Conservation Effects Assessment Project Research Articles

An Application of a Small Area Procedure with Correlation Between Measurement Error and Sampling Error to the Conservation Effects Assessment Project

County level estimates of mean sheet and rill erosion from the Conservation Effects Assessment Project (CEAP) are useful for program development and evaluation. Since county sample sizes in the CEAP survey are insufficient to support reliable direct estimators, small area estimation procedures are needed. The quantity of water runoff is a useful covariate but is unavailable for the full population. We use an estimate of mean runoff from the CEAP survey as a covariate in a small area model with sheet and rill erosion as the response. As the runoff and sheet and rill erosion are estimators from the same survey, the measurement error in the covariate is important as is the correlation between the measurement error and the sampling error. We conduct a detailed investigation of small area estimation in the presence of a correlation between the measurement error in the covariate and the sampling error in the response. In simulations, the proposed predictor is superior to small area predictors that assume the response and covariate are uncorrelated or that ignore the measurement error entirely.

Assessing Soil Vulnerability Index classification with respect to rainfall characteristics

The Soil Vulnerability Index (SVI) uses widely available inputs from the SSURGO database to classify cropland into four levels of vulnerability to sediment and nutrient losses: Low, Moderate, Moderately High, and High. Previous work has identified inconsistencies in SVI assessments across the United States, possibly because neither precipitation amount nor intensity were included in the development of SVI. This study aimed to determine if rainfall characteristics influence the SVI classification and which ones are most critical. The objectives were to (1) evaluate the impact of precipitation characteristics on land vulnerability to sediment loss, and (2) evaluate if rainfall characteristics alter the degree of agreement between the simulated sediment yield and SVI classification. The study focused on four Conservation Effects Assessment Project (CEAP) watersheds in Ohio, Missouri, Mississippi, and Pennsylvania for which sediment yields were simulated using previously calibrated models. The models were run with input precipitation data from these four watersheds. In addition, in order to examine a wider range of precipitation characteristics, model runs were made for the same four watersheds utilizing precipitation data from two CEAP areas in Georgia and Maryland. Sediment yields for all the cropland units in four of the watersheds were simulated using the Soil and Water Assessment Tool or the Annualized Agricultural Nonpoint Source Pollution Model using 1985 to 2014 precipitation data from all six areas as inputs. Similarities and differences between precipitation characteristics such as precipitation amount, intensity, and rainfall erosivity R-factors were compared with the similarities and differences in simulated sediment loss. Results confirmed that SVI is a useful tool for relative ranking of cropland at risk of erosion within a region, as SVI and the model-based vulnerability classifications agreed for 55% to 100% of the watersheds’ subunits. However, model-based classification of field vulnerability could shift due to changes in precipitation characteristics. Thus, the range of soil loss for each vulnerability class can shift from one region to another. The results suggest that precipitation intensity or annual R-factor may help improve the correspondence between vulnerability and the range of expected soil loss.

Bivariate small-area estimation for binary and gaussian variables based on a conditionally specified model.

Many large-scale surveys collect both discrete and continuous variables. Small-area estimates may be desired for means of continuous variables, proportions in each level of a categorical variable, or for domain means defined as the mean of the continuous variable for each level of the categorical variable. In this paper, we introduce a conditionally specified bivariate mixed-effects model for small-area estimation, and provide a necessary and sufficient condition under which the conditional distributions render a valid joint distribution. The conditional specification allows better model interpretation. We use the valid joint distribution to calculate empirical Bayes predictors and use the parametric bootstrap to estimate the mean squared error. Simulation studies demonstrate the superior performance of the bivariate mixed-effects model relative to univariate model estimators. We apply the bivariate mixed-effects model to construct estimates for small watersheds using data from the Conservation Effects Assessment Project, a survey developed to quantify the environmental impacts of conservation efforts. We construct predictors of mean sediment loss, the proportion of land where the soil loss tolerance is exceeded, and the average sediment loss on land where the soil loss tolerance is exceeded. In the data analysis, the bivariate mixed-effects model leads to more scientifically interpretable estimates of domain means than those based on two independent univariatemodels.

Agricultural Conservation Practices and Aquatic Ecological Responses

Conservation agriculture practices (CAs) have been internationally promoted and used for decades to enhance soil health and mitigate soil loss. An additional benefit of CAs has been mitigation of agricultural runoff impacts on aquatic ecosystems. Countries across the globe have agricultural agencies that provide programs for farmers to implement a variety of CAs. Increasingly there is a need to demonstrate that CAs can provide ecological improvements in aquatic ecosystems. Growing global concerns of lost habitat, biodiversity, and ecosystem services, increased eutrophication and associated harmful algal blooms are expected to intensify with increasing global populations and changing climate. We conducted a literature review identifying 88 studies linking CAs to aquatic ecological responses since 2000. Most studies were conducted in North America (78%), primarily the United States (73%), within the framework of the USDA Conservation Effects Assessment Project. Identified studies most frequently documented macroinvertebrate (31%), fish (28%), and algal (20%) responses to riparian (29%), wetland (18%), or combinations (32%) of CAs and/or responses to eutrophication (27%) and pesticide contamination (23%). Notable research gaps include better understanding of biogeochemistry with CAs, quantitative links between varying CAs and ecological responses, and linkages of CAs with aquatic ecosystem structure and function.

The USDA‐ARS Experimental Watershed Network: Evolution, Lessons Learned, Societal Benefits, and Moving Forward

AbstractThe U.S. Department of Agriculture‐Agricultural Research Service's (ARS) Experimental Watershed Network grew from Dust Bowl era efforts of the Soil Conservation Service in the mid‐1930s with the establishment of small experimental watersheds. In the 1950s, five watershed research centers with intensively instrumented watersheds at the scale of 100 to 700 km2 were established. Primary network research objectives were to quantify on‐site and downstream effects of conservation practices and develop rainfall‐runoff relationships for design of water conservation structures. With passage of the Clean Water Act in 1972, research objectives have evolved to add a variety of observations relevant to the water quality issues. Many of the watersheds within the network have served, and continue to serve, as core validation sites for satellite sensors. As a result of the network's long history and intensive monitoring, coupled with mission‐driven research, a deep knowledge base of watershed processes has been developed. This has led to the extensive development and validation of numerous watershed models that are in widespread use today. The visionary investments in building and maintaining this network and associated scientific investigations for more than half a century have not only resulted in numerous high‐impact research accomplishments but also a wide array of accomplishments that directly benefit society. The ARS Experimental Watersheds formed the core of the Conservation Effects Assessment Project (CEAP) as well as the recently established Long‐Term Agroecosystem Research (LTAR) network. LTAR will expand the mission of the ARS Watersheds Network to include agricultural intensification, maintaining or improving ecosystem services while enhancing rural prosperity.

Long‐term database of Beasley Lake Watershed with 25 years of agricultural conservation practices

AbstractBeasley Lake Watershed is an agriculturally influenced drainage basin in western Mississippi that has been intensively studied for 25 years. As part of the USDA Conservation Effects Assessment Project (CEAP), the watershed has archived hydrology, precipitation, and water quality data in order to measure the effects of multiple USDA Natural Resources Conservation Service conservation practices on lake water quality. The long‐term database is available to researchers using a web‐based application, Sustaining the Earth's Watersheds, Agricultural Research Data System (STEWARDS). STEWARDS is a GIS‐based data retrieval application that encompasses spatial and temporal data collected from multiple sites within the watershed. This data note describes information located in the STEWARDS Beasley Lake Watershed database, including hydrology, precipitation, and water quality data. This information is valuable to researchers and agencies beyond the USDA as an available and useful database to improve the understanding of how land‐use practices affect the water quality of shallow lake systems.

Empirical Bayes small area prediction under a zero-inflated lognormal model with correlated random area effects.

Many variables of interest in agricultural or economical surveys have skewed distributions and can equal zero. Our data are measures of sheet and rill erosion called Revised Universal Soil Loss Equation - 2 (RUSLE2). Small area estimates of mean RUSLE2 erosion are of interest. We use a zero-inflated lognormal mixed effects model for small area estimation. The model combines a unit-level lognormal model for the positive RUSLE2 responses with a unit-level logistic mixed effects model for the binary indicator that the response is nonzero. In the Conservation Effects Assessment Project (CEAP) data, counties with a higher probability of nonzero responses also tend to have a higher mean among the positive RUSLE2 values. We capture this property of the data through an assumption that the pair of random effects for a county are correlated. We develop empirical Bayes (EB) small area predictors and a bootstrap estimator of the mean squared error (MSE). In simulations, the proposed predictor is superior to simpler alternatives. We then apply the method to construct EB predictors of mean RUSLE2 erosion for South Dakota counties. To obtain auxiliary variables for the population of cropland in South Dakota, we integrate a satellite-derived land cover map with a geographic database of soil properties. We provide an R Shiny application called viscover (available at https://lyux.shinyapps.io/viscover/) to visualize the overlay operations required to construct the covariates. On the basis of bootstrap estimates of the mean square error, we conclude that the EB predictors of mean RUSLE2 erosion are superior to direct estimators.

Using NASA Earth observations and Google Earth Engine to map winter cover crop conservation performance in the Chesapeake Bay watershed

Winter cover crops such as barley, rye, and wheat help to improve soil structure by increasing porosity, aggregate stability, and organic matter, while reducing the loss of agricultural nutrients and sediments into waterways. The environmental performance of cover crops is affected by choice of species, planting date, planting method, nutrient inputs, temperature, and precipitation. The Maryland Department of Agriculture (MDA) oversees an agricultural cost-share program that provides farmers with funding to cover costs associated with planting winter cover crops, and the U.S. Geological Survey (USGS) and the U.S. Department of Agriculture-Agricultural Research Service (USDA-ARS) have partnered with the MDA to develop satellite remote sensing techniques for measuring cover crop performance. The MDA has developed the capacity to digitize field boundaries for all fields enrolled in their cover crop programs (>26,000 fields per year) to support a remote sensing performance analysis at a statewide scal,e and has requested assistance with the associated imagery processing from the National Aeronautics and Space Administration (NASA). Using the Google Earth Engine (GEE) cloud computing platform, scripts were developed to process Landsat 5/7/8 and Harmonized Sentinel-2 imagery to measure winter cover crop performance. We calibrated cover crop performance models using linear regression between satellite vegetation indices and USGS / USDA-ARS field sampling data collected on Maryland farms between 2006 and 2012 (1298 samples). Satellite-derived Normalized Difference Vegetation Index (NDVI) values showed significant correlation with the natural logarithm of cover crop biomass (p ≤0.01, R2 = 0.56) and with observed percent vegetative ground cover (p ≤0.01, R2 = 0.68). The GEE scripts were used to composite seasonal maximum NDVI values for each enrolled cover crop field and calculate performance metrics for the winter and spring seasons of three enrollment years (2014–15, 2015–16, and 2017–18) for four Maryland counties. Results from winter 2017–18 demonstrate that rye and barley fields had higher biomass than wheat fields, and that early planting, along with planting methods that increase seed-soil contact, increased performance. The processing capabilities of GEE will support the MDA in scaling up remote sensing performance analysis statewide, providing information to evaluate the environmental outcomes associated with various agronomic management strategies. The tool can be modified for different seasonal cutoffs, utilize new sensors to capture phenology in winter and spring, and scale to larger regions for use in adaptive management of winter cover crops planted for environmental benefit. Project supportThis project was supported by the USGS Land Change Science Program within the Land Resources Mission Area, the USDA Choptank River Conservation Effects Assessment Project (CEAP), the USDA Lower Chesapeake Bay Long Term Agricultural Research (LTAR) Project; the Maryland Department of Agriculture; and the NASA DEVELOP National Program.

An overview of research into conservation practice effects on soil and water resources in the Upper Washita Basin, Oklahoma, United States

The Fort Cobb Reservoir Experimental Watershed (FCREW) and Little Washita River Experimental Watershed (LWREW), located within the Upper Washita Basin (UWB) in Oklahoma, are part of the Agricultural Research Service (ARS) Benchmark Conservation Effects Assessment Project (CEAP)–Watershed Assessment Studies locations. The CEAP was created in 2003 by the USDA Natural Resources Conservation Service (NRCS) in partnership with USDA ARS and many other partners to quantify the environmental effects of conservation practices (CPs) and programs and to develop the science base for managing the agricultural landscape for environmental quality. The ultimate goal of this study was to present CPs that are expected to work at respective spatial scales, based on the findings of research that has been carried out in these CEAP and other watersheds within the UWB in the last 15 years. A summary of research findings indicates that the effects of CPs on soil and water resources were simulated at various spatial scales. At the large watershed scale, average annual suspended sediment yield at the 786 km² (303 mi²) FCREW outlet was reduced by 86% based on multiple CPs implemented from the 1950s to 2008 by NRCS. Specific quantified effects of studied CPs are presented herein. With the exception of red cedar (<i>Juniperus virginiana</i> L.) removal, single CPs were expected to show improvement of soil and water resources in smaller-scale watersheds. Practices that are expected to improve soil and water resources include grassland conservation from red cedar encroachment (brush control), combined streambank stabilization practices, riparian and filter strip buffer practices, and conversion of cropped area to Bermuda grass (<i>Cynodon dactylon</i> [L.] Pers.).

Development of a novel framework for modeling field-scale conservation effects of depressional wetlands in agricultural landscapes

The intermixed cropland, grassland, and wetland ecosystems of the upper mid-western United States combine to provide a suite of valuable ecological services. Grassland and wetland losses in the upper midwestern United States have been extensive, but government-funded conservation programs have protected and restored hundreds of thousands of acres of wetland and grassland habitat in the region. The value of restored wetlands in agricultural fields is complex, and the USDA Natural Resource Conservation Service, Conservation Effects Assessment Project (CEAP) has been lacking the methodology to include these conservation practices in their analyses. Our aim is to develop a reproducible methodology for simulating wetlands within the CEAP cropland modeling framework used to evaluate other agricultural conservation practices. Furthermore, we evaluate the effect of using upland conservation practices on the functioning of restored wetlands. By simulating the addition of a depressional wetland that effectively removes 6% of the field from crop production, we obtained a 15% reduction in annual runoff and a 29% and 28% reduction in mean annual nitrogen (N) and phosphorus (P) losses, respectively. The presence of the depressional wetland in the field is estimated to also reduce edge-of-field losses of sediments by 20% and sediment-bound N and P by 19% and 23%, respectively. Additionally, adding a grass filter strip around the wetland greatly decreased sediment inputs to the wetland, increasing the effective life of the wetland, in terms of its ability to perform valued services, by decades to centuries. Our method for modeling depressional wetlands embedded in cropped fields provides a means to quantify the effects of wetland conservation practices on field-level losses for regional assessments, such as the CEAP.

Conservation tillage effects in the Atlantic Coastal Plain: An APEX examination

The Conservation Effects Assessment Project (CEAP) was established to develop a scientific understanding and methodology for estimating environmental benefits and effects of conservation practices on agricultural landscapes at watershed, regional, and national scales. CEAP9s goal is to improve the effectiveness of conservation practices and programs by quantifying conservation effects and providing the science and education needed to enrich conservation planning, implementation, management decisions, and policy. Field observations and computer-based simulation of the effects of agricultural conservation are important components of CEAP. This research supports the CEAP effort by utilizing well-documented field data in conjunction with the Agricultural Policy/Environmental eXtender (APEX) model to quantify long-term conservation effects. In this study, field data collected at a research site located near Tifton, Georgia, were used to evaluate APEX and to quantify long-term benefits of implementing conservation tillage in the Atlantic Coastal Plain region of the United States. The objectives of this research were to (1) quantify differences in crop yield, hydrology, and sediment transport for conventional and conservation tillage systems in the Atlantic Coastal Plain; (2) develop a calibrated APEX simulation for these tillage systems; and (3) quantify the performance of the APEX model with respect to crop yields, hydrology, and sediment yield. Fourteen years of crop yield, surface runoff, subsurface flow, and sediment transport data were quantified comparing conventional tillage (CT) to strip tillage (ST). No treatment differences were found for either cotton (<i>Gossypium hirsutum</i> L.) or peanut (<i>Arachis hypogea</i> L.) yields. Surface runoff from the CT was found to be 1.7 times that of the ST, while subsurface flow from the ST was found to be 1.7 times that of CT. Total water loss (surface and subsurface) was nearly equivalent for the two systems: 30% of annual rainfall. Satisfactory model performance was found for APEX surface runoff simulations. Mixed results were found for model performance of crop yield while model simulations of subsurface flow and sediment yield were less than satisfactory. The APEX modeling framework provides a useful tool for assessing crop yield and hydrologic differences between tillage management systems in the Atlantic Coastal Plain. Additional refinement of modeling approaches may be necessary to adequately represent subsurface flow and sediment transport in these same systems.

Quantifying the impacts of the Conservation Effects Assessment Project watershed assessments: The first fifteen years

T he United States Department of Agriculture (USDA) spends about US$6 billion each year on agricultural conservation programs to help producers and landowners implement conservation practices (CPs) and systems on their land. In 2003, the USDA Natural Resources Conservation Service (NRCS) entered into partnership with USDA Agricultural Research Service (ARS), USDA National Institute of Food and Agriculture (NIFA), other federal agencies, and many external partners to create the Conservation Effects Assessment Project (CEAP). The goal of CEAP is to quantify the environmental effects of CPs and programs and develop the science base for managing the agricultural landscape for environmental quality (Mausbach and Dedrick 2004; Duriancik et al. 2008). Conservation effects are assessed at national, regional, and watershed scales on cropland, grazing lands, wetlands, and for wildlife. As part of these efforts, CEAP initiated the Watershed Assessment Studies (WAS) component …

Evaluation of Conservation Effects Assessment Project Grazing Lands conservation practices on the Cienega Creek watershed in southeast Arizona with AGWA/RHEM modeling tools

The Automated Geospatial Watershed Assessment Tool (AGWA) and the Rangeland Hydrology Erosion Model (RHEM) were used to evaluate conservation practices on the Cienega Creek watershed (CCW) that were implemented under the Conservation Effects Assessment Project (CEAP) on Grazing Lands. CEAP on Grazing Lands is a multi-agency effort to quantify the environmental effects of conservation practices and programs, and develop the science base for managing rangelands for environmental quality using conservation practices (Spaeth et al. 2013). The evaluation was performed on the CCW and the Empire Ranch, located in southeastern Arizona, where numerous conservation practices have been implemented to achieve their management goals of maintaining desired plant communities and watershed processes. To assess the effects of the conservation practices on long-term soil and water loss, RHEM was applied to the entire CCW using National Resources Inventory (NRI) data. Four analysis periods were selected based on climatic contrasts, conservation spending, and availability of NRI sample points. The CCW results showed that the simulations using RHEM parameters derived from NRI data could be used to demonstrate the impact of climate on vegetation condition and sediment yield. A subsection, dubbed “select treatment areas,” of the CCW, which received extensive treatments with brush removal, prescribed burns, and stock ponds, was assessed using remotely sensed data. The select treatment areas were modeled over three different periods, representing preconservation spending, postconservation spending, and later postconservation spending. Remote sensing was capable of detecting and estimating the changes in vegetation cover from brush removal and prescribed burns. Simulations of sediment yield using pre- and posttreatment data indicated a modest reduction in sediment yield. Simulations in the select treatment areas indicated mechanical brush treatments were typically more effective than prescribed burns for improving watershed condition as estimated by reductions in sediment yield, but were more costly to implement. Stock ponds had a larger impact on sediment yield than the land treatments. The assessment demonstrated the utility of remotely sensed estimates of plant growth form and cover for model inputs to estimate changes in runoff and sediment yield with changing cover conditions over large areas.

Understanding the use of decision support tools by conservation professionals and their education and training needs: An application of the Reasoned Action Approach

Decision support tools (DSTs) are a means to facilitate science-based conservation planning. Technical advancements in conservation science, the pragmatic needs of conservation planning, and government support for collaborative initiatives such as the Conservation Effects Assessment Project (CEAP), have contributed to evaluation and development of both existing and new DSTs. Much of current scholarship on DSTs, however, focuses on their uptake by farmers and their crop advisors. Limited, to almost no, attention has been paid to the education and training needs of conservation agency staff—the primary users of these tools. To address this knowledge gap, we conducted an online survey of staff in conservation agencies that are located in counties that either currently include or included a CEAP Watershed Assessment Study site. We found that agency staff did not use all DSTs, and not all DSTs we surveyed were equally popular with respect to their usage and awareness. The desired technical roles of DSTs included conservation targeting, watershed assessment and planning, and quantifying environmental and financial benefits of conservation practices. The desired stakeholder engagement roles of DSTs included facilitating engagement with watershed stakeholders, educating farmers about areas of concern in the watershed, and facilitating engagement with farmers one-on-one and in a group setting. By applying the Reasoned Action Approach framework, we found that DST users and nonusers are not only differently skilled, but also perceive barriers related to learning about and using DSTs differently. Taken together, our findings suggest the need for future research on establishing a deeper understanding of conservation agency staffs9 skills, attitudes, perceived norms, behavioral limitations, and intentions toward using DSTs, in order to refine future training and education to better meet needs.

Wetlands in agricultural landscapes— Significant findings and recent advances from CEAP-Wetlands

The Wetlands Component of the USDA’s Conservation Effects Assessment Project (CEAP-Wetlands) is a multi-agency effort advancing science related to quantifying and interpreting effects and effectiveness of conservation practices and programs on ecosystem services provided by wetlands in agricultural landscapes. This special section originated from a symposium held at the 73rd Soil and Water Conservation Society’s International Annual Conference in Albuquerque New Mexico, July 29 to August 1, 2018. The symposium was jointly organized by the USDA Natural Resources Conservation Service and the US Geological Survey. To facilitate CEAP-Wetlands efforts, several regional assessments were conducted across the United States. These regional assessments were designed to address science gaps hindering wetland conservation and to develop tools facilitating conservation assessments. Conservation decisions affect not just agricultural wetlands, but also the services that these complex ecosystems provide to society. Papers in this special section of the <i>Journal of Soil and Water Conservation</i> present key findings and recent advances from several CEAP-Wetlands regional assessments and discuss the significant contributions of each assessment to an ever-increasing understanding of wetland ecosystems and their provisioning of ecosystem services. Modeling efforts using the Agricultural Policy and Environmental eXtender (APEX) and other process-based models are an integral component of CEAP-Wetlands. Results of these modeling efforts are also presented, and conservation implications are discussed.

Making conservation count: The importance of assessing resources and documenting outcomes to USDA

O ne of the requests of the 2018 Farm Bill was to refocus USDA's efforts to document outcomes of conservation programs on private lands. We agree. It's imperative that we show that USDA conservation programs work and that farmers and ranchers using voluntary conservation efforts are making a difference. In fact, USDA has a long history of working toward this goal. For the past 17 years, USDA has been developing the science baseline and methods to carry out assessments and document conservation outcomes with the establishment of its Conservation Effects Assessment Project (CEAP). In 2003, the USDA's Natural Resources Conservation Service partnered with USDA's Agricultural Research Service (ARS), National Institute of Food …

Depressional wetland classification and ecosystem service predictive models for the Integrative Landscape Modeling partnership

Depressional wetlands in the Great Plains are experiencing watershed alterations that impact the provisioning of important ecosystem services, which are unmonitored on a large scale (Smith et al. 2011). The Natural Resources Conservation Service’s (NRCS) Conservation Effects Assessment Project (CEAP) determines the effects of conservation programs on ecosystem service provisioning across the nation (Tomer et al. 2014). CEAP–Wetlands has focused on the effects of conservation programs and land use on ecosystem service provisioning in areas dominated by different wetland types. The High Plains region (HPR) primarily contains playa wetlands. The dominant land uses are native grassland, cropland, and conservation program land (Brinson and Eckels 2011). Predictive models were developed from CEAP–Wetlands data and can be used to estimate services by identifying playa wetlands and measuring variables required to populate the models (Duriancik et al. 2008). We developed a sampling manual that can be used to remotely classify playa function and ecosystem service provisioning. The manual and models can be used to monitor ecosystem services and inform USDA conservation decisions. Playas are depressional recharge wetlands that exist within western portions of Texas, Oklahoma, and Kansas, western and central Nebraska, the eastern plains of Colorado and New Mexico, and southeast Wyoming (Smith 2003) (figure 1). Playas exist within closed watersheds and receive water only through precipitation and overland flow (Bolen et al. 1989). Playa hydrology is similar among basins, allowing application of CEAP–Wetlands models to estimate service provisioning (Smith et al. 2015). Playas provide ecosystem services including habitat provisioning, floodwater storage, and carbon (C) sequestration (Smith et al. 2011). When cultivation occurs in …

Effects of combined conservation practices on soil and water quality in the Central Mississippi River Basin

Conventional cultivation of claypan soils leads to soil and water quality degradation because of high runoff and associated soil erosion. The Goodwater Creek Experimental Watershed, which is part of the USDA Agricultural Research Service Benchmark Conservation Effects Assessment Project, Watershed Assessment Studies, was established to address these issues. Plot studies have highlighted trade-offs between erosion control and herbicide or nutrient runoff. There is a need for long-term field-scale evaluation of combined practices that reduce sediment, nutrient, and herbicide losses by runoff. A 36 ha field located in Missouri was under a conventional corn (<i>Zea mays</i> L.)–soybean (<i>Glycine max</i> L.) system from 1993 to 2003 with fertilizer application and tillage prior to planting in the spring. A precision agriculture system defined by two main management zones was implemented from 2004 to 2014: wheat (<i>Triticum aestivum</i> L.) and soybean in 60% of the field, and corn and soybean in the remaining 40%. The system included no-till, cover crops, atrazine split-applications based on weed pressure, variable rates of nitrogen (N), and variable rates of fall-applied phosphorus (P). The objective of this study was to compare runoff water quality from the two management systems, based on flow and load duration curves, cumulative distribution functions, and conclusions from replicated plot studies. The precision agriculture system did not affect annual runoff, but it did increase the frequency of low flows. Sediment losses were reduced by 87% as a result of no-till and cover crops. Atrazine and P losses were lower than expected, despite the lack of incorporation into the soil. Atrazine losses were possibly lower because of the wheat area acting as a buffer, greater atrazine adsorption and retention in the field, and faster decay. Dissolved P losses as a fraction of applied remained the same, likely because of greater adsorption and lower runoff risk when applying P. Finally, nitrate-N (NO₃-N) losses decreased and resulted in an overall decrease of N losses despite a slight increase of ammonium-N (NH₄-N) losses. Explanations included a greater soil water content, a different timing of N applications, and N uptake by cover crops. Building on these successes, an aspirational management system is proposed to further improve on the performance and practicality of the precision agriculture system.

STEWARDS: A decade of increasing the impact of Agricultural Research Service watershed research programs

T he online database Sustaining the Earth's Watersheds–Agricultural Research Data System (STEWARDS), was developed in a six year project by a team from several USDA Agricultural Research Service (ARS) locations to deliver weather, hydrology, and water quality data to the public. Launched as part of the Conservation Effects Assessment Project (CEAP; Mausbach and Dedrick 2004), the timeline started with 2002 to 2003's Conception and Agency commitment, extended through July 7, 2007's, beta release with three watersheds, to the 2007 to 2008 public release and population with other data and watersheds (Steiner et al. 2008). In fact, the database continues to grow, adding between 1 and 2 million data records a year. At the decadal anniversary of public availability, the authors set out to examine the impact STEWARDS has had on the scientific community, conservation programs, and the general public. Data in STEWARDS were collected by a number of USDA ARS locations, some of which have documented the various data collection efforts in the literature. The six regional watersheds established after authorization by Senate Bill 59 (USDA 1959) all have database documentation paper series published. Marks (2001) introduced …

Overview of the USDA Mid-Atlantic Regional Wetland Conservation Effects Assessment Project

This paper provides an overview of studies conducted under the USDA Mid-Atlantic Regional Wetland Conservation Effects Assessment Project (MIAR study). Under the MIAR effort, numerous studies were conducted to (1) quantify ecosystem functions provided by restored wetlands by comparing functions within depressional nontidal wetlands with a varying degree of alteration (i.e., natural wetlands, restored wetlands, and prior converted croplands [PCCs]) and (2) develop tools for wetland monitoring and assessment. We present these studies after classifying them according to wetland functional (biodiversity, biogeochemical, and hydrologic) and tool development categories (remote sensing, hydrologic modeling, and geospatial analysis). Furthermore, we provide lessons from the MIAR study’s findings for enhanced wetland conservation practices. Our overview demonstrates that restoration of wetlands contributes to enhancing wetland biodiversity, biogeochemical, and hydrologic functions in the Mid-Atlantic Region. Wetland monitoring tools that were developed as part of this study aid our understanding of wetland functions and the effect of restoration on those functions. Findings from these studies suggest that it is important to (1) establish long-term restoration plans; (2) minimize soil compaction during restoration; (3) increase wetland water storage capacity; (4) locate restored wetlands around natural wetlands to magnify restoration effects and improve water quality management; (5) consider the importance of shallow water and topography for supporting native plant species; (6) use landscape parameters for targeting and implementing restoration efforts; and (7) use wetland monitoring tools for precision management. This MIAR study provides scientific data to support wetland restoration activities and guidelines to foster the restoration of wetland-mediated ecosystem services.