Long-Term Agroecosystem Research Research Articles

Integrating human dimensions within the LTAR Network to achieve agroecological system transformation

• Agroecosystem research often focuses on biophysical processes and productivity without incorporating human dimensions research and/or stakeholder engagement. • Connecting individual and community well-being to agro-innovation research is required for agro-ecological transformation to sustainable intensification. • Long-Term Agroecosystem Research (LTAR) Network sites have historically had varied degrees of human dimensions research within their research plan; however, LTAR's human dimensions capacity has grown. • To capitalize on this capacity, we propose a four-step framework for the LTAR Network to evolve a cohesive human dimensions strategy that brings together the social and ecological. • Continued institutional support is required to maintain and further pursue research that will support stakeholder co-developed science that facilitates agroecosystem transformations benefiting society.

Drivers of Hot Spots and Hot Moments of Denitrification in Agricultural Systems

AbstractDenitrification, the most poorly understood process in the nitrogen (N) cycle, is of great interest as it can significantly reduce pools of reactive N and act as a source of the potent greenhouse gas nitrous oxide (N2O). A particular study challenge is that small areas (hot spots) and brief periods (hot moments) of denitrification frequently account for a high percentage of N gas flux activity. Our study utilized sites within the U.S. Department of Agriculture Long‐Term Agroecosystem Research (LTAR) Network to understand the importance of potential drivers of such hot spots and hot moments of denitrification in agricultural systems. We quantified in situ denitrification rates in intact soil cores from three LTAR sites – Upper Chesapeake Bay (UCB), PA, Central Mississippi River Basin (CMRB), MO, and Gulf Atlantic Coastal Plain (GACP), GA – by directly measuring dinitrogen (N2) and N2O production via the Nitrogen‐Free Air Recirculation Method (N‐FARM). Each site provided an opportunity to study a different potential driver of denitrification: landscape‐scale topography (UCB), soil confining layers (CMRB), and ecosystem‐scale climate (e.g., drying‐rewetting events; GACP). At the UCB site, wetter, low topographic positions released a higher proportion of N2:N2O, suggesting that N removal does not result in increased greenhouse emissions. Results at the CMRB site show evidence that confining features, like hard clays, could drive denitrification hot spots. Similarly, such features at the GACP site could drive denitrification hot spots (at depth) and hot moments (drying‐rewetting). These results suggest that denitrification is a significant sink for excess agricultural N at multiple scales, which may inform management decisions in the future.

Ecosystem Services in Working Lands of the Southeastern USA

Agriculture and natural systems interweave in the southeastern US, including Florida, Georgia, and Alabama, where topographic, edaphic, hydrologic, and climatic gradients form nuanced landscapes. These are largely working lands under private control, comprising mosaics of timberlands, grazinglands, and croplands. According to the “ecosystem services” framework, these landscapes are multifunctional. Generally, working lands are highly valued for their provisioning services, and to some degree cultural services, while regulating and supporting services are harder to quantify and less appreciated. Trade-offs and synergies exist among these services. Regional ecological assessments tend to broadly paint working lands as low value for regulating and supporting services. But this generalization fails to consider the complexity and tight spatial coupling of land uses and land covers evident in such regions. The challenge of evaluating multifunctionality and ecosystem services is that they are not spatially concordant. While there are significant acreages of natural systems embedded in southeastern working lands, their spatial characteristics influence the balance of tradeoffs between ecosystem services at differing scales. To better understand this, we examined the configuration of working lands in the southeastern US by comparing indicators of ecosystem services at multiple scales. Indicators included measurements of net primary production (provisioning), agricultural Nitrogen runoff (regulating), habitat measured at three levels of land use intensity, and biodiversity (supporting). We utilized a hydrographic and ecoregional framework to partition the study region. We compared indicators aggregated at differing scales, ranging from broad ecoregions to local landscapes focused on the USDA Long-Term Agroecosystem Research (LTAR) Network sites in Florida and Georgia. Subregions of the southeastern US differ markedly in contributions to overall ecosystem services. Provisioning services, characterized by production indicators, were very high in northern subregions of Georgia, while supporting services, characterized by habitat and biodiversity indicators, were notably higher in smaller subregions of Florida. For supporting services, the combined contributions of low intensity working lands with embedded natural systems made a critical difference in their regional evaluation. This analysis demonstrated how the inclusion of working lands combined with examining these at different scales shifted our understanding of ecosystem services trade-offs and synergies in the southeastern United States.

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.

Role of Concentrated Flow Pathways on the Movement of Pesticides through Agricultural Fields and Riparian Buffer Zones

HighlightsLand management and hydrologic connectivity cause concentrated flow pathways (CFPs) to serve various functions.Pesticide concentrations diminished along flow pathways from row-cropped fields through functional riparian zones.CFPs facilitated pesticide transport into pasture/hay fields from upgradient corn fields.Subsurface transport was likely a more important transport pathway relative to surface runoff for imidacloprid.Abstract. Riparian buffers, which are an important component of watershed management strategies, can effectively mitigate nutrients and pesticides in agricultural runoff. However, concentrated flow pathways (CFPs) can undermine the performance of buffers by allowing contaminant-laden runoff to bypass the mitigation potential offered by the buffer soils and vegetation. To determine the extent to which CFPs increase pesticide transport from agricultural fields to nearby streams, soil samples (0-2 cm depth) were collected along both CFPs and overland flow (OLF) pathways from the field to the stream for nine fields in a Long-Term Agroecosystem Research (LTAR) site in the ridge and valley physiographic region of Pennsylvania. Soil samples were analyzed for atrazine, metolachlor, and imidacloprid, with two dominant patterns emerging. In corn fields, pesticide concentrations were higher in OLF than CFP samples, suggesting that pesticides were mitigated during transport through each corn field. In contrast, hay and pasture fields, which had not been treated with any of the three pesticides of interest, had lower pesticide concentrations in the OLF samples than the CFP samples. Because the CFPs from these fields originated in upgradient unsampled corn fields, these results suggest that the CFPs were a conduit for pesticides applied in the corn fields and were simply flowing through the hay and pasture fields. Similarly, CFPs in riparian buffers and grass pathways located between the row-cropped fields and the stream tended to have lower concentrations than the upland field (OLF-F) but higher concentrations than the buffer OLF, suggesting a potential for increasing overland flow effectiveness in riparian zones by interrupting CFPs leading to the stream. This study highlights the importance of the land management factors and hydrologic connectivity that cause CFPs to serve different functions (mitigation or enhancement) as runoff is conveyed from agricultural fields to a riparian buffer, and ultimately to an adjacent stream. Further, the results highlight the need for design and maintenance solutions addressing the erosion and sediment control issues that commonly undermine agricultural buffer effectiveness. Keywords: Buffers, Concentrated flow, Contaminant fate and transport, Hydrology, Land management, Pesticides, Overland flow, Water quality.

Comparison of Evapotranspiration and Biomass Simulation in Winter Wheat under Conventional and Conservation Tillage Systems using APEX Model

The Agricultural Policy/Environmental eXtender (APEX) is one of the hydrologic and water quality models being used in the USDA-ARS Long-Term Agroecosystem Research (LTAR) to evaluate current and develop sustainable agricultural production systems throughout the United States. Tillage practices used affect agricultural production, soil erosion, and evapotranspiration (ET), which is a major component of the hydrologic cycle. However, there is limited literature on the impact of tillage practices on parameterization and performance of APEX to simulate ET. The goals of this study were to 1) determine model parameters that affect ET simulation in APEX model for winter wheat (Triticum aestivum L.) fields managed under conservation and conventional tillage systems, and 2) evaluate the ability of APEX to simulate ET and daily biomass for each of these tillage systems in central Oklahoma. Tillage system had an impact on the number and type of APEX parameters sensitive for simulation of ET. Therefore, it is essential to perform a sensitivity analysis for study areas with different tillage management practices to determine appropriate parameters for inclusion in the calibration process. Overall, APEX simulated daily, biweekly, and monthly ET and daily biomass relatively well for both tillage systems. The Nash-Sutcliffe efficiency (NSE) for the simulated monthly ET of the calibrated model was 0.98 and 0.96 for conservation and conventional tillage fields, respectively. The percent bias (PBIAS) values for the ET simulation were within 3%, while PBIAS values for daily biomass simulation were within 25%, which indicates that the average simulated ET and daily biomass values were within 3% and 25% of the measured ET and daily biomass, respectively, in both tillage fields. This result indicates that a well-calibrated APEX model using appropriate sensitive parameters can simulate ET and biomass satisfactorily in both tillage systems.

Comparative analysis of water budgets across the U.S. long-term agroecosystem research network

Understanding the movement and storage of water within agricultural landscapes as functions of management and climate is essential for more efficient and sustainable water use. However, knowledge of water storage and fluxes on U.S. agricultural lands is largely incomplete. The Long-Term Agroecosystem Research (LTAR) network provides a unique and geographically diverse set of agricultural study sites in the United States. The objectives of this study were to: 1) characterize the hydrologic variability across the LTAR network; 2) identify data gaps in the water budgets across the LTAR network; and 3) identify opportunities to leverage the LTAR network to improve understanding of water budgets across agricultural landscapes. For each of the 18 LTAR sites, we developed water budgets on an average annual basis. Uncertainty propagation methods combined individual component uncertainties to calculate an overall water budget uncertainty. Datasets length ranged from three to 50 years. The network covers a range of precipitation from 240 to 1400 mm yr−1, evapotranspiration from 228 to 1080 mm yr−1, and surface runoff and subsurface flow from negligible to 560 mm yr−1. However, uncertainties of where all the water is going remained high, in part because soil water storage and downward movement of water were often neglected or measured for very short periods, resulting in average water budget uncertainty of 25% of the water inputs. More accurate measurement of the major inputs and outputs, and direct measurement of water content and percolation are key to understanding how agricultural lands affect terrestrial water budgets.

Social-Ecological Processes and Impacts Affect Individual and Social Well-Being in a Rural Western U.S. Landscape

To achieve agroecosystem conservation strategies while balancing the needs of people who live and work across rural landscapes, it is critical to understand what people need to improve and sustain their quality of life and well-being. Research that is designed to connect social-ecological dynamics, landscape change, and human impacts to human well-being and ecosystem health is well-suited to inform land management strategies and decision-making for agricultural production policies. We asked livestock producers, public land and resource managers, recreation users, conservationists, and wilderness advocates who live and work among rural communities in southwestern Idaho to describe social-ecological conditions that support and degrade their well-being. Using grounded theory methodology, we analyzed semi-structured interviews to discover meanings of well-being and to understand how people experience changes to their quality of life in an arid rangelands context. Our findings support previous research that suggests well-being is experienced at both individual and community scales, with sense of well-being influenced by ecological, economic, and socio-cultural processes. Specifically, our findings illuminate the role of social interactions as processes that support agroecosystem conditions and functions to the benefit or detriment of human well-being and ecosystem health. Community is not just a geographic territory; it is a process of social interactions through which people build, improve, or damage relationships that support or degrade well-being. By integrating scholarship on social change processes, ecosystem services, and impacts to human well-being, we contribute an integrated framework with a comprehensive set of social-ecological concepts to be used as a common language and synthesis guide for agroecosystem researchers and practitioners. We discuss our findings in the context of the USDA Agricultural Research Service’s national network for Long-Term Agroecosystem Research (LTAR). The LTAR network is charged with identifying strategies for sustainable intensification that support agricultural productivity, environmental quality, and rural well-being. Our research sheds light on the functions of agroecosystem stakeholders and rural communities beyond their adoption (or not) of new technologies and management practices. Future assessments of environmental change and impacts must adequately address social processes that, alongside ecological processes, affect well-being for rural communities and landscapes.

Response of Tallgrass Prairie to Management in the U.S. Southern Great Plains: Site Descriptions, Management Practices, and Eddy Covariance Instrumentation for a Long-Term Experiment

Understanding the consequences of different management practices on vegetation phenology, forage production and quality, plant and microbial species composition, greenhouse gas emissions, and water budgets in tallgrass prairie systems is vital to identify best management practices. As part of the Southern Plains Long-Term Agroecosystem Research (SP-LTAR) grassland study, a long-term integrated Grassland-LivestOck Burning Experiment (iGLOBE) has been established with a cluster of six eddy covariance (EC) systems on differently managed (i.e., different burning and grazing regimes) native tallgrass prairie systems located in different landscape positions. The purpose of this paper is to describe this long-term experiment, report preliminary results on the responses of differently managed tallgrass prairies under variable climates using satellite remote sensing and EC data, and present future research directions. In general, vegetation greened-up and peaked early, and produced greater forage yields in burned years. However, drought impacts were greater in burned sites due to reductions in soil water availability by burning. The impact of grazing on vegetation phenology was confounded by several factors (e.g., cattle size, stocking rate, precipitation). Moreover, prairie systems located in different landscapes responded differently, especially in dry years due to differences in water availability. The strong correspondence between vegetation phenology and eddy fluxes was evidenced by strong linear relationships of a greenness index (i.e., enhanced vegetation index) with evapotranspiration and gross primary production. Results indicate that impacts of climate and management practices on vegetation phenology may profoundly impact carbon and water budgets of tallgrass prairie. Interacting effects of multiple management practices and inter-annual climatic variability on the responses of tallgrass prairie highlight the necessity of establishing an innovative and comprehensive long-term experiment to address inconsistent responses of tallgrass prairie to different intensities, frequencies, timing, and duration of management practices, and to identify best management practices.

Multiparameter Regression Modeling for Improving Quality of Measured Rainfall and Runoff Data in Densely Instrumented Watersheds

AbstractThe Walnut Gulch Experimental Watershed is a semi-arid experimental watershed and long-term agro-ecosystem research (LTAR) site managed by the USDA-Agricultural Research Services (ARS) Sout...

Adjustment of CO2 flux measurements due to the bias in the EC150 infrared gas analyzer

During the Regional Approaches to Climate Change (REACCH) program, eddy covariance monitoring over agricultural fields were used to estimate annual carbon and water budgets in the inland Pacific Northwest. Here, we assess the effect of a bias in the high-frequency CO2 concentration measurements using the Campbell Scientific EC150 infra-red gas analyzer on the CO2 fluxes and field-scale carbon balances. The bias stems from using a lower frequency temperature measurement to calculate the CO2 density, which misses higher frequency temperature fluctuations. To generate the bias adjustment, data were collected over four similar agricultural sites as part of the Long-Term Agroecosystem Research network for multiple months using the same four instrument sets used in the REACCH project. The difference between the high-frequency and low-frequency CO2 fluxes were regressed against the kinematic heat fluxes to generate a correction equation for each instrument set, which were applied to the historical REACCH data to determine the effect of the bias on the measured and gap-filled flux values. The re-calculated positive biases in the measured fluxes were 40 gC-CO2 m−2 yr-1 to 126 gC-CO2 m−2 yr-1, indicating greater losses to the atmosphere than initially estimated. Once gap-filled, three out of fourteen site-years switched from weak carbon sinks to weak carbon sources. When the carbon exported via harvest was included in the budget calculation the bias correction still impacted the source/sink strength but did not change the sign of the carbon balance. Overall, the total net ecosystem exchange decreased between 300–470 gC-CO2 m-2 per site (29–46%) over the 4 crop-years from the bias adjustment process.

Evaluating the Reliability of the U.S. Cooperative Observer Program Precipitation Observations for Extreme Events Analysis Using the LTAR Network

AbstractThe detection and attribution of changes in precipitation characteristics relies on dense networks of rain gauges. In the United States, the COOP network is widely used for such studies even though there are reported inconsistencies due to changes in instruments and location, inadequate maintenance, dissimilar observation time, and the fact that measurements are made by a group of dedicated volunteers. Alternately, the Long-Term Agroecosystem Research (LTAR) network has been consistently and professionally measuring precipitation since the early 1930s. The purpose of this study is to compare changes in extreme daily precipitation characteristics during the warm season using paired rain gauges from the LTAR and COOP networks. The comparison, done at 12 LTAR sites located across the United States, shows underestimation and overestimation of daily precipitation totals at the COOP sites compared to the reference LTAR observations. However, the magnitude and direction of the differences are not linked to the underlying precipitation climatology of the sites. Precipitation indices that focus on extreme precipitation characteristics match closely between the two networks at most of the sites. Our results show consistency between the COOP and LTAR networks with precipitation extremes. It also indicates that despite the discrepancies at the daily time steps, the extreme precipitation observed by COOP rain gauges can be reliably used to characterize changes in the hydrologic cycle due to natural and human causes.

Advancing the Sustainability of US Agriculture through Long-Term Research.

Agriculture in the United States must respond to escalating demands for productivity and efficiency, as well as pressures to improve its stewardship of natural resources. Growing global population and changing diets, combined with a greater societal awareness of agriculture's role in delivering ecosystem services beyond food, feed, fiber, and energy production, require a comprehensive perspective on where and how US agriculture can be sustainably intensified, that is, made more productive without exacerbating local and off-site environmental concerns. The USDA's Long-Term Agroecosystem Research (LTAR) network is composed of 18 locations distributed across the contiguous United States working together to integrate national and local agricultural priorities and advance the sustainable intensification of US agriculture. We explore here the concept of sustainable intensification as a framework for defining strategies to enhance production, environmental, and rural prosperity outcomes from agricultural systems. We also elucidate the diversity of factors that have shaped the past and present conditions of cropland, rangeland, and pastureland agroecosystems represented by the LTAR network and identify priorities for research in the areas of production, resource conservation and environmental quality, and rural prosperity. Ultimately, integrated long-term research on sustainable intensification at the national scale is critical to developing practices and programs that can anticipate and address challenges before they become crises.

Evaluating Concentrated Flowpaths in Riparian Forest Buffer Contributing Areas Using LiDAR Imagery and Topographic Metrics

Riparian forest (CP22) buffers are implemented in the Chesapeake Bay Watershed to trap pollutants in surface runoff thus minimizing the amount of pollutants entering the stream network. For these buffers to function effectively, overland flow must enter the riparian zones as dispersed sheet flow to facilitate slowing, filtering, and infiltrating of surface runoff. The occurrence of concentrated flowpaths, however, is prevalent across the watershed. Concentrated flowpaths limit buffer filtration capacity by channeling overland flow through or around buffers. In this study, two topographic metrics (topographic openness and flow accumulation) were used to evaluate the occurrence of concentrated flowpaths and to derive effective CP22 contributing areas in four Long-Term Agroecosystem Research (LTAR) watersheds within the Chesapeake Bay Watershed. The study watersheds include the Tuckahoe Creek watershed (TCW) located in Maryland, and the Spring Creek (SCW), Conewago Creek (CCW) and Mahantango Creek (MCW) watersheds located in Pennsylvania. Topographic openness identified detailed topographic variation and critical source areas in the lower relief areas while flow accumulation was better at identifying concentrated flowpaths in higher relief areas. Results also indicated that concentrated flowpaths are prevalent across all four watersheds, reducing CP22 effective contributing areas by 78% in the TCW, 54% in the SCW, 38% in the CCW and 22% in the MCW. Thus, to improve surface water quality within the Chesapeake Bay Watershed, the implementation of riparian forest buffers should be done in such a way as to mitigate the effects of concentrated flowpaths that continue to short-circuit these buffers.

Evaluating strategies for sustainable intensification of US agriculture through the Long-Term Agroecosystem Research network

Sustainable intensification is an emerging model for agriculture designed to reconcile accelerating global demand for agricultural products with long-term environmental stewardship. Defined here as increasing agricultural production while maintaining or improving environmental quality, sustainable intensification hinges upon decision-making by agricultural producers, consumers, and policy-makers. The Long-Term Agroecosystem Research (LTAR) network was established to inform these decisions. Here we introduce the LTAR Common Experiment, through which scientists and partnering producers in US croplands, rangelands, and pasturelands are conducting 21 independent but coordinated experiments. Each local effort compares the outcomes of a predominant, conventional production system in the region (‘business as usual’) with a system hypothesized to advance sustainable intensification (‘aspirational’). Following the logic of a conceptual model of interactions between agriculture, economics, society, and the environment, we identified commonalities among the 21 experiments in terms of (a) concerns about business-as-usual production, (b) ‘aspirational outcomes’ motivating research into alternatives, (c) strategies for achieving the outcomes, (d) practices that support the strategies, and (e) relationships between practice outreach and adoption. Network-wide, concerns about business as usual include the costs of inputs, opportunities lost to uniform management approaches, and vulnerability to accelerating environmental changes. Motivated by environmental, economic, and societal outcomes, scientists and partnering producers are investigating 15 practices in aspirational treatments to sustainably intensify agriculture, from crop diversification to ecological restoration. Collectively, the aspirational treatments reveal four general strategies for sustainable intensification: (1) reducing reliance on inputs through ecological intensification, (2) diversifying management to match land and economic potential, (3) building adaptive capacity to accelerating environmental changes, and (4) managing agricultural landscapes for multiple ecosystem services. Key to understanding the potential of these practices and strategies are informational, economic, and social factors—and trade-offs among them—that limit their adoption. LTAR is evaluating several actions for overcoming these barriers, including finding financial mechanisms to make aspirational production systems more profitable, resolving uncertainties about trade-offs, and building collaborative capacity among agricultural producers, stakeholders, and scientists from a broad range of disciplines.

The value of long‐term data in agricultural systems

The value of long‐term data in agricultural systems

Agroecosystem research with big data and a modified scientific method using machine learning concepts

AbstractLong‐term studies of agroecosystems distributed across the North American continent are providing an extraordinary understanding of regional environmental dynamics. The new Long‐Term Agro‐ecosystem Research (LTAR) network (organized in 2012) has designed an explicit cross‐site research program with multiple U.S. Department of Agriculture (USDA) experimental watersheds, ranges, and forests. Here, we report results from studies using a modified scientific method that includes learning through time that was implemented over the past five years with long‐term data from USDA experimental sites in coordination with other networks. The results offer a compelling argument for the LTAR concept of combining site‐based expertise with network‐wide coordination and collaboration to arrive at more accurate scientific conclusions than possible from individual researchers working alone. Simply put, without site‐based expertise and cross‐site communication working in parallel to provide input, feedback, and refinement to each subsequent step, similar to the way machine learning works, the interpretations and conclusions of these studies would have been incomplete, if not incorrect. Further, the up‐front time commitment to data processing and analytics above the time dedicated to place‐based studies increased the productivity of the team and the impact of the research, unlike the common perception that cross‐site research is often less efficient. In turn, this approach supported a non‐traditional system of credit for co‐authors based on citation impact of the journal selected as the publication outlet with less regard for author order. The LTAR network has embraced this modified scientific method in its shared research strategy and common experiment to address the problematic issues of mixed data quality across studies and sites, co‐author credit, research efficiency, and scientific impact on data‐intensive research. This approach can be combined with other types of collaborative and social media approaches, such as crowdsourcing, to take advantage of the wide range of expertise in the agroecological community as well as other disciplines to move science forward in the time of big data.

Preparing to Face the Future of Agriculture in the United States

Third Annual Long-Term Agroecosystem Research (LTAR) Meeting; Venus, Florida, 22–26 February 2016

Long-term agroecosystem research on northern Great Plains mixed-grass prairie near Mandan, North Dakota

Sanderson, M. A., Liebig, M. A., Hendrickson, J. R., Kronberg, S. L., Toledo, D., Derner, J. D. and Reeves, J. L. 2015. Long-term agroecosystem research on northern Great Plains mixed-grass prairie near Mandan, North Dakota. Can. J. Plant Sci. 95: 1101–1116. In 1915, a stocking rate experiment was started on 101 ha of native mixed-grass prairie at the Northern Great Plains Research Laboratory (NGPRL) near Mandan, ND (100.9132N, 46.7710W). Here, we document the origin, evolution, and scientific outcomes from this long-term experiment. Four pastures of 12.1, 20.2, 28.3, and 40.5 ha were laid out and stocked continuously from May until October with 2-yr-old or yearling beef steers at four rates [initially 0.98, 1.39, 1.83, and 2.4 animal unit months ha−1]. The experiment generated some of the first information on the resilience of mixed-grass prairie to grazing and drought and relationships of livestock productivity to soil moisture for predictive purposes. After 1945, the experiment was reduced to the light and heavy stocking rate pastures only, which have been managed and grazed in approximately the same manner to the present day. The pastures were used to assess responses of vegetation to fertilizer in the 1950s and 1960s, develop grazing readiness tools in the 1990s, and assess remote sensing technologies in the 2000s. The long-term pastures currently serve as a unique resource to address contemporary questions dealing with drought, soil quality, carbon dynamics, greenhouse gas emissions, invasive species, and climate change.

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.