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

Location: Rangeland Resources & Systems Research

2022 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 focuses on the Collaborative Adaptive Rangeland Management experiment, located in shortgrass steppe at the Central Plains Experimental Range (CPER). A dry fall, winter, spring, and early summer resulted in the stakeholder group deciding to remove cattle from the experiment at the end of July. This decision was facilitated using a newly developed remote sensing tool that provides probabilities of forage biomass values at the pasture scale. New research efforts used jaw movement detection devices to compare cattle bite numbers, rate, and size between local cattle and those from a tallgrass prairie in south-central Nebraska. These comparisons were conducted in large pastures (>800 acres). In addition, a pilot study assessing enteric methane emissions of yearling cattle was conducted using new field-technology. The second objective is focused on how changes in precipitation influence the hydrology and productivity of semiarid rangelands. We incorporated eddy covariance data into an analysis by the Long-Term Agroecosystem Research (LTAR) Phenology working group. At the CPER, we tested interactive effects of droughts and deluges on forage production and carbon cycling using both a precipitation manipulation experiment and a long-term (36-year) observational study of plant productivity data from a topographic sequence. In the Thunder Basin region of northeastern Wyoming (where sagebrush grassland, shortgrass steppe and northern mixed-grass prairie converge), we are using a precipitation manipulation experiment to test effects of 1) greater interannual precipitation variability, and 2) more precipitation in the winter/early spring on plant productivity, drought stress and phenology. Preliminary results indicate that higher precipitation variability may negatively impact livestock forage in this system. Prior year addition of water followed by drought the next year led to high abundance of invasive annual bromes, but perennial grass production was resistant to increased precipitation variability. The third objective is focused on early spring grazing for control of cheatgrass in mixedgrass rangeland (High Plains Grasslands Research Station). We have completed the first study, which enabled us to predict when cattle select for and against cheatgrass both within and among years. We used those predictions to create grazing windows - phenological periods when cattle are likely to be most effective in controlling cheatgrass. The second study is testing the degree to which early spring grazing, during the predicted grazing windows, can shift plant community composition towards desirable native species. We selected a site that was heavily invaded by cheatgrass, added water tanks and fencing to construct 6 replicated pastures, and implemented grazing treatments. Preliminary plant response data indicated that targeted grazing effectively controlled cheatgrass despite very dry spring conditions. The fourth objective is focused on interactions between prairie dogs and cattle in the western Great Plains. We monitored cattle foraging behavior via GPS collars at the Thunder Basin site. We also collected data on prairie dog densities, vegetation composition, cattle diet quality, forage quality, and weight gains throughout the summer and fall (from branding to weaning) from this site. Results will help us to understand the impacts of prairie dogs and plague (which periodically decimates prairie dog colonies), as well as the drivers and consequences of cattle foraging behavior decisions. We have also continued to measure the separate and combined effects of prairie dogs, livestock, and native grazing animals on forage quality, quantity, and composition via a long-term nested exclosure project in Thunder Basin. For each project, we provided data summaries to ranchers participating in these projects. The fifth objective addresses the provision of information and decision tools to land managers. The USDA Northern Plains Climate Hub continued to work with livestock producers and other rangeland managers to prepare for increasing weather variability and a changing climate. Grass-Cast, a grassland production forecasting tool that currently serves the Great Plains and the Southwest states of New Mexico and Arizona ( is a product of the USDA Northern Plains Climate Hub. Improvements were made to the Grass-Cast website this year based on land manager feedback. Specifically, the zoomable maps now provide location-specific information about the amount of precipitation assumed in the Grass-Cast model. This enables Grass-Cast users to decide for themselves whether the amount assumed is similar enough to precipitation received on their specific pasture or allotment to trust Grass-Cast’s production estimates for the surrounding local area. A new interface for the Wind Erosion Prediction System (WEPS), a process-based simulation model for conservation planning, management, and assessment of environmental impacts of wind erosion, was started for the Natural Resources Conservation Service (NRCS). This interface provides capacity to run both WEPS and the Water Erosion Prediction Project (WEPP) model together. Rangeland and dryland cropping sites are being monitored for the National Wind Erosion Research Network (NWERN) for use with the Aeolian Erosion (AERO) model. The APEX (Agricultural Policy/Environmental eXtender Model) model is being enhanced to incorporate climate extreme data (droughts and deluges) with assessments for the robustness of this addition to be conducted at the Central Plains Experimental Range LTAR site.

1. Applications of on-animal sensor technologies to advance precision livestock and rangeland management. ARS scientists in Fort Collins, Colorado, and University Park, Pennsylvania, quantified foraging behavior and distribution of free-ranging beef cattle with on-animal sensors. Topographic variability consistently affected grazing distribution in grazing lands across seven states spanning the western United States to Florida. Integrating three sensor types - GPS tracking collars, accelerometers, and jaw movement devices - revealed how daily metrics of foraging behavior are influenced by grazing management. These foraging behavior metrics, including length of grazing event, patterns of animal movement, and number of grazing bites per minute, provide managers with real-time indicators of how forage conditions affect livestock intake and subsequent weight gains. Integrating these indicators with commercially-available technologies like virtual fence offers novel applications to managers for capitalizing on precision livestock and rangeland management in extensive rangeland systems.

2. Remote sensing advances for precision livestock and rangeland management. Tools are needed to help rangeland managers rapidly respond to changing forage conditions within the grazing season at pasture or sub-pasture scales. In extensive rangeland systems, it is often impractical to measure plant biomass available for grazing or diet quality in the field. Existing remote-sensing technologies do not provide managers with near-real-time, production-relevant metrics like currently available plant biomass, diet quality, or animal weight gain at spatial scales relevant for management decisions. ARS scientists in Fort Collins, Colorado, linked long-term field-based datasets with freely available satellite data to accurately predict daily plant biomass, diet quality, and animal weight gains across highly variable conditions. These remote sensing advances yield near-real-time plant biomass and diet quality maps at fine (100 feet) spatial scales to assist managers with ranch- and pasture-scale decision-making. These near-real-time tools, combined with commercially available technologies like virtual fence, open up a new frontier for precision and livestock management that increases efficiency and lowers environmental impact by accurately matching forage supply with animal demand in extensive rangelands.

3. Assessing effects of grazing management practices on grazing lands with enhanced modeling. Decision support tools help ranchers and land managers assess effects of grazing management practices. ARS scientists in Fort Collins, Colorado, and Texas A&M University collaborated to enhance the APEX (Agricultural Policy / Environmental eXtender) model and evaluate effects of season-long and rotational grazing management practices using several years of forage production and animal production of yearlings (stockers) and cow-calf pairs at two sites. For both semiarid (north central Colorado) and mesic (central Texas) grazing lands, the enhanced model successfully simulated responses of forage and animal production with the grazing management practices. This model provides scientists with a novel tool for collaborative adaptive rangeland management, helping them to improve decision making with quantitative predictions of both forage and livestock productivity. Planned extension of APEX to include other Long-Term Agroecosystem Research (LTAR) network sites and climate extremes will lead to a decision support tool that managers can use across a wide array of U.S. rangelands.

Review Publications
Wagner, L.E., Haas, M.E., Fox, F.A. 2022. WebStart WEPS: WEPS with remote data access and cloud-computing functionality. Journal of the ASABE. 65(2):427-436.
Derner, J.D., Budd, B., Grissom, G., Kachergis, E., Augustine, D.J., Wilmer, H., Scasta, J., Ritten, J.P. 2022. Adaptive grazing management in semiarid rangelands: An outcome-driven focus. Rangelands. 44(1):111-118.
Kearney, S.P., Porensky, L.M., Augustine, D.J., Derner, J.D., Gao, F.N. 2022. Predicting spatial-temporal patterns of diet quality and large herbivore performance using satellite time series. Ecological Applications. 32. Article e2503.
Cheng, G., Harmel, R.D., Ma, L., Derner, J.D., Augustine, D.J., Bartling, P., Fang, Q., Williams, J., Zilverberg, C., Boone, R., Yu, Q. 2022. Evaluation of APEX cattle weight gain component for grazing decision-support in the Western Great Plains. Rangeland Ecology and Management. 82:1-11.
Ebeling, A., Strauss, A.T., Adler, P., Arnilla, C.A., Barrio, I.C., Biederman, L.A., Borer, E.T., Bughalo, M.N., Caldeira, M.C., Daleo, P., Eisenhauer, N., Eskelinen, A., Fay, P.A., Firn, J., Graff, P., Haider, S., Komatsu, J., McCulley, R.L., Mitchell, C.E., Peri, P.L., Power, S.A., Prober, S.M., Risch, A.C., Roscher, C., Seabloom, E.W., Schielzeth, H., Tedder, M., Virtanen, R., Blumenthal, D.M. 2021. Nutrient enrichment increases invertebrate herbivory and pathogen damage in grasslands. Journal of Ecology. 110:327-339.
Fang, Q.X., Harmel, R.D., Ma, L., Bartling, P., Derner, J.D., Jeong, J., Williams, J., Boone, R. 2021. Evaluating the APEX Model for alternative cow-calf grazing management strategies in Central Texas. Agricultural Systems. 195. Article e103287.
Coetsee, C., Wigley, B.J., Sankaran, M., Ratnam, J., Augustine, D.J. 2022. Contrasting effects of grazing vs browsing herbivores determine changes in soil fertility in an East African savanna. Ecosystems. 1-11.
Wells, H.B., Porensky, L.M., Veblen, K.E., Riginos, C., Stringer, L.C., Dougill, A.J., Young, T.P. 2022. At high stocking rates, cattle do not functionally replace wild herbivores in shaping savanna understory community composition. Ecological Applications. 32. Article e2520.
Tatarko, J. 2022. Erosion by wind. In: Goss, M.J. and Oliver, M.A., editors. Encyclopedia of Soils in the Environment, Reference Module in Earth Systems and Environmental Sciences. Second Edition. Elsevier Ltd. p. 1-15.
Kearney, S.P., Porensky, L.M., Augustine, D.J., Gaffney, R.M., Derner, J.D. 2022. Monitoring standing herbaceous biomass and thresholds in semiarid rangelands from harmonized Landsat 8 and Sentinel-2 imagery to support within-season adaptive management. Remote Sensing of Environment. 271. Article e112907.
Gaffney, R.M., Augustine, D.J., Kearney, S.P., Porensky, L.M. 2021. Using hyperspectral imagery to characterize rangeland vegetation composition at process-relevant scales. Remote Sensing. 13. Article 4603. https//
Hoover, D.L., Hajek, O.L., Smith, M.D., Wilkins, K., Slette, I.J., Knapp, A.K. 2022. Compound hydroclimatic extremes in a semi-arid grassland: Drought, deluge, and the carbon cycle. Global Change Biology. 28:2611-2621.
Podebradska, M., Wylie, B.K., Bathke, D.J., Bayissa, Y.A., Dahal, D., Derner, J.D., Fay, P.A., Hayes, M.J., Wagle, P. 2021. Monitoring climate impacts on annual forage production across U.S. semi-arid grasslands. Remote Sensing. 14(1). Article 4.
Wells, H.B., Crego, R.D., Ekadell, J., Namoni, M., Kimuyu, D.M., Odadl, W.O., Porensky, L.M., Dougill, A.J., Stringer, L.C., Young, T.P. 2022. Less is more: Lowering cattle stocking rates enhances wild herbivore habitat use and cattle foraging efficiency. Frontiers in Ecology and Evolution. 10. Article 825689.
Schnarr, C., Schipanski, M., Tatarko, J. 2022. Crop residue cover dynamics for wind erosion control in a dryland, no-till system. Journal of Soil and Water Conservation. 77(3):221-229.
Porensky, L.M., Augustine, D.J., Derner, J.D., Wilmer, H., Lipke, M., Fernandez-Gimenez, M., Briske, D. 2021. Collaborative adaptive rangeland management, multi-paddock rotational grazing, and the story of the regrazed grass plant. Rangeland Ecology and Management. 78:127-141.
Davidson, A., Augustine, D.J., Jacobsen, H., Pellatz, D., Porensky, L.M., McKee, G., Duchardt, C. 2022. Boom and bust cycles of black-tailed prairie dog populations in the Thunder Basin grassland ecosystem. Journal of Mammalogy. Article gyac035.
Schulz, T.T., Wilmer, H.N., Yocum, H., Winford, E., Peck, D.E., Monlezun, A.C., Schmalz, H., Klemm, T., Epstein, K., Jansen, V., Kelley, W., Bruegger, R., Fick, S., Grazing Wolf, J., Grace, J., Mann, R., Derner, J.D. 2021. Campfire conversations at the 2020 annual meeting: Insights and lessons learned from “cuss-and-discuss” rather than “chalk-and-talk”. Rangelands. 43(4):166-172.
Wilmer, H., Meadow, A.M., Bentley Brymer, A., Russo Carroll, S., Ferguson, D.B., Garba, I., Greene, C., Owen, G., Peck, D.E. 2021. Expanded ethical principles for research partnership and transdisciplinary natural resource management science. Environmental Management. 68:453-467.
Browning, D.M., Russell, E.S., Ponce-Campos, G.E., Kaplan, N.E., Richardson, A.D., Seyednasrollah, B., Spiegal, S.A., Saliendra, N.Z., Alfieri, J.G., Baker, J.M., Bernacchi, C.J., Bestelmeyer, B.T., Bosch, D.D., Boughton, E.H., Boughton, R.K., Clark, P., Flerchinger, G.N., Gomez-Casanovas, N., Goslee, S.C., Haddad, N., Hoover, D.L., Jaradat, A.A., Mauritz, M., Miller, G.R., McCarty, G.W., Sadler, J., Saha, A., Scott, R.L., Suyker, A., Tweedie, C., Wood, J., Zhang, X., Taylor, S.D. 2021. Monitoring agroecosystem productivity and phenology at a national scale: A metric assessment framework. Ecological Indicators. 131. Article 108147.
Hoover, D.L., Pfennigwerth, A., Duniway, M. 2021. Drought resistance and resilience: The role of moisture-plant interactions and legacies in a dryland ecosystem. Journal of Ecology. 109:3280-3294.
Post, A.K., Davis, K.P., LaRoe, J., Hoover, D.L., Knapp, A.K. 2021. Semiarid grasslands and extreme precipitation events: Do experimental results scale to the landscape? Ecology. Article e03437.
Augustine, D.J., Derner, J.D. 2021. Long-term effects of black-tailed prairie dogs on livestock grazing distribution and mass gain. Journal of Wildlife Management. 85(7):1332-1343.
Raynor, E.J., Derner, J.D., Soder, K.J., Augustine, D.J. 2021. Noseband sensor validation and behavioural indicators for assessing beef cattle grazing on extensive pastures. Applied Animal Behaviour Science. 242:1-30.
Augustine, D.J., Raynor, E.J., Kearney, S.P., Derner, J.D. 2022. Can measurements of foraging behaviour predict variation in weight gains of free-ranging cattle? Animal Production Science. Special Issue: AAAS|Stobbs Lecture.
Reike, E., Cappellazzi, S.B., Cope, M., Liptzin, D., Bean, G.M., Greub, K.L., Norris, C.E., Tracy, P.W., Aberle, E., Ashworth, A.J., Baumhardt, R.L., Dell, C.J., Derner, J.D., Ducey, T.F., Fortuna, A., Kautz, M.A., Kitchen, N.R., Moore Jr., P.A., Osborne, S.L., Owens, P.R., Sainju, U.M., Sherrod, L.A., Watts, D.B., et al. 2022. Linking soil microbial community structure to potential carbon mineralization: A continental scale assessment of reduced tillage. Soil Biology and Biochemistry. 168. Article 108618.
Liu, M., Pan, Y., Pan, X., Sosa, D., Blumenthal, D.M., Van Kleunen, M., Li, B. 2021. Plant invasion alters latitudinal patterns of plant-defense syndromes. Ecology. 102(12). Article e03516.
Augustine, D.J., Davidson, A., Dickinson, K., Van Pelt, B. 2021. Thinking like a grassland: Challenges and opportunities for biodiversity conservation in the Great Plains of North America. Rangeland Ecology and Management. 78:281-295.
Davis, K.P., Augustine, D.J., Monroe, A.P., Aldridge, C.L. 2021. Vegetation characteristics and precipitation jointly influence grassland bird abundance beyond the effects of grazing management. The Condor: Ornithological Applications. 123:1-15.
Schoenecker, K.A., Zeigenfuss, L.C., Augustine, D.J. 2022. Can grazing by elk and bison stimulate herbaceous plant productivity in semi-arid ecosystems? Ecology. 13. Article e4025.
Irisarri, J.G., Durante, M., Derner, J.D., Oesterheld, M., Augustine, D.J. 2022. Remotely sensed spatiotemporal variation in crude protein of shortgrass steppe forage. Remote Sensing. 14. 854.
Bagnall, D.K., Morgan, C., Cope, M., Bean, G.M., Cappellazzi, S., Greub, K., Liptzin, D., Norris, C.E., Rieke, E.L., Tracy, P.W., Ashworth, A.J., Baumhardt, R.L., Dell, C.J., Derner, J.D., Ducey, T.F., Fortuna, A., Kautz, M.A., Kitchen, N.R., Moore Jr., P.A., Osborne, S.L., Owens, P.R., Sainju, U.M., Sherrod, L.A., Watts, D.B., et al. 2022. Carbon-sensitive pedotransfer functions for plant available water. Soil Science Society of America Journal. 86(3):612-629.
Porensky, L.M. 2022. Embracing complexity and humility in rangeland science. Rangelands. 43(4):142-150.
Ebel, C.R., Case, M.F., Kimuyu, D.M., Langendorf, R.E., Porensky, L.M., Veblen, K.E., Wells, H.B., Werner, C.M., Young, T.P., Hallett, L.M. 2022. Herbivory and drought reduce the temporal stability of herbaceous cover by increasing synchrony in a semi-arid savanna. Frontiers in Ecology and the Environment. 10. Article e867051.
Chu, X., Flerchinger, G.N., Ma, L., Fang, Q., Malone, R.W., Yu, Q., He, J., Wang, N., Feng, H., Zou, Y. 2022. Development of RZ-SHAW for simulating plastic mulch effects on soil water, soil temperature, and surface energy balance in a maize field. Agricultural Water Management. 269. Article 107666.
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.
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. [Corrigendum: Hydrological Processes: 2022, 36(6), Article e14609.]
Finger-Higgins, R., Duniway, M., Fick, S., Geiger, E., Hoover, D.L., Pfennigwerth, A., Van Scoyoc, M., Belnap, J. 2022. Decline in biological soil crust N-fixing lichens linked to increasing summertime temperatures. Proceedings of the National Academy of Sciences (PNAS). 119(16). Article e2120975119.
Coverdale, T.C., O'Connell, R., Hutchinson, M.C., Savagian, A., Kartzinel, T.R., Palmer, T.M., Goheen, J.R., Augustine, D.J., Sankaran, M., Tarrita, C.E., Pringle, R.M. 2021. Large herbivores suppress liana infestation in an African savanna. Proceedings of the National Academy of Sciences (PNAS). 118(4). Article e2101676118.
Wagner, L.E. 2020. A history of Wind Erosion Prediction Models in the U.S. Department of Agriculture, Part 2: The Wind Erosion Prediction System (WEPS). In: Tatarko, J., editor. Wind Erosion Prediction System (WEPS): Technical Documentation. USDA Agriculture Handbook 727. United States Department of Agriculture, Agricultural Research Service, Beltsville, MD. p. 28-56.
Wagner, L.E. 2020. Input and command line arguments for WEPS. In: Tatarko, J. editor. Wind Erosion Prediction System (WEPS): Technical Documentation. USDA Agriculture Handbook 727. United States Department of Agriculture, Agricultural Research Service, Beltsville, MD. p. 343-490.
Wagner, L.E. 2020. Future work and uses of WEPS. In: Tatarko, J., editor. Wind Erosion Prediction System (WEPS): Technical Documentation. USDA Agriculture Handbook 727. United States Department of Agriculture, Agricultural Research Service, Beltsville, MD. p. 511-517.
Shackelford, N., Paterno, G.B., Winkler, D.E., Porensky, L.M., Boyd, C.S., Clements, T.C., Espeland, E.K., Monaco, T.A., Rinella, M.J., Munson, S.M., Ballenger, E.A., Quiroga, R., Wainwright, C.E., Bahm, M.A., Barger, N., Baughman, O.W., Becker, C., Esteban Lucas-Borja, M., Calleja, E., Caruana, A., Davies, K.W., Deák, B., Drake, J., Dallau, S., Eldridge, J., Farrell, H.L., Fick, S.E., Garbowski, M., de la Riva, E., Golos, P.J., Grey, P.A., Heydenrych, B., Holmes, P.M., James, J.J., Jonas-Bratten, J., Kiss, R., Kramer, A.T., Larson, J.E., Lorite, J., Mayence, C., Merino-Martín, L., Miglécz, T., Montalvo, A.M., Navarro-Cano, J.A., Paschke, M.W., Luis Peri, P., Pokorny, M.L., Saayman, N., Schantz, M.C., Parkhurst, T., Seabloom, E.W., Stuble, K.L., Uselman, S.M., Valkó, O., Veblen, K., Wilson, S., Wong, M., Xu, Z., Suding, K.L., Svejcar, L.N., Erickson, T.E., Leger, E.A., Breed, M.F., Faist, A.M., Harrison, P.A., Curran, M.F., Guo, Q., Kirmer, A., Law, D.J., Mganga, K.Z., Török, P., Abdullahi, A., Carrick, P.J., Burton, C., Burton, P.J. 2021. Drivers of seedling establishment success in dryland restoration efforts. Nature Ecology and Evolution. 5:1283-1290.
Van Pelt, R.S., Tatarko, J., Gill, T.E., Chang, C., Li, J., Eibedingil, I.G., Mendez, M. 2020. Dust emission source characterization for visibility hazard assessment on Lordsburg Playa in southwestern New Mexico, USA. Geoenvironmental Disasters. 7:34.
Tatarko, J. and L.E. Wagner. 2020. Introduction to the Wind Erosion Prediction System (WEPS). In: Tatarko, J., editor. The Wind Erosion Prediction System (WEPS): Technical Documentation. USDA Agriculture Handbook 727. United States Department of Agriculture, Agricultural Research Service, Beltsville, MD. p. 1-12.
Tatarko, J., Sporcic, M., Skidmore, E.L. 2020. A history of wind erosion models in the United States Department of Agriculture, Part 1: Prior to the Wind Erosion Prediction System. In: Tatarko, J., editor. The Wind Erosion Prediction System (WEPS): Technical Documentation. USDA Agriculture Handbook 727. United States Department of Agriculture, Agricultural Research Service, Beltsville, MD. p. 28-56.
Tatarko, J. 2020. Single storm applications of WEPS and the single-event Wind Erosion Evaluation Program (SWEEP). In: Tatarko, J., editor. The Wind Erosion Prediction System (WEPS): Technical Documentation. USDA Agriculture Handbook 727. United States Department of Agriculture, Agricultural Research Service, Beltsville, MD. p. 491-497.
Van Donk, S., Tatarko, J., Skidmore, E.L., Wagner, L.E., Fox, F.A. 2020. Weather generators of WEPS. In: Tatarko, J., editor. The Wind Erosion Prediction System (WEPS): Technical Documentation. USDA Agriculture Handbook 727. United States Department of Agriculture, Agricultural Research Service, Beltsville, MD. p. 57-84.
Fox, F.A., A.A. Durar, and E.L. Skidmore. 2020. Hydrology submodel of WEPS. In: Tatarko, J., editor. The Wind Erosion Prediction System (WEPS): Technical Documentation. USDA Agriculture Handbook 727. United States Department of Agriculture, Agricultural Research Service, Beltsville, MD. p. 158-225.
Fox, F. and A. Retta. 2020. Crop submodel of WEPS. In: Tatarko, J., editor. The Wind Erosion Prediction System (WEPS): Technical Documentation. USDA Agriculture Handbook 727. United States Department of Agriculture, Agricultural Research Service, Beltsville, MD. p. 272-321.
Hagen, L.J. and F.A. Fox. 2020. Erosion submodel of WEPS. In: Tatarko, J., editor. The Wind Erosion Prediction System (WEPS): Technical Documentation. USDA Agriculture Handbook 727. United States Department of Agriculture, Agricultural Research Service, Beltsville, MD. p. 85-157.