and southern United States. The database also includes runoff and erosion rates; soil-test P; tillage practices; planting and harvesting rates and practices; fertilizer application rate, method, and timing; manure application rate, method, and timing; and livestock grazing density and timing. In total, >1800 individual runoff events-ranging in duration from 0.4 to 97 h-have been included in the database. Event runoff P losses ranged from <0.05 to 1.3 and 3.0 kg P ha for dissolved and total P, respectively. The data contained in this database have been used in multiple research studies to address important modeling questions relevant to P management planning. We provide these data to encourage additional studies by other researchers. The PLEAD database is available at .

Evaluation of Phosphorus Site Assessment Tools: Lessons from the USA.

Critical source area identification through phosphorus (P) site assessment is a fundamental part of modern nutrient management planning in the United States, yet there has been only sparse testing of the many versions of the P Index that now exist. Each P site assessment tool was developed to be applicable across a range of field conditions found in a given geographic area, making evaluation extremely difficult. In general, evaluation with in-field monitoring data has been limited, focusing primarily on corroborating manure and fertilizer "source" factors. Thus, a multiregional effort (Chesapeake Bay, Heartland, and Southern States) was undertaken to evaluate P Indices using a combination of limited field data, as well as output from simulation models (i.e., Agricultural Policy Environmental eXtender, Annual P Loss Estimator, Soil and Water Assessment Tool [SWAT], and Texas Best Management Practice Evaluation Tool [TBET]) to compare against P Index ratings. These comparisons show promise for advancing the weighting and formulation of qualitative P Index components but require careful vetting of the simulation models. Differences among regional conclusions highlight model strengths and weaknesses. For example, the Southern States region found that, although models could simulate the effects of nutrient management on P runoff, they often more accurately predicted hydrology than total P loads. Furthermore, SWAT and TBET overpredicted particulate P and underpredicted dissolved P, resulting in correct total P predictions but for the wrong reasons. Experience in the United States supports expanded regional approaches to P site assessment, assuming closely coordinated efforts that engage science, policy, and implementation communities, but limited scientific validity exists for uniform national P site assessment tools at the present time.

Multisite Evaluation of APEX for Water Quality: I. Best Professional Judgment Parameterization.

The Agricultural Policy Environmental eXtender (APEX) model is capable of estimating edge-of-field water, nutrient, and sediment transport and is used to assess the environmental impacts of management practices. The current practice is to fully calibrate the model for each site simulation, a task that requires resources and data not always available. The objective of this study was to compare model performance for flow, sediment, and phosphorus transport under two parameterization schemes: a best professional judgment (BPJ) parameterization based on readily available data and a fully calibrated parameterization based on site-specific soil, weather, event flow, and water quality data. The analysis was conducted using 12 datasets at four locations representing poorly drained soils and row-crop production under different tillage systems. Model performance was based on the Nash-Sutcliffe efficiency (NSE), the coefficient of determination () and the regression slope between simulated and measured annualized loads across all site years. Although the BPJ model performance for flow was acceptable (NSE = 0.7) at the annual time step, calibration improved it (NSE = 0.9). Acceptable simulation of sediment and total phosphorus transport (NSE = 0.5 and 0.9, respectively) was obtained only after full calibration at each site. Given the unacceptable performance of the BPJ approach, uncalibrated use of APEX for planning or management purposes may be misleading. Model calibration with water quality data prior to using APEX for simulating sediment and total phosphorus loss is essential.

Multisite Evaluation of APEX for Water Quality: II. Regional Parameterization.

Phosphorus (P) Index assessment requires independent estimates of long-term average annual P loss from fields, representing multiple climatic scenarios, management practices, and landscape positions. Because currently available measured data are insufficient to evaluate P Index performance, calibrated and validated process-based models have been proposed as tools to generate the required data. The objectives of this research were to develop a regional parameterization for the Agricultural Policy Environmental eXtender (APEX) model to estimate edge-of-field runoff, sediment, and P losses in restricted-layer soils of Missouri and Kansas and to assess the performance of this parameterization using monitoring data from multiple sites in this region. Five site-specific calibrated models (SSCM) from within the region were used to develop a regionally calibrated model (RCM), which was further calibrated and validated with measured data. Performance of the RCM was similar to that of the SSCMs for runoff simulation and had Nash-Sutcliffe efficiency (NSE) > 0.72 and absolute percent bias (|PBIAS|) < 18% for both calibration and validation. The RCM could not simulate sediment loss (NSE < 0, |PBIAS| > 90%) and was particularly ineffective at simulating sediment loss from locations with small sediment loads. The RCM had acceptable performance for simulation of total P loss (NSE > 0.74, |PBIAS| < 30%) but underperformed the SSCMs. Total P-loss estimates should be used with caution due to poor simulation of sediment loss. Although we did not attain our goal of a robust regional parameterization of APEX for estimating sediment and total P losses, runoff estimates with the RCM were acceptable for P Index evaluation.

Calibration of the APEX Model to Simulate Management Practice Effects on Runoff, Sediment, and Phosphorus Loss.

Process-based computer models have been proposed as a tool to generate data for Phosphorus (P) Index assessment and development. Although models are commonly used to simulate P loss from agriculture using managements that are different from the calibration data, this use of models has not been fully tested. The objective of this study is to determine if the Agricultural Policy Environmental eXtender (APEX) model can accurately simulate runoff, sediment, total P, and dissolved P loss from 0.4 to 1.5 ha of agricultural fields with managements that are different from the calibration data. The APEX model was calibrated with field-scale data from eight different managements at two locations (management-specific models). The calibrated models were then validated, either with the same management used for calibration or with different managements. Location models were also developed by calibrating APEX with data from all managements. The management-specific models resulted in satisfactory performance when used to simulate runoff, total P, and dissolved P within their respective systems, with > 0.50, Nash-Sutcliffe efficiency > 0.30, and percent bias within ±35% for runoff and ±70% for total and dissolved P. When applied outside the calibration management, the management-specific models only met the minimum performance criteria in one-third of the tests. The location models had better model performance when applied across all managements compared with management-specific models. Our results suggest that models only be applied within the managements used for calibration and that data be included from multiple management systems for calibration when using models to assess management effects on P loss or evaluate P Indices.

Long-term agroecosystem research in the central Mississippi river basin: goodwater creek experimental watershed flow data.

Flow monitoring in Goodwater Creek Experimental Watershed started in 1971 at three nested watersheds ranging from 12 to 73 km. Since then, runoff or stream flow has been measured at 14 plots, three fields, and 12 additional stream sites ranging from 0.0034 to 6067 km in the Central Mississippi River Basin. Long-term data sets are important to document the changes resulting from anthropogenic and natural drivers. The data set presented here documents discharge across a range of catchment sizes in an area known for its high runoff potential. It constitutes the flow database of the Central Mississippi River Basin site of the Long-Term Agricultural Research network. Like the other sites of this network, data are accessible through the STEWARDS web interface (). Here we (i) describe the data collection methods, (ii) document the data available at plot, field, and watershed scales, and (iii) provide the main characteristics of discharge. General characteristics of discharge per unit area for different cropping system management systems show that in this claypan soil setting, management and tillage of row crop systems do not affect surface flow during the growing season (April-October). Data from fields and stream sites show the dampening of peak flow values and lengthening of storm hydrographs caused by mixed land uses and longer times of concentration. Overall, stream flow accounts for a third of the precipitation, of which 80% is from surface runoff and 20% is from groundwater.

Long-term agroecosystem research in the central Mississippi river basin: introduction, establishment, and overview.

Many challenges currently facing agriculture require long-term data on landscape-scale hydrologic responses to weather, such as from the Goodwater Creek Experimental Watershed (GCEW), located in northeastern Missouri, USA. This watershed is prone to surface runoff despite shallow slopes, as a result of a significant smectitic clay layer 30 to 50 cm deep that restricts downward flow of water and gives rise to a periodic perched water table. This paper is the first in a series that documents the database developed from GCEW. The objectives of this paper are to (i) establish the context of long-term data and the federal infrastructure that provides it, (ii) describe the GCEW/ Central Mississippi River Basin (CMRB) establishment and the geophysical and anthropogenic context, (iii) summarize in brief the collected research results published using data from within GCEW, (iv) describe the series of papers this work introduces, and (v) identify knowledge gaps and research needs. The rationale for the collection derives from converging trends in data from long-term research, integration of multiple disciplines, and increasing public awareness of increasingly larger problems. The outcome of those trends includes being selected as the CMRB site in the USDA-ARS Long-Term Agro-Ecosystem Research (LTAR) network. Research needs include quantifying watershed scale fluxes of N, P, K, sediment, and energy, accounting for fluxes involving forest, livestock, and anthropogenic sources, scaling from near-term point-scale results to increasingly long and broad scales, and considering whole-system interactions. This special section informs the scientific community about this database and provides support for its future use in research to solve natural resource problems important to US agricultural, environmental, and science policy.

Long-Term Agroecosystem Research in the Central Mississippi River Basin: SWAT Simulation of Flow and Water Quality in the Goodwater Creek Experimental Watershed.

Starting in 1971, stream flow and climatologic data have been collected in the Goodwater Creek Experimental Watershed, which is part of the Central Mississippi River Basin (CMRB) Long-Term Agroecosystem Research (LTAR) site. Since 1992, water quality and socio-economic data have complemented these data sets. Previous modeling efforts highlighted the challenges created by the presence of a claypan. Specific changes were introduced in the Soil and Water Assessment Tool (SWAT) (i) to better simulate percolation through and saturation above the claypan and (ii) to simulate the spatial and temporal distributions of the timing of field operations throughout the watershed. Our objectives were to document the changes introduced into the code, demonstrate that these changes improved simulation results, describe the model's parameterization, calibration, and validation, and assess atrazine [6-chloro--ethyl-'-(1-methylethyl)-1,3,5-triazine-2,4-diamine] management practices in the hydrologic context of claypan soils. Model calibration was achieved for 1993 to 2010 at a daily time step for flow and at a monthly time step for water quality constituents. The new percolation routines ensured correct balance between surface runoff and groundwater. The temporal heterogeneity of atrazine application ensured the correct frequency of daily atrazine loads. Atrazine incorporation by field cultivation resulted in a 17% simulated reduction in atrazine load without a significant increase in sediment yields. Reduced atrazine rates produced proportional reductions in simulated atrazine transport. The model can be used to estimate the impact of other drivers, e.g., changing aspects of climate, land use, cropping systems, tillage, or management practices, in this context.

Evaluation of a Stepwise, Multiobjective, Multivariable Parameter Optimization Method for the APEX Model.

Hydrologic models are essential tools for environmental assessment of agricultural nonpoint-source pollution. The automatic calibration of hydrologic models, though efficient, demands significant computational power, limiting their application. The study objective was to develop and evaluate a stepwise, multiobjective, multivariable automatic calibration method for the Agricultural Environmental Policy eXtender (APEX) model for simulating runoff, sediment, total phosphorus (TP), and total nitrogen (TN). The most sensitive parameters were grouped according to the process they primarily affect (runoff, sediment transport, soil biological activity, TP transport, and TN transport) and were optimized separately and consecutively. Two multiobjective functions comprising combinations of coefficient of determination (), regression slope, and Nash-Sutcliffe coefficient (NSC) and a global objective function, the Generalized Likelihood Uncertainty Estimation, were considered to select the optimal parameter combination. A previously manually calibrated and validated APEX model for three adjacent row-crop field-size watersheds in northeast Missouri was used as the baseline. The greatest improvements in model performance for sediment, TP, and TN, but not for runoff, were found after runoff parameter optimization, indicating that runoff parameter optimization was crucial for good simulation of sediment and nutrients. The values for sediment, TP, and TN improved from 0.59-0.87 to 0.77-0.94. The NSC values for TP also improved after soil biological activity and TP parameter optimizations, but subsequent optimizations did not improve sediment or TN simulations. The objective function based on , slope, and NSC outperformed the other objective functions. Modelers can benefit from this cost-efficient optimization technique (2570 runs for 23 parameters).

Agricultural Policy Environmental eXtender Simulation of Three Adjacent Row-Crop Watersheds in the Claypan Region.

The Agricultural Policy Environmental Extender (APEX) model is used to evaluate best management practices on pollutant loading in whole farms or small watersheds. The objectives of this study were to conduct a sensitivity analysis to determine the effect of model parameters on APEX output and use the parameterized, calibrated, and validated model to evaluate long-term benefits of grass waterways. The APEX model was used to model three (East, Center, and West) adjacent field-size watersheds with claypan soils under a no-till corn ( L.)/soybean [ (L.) Merr.] rotation. Twenty-seven parameters were sensitive for crop yield, runoff, sediment, nitrogen (dissolved and total), and phosphorous (dissolved and total) simulations. The model was calibrated using measured event-based data from the Center watershed from 1993 to 1997 and validated with data from the West and East watersheds. Simulated crop yields were within ±13% of the measured yield. The model performance for event-based runoff was excellent, with calibration and validation > 0.9 and Nash-Sutcliffe coefficients (NSC) > 0.8, respectively. Sediment and total nitrogen calibration results were satisfactory for larger rainfall events (>50 mm), with > 0.5 and NSC > 0.4, but validation results remained poor, with NSC between 0.18 and 0.3. Total phosphorous was well calibrated and validated, with > 0.8 and NSC > 0.7, respectively. The presence of grass waterways reduced annual total phosphorus loadings by 13 to 25%. The replicated study indicates that APEX provides a convenient and efficient tool to evaluate long-term benefits of conservation practices.

Specificity of a Bacteroides thetaiotaomicron marker for human feces.

A bacterial primer set, known to produce a 542-bp amplicon specific for Bacteroides thetaiotaomicron, generated this product in PCR with 1 ng of extracted DNA from 92% of 25 human fecal samples, 100% of 20 sewage samples, and 16% of 31 dog fecal samples. The marker was not detected in 1 ng of fecal DNA from 61 cows, 35 horses, 44 pigs, 24 chickens, 29 turkeys, and 17 geese.