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ABSTRACT Land conversion for intensive agriculture produces unfavorable changes to soil ecosystems, causing global concern. Soil bacterial communities mediate essential terrestrial ecosystem processes, making it imperative to understand their responses to agricultural perturbations. Here, we used high-throughput sequencing coupled with a functional gene array to study temporal dynamics of soil bacterial communities over 1 year under different disturbance intensities across a U.S. Southern Plains agroecosystem, including tallgrass prairie, Old World bluestem pasture, no-tillage (NT) canola, and conventional tillage (CT) wheat. Land use had the greatest impact on bacterial taxonomic diversity, whereas sampling time and its interaction with land use were central to functional diversity differences. The main drivers of taxonomic diversity were tillage > sampling time > temperature, while all measured factors explained similar amounts of variations in functional diversity. Temporal differences had the strongest correlation with total nitrogen > rainfall > nitrate. Within land uses, community variations for CT wheat were attributed to nitrogen levels, whereas soil organic matter and soil water content explained community variations for NT canola. In comparison, all measured factors contributed almost equally to variations in grassland bacterial communities. Finally, functional diversity had a stronger relationship with taxonomic diversity for CT wheat compared to phylogenetic diversity in the prairie. These findings reinforce that tillage management has the greatest impact on bacterial community diversity, with sampling time also critical. Hence, our study highlights the importance of the interaction between temporal dynamics and land use in influencing soil microbiomes, providing support for reducing agricultural disturbance to conserve soil biodiversity. IMPORTANCE Agricultural sustainability relies on healthy soils and microbial diversity. Agricultural management alters soil conditions and further influences the temporal dynamics of soil microbial communities essential to ecosystem functions, including organic matter dynamics, nutrient cycling, and plant nutrient availability. Yet, the responses to agricultural management are also dependent on soil type and climatic region, emphasizing the importance of assessing sustainability at local scales. To evaluate the impact of agricultural management practices, we examined bacterial communities across a management disturbance gradient over 1 year in a U.S. Southern Plains agroecosystem and determined that intensive management disturbance and sampling time critically impacted bacterial structural diversity, while their interactive effect influenced functional diversity and other soil health indicators. Overall, this study provides insights into how reducing soil disturbance can positively impact microbial community diversity and soil properties in the U.S. Southern Plains.

Alfalfa (Medicago sativa L.), referred to as the “Queen of Forages” because of its importance among forage crops, provides high quality forage for the livestock industry. The timing and frequency of alfalfa hay harvesting have implications on its quality and quantity. With ever-increasing capability, it is possible to use satellite remote sensing data to monitor alfalfa harvests. This study investigated the potential of using satellite remote sensing to capture frequent harvesting events on an alfalfa field in central Oklahoma. Both passive remote sensing data, namely Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat-7 and -8, Sentinel-2, Harmonized Landsat and Sentinel-2 (HLS), and active remote sensing data, namely Sentinel-1, were included. Our results indicate that good quality optical remote sensing datasets (i.e., cloud and cloud shadow free) with both fine spatial (≤100 m) and high temporal (effective observation at 8-day intervals or better) resolutions are necessary to detect frequent alfalfa harvesting events, challenged by possible adverse weather conditions and quick regrowth of vegetation after harvest. Landsat (7 and 8) and Sentinel-2 were more sensitive to changes in vegetation indices after harvest than MODIS due to their higher spatial resolutions, which helped avoid the mixed pixel issue in MODIS caused by its coarser spatial resolution (∼500 m). Combining Landsat (7 and 8) with Sentinel-2 imageries through linear regression between the Normalized Difference Vegetation Index (NDVI) values, up to one week apart, increased the accuracy of detecting frequent alfalfa harvesting events. The responses of HLS to alfalfa harvesting events were similar with fused Landsat and Sentinel-2 data using their linear relationship of NDVI values. However, the high noise level in the HLS data needs to be minimized before it can be used to detect alfalfa harvests at the regional scale. In most cases, both Sentinel-1 radar backscatter coefficients (vertical transmit and vertical receive, VV + vertical transmit and horizontal receive, VH) and interferometric coherence from Sentinel-1 Simple Look Complex (SLC) data were decreased by harvesting events in small incident angle observations (34.31°). No consistent relationships existed between backscatter or coherence and alfalfa harvests in larger incident angle observations (45.11°). Future studies should focus on small incident angle observations instead of processing all of the radar data, which has big data volume and is time-consuming. Overall, active radar has the potential to detect alfalfa harvesting events. However, it is visually less intuitive than optical data with incident angles, quantity harvested, and soil moisture being the compounding factors. This study illustrates that combining multiple optical sensors with a fine spatial resolution (e.g., Landsat-7, 8, and Sentinel-2) and/or fusing radar with optical remote sensing to increase the temporal resolution are promising approaches to detect frequent alfalfa harvesting events and other hay harvesting activities.

Abstract Increasing demand for agricultural products is driving grassland management intensification with subsequent impacts on ecosystem services and disservices. Key questions related to grassland production as well as environmental and social concerns must be addressed to ensure sustainability. We propose a unified perspective, addressing numerous trade‐offs and synergies between grassland ecosystem services and disservices, and considering an array of ecological and human consequences associated with history and ongoing shifts in management strategies. Much of our discussion utilizes evidence from humid grasslands; however, our examples and recommendations have global implications for the future of grassland management. We characterize four categories of ecosystem services and disservices (provisioning, supporting, regulating, and cultural) provided by perennial grasslands that are extensively managed (low or no input, never cultivated) or intensively managed (high‐input, cultivated). We explore a range of potential outcomes following transition from extensive to intensive agroecosystems around the globe. Additionally, we suggest specific research priorities to better evaluate ecosystem services and disservices across management intensities. Finally, we highlight potential benefits of landscape mosaics that include grasslands across a continuum of extensive to intensive strategies.

Carbon dioxide (CO2) fluxes and evapotranspiration (ET) during the non-growing season can contribute significantly to the annual carbon and water budgets of agroecosystems. Comparative studies of vegetation phenology and the dynamics of CO2 fluxes and ET during the dormant season of native tallgrass prairies from different landscape positions under the same climatic regime are scarce. Thus, this study compared the dynamics of satellite-derived vegetation phenology (as captured by the enhanced vegetation index (EVI) and the normalized difference vegetation index (NDVI)) and eddy covariance (EC)-measured CO2 fluxes and ET in six differently managed native tallgrass prairie pastures during dormant seasons (November through March). During December–February, vegetation phenology (EVI and NDVI) and the dynamics of eddy fluxes were comparable across all pastures in most years. Large discrepancies in fluxes were observed during March (the time of the initiation of growth of dominant warm-season grasses) across years and pastures due to the influence of weather conditions and management practices. The results illustrated the interactive effects between prescribed spring burns and rainfall on vegetation phenology (i.e., positive and negative impacts of prescribed spring burns under non-drought and drought conditions, respectively). The EVI better tracked the phenology of tallgrass prairie during the dormant season than did NDVI. Similar EVI and NDVI values for the periods when flux magnitudes were different among pastures and years, most likely due to the satellite sensors’ inability to fully observe the presence of some cool-season C3 species under residues, necessitated a multi-level validation approach of using ground-truth observations of species composition, EC measurements, PhenoCam (digital) images, and finer-resolution satellite data to further validate the vegetation phenology derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) during dormant seasons. This study provides novel insights into the dynamics of vegetation phenology, CO2 fluxes, and ET of tallgrass prairie during the dormant season in the U.S. Southern Great Plains.

From grazing lands to meat packing, beef production systems in the United States are striving to meet global demands without compromising environmental quality or local profitability. These challenges and opportunities are manifest in four US regions connected ecologically and socially through beef production: the American Southwest, the Ogallala Aquifer region, the Northern Plains, and the Upper Midwestern Corn Belt. Most calves raised on extensive, arid Southwestern ranches are exported to the Ogallala Aquifer region for finishing on grains that are grown either locally on Ogallala Aquifer water or imported from the Upper Midwest. Changes in climate, vegetation, and human demographics threaten the sustainability of the regionally-interconnected system. Heritage cattle genetics, precision ranching, and alternative supply chain options are three strategies that show promise for addressing these sustainability threats, but major knowledge gaps exist. For instance, while environmentally-friendly landscape use by Raramuri Criollo, a heritage cattle type, has been identified in several arid rangeland settings, little is known about their performance in conventional feed yards. While precision agriculture is already prevalent in croplands, less is known about how such technologies can be cost effective in arid rangelands. Moreover, many perceive grass-finishing on rangeland as environmentally friendly and beneficial for local agricultural communities, but tradeoffs involving greenhouse gas emissions, increased rangeland use, and disruption of cattle feeding systems of the Ogallala Aquifer region must be assessed. Here we introduce a USDA-NIFA Coordinated Agricultural Project designed to fill these knowledge gaps and advance sustainability of beef production linked to the US Southwest. With a boundary-spanning approach of education, participatory research, and extension, the project is identifying tradeoffs of the three strategies with explicit attention to pericoupling (i.e., socioeconomic and environmental interactions) of regions connected by beef production and full consideration of the coupled ecological and social systems within those regions.

Study region: The Little Washita River Experimental Watershed (LWREW) is located between Chickasha and Lawton in southwestern Oklahoma, US. Study focus: In this study, frequency analyses were conducted on sub-hourly precipitation event descriptors to quantify the changes in precipitation patterns commonly masked in annual analysis. Precipitation events were derived from 5-min data collected by USDA-ARS from 1961 to 2015. New hydrological insights for the region: During the 1962–2015 period, this region experienced successive regional long-term wet (1962–1995) and dry (1996–2015) dominated periods of more than 20 years each. During the wet period, precipitation intensity ranging from 1 to 12 mm were 20% less likely to occur while event daily average precipitation and number of events increased by 10% and 11%, respectively. Also, the average daily precipitation occurred more often at lower intensities. In contrast, during the dry period, instantaneous intensity ranging from 1 to 12 mm became more likely to occur (64% increase; 1996–2015) while event daily average precipitation and number of events decreased by 16% and 18%, respectively. Overall, comparisons with the baseline data (1962–2015) indicated that in the last 20 years, sub-hourly precipitation intensities have increased while daily event duration and extreme 5-min precipitation intensities larger than 24 mm (precipitation intensification below extremes) have remained unchanged.

The Ogallala Aquifer underlies 45 million ha, providing water for approximately 1.9 million people and supporting the robust agriculture economy of the US Great Plains region. The Ogallala Aquifer has experienced severe depletion, particularly in the Southern Plains states. This paper presents policy innovations that promote adoption of irrigation technology, and management innovations. Innovation in Kansas water policy has had the dual effects of increasing the authority of the state to regulate water while also providing more flexibility and increasing local input to water management and regulation. Technology innovations have focused on improved timing and placement of water. Management innovations include soil water monitoring, irrigation scheduling, soil health management and drought-tolerant varieties, crops, and cropping systems. The most noted success has been in the collective action which implemented a Local Enhanced Management Area (LEMA), which demonstrated that reduced water pumping resulted in low to no groundwater depletion while maintaining net income. Even more encouraging is the fact that irrigators who have participated in the LEMA or other conservation programs have conserved even more water than their goals. Innovative policy along with creative local–state–federal and private–public partnerships are advancing irrigation technology and management. Flexibility through multi-year allocations, banking of water not used in a given year, and shifting water across multiple water rights or uses on a farm are promising avenues to engage irrigators toward more sustainable irrigation in the Ogallala region.

With the need to increase crop production to meet the needs of a growing population, protecting the productivity of our soil resource is essential. However, conservationists are concerned that conservation practices that were effective in the past may no longer be effective in the future under projected climate change. In winter wheat cropland in the Southern Great Plains of the U.S., increased precipitation intensity and increased aridity associated with warmer temperatures may pose increased risks of soil erosion from vulnerable soils and landscapes. This investigation was undertaken to determine which conservation practices would be necessary and sufficient to hold annual soil erosion by water under a high greenhouse gas emission scenario at or below the present soil erosion levels. Advances in and benefits of agricultural soil and water conservation over the last century in the United States are briefly reviewed, and challenges and climate uncertainties confronting resource conservation in this century are addressed. The Water Erosion Prediction Project (WEPP) computer model was used to estimate future soil erosion by water from winter wheat cropland in Central Oklahoma and for 10 projected climates and 7 alternative conservation practices. A comparison with soil erosion values under current climate conditions and conventional tillage operations showed that, on average, a switch from conventional to conservation tillage would be sufficient to offset the average increase in soil erosion by water under most projected climates. More effective conservation practices, such as conservation tillage with a summer cover crop would be required to control soil erosion associated with the most severe climate projections. It was concluded that a broad range of conservation tools are available to agriculture to offset projected future increases in soil erosion by water even under assumed worst case climate change scenarios in Central Oklahoma. The problem is not one of a lack of effective conservation tools, but one of adoption and implementation. Increasing the implementation of today’s conservation programs to address current soil erosion problems associated with the large year-to-year climate variability in the Southern Great Plains would greatly contribute towards mitigation of projected future increases in soil erosion due to climate change.

Devastating wildfires in Texas, Oklahoma, and Kansas in 2016 and 2017 resulted in significant social, economic, and environmental losses, with the agricultural sector among those severely affected. Several satellite-based indices were evaluated as potential monitoring tools for post-wildfire ecological recovery and management of grasslands. All indices evaluated provided useful information and indicated rapid vegetation recovery from wildfire. The Leaf Water Stress Index (LSWI) and Gross Primary Productivity (GPP) showed a distinct response to the wildfire events, and differentiated between burned and unburned areas throughout the post-wildfire growing seasons better than the Normalized Difference Vegetative Index (NDVI) and Enhanced Vegetative Index (EVI). In particular, the LSWI may provide a useful tool for mapping the footprint of wildfire, with potential utility for organizations that provide post-fire recovery resources. The GPP, which estimates the biomass productivity of vegetation, can provide information to livestock operators to guide the re-stocking of cattle in the aftermath of wildfire. In sum, satellite-based proxies can provide timely information both to characterize a wildfire’s footprint and to guide post-fire grazing management in a manner that balances short term needs for forage with long-term productivity and ecological function.

Groundwater resources worldwide are being depleted at alarming rates since 1960 to support agriculture, industry, and domestic water demand. Water harvesting and the implementation of reduced application or more efficient irrigation technologies were identified as two of the most efficient practices to mitigate the declining patterns on groundwater resources. However, prior to implementing these practices, understanding how groundwater interacts with surface water and responds to natural and anthropogenic stressors is crucial. Integrated modeling tools that are able to exchange fluxes in both domains are needed to assess how conservation practices will affect our water resources under different projected climate and land use scenarios. This study aimed to evaluate the most likely impacts of current land management practices under the most severe projections of future climate and quantify the potential mitigation effects of three conservation scenarios on the water resources of the Fort Cobb Reservoir Experimental Watershed (FCREW) in western Oklahoma. The semicoupled SWAT-MODFLOW (SWATmf) model was used to simulate the hydrologic responses of the FCREW to a 50% reduction in the irrigation depths and the transition of 50% and 75% of croplands to rangelands under 32 distinct climate projections. Results showed that future climate can drive a reduction in the streamflow (−18%) and an increase to the depth of the water table (99%−120%) in the western part of the FCREW by the end of the century. The Fort Cobb Reservoir was expected to reduce its release after the mid-2060s to maintain its current target level. All the scenarios, aimed at decreasing groundwater extractions or implementing conservation measures, signaled a full recovery response in the groundwater levels 7−10 years after the year the conservation practices were implemented. The 50% reduction in the irrigation depths was found to elicit faster hydrologic systemic responses than the two that implemented conservation measures, which contravene tradition and would imply cessation of agricultural activities. This study can enable stakeholders to formulate timely adaptation and mitigating strategies to adopt to land use changes.

Agriculture in the Southern Great Plains of the United States depends on precipitation and temperature thresholds for productivity. The region’s climate and weather are variable, presenting farming challenges that are predicted to increase. Building and conserving healthy, resilient soil is one way farmers manage for future uncertainty. Few studies have compared soil health–managed and conventionally managed farms at the regional scale. To better understand management effects on soil health across the Southern Great Plains, we studied farms at 12 locations. We piloted the study using three of the locations, collecting soils from 10 fields per location and analyzing them for indicators of soil health. Our objective was to test the suitability of our experimental framework and identify additional indicators and analyses of interest. Our framework was generally suitable to the purpose of this study. We also noted that soil health–managed soils had organic matter stratification similar to native soils, which we plan to explore further.

The Great Plains of the USA is one of largest expanses of prairie ecosystems in the world. Prairies have been extensively converted to other land uses. The remaining prairie ecosystems are important for livestock grazing and provide benefits including habitat for avian, terrestrial, and aquatic species, carbon regulation, and hydrologic function. While producers, land management agencies, and some researchers have promoted livestock management using rotational stocking for increased production efficiency and enhanced ecosystem function, scientific literature has not provided a consensus on whether rotational stocking results in increased plant biomass or animal productivity. To address this research need, we established long-term grazing research using an adaptive management framework to encompass a wide range of production and ecological interactions on native grassland pastures. This paper describes objectives, design, and implementation of the long-term study to evaluate productivity and ecological effects of beef cow−calf management and production under continuous system (CS) or rotational system (RS) on native tallgrass prairie. Findings from 2009 to 2015 indicate that plant biomass and animal productivity were similar in the two grazing management systems. There were some indicators that forage nutritive value of standing biomass and soil nutrient content were enhanced in the RS system compared with the CS, yet individual calf body weight (BW) at weaning was greater in the CS. This prepares us to engage with producers to help determine the focus for the next phase of the research.

This research compared the accuracy of laboratory reference measurements of soil C and N fractions with soil reflectance spectra acquired using a portable field spectroradiometer with an illuminating contact probe. Soil samples were taken from eight, 1.6 ha watersheds, located in El Reno, Oklahoma on native warm season grasslands and agronomic managements with landform complexes serving as replicates within and among treatments. Soil samples were taken from 0−30-cm. Measurements included total soil organic carbon (TSOC), total soil nitrogen (TSN), residual C of acid hydrolysis (RCAH), and particulate organic matter C (POMC) and N (POMN). Soil reflectance in the 350 to 2500 nm region was correlated with individual laboratory measurements. Each reference dataset was divided into model development data (70%) and model validation data (30%). Calibrated models were applied to validation datasets. Statistical analysis revealed that prediction efficiencies of soil reflectance models were highly quantitative. Coefficients of determination (R2) were near 1 (≥0.90) and ratios of predicted values to the measured standard deviation (RPD) were >2, indicative of good predictive models. The field spectroradiometer enabled us to parameterize soil spatial variability and soil reflectance measurements, reducing the resources required to acquire edaphic measurements.

This study evaluated the impacts of different grazing treatments (continuous (C) and rotational (R) grazing) on tallgrass prairie landscape, using high-spatial-resolution aerial imagery (1-m at RGB and near-infrared bands) of experimental C and R pastures within two replicates (Rep A and Rep B) in the southern Great Plains (SGP) of the United States. The imagery was acquired by the National Agriculture Imagery Program (NAIP) during the agricultural growing season of selected years (2010, 2013, 2015, and 2017) in the continental United States. Land cover maps were generated by combining visual interpolation, a support vector machine, and a decision tree classifier. Landscape metrics (class area, patch number, percentage of landscape, and fragmentation indices) were calculated from the FRAGSTATS (a computer software program designed to compute a wide variety of landscape metrics for categorical map patterns) based on land cover results. Both the metrics and land cover results were used to analyze landscape dynamics in the experiment pastures. Results showed that both grass and shrubs of different pastures differed largely in the same year and had significant annual dynamics controlled by climate. High stocking intensity delayed grass growth. A large proportion of bare soil occurred in sub-paddocks of rotational grazing that were just grazed or under grazing. Rep A experienced rapid shrub encroachment, with a large proportion of shrub at the beginning of the experiment. Shrub may occupy 41% of C and 15% of R in Rep A by 2030, as revealed by the linear regression analysis of shrub encroachment. In contrast, shrub encroachment was not significant in Rep B, which only had a small number of shrub patches at the beginning of the experiment. This result indicates that the shrub encroachment is mainly controlled by the initial status of the pastures instead of grazing management. However, the low temporal resolution of the NAIP imagery (one snapshot in two or three years) limits our comparison of the continuous and rotational grazing at the annual scale. Future studies need to combine NAIP imagery with other higher temporal resolution imagery (e.g., WorldView), in order to better evaluate the interannual variabilities of grass productivity and shrub encroachment.

Early warning of detrimental weather and climate (particularly drought) on forage production would allow for tactical decision-making for the management of pastures, supplemental feed/forage resources, and livestock. The standardized precipitation and evaporation index (SPEI) has been shown to be correlated with production of various cereal and vegetable crops, and with above-ground tree mass. Its correlation with above-ground grassland or forage mass (AGFM) is less clear. To investigate the utility of SPEI for assessing future biomass status, we used biomass data from a site on the Konza Prairie (KP; for years 1984−1991) and from a site at the United States Department of Agriculture-Agricultural Research Service’s (USDA-ARS) Grazinglands Research Laboratory (GRL; for years 2009−2015), and a publicly-available SPEI product. Using discriminant analysis and artificial neural networks (ANN), we analyzed the monthly timescale SPEI to categorize AGFM into above average, average, and below average conditions for selected months in the grazing season. Assessment of the confusion matrices from the analyses suggested that the ANN better predicted class membership from the SPEI than did the discriminant analysis. Within-site cross validation of the ANNs revealed classification errors ranging from 0 to 50%, depending upon month of class prediction and study site. Across-site ANN validation indicated that the GRL ANN algorithm better predicted KP AGFM class membership than did the KP ANN prediction of GRL AGFM class membership; however, misclassification rates were ≥25% in all months. The ANN developed from the combined datasets exhibited cross-validation misclassification rates of ≤20% for three of the five months being predicted, with the remaining two months having misclassification rates of 33%. Redefinition of the AGFM classes to identify truly adequate AGFM (i.e., average to above average forage availability) improved prediction accuracy. In this regard, results suggest that the SPEI has potential for use as a predictive tool for classifying AGFM, and, thus, for grassland and livestock management. However, a more comprehensive investigation that includes a larger dataset, or combinations of datasets representing other areas, and inclusion of a bi-weekly SPEI may provide additional insights into the usefulness of the SPEI as an indicator for biomass production.

Native grasslands in the Great Plains of North America have mostly disappeared in the past century due to agricultural expansion. A grazing study was established on Paleustolls and Argiustolls supporting a remnant, but historically grazed tallgrass prairie in central Oklahoma. Stocking method of beef cattle was differentiated into continuous and rotational treatments (10 sub-paddocks) in 2009 and these treatments continued until present. Soil was sampled in 2009 and 2012 at depths of 0–6, 6–12, 12–20, and 20–30 cm and in 2017 at depths of 0–15 and 15–30 cm. Total, particulate, microbial biomass, and mineralizable C and N fractions were highly stratified with depth, having 2–10 times greater concentration at a depth of 0–6 cm as that at 20–30 cm. Strong associations existed among most of these soil organic C and N fractions, given the large range that resulted from sampling at multiple depths. No discernable differences in soil organic C and N fractions occurred due to stocking method at any sampling time or depth. Evidence for biological nitrification inhibition suggested a mechanism for conservation of available N with less opportunity for loss. In addition, strong association of available N with biologically active C indicated slow, but sustained release of N that was strongly coupled to C cycling. We conclude that stocking method had a neutral effect on conservation of already high antecedent conditions of soil organic C and N fractions during the first 8 years of differentially imposed management.

Cattle grazing is an important economic activity in the tallgrass prairie systems in the Great Plains of the United States. Tallgrass prairie may respond differently to grazing management (e.g., high and low grazing intensity) under variable climate conditions. This study investigated the responses of two replicated (rep a and rep b) tallgrass prairie systems to continuous (C) and rotational (R) grazing under different climate conditions over a decade (2008−2017). The enhanced vegetation index (EVI) and gross primary productivity (GPP) were compared between grazing systems (C vs. R), while EVI was compared among paddocks under rotational grazing to show the impacts of time since grazing. The average EVI in rep a was usually higher than that in rep b which could be explained by different land characteristics (e.g., soil types) associated with different landscape positions. Similar to EVI, GPP was usually higher in rep a than rep b. The average growing season EVI and GPP were higher in rotational grazing than continuous grazing in rep b but not in rep a. The average EVI of paddocks in rotational grazing systems only converged in the growing season-long drought year (2011). In other years, EVI values varied from year to year and no paddock consistently outperformed others. The variations in EVI among rotational grazing paddocks in both reps were relatively small, indicating that rotational grazing generated an even grazing pressure on vegetation at annual scale. Overall, climate and inherent pasture conditions were the major drivers of plant productivity. However, the stocking rate in continuous grazing systems were reduced over years because of deteriorating pasture conditions. Thus, the results indirectly indicate that rotational grazing improved grassland productivity and had higher stocking capacity than continuous grazing systems under variable climate conditions. Adaptive grazing management (adjustment in stocking rates and season of use to adapt to changing climatic conditions) instead of a fixed management system might be better for farmers to cooperate with changing climatic conditions.

Meeting the ever-increasing global food, feed, and fiber demands while conserving the quantity and quality of limited agricultural water resources and maintaining the sustainability of irrigated agriculture requires optimizing irrigation management using advanced technologies such as soil moisture sensors. In this study, the performance of five different soil moisture sensors was evaluated for their accuracy in two irrigated cropping systems, one each in central and southwest Oklahoma, with variable levels of soil salinity and clay content. With factory calibrations, three of the sensors had sufficient accuracies at the site with lower levels of salinity and clay, while none of them performed satisfactorily at the site with higher levels of salinity and clay. The study also investigated the performance of different approaches (laboratory, sensor-based, and the Rosetta model) to determine soil moisture thresholds required for irrigation scheduling, i.e., field capacity (FC) and wilting point (WP). The estimated FC and WP by the Rosetta model were closest to the laboratory-measured data using undisturbed soil cores, regardless of the type and number of input parameters used in the Rosetta model. The sensor-based method of ranking the readings resulted in overestimation of FC and WP. Finally, soil moisture depletion, a critical parameter in effective irrigation scheduling, was calculated by combining sensor readings and FC estimates. Ranking-based FC resulted in overestimation of soil moisture depletion, even for accurate sensors at the site with lower levels of salinity and clay.