Research Project: Knowledge Systems and Tools to Increase the Resilience and Sustainability of Western Rangeland Agriculture

Location: Range Management Research

2025 Annual Report

Objectives
Objective 1: Build predictive models of the impacts of land management and climate on western rangeland systems to guide decision making. Sub-objective 1.1: Develop and test models of arid rangeland ecosystem dynamics using field experiments and remote sensing data. Sub-objective 1.2: Apply erosion models to assess interactions among vegetation, climate (e.g., drought), and management changes with land, air, and water resources at multiple scales on western rangelands. Objective 2: Develop strategies to improve environmental and economic outcomes for Southwestern livestock-based agroecosystems. Sub-objective 2.1: Create and test new strategies to supply sustainable beef from western rangelands (LTAR Common Experiment). Sub-objective 2.2: Expand manureshed solutions to recouple animal and cropland systems. Objective 3: Co-develop indicators of sustainability and climate resilience with scientists, partners, and other stakeholders. Sub-objective 3.1: Co-develop sustainability indicator framework and peer-to-peer benchmarking tool to evaluate how agricultural systems perform in relation to sustainability goals at the farm/ranch level. Sub-objective 3.2: Develop new indicators of wind erosion that can support rangeland monitoring programs, land use planning, and management through the National Wind Erosion Research Network. Sub-objective 3.3: Develop methods for establishing quantitative benchmarks to interpret indicators and assess management effectiveness to improve sustainability and climate resilience. Objective 4: Co-develop decision support tools with stakeholders to help producers adapt to changing climate across landscapes modified by water scarcity (and excess), invasive species, erosion, changes in fire frequency, and historic land degradation. Sub-objective 4.1: Build tools that connect land potential information, monitoring, local knowledge, and big data for rangeland systems to improve adaptive decision-making. Sub-objective 4.2: Work with regional partner groups and the USDA Southwest Climate Hub to understand partner decision space and co-develop, test, and refine decision-support applications and concepts. Sub-objective 4.3: Co-develop a framework for “knowledge systems” that allow scientists, producers, managers, and policymakers to easily access and apply databases, knowledge sources, models, and decision support tools to inform land management at local to global scales.

Approach
Arid and semiarid rangelands of the United States and world face accelerating changes in climate, land use, and ecosystem function. Now more than ever, livestock producers and land managers need access to locally relevant, site-specific information and tools to manage change and build resilience to achieve sustainability goals. Available information, however, is insufficient for this task because a) system-level science to predict site-specific ecosystem changes in rangelands does not exist; b) the costs and benefits of new technologies and alternative livestock production systems are unknown; c) indicators for evaluating costs and benefits of available technologies are not comprehensive; and d) stakeholders often do not have the ability to identify, select, access, and apply suitable land management decision-support tools from among the hundreds that are available. The proposed project contributes solutions to these problems through a combination of field research, research co-production with stakeholders, modeling, and tool development. We will develop spatially explicit predictive models of vegetation change, productivity, carbon dynamics, and soil erosion potential in arid rangelands that will enable precision management at fine scales. We will create cost and benefit information for existing beef supply chain options and new technologies and practices (e.g., precision ranching and circular nutrient management). Simultaneously, we will work with the Long-Term Agroecosystem Research Network to develop new, standardized approaches for measuring and using sustainability indicators for comprehensive evaluation of management alternatives. Finally, we will advance the development of knowledge systems that integrate indicator tools and information sources, and we will connect them to the decision-making needs of stakeholders via database integration and use cases in the adaptive management of large rangeland landscapes. We will maintain and leverage century-long datasets, long-term collaborations with diverse partners including the Southwest Climate Hub, and a suite of existing models and computational tools to achieve these objectives.

Progress Report
Progress was made in all objectives. ARS researchers developed low-cost approaches using PhenoCams to complement high-resolution satellite imagery across 75 site-years of data in rangelands to detect productivity changes and plant responses to rainfall with greater precision than satellite imagery alone (Objective 1). ARS researchers developed and tested performance indicators with five ranchers across the Southwestern U.S. to systematically evaluate management outcomes, resulting in several partnering ranches changing practices to reduce input costs based on knowledge gained from the indicator system. Collaborated with New Mexico State University to examine Long Range Wide Area Network (LoRaWAN) tracking technology and machine learning to classify cattle activity and discriminate walking, grazing and resting behaviors in real time on large arid rangelands, creating a publicly available dataset with management implications for monitoring cattle health and critical activities (e.g. calving). Progress was made towards developing strategies to improve environmental and economic outcomes for Southwestern livestock-based agroecosystems through precision ranching tools that enable remote monitoring of cattle behavior and advanced low-cost technologies to support drought resilience by helping producers adapt grazing plans and optimize forage use (Objective 2). ARS researchers collaborated with Natural Resources Conservation Service (NRCS) and Bureau of Land Management (BLM) to develop benchmarking approaches using the Aeolian EROsion (AERO) model and created a Benchmark Exploration Tool connected to the Landscape Data Commons to enable managers to make objective decisions about wind erosion mitigation on rangelands. ARS researchers convened twenty focus group discussions across three states (New Mexico, Minnesota and Colorado) with animal producers, crop farmers, agricultural professionals, and conservation stakeholders to explore manure redistribution challenges and established the Manureshed Action Network to implement optimal approaches for nutrient recycling (Objective 3). ARS researchers developed a 10-meter spatial resolution vegetation cover product using Landscape Data Commons data, Sentinel-2 satellite imagery, and AI/ML models to enhance the Rangeland Analysis Platform with annual estimates by plant functional group including invasive annual grass and sagebrush cover. Predictive models of forage response to brush management using long-term field monitoring data were developed to provide guidance for optimizing conservation practice effectiveness across millions of acres where significant investments are being made to combat woody plant encroachment (Objective 4).

Accomplishments
1. Tool for monitoring animal behavior in extensive rangelands. Cattle ranching in the western U.S. involves large pastures of several thousand acres. Monitoring of animal behaviors and distress under these circumstances can be challenging, particularly in areas with rugged terrain and limited accessibility. ARS researchers in Las Cruces, New mexico, collaboration with scientists from New Mexico State University used video records of cattle behavior alongside Long Range Wide Area Network (LoRaWAN) tracking and monitoring technology to test the ability of five machine learning classifiers to discriminate walking, grazing and resting behaviors of cattle in real time. Machine and deep learning models were trained and tested. The learning classifiers (logistic regression, support vector machine, multilayer perceptron, XGBoost and random forest algorithms) all correctly differentiated between active versus resting behavior and among three activities (grazing, walking and resting). Results assist producers in detecting behaviors associated with animal health and at critical times such as calving.

2. Developed benchmarking approaches to evaluate wind erosion risk and management outcomes. Wind erosion on rangelands is a critical environmental and human health concern, costing the U.S. over $154 billion annually. Managers urgently need tools for evaluating wind erosion risk and effects of land management. ARS researchers in Las Cruces, New Mexico, collaborated with range and soil conservationists at Natural Resources Conservation Service (NRCS) and Bureau of Land Management (BLM) to develop benchmarking approaches and guidance for managers to use publicly available monitoring datasets and the Aeolian EROsion (AERO) model to make objective and actionable decisions about wind erosion and dust mitigation on rangelands. Extensive testing of the benchmarking approaches through workshops held with BLM across the western U.S. demonstrated utility of the approaches to support data-informed land use and management decision making on rangelands. A Benchmark Exploration Tool, connected to the Landscape Data Commons, was developed to enable managers to access monitoring data and wind erosion predictions, and apply benchmarks to indicators of land health that complement adaptive management approaches.

3. Tested agricultural performance indicators to evaluate management outcomes. Natural resource conditions and economic pressures are highly variable among farms and ranches, making a standardized approach to measuring management outcomes elusive. ARS researchers in Las Cruces, New Mexico, collaborated with five ranchers across the Southwestern U.S. to test a set of performance indicators and a methodology adopted by the Long-Term Agroecosystem Research (LTAR) network to measure outcomes of farming and ranching approaches. On-ranch data on production, natural resource, economic, and social outcomes were collected. Ranchers provided feedback on the structure of the indicator system and learned how their management decisions affect the long-term success of their ranches. Several participants changed practices to reduce input costs as a result of knowledge and information obtained from the indicator system. Vetting by ranchers will improve the utility and impact of the performance indicator system and improve the capacity of USDA to help ranchers and farmers save on input costs.

4. Advanced low-cost technologies to support drought resilience on rangelands. The effects of drought are highly variable in space and time, which is a primary limitation to decision-making in rangelands. Rural producers and land managers want better tools to track vegetation productivity. ARS researchers in Las Cruces, New Mexico, developed and tested two complementary monitoring approaches: PhenoCams—simple, ground-based cameras—and high-resolution satellite imagery. Using over 75 site-years of data across grasslands and shrublands, researchers showed that these tools can detect changes in productivity, capture plant responses to rainfall, and differentiate responses in different land cover types with greater precision than satellite imagery alone. PhenoCams were particularly effective in spotting early signals of change in dry, remote areas where vegetation is patchy and hard to monitor. These innovations can potentially support rural prosperity by helping producers adapt grazing plans, optimize forage use, and respond more effectively to drought stress at both local and landscape scales.

5. Created strategies to meet manure challenges. Manure contains valuable nutrient resources and has been shown to increase soil health, but it is challenging to transport in a timely manner from areas of manure generation to areas that could use it productively. Yet opportunities abound: if crop farmers of just two counties in New Mexico would use manure nutrients in place of fertilizer, they could save $8 million per year on fertilizer. To develop new strategies to transfer manure nutrients, ARS researchers in Las Cruces, New Mexico convened twenty-one focus groups in major manuresheds of three states (New Mexico, Minnesota and Colorado). Researchers gathered data on four groups: livestock producers who have manure, crop farmers who need manure, manure management professionals who move and apply manure, and interested parties from conservation organizations and agencies. Using the methods developed and connections made at workshops, new transactional relationships between livestock producers and crop farmers were created, yielding cost savings for all parties and creating new long-term on-farm research to evaluate return on investment of manure land application.

6. Precision maps for evaluating conservation practice effectiveness at broad scales. Precision information about rangeland condition and trend is critical for producers to implement management strategies at the correct times and locations and to assess outcomes of conservation practices. ARS researchers in Las Cruces, New Mexico, collaborated to develop a 10-m spatial resolution vegetation cover product to enhance the Rangeland Analysis Platform. This model leveraged standardized datasets from the Landscape Data Commons, Sentinel-2 satellite imagery, and machine learning models to produce annual estimates of vegetation cover by functional group. This is a significant improvement over previous models, providing both increased spatial resolution and additional indicators such as invasive annual grass, pinyon-juniper, sagebrush cover, and canopy gaps. These results are being used by agency land managers across the western U.S. to map available forage and develop strategies for responding to threats to U.S. agriculture (e.g., wildfire, wind erosion, invasive species).

7. Decision support for brush management efficiency and effectiveness. Woody plant encroachment reduces livestock production and other services in rangelands across western U.S. Tens of millions of dollars are spent to combat shrub encroachment across millions of acres, but the effectiveness of these treatments is variable in space and time and has been unpredictable. ARS researchers in Las Cruces, New Mexico, used data from a long-term, large-scale field monitoring study to develop a predictive model of forage response to brush management as a function of environmental variables. The model effectively predicts responses and provides guidance to public and private land managers in the Southwest for future brush management decisions and the adaptive management of past investments. The model can optimize forage production and other benefits from this widespread conservation practice.

Review Publications
Andreoni, K.J., Bestelmeyer, B.T., Lightfoot, D., Schooley, R. 2024. Effects of multiple mammalian herbivores and climate on grassland-shrubland transitions in the Chihuahuan Desert. Ecology. 105(12). Article e4460. https://doi.org/10.1002/ecy.4460.
Mozelewski, T.G., Freeman, P.T., Kumar, A.V., Naugle, D.E., Olimpi, E.M., Morford, S.L., Jeffries, M.I., Pilliod, D.S., Littlefield, C.E., McCord, S.E., Wiechmanf, L.A., Doherty, K.E. 2024. Closing the conservation gap in the sagebrush biome: Spatial targeting and exceptional coordination are needed for conservation efforts to keep pace with ecosystem losses. Rangeland Ecology and Management. 97:12-24. https://doi.org/10.1016/j.rama.2024.08.016.
Boggess, L.M., Harrison, G.R., Lendemer, J.C. 2024. Cliffs support lichen communities unique from nearby forests: Cliff lichens. Basic and Applied Ecology. 81:112-120. https://doi.org/10.1016/j.baae.2024.11.003.
McCord, S.E., Brehm, J.R., Condon, L., Dreesmann, L., Ellsworth, L.M., Germino, M.J., Herrick, J.E., Howard, B.K., Kachergis, E., Karl, J.W., Knight, A., Meadors, S., Nafus, A., Newingham, B.A., Olsoy, P.J., Pietrasiak, N., Pilliod, D.S., Schaefer, A., Webb, N.P., Wheeler, B., Williams, C.J., Young, K.E. 2025. Evaluation of the gap intercept method to provide measurements and indicators of rangeland connectivity. Rangeland Ecology and Management. 98:297-315. https://doi.org/10.1016/j.rama.2024.09.001.
Dornelas, M., Antão, L.H., Bates, A.E., Brambilla, V., Chase, J., Bestelmeyer, B.T., James, D.K., Slaughter, A.L. 2025. BioTIME 2.0: Expanding and improving a database of biodiversity time series. Global Ecology and Biogeography. 34(5). Article e70003. https://doi.org/10.1111/geb.70003.
Zhang, P., Edwards, B., Webb, N.P., Trautz, A., Gillies, J., Ziegler, N., Van Zee, J.W. 2024. An evaluation of different approaches for estimating shear velocity in aeolian research studies. Aeolian Research. 70-71. Article 100945. https://doi.org/10.1016/j.aeolia.2024.100945.
Tremino, R., Webb, N.P., Dhital, S., Faist, A., Newingham, B.A., Brungard, C., Dubois, D., Edwards, B., Kachergis, E. 2025. Dust transport pathways from The Great Basin. Journal of Geophysical Research Atmospheres. 72. Article 100958. https://doi.org/10.1016/j.aeolia.2024.100958.
Snapp, S., Chamberlin, J., Marenya, P., Winowiecki, L., Amede, T., Aynekulu, E., Gameda, S., Herrick, J.E., Lal, R., Nagrajan, L., Stewart, Z., Vagen, T. 2024. Realizing soil health for food security in Africa. Nature Sustainability. 8:3-5. https://doi.org/10.1038/s41893-024-01482-9.
Harrison, G.R., Rigge, M., Assal, T.J., Applestein, C., James, D.K., McCord, S.E. 2025. An accuracy assessment of satellite-derived rangeland fractional cover. Ecological Indicators. 172. Article e113267. https://doi.org/10.1016/j.ecolind.2025.113267.
Young, K.E., Bishop, T., Johnson, D.B., Gunnell, K., Faist, A., Garbowski, M., Kildisheva, O., Neumann, D., Gornish, E. 2025. Practitioner tools for addressing knowing–doing gaps in seed-based restoration. Restoration Ecology. 33(4). Article e70043.
Herrick, J.E., Fowler, C., Sibanda, L.M., Lal, R., Nelson, A.M. 2024. The vision for adapted crops and soils: How to prioritize investments to achieve sustainable nutrition for all. Nature Plants. 10:1840-1846. https://doi.org/10.1038/s41477-024-01867-w.
Rigge, M., Bunde, B., McCord, S.E., Harrison, G.R., Assal, T.J., Smith, J.L. 2025. Spatial scale dependence of error in fractional component cover maps. Rangeland Ecology and Management. 99:77-87. https://doi.org/10.1016/j.rama.2025.01.004.
McCord, S.E., Webb, N.P., Van Zee, J.W., Courtright, E.M., Duniway, M.C., Edwards, B., Kachergis, E., Moriasi, D.N., Morra, B., Nafus, A., Newingham, B.A., Scott, D.A., Toledo, D.N. 2025. Optimizing sampling across transect-based methods improves the power of agroecological monitoring data. Journal of Environmental Quality. 54(3):706-719. https://doi.org/10.1002/jeq2.20678.
Peng, Y., Ben-Dor, E., Biswas, A., Chabrillat, S., Dematt, J., Ge, Y., Gholizadeh, A., Gomez, C., Guerrero, C., Herrick, J.E., Maynard, J.J., Mounem Mouazen, A., Ma, Y., McBratney, A., Minasny, B., Ramirez-Lopez, L., Robertson, A., Viscarra Rossel, R.A., Shi, Z., Stenberg, B., C. Wadoux, A.M., Winowiecki, L.A., Zhang, G. 2025. Spectroscopic solutions for generating new global soil data and information efficiently. Material Research Innovations. 6(5). Article e100839. https://doi.org/10.1016/j.xinn.2025.100839.
Herrick, J.E., Bestelmeyer, B.T., Hoover, D.L., Toledo, D.N., Webb, N.P. 2025. A proposal for simplifying and increasing the value of local to global land degradation monitoring. Drylands. 2(e8):1-7. https://doi.org/10.1017/dry.2025.4.
Webb, N.P., Wheeler, B., Edwards, B.L., Schallner, J.W., Macanowicz, N., Van Zee, J.W., Courtright, E.M., Cooper, B., McCord, S.E., Browning, D.M., Dhital, S., Young, K.E., Bestelmeyer, B.T. 2025. Magnitude shifts in aeolian sediment transport associated with degradation and restoration thresholds in drylands. Journal of Geophysical Research-Biogeosciences. 130(3). Article e2024JG008581. https://doi.org/10.1029/2024JG008581.
Sundstrom, S., Awada, T., Bennett, E.M., Bestelmeyer, B.T., Hodbod, J., Pacheco, A., Spiegal, S.A., Allen, C. 2025. Addressing key Issues and knowledge gaps in resilience science for agriculture. Agricultural Systems. 227. Article e104335. https://doi.org/10.1016/j.agsy.2025.104335.
Spetter, M.J., Utsumi, S.A., Armstrong, E.M., Rodriguez-Almeida, F.A., Ross, P.J., Macon, L.K., Jara, E., Cox, A., Perea, A.R., Funk, M., Redd, M., Cibils, A.F., Spiegal, S.A., Estell, R.E. 2025. Genetic diversity, admixture, and selection signatures in a Rarámuri Criollo cattle population introduced to the Southwestern United States. International Journal of Molecular Sciences. 26(10). Article 4649. https://doi.org/10.3390/ijms26104649.
Pi, H., Wang, C., Li, S., Li, S., Webb, N.P. 2025. Crushing energy-based indicators of dry soil aggregate stability from contrastive land management practices in a semi-arid agroecosystem. Ecological Engineering. 217. Article 107663. https://doi.org/10.1016/j.ecoleng.2025.107663.
Wagnon, C., Bestelmeyer, B.T., Schooley, R. 2024. Dryland state transitions alter trophic interactions in a predator-prey system. Journal of Animal Ecology. 93(12):1881-1895. https://doi.org/10.1111/1365-2656.14197.
Root-Bernstein, M., Addo-Danso, S., Bestelmeyer, B.T. 2024. A perspective on restoring with foundation plants across anthropogenic dry forests of the Southern Cone and the Sahel. Frontiers in Ecology and Evolution. 12. https://doi.org/10.3389/fevo.2024.1176747
Schaeffer, K., Bestelmeyer, B.T., Burkett, L.M., McLaren, J. 2025. The potential for using soil carbon, soil texture, and elevation as indicators of grass-cover response in Chihuahuan Desert grassland restoration practices. Journal of Arid Environments. 227. Article 105326. https://doi.org/10.1016/j.jaridenv.2025.105326.
Delpierre, N., Garnier, S., Treuil-Dussouet, H., Hufkens, K., Berveiller, D., Lin, J., Morfin, A., Wilkinson, M., Noormets, A., Klosterhalfen, A., Domec, J., Cuntz, M., Joetzjer, E., Munger, J., Richardson, A.D., Hart, K.M., Denham, S.O., Desai, A.R., Soudani, K. 2024. Phenology across scales: An intercontinental analysis of budburst in temperate deciduous tree communities. Global Ecology and Biogeography. 33(12). Article e13910. https://doi.org/10.1111/geb.13910.
Harrison, G.R., Jones, L.C., Ellsworth, L.M., Strand, E.K., Prather, T.S. 2024. Cheatgrass alters flammability of native perennial grasses in laboratory combustion experiments. Fire Ecology. 20. Article 103. https://doi.org/10.1186/s42408-024-00338-z.
Romig, K.B., James, D.K., Maxwell, C., Bestelmeyer, B.T., Brown, J., Salley, S., Faist, A. 2025. Hidden biodiversity: Dryland soil seed banks across ecological sites and states. Restoration Ecology. 227. Article 105307. https://doi.org/10.1016/j.jaridenv.2024.105307.
Castano-Sanchez, J.P., Rotz, C.A., Steiner, J., Golden, B., Spiegal, S.A. 2025. Farmer driven water conservation policy on the Ogallala aquifer reduces the environmental footprints of crop production. Agricultural Water Management. 310. Article 109370. https://doi.org/10.1016/j.agwat.2025.109370.
Flynn, K.C., Erb, K., Meinen, R.J., Krecker-Yost, J.L., Inaoka, M., Spiegal, S.A. 2025. Manure handling certification programs in manuresheds across the United States. Cleaner Waste Systems. 10. Article 100241. https://doi.org/10.1016/j.clwas.2025.100241.
Duniway, M.C., Knight, A., Nauman, T., Bishop, T.B., McCord, S.E., Webb, N.P., Williams, C.J., Humphries, J.T. 2025. Quantifying regional ecological dynamics using agency monitoring data, ecological site descriptions, and ecological site groups. Rangeland Ecology and Management. 99:119-142. https://doi.org/10.1016/j.rama.2024.12.006.
Spiegal, S.A., Estell, R.E., Cibils, A.F., Cox, A., McIntosh, M.M., Browning, D.M., Duniway, M., Funk, M., Macon, L.K., McCord, S.E., Redd, M., Tolle, C., Utsumi, S., Walker, J., Webb, N.P., Bestelmeyer, B.T. 2024. The LTAR Grazing Land Common Experiment at the Jornada Experimental Range: Old genetics, new precision technologies, and adaptive value chains. Journal of Environmental Quality. 53(6):880-892. https://doi.org/10.1002/jeq2.20605.
Harrison, G.R., Boggess, L.M., McCord, S.E., March-Salas, M. 2024. A call to action for inventory and monitoring of cliff ecosystems to support conservation. Basic and Applied Ecology. 80:31-39. https://doi.org/10.1016/j.baae.2024.07.006.
Mangum, A., Carling, G., Bickmore, B., Webb, N.P., Leifi, D., Brahney, J., Fernandez, D., Rey, K., Nelson, S., Burgener, L., Lemonte, J., Thompson, A., Newingham, B.A., Duniway, M.C., Aanderud, Z. 2024. Characterizing variability in geochemistry and mineralogy of western US dust sources. Aeolian Research. 70-71. Article 100941. https://doi.org/10.1016/j.aeolia.2024.100941.
Perea, A.R., Rahman, S., Chen, H., Cox, A., Nyamuryekung'E, S., Bakir, M., Cao, H., Estell, R.E., Bestelmeyer, B.T., Cibils, A.F., Utsumi, S.A. 2025. Integrating LoRaWAN sensor network and machine learning models to classify beef cattle behavior on arid rangelands of the southwestern United State. Smart Agricultural Technology. 11. Article 101002. https://doi.org/10.1016/j.atech.2025.101002.
Tsegaye, T., Marlen, E., Hapeman, C.J., Kleinman, P.J., Baffaut, C., Browning, D.M., Coffin, A.W., Spiegal, S.A. 2024. The Long-Term Agroecosystem Research Network: Cross-site transdisciplinary science to support a sustainable and resilient agriculture. Journal of Environmental Quality. 53(6):777-786. https://doi.org/10.1002/jeq2.20649.
Hague, M., Ansari, A.H., Veith, T.L., White, M.J., Costello, C., Spiegal, S.A., Kleinman, P.J., Arnold, J.G., Cibin, R. 2025. Reducing national water degradation: Development and application of a manureshed-identification framework. Agricultural Systems. 227. Article 104349. https://doi.org/10.1016/j.agsy.2025.104349.
Young, K.E., Edwards, B., Duniway, M., Webb, N.P. 2025. Optimizing the effectiveness of connectivity modifiers to reduce dryland degradation. Restoration Ecology. Article e70055.
Allred, B.W., McCord, S.E., Morford, S.L. 2025. Canopy height model and NAIP imagery pairs across CONUS. Scientific Data. 12. Article 322. https://doi.org/10.1038/s41597-025-04655-z.
Roy, K., Brill, E., Mikros, D., Tobin, K., Juzwik, J., Mcnellis, B.E., Jacobs, D., Keith, L.M., Cha, D.H., Ginzel, M. 2025. The in vitro and in vivo fungal volatile organic compounds associated with rapid 'Ohi'a death and the response of Xyleborine ambrosia beetles to those compounds. Journal of Chemical Ecology. 51. Article 59. https://doi.org/10.1007/s10886-025-01606-1.
Donovan, M.E., Spiegal, S.A., Kaplan, N.E., Archer, D.W., Bean, A., Beebout, S.E., Bestelmeyer, B.T., Clark, P., DeLong, A., Fortuna, A., Friedrichsen, C.N., Hoover, D.L., Huggins, D.R., Kleinman, P.J., McIntosh, M.M., Renschler, C.S., Ritten, J., Smith, D.R., Webb, N.P., Wulfhorst, J.D. 2025. Selecting performance indicators for farms and ranches engaged in collaborative agroecosystem research. Journal of Environmental Quality. Article 70051. https://doi.org/10.1002/jeq2.70051.
Feng, I., Tong, D.Q., Gill, T.E., Van Pelt, R.S., Webb, N.P. 2025. The economic costs of wind erosion in the United States. Nature Sustainability. 8:307-314. https://doi.org/10.3390/agriengineering6040254.
Lisonbee, J., Parker, B., Fleishman, E., Ford, T., Bocinsky, K., Follinstad, G., Frazier, A., Hoylman, Z.H., Hudson, A.R., Nielsen-Gammon, J., Umphlett, N., Wickham, E., Bamzai-Dodson, A., Fontenot, R., Fuchs, B., Hammond, J., Herrick, J.E., Hobbins, M., Hoell, A., Jones, J., Lane, E., Leasor, Z., Liu, Y., Otkin, J., Sheffield, A., Todey, D.P., Pulwarty, R. 2025. Prioritization of research on drought assessment in a changing climate. Earth's Future. 13(3). Article e2024EF005276. https://doi.org/10.1029/2024EF005276.
Phillips, M., Young, K.E., Lauria, C., Jech, S., Giraldo-Silva, A., Reed, S. 2025. Navigating the possibilities and pitfalls of biocrust recovery under a changing climate. American Journal of Botany. 112(6). Article e70055. https://doi.org/10.1002/ajb2.70055.
Campa-Madrid, S.E., Perea, A.R., Funk, M., Spetter, M.J., Bakir, M., Walker, J., Estell, R.E., Soto-Navarro, S.A., Spiegal, S.A., Bestelmeyer, B.T., Utsumi, S.A. 2025. Training Raramuri Criollo cattle to virtual fencing in chaparral rangeland. Animals. 15(15):2178. https://doi.org/10.3390/ani15152178.
Hajek, O.L., Kaplan, N.E., Azad, S., Fay, P.A., Khorchani, M., Nelson, A.M., Schreiner-McGraw, A.P., Abendroth, L.J., Baffaut, C., Baker, J.M., Bestelmeyer, B.T., Boughton, E.H., Browning, D.M., Carlson, B.R., Cavigelli, M.A., Clark, P., Dell, C.J., Guo, Y., Hendrickson, J.R., Huggins, D.R., Hussain, M., King, K.W., Kovar, J.L., Liebig, M.A., Locke, M.A., Schmer, M.R., Silveira, M., Smith, D.R., Snyder, K.A., Starks, P., White, K.E., Wilke, B., Hoover, D.L. 2025. Variation in patterns of production and water-use efficiency among agroecosystems. Science of the Total Environment. 995. Article e180115. https://doi.org/10.1016/j.scitotenv.2025.180115.
Denham, S.O., Browning, D.M., Schreiner-McGraw, A.P., Scott, R.L., Dalzell, B.J., Flerchinger, G.N., Clark, P., Goslee, S.C., Hoover, D.L., Litvak, M., Maritz, M., Huggins, D.R., Phillips, C.L., Prueger, J.H., Alfieri, J.G., Bracho, R., Silveira, M., Whippo, C.W. 2025. Utility of near-surface phenology in estimating productivity and evapotranspiration across diverse ecosystems. Journal of Environmental Quality. Article e70043. https://doi.org/10.1002/jeq2.70043.
Liebig, M.A., Abendroth, L.J., Robertson, G., Augustine, D.J., Boughton, E.H., Bagley, G.A., Busch, D.L., Clark, P., Coffin, A.W., Dalzell, B.J., Dell, C.J., Fortuna, A., Freidenreich, A.S., Heilman, P., Helseth, C.M., Huggins, D.R., Johnson, J.M., Khorchani, M., King, K.W., Kovar, J.L., Locke, M.A., Mirsky, S.B., Schantz, M.C., Schmer, M.R., Silveira, M.L., Smith, D.R., Soder, K.J., Spiegal, S.A., Stinner, J.H., Toledo, D.N., Williams, M.R., Krecker-Yost, J.L. 2024. The LTAR Common Experiment: Facilitating improved agricultural sustainability through coordinated cross-site research. Journal of Environmental Quality. 53(6):787-801. https://doi.org/10.1002/jeq2.20636.