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.

Pulmonary hypertension (PH) causes morbidity and mortality in sickle cell disease (SCD). The release of heme during hemolysis triggers endothelial dysfunction and contributes to PH. Long non-coding RNAs (lncRNAs) may play a pivotal role in endothelial dysfunction and PH pathogenesis. This study assessed the regulatory role of the lncRNA–heme oxygenase-1 (HMOX1) axis in SCD-associated PH pathogenesis. Total RNAs were isolated from the lungs of 15–17-week-old sickle cell (SS) mice and littermate controls (AA) mice and subjected to lncRNA expression profiling using the Arrystar™ lncRNA array. Volcano plot filtering was used to screen for differentially expressed lncRNAs and mRNAs with statistical significance (fold change > 1.8, p < 0.05). A total of 3915 lncRNAs were upregulated and a total of 3545 lncRNAs were downregulated in the lungs of SS mice compared to AA mice. To validate differentially expressed lncRNAs, six upregulated lncRNAs and six downregulated lncRNAs were selected for quantitative PCR. MALAT1 expression was significantly upregulated in the lungs of SS mice and in hemin-treated human pulmonary artery endothelial cells (HPAECs), suggesting that hemolysis induces MALAT1. Functional studies revealed that MALAT1 depletion increased, while MALAT1 overexpression decreased, the endothelial dysfunction markers endothelin-1 (ET-1) and vascular cell adhesion molecule-1 (VCAM1), indicating a protective role of MALAT1 in maintaining endothelial homeostasis. In vivo, adenoviral MALAT1 overexpression attenuated PH, right ventricular hypertrophy (RVH), vascular remodeling, and reduced ET-1 and VCAM1 expression in SS mice. Given that HMOX1 protects endothelial cells during hemolysis, we observed that HMOX1 expression and activity were elevated in SS mouse lungs and hemin-treated HPAECs. HMOX1 knockdown enhanced ET-1 and VCAM1 expression, confirming its endothelial-protective function. Importantly, MALAT1 overexpression increased HMOX1 expression and activity, whereas MALAT1 knockdown reduced HMOX1 levels and mRNA stability. Collectively, these findings identify MALAT1 as a protective regulator that mitigates endothelial dysfunction, vascular remodeling, and PH in SCD, at least in part through the induction of HMOX1. These results suggest that SCD modulates the MALAT1–HMOX1 axis, and further characterization of MALAT1 function may provide new insights into SCD-associated endothelial dysfunction and PH pathogenesis, as well as identify novel therapeutic targets.

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.

Quantifying spatial and temporal dynamics of crop sequences is often accomplished through crop biodiversity metrics. Existing metrics are confounded by crop sequence length, subsequence repetition, and perennialization. Our objective was to formulate a Crop Sequence Complexity Index (CSCI) that accounts for differences in crop sequence lengths, crop sequence compressibility, functional type transitions, and back-to-back perennials. Additionally, we mapped the distribution of crop sequence metrics across the Contiguous United States (CONUS). We joined Crop Sequence Boundary data from the USDA-NASS for two periods: (2008-2015) and (2016-2023) to assemble the 16-year crop sequence of 13.5 million field centroids between 2008 and 2023 and calculated crop sequence metrics aggregated by Major Land Resource Areas (MLRA). We also examined the correlations among crop sequence complexity metrics. We found CSCI was less correlated with both crop sequence length and the number of back-to-back perennials in a crop sequence compared to the Rotational Complexity Index (RCI). Consequently, RCI tended to be lower in MLRA where annual cropping systems dominated, such as the Corn Belt, Mississippi River Basin, and southern Great Plains, and RCI was highest in the irrigated southwestern US. In contrast, CSCI was highest in the northern Great Plains and lowest in the southern Great Plains, with intermediate values throughout most of CONUS. Crop sequences in CONUS usually consist of a very limited number of species. However, crop sequence complexity varies widely because of how sequences ordered functional type transitions, and perennialization. While biophysical constraints are important, socioeconomic factors drive crop sequence complexity.

Cover crops (CCs) are promoted as a mechanism for reducing soil erosion, enhancing soil fertility, and improving diversity in agricultural systems, but in drier climates, there are concerns about their impact on soil water availability for the subsequent crop. We conducted two trials to evaluate the impact of CC mixtures on subsequent spring wheat (Triticum aestivum L., SpW), irrigated at either 75% or 100% of the long-term average precipitation. In the first year of each trial, plots were seeded with one of two full-season CC mixtures or SpW. The CC treatments included GL, a grass-legume mixture composed of spring triticale (X Triticosecale Wittmack 'VNS') and forage pea (Pisium sativum 'Arvika' L.), and GGLF, a mixture of two grasses, triticale and white proso millet (Panicum miliaceum L. 'VNS'), a legume (forage pea), and a forb, forage radish (Raphanus sativus L. 'Nitro'). In the second year of each trial all plots were seeded to SpW, with half irrigated at the 75% rate and half irrigated at the 100% rate. Previous CCs and irrigation treatments impacted SpW yields only in Trial 1 (2015-2016) but not in Trial 2 (2018-2019). In Trial 1, plots previously planted with a GL produced less grain and residue than the other treatments under 75% irrigation but more grain and residue with the 100% irrigation rate. Yields and residue were not influenced by irrigation treatments in plots previously planted with SpW or GGLF. Despite no treatment effects in Trial 2, SpW produced higher grain yields but less residue than Trial 1. Our experiments suggest that the influence of a previous season's CC on SpW may be overshadowed by management decisions or current growing conditions but also indicate wheat yields are not systematically improved or diminished by a single preceding CC.

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.

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.

Agroecosystems comprise environmental, economic, and social components with complex interactions that affect systemwide performance. Attempts to describe or predict how agroecosystems respond to management must account for these interconnected components, so approaches that are limited to a single discipline cannot capture the complexities necessary for a holistic understanding of performance. The goal of this research is to develop a system dynamics (SD) modeling framework that can provide quantitative measures of consequences of management on each component of an agroecosystem. A SD framework is proposed with a description of model components, as well as an illustration of methodological steps to evaluate model performance through calibration, validation, and sensitivity testing. The model structure is based on a complex web of (i) stocks that describe the system's state, (ii) flows that represent the direction and rate of change, and (iii) auxiliary parameters that assign quantitative values to each component. The capacity of the model to adequately evaluate agroecosystem response is demonstrated using a case study investigating environmental, economic, and social indicators while manipulating multiple management practices, including cover crops, tillage, and integration of crop and livestock operations. Importantly, the SD model identified tradeoffs in the three indicators that accurately reflect producer experiences when making management decisions. For example, the integration of cash crops, cover crops, and livestock clearly improves economic and environmental endpoints while negatively impacting social quality with reduction in leisure time. These findings suggest the SD modeling framework provides a viable approach for the quantitative evaluation of management interventions that can be adapted to a range of complex agroecosystems.

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.

High‐protein wheat ( Triticum aestivum L.) grain is useful for bread flour, and normalized difference vegetation index (NDVI) can be useful in predicting crop yields and assessing overall crop health in response to a wide variety of management systems. However, protein and NDVI responses to nitrogen rates in systems containing cover crops have been understudied in spring wheat. Protein, grain yield, and NDVI measurements were collected during the spring wheat phase of spring wheat–pea ( Pisum Sativum L.)/cover crop rotations in different plots in 2018 and 2019 at the Northern Great Plains Research Laboratory, Mandan, ND. Grain protein concentration increased with nitrogen (N) rate, but not every level of N rate was significantly different. This result suggests that preceding pea then cover crop mixture can slightly reduce the nitrogen fertilizer requirements of subsequent spring wheat. Spring wheat NDVI did not significantly respond to categorical nitrogen rates, but continuous N rate had a small positive effect. Adding NDVI heterogeneity (as measured by the nugget:sill ratio) improved peak NDVI‐based spring wheat grain yield predictions at the relatively small scales that were measured.

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.

Background: Despite being the first genetic disease described, sickle cell disease (SCD) continues to afflict millions of individuals worldwide. Patients with SCD can experience severe complications, including vasoocclusive crisis (VOC), which can progress to acute chest syndrome (ACS), a form of acute lung injury. While VOC can cause significant morbidity, ACS is the leading cause of mortality in patients with SCD. Despite the devastating consequences of ACS, no interventions exist that directly treat this complication. As a result, when patients present with ACS, options often remain limited to supportive care. The lack of optimal treatment options for patients with SCD experiencing ACS directly contributes to their morbidity and mortality. Using a combined approach of prospective observational studies in patients with SCD that experienced ACS and a novel preclinical model specifically designed to define the role of complement in SCD pathophysiology, we tested the hypothesis that complement plays a central role in the pathophysiology of ACS. Methods: Samples from patients with SCD experiencing ACS were compared to baseline measurements for the same patient obtained at outpatient follow up 4-6 weeks later. ELISA based assays were used to measure Ba, Bb, C3a, C5a, C5b-9 (membrane attack complex (MAC)) in each sample. SCD mice (HbSS) and control mice (HbAA) were injected with 7.5 units of cobra venom factor (CVF), a potent complement activator, followed by evaluation of hematocrit (Hct) measured by a Sysmex veterinary hematology analyzer, free heme by calorimetric assay, and complement deposition on red blood cells (RBCs) by flow cytometry or pulmonary endothelial cells by confocal analysis. Respiratory rate and O2 saturation were measured using a MouseOx pulse oximeter. HbSS or HbAA mice were crossed with complement component 3 (C3) knock out (KO) mice to generate HbSS x C3 KO and HbAA x C3 KO mice. Hemin (70 to 210 mmol/kg concentration) or CVF (7.5 units/mouse) were injected into HbSS, HbAA, HbSS x C3 KO or HbAA x C3 KO followed by evaluation of hemolysis, C3 deposition and pulmonary function. A one-way ANOVA with a Tukey's post hoc with a p value <0.05 was considered significant. Results: During ACS in patients, significant elevations in Ba and Bb, complement activation products unique to the alternative pathway, and downstream activation of complement, including C3a, C5a and MAC, were observed (p<0.0001). Changes in complement activation were accompanied by a drop in hemoglobin during ACS when compared to baseline (p<0.001), suggesting that complement activation results in hemolysis. To formally test this, the impact of complement activation in a preclinical model of SCD was defined. Injection of CVF or hemin resulted in rapid C3 deposition on RBCs and pulmonary endothelium in HbSS, but not HbAA, recipients. In addition, CVF or hemin injection was accompanied by increased hemolysis and ACS manifested by increased respiratory rate, drop in oxygen saturation and death within 2 hours in the majority of recipients (p<0.001). In contrast, control Hb AA mice were unaffected by CVF or hemin injection. Given the role of free heme in the development of ACS, we next defined the role of complement in hemin-induced lung injury. To accomplish this, SCD mice were crossed with C3 KO mice to generate HbSS x C3 KO. HbSS x C3 KO mice displayed a mild increase in Hb values at baseline (p<0.01), suggesting a role of C3 even in steady-state SCD-related hemolysis. Equally important, injection of HbSS x C3 KO mice with CVF or hemin failed to result in the same levels of C3 deposition, hemolysis, compromised pulmonary function, or mortality (p<0.001) as HbSS recipients. Discussion: These results demonstrate a critical role for C3 in the development of acute lung injury in SCD. The sensitivity of HbSS RBCs to complement-induced hemolysis and C3 deposition observed following hemin injection in SCD recipients suggests that C3 plays a key role in decreased hematocrits and pulmonary injury that accompanies ACS. As treatment of ACS largely relies on supportive care, these results suggest that approaches aimed at targeting complement activation may represent a useful prophylactic or treatment strategy for ACS. In doing so, these results hold promise in providing a more direct approach at reducing one of the most severe complications of patients with SCD.

Abstract Introduction: Sickle haemoglobin (HbS) polymerisation perturbs red blood cell (RBC) rheology and drives sickle cell disease (SCD) pathophysiology. Voxelotor is an HbS polymerisation inhibitor that increases haemoglobin (Hb)–oxygen affinity. Methods/Results: In this 48‐week, prospective, single‐centre translational study, 10 children aged 4–11 years with SCD were treated with voxelotor. Improvements in RBC deformability were observed using osmotic/oxygen gradient ektacytometry, with increases in minimal and maximal elongation index and reductions in point of sickling. Increased Hb and reduced markers of haemolysis were also observed. Conclusion: These findings suggest that voxelotor treatment is associated with reduced RBC sickling and haemolysis in children with SCD.

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.

Integrated crop-livestock systems (ICLS) are more complex to properly manage than specialized farming systems due to multiple interactions between crops, livestock, and grassland. Despite individual and structural barriers to adopting sustainable ICLS, some innovative producers have successfully conducted integrated production practices. In this context, a research gap exists in understanding the motivations and incentives for transitioning to such systems. This study aims to address ICLS adoption barriers by analyzing the trajectory, achievements, and thought processes of 15 producers practicing ICLS. Our objectives were to (1) highlight producers’ perceptions of ICLS levers and barriers and (2) identify turning point factors that enabled producers to overcome the barriers. We used a unique set of cases in three continental regions (southern Brazil, the northern Great Plains region in the United States, and southern France) and conducted semi-structured interviews. Interviewees emphasized that ICLS imply dealing with barriers ranging from mindset change to operational adaptations, but they also emphasized the rewarding nature of ICLS when properly managed. All their trajectories had important turning points, such as programs or initiatives, human influence, and broader social and economic reasons that resulted in shifts in their production practices and thought processes. The cases also highlighted that integrating crops and livestock positively impacted family producers’ business outcomes, soil health, and livelihood options. Still, individual barriers, including operational management, and structural barriers, including stakeholder awareness and commitment, must be overcome. Encouraging initiatives that offer a systemic approach and promote knowledge exchange can address part of ICLS adoption barriers. Initiatives must embrace a broader innovation ecosystem, having extension teams in close contact with researchers and stakeholders to assist producers in providing support for a more sophisticated level of management that ICLS require. Overall, we found commonalities in consciousness and proactiveness in remarkable cases that could inspire broader sustainability transitions.

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.

Brassicaceae oilseed crops have proven potential as vegetable oil feedstock for biofuels and food uses. However, meeting a growing demand for vegetable oils for food and industrial uses will require identifying oilseed species that are best suited for various growing environments within a particular region. The objective of this study was to compare growth dynamics, seasonal water use (WU), seed yields, and water use efficiency (WUE) of canola ( Brassica napus L.), camelina ( Camelina sativa L.), and white mustard ( Sinapis alba L.) to determine their suitability under three different environments within the northern Great Plains. Comparisons were made among these species over three growing seasons between 2013 and 2016 at Morris, MN; Mandan, ND; and Sidney, MT, situated along a strong precipitation gradient from east to west. Generally, growing season precipitation was similar at Morris and Mandan, but both were considerably greater than at Sidney. Seasonal WU was similar among these oilseed species at Morris and Mandan but was greatest for camelina at the drier Sidney environment. Canola seed yield was the greatest at Morris and had higher WUE than camelina and white mustard. At Mandan and Sidney, canola and camelina had similar seed yields and WUE, which were generally greater than white mustard. Under abundant moisture and low stress (e.g., Morris), seed yield per millimeter of water used could be maximized by growing canola, while in a drier more stressful environment like Sidney, seed yield per millimeter of water used could be maximized by growing camelina.