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

Location: Range Management Research

2020 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. In an effort to identify cattle biotypes more suited for low-input production systems in arid rangelands (Objective 1A), heat tolerance of Raramuri Criollo (RC) cows was compared to Angus x Hereford (AH) cows typically raised in the southwestern U.S. During the hottest part of the day, RC cows had lower body temperature and traveled further than AH cows. Identifying biotypes with attributes that match environmental conditions and forage resources in extensive semiarid ecosystems will benefit ranchers in the region. A long-term experiment was implemented to evaluate effects of brush management practices on restoration of shrub-dominated landscapes (Objective 1B). Analyses were completed and a report was generated detailing effects of brush management practices on grassland recovery for use by land managers for conservation planning. 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 to harmonize data used 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. Sediment transport measurements collected in real time at National Wind Erosion Research Network sites (Objective 2B) across the U.S. was used to calibrate the Aeolian Erosion (AERO) model for use in assessing wind erosion across western U.S. grazing lands. The USDA SCINet Scientific Computing Initiative was used to develop code to apply the model to large vegetation monitoring datasets that will assist land managers and producers in identifying management practices that reduce wind erosion. Models are being developed to predict climate-driven vegetation changes in western rangelands using future precipitation models, long-term datasets, and sensor and imagery products (Objective 3A). Previously unanalyzed long-term pantograph data beginning in 1915 revealed that subtle variations in soil texture affect grass decline and recovery due to drought and high rainfall. These results will improve the ability of land managers and producers to predict vegetation responses under changing climate scenarios. Time series images from satellite and surface cameras (phenocam) from multiple sites across the U.S. were compiled to develop long-term grass production forecasts and tools to support management decisions for livestock, forage and crop production (Objective 3B). A national online database, the Ecosystem Dynamics Interpretative Tool (EDIT), was enhanced and expanded during the past year (Objective 4). The database now contains 4,778 published Ecological Site Descriptions with nearly 6000 more in development and receives approximately 3100 site visits per day. The database significantly improves access to ESDs needed to assist land managers with conservation planning. Standardized rangeland monitoring training and procedures were developed and tested and the Monitoring Manual for Grassland, Shrubland, and Savanna Ecosystems was published online and distributed to monitoring field staff (Objective 5A). These online training materials, software programs, and analytical tools are being used by the Bureau of Land Management, the Natural Resources Conservation Service, and other public and private land managers to inform rangeland and wildlife management decisions and conservation planning on millions of acres of rangelands. Progress was also made on the development of the Land-Potential Knowledge System (LandPKS) application (Objective 5B). New features were added for monitoring soil health, accessing and comparing local habitat information, and maintaining data privacy. The app will allow users to rapidly access information about their soil and vegetation and assist with land management decisions. Progress was also made in building climate-resilient landscapes and communities in the Southwest (Objective 6). The Southwest Climate Hub team launched or expanded several online decision support tools to help land managers and producers adapt to the impacts of extreme weather conditions and climate change. The team co-developed an online dust mitigation handbook, as well as the AgRisk Viewer, and the AfterFire toolkit. The Southwest Climate Hub presented and/or hosted 32 scientific meetings, workshops and webinars to various stakeholders, and co-launched the Drought Learning Network with climate scientists and land managers. 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, co-led an initiative to understand the potential to recycle and redistribute manure from areas with excess to areas for use as a resource in an effort to connect livestock and crop production systems.

Accomplishments
1. 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 (RC) cattle have undergone approximately 500 years of natural selection and adaptation to harsh rangeland conditions. ARS scientists in Las Cruces, New Mexico, have been studying this biotype. Effects of temperature on foraging behavior of RC was compared to Angus x Hereford (AH) cows typically raised in the region using body temperature loggers and GPS collars to record ambient temperature. In the summer, RC cows had lower body temperature and higher collar temperature than AH cows during the hottest part of the day. They also traveled further and spent more time grazing and traveling and less time resting than AH cows. Differences between breeds were greatest during the hottest part of the day during summer, suggesting the RC biotype may have a higher thermal tolerance and be more adapted to harsh desert environments. Identifying biotypes with attributes that match environmental conditions in extensive semiarid ecosystems will benefit ranchers in the Southwest by imposing fewer constraints on movement and optimizing use of available forage.

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 knowledge co-production 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 developed an online dust mitigation handbook with Natural Resources Conservation Service and hosted webinars and presentations to share the handbook. The team evaluated the AgRisk Viewer (an on-line risk management decision support tool) and contributed to the AfterFire toolkit (an on-line resource for water managers post-fire). These two web pages have had approximately 1400 views in from September 2019-May 2020. The SW Climate Hub also hosted an urban tree adaptation workshop, expanded Grass-Cast (a forage production forecasting tool) to New Mexico and Arizona, and conducted a survey of cattle producers at the Southwest Beef Symposium regarding grass finishing and sustainable Southwest beef production to help understand vulnerabilities to climate change and adaptation options. During the past year the SW Climate Hub presented and/or hosted 32+ scientific meetings, workshops and webinars to various stakeholders, and co-launched the Drought Learning Network with climate scientists and land managers. 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. 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. The Monitoring Manual for Grassland, Shrubland, and Savanna Ecosystems was published online and physical copies were distributed to monitoring field staff. Statistical analysis software programs and R packages were developed and updated to support monitoring sample design, multi-scale monitoring data analysis, and standardized rangeland indicator development. Additional analytical and computing improvements were added to enable the aggregation of standardized monitoring data from BLM and NRCS so that standardized monitoring information could be used to develop ecological site concepts and prioritize conservation planning. These tools, datasets, and R packages were used by BLM and NRCS to produce reports and make management decisions regarding wildlife habitat suitability, evaluate conservation practice effectiveness, and to improve grazing management systems. Methods, tools, databases, information resources and training are available on-line and are being used by land managers and policy makers to manage rangelands at local to continental scales over millions of acres of rangelands.

4. Ecological dynamics national 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 4,778 published ESDs and 5,979 ESDs in development with 312 NRCS contributors. The website receives approximately 3100 site visits per day. Integration of the Ecological Site Information System (ESIS) database is complete and additional functions were added to EDIT that align it with NRCS conservation planning. The database dramatically improves access to ESD information by land managers and the public, which in turn has increased the impact of ESDs on land management.

5. 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 identify their soil and access soil survey information (LandInfo) and monitor vegetation (LandCover), both of which are necessary to support outcome-based rangeland management. A module for monitoring soil health (SoilHealth) and accessing and comparing local habitat information, as well as a data privacy option were added. 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. 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 long-term distributed experiment to measure the conservation effects of brush management in 45 treatment areas across southern New Mexico. Analysis of data from 5 and 10 years of vegetation monitoring was completed and a report was produced indicating the conditions under which grassland recovery occurs in response to brush management. This study will provide land managers with an estimate of the overall effects of brush management on conservation and forage production outcomes as well as a model for prioritizing future brush management efforts.

7. 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.

8. 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, calibrated the Aeolian Erosion (AERO) model against sediment transport measurements collected in real time at National Wind Erosion Research Network sites. The model calibration included explicit representation of model uncertainty that can be communicated to stakeholders. Code was developed to apply AERO to large standardized vegetation monitoring datasets using the USDA SCINet Scientific Computing Initiative. The AERO model is now available for applications to assess wind erosion across western U.S. grazing lands.

9. 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, co-led a network initiative on livestock waste management. Managing manures is one of the most difficult challenges of modern agriculture, affecting not only resource management, but also crop production and human and environmental health. The LTAR Network developed the concept of a "manureshed” to create a framework for addressing this challenge by reconnecting livestock and crop production systems through the use of manure. Ten LTAR sites collaborated to classify the lower U.S. counties for their capacity to either supply manure phosphorus (P) and nitrogen (N) from confined livestock production (“sources”) or to assimilate and remove excess P and N via crops (“sinks”). The county-level P balances of the source and sink counties were used to delineate four regional manuresheds, with source areas dominated by various combinations of confined hog, poultry, dairy, and beef industries. Results showed there is potential to redistribute manure from source to sink counties across much of the country, with significant opportunity in the South. The manureshed concept is designed to help everyone in our agricultural systems – from farmers to consumers, to industry leaders and policy-makers – to understand the potential for recycling manure and transforming it from a liability to a valuable resource. Multiple stakeholders have already demonstrated interest in the concept, including university extension, crop farmers, and developers of technologies to treat manure before land application.

10. 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, compiled image time series from satellite and digital near-surface camera (phenocam) instruments for 60 and 91 sites across the U.S., respectively. Phenocam time series data are being used to evaluate long-term forecasts for grassland productivity. In addition, phenocam and satellite time series data are being used to develop tools to identify the start and end of the growing season as a way to support management decision-making for livestock, forage and crop production. Land managers and producers will benefit from new technologies to remotely determine vegetation characteristics, forecast forage production, and target specific management practices, such as herbicide applications and prescribed fire.

11. 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. ARS scientists in Las Cruces, New Mexico, collaborated with other ARS research locations to retrospectively integrate and harmonize environmental, vector, host and viral variables with disease occurrence data 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, regulating grass declines and recovery in response to drought events and high rainfall years. This information will assist land managers and producers in planning for weather variability and targeted restoration.

Review Publications
McIntosh, M., Holechek, J., Spiegal, S.A., Cibils, A.F., Estell, R.E. 2019. Long-term declining trends in Chihuahuan Desert forage production in relation to precipitation and ambient temperature. Rangeland Ecology and Management. 72:976-987. https://doi.org/10.1016/j.rama.2019.06.002.
Peters, D.C., Burruss, N., Okin, G., Hatfield, J.L., Scroggs, S.S., Huang, H., Brungard, C., Yao, J. 2020. Deciphering the past to inform the future: preparing for the next ("really big") extreme event. Frontiers in Ecology and the Environment. https://doi.org/10.1002/fee.2194.
Pi, H., Huggins, D.R., Webb, N., Sharratt, B.S. 2020. Comparison of soil-aggregate crushing-energy meters. Aeolian Research. 42:100559. https://doi.org/10.1016/j.aeolia.2019.100559.
Bailey, D., Mosley, J.C., Estell, R.E., Cibils, A., Horney, M., Hendrickson, J.R., Walker, J.W., Launchbaugh, K.L., Burritt, E.A. 2019. Synthesis paper: Targeted livestock grazing: A prescription for healthy rangelands. Rangeland Ecology and Management. 72:865-877. https://doi.org/10.1016/j.rama.2019.06.003.
Elias, E.H., Flynn, R., Idowu, O.J., Reyes, J.T., Sanogo, S., Schutte, B., Smith, R., Steele, C., Sutherland, C. 2019. Crop vulnerability to climate risk: Analysis of interacting systems and adaptation efficacy for sustainable crop production. Sustainability. 11(23):6619. https://doi.org/10.3390/su11236619.
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. https://doi.org/10.1016/j.ecolind.2019.105881.
Webb, N., Chappell, A., LeGrand, S., Ziegler, N., Edwards, B. 2020. A note on the use of drag partition in aeolian transport models. Aeolian Research. 42:100560. https://doi.org/10.1016/j.aeolia.2019.100560.
Gaiser, E.E., Bell, D.M., Castorani, M.C., Childers, D.L., Groffman, P.M., Jackson, R., Kominoski, J.S., Peters, D.C., Pickett, S.T., Ripplinger, J., Zinnert, J.C. 2020. Long-Term Ecological Research and Evolving Frameworks of Disturbance Ecology. Bioscience. 70(2):141-156. https://doi.org/10.1093/biosci/biz162.
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. https://doi.org/10.1029/2019EO137858.
Whitford, W.G., Steinberger, Y. 2020. Herbivory effects on Ephedra spp. in the Chihuahuan Desert. Open Journal of Ecology. 10:37-44. https://doi.org/10.4236/oje.2020.102003.
Taylor, S.D., Marconi, S. 2020. Rethinking global carbon storage potential of trees. A comment on Bastin et al. (2019). Annals of Forest Science. 77:23. https://doi.org/10.1101/730325.
Di Stefano, S., Karl, J., Bailey, D., Hale, S. 2020. Evaluation of the automated reference toolset as a method to select reference plots for oil and gas reclamation on Colorado Plateau rangelands. Journal of Environmental Management. 265:110578. https://doi.org/10.1016/j.jenvman.2020.110578.
Spiegal, S.A., Kleinman, P.J., Endale, D.M., Bryant, R.B., Dell, C.J., Goslee, S.C., Meinen, R.J., Flynn, K.C., Baker, J.M., Browning, D.M., McCarty, G.W., Bittman, S., Carter, J.D., Cavigelli, M.A., Duncan, E.W., Gowda, P.H., Li, X., Ponce, G., Raj, C., Silveira, M., Smith, D.R., Arthur, D.K., Yang, Q. 2020. Manuresheds: Advancing nutrient recycling in US agriculture. Agricultural Systems. 182:102813. https://doi.org/10.1016/j.agsy.2020.102813.
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. https://doi.org/10.2489/jswc.75.1.5A.
Nyamuryekung'e, S., Cibils, A., Estell, R.E., VanLeeuwen, D., Steele, C., Roacho, E.O., Rodriguez, A.F., Gonzalez, A.L., Spiegal, S.A. 2020. Do young calves influence movement patterns of nursing Raramuri Criollo cows on rangeland? Rangeland Ecology and Management. 73:84-92. https://doi.org/10.1016/j.rama.2019.08.015.
Mayagoitia, P., Bailey,, D.W., Estell, R.E. 2020. Phenological changes in the nutritive value of honey mesquite leaves, pods, and flowers in the Chihuahuan Desert. Agrosystems, Geosciences & Environment. 3:e20026. https://doi.org/10.1002/agg2.20026.
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. https://doi.org/10.1093/biosci/biz126.
Torell, G.L., Lee, K.D., Steele, C. 2019. Understanding future threats to western rangelands: Modeling the performance of grazing strategies in the face of environmental change. Western Economics Forum. 17(1):40-45.
Spiegal, S.A., Huntsinger, L., Starrs, P.F., Hruska, T., Schellenberg, M.P., McIntosh, M. 2019. Rangeland livestock production in North America. In: Squires, V. R., Bryden, W. L. (editors). Livestock Production, Management, Strategies and Challenges. Nova Science Publishers. Hauppauge, NY. 532 p.
Qin, J., Ren, H., Han, G., Zhang, J., Browning, D.M., Willms, W., Yang, D. 2019. Grazing reduces the temporal stability of temperate grasslands in northern China. Flora. 259:151450. https://doi.org/10.1016/j.flora.2019.151450.
Niles, M., Wiener, S., Schattman, R., Roesch-McNally, G., Reyes, J.T. 2019. Seeing is not always believing: crop loss and climate change perceptions among farm advisors. Environmental Research Letters. 14(4):044003. https://doi.org/10.1088/1748-9326/aafbb6.
Leimer, A.K., Boykin, K., Anderson, M.C., Steele, C., Bestelmeyer, B.T. 2019. Applicability of functional groups as indicators of resilience and redundancy in the San Pedro Watershed, Arizona. AIMS Environmental Science. 6(3):127–146. https://doi.org/10.3934/environsci.2019.3.127.
Bestelmeyer, B.T., Burkett, L.M., Lister, L., Schooley, R. 2019. Collaborative approaches to strengthen the role of science in rangeland conservation. Rangelands. 41(5):218-226. https://doi.org/10.1016/j.rala.2019.08.001.
Spiegal, S.A., Bestelmeyer, B.T., Archer, D.W., Augustine, D.J., Boughton, E., Boughton, R., Clark, P., Derner, J.D., Duncan, E.W., Cavigelli, M.A., Hapeman, C.J., Harmel, R.D., Heilman, P., Holly, M.A., Huggins, D.R., King, K.W., Kleinman, P.J., Liebig, M.A., Locke, M.A., McCarty, G.W., Millar, N., Mirsky, S.B., Moorman, T.B., Pierson, F.B., Rigby, J.R., Robertson, G., Steiner, J.L., Strickland, T.C., Swain, H., Wienhold, B.J., Wulfhorts, J., Yost, M., Walthall, C.L. 2018. Evaluating strategies for sustainable intensification of U.S. agriculture through the Long-Term Agroecosystem Research network. Environmental Research Letters. 13(3):034031. https://doi.org/10.1088/1748-9326/aaa779.
Kleinman, P.J., Spiegal, S.A., Rigby Jr., J.R., Goslee, S.C., Baker, J.M., Bestelmeyer, B.T., Boughton, R., Bryant, R.B., Cavigelli, M.A., Derner, J.D., Duncan, E.W., Goodrich, D.C., Huggins, D.R., King, K.W., Liebig, M.A., Locke, M.A., Mirsky, S.B., Moglen, G.E., Moorman, T.B., Pierson Jr., F.B., Robertson, G., Sadler, E.J., Shortle, J., Steiner, J.L., Strickland, T.C., Swain, H., Williams, M.R., Walthall, C.L., Tsegaye, T.D. 2018. Advancing the sustainability of US agriculture through long-term research. Journal of Environmental Quality. 47(6):1412-1425. https://doi.org/doi:10.2134/jeq2018.05.0171.
Schreiner-McGraw, A., Vivoni, E., Ajami, H., Sala, O., Throop, H., Peters, D.C. 2020. Woody plant encroachment has a larger impact than climate change on dryland water budgets. Scientific Reports. 10:8112. https://doi.org/10.1038/s41598-020-65094-x.
Kimiti, D., Ganguli, A., Herrick, J.E., Karl, J., Bailey, D. 2020. A decision support system for incorporating land potential information in the evaluation of restoration outcomes. Ecological Restoration. 38:94-104.
Kimiti, D., Ganguli, A., Herrick, J.E., Bailey, D. 2020. Evaluation of restoration success to inform future restoration efforts in Acacia reficiens invaded rangelands in northern Kenya. Ecological Restoration. 38:105-113.
Peters, D.C., Rivers, A.R., Hatfield, J.L., Lemay, D.G., Liu, S.Y., Basso, B. 2020. Harnessing AI to transform agriculture and inform agricultural research. IEEE IT Professional. 22(3):16-21. https://doi.org/10.1109/MITP.2020.2986124.
Peters, D.C., Savoy, H.M., Ramirez, G., Huang, H. 2020. AI recommender system with ML for agricultural research. IEEE IT Professional. 22:29-32.
Bestelmeyer, B.T., Marcillo, G., McCord, S.E., Mirsky, S.B., Moglen, G.E., Neven, L.G., Peters, D.C., Sohoulande Djebou, D.C., Wakie, T. 2020. Scaling up agricultural research with artificial intelligence. IEEE IT Professional. 22:32-38.
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. https://doi.org/10.1002/ecs2.3157.
Pi, H., Webb, N., Huggins, D.R., Sharratt, B.S. 2020. Critical standing crop residue amounts for wind erosion control in the inland Pacific Northwest, USA. Catena. 195:104742. https://doi.org/10.1016/j.catena.2020.104742.
Webb, N., Okin, G., Bhattachan, A., D'Odorico, P., Dintwe, K., Tatlhego, M. 2020. Ecosystem dynamics and aeolian sediment transport in the southern Kalahari. African Journal of Ecology. 58:337-344. https://doi.org/10.1111/aje.12700.
Quandt, A., Herrick, J.E., Peacock, G., Salley, S.W., Buni, A., Mkalawa, C., Neff, J. 2020. A standardized land capability classification system for land evaluation using mobile phone technology. Journal of Soil and Water Conservation. https://doi.org/10.2489/jswc.2020.00023.