Location: Range Management Research2019 Annual Report
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.
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 was made in all seven objectives. In an effort to identify cattle biotypes more suited for low-input production systems in arid rangelands (Objective 1A), behavior of nursing and non-nursing Raramuri Criollo cattle was evaluated. Movement patterns of Criollo cows with and without calves were similar, suggesting this biotype is less constrained by its calf than is typically observed for rangeland cattle. A new experiment (the Duneland Restoration Project) was implemented to evaluate practices for restoring shrub-dominated landscapes to perennial grasslands (Objective 1B). This study will examine a host of attributes to identify barriers to grass recovery. 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 locations to integrate multiple variables into models in order to predict outbreaks of vector-borne diseases. Analyses at the landscape scale in parts of Colorado, Texas, and New Mexico revealed that distance to water and host density were important factors in transmission of vesicular stomatitis virus. A national wind erosion network has been established (Objective 2B) on 13 sites across the western U.S., with five additional rangeland and cropland sites currently being implemented. Personnel training and standardized data collection methods were implemented to collect data for a quantitative study to assess sampling rigor across the network during the past year. Wind erosion assessments using models developed by the network will help land managers and producers identify management practices that reduce wind erosion. Models were developed to predict climate-driven alternative vegetation states in western rangelands using future precipitation models, long-term datasets, and sensor and imagery products (Objective 3A). Sequences of four or more years with above-average precipitation accompanied by establishment of perennial grasses are projected to reverse state changes in degraded shrublands under managed livestock grazing. A method depicting grass production in real time from remotely sensed phenological data was developed for use in managing livestock movements (Objective 3B). A national on-line database, the Ecosystem Dynamics Interpretative Tool (EDIT), was improved based on user feedback and released to the public during the past year (Objective 4). This database houses ecological site information that provides the scientific basis for conservation decisions currently being made by Natural Resources Conservation Service and Bureau of Land Management planners. Standardized rangeland monitoring training and procedures to improve quality assurance and control were developed and tested (Objective 5A). These online training materials and sampling design and analysis tools are being used by the Bureau of Land Management, the Natural Resources Conservation Service, and other public and private land managers to inform management decisions on millions of acres of rangelands. Progress was also made on the development of the Land-Potential Knowledge System (LandPKS) app (Objective 5B), with the deployment of two new features (a Soil Identification function and the first version of a Management module). The Management module will provide farmers with a simple, rapid recordkeeping tool to document management practices. Progress was also made in building climate-resilient landscapes and communities in the Southwest (Objective 6). The Southwest Climate Hub team launched two online decision support tools (the AgRisk Viewer and the Climate Smart Restoration Tool) to assist land managers and producers in making decisions, co-authored the 4th National Climate Assessment, and helped launch the Weather and Climate working group in the Long-Term Agroecosystem Research (LTAR) network. This network, composed of 18 research sites across the U.S., coordinates research activities in a variety of conditions and environments at a national scale. ARS scientists in Las Cruces, New Mexico led or co-led network initiatives on wind erosion, phenology, grazingland nutrient transport, and grazingland common indicators (Objective 7) that seek science-based solutions to sustainably intensify agricultural production.
1. Multi-scale big data-model integration to improve production and environmental quality on western rangelands. Vector-borne diseases such as vesicular stomatitis virus (VSV) have major economic implications for animal agriculture globally, including animal quarantine, animal loss, and lost capital. ARS scientists in Las Cruces, New Mexico, are collaborating with others to retrospectively integrate environmental, vector, host and viral variables with disease occurrence in an effort to predict future occurrence and distribution of vector-borne diseases. Landscape-scale analyses within select counties of Colorado, Texas, and New Mexico showed the importance of distance to water and host density to the transmission of VSV between vectors and hosts. VSV genetic data were used to build phylogenetic trees and develop relationships with environmental variables across the western U.S. in an effort to identify outbreak and dispersal pathways. Vector-specific proactive mitigation strategies were examined that could be employed by producers at the ranch level to reduce economic costs during VSV incursions and outbreaks. Successful implementation of tools to predict VSV outbreaks could prevent them and prevent financial losses to ranchers and horse owners throughout the Western U.S.
2. Building climate-resilient landscapes and communities in the Southwest. Weather and climate impacts on Southwestern U.S. ecosystems and communities include weather-related crop loss, large interannual and spatial variability in precipitation and rangeland production, wildfire, and extreme drought. As members of the USDA Southwest Climate Hub (SW Climate Hub), ARS scientists in Las Cruces, New Mexico, engage in collaborative projects with resource managers and stakeholders to 1) investigate and report on impacts using the best-available scientific information, 2) develop decision-support tools, and 3) convene stakeholder sessions regarding drought, wildfire, extreme events, as well as future projections of these stressors and adaptation and mitigation strategies to minimize their effects. The SW Climate Hub team recently completed the launch of two online decision support tools (the AgRisk Viewer and the Climate Smart Restoration Tool) to inform members of the agricultural community, and contribute to drought vulnerability assessment projects linked to ecological sites. Of particular importance, the SW Climate Hub team co-authored the 4th National Climate Assessment. During the past year, we hosted more than 12 stakeholder meetings and workshops and gave more than 20 presentations to stakeholder groups and scientific audiences, and helped launch the Weather and Climate working group in the Long-Term Agroecosystem Research (LTAR) network. Collectively, these efforts will assist Southwestern farmers, ranchers, foresters, and other land managers in strategically adapting to the impacts of extreme weather and climate change.
3. Ecological Site Description database. Ecological Site Descriptions (ESDs) provide the scientific basis for conservation decisions made by Natural Resources Conservation Service (NRCS) and Bureau of Land Management (BLM) planners, yet this information is not organized such that it can 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 NRCS staff across the country. The EDIT database now contains approximately 8000 ESDs and is actively being used for ESD development by NRCS and other agency staff, receiving approximately 250 site visits per day. The database dramatically improves access to ESD information by land managers and the public that is currently in demand but unavailable to them, which in turn allows for more effective land management decisions across the entire U.S.
4. Land-Potential Knowledge System (LandPKS) development and implementation. 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 app on iOS and Android phones and tablets, allowing managers to rapidly collect and store soil and topographic information (LandInfo) and monitor vegetation (LandCover) of a given area, both of which are necessary to support outcome-based land management. A soil identification function and the first version of a management module were deployed, providing small farmers with a simple, rapid recordkeeping tool that can be used to document their management practices. These tools will be combined with other apps to allow for the identification of site-specific management options by land managers worldwide in the field; site-specific information is in high demand by landowners and the agricultural industry. Access to site-specific information will enhance global land productivity and sustainability.
5. Wind erosion network implementation to support a national assessment. Rangeland and cropland wind erosion reduces soil productivity 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, led the coordination of National Wind Erosion Research Network sites at thirteen locations. Five additional sites in cropland and rangeland sites are being coordinated in collaboration between ARS and the Bureau of Land Management. These Network sites are part of the Long-Term Agroecosystem Research (LTAR) network that collects data in real time (e.g., sediment mass flux, meteorological conditions, dust deposition). Personnel training and standardized data collection methods were implemented across the network during the past year that resulted in a quantitative study to assess sampling rigor across the network. Network data were analyzed that allowed changes in wind erosion to be detected across cropland and rangelands. These analyses were used to support wind erosion modeling for a national wind erosion assessment that will inform producers and land managers regarding land use practices that help reduce wind erosion.
6. Tools and techniques for multi-scale inventory, monitoring, and assessment. 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 the expansion of the rangeland monitoring program that directly supports the Bureau of Land Management (BLM) and Natural Resources Conservation Service (NRCS) national inventory and monitoring programs as well as the interagency National Wind Erosion Research Network. Design tools (sample.design R package, statistical analysis programs) were developed to improve quality assurance and control, enhance existing monitoring designs, and streamline sample designs. Additional analytical improvements were added to the terradactyl and aim.analysis R packages to include new data formats, expedite data processing, and combine multiple sample designs in a statistically valid manner. These tools and R packages are used by BLM staff to produce reports and make management decisions regarding sage-grouse habitat suitability and to improve grazing management systems. Methods, tools, databases, information resources and training are available online and are being used by land managers and policy makers to manage rangelands at local to continental scales over millions of acres. The use of these tools will allow managers to detect resource problems in time to avoid persistent and expensive damage.
7. Long-Term Agroecosystem Research. The Long-Term Agroecosystem Research (LTAR) network seeks to integrate scientific research across a network of 18 sites via integration of experimental approaches, measurements, and data. ARS scientists in Las Cruces, New Mexico, led or co-led network initiatives on wind erosion, phenology, grazingland nutrient transport, and grazinglands common indicators, and provided data for other initiatives. These coordinated research activities will link ARS science to stakeholders across the country seeking to sustainably intensify agricultural production guided by multi-disciplinary, systems-level science. Specifically, our customers seek new options for adapting their operations and management practices to increasingly arid environments. Our research will lead to adoption of new livestock production systems, more effective restoration strategies, and increased use of science information in management decisions by private and public lands managers throughout the western U.S.
8. Low input livestock production strategies. New world cattle biotypes may help ranchers cope with low and variable forage production that often occurs on western U.S. rangelands. Raramuri Criollo cattle have undergone approximately 500 years of natural selection and adaptation to harsh rangeland conditions. ARS scientists in Las Cruces, New Mexico, have been examining attributes of this biotype. Movement patterns of nursing vs. non-nursing cows and cow-calf proximity patterns of nursing cows were compared using GPS collars on cows and proximity loggers on cow-calf pairs. Nursing and dry Criollo cows travelled similar distances per day, moved at similar speeds, and did not differ in time spent grazing, resting, or traveling each day. Area explored per day by a calf and its mother were similar and cow-calf contact events occurred throughout the entire area grazed by the dams. This biotype exhibited a strong follower behavior, suggesting Raramuri Criollo cows are less constrained by the presence of a calf than typically observed in conventional breeds of rangeland cattle. Identifying biotypes with behaviors that match forage resources in extensive semiarid ecosystems will benefit ranchers by optimizing use of available forage.
9. Remotely sensed phenological indicators of plant production for livestock management. Integration of remote sensing and data acquisition technologies is needed to improve rangeland vegetation monitoring and use of natural resources. ARS scientists in Las Cruces, New Mexico, developed a method to support data-driven decision-making tools for livestock management. The method uses online tools to depict forage production in real time for guiding livestock management decisions. Land managers and producers will benefit from new technologies to remotely determine vegetation characteristics and forecast forage production that can be used to enhance livestock production. These integrated analyses will increasingly allow managers to target management interventions, including grazing, herbicide applications, and prescribed fire, with pinpoint accuracy in both space and time.
10. Evaluation of conservation practices for desert grasslands. Grassland restoration success in arid southwestern rangelands is highly variable, and little is known about the sources of variability that can be used in restoration planning. ARS scientists in Las Cruces, New Mexico, established a new experiment—the “Duneland Restoration Project”—designed to understand the causes of variability in grassland recovery within shrub-dominated areas. Data are being collected that compare reference, restored, and unrestored areas with respect to vegetation and soil seed banks, soil physical and chemical properties, landscape position, soil water dynamics, wind erosion, and phenology using a variety of instruments. These studies will establish the barriers to grass recovery in unrecovered areas as a basis for designing novel restoration strategies for use by land managers.
11. Prediction of climate-driven vegetation state changes. Directional decreases or increases in precipitation are predicted for rangelands in the future. ARS scientists in Las Cruces, New Mexico, are integrating long-term datasets with sensor and imagery products, static and dynamic maps, and conceptual models, to improve understanding and prediction of vegetation responses of drylands to alternative climate scenarios. These modeling efforts indicate that sequences of four or more years with above-average precipitation which promote establishment and persistence of perennial grasses in degraded shrublands are expected to lead to state change reversals under managed livestock grazing. This information will assist land managers and producers in responding to shifting weather conditions.
Edwards, B.L., Allen, S.T., Braud, D.H., Keim, R.F. 2019. Stand density and carbon storage in cypress-tupelo wetland forests of the Mississippi River delta. Forest Ecology and Management. 441:106-114. https://doi.org/10.1016/j.foreco.2019.03.046.
Herrick, J.E., Shaver, P., Pyke, D., Pellant, M., Toledo, D.N., Lepak, N. 2019. A strategy for defining the reference for land health and degradation assessments. Ecological Indicators. 97:225-230. https://doi.org/10.1016/j.ecolind.2018.06.065.
Estell, R.E., Cibils, A.F., Utsumi, S.A., Stricklan, D., Butler, E.M., Fish, A.I., Ganguli, A.C. 2018. Controlling one-seed juniper saplings with small ruminants: What we’ve learned. Rangelands. 40:129-135. https://doi.org/10.1016/j.rala.2018.07.002.
Peinetti, H., Bestelmeyer, B.T., Chirino, C., Kin, A., Frank Buss, M. 2019. Generalized and specific state-and-transition models to guide management and restoration of Caldenal forests. Rangeland Ecology and Management. 72:230-236. https://doi.org/10.1016/j.rama.2018.11.002.
Herrick, J.E., Neff, J., Quandt, A., Salley, S.W., Maynard, J.J., Ganguli, A., Bestelmeyer, B.T. 2019. Prioritizing land for investments based on short- and long-term land potential and degradation risk: A strategic approach. Environmental Science and Policy. 96:52-58. https://doi.org/10.1016/j.envsci.2019.03.001.
Levi, M.R., Bestelmeyer, B.T. 2018. Digital soil mapping for predicting and managing fire in rangelands. Fire Ecology. https://doi.org/10.1186/s42408-018-0018-4.
Bestelmeyer, B.T., Peters, D.C., Archer, S.R., Browning, D.M., Okin, G.S., Schooley, R.L., Webb, N.P. 2018. The grassland–shrubland regime shift in the southwestern United States: Misconceptions and their implications for management. Bioscience. 68:678-690. https://doi.org/10.1093/biosci/biy065.
Bestelmeyer, S., Grace, E., Haan-Amato, S., Pemberton, R., Havstad, K. 2018. Broadening the impact of K–12 science education collaborations in a shifting education landscape. Bioscience. 68:706-714. https://doi:10.1093/biosci/biy088.
Browning, D.M., Crimmins, T., James, D.K., Spiegal, S.A., Levi, M.R., Anderson, J.P., Peters, D.C. 2018. Synchronous species responses reveal phenological guilds – Implications for management. Ecosphere. 9(9):e02395. https://doi.org/10.1002/ecs2.2395.
Browning, D.M., Spiegal, S.A., Estell, R.E., Cibils, A., Peinetti, H. 2018. Integrating space and time: A case for phenological context in grazing studies and management. Frontiers of Agricultural Science and Engineering. 5(1):44-56. https://doi.org/10.15302/j-FASE-2017193.
Chappell, A., Webb, N., Guerschman, J., Thomas, D., Mata, G., Handcock, R., Leys, J. 2017. Improving ground cover monitoring for wind erosion assessment using MODIS BRDF parameters. Remote Sensing of Environment. 204:756-768. https://doi.org/10.1016/j.rse.2017.09.026.
Duniway, M.C., Petrie, M., Peters, D.C., Anderson, J., Crossland, K., Herrick, J.E. 2018. Soil water dynamics at 15 locations distributed across a desert landscape: Insights from a 27-year dataset. Ecosphere. 97:e02335. https://doi.org/10.1002/ecs2.2335.
Galloza, M.S., Webb, N.P., Bleiweiss, M., Winters, C., Herrick, J.E., Ayers, E. 2018. Resolving dust emission responses to land cover change using an ecological land classification. Aeolian Research. 32:141-153. https://doi.org/10.1016/j.aeolia.2018.03.001.
Havstad, K.M., Brown, J.R., Estell, R.E., Elias, E.H., Rango, A., Steele, C. 2018. Vulnerabilities of southwestern U.S. rangeland-based animal agriculture to climate change . Climatic Change. 148:371-386. https://doi.org/10.1007/s10584-016-1834-7.
Jones, M., Allred, B.W., Naugle, D.E., Maestas, J.D., Donnelly, P., Metz, L., Karl, J., Smith, R., Bestelmeyer, B.T., Boyd, C.S., Kerby, J.D., McIver, J.D. 2018. Innovation in rangeland monitoring: Annual, 30m, plant functional type percent cover maps for US rangelands, 1984–2017. Ecosphere. 9(9):e02430. https://doi.org/10.1002/ecs2.2430.
Peters, D.C., Burruss, N., Rodriguez, L.L., McVey, D.S., Elias, E.H., Pelzel-McCluskey, A.M., Derner, J.D., Schrader, T.S., Yao, J., Pauszek, S.J., Lombard, J., Archer, S.R., Bestelmeyer, B.T., Browning, D.M., Brungard, C., Hatfield, J.L., Hanan, N.P., Herrick, J.E., Okin, G.S., Sala, O.E., Savoy, H., Vivoni, E.R. 2018. An integrated view of complex landscapes: A big data-model integration approach to transdisciplinary science. Bioscience. 68:653-669. https://doi.org/10.1093/biosci/biy069.
Petrie, M., Peters, D.C., Yao, J., Blair, J.M., Burruss, N., Collins, S., Derner, J.D., Gherardi, L.A., Hendrickson, J.R., Sala, O., Starks, P.J., Steiner, J.L. 2018. Regional grassland productivity responses to precipitation during multiyear above- and below-average rainfall periods. Global Change Biology. 24:1935-1951. https://doi.org/10.1111/gcb.14024.
Ratcliff, F., Bartolome, J.W., Macaulay, L., Spiegal, S.A., White, M.D. 2018. Applying ecological site concepts and state-and-transition models to a grazed riparian rangeland. Ecology and Evolution. https://doi.org/10.1002/ece3.4057.
Salley, S.W., Herrick, J.E., Holmes, C., Karl, J.W., Levi, M.R., McCord, S.E., Van De Waal, C., Van Zee, J.W. 2018. A comparison of soil texture-by-feel estimates: Implications for the citizen soil scientist. Soil Science Society of America Journal. 82:1526-1537. https://doi.org/10.2136/sssaj2018.04.0137.
Bergstrom, R., Borch, T., Martin, P., Melzer, S., Rhoades, C., Salley, S.W., Kelly, E. 2019. The generation and redistribution of soil cations in high elevation catenas in the Fraser Experimental Forest, Colorado, U.S. Geoderma. 333:135-144. https://doi.org/10.1016/j.geoderma.2018.07.024.
Elias, E.H., McVey, D.S., Peters, D.C., Derner, J.D., Pelzel-McCluskey, A., Schrader, T.S., Rodriguez, L.L. 2018. Contributions of hydrology to Vesicular Stomatitis Virus emergence in the western United States. Ecosystems. 22:416-433. https://doi.org/10.1007/s10021-018-0278-5.
Klose, M., Gill, G., Etyemezian, V., Nikolich, G., Ghodsi Zadeh, Z., Webb, N., Van Pelt, R.S. 2019. Dust emission from crusted surfaces: Insights from field measurements and modelling. Aeolian Research. 40:1-14.
Chappell, A., Webb, N., Leys, J., Waters, C., Orgill, S., Eyres, M. 2019. Minimising soil organic carbon erosion by wind is critical for land degradation neutrality. Environmental Science and Policy. 93:43-52. https://doi.org/10.1016/j.envsci.2018.12.020.
Webb, N., Chappell, A., Edwards, B., McCord, S.E., Van Zee, J.W., Cooper, B., Courtright, E.M., Duniway, M., Sharratt, B.S., Tedela, N., Toledo, D.N. 2019. Reducing sampling uncertainty in aeolian research to improve change detection. Journal of Geophysical Research. 1-12. https://doi.org/10.1029/2019JF005042.
Browning, D.M., Snyder, K.A., Herrick, J.E. 2019. Plant phenology: Taking the pulse of rangelands. Rangelands. 41(3):129-134. https://doi.org/10.1016/j.rala.2019.02.001.
Pierce, N., Archer, S., Bestelmeyer, B.T., James, D.K. 2019. Grass-shrub competition in arid lands: An overlooked driver in grassland-shrubland state transition? Ecosystems. 22(3):619-628. https://doi.org/10.1007/s10021-018-0290-9.
Spiegal, S.A., Estell, R.E., Cibils, A.F., James, D.K., Peinetti, R., Browning, D.M., Romig, K.B., Gonzalez, A.L., Lyons, A.J., Bestelmeyer, B.T. 2019. Seasonal divergence of landscape use by heritage and conventional cattle on desert rangeland. Rangeland Ecology and Management. 72(4):590-601. https://doi.org/10.1016/j.rama.2019.02.008.
Ji, W., Hanan, N., Browning, D.M., Monger, H., Peters, D.C., Bestelmeyer, B.T., Archer, S.R., Ross, C., Lind, B.M., Anchang, J., Kumar, S., Prihodko, L. 2019. Constraints on shrub cover and shrub-shrub competition in a U.S. southwest desert. Ecosphere. 10(2):e02590. https://doi.org/10.1002/ecs2.2590.
Svejcar, L., Bestelmeyer, B.T., James, D.K., Peters, D.C. 2019. Small mammal herbivory and grassland recovery potential in the Chihuahuan Desert. Journal of Arid Environments. 166:11-16. https://doi.org/10.1016/j.jaridenv.2019.04.00.
Maynard, J.J., Nauman, T., Salley, S.W., Bestelmeyer, B.T., Duniway, M., Talbot, C.J., Brown, J.R. 2019. Digital mapping of ecological land units using a nationally scalable modeling framework. Soil Science Society of America Journal. 83:666-686. https://doi.org/10.2136/sssaj2018.09.0346.
Forster, M., Bestelmeyer, S., Baez-Rodriguez, N., Berkowitz, A., Caplan, B., Esposito, R., Grace, E., Mcgee, S. 2018. Data jams: Promoting data literacy and science engagement while encouraging creativity. Science Teacher. 86(2).
Di Stefano, S.F., Karl, J.W., McCord, S.E., Stauffer, N.G., Makela, P., Manning, M. 2018. Comparison of 2 vegetation height methods for assessing greater sage-grouse seasonal habitat. Wildlife Society Bulletin. 42(2):213-224. https://doi.org/10.1002/wsb.877.
Edwards, B.L., Webb, N.P., Brown, D.P., Elias, E.H., Peck, D.E., Pierson Jr, F.B., Williams, C.J., Herrick, J.E. 2019. Climate change impacts on wind and water erosion on US rangelands. Journal of Soil and Water Conservation. 74(4):405-418. https://doi.org/10.2489/jswc.74.4.405.
Reyes, J.T., Elias, E.H. 2019. Spatio-temporal variation of crop loss in the United States from 2001 to 2016. Environmental Research Letters. 14:074017. https://doi.org/10.1088/1748-9326/ab1ac9.