Grazing lands cover approximately one-third of the contiguous United States, support much of the nation's beef production, and are an important component of the U.S. terrestrial carbon budget. In this study, we quantified net ecosystem carbon balance (NECB), the net status of grazing lands as a carbon sink (C-sink) or source (C-source) and a key determinant of soil health and productivity. Our primary objective was to synthesize multiple years of annual NECB across heterogeneous grazing lands across the continental U.S and evaluate annual NECB against physical drivers (mean annual precipitation (MAP), mean annual temperature (MAT), vegetation, and moisture condition) and management practices (grazing pressure index (GPI) and fertilization history). We hypothesized that (1) NECB is higher in mesic and fertilized grasslands; (2) NECB increases with MAP and MAT but decreases with GPI; and (3) interactive effects exist among MAP, MAT, and GPI. Using carbon fluxes measured by eddy covariance towers and methane emissions including both enteric methane and manure derived from stocking rates across seven USDA Long-term Agroecosystem Research Network sites, we found: (1) grazing lands were a C-sink or carbon neutral at most sites; (2) vegetation type, moisture conditions, or fertilization had no significant effect on NECB; (3) NECB increased with MAP and MAT, but decreased with a higher GPI; and (4) MAT had a significant positive effect on NECB when MAP exceeded 750 mm (greater water availability). The effect of GPI on NECB was significantly negative when MAP was below 1000 mm, significantly negative when MAT < 12 °C and significantly positive when MAT > 16 °C. Thus, most grazing lands in our study acted as C-sinks unless water deficit, low temperature, or heavy grazing were interactively present. Understanding how climate and management influence NECB of grazing lands is key to maintaining resilient agroecosystems that secure beef production and sustain rural prosperity.

Context Controlling weeds and reducing the weed seed bank is critical for the success of future crops. The use of cover crops and grazing animals during the transition to organic agriculture can be effective in addressing weed management challenges. Objective Six objective-based cover crop systems with and without livestock grazing were investigated for their effects on weeds during the organic transition phase at the USDA-ARS laboratory in Mandan, ND. Methods The study employed a randomized complete block design with a split-plot arrangement and four replicates, with main-plot factors grazed vs. ungrazed, while cover crop systems (soil-building mix, pollinator mix, weed suppression mix, multipurpose cover crop mix, annual crop rotation, or perennial forage biculture) were split-plot factors. Weed seed bank was estimated from soil cores before and after the organic transition and weed density and canopy cover were assessed twice during the growing season each year using the modified Daubenmire method. Results Cover crop systems affected the weed seedbanks of purslane (Portulaca oleracea L.) and lambsquarters (Chenopodium album L.). Grazing decreased yellow foxtail (Setaria glauca L.) seedbank. Grazing did not affect or total weed plant density; only Setaria glauca weed density was affected; nor did it affect canopy cover. Total weed populations were greater in the multi-purpose and weed suppression mixtures in the second and third years of evaluation. Predominant weed species changed throughout the years, suggesting environmental factors were driving weed growth dynamics. Cover crop systems affected canopy cover. Implications Outcomes from this study did not support using grazing to control weeds in the transition to organic systems. Study outcomes highlighted the important role of cover crops in controlling weeds during the organic transition phase.

Field peas (Pisum sativum L.) are an important source of protein, fiber, and minerals for human consumption. As N-fixing pulse crops, incorporating field peas into crop rotations can also enhance agricultural sustainability. Agricultural management influences soil, plant, and grain characteristics. However, the influence of agricultural management on field pea quality under semiarid conditions is poorly understood. A 12-year biomass removal experiment in the Northern Great Plains allowed evaluation of how management influences food quality. Here, we assessed how biomass removal treatments in a 2-year crop rotation of field pea and spring wheat (Triticum aestivum L.) influenced field pea protein, fat, and minerals Ca, P, K, Zn, Mg, Fe, Cu, Mn, and Na. Treatments after grain harvest included no biomass removal (NR), removal of wheat straw (WH), removal of wheat and pea residue (WPH), and a grazed treatment where wheat and pea residue was grazed (WPG). Our results showed that differences in minerals and protein were more affected by annual weather variability than residue removal treatments from 2019 to 2021. With increasing drought severity, our experiment showed significant decreases in field pea yield (p <= 0.01), yet pea grain had greater protein, P, K, Fe, Zn, and Cu (p <= 0.01). While the yield of field peas was lower during severe drought, the nutritional quality of field peas increased. This may lead to higher premiums to producers for field peas during times of drought.

We conducted a 4-year organic transition field study to evaluate the effects of objective-based cover crop mixtures and grazing on cover crop and forage biomass, residue, and carryover effects on the yield of the first organic certified crop. The experiment, conducted at the USDA-ARS Northern Great Plains Research Laboratory near Mandan, ND, was a split-plot design with grazing (grazed or ungrazed) as whole plots and cover crop mixture (soil-building cover crop mix, pollinator cover crop mix, weed suppression cover crop mix, multipurpose cover crop mix, annual crop rotation, or perennial forage biculture) as subplots. Weed biomass decreased over the years, and cover crop biomass was three- to fourfold greater in the perennial cover crop treatment compared to annual mixtures. Grazing did not affect aboveground biomass but affected the botanical composition of aboveground biomass. Weed biomass was 65% greater in the grazed treatments in 2017 and 20% greater in the grazed treatments in 2018 compared to the ungrazed treatments. Annual crop mixtures had the greatest residue cover, and perennial biculture had the least. Cover crop mixtures or livestock integration did not affect grain yield in the first year of certified organic production. We found that in a drought year, grazing reduced the benefits of cover crops on weed suppression and the carryover of cover crop biomass from the previous year. These results highlight complex interactions among cover crop mixtures, grazing, and environmental conditions on biomass, residue, and carry-over effects of cover crops.

AbstractAbiotic efflux of CO2 from soil is typically attributed to weathering of carbonates but also arises from concurrent oxidation of organic matter and reduction of metal oxides. Little is known, however, about the magnitude of the latter reaction in soil environments. We observed rapid formation of CO2 from soils treated with a simple phenolic acid (gallic acid, [GA]), consistent with redox reactions catalyzed by Mn or Fe oxide. We measured CO2 formed during 4‐h incubations of soil from different management systems (n = 5), archived benchmark soils (n = 18), and samples of reagent‐grade metal oxides (n = 4). Treatments included water, pH 4 phthalate buffer, glucose (0.029 M), or GA (0.025 M). Little CO2 was formed when samples were treated with water or glucose, but CO2 quickly evolved with GA. Adding buffer elicited CO2 in some samples. Soil from a 5‐year rotation produced less net CO2 (p ≤ 0.05) than other crop rotations or pasture. Net responses from benchmark samples ranged broadly. The CO2 from some soils was attributable to an acid‐carbonate reaction, while for other soils CO2 was inferred to derive from oxidation of GA by metal oxides. Unlike other tested oxides, Mn(IV) oxide produced a CO2 response similar to that seen in soil. Redox reactions producing CO2 can occur in a variety of soils after inputs of GA, a simple phenolic constituent of root exudates, and be influenced by management. Such processes, catalyzed by Mn(IV) oxide, might be significant abiotic sources of CO2 from agricultural land.

A component of the USDA ARS Long-Term Agroecosystem Research (LTAR) network is a Common Experiment standardized across all sites. This collection contains all standardized protocols for the biophysical metrics collected in the Common Experiment.

The authors studied the efficacy of six objective-based, reduced tillage cover cropping systems with or without livestock grazing to induce changes in soil condition and soil health on a fine sandy loam during the organic transition phase in the northern Great Plains. A randomized complete block design with a split-plot arrangement and four replicates was used in an experiment conducted at the USDA-ARS Northern Great Plains Research Laboratory, Mandan, ND. Main-plot factors were grazing versus no grazing, while six cover crop mixtures (soil building cover crop mix, pollinator cover crop mix, weed suppression cover crop mix, multipurpose cover crop mix, annual crop rotation, or perennial forage biculture) were the split-plot factors. Soil parameters were analyzed at the beginning and end of the 3-year organic transition period from 0- to 10-cm and 10- to 30-cm depth samples. No cover crop mixtures or grazing effect was observed on wet aggregate stability. However, wet aggregate stability decreased in all treatments after 3 years of organic transition. In general, soil pH decreased with the transition to organic systems. Soil organic C increased in both the grazed and ungrazed perennial forage biculture treatments and the ungrazed soil building, annual crop rotation, and multipurpose cover crop mixes. Soil total N increased under the grazed annual crop rotation. Aggregated soil quality index values did not vary between cover cropping systems after organic transition. Outcomes from this study provided useful insight into perennial and cover crop effects on key chemical and physical properties of soil known to influence crop productivity in semi-arid regions.

Novel approaches that are fast and sensitive are needed to evaluate soil change and integrate soil ecosystem properties. Carbon (C) and nitrogen (N) extracted from soil with water are associated with plant nutrients and microbial activity but information about change over time in the US Great Plains is sparse. We used cool (20°C) and hot (80°C) water extracts from historic (1947) and contemporary (2018) soil samples collected at Moccasin, MT; Akron, CO; and Big Spring, TX; to examine changes to labile C and N and optical properties after 71 years of dryland cropping. Concentrations of C and N extracted with cool water decreased between 1947 and 2018 in surface (0–15.2 cm) samples from Moccasin, by 52% and 35%, and Big Spring, by 37% and 32%, but remained unchanged at Akron. Conversely, net (hot−cool) extractable C did not change at Moccasin or Big Spring but increased at Akron by 26%. Net extractable N decreased at Moccasin by 22% but did not change elsewhere. Sequential principal component analysis and stepwise discriminant analysis identified three important optical properties. Values of SUVA 254 (where SUVA 254 is the specific ultraviolet absorbance at 254 nm) in extracts did not change at Moccasin between 1947 and 2018 but increased at Akron, indicating increased aromaticity. Conversely, SUVA 254 decreased at Big Spring. Values for Sag 350–400 (where Sag 350–400 is the slope from a nonlinear fit of an exponential function to the absorption spectrum over the wavelength range from 350 to 400 nm), inversely related to extract molecular weight and aromaticity, decreased at Moccasin but not elsewhere. The proportion of recalcitrant to labile compounds, C:T (where C:T is the ratio of fluorescence intensity from Peak C [ex340/em440] to Peak T [ex275/em340]), increased in extracts from all sites but especially at Akron. Together, these methods provided insights into soil change while conserving samples.

Microbial communities are essential to soil functions within agroecosystems. Understanding interactions between agricultural management and soil biological properties is important for sustainability, however, broadscale inferences on these interactions are challenged by differences in site-specific characteristics. To identify the effects of conservation management on soil microbial communities, we conducted a multi-location study of 15 sites across the United States, which varied in crop management strategies and climate and edaphic characteristics. Microbial community composition was assessed by ester-linked fatty acid methyl esters (EL-FAME) with biomarkers for gram-negative bacteria, gram-positive bacteria, actinobacteria, saprotrophic fungi, and arbuscular mycorrhizal fungi. Among the edaphic characteristics considered in this study, soil organic C (SOC) was more correlated with EL-FAME than pH and clay content. Reduced tillage, cover cropping, and manure increased total EL-FAME and SOC, whereas crop diversity had no significant effect. Abundance of bacterial fatty acid biomarkers had stronger relationships to SOC (r(2) = 0.64-0.65) than fungal biomarkers (r(2) < 0.23), but fungi exhibited more sensitivity to management than bacteria. Though some fatty acids were sensitive to management across locations, manure had the overall largest effect on EL-FAMEs. This study revealed a strong response of the microbial community to conservation management practices regardless of location, but the magnitude differed across locations. Additionally, SOC and moisture deficit were key drivers of site-specific responses. Our multilocation study supports the utility of EL-FAMEs as an important soil health indicator that should be considered in national soil health assessments.

A spring wheat (Triticum aestivum L.)-corn (Zea mays L.)-soybean (Glycine max (L.) Merr.) rotation has become widespread in dry-land cropping systems in the northern Great Plains of the United States. But this region experiences extreme variability in climate, which is projected to increase in the future, and little is known about how seasonal weather changes impact this crop rotation in terms of carbon and water balances. To address this research gap, we analyzed micrometeorological and eddy covariance measurements through two rotations of spring wheat-corn-soybean in a no-till, rainfed field managed according to prevailing local practices near Mandan, ND USA. Using linear regression models, we found a negative correlation between vapor pressure deficit (VPD) and soil water content, which explained 84 % of the variation in net-ecosystem production (NEP) and 64 % of the variation in gross ecosystem production (GEP). Results also indicated that evapotranspiration (ET) across dormant and growing seasons among three crops (i.e., six crop-seasons) was mainly determined by VPD during the dormant season but a threshold ET was attained as VPD increased between growing seasons. Elevated temperatures during the dormant season explained 88 % of the variability in ecosystem respiration during the dormant season. These results imply that anticipated increases in evaporative demand due to elevated temperatures and/or low humidity in conjunction with soil drought may necessitate wider adoption of conservation agricultural practices that enhance soil moisture recharge during the dormant season.

A PhenoCam is a near-surface remote sensing system traditionally used for monitoring phenological changes in diverse landscapes. Although initially developed for forest landscapes, these near-surface remote sensing systems are increasingly being adopted in agricultural settings, with deployment expanding from 106 sites in 2020 to 839 sites by February 2025. However, agricultural applications present unique challenges because of rapid crop development and the need for precise phenological monitoring. Despite the increasing number of PhenoCam sites, clear guidelines are missing on (i) the phenological analysis of images, (ii) the selection of a suitable color vegetation index (CVI), and (iii) the extraction of growth stages. This knowledge gap limits the full potential of PhenoCams in agricultural applications. Therefore, a study was conducted in two soybean (Glycine max L.) fields to formulate image analysis guidelines for PhenoCam images. Weekly visual assessments of soybean phenological stages were compared with PhenoCam images. A total of 15 CVIs were tested for their ability to reproduce the seasonal variation from RGB, HSB, and Lab color spaces. The effects of image acquisition time groups (10:00 h–14:00 h) and object position (ROI locations: far, middle, and near) on selected CVIs were statistically analyzed. Excess green minus excess red (EXGR), color index of vegetation (CIVE), green leaf index (GLI), and normalized green red difference index (NGRDI) were selected based on the least deviation from their loess-smoothed phenological curve at each image acquisition time. For the selected four CVIs, the time groups did not have a significant effect on CVI values, while the object position had significant effects at the reproductive phase. Among the selected CVIs, GLI and EXGR exhibited the least deviation within the image acquisition time and object position groups. Overall, we recommend employing a consistent image acquisition time to ensure sufficient light, capture the largest possible image ROI in the middle region of the field, and apply any of the selected CVIs in order of GLI, EXGR, NGRDI, and CIVE. These results provide a standardized methodology and serve as guidelines for PhenoCam image analysis in agricultural cropping environments. These guidelines can be incorporated into the standard protocol of the PhenoCam network.

Predicting forage biomass yield is critical in managing livestock since it impacts livestock stocking rates, hay procurement, and livestock marketing strategies. Only a few biomass yield prediction studies on pasture and rangeland exist despite the need. Therefore, this study focused on developing a biomass yield prediction methodology through remote sensing satellite imagery (multispectral bands) and climate data, employing open-source software technologies. Biomass ground truth data were obtained from local pastures, where Kentucky bluegrass is the predominant species among other forages. Remote sensing data included spatial bands (6), vegetation indices (30), and climate data (16). The top-ranked features (52 tested) from recursive feature elimination (RFE) were short-wave infrared 2, normalized difference moisture index, and average turf soil temperature in the machine learning (ML) model developed. The random forest (RF) model produced the highest accuracy (R2=0.83) among others tested for biomass yield prediction. Applications of the developed methodology revealed that (i) the methodology applies to other unseen pasters (R2=0.79), (ii) finer satellite spatial resolution (e.g., CubeSat; 3 m) better-predicted pasture biomass, and (iii) the methodology successfully developed for a combination of Kentucky bluegrass and other forages, extended to high-value alfalfa hay crop with excellent yield prediction accuracy (R2=0.95). The developed methodology of RFE for feature selection and RF for biomass yield modeling is recommended for biomass and hay forage yield prediction.

Plant ecometabolomics is a growing field of study that allows broader understanding of the metabolomic dynamics within and between plants and their ecosystem. Plants constantly respond to environmental cues, producing plant secondary metabolites (PSMs) to communicate with and adapt to their ever‐changing ecosystems. PSMs allow plants to withstand biotic and abiotic stressors and are mediators of interactions between their aboveground and belowground ecosystem. However, the way PSMs are affected by and respond to agricultural management is poorly understood. As part of the long‐term agroecosystem research network, we assessed ecometabolomic profiles of corn ( Zea mays L.) leaves and roots between contrasting prevailing (prevailing practice, PP) and alternative (alternative practice, AP) cropping practices, which utilized cover crops and cover crop interseeding. The ecometabolomic profiles of corn leaves and roots were 90% and 71%, respectively, richer in PSMs in the AP than PP treatments. Our untargeted metabolomic analyses resulted in 124 annotated features, with 68 features significantly different between AP and PP treatments. We detected 43 features annotated as PSMs, 39 of which were greater ( p ≤ 0.10) in the AP than PP treatments. This research shows that our agricultural management practices influence the way plants respond within their agroecosystem. Increased production of PSMs allows plants to better adapt to various abiotic and biotic stresses, enhancing the resilience of plants within their ecosystem.

Visual soil evaluations (VSEs) offer land managers a valuable method to efficiently assess soil condition. Scores from quantitative VSEs are often associated with soil properties known to directly influence agroecosystem function, thereby providing useful information to guide management decisions. However, practitioner awareness and adoption of VSEs is limited, particularly in North America. To explore the potential utility of VSEs for practitioner use, a half-day workshop was developed for interested farmers, conservationists, extension educators, and other agriculturalists. The workshop, developed by the USDA-ARS Northern Great Plains Research Laboratory, Mandan, ND USA, provided a brief overview of the Visual Evaluation of Soil Structure (VESS) followed by opportunities to apply the method on five fields with different cropping practices but a common soil type (Typic Haplustoll; USDA). The workshop was held four times between 2018 and 2023 following spring wheat (Triticum aestivum L.) harvest. Workshop attendees were able to discern differences in soil structure among cropping practices using VESS (P <= 0.01). Mean attendee VESS scores were 3.8, 2.6, 3.0, 2.4, and 1.1 for spring wheat-fallow, 3-yr, 5-yr, Dynamic, and Dynamic + Manure cropping system treatments, respectively. Attendee VESS scores were significantly associated with the instructor's VESS scores (r = 0.85), along with measurements of soil organic matter (r = -0.82), soluble C (r = -0.84), C mineralization (r = -0.82), spring wheat grain yield (r = -0.51), and straw yield (r = -0.67). Findings from this study suggest land managers can quickly acquire skills necessary to effectively apply VSEs for assessment of rainfed cropping practices in a semiarid region.

AbstractDiverse patterns of climate and edaphic factors challenge detection of soil property change in the US Great Plains. Because detectable soil change can take decades, insights into the trajectory of soil properties frequently require long‐term site monitoring and, where available, associated soil archives to enable comparisons with initial or baseline states. Unfortunately, few multi‐decadal soil change investigations have been conducted in this region. Here, we document effects of dryland cropping on a suite of soil properties by comparing matched historic (1947) and contemporary (2018) soil samples from the Haas Soil Archive at three sites in the US Great Plains: Moccasin, MT, Akron, CO, and Big Spring, TX. Current analytical methods were used to provide insight into changes in soil texture, pH, carbon, and micronutrients at 0‐ to 15.2‐cm and 15.2‐ to 30.5‐cm depths. Changes in direction and magnitude of soil properties over 71 years were site specific. Changes in textural class occurred at all sites, with Moccasin and Akron transitioning from loam to clay loam and Big Spring from sandy clay loam to sandy loam. The soil pH reaction class changed from slightly alkaline to moderately acid at Akron and slightly alkaline to moderately alkaline at Big Spring. At 0–15.2 cm, soil organic carbon decreased by 15% and 36% at Moccasin and Big Spring, respectively, but increased by 15% at Akron. Soil micronutrients generally declined at all sites. Weather‐related variables derived from air temperature and precipitation records were not correlated with soil change. Inferred factors contributing to soil change included on‐site management, inherent soil features, weather metrics not evaluated, or a combination thereof.

Soybean (Glycine max (L.) Merr.) planting has increased in central and western North Dakota despite frequent drought occurrences that limit productivity. Soybean plants need high photosynthetic and transpiration rates to be productive, but they also need high water use efficiency when water is limited. Crop residues and cover crops in crop rotations may improve soybean drought tolerance in northern Great Plains. We aimed to examine how a management practice that included cover crops and residue retention impacts agronomic, ecosystem water and carbon dioxide flux, and canopy-scale physiological attributes of soybeans in the northern Great Plains under drought conditions. The experiment consisted of two soybean fields over two years with business-as-usual (no-cover crops and spring wheat residue removal) and aspirational management (cover crops and spring wheat residue retention) during a drought year. We compared yield; aboveground biomass; green chromatic coordinates, and CO2 and H2O fluxes from eddy covariance, Phenocam images, and ancillary micrometeorological measurements. These measurements were used to derive ecosystem-scale physical, and physiological attributes with the ‘big leaf’ framework to diagnose underlying processes. Soybean yields were 29% higher under drought conditions in the field managed in a system that included cover crops and residue retention. This yield increase was associated with a 5 day increase in the green-chromatic-coordinate defined maturity phenophase, increasing agronomic and intrinsic water use efficiency by 27% and 33%, respectively, increasing water uptake, and increasing the rubisco-limited photosynthetic capacity (Vcmax25) by 42%. The inclusion of cover crops and residue retention into a cropping system improved soybean productivity because of differences in water use, phenology timing, and photosynthetic capacity. These results suggest that farmers can improve soybean productivity and yield stability by incorporating cover crops and residue retention into their management suite because these practices to facilitate more aggressive water uptake.

Long-term research is essential for guiding the development of agroecosystems to meet escalating production demands in a manner that is environmentally sound and socially acceptable. Research must integrate biophysical and socioeconomic factors to provide geographically scalable knowledge that involves stakeholders across the research-education-extension-policy spectrum. In response to this need, the Long-Term Agroecosystem Research (LTAR) network developed a "Common Experiment," which seeks to develop and disseminate multi-region, science-based information to enable implementation of visionary agricultural innovations while simultaneously promoting food security, well-being, environmental quality, and climate adaptation and mitigation. The core design of the Common Experiment contrasts prevailing and alternative/aspirational production systems, with the latter including novel innovations hypothesized to advance sustainable intensification in locally appropriate ways. Treatments in the Common Experiment represent a diversity of production systems under cropland, grazing land, and integrated crop/grazing land management. Where possible, treatments are evaluated at multiple spatial scales (e.g., from plot to enterprise) and are designed to evolve over the course of the experiment with stakeholder input. A common assessment framework guides data collection for the experiment and is complemented by metric-specific protocols and an emerging data management infrastructure. Currently, there are large differences among sites in the application of the experimental framework and degree of stakeholder engagement; differences largely grounded in pragmatic issues related to land access, site expertise, and resource availability. The full potential of the LTAR Common Experiment may be realized with strategic investments in network capacity.

Crop rotations in the northern Great Plains of North America increasingly include corn ( Zea mays L.) and soybean ( Glycine max (L.) Merr.). Use of cover crops, while less extensive, is also increasing given their purported agronomic and environmental benefits. To date, soil responses to the inclusion of corn, soybean, and cover crops in rainfed cropping systems have not been well documented in the region. Therefore, soil properties were evaluated 6 years after establishment of three crop rotations (spring wheat ( Triticum aestivum L.)–soybean (SW–S), spring wheat–corn–soybean (SW–C–S), and spring wheat–corn–cover crop (SW–C–cc)) each split by no and minimum tillage on a Dark Brown Chernozem near Mandan, ND, USA. Soil responses to treatments were subtle and exclusive to the 0–7.6 cm depth. Soil pH was lower in SW–S than SW–C–cc (5.28 vs. 5.48; P = 0.05), SO 4 -S was greater under SW–C–cc than SW–C–S (13.4 vs. 11.6 g S kg −1 ; P = 0.03), exchangeable K was greater under SW–C–S and SW–C–cc than SW–S (0.83 cmol kg −1 vs. 0.52 cmol kg −1 ; P = 0.05), and water-stable aggregates were greater in SW–S than SW–C–S (26% vs. 19%; P = 0.08). Soil organic carbon (SOC) and total N did not differ among crop rotations or between tillage treatments, while particulate organic matter N was greater under no tillage compared to minimum tillage ( P = 0.08). Between 2012 and 2018, soil pH decreased and SOC increased under SW–C–S. Frequent monitoring of near-surface soil conditions in rotations with soybean every other year is recommended. Furthermore, innovative management practices are needed to enhance soil C and N fractions in rotations with full-season cover crops.

A component of the USDA ARS Long-Term Agroecosystem Research (LTAR) network is a Common Experiment standardized across all sites. In this overview protocol we describe the development of standardized protocols for the biophysical metrics collected in the Common Experiment. Throughout this collection, we refer to “metric” as the physical sample that can be quantified and used to inform the status of performance indicators within production, environment, economic, and society domains. We refer to “protocol” as the methods used to collect that metric so that all experimental sites are compatible. This set of protocols were developed for the Cropland Sites although some are also usable for Grazingland and Integrated Common Experiment Sites. This collection allows the LTAR network to ensure research is scalable and robust. All Cropland Common Experiment Sites within the network started following these protocols with the 2024 growing season.

The USDA Long-Term Agroecosystem Research (LTAR) network aims to enhance sustainable agricultural management practices through a coordinated, cross-site common experiment involving 18 locations across the United States. The objective of this paper is to provide an overview of the LTAR Grazing Land Common Experiment at the Northern Plains (NP) site, where an experiment was initiated in 2019 to answer producers' and researchers' questions about whether the tactical application of fire or grazing can reduce the dominance of invasive Kentucky bluegrass in northern Great Plains ecosystems. As part of the LTAR common experiment, we contrast a prevailing practice (season-long grazing at moderate stocking rate) with four alternative practices at a half-hectare plot scale: (1) mob grazing by cattle, (2) multi-species grazing (mob grazing by cattle, with goats foraging at key times of the year), (3) prescribed fire, and (4) prescribed fire followed by cattle grazing. A stakeholder group is engaged in the co-production process to determine alternative practices and how to apply them. Every 5 years, the treatment with the best overall outcomes is applied at a field scale (15 ha), resulting in a core treatment contrast of prevailing versus alternative grazing management systems. This experiment aims to develop alternative agroecological practices that optimize current and future economic and ecosystem benefits.