Skip to main content
ARS Home » Plains Area » Las Cruces, New Mexico » Range Management Research » Research » Research Project #435564

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

Location: Range Management Research

Project Number: 3050-11210-009-000-D
Project Type: In-House Appropriated

Start Date: Sep 28, 2018
End Date: Sep 27, 2023

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.