Research Project: Science and Technologies for the Sustainable Management of Western Rangeland Systems

Location: Range Management Research

2022 Annual Report

Objectives
1: Develop or improve livestock management & restoration practices to promote resilience to climate variability & adaptation to increasingly shrub-dominated environments. 1A: Compare productivity & environmental impacts of Raramuri Criollo cattle to conventional livestock production systems in the arid Southwest (part of LTAR Common Experiment). 1B: Develop collaborative science approaches to test the efficacy of practices to recover & sustain perennial grass cover in the desert grassland region. 2: Leveraging temporal & spatial datasets from the Jornada & surrounding region, design & implement big data-model integration approaches to predict and/or resolve disease outbreaks & other regional agricultural problems. 2A: Develop a strategy & operational framework for a gricultural Grand Challenges that require big data & trans-disciplinary scientific expertise based on spatio-temporal modeling of cross-scale interactions & interactive machine learning. 2B: Develop national wind erosion assessments using big data & models developed through the National Wind Erosion Research Network. 3: Improve understanding of ecological state change in the desert grassland region through synthesis & analysis of long-term climate, vegetation, & livestock data, alongside numerous ongoing short- and long-term experiments, including how gradual & abrupt transitions occur in rangeland agroecosystems & how they can be managed. 3A: Predict alternative states in Western rangelands by integrating multiple lines of evidence including spatiotemporal modeling. 3B: Formulate phenological indicators of gradual & abrupt changes in primary production using integration of remotely-sensed imagery and ground-based observations. 4: Complete development of a new database to improve quality, accessibility, & utility of Ecological Site Description (ESD) information nationwide, & collaborate with NRCS to complete national population of ESD information. 5: Develop tools & techniques for managing & integrating ground-based assessment & monitoring data, remotely sensed & digital spatial data, & connect data to interpretive frameworks & models to develop actionable interpretations for land management. 5A: Develop tools & techniques for managing & integrating ground-based assessment and monitoring data, remotely sensed and digital spatial data, and connect data to interpretive frameworks and models to develop actionable interpretations for land management. 5B: Develop, test, and facilitate adoption of a data collection and decision support system that increases land manager ability to monitor their land, and to access, evaluate, integrate and apply local and scientific knowledge. 6: Develop new tools and information to assist agricultural stakeholders in coping with climate variability through: research, science translation & information synthesis; tool development & technology transfer; stakeholder outreach & education (Southwest Regional Climate Hub). 7: Operate & maintain the Jornada Experimental Range LTAR network site using technolgies & practices agreed upon by LTAR leadership. Contribute to the LTAR working groups & common experiments as resources allow.

Approach
1a. We will initiate a grazing experiment to determine whether ecosystem parameters respond differently to grazing of Raramuri Criollo and common British breeds; compare behavioral attributes; and monitor input and output parameters to evaluate productivity of these two types of cattle.1b. We will embed monitoring experiments in public lands brush management treatments to determine the circumstances of successful grassland restoration and test the role of soil properties in grass restoration. 2a. We will use interactive machine learning to improve predictions of Vesicular Stomatitis Virus occurrence. 2b. We will develop a national, standard, public dataset coupled to an improved wind erosion model to develop scalable, precise wind erosion estimates. 3a. We will model spatiotemporal dynamics of ecosystems based on Jornada long-term data to develop a novel approach for spatial predictions of ecosystem processes. 3b. We will use multi-scale measurements of plant phenology to improve estimates of climate impacts on agricultural production. 4a. We will expand an ecological site database (EDIT) to make management-relevant information more widely available. 5a. We will develop training and user support systems to make national rangeland monitoring datasets more useful to the public. 5b. We will expand capabilities of LandPKS mobile apps to provide accurate estimates of soil processes and linkages to other databases. 6. We will use climate science synthesis, web tool development, and collaborative outreach to improve adaptive capacity of Southwestern producers and managers. 7. We will contribute network-level research, local research, and data sharing to advance national LTAR goals.

Progress Report
Progress was made in all seven objectives. Raramuri Criollo (RC) cattle are being evaluated for their suitability for low-input production systems in arid southwestern rangelands (Objective 1A). This biotype exhibits behaviors that are well matched to extensive rangeland conditions. Performance of RC x Brangus crossbred calves were compared to Brangus calves on wheat pasture and in the feedlot. Results from the first year showed comparable average daily gains for crossbreds and purebreds, suggesting crossbreeding may be a way to capitalize on cow attributes that impose fewer constraints on movement and optimize use of available forage on southwestern rangelands, while producing a calf with desirable growth performance. Evaluation of conservation practices for restoration of desert grasslands continued (Objective 1B). Experiments were implemented that couple shrub removal with novel devices that reduce sediment transport and enhance grass establishment (connectivity modifiers) for grassland restoration. The combination of shrub control and connectivity modifiers enhanced grass recovery rates and may have potential for accelerating grass recovery in degraded southwestern rangelands. Progress was made in developing a framework for agricultural Grand Challenges using big data and trans-disciplinary scientific expertise (Objective 2A). ARS scientists in Las Cruces, New Mexico, collaborated with other ARS research locations and Animal and Plant Health Inspection Service researchers to determine the impact of drought on the spread of two vector-borne equine diseases: West Nile Virus (WNV) and Vesicular Stomatitis Virus (VSV). Spread of WNV exhibited a peak while VSV spread was diminished in counties across the U.S. during the June flash drought, suggesting the ability to protect the health of the U.S. horse population could be increased by improving the ability to predict flash drought. National Wind Erosion Research Network (NWERN) data collected by researchers across the U.S. (Objective 2B) was used to create regional simulations of wind erosion for U.S. grazing lands using a model developed and calibrated with the NWERN database. Inputs from standardized inventory and monitoring datasets collected by Bureau of Land Management (BLM) and Natural Resources Conservation Service (NRCS) partners at approximately 70,000 locations were used to produce wind erosion indicators for each location. Wind erosion risk across U.S. grazing lands and trends through time were analyzed and initial analyses revealed hotspots for wind erosion. Access to wind erosion indicators will allow land managers to incorporate wind erosion information into land health assessments and management planning. Models continue to be developed to help understand and predict climate-driven vegetation changes in southwestern rangelands using long-term datasets, sensor and imagery products, and conceptual models (Objective 3A). A 101 year record of vegetation monitoring and climate data was used to develop a predictive model of vegetation change. The Pacific Decadal Oscillation (PDO), a multi-decadal pattern of Pacific sea surface temperatures, was the best predictor of grass cover variation before 1979. After that point, grass response to the PDO was limited by shrub encroachment. New models based on long-term field data can help producers and land managers evaluate rangeland health and plan for change. Remotely sensed satellite and surface cameras can be used to map and monitor plant phenology and productivity (Objective 3B), but information to guide selection of sensors and appropriate timing of use is required. Metrics for growing season length and productivity of grazing, cropping, and mixed grazing-cropping agroecosystems were developed and a metric assessment framework was created to optimize instrument selection to monitor, model, and forecast ecosystem productivity at multiple time scales. This method allows different sources of image and climatological data sets to be integrated to help land managers and producers improve monitoring and forecasting of plant growth and anticipate changes due to weather and climate. The web-based Ecosystem Dynamics Interpretive Tool (EDIT; Objective 4) was expanded during the past year. This national database housing natural resource information contains 5136 complete Ecological Site Descriptions (ESDs) and receives about 126,000 views per month. A parallel web database Ecosystem Dynamic Interpretive Tool Global (EDIT) was created this year. These databases allow land managers globally to access ESDs that provide a scientific basis for site specific conservation practices and management decisions. Standardized tools and techniques were developed for multi-scale inventory, monitoring, and assessment of rangelands (Objective 5A). A collection of papers was assembled in a special issue to capture progress on standardizing methods for adaptive monitoring of rangelands. This collection contains the latest advances for monitoring tools and techniques in one location and establishes a framework for teaching the next generation of scientists how to design and implement high quality monitoring programs. Sampling strategy guidelines and data analysis tools will allow land managers to make meaningful decisions on management and conservation of millions of acres of rangeland. Progress was also made on the development of the Land-Potential Knowledge System (LandPKS) application (Objective 5B). The Habitat module was expanded to include over 100 species and a new module was added that allows over 100 soil conservation technologies to be filtered. Also, the SoilID function was enhanced and specifications for the next generation of LandPKS tools were also developed. These tools will be combined with other applications to develop information databases for identification of management options to enhance global land productivity and sustainability. Progress was also made in building climate-resilient landscapes and communities in the Southwest (Objective 6). During the past year, the Southwest Climate Hub teamed with the other members of the network to broaden its reach through partnership and collaboration, hosting nine drought briefings (reaching at least 2,700 listeners). The indigenous collaboration team of the Drought Learning Network co-hosted an in-person tribal drought summit. Natural resource managers from more than 11 pueblos attended and expanded precipitation monitoring on tribal lands via installment of more than 50 rain gauges. The Long-Term Agroecosystem Research (LTAR) network, composed of 18 research sites across the U.S., coordinates research activities in a variety of conditions and environments at a national scale (Objective 7). ARS scientists in Las Cruces, New Mexico led a network initiative to identify indicators to measure the performance of agricultural innovations being examined across the LTAR network. Four major types of innovations were identified (farm/ranch practices, manureshed management, phenology monitoring systems, and knowledge co-production). Also, the "Manureshed" management program, which develops innovative systems to recycle fertilizer nutrients between the nation's animal and crop production systems, worked to identify and promote opportunities for manure nutrient recycling across agricultural supply chains. These efforts will help agricultural industries cope with unprecedented fertilizer costs which are increasing food prices and concerns over food security.

Accomplishments
1. Hotspots for wind erosion identified in U.S. rangelands using big data. Rangeland and cropland wind erosion reduces soil productivity, impacts water resources, and causes highway fatalities, human health problems, and infrastructure damage. Long-term networked research using standardized methodology is needed to accurately measure and model effects of management practices on wind erosion to mitigate this problem. ARS scientists in Las Cruces, New Mexico, developed regional simulations of wind erosion for U.S. grazing lands using the Aeolian Erosion (AERO) model they developed and calibrated using National Wind Erosion Research Network (NWERN) data. AERO inputs were produced for ~70,000 locations (2011-2020) from standardized inventory and monitoring datasets collected by partners at Bureau of Land Management (BLM) and Natural Resources Conservation Service (NRCS) and the model implemented using the USDA scientific computing initiative (SCINet) to produce probabilistic estimates of wind erosion indicators for each location. Preliminary analyses are revealing hotspots for rangeland wind erosion and interactions between erosion and invasive plant species. The Landscape Data Commons Application Programming Interface was extended to enable public access to the AERO indicators. For the first time, this will enable land managers to access grazing land wind erosion indicators and incorporate wind erosion information into land health assessments and land use and resource management planning.

2. Comprehensive indicators to evaluate agricultural innovations. ARS scientists in Las Cruces, New Mexico, led an initiative on indicators to measure the performance of agricultural innovations under investigation across the Long-Term Agroecosystem Research Network. A survey was conducted of network scientists to identify the innovations for which performance indicators are needed; four major types of innovations were identified (farm/ranch practices, manureshed management, phenology monitoring systems, and knowledge co-production). The initiative also built consensus on a “menu” of indicators that measure the status of six attributes of sustainable agricultural systems at farm/ranch scales. Measurable, general, and robust indicators that reflect a full range of interests in U.S. agricultural production systems will improve communication and speed adoption of useful agricultural innovations.

3. Prediction of climate-driven vegetation state changes. Changes in climate can have complex effects on rangeland vegetation that are difficult to predict. A lack of predictions limits the ability of producers and land managers to plan for change. ARS scientists in Las Cruces, New Mexico, used a 101 year record of vegetation monitoring and climate data to develop a predictive model of vegetation change. The Pacific Decadal Oscillation (PDO), a multi-decadal pattern of Pacific sea surface temperatures, proved to be the best predictor of variation in grass cover until 1979, likely due to its effect on local water stress. After 1979, shrub encroachment limited grass response to the PDO, but the next positive PDO period is predicted to favor grass recovery in restoration treatments. The new model based on long-term field data can assist land managers in evaluating rangeland health and long-term planning for rangeland restoration.

4. Shrub control plus erosion control accelerates grass restoration. The ability to restore historical grassland productivity in degraded arid rangelands is often limited and land managers seek new strategies to enhance restoration success. ARS scientists in Las Cruces, New Mexico, collaborated with researchers at New Mexico State University to implement experiments on the Jornada Experimental Range that couple shrub removal with simple, novel devices that reduce sediment transport and enhance grass establishment (connectivity modifiers) for grassland restoration. Results indicate that shrub control with connectivity modifiers have a strong synergistic effect on rates of grass recovery. Coupling shrub removal with other interventions may be a promising approach to accelerate grass recovery in degraded Southwestern rangelands.

5. Mobile applications to improve land management decisions. Land managers in the U.S. currently lack an efficient system for accessing and sharing knowledge about land management that is relevant to the potential of their land. Because land potential depends on soil, topography and climate, the identification of appropriate management systems begins by matching areas with similar conditions. ARS scientists in Las Cruces, New Mexico, continued development of the LandPKS mobile app on iOS and Android phones and tablets allowing managers to rapidly identify their soil and access soil survey information (LandInfo) and monitor vegetation (Vegetation), both of which are necessary to support outcome-based rangeland management. The Habitat module was expanded to include over 100 species, a new module providing access and the ability to filter over 100 soil conservation technologies was added, and the SoilID function was further improved. Specifications for the next generation of LandPKS tools were also drafted. These tools will be combined with other applications to develop information databases for identification of management options for enhanced global land productivity and sustainability.

6. Drought-adapted heritage cattle performance measured. Raramuri Criollo (RC) cattle have undergone approximately 500 years of natural selection and adaptation to harsh rangeland conditions. RC cows exhibit behavioral traits that are well matched to the environmental conditions of extensive arid rangelands. ARS scientists in Las Cruces, New Mexico, compared performance of RC x Brangus crossbred calves vs purebred Brangus calves on wheat pasture and in the feedlot. Preliminary results based on the first year of data revealed comparable average daily gain for crossbreds and purebreds on wheat pasture and feedlot. These preliminary results suggest RC crossbred calves may perform similarly to conventional cattle while capitalizing on attributes of the dams that impose fewer constraints on movement and optimize use of available forage on southwestern rangelands.

7. Choosing the right sensors to track agricultural productivity. Technology offers many options for tracking rangeland and cropland production. Users need information to guide the selection of sensors and when to use them to meet management and production needs. ARS scientists in Las Cruces, New Mexico, documented differences in metrics for growing season length and productivity in grazing, cropping, and mixed grazing-cropping agroecosystems. They also presented a novel “metric assessment framework” to optimize the selection of instruments used to monitor, model, and forecast ecosystem productivity at short- and longer-term time scales. The method provided a path to integrate different sources of image and climatological data sets now available to producers and land managers for better monitoring and forecasting of primary production.

8. Synthesis of advances in rangeland health monitoring. Standardized approaches for monitoring rangelands are needed to allow land managers and public land agencies to collect and share data that address numerous rangeland management and policy needs. ARS scientists in Las Cruces, New Mexico, led a special issue, “Adaptive Monitoring in Support of Adaptive Management” in Rangelands that synthesized the latest advances in rangeland monitoring tools and techniques. The ten open-access articles, co-produced with scientists at ARS, United States Dept of Geological Survey (USGS), universities and partnering agencies (Natural Resources Conservation Service, Bureau of Land Management), present emerging research on frameworks for implementing high quality monitoring programs and teaching the next generation of rangeland scientists; sample design tools to empower spatially balanced, survey designs; strategies for incorporating meaningful qualitative assessments into monitoring protocols; remote sensing products for aiding management decisions; perspectives on leveraging vegetation monitoring data for wildlife habitat modeling and multi-scale assessments; ways to engage community-led monitoring; and examples from successful place-based monitoring and national monitoring programs. This special issue will inform and improve private and public rangeland monitoring programs to support managing multiple ecosystem services and identify areas for improving rangeland agricultural production.

9. Flash drought effects on vector-borne disease spread. Vector-borne diseases including vesicular stomatitis virus (VSV) have major economic implications for animal agriculture globally. ARS scientists in Las Cruces, New Mexico, collaborated with other ARS research locations and Animal and Plant Health Inspection Service researchers to compare climate variables with county level disease occurrence data of equine West Nile Virus (WNV) and equine vesicular stomatitis virus. Divergent impacts of temperature and drought on the spread of WNV and VSV were discovered. WNV experienced a relative peak in occurrence across the continental U.S., including the central U.S. counties impacted by drought. VSV, on the other hand, exhibited a full stop in its spread across the central. U.S. with the June flash drought. These divergent responses are likely driven by the reliance of black flies on flowing water, while mosquitoes have demonstrated increased vector competency under drought conditions. These results indicate that improved predictions of flash drought can be used to identify and mitigate threats to the health of horses across the U.S.

10. National and global database of land and agroecosystem dynamics. Ecological Site Descriptions (ESDs) provide the scientific basis for site specific conservation decisions made by planners and land managers, yet this information was not organized such that it could be readily accessed and integrated with other decision tools. A new version of the web-based Ecosystem Dynamics Interpretative Tool (EDIT) developed by ARS scientists in Las Cruces, New Mexico, was released in 2019 based on feedback from across the country. The EDIT database now contains 5136 publicly accessible and complete ESDs and receives an average of 126,000 views per month to access natural resource information from the webpage or Application Programming Interfaces linked to other tools. This year we developed a parallel web database, EDIT Global, that guides land management decision support based on state transition theory and is accessible to a global audience. The two databases dramatically improve organization and access to site-specific decision support in rangelands by land managers and the public across the world.

Review Publications
Archer, S., Peters, D.C., Burrus, D.N., Yao, J. 2022. Mechanisms and drivers of alternative shrubland states. Ecosphere. 13(4):Article e3987. https://doi.org/10.1002/ecs2.3987.
McIntosh, M., Cibils, A.F., Estell, R.E., Gong, Q., Cao, H., Gonzalez, A.L., Nyamuryekung'e, S., Spiegal, S.A. 2021. Can cattle geolocation data yield behavior-based criteria to inform precision grazing systems on rangeland? Livestock Science. 255: Article 104801. https://doi.org/10.1016/j.livsci.2021.104801.
Meinen, R.J., Spiegal, S.A., Kleinman, P.J., Flynn, K.C., Goslee, S.C., Mikesell, R.E., Church, C., Bryant, R.B., Boggess, M.V. 2022. Opportunities to implement manureshed management in the Iowa, North Carolina, and Pennsylvania swine industry. Journal of Environmental Quality. 51(4):510-520. https://doi.org/10.1002/jeq2.20340.
Nyamuryekung'e, S., Cibils, A., Estell, R.E., Vanleeuwen, D., Spiegal, S.A., Steele, C., Gonzalez, A.L., McIntosh, M.M., Gong, Q., Cao, H. 2022. Movement, activity, and landscape use patterns of heritage and commercial beef cows grazing Chihuahuan Desert rangeland. Journal of Arid Environments. 199:Article 104704. https://doi.org/10.1016/j.jaridenv.2021.104704.
Dinan, M., Adler, P., Bradford, J., Brunson, M., Elias, E.H., Felton, A., Greene, C., James, J., Suding, K., Thacker, E. 2021. Making research relevant: Sharing climate change research with rangeland advisors to transform results into drought resilience. Rangelands. 43(5):185-193. https://doi.org/10.1016/j.rala.2021.08.004.
Boughton, E., Bestelmeyer, B.T., Kleinman, P.J., Moglen, G.E., Spiegal, S.A., Tsegaye, T.D. 2021. Long-term network research for the next agricultural revolution. Frontiers in Ecology and the Environment. 19(8):432-434. https://doi.org/10.1002/fee.2403.
McCord, S.E., Pilliod, D. 2022. Adaptive monitoring in support of adaptive management in rangelands. Rangelands. 44(1):1-7. https://doi.org/10.1016/j.rala.2021.07.003.
Webb, N., LeGrand, S., Cooper, B., Courtright, E.M., Edwards, B., Felt, C., Van Zee, J.W., Ziegler, N. 2021. Size distribution of mineral dust emissions from sparsely vegetated and supply-limited dryland soils. Journal of Geophysical Research Atmospheres. 126(22):Article e2021JD035478. https://doi.org/10.1029/2021JD035478.
Edwards, B.L., Webb, N.P., Van Zee, J.W., Courtright, E.M., Cooper, B.F., Metz, L., Herrick, J.E., Okin, G., Duniway, M.C., Tatarko, J., Tedela, N., Newingham, B.A., Pierson Jr, F.B., Toledo, D.N., Van Pelt, R.S. 2021. Parameterizing an aeolian erosion model for rangelands. Aeolian Research. 54.Article 100769. https://doi.org/10.1016/j.aeolia.2021.100769.
Taylor, S.D., Browning, D.M., Baca, R.A., Gao, F.N. 2021. Constraints and opportunities for detecting land surface phenology in drylands. Journal of Remote Sensing. 2:1-15. https://doi.org/10.1101/2021.05.21.445173.
Burrus, D.N., Rodriguez, L.L., Drolet, B.S., Geil, K., Cohnstaedt, L.W., Derner, J.D., Peters, D.C. 2021. Predicting the geographic range of an invasive livestock disease across the contiguous USA under current and future climate conditions. Climate. 9(11):159. https://doi.org/10.3390/cli9110159.
Akram, H., Levia, D., Herrick, J.E., Lydiasari, H., Schütze, N. 2021. Water requirements for oil palm grown on marginal lands: A simulation approach. Agricultural Water Management. 260. Article 107292. https://doi.org/10.1016/j.agwat.2021.107292.
Taylor, S.D., Browning, D.M. 2022. Classification of daily crop phenology in PhenoCams using deep learning and hidden markov models. Remote Sensing. 14(2):286. https://doi.org/10.3390/rs14020286.
Heller, A., Webb, N.P., Bestelmeyer, B.T., Brungard, C.W., Davidson, Z.M. 2022. An inductive approach to developing ecological site concepts with existing monitoring data. Rangeland Ecology and Management. 83:133-148. https://doi.org/10.1016/j.rama.2022.03.009.
Gao, F.N., Anderson, M.C., Johnson, D., Seffrin, R., Wardlow, B., Suyker, A., Diao, C., Browning, D.M. 2021. Towards routine mapping of crop emergence within the season using the Harmonized Landsat and Sentinel-2 dataset. Remote Sensing. 13(24):5074 https://doi.org/10.3390/rs13245074.
Goodrich, D.C., Bosch, D.D., Bryant, R.B., Cosh, M.H., Endale, D.M., Veith, T.L., Kleinman, P.J., Langendoen, E.J., McCarty, G.W., Pierson Jr., F.B., Schomberg, H.H., Smith, D.R., Starks, P.J., Strickland, T.C., Tsegaye, T.D., Awada, T., Swain, H., Derner, J.D., Bestelmeyer, B.T., Schmer, M.R., Baker, J.M., Carlson, B.R., Huggins, D.R., Archer, D.W., Armendariz, G.A. 2022. Long term agroecosystem research experimental watershed network. Hydrological Processes. 36(3). Article e14534. https://doi.org/10.1002/hyp.14534. [Corrigendum: Hydrological Processes: 2022, 36(6), Article e14609. https://doi.org/10.1002/hyp.14609.]
Spiegal, S.A., Webb, N., Boughton, E., Boughton, R., Bentley-Brymer, A., Clark, P., Holifield Collins, C.D., Hoover, D.L., Kaplan, N.E., McCord, S.E., Meredith, G., Porensky, L.M., Toledo, D.N., Wilmer, H.N., Wulfhorst, J.D., Bestelmeyer, B.T. 2022. Measuring the social and ecological performance of agricultural innovations on rangelands: Progress and plans for an indicator framework in the LTAR network. Rangelands. 44:334-344. https://doi.org/10.1016/j.rala.2021.12.005.
Williams, M.R., Welikhe, P., Bos, J.H., King, K.W., Akland, M., Augustine, D.J., Baffaut, C., Beck, G., Bierer, A.M., Bosch, D.D., Boughton, E., Brandani, C., Brooks, E., Buda, A.R., Cavigelli, M.A., Faulkner, J., Feyereisen, G.W., Fortuna, A., Gamble, J.D., Hanrahan, B.R., Hussain, M., Kohmann, M., Kovar, J.L., Lee, B., Leytem, A.B., Liebig, M.A., Line, D., Macrae, M., Moorman, T.B., Moriasi, D.N., Nelson, N., Ortega-Pieck, A., Osmond, D., Pisani, O., Ragosta, J., Reba, M.L., Saha, A., Sanchez, J., Silveira, M., Smith, D.R., Spiegal, S.A., Swain, H., Unrine, J., Webb, P., White, K.E., Wilson, H., Witthaus, L.M. 2022. P-FLUX: A phosphorus budget dataset spanning diverse agricultural production systems in the United States and Canada. Journal of Environmental Quality. 51:451–461. https://doi.org/10.1002/jeq2.20351.
Kachergis, E., Miller, S.W., McCord, S.E., Dickard, M., Savage, S., Reynolds, L.V., Lepak, N., Dietrich, C., Green, A., Nafus, A., Prentice, K., Davidson, Z. 2022. Adaptive monitoring for multiscale land management: Lessons learned from the Assessment, Inventory, and Monitoring (AIM) principles. Rangelands. 44(1):50-63. https://doi.org/10.1016/j.rala.2021.08.006.
Newingham, B.A., Kachergis, E., Ganguli, A.C., Foster, B., Price, L., McCord, S.E. 2021. Lessons given and learned from rangeland monitoring courses. Rangelands. 44(1):29-38. https://doi.org/10.1016/j.rala.2021.08.003.
Spiegal, S.A., Vendramini, J.M., Bittman, S., Silveira, M., Gifford, C., Ragosta, J.P., Kleinman, P.J. 2022. Recycling nutrients in the beef supply chain through circular manuresheds: Data to assess tradeoffs. Journal of Environmental Quality. 51(4):494-509. https://doi.org/10.1002/jeq2.20365.
Dell, C.J., Baker, J.M., Spiegal, S.A., Porter, S.A., Leytem, A.B., Flynn, K.C., Rotz, C.A., Bjorneberg, D.L., Bryant, R.B., Hagevoort, R., Williamson, J., Slaughter, A.L., Kleinman, P.J. 2022. Challenges and opportunities for manureshed management across U.S. dairy systems: Case studies from four regions. Journal of Environmental Quality. 54(4):521-539. https://doi.org/10.1002/jeq2.20341.
Estell, R.E., Nyamuryekung'e, S., James, D.K., Spiegal, S.A., Cibils, A.F., Gonzalez, A.L., McIntosh, M.M., Romig, K.B. 2022. Diet selection of Raramuri Criollo and Angus x Hereford crossbred cattle in the Chihuahuan Desert. Journal of Arid Environments. 205. Article 104823. https://doi.org/10.1016/j.jaridenv.2022.104823.
Meredith, G., Spiegal, S.A., Kleinman, P.J., Harmel, R.D. 2022. The social networks of manureshed management. Journal of Environmental Quality. 51(4):566-579. https://doi.org/10.1002/jeq2.20334.
Kleinman, P.J., Spiegal, S.A., Silviera, M., Baker, J.M., Dell, C.J., Bittman, S., Cibin, R., Vadas, P.A., Buser, M.D., Tsegaye, T.D. 2022. Envisioning the manureshed: Towards comprehensive integration of modern crop and animal production. Journal of Environmental Quality. 51(4):481-493. https://doi.org/10.1002/jeq2.20382.
Ahlering, M.A., Kazanski, C., Lendrum, P., Borrelli, P., Clark, L., Ellis, C., Gadzia, K., Gelbard, J., Goodwin, J., Herrick, J.E., Kachergis, E., Knapp, C., Maczko, K., Porzig, E., Rizzo, D., Spiegal, S.A., Wilson, C. 2021. A synthesis of ranch-level sustainability indicators for land managers and to communicate across the US beef supply chain. Rangeland Ecology and Management. 79:217-230. https://doi.org/10.1016/j.rama.2021.08.011.
Armstrong, E., Rodriguez-Almeida, F.A., McIntosh, M.M., Poli, M., Cibils, A.F., Martinez-Quintana, J.A., Felix-Portillo, M., Estell, R.E. 2022. Genetic background of Criollo cattle in Uruguay, Mexico, Argentina and the United States. Journal of Arid Environments. 200. Article 104722. https://doi.org/10.1016/j.jaridenv.2022.104722.
Sun, J., Wang, Y., Liu, M., Han, G., Piao, S., Li, J., Liu, G., Wilkes, A., Liu, S., Zhao, W., Zhou, H., Yibeltal, M., Berihun Liyew, M., Browning, D.M., Fenta Almaw, A., Tsunekawa, A., Brown, J., Willms, W., Tsubo, M. 2022. Toward a sustainable grassland ecosystem worldwide. Nature Ecology and Evolution. 3(4):Article e100265. https://doi.org/10.1016/j.xinn.2022.100265.
Osborne, B., Bestelmeyer, B.T., Currier, C., Homyak, P., Throop, H., Young, K., Reed, S. 2022. The consequences of climate change for dryland biogeochemistry. New Phytologist. https://doi.org/10.1111/nph.18312.
Sumjidmaa, S., Barrio, I., Bulgamaa, D., Bestelmeyer, B.T., Asa, A. 2021. Rangeland degradation in Mongolia: A review of the evidence. Journal of Arid Environments. 196. Article 10465. https://doi.org/10.1016/j.jaridenv.2021.104654.
Lopez, D., Cavallero, L., Willems, P., Bestelmeyer, B.T., Brizuela, M. 2022. Degradation influences equilibrium and non-equilibrium dynamics in rangelands: Implications in resilience and stability. Applied Vegetation Science. Article e12670. https://doi.org/10.1111/avsc.12670.