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ARS Home » Plains Area » Fort Collins, Colorado » Center for Agricultural Resources Research » Rangeland Resources & Systems Research » Research » Research Project #436575

Research Project: Adaptive Grazing Management and Decision Support to Enhance Ecosystem Services in the Western Great Plains

Location: Rangeland Resources & Systems Research

2020 Annual Report

Objective 1-Determine the potential for adaptive grazing management to enhance beef production, vegetation heterogeneity, grassland bird conservation, carbon/energy/water balance, and soil health in western Great Plains rangelands. Subobjective 1.1–Compare responses of livestock, wildlife, plants, and soils to adaptive grazing management and traditional grazing management. Subobjective 1.2–Determine the contribution of flexible stocking strategies, adjusted annually based on forecasted weather and forage availability, to the sustainable intensification of livestock production. Subobjective 1.3–Determine the contribution of genetic variability (source population) in livestock, and its interaction with environmental variability and management strategies, to variability in livestock performance. Objective 2-Evaluate the impacts of droughts and deluges on shrub-grass interactions and carbon/energy/water fluxes and balances; learn how livestock management affects these responses. Subobjective 2.1–Quantify the effects of precipitation variability, extreme events (seasonal to multi-year droughts and individual deluges), topoedaphic variation, and livestock management on forage, livestock production, and carbon/energy/water fluxes. Subobjective 2.2–Evaluate the effects of increased interannual and intraannual precipitation variability and soil texture on grass-shrub competition, plant production, and forage quality. Objective 3-Identify temporal windows for spring grazing of cheatgrass to increase invasion resistance and forage production. Subobjective 3.1–Quantify temporal patterns of cattle consumption of cheatgrass and native, cool-season perennial grasses. Predict ideal grazing windows from associated measurements of climate, plant phenology, and forage quality. Subobjective 3.2–Test the utility of predicted grazing windows for controlling cheatgrass and increasing forage production. Objective 4-Evaluate where, when, and to what extent prairie dogs suppress livestock production in western Great Plains rangelands by altering forage resources and livestock foraging behavior. Subobjective 4.1–Quantify relationships between cattle weight gains and prairie dog abundance at pasture scales, at multiple sites, and across multiple years. Subobjective 4.2–Evaluate whether spatiotemporal patterns of livestock foraging can explain the mechanisms by which prairie dog abundance and distribution affect livestock weight gains. Objective 5-Provide land managers with information and decision tools needed to maintain profitability and environmental sustainability, and reduce risk to livestock operations in a changing climate. Subobjective 5.1–Simulate effects of adaptive grazing management on forage and livestock production in a spatially and temporally complex rangeland ecosystem; use simulations to explore alternative scenarios for stakeholder decision making. Subobjective 5.2-Evaluate the Wind Erosion Prediction System (WEPS) model at site and regional scales of rangeland agroecosystems. Subobjective 5.3-Develop interactive learning experiences and social networks to enhance stakeholder capacity for risk management and adaptation in a changing climate.

Semiarid rangelands of the western Great Plains simultaneously support livestock production and other ecosystem services such as wildlife habitat and soil carbon storage. To enhance decision-making by managers in these complex socio-ecological systems, we must first understand processes that regulate the provision of ecosystem services. The interactive effects of climate, soils, and management on forage production, plant invasion, livestock weight gain, and wildlife habitat are poorly understood. Moreover, key tools available to rangeland managers—adjusting stocking rates to match animal demand to forage availability, and moving livestock to better utilize spatially and temporally variable forage resources—are often underutilized. Through the coordinated and interdisciplinary work of eight scientists, we propose to: 1) conduct collaborative adaptive grazing management experiments, with direct involvement of diverse stakeholders, to balance multiple ecosystem services; 2) use intensive measurements of carbon fluxes and soil water to discover how precipitation interacts with topographic and edaphic variation to influence forage productivity and cattle weight gain; 3) use site-level models and cross-site comparisons to enhance predictions of key rangeland processes, including livestock weight gain and wind erosion; and 4) enhance stakeholder capacity for risk management and adaptation in a changing climate. To help achieve these goals we will leverage extensive historical data from the western Great Plains, participate in regional/national research efforts with other ARS units (e.g., Long Term Agroecosystem Research Network, USDA Climate Hubs, Grand Challenges, National Wind Erosion Network), and actively engage university partners, livestock producers, and other stakeholders.

Progress Report
The first objective addresses adaptive grazing management in the western Great Plains via the Collaborative Adaptive Rangeland Management (CARM) experiment which engages an 11-member stakeholder group in full-decision making capacity to compare traditional season-long grazing to adaptive management of a single large herd at a higher stocking density. This year, the stakeholder group halved the stocking density of the large herd to enhance livestock diet quality and weight gain. We field-quantified bite numbers, bite rate, and bite size with direct observations and jaw movement detection devices. New cattle GPS collars, designed within the unit, integrate location and accelerometer devices to determine grazing behavior patterns at much greater temporal resolutions (seconds rather than 5-minute intervals). A second adaptive grazing experiment is focused on potential benefits of flexible stocking rates in northern mixed-grass prairie. We use a combination of prior year remaining vegetation, precipitation to the start of the grazing season, seasonal climate projections, Grass-Cast predictions for vegetation production, and the Drought Monitor Seasonal Outlook, to match animal demand to forage availability. Stocking rates were adjusted to their lowest levels to date in the 5-year study due to low residual forage, a warm, dry spring, and seasonal climate projections of low precipitation over the growing season. The third experiment focuses on the contribution of genetic variability (source population) of steers to livestock performance. For the second year, steers from a local producer, ARS at Clay Center, Nebraska, and a high-elevation ranch operated by Colorado State University will be summer grazed on shortgrass steppe and then fed out to harvest. The second objective is focused on how changes in precipitation influence the hydrology and productivity of semiarid rangelands. At the Central Plains Experimental Range (CPER), precipitation, soil moisture, and fluxes of carbon and water were measured continuously across a wide range of topoedaphic variation and livestock management. Data was checked and delivered to scientists and stakeholders in near-real time using dashboards with automated scripts. Eddy covariance data was incorporated into an analysis by the Long-Term Agroecosystem Research (LTAR) Phenology working group. The interactive effects of droughts and deluges on forage production and carbon cycling was studied using a precipitation manipulation experiment quantifying effects of a mid-summer deluge (60 mm or 2.4 inches) during simulated drought on soil moisture, phenology, forage production, and carbon fluxes. Long-term (36-year) plant productivity data from a topographic sequence was analyzed and compared with various precipitation metrics. In the Thunder Basin ecoregion of northeastern Wyoming (where sagebrush grassland, shortgrass steppe and northern mixed-grass prairie converge), we collected vegetation, soils, and weather data from a precipitation variability experiment. The experiment explores the separate and combined effects of 1) greater interannual precipitation variability, and 2) more precipitation in the winter/early spring. Preliminary results indicate that higher precipitation variability may negatively impact livestock forage and wildlife habitat in this system. Plots subjected to watering followed by drought had high abundance of invasive annual bromes and low shrub growth, relative to ambient plots. We are measuring water potential bi-weekly on dominant forage grasses in order to quantify the timing and intensity of drought stress experienced by these species under different precipitation treatments. The third objective is focused on early spring grazing for control of cheatgrass in mixed-grass rangeland. This is an ongoing project for which we just completed the fourth field season. Data collection included productivity and forage quality of cheatgrass and native perennial grasses, plant- and pasture-scale phenological observations, cheatgrass seed production, and fecal samples for genetic analysis of diet composition and evaluation of diet quality. New GPS collars were successful in providing data to track cattle foraging time within cheatgrass-dominated and native-dominated patches in the pasture. We used aerial imagery to identify two potential sites for the second phase of the study (Objective 3.2), in which we will evaluate the degree to which early-spring grazing can shift plant community composition towards desirable native species. The fourth objective is focused on interactions between prairie dogs and cattle in the western Great Plains. Data collection during 2020 included cattle weight gain and vegetation monitoring in each of five pastures with prairie dogs present and ten pastures where prairie dogs are controlled annually. In addition, we monitored cattle foraging behavior via GPS collars in one pair of these pastures early in the growing season (mid-May to mid-June), when we hypothesize competition between prairie dogs and cattle will be most intense. In Thunder Basin, we have been working with ranchers to measure the impacts of prairie dogs and plague (which periodically wipes out prairie dog colonies) on forage quality and quantity, cattle weight gains, cattle foraging behavior, diet quality and plant diversity. We have also been continuing to measure the separate and combined effects of prairie dog, livestock, and native grazing animals on forage quality, quantity, and composition via a long-term nested exclosure project. The fifth objective addresses the provision of information and decision tools to land managers. Since its creation in 2014, the USDA Northern Plains Climate Hub has worked to better prepare livestock producers and other rangeland managers for increasing weather variability and a changing climate, by actively engaging stakeholders in co-development of interactive learning experiences and social networks. Grass-Cast, a grassland production forecasting tool, was expanded geographically from the Great Plains to the Southwest states of New Mexico and Arizona, and is available to stakeholders through an expanded website. Grass-Cast was shared with over 450 stakeholders during several in-person and virtual events including: 1) the 2020 National Grasshopper Management Board meeting, 2) USDA Farm Service Agency Colorado State Committee meeting, 3) Society for Range Management annual meeting, and 4) virtual workshops or webinars for USDA ARS, Natural Resources Conservation Service (NRCS), and Farm Service Agency, along with the Department of Interior’s Bureau of Land Management, Bureau of Indian Affairs, U.S. Geological Survey, and the Department of Commerce’s National Oceanic and Atmospheric Administration. To reach stakeholders with limited access to high-speed internet, the Climate Hub also contributed to five press releases, five agricultural newspaper stories, and two podcasts. The Wind Erosion Prediction System (WEPS) is a process-based simulation model for conservation planning, management, and assessment of environmental impacts of wind erosion. A new version of the WEPS model is being finalized for public and NRCS release. Data enhancements include aligning the operation and crop/residue records to be common with the Water Erosion Prediction Project (WEPP) model. Significant progress was made on incorporating the Universal Plant Growth Model into WEPS. In addition, progress is being made in the development of a new multi-subregion interface including temporal wind barrier porosity and height codes. Final editing and formatting of the WEPS Technical Documentation was completed and the full document is awaiting final approval to be published as a USDA Handbook. ARS researchers continued collaboration with the National Wind Erosion Research Network, operating rangeland and dryland cropland sites. The APEX (Agricultural Policy/Environmental eXtender Model) model was selected for comparing grazing management practices (traditional vs adaptive grazing management) at two LTAR sites: the CPER and the Texas Gulf. Models were adapted for the specific plant species and livestock weight gains at these sites.

1. Effects of multiple, interactive disturbances in the Thunder Basin Ecoregion. To support sound land management decisions, rangeland managers require knowledge of how disturbances influence vegetation and ecosystem function. Such knowledge was previously lacking for northeastern Wyoming, which is a complex, diverse ecosystem located in a transitional zone (ecotone) between the Great Basin and the Great Plains. Using a stakeholder-driven research approach in collaboration with the Thunder Basin Grasslands Prairie Ecosystem Association, the University of Wyoming, and the USDA Forest Service, ARS scientists from Fort Collins, Colorado, and Cheyenne, Wyoming, demonstrated that: 1) wildfires do not promote cheatgrass invasion in this system, but they do lead to long-term ecosystem change by removing shrubs and shifting herbaceous species composition; 2) prairie dogs and historical wildfires shape vegetation structure more than short-term livestock management; 3) prairie dogs are associated with shorter structure vegetation and higher quality herbaceous forage throughout the growing season; 4) prairie dogs suppress forage biomass in droughts but not in average to wet years; and 5) prairie dog colonies and wildfire disturbances support high grassland bird diversity and sensitive bird species. Results demonstrate that transitional zones such as Thunder Basin can function differently from adjacent, well-studied regions such as the Great Plains or the Great Basin. These discoveries played key roles in the development of candidate conservation agreements (CCAs) between private landowners and the U.S. Fish and Wildlife Service, and a new USDA Forest Service management plan which aims to better balance needs of livestock production and biodiversity conservation on the Thunder Basin National Grassland. Moreover, ARS scientists are using these results to update Ecological Site Descriptions and associated state-and-transition models for the region via a formal USDA-NRCS process.

2. Stocking rate decision-support to enhance resiliency of rangeland livestock operations. Flexible stocking strategies match animal demand with variable forage availability for rangeland livestock operations. However, uncertainty in precipitation often prevents use of flexible stocking strategies across the western U.S. ARS scientists from Cheyenne, Wyoming, and Fort Collins, Colorado, in collaboration with scientists from Colorado State University, integrated eight decades of livestock production and climatic data to produce an enhanced stocking rate decision tree for western Great Plains rangelands. The decision tree incorporated influences of hierarchical temporal precipitation controls for livestock production, as temperature was not influential. Results showed that indices of decadal-scale sea surface temperatures off the Pacific Coast (Pacific Decadal Oscillation [PDO] phases) and a shorter-term (1-4 year) sea surface temperature fluctuations at the equator (El Nino Southern Oscillation phase) can be combined with local-scale (1-3 month) precipitation patterns to improve predictions of livestock weight gains in the western Great Plains. This decision tree substantially reduces enterprise risk enabling managers to make timely stocking rate adjustments without knowledge of impending growing-season precipitation amount. This innovative tool empowers livestock managers to make proactive stocking rate decisions, thus increasing profitability, production efficiency, and environmental sustainability on western U.S. rangelands.

3. Soil surface characteristics influence fine dust emissions on US drylands. Wind erosion and blowing dust in U.S. dryland ecosystems threaten food security through loss of productive soils and human health through reduced air quality and visual constraints for safe driving conditions. ARS scientists in Fort Collins, Colorado, in collaboration with scientists from the U.S. Geological Survey, Kansas State University, and Shandong Agricultural University and Beijing Normal University, China, conducted a series of wind tunnel and field experiments to understand and predict the effects of surface characteristics on fine dust emissions. The wind tunnel studies provided a 3-D computer simulation of wind flow through a plant canopy, demonstrated that fine dust emissions from abrasion of soil clods were greater for sandy soils than finer textured soils, and provided predictive equations for very fine dust emissions. A complementary field study demonstrated that bare soil inoculated with locally collected biological soil crust produced sediment-accumulating benefits within four-months, especially when combined with a soil stabilizer, indicating potential for dust mitigation in drylands. These results further quantify fine dust emissions from a variety of land surfaces, improve predictive wind erosion models of dust emissions, and provide promising methods for reducing dust emission from drylands, which together improve our ability to predict dust sources and develop controls for improved air, soil and water quality in the western U.S.

Review Publications
Wilmer, H.N., Fernandez-Gimenez, M., Ghajar, S., Taylor, P.L., Souza, C., Derner, J.D. 2019. Managing for the middle: Rancher care ethics under uncertainty on Western Great Plains rangelands. Agriculture and Human Values. 1-20.
Raynor, E.J., Derner, J.D., Hoover, D.L., Parton, W., Augustine, D.J. 2020. Large-scale and local climatic controls on large herbivore productivity: Implications for adaptive rangeland management. Ecological Applications. 30(3). Article e02053.
Hillis, A.V., Berry, K., Souza Leao Swette, B., Aslan, C., Berry, S., Porensky, L.M. 2020. Unlikely alliances and their implications for resource management in the American West. Environmental Research Letters. 15(4):045002.
Tatarko, J., Kucharski, M., Li, H., Li, H. 2020. PM2.5 and PM10 emissions by abrasion of agricultural soils. Soil and Tillage Research. 200:104601.
Augustine, D.J., Wigley, B., Ratnam, J., Kibet, S., Nyangito, M., Sankaran, M. 2019. Large herbivores maintain a two-phase herbaceous vegetation mosaic in a semi-arid savanna. Ecology and Evolution. 9:12779-12788.
Reynolds, A., Derner, J.D., Augustine, D.J., Porensky, L.M., Wilmer, H.N., Jorns, T., Briske, D.D., Scasta, J., Fernandez-Gimenez, M. 2019. Ecological sites: Can they be managed to promote livestock production? Rangelands. 41(6):239-243.
Derner, J.D., Raynor, E.J., Reeves, J., Augustine, D.J., Milchunas, D. 2019. Climatic and management determinants of large herbivore production in semiarid grassland. Agriculture, Ecosystems and Environment. 290:106761.
Scasta, J., Jorns, T., Derner, J.D., Lake, S., Augustine, D.J., Windh, J., Smith, T. 2019. Validation of DNA metabarcoding of fecal samples using cattle fed known rations. Animal Feed Science And Technology. 255:114219.
Ma, L., Derner, J.D., Harmel, R.D., Tatarko, J., Moore, A., Rotz, C.A., Augustine, D.J., Boone, R., Coughenour, M. 2019. Application of grazing land models in ecosystem management: Current status and next frontiers. Advances in Agronomy. 158:173-216.
Coverdale, T., McGeary, I., O'Connell, R., Palmer, T., Goheen, J., Sankaran, M., Augustine, D.J., Ford, A., Pringle, R. 2019. Strong but opposing effects of associational resistance and susceptibility on defense phenotype in an African savanna plant. Oikos. 128:1772-1782.
Duchardt, C., Augustine, D.J., Beck, J. 2020. Anthropogenic and natural disturbance differentially affect sagebrush bird habitat use. Journal of Wildlife Management. 84(7):1361-1372.
Sanderson, J., Beutler, C., Brown, J.R., Burke, I., Chapman, T., Conant, R., Derner, J.D., Easter, M., Fuhlendorf, S.D., Grissom, G., Herrick, J.E., Liptzin, D., Morgan, J.A., Murph, R., Pague, C., Rangwala, I., Ray, D., Rondeau, R., Schulz, T., Sullivan, T. 2020. Cattle, conservation and carbon in the western Great Plains. Journal of Soil and Water Conservation. 75(1):5A-12A.
Chen, M., Parton, W.J., Hartman, M.D., Del Grosso, S.J., Smith, W.K., Knapp, A.K., Lutz, S., Derner, J.D., Tucker, C.J., Ojima, D.S., Volesky, J., Stephenson, M., Schacht, W., Gao, W. 2019. Assessing precipitation, evapotranspiration, and NDVI as controls of Great Plains plant production. Ecosphere. 10(10):e02889.
Smart, A.J., Harmoney, K., Scasta, J.D., Stephenson, M.B., Volesky, J.D., Vermeire, L.T., Mosely, J., Sedivec, K., Meehan, M., Haigh, T., Derner, J.D., McClaran, M.P. 2019. Forum: Critical decision dates for drought management in central and northern Great Plains rangelands. Rangeland Ecology and Management. 1-10.
Chen, X., Qi, Z., Gui, D., Gu, Z., Ma, L., Zeng, F., Li, L. 2019. A Decision Support System for Irrigation Scheduling (DSSIS) based on model predicted water stress index and forecast weather data. Agronomy. 9:686.
Sadhukhan, D., Qi, Z., Zhang, T., Tan, C., Ma, L. 2019. Modeling and mitigating phosphorus losses in a tile-drained and manured field using RZWQM2-P. Journal of Environmental Quality. 48:995-1005.
Chen, X., Qi, Z., Gui, D., Gu, Z., Ma, L., Zeng, F., Li, L. 2019. Simulating impacts of climate change on cotton yield and water requirement using RZWQM2. Agricultural Water Management. 222:231-241.
Zhang, H., Han, M., Comas, L.H., DeJonge, K.C., Gleason, S.M., Trout, T.J., Ma, L. 2019. Response of maize yield components to growth stage-based deficit irrigation. Agronomy Journal. 111:14-9.
Griffin-Nolan, R.J., Blumenthal, D.M., Collins, S.L., Farkas, T.E., Hoffman, A.M., Mueller, K.E., Ocheltree, T.W., Smith, M.D., Whitney, K.D., Knapp, A.K. 2020. Shifts in plant functional composition following long-term drought in grasslands. Journal of Ecology. 107:2133-2148.
Wallingford, P.D., Morelli, T.L., Allen, J.M., Beaury, E.M., Blumenthal, D.M., Bradley, B.A., Dukes, J.S., Early, R., Fusco, E.J., Goldberg, D.E. 2020. Adjusting the lens of invasion biology to focus on the aspects of climate-driven range shifts. Nature Climate Change.
Ocheltree, T.W., Muller, K.M., Chesus, K., Lecain, D.R., Kray, J.A., Blumenthal, D.M. 2020. Identification of suites of traits that explains drought resistance and pheonological patterns of plants in a semi-arid grassland community. Physiological Ecology. 192:55-66.
Kattge, J., Bonisch, G., Diaz, S., Lavorel, S., Prentice, I.C., Leadley, P., Tautenhahn, S., Werner, G., Gillison, A., Wirth, C., Gleason, S.M., Blumenthal, D.M. 2020. TRY plant trait database - enhanced coverage and open access. Global Change Biology. 26:119-188.
Terrer, C., Franklin, O., Prentice, I.C., Keenan, T.F., Kaiser, C., Vicca, S., Fisher, J.B., Reich, P.B., Stocker, B.D., Blumenthal, D.M. 2019. Nitrogen and phosphorus constrain the CO2 fertilization of global plant biomass. Nature Climate Change. 9:684-689.
Hoover, D.L., Bestelmeyer, B.T., Grimm, N., Huxman, T., Reed, S., Sala, O., Seastedt, T., Wilmer, H.N., Ferrenberg, S. 2019. Traversing the wasteland: A framework for assessing ecological threats to drylands. Bioscience. 70(1):35-47.
Smith, M., Koerner, S., Knapp, A., Avolio, M., Chaves, F.A., Denton, E.M., Dietrich, J., Gibson, D.J., Gray, J., Hoffman, A.M., Hoover, D.L., Komatsu, K.J., Silletti, A., Wilcox, K., Yu, Q., Blair, J.M. 2020. Mass ratio effects underlie ecosystem responses to environmental change. Journal of Ecology. 108(3):855-864.
Zhang, F., Quan, Q., Ma, F., Tian, D., Hoover, D.L., Zhou, Q., Niu, Z. 2019. When does extreme drought elicit extreme ecological responses? Journal of Ecology. 107(6):2553-2563.
Gonzales, H., Tatarko, J., Casada, M.E., Maghirang, R., Hagen, L., Barden, C. 2020. Computational fluid dynamics simulation of airflow through standing vegetation. American Society of Agricultural and Biological Engineers. 62(6):1713-1722.
Fick, S.E., Barger, N., Tatarko, J., Duniway, M. 2020. Induced biological soil crust controls on wind erodibility and PM10 emissions. Earth Surface Processes and Landforms. 45:224-236.
Jarrah, M., Mayel, S., Tatarko, J., Funk, R., Kuka, K. 2019. A review of wind erosion models: data requirements, processes, and validity. Catena. 187:104388.
Webb, N., Kachergis, E., Miller, S., McCord, S.E., Bestelmeyer, B.T., Brown, J., Chappell, A., Edwards, B., Herrick, J.E., Karl, J., Leys, J., Metz, L., Smarik, S., Tatarko, J., Van Zee, J.W., Zwicke, G. 2020. Indicators and benchmarks for wind erosion monitoring, assessment and management. Ecological Indicators. 110:105881.
Veblen, K.E., Porensky, L.M. 2019. Thresholds are in the eye of the beholder: Plants and wildlife respond differently to short-term cattle corrals. Ecological Applications. 29(8):e01982.
Espeland, E.K., Schreeg, L., Porensky, L.M. 2019. Managing risks related to climate variability in rangeland-based livestock production: What producer driven strategies are shared and prevalent across diverse dryland geographies? Journal of Environmental Management. 255:109889.
Mamedov, A., Wagner, L.E., Presley, D., Norton, D., Levy, G. 2020. Polyacrylamide dissolved in low quality water effects on structure stability of soils varying in texture and clay type. Journal of Soils and Sediments.
Wilmer, H.N., Sturrock, J. 2020. Humbled by nature: A rancher’s mental-model of adaptation in the Great Plains. Great Plains Research. 30(1):15-33.
Raynor, E.J., Coon, J.J., Swartz, T.M., Morton, L.W., Schacht, W.H., Miller, J.R. 2019. Shifting cattle producer beliefs on stocking and invasive forage: Implications for grassland conservation. Rangeland Ecology and Management. 72:888-898.
Raynor, E.J., Harrison, J.O., Whalen, C.E., Smith, J.A., Schacht, W.H., Benson, J.F., Tyre, A.J., Brown, M.B., Powell, L.A. 2019. Anthropogenic noise does not surpass land cover in explaining habitat selection of Greater Prairie-Chicken (Tympanichus cupido). The Condor: Ornithological Applications. 121(4):duz044.
Levi, M., Krueger, E., Snitker, G.J., Ochsner, T., Villarreal, M.L., Elias, E.H., Peck, D.E. 2019. Rating fire danger from the ground up. Eos GeoHealth. 100.
Peck, D.E., Reeves, W.K., Pelzel-McCluskey, A.M., Derner, J.D., Drolet, B.S., Cohnstaedt, L.W., Swanson, D.A., McVey, D.S., Rodriguez, L.L., Peters, D.C. 2020. Management strategies for reducing the risk of equines contracting Vesicular Stomatitis Virus (VSV) in the Western United States. Journal of Equine Veterinary Science. 90:103026.
Elderbrook, M., Schumaker, B., Cornish, T., Peck, D.E., Sondgeroth, K. 2019. Seroprevalence and risk factors of Brucella ovis in domestic sheep in Wyoming, USA. BMC Veterinary Research. 15:246.
Bharath, S., Borer, E., Biederman, L., Blumenthal, D.M., Fay, P.A., Gheradi, L., Knops, J., Leakey, A., Yahdjian, L., Seabloom, E. 2020. Nutrient addition increases grassland sensitivity to droughts. Ecology. 101(5):e02981.
Ziska, L.H., Blumenthal, D.M., Franks, S.J. 2019. Understanding the nexus of rising CO2, climate change and evolution in weed biology. Invasive Plant Science and Management. 12:79-88.
Blumenthal, D.M., Mueller, K., Kray, J.A., Ocheltree, T.W., Augustine, D.J., Wilcox, K.R. 2020. Traits link drought resistance with herbivore defense and plant economics in two semiarid grasslands: The central role of leaf dry matter content. Journal of Ecology.
Sohoulande Djebou, D.C., Ma, L., Szogi, A.A., Sigua, G.C., Stone, K.C., Malone, R.W. 2020. Evaluating nitrogen management for corn production with supplemental irrigation on sandy soils of the Southeastern Coastal Plain region of the United States. Transactions of the ASABE. 63(3):731-740.
Peters, D.C., McVey, D.S., Elias, E.H., Pelzel-McCluskey, A.M., Derner, J.D., Burruss, N., Schrader, T.S., Yao, J., Pauszek, S.J., Lombard, J., Rodriguez, L.L. 2020. Big data-model integration and AI for vector-borne disease prediction. Ecosphere. 11:1-20.