Project : USDA ARS

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Research Project: Disturbance Mitigation and Adaptive Restoration of Sagebrush-Steppe Ecosystems

Location: Northwest Watershed Research Center

2025 Annual Report

Objectives
Objective 1: Conduct long-term, big-data oriented, network scale research (e.g., LTAR, NWERN, PhenoCam, and SCINet) and data synthesis to innovate applications and solutions for adaptive land and watershed management. Sub-objective 1A: Develop and evaluate unoccupied aerial systems (UAS) remote sensing and other big data methods, analysis procedures, and applications for solving rangeland resource management problems. Sub-objective 1B: Develop databases and web-tools to extract and optimize North American Multi-Model Ensemble (NMME) historical seasonal forecasts for multi-site and regional forecasting applications across the LTAR site network. Sub-objective 1C: Evaluate Great Basin community and individual human dimension responses to cheatgrass, wildfire, and other challenges through expansion of spatially explicit formats integrated between ecological landscape layers with primary sociological data pertinent to management decision-making, perceived risk of annual grass invasion scales, and ranch-scale adaptation capacity behaviors. Sub-objective 1D: Continue to collaborate in LTAR and other network cross-site research projects contributing leadership, expertise, and data to address the regional and national scale problems concerning environmental health, agricultural productivity, and human dimensions of U.S. agroecosystems. Objective 2: Develop methods and tools to facilitate successful restoration outcomes in sagebrush-steppe ecosystems in the Great Basin. Sub-objective 2A: Assess the efficacy of prescriptive cattle grazing for restoring degraded sagebrush-steppe rangelands currently dominated by invasive annual grasses. Sub-objective 2B: Utilize seedlot and seedbed models to identify restoration opportunities in the highly variable and changing weather environment of the Intermountain western U.S. Objective 3: Assess weather and climate impacts on soil health, seedling establishment and rangeland productivity given the complex soil, vegetation, and topography typical of the western U.S. Sub-objective 3A: Utilize the Bureau of Land Management Land Treatment Digital Library (LTDL) and gridMET historical climate database to characterize what type of weather year is required to yield a positive restoration outcome after wildfire. Sub-objective 3B: Determine whether seasonal climate forecasting has sufficient skill for predictions of positive and negative restoration outcomes for post-fire seeding projects in the Great Basin.

Approach
Goal 1A: Develop UAS remote sensing for monitoring rangeland fuel load, height, and continuity. We will use a combination ongoing field data and UAS imagery collections (initiated in 2015) to develop tools and workflows for characterizing fuels in 3 vegetations types which dominate much of the Great Basin region. Hypoth. 1B: The North American Multi-Model Ensemble (NMME) can be used to develop forecasting applications across a wide sector of U.S. agricultural. We will conduct hindcast assessments of all current NMME models for the period 1982-2022. Hindcast skill will be evaluated by comparing predictions to a gridded historical weather database, gridMET spanning the contiguous U.S. Goal 1C: Develop a socio-ecological adaptation capacity index for the northern Great Basin region. About 50-60 interviews will be collected from rural communities of the region. Focus Groups will conduct participatory analyses of adaptation drivers and challenges identified from the interviews, and then weight these factors across geographic/social contexts to develop an applicable index. Goal 1D: Develop long-term vegetation datasets in support of the LTAR network. We will continue ongoing collections (begun in 2015) of foliar cover, biomass, species richness/abundance, and other vegetation field data as well as phenology camera imagery along an elevational and precipitation gradient with the Great Basin LTAR site. Hypoth. 2A: High Intensity Low Frequency (HILF) beef cattle grazing will more effectively promote restoration of cheatgrass-invaded rangelands than lower intensity, BLM-permitted cattle grazing. We will continue analysis and publication of vegetation response data from the previous 9 years of this experiment. This experiment will then be replicated at a new study area. Hypoth. 2B: Seedbed microclimatic indices are correlated with native species distributions and the persistence and spread of invasive species over space. Time-series estimates of seedbed temperature and water potential will be developed for multiple plant materials, locations and temporal scenarios at selected field sites in the western U.S. using the Simultaneous Heat and Water (SHAW) model. Hypoth. 3A: Postfire seedling establishment success is correlated with winter/spring precipitation and winter temperature conditions in the year after planting. We will screen the USGS Land Treatment Digital Library (LTDL) records of post-fire rehabilitation treatments in the Great Basin to identify those with sufficient post-treatment data to indicate the level of both seed-mix and individual seedlot success in the first one to three years after seeding. We will then identify seedbed-microclimatic profiles that are correlated with relative seeding success or non-success at all selected LTDL field sites. Hypoth. 3B: Postfire seeding success in the Great Basin can be predicted using climate forecasts and historical weather and restoration data. We will identify and optimize seasonal forecasting models for all sites from Sub-objective 3A parametric/nonparametric analyses will be used to determine whether climate metrics identified in Sub-objective 3A are associated with establishment success.

Progress Report
This report documents FY 2025 progress for project 2052-21500-001-000D, “Disturbance Mitigation and Adaptive Restoration of Sagebrush-Steppe Ecosystems”, which began in February 2024. In support of Objective 1, ARS researchers in Boise, Idaho, used unoccupied aircraft systems (UAS) to collect remote sensing imagery in the 15 long-term vegetation research sites at the Reynolds Creek Experimental Watershed (RCEW) for modeling and evaluating herbaceous fuel height and load estimates. To further the scope of this UAS fuel assessment research, three additional sites were established, one in the RCEW (Flats) and two on Idaho Department of Fish and Game lands (Adelmann and Cornell). Python scripts were developed and refined to geotag these UAS imagery. Field data for herbaceous fuel height were collected at each of above sites to ground-truth the UAS-derived fuel height estimates. The Scientific Computing Initiative Network’s (SCINet) graphics processing and storage resources (Atlas and Juno, respectively) were used to process and analyze UAS imagery for fuel height. Two manuscripts were published on estimating rangeland total leaf area and fractional cover using UAS imagery. A manuscript was submitted on accessing rangeland biomass (fuel load) using remote sensing. A fire severity map of the Johnston Draw Prescribed Fire (2023), using a support vector machine analysis approach, was published to Ag Data Commons. The map has received 289 public downloads since it was posted on February 6, 2025. The ARS researchers worked with ARS Office of Communications to create two public-facing videos describing research on the use of prescribed fire for western juniper control. An ARS researcher concluded seven years of service representing the Pacific West Area on the SCINet Science Advisory Committee. A hindcast assessment of precipitation and air temperature estimates from the North American Multi-Model Ensemble (NMME) was completed for 1,812 points (every 0.67 degrees of latitude/longitude) within the contiguous 48 states. Three research papers were published on plant production forecasting. A postdoctoral researcher was hired to conduct qualitative fieldwork and analysis in support of Sub-objective 1C. ARS researchers in Boise, Idaho, in collaboration with researchers from the University of Idaho, met with agency representatives, social and rangeland scientists, and producers to refine research questions for Sub-objective 1C. The postdoctoral researcher then collected qualitative data from producers via in-person interviews focused on producer perceptions and adaptative behaviors regarding invasive annual grasses. A research manuscript reporting the analysis of these producer perceptions is in progress. Another paper on structural challenges associated with annual grass invasions is also under development. Phenology cameras (PhenoCams) located at Nancy Gulch, Lower Sheep Creek, and Reynolds Mountain sites within the RCEW were enhanced and maintained. All three automated cameras successfully contributed imagery to the nation-wide PhenoCam and Long-Term Agroecosystem Research (LTAR) networks. Field data for the RCEW Long-Term Vegetation Research (LTVR) program and the Great Basin LTAR site were collected at one-fifth of nominal level due to technical staff shortage. Alternately, multispectral UAS imagery were collected at sites where the LTVR field sampling could not be conducted. These imagery are intended to be used to develop surrogate measurements as alternatives to the missing field data. Under Objective 2, ARS researchers in Boise, Idaho, continued analysis of existing nine-year dataset contrasting prevalent and alternative livestock grazing strategies as part of the LTAR network’s Common Experiment at the Great Basin site. The LTAR Common Experiment at the Great Basin site was expanded to also include prescribed fire research for woody fuels management (e.g., Johnston Draw Prescribed Fire mentioned above). The long-term modeling study of previous seeding treatments at 15 field sites in northern Nevada, southern Idaho, and southeastern Oregon, was also completed. A manuscript was submitted assessing spatial variability in ecological resistance and resilience and expected seeding response across field patterns of soil and topography in a 50K acre, large-scale post-fire restoration scenario. For Objective 3, ARS researchers in Boise, Idaho, investigated the correlation of restoration seeding success metrics with seasonal patterns of temperature and precipitation. A research paper was submitted describing a model for correlating various levels of seeding success with specific climate-patterns, seeding date, and plant materials. Further work on this objective was curtailed due to the retirement of senior project staff.

Accomplishments
1. Remote sensing of wildfire fuel accumulations. The behavior, severity, and extent of wildfires which threaten rangeland and wildland-urban interface throughout the western United States are largely controlled by the type, continuity, and load of fuels on those landscapes. Yet, fuel managers and wildland firefighters often lack efficient and effective tools to stay abreast of rapidly changing fuel conditions across the extensive and complex landscapes that typify the West. ARS researchers in Boise, Idaho, in collaboration with students and colleagues at Boise State University, developed remote sensing tools and protocols for using unoccupied aircraft systems (UAS) to assess and map plant fractional cover, greenness, and leaf area index and thus classify and measure fuel type, continuity, and load for sagebrush steppe rangeland. These readily available and relatively inexpensive tools can greatly reduce the $2.4 billion mean annual cost of wildfire suppression to the federal government, have applicability to 175 million acres of the western United States, and provide fuels managers and firefighters with an efficient means to directly characterize fuel accumulations at local scales or ground-truth satellite-based fuels products at broader scales.

2. Developing tools for western juniper control with prescribed fire. Encroachment by western juniper, a native but invasive tree species, reduces rangeland livestock forages, degrades wildlife habitat, increases runoff and soil erosion, and amplifies water loss on rangelands of the northern Great Basin and Pacific Northwest. Prescribed fire is often used to control junipers, but this management practice is hampered by a critical lack of planning and assessment tools. ARS researchers in Boise, Idaho, in collaboration with local ranchers, the Bureau of Land Management, and researchers from Boise State University and the University of Texas, El Paso, developed satellite remote-sensing tools and datasets for quantifying and mapping pre-fire fuel conditions and prescribed fire efficacy and impact. Pre-fire fuel types were mapped to 50-cm resolution with 83% accuracy, generally outperforming existing products, including the Landfire Existing Vegetation Type dataset while burned area and fire severity were mapped to 72.8% and 88.3% accuracy, respectively. These remote sensing tools enable land managers, fuels specialists, and fire fighters timely and spatially relevant planning and assessment for prescribed fire applications within the western juniper zone (46 million acres) with likely extension to the pinyon-juniper zone (100 million acres).

3. Preferred nectar sources for the monarch butterfly decrease in abundance but are diverse along autumn southern migration through the Great Plains. During the autumn monarch migration through the southern United States, monarchs actively seek quality nectar to build up lipid reserves for over-wintering in Mexico. The U.S. Fish and Wildlife Service determined that the availability, quality, and spatial distribution of nectar plants during fall migration is a critical factor in monarch population declines in North America. Natural Resources Conservation Service (NRCS; Fort Worth, Texas) and ARS scientists (Boise, Idaho; Tucson, Arizona) utilized vegetation data from more than 8,000 study sites to quantify and assess the density, richness, and diversity of monarch butterfly preferred nectar sources. They also studied the associated ecosystem attributes and functioning along the autumn migration pathway through the Great Plains Region in the United States. The data were acquired from the NRCS's rangeland National Resource Inventory and analyzed by NRCS and ARS scientists from Boise, Idaho. The resultant study found that preferred nectar sources for monarchs decrease in abundance from north to south along the autumn migration through the Great Plains Region, but that nectar sources at southern latitudes along this pathway remain diverse. Results indicate this nectar diversity may maintain components of key habitat in the wake of ongoing land use intensification. The study presents the most extensive quantification to date of preferred nectar sources for monarch butterflies along the Great Plains autumn migratory pathway and provides farmers, ranchers, and other producers and land managers vital information to aid voluntary conservation efforts of the monarch butterfly in North America.

4. Predicting forage biomass on cheatgrass-invaded sagebrush rangelands. Cheatgrass is a broadly occurring invasive grass that substantively alters vegetation production on sagebrush rangelands in the western United States. Land managers and producers require tools to forecast the effects of cheatgrass invasions on forage quantity and quality and to target effective land use and management on cheatgrass-invaded sites. A collaborative group of ARS scientists (Temple, Texas; Boise, Idaho; Reno, Nevada; Tucson, Arizona; Burns, Oregon) evaluated the capability of the ALMANAC (Agricultural Land Management Alternatives with Numerical Assessment Criteria) model to predict biomass of key forage components in plant communities typical of sagebrush rangelands, including those with substantive cheatgrass. The model effectively predicted cheatgrass and perennial grass biomass for select communities, indicating its potential application to inform management on cheatgrass-invaded rangelands. The model was less effective at predicting sagebrush and forb biomass. Results from the study provide land managers and producers insight into the best applications and potential limitations of ALMANAC in forecasting grass biomass and prescribing foraging strategies on cheatgrass-invaded rangeland sites.

U.S. DEPARTMENT OF AGRICULTURE

Northwest Watershed Research Center: Boise, ID