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USGS2023

Biocrusts indicators of livestock grazing effects on soil stability in sagebrush steppe: A case study from a long-term experiment in the northern Great Basin

Biocrusts are sensitive to changes in livestock grazing intensity in arid rangelands and may be useful indicators of ecosystem functions, particularly soil properties like soil stability, which may suggest the potential for soil erosion. We compared biocrust community composition and surface soil stability in a big sagebrush (Artemisia tridentata) steppe rangeland in the northwestern Great Basin in several paired sites, with or without long-term cattle grazing exclusion, and similar soils (mostly sandy loams), climate, and vegetation composition. We found that livestock grazing was associated with both lower surface soil stability and cover of several biocrust morphogroups, especially lichens, compared with sites with long-term livestock exclusion. Surface soil stability did not modify the effects of grazing on most biocrust components via interactive effects. Livestock grazing effects on total biocrust cover were partially mediated by changes in surface soil stability. Though lichens were more sensitive to grazing disturbance, our results suggest that moss (mostly Tortula ruralis in this site) might be a more readily observable indicator of grazing-related soil stability change in this area due to their relatively higher abundance compared with lichens (moss: mean, 8.5% cover, maximum, 96.1%, lichens: mean, 1.0% cover, maximum, 14.1%). These results highlight the potential for biocrust components as sensitive indicators of change in soil-related ecosystem functions in sagebrush steppe rangelands. However, further research is needed to identify relevant indicator groups across the wide range of biocrust community composition associated with site environmental characteristics, variable grazing systems, other rangeland health metrics, and other disturbance types such as wildfire.

Northern Great Basin↗

USGS2024

Cooperative conservation actions improve sage-grouse population performance within the Bi-State Distinct Population Segment

Developing a robust monitoring framework that integrates efficacy assessments of cooperative conservation and restoration actions in relation to population viability is critical for successful long-term recovery of target ecosystems and species. However, often it is difficult to quantify conservation action efficacy because of the complex, dynamic nature of ecosystem processes and practical limitations associated with assessing target species’ population dynamics. Here, we present an analytical framework that allows for quantification of conservation action efficacy using greater sage-grouse ( Centrocercus urophasianus ; hereafter, sage-grouse) within the Bi-State Distinct Population Segment which borders Nevada and California. This framework utilizes web-based repositories of conservation efforts carried out in sagebrush ecosystems and readily fits within contemporary sagebrush conservation design strategies. We employed a state-space model within a Bayesian framework to estimate abundance (N) as inputs for a progressive change before-after-control-impact paired series (BACIPS) design. Count data from 57 leks (monitored between 2003–2021) coupled with 85 unique actions (initiated between 2012–2019) provided clear evidence that conservation actions increased population abundance, on average, by 4.4% annually across the study area, resulting in a 37.4% cumulative increase since 2012. Population gains varied by the type of conservation action and according to the number of lag years following its implementation.

California, Nevada↗

USGS2025

Spatial scale dependence of error in fractional component cover maps

Geospatial products such as fractional vegetation cover maps often report overall, pixel-wise accuracy, but decision-making with these products often occurs at coarser scales. As such, data users often desire guidance on the appropriate spatial scale to apply these data. We worked toward establishing this guidance by assessing RCMAP (Rangeland Condition Monitoring Assessment and Projection) accuracy relative to a series of high-resolution predictions of component cover. We scale the 2-m and RCMAP predictions to various focal window sizes scales ranging from 30 to 1 500 m using focal averaging. We also evaluated variation in scaling effects on error at ecoregion and pasture (mean area of 1 050 ha) scales. Our results demonstrate increased accuracy at broader windows, across all components, and most increases in accuracy level off at ∼200–600 m scales. At the scale with highest accuracy, cross-component average correlation ( r ) increased by 6.5%, and root mean square error (RMSE) was reduced 46.4% relative to 30-m scale data. Scaling-related improvements to accuracy were greatest in components such as shrub and tree with more spatially heterogeneous cover and in ecoregions with more spatially heterogenous cover. When components were aggregated at the pasture scale, r increased 10% and RMSE decreased 34.3% on average relative to the 30-m scale. Our results provide empirical data on the scale dependence of error, which fractional cover data users may consider alongside their needs when using these data. Although the general principle remains that remotely sensed products are intended to address landscape-scale questions, our analysis indicates that applying data at finer than landscape spatial scales and grouping even a handful of pixels resulted in lowered error compared to pixel-level comparisons. Our results quantify the trade-offs between data granularity and error related to scale for fractional vegetation cover.

western United States↗

USGS2025

Correspondence between satellite-derived and long-term field observations of vegetation cover at Great Basin experimental treatments.

Vegetation treatments are frequently utilized in Western US rangelands to reduce woody plant cover in sagebrush stands threatened by increased wildfire risk and in pinyon-juniper woodlands expanding into formerly high-value sagebrush habitats. Despite widespread use of these treatments, monitoring data to evaluate long-term vegetation responses are often insufficient or absent. Long-term field experiments and remote-sensing based vegetation data may be complementary for assessing treatment effectiveness across temporal and spatial scales. The SageSTEP project experimentally implemented treatments at numerous sites across the Intermountain West and monitored the subsequent response of vegetation cover components with 15+ yr of field observations. However, while pretreatment data were collected in the year of implementation, long-term observations of pretreatment vegetation conditions are lacking in the SageSTEP database. Remote-sensing based time-series maps (1985–2023) of vegetation cover from Rangeland Condition Monitoring Assessment and Projection (RCMAP) could fill temporal gaps in monitoring data and scale findings across broader extents. We evaluate the relationship between pretreatment vegetation cover in the RCMAP data and the post-treatment response in both the RCMAP and field observations. Additionally, we explore the correspondence between SageSTEP field observations and RCMAP at various scales, and examine key factors related to the strength of relationships. Overall, SageSTEP and RCMAP data show a similar direction of treatment effect for each component, and to a lesser extent the magnitude of effect. SageSTEP and RCMAP data tended to agree most strongly where treatment effects were strong; when averaged across broader spatial scales; and for components such as tree and bare ground that are more easily distinguished spectrally. Remote sensing tools such as RCMAP, in combination with field-based climate and vegetation observations, can help assess postdisturbance recovery trajectories and facilitate regional decision-making around treatment alternatives, fire risk reduction, and protection of critical habitats.

Great Basin↗

USGS2026

Long-term effects of rangeland improvements on cattle distribution: A ranch-scale case study

Resource matching can be a common assumption that underlies anthropogenic rangeland improvements for wildlife or livestock. Countless resources are spent on targeted vegetation manipulations for both livestock and wildlife, but selection for improved areas has not been well quantified in livestock. This case study investigates whether cattle exhibit preferential use of historically improved rangeland sites within sagebrush steppe ecosystems, and whether these effects are relevant long-term compared with inherent landscape heterogeneity. We used a generalized linear mixed-effects resource selection function on Global Positioning System points collected at a fix rate of 2 h from a subset of animals grazing throughout 14 pastures (totaling 13 079 ha) over 3 yr to investigate cattle distribution in relation to historical rangeland improvements. These consisted of various methods for reducing woody plant cover and increasing forage production, most followed by grass and legume reseeding. Overall selection for treated areas was positive (0.16, P < 0.0 0 01), but highly variable (pasture estimates range from-1.81 to 0.77). Differences in enhanced vegetation index (EVI) accounted for 25% of the variation in treatment selection, whereas herbaceous production did not have an appreciable effect on treatment selection. Within individual pastures, the effects of landscape variables (distance to water, slope, herbaceous production, EVI, tree cover, and shrub cover) were more variable than treatment effects and on average 2.4-fold more influential to selection than anthropogenic treatments. Still, the combined effects of all landscape variables accounted for only 8% of the variation in site selection. The observed inconsistency among selection patterns underscores the complexity of large herbivore resource selection behavior, and the statistical challenges to modeling that behavior. These results provide limited and inconsistent support for the hypothesis that large herbivores select long-term (5–20 yr post establishment) for range improvements in relation to their forage quality/quantity in a resource-matching manner.

Utah↗

USGS2026

Habitat restoration efforts increase patch retention times in migratory mule deer (Odocoileus hemionus)

Mule deer ( Odocoileus hemionus ) populations have been declining across much of their range, often due to habitat alteration. Habitat alterations, including the introduction of non-native annual grasses and the expansion of pinyon–juniper (PJ) forests on sagebrush ecosystems, are changing resource availability compared to historical conditions. Extensive habitat restoration has been completed across the State of Utah to foster plant communities that better reflect historical conditions and optimal mule deer habitat. We investigated how patch retention times differ on eight different habitat restoration treatment types and random locations during summer and winter across the State of Utah, to evaluate the efficacy of restoration treatments for migratory mule deer, as retention time is expected to reflect resource availability. We developed seasonal moving-window Brownian Bridge Movement Models for individual mule deer ( n = 593 animals), and intersected occurrence distributions (OD) with habitat restoration treatments and randomly generated background landscape polygons. We quantified patch retention time as the number of days individuals’ OD overlapped treatment or random polygons during each season, using a Poisson regression. In winter sites treated to remove PJ, both with (56.5 days, 95% CI [29.3, 108.0]) and without seeding (55.3 days, 95% CI [29.1, 105.8]), as well as sagebrush restoration sites (59.0 days, 95% CI [30.6, 114.8]), had increased retention times when compared to the landscape average (41.9 days, 95% CI [20.7, 84.1]), with effects decreasing 5+ years post-treatment. Retention times in summer were longer across all treatment types in the 2–4-year post-treatment age class (37.5 days, 95% CI [26.3, 53.1]) compared to the landscape average (28.6 days, 95% CI [25.7, 31.8]). Our results demonstrate the positive effects of habitat restoration through increased patch retention times on mule deer winter and summer range and may suggest follow-up treatment 5+ years after initial treatment to maximize mule deer use.

Utah↗

USGS2024

Resilience is not enough: Toward a more meaningful rangeland adaptation science

Rangeland ecosystems, and their managers, face the growing urgency of climate change impacts. Researchers are therefore seeking integrative social-ecological frameworks that can enhance adaptation by managers to these climate change dynamics through tighter linkages among multiple scientific disciplines and manager contexts. Social-ecological framings, including resilience and vulnerability, are popular in such efforts, but their potential to inform meaningful rangeland adaptation science is limited by traditional disciplinary silos. Here, we provide reflective lessons learned from a multidisciplinary Rangelands, Ranching, and Resilience (R3) project on U.S. western rangelands that addressed 1) biophysical science projections of forage production under future climate scenarios, 2) ranchers’ views of resilience using social science methods, and 3) outreach efforts coordinated through extension professionals. Despite the project's initial intentions, human dimensions and ecological researchers largely worked in parallel sub-teams during the project, rather than weaving their expertise together with managers. The R3 project was multidisciplinary, but it provides a case study on lessons learned to suggest how social and ecological researchers can move towards approaches that transcend individual disciplines. Transdisciplinary science and management in rangelands requires more than just conceptual social-ecological frameworks. Additional methodological concepts need to include: 1) relationship building; 2) shared meaning making; and 3) a commitment to continual conversations and learning, or staying with the trouble, following Haraway (2016). If the goal is to address meaningful rangeland adaptation science rather than just produce academic products, researchers, outreach professionals, and rangeland-based communities should address a series of critical troubling questions. In the process of addressing these, deeper engagement among and beyond disciplines will occur as relationship building, shared meaning, and continual conversations and learning facilitate staying with the trouble.

Rangeland Ecology & Management↗

USGS2011

Allelopathic cover crop prior to seeding is more important than subsequent grazing/mowing in grassland establishment

The effects of grazing, mowing, and type of cover crop were evaluated in a previous winter wheat–fallow cropland seeded to grassland under the Conservation Reserve Program in eastern Colorado. Prior to seeding, the fallow strips were planted to forage sorghum or wheat in alternating strips (cover crops), with no grazing, moderate to heavy grazing, and mowing (grazing treatments) superimposed 4 yr after planting and studied for 3 yr. Plots previously in wheat had more annual and exotic species than sorghum plots. Concomitantly, there were much greater abundances of perennial native grass and all native species in sorghum than wheat cropped areas. The competitive advantage gained by seeded species in sorghum plots resulted in large increases in rhizomatous western wheatgrass. Sorghum is known to be allelopathic and is used in crop agriculture rotations to suppress weeds and increase crop yields, consistent with the responses of weed and desired native species in this study. Grazing treatment had relatively minor effects on basal and canopy cover composition of annual or exotic species versus perennial native grass or native species. Although grazing treatment never was a significant main effect, it occasionally modified cover crop or year effects. Opportunistic grazing reduced exotic cheatgrass by year 3 but also decreased the native palatable western wheatgrass. Mowing was a less effective weed control practice than grazing. Vegetative basal cover and aboveground primary production varied primarily with year. Common management practices for revegetation/restoration currently use herbicides and mowing as weed control practices and restrict grazing in all stages of development. Results suggest that allelopathic cover crop selection and opportunistic grazing can be effective alternative grass establishment and weed control practices. Susceptibility, resistance, and interactions of weed and seeded species to allelopathic cover species/cultivars may be a fruitful area of research.

Rangeland Ecology and Management↗

USGS2014

Natural regeneration processes in big sagebrush ( Artemisia tridentata )

Big sagebrush, Artemisia tridentata Nuttall (Asteraceae), is the dominant plant species of large portions of semiarid western North America. However, much of historical big sagebrush vegetation has been removed or modified. Thus, regeneration is recognized as an important component for land management. Limited knowledge about key regeneration processes, however, represents an obstacle to identifying successful management practices and to gaining greater insight into the consequences of increasing disturbance frequency and global change. Therefore, our objective is to synthesize knowledge about natural big sagebrush regeneration. We identified and characterized the controls of big sagebrush seed production, germination, and establishment. The largest knowledge gaps and associated research needs include quiescence and dormancy of embryos and seedlings; variation in seed production and germination percentages; wet-thermal time model of germination; responses to frost events (including freezing/thawing of soils), CO 2 concentration, and nutrients in combination with water availability; suitability of microsite vs. site conditions; competitive ability as well as seedling growth responses; and differences among subspecies and ecoregions. Potential impacts of climate change on big sagebrush regeneration could include that temperature increases may not have a large direct influence on regeneration due to the broad temperature optimum for regeneration, whereas indirect effects could include selection for populations with less stringent seed dormancy. Drier conditions will have direct negative effects on germination and seedling survival and could also lead to lighter seeds, which lowers germination success further. The short seed dispersal distance of big sagebrush may limit its tracking of suitable climate; whereas, the low competitive ability of big sagebrush seedlings may limit successful competition with species that track climate. An improved understanding of the ecology of big sagebrush regeneration should benefit resource management activities and increase the ability of land managers to anticipate global change impacts.

Rangeland Ecology and Management↗

USGS2014

Detecting the influence of best management practices on vegetation near ephemeral streams with Landsat data

Various best management practices (BMPs) have been implemented on rangelands with the goals of controlling nonpoint source pollution, reducing the impact of livestock in ecologically important riparian areas, and improving grazing distribution. Providing off-stream water sources to livestock in pastures, cross-fencing, and rotational grazing are common rangeland BMPs that have demonstrated success in drawing livestock grazing pressure away from streams. We evaluated the effects of rangeland BMP implementation with six commercial-scale pastures in the northern mixed-grass prairie. Four pastures received a BMP suite consisting of off-stream water, cross-fencing, and deferred-rotation grazing, and two pastures did not receive BMPs. We hypothesized that the BMPs increased the quantity of riparian vegetation cover relative to the conditions in these pastures during the pre-BMP period and to the two pastures that did not receive BMPs. We used a series of 30-m Landsat normalized difference vegetation index (NDVI) images to track the spatial and temporal changes (1984–2010, n = 24) in vegetation cover, to which NDVI has been well correlated. Validation indicated that the remotely sensed signal from in-channel vegetation was representative of ground conditions. The BMP suite was associated with a 15% increase in the in-channel NDVI (0–30 m from stream centerline) and 18% increase in the riparian NDVI (30–180 m from stream center line). Conversely, the in-channel and riparian NDVI of non-BMP pastures declined 30% and 18% over the study period. The majority of change occurred within 2 yr of BMP implementation. The patterns of in-channel NDVI among pastures suggested that BMP implementation likely altered grazing distribution by decreasing the preferential use of riparian and in-channel areas. We demonstrated that satellite imagery time series are useful in retrospectively evaluating the efficacy of conservation practices, providing critical information to guide adaptive management and decision makers.

Rangeland Ecology and Management↗

USGS2012

Ecosystem performance monitoring of rangelands by integrating modeling and remote sensing

Monitoring rangeland ecosystem dynamics, production, and performance is valuable for researchers and land managers. However, ecosystem monitoring studies can be difficult to interpret and apply appropriately if management decisions and disturbances are inseparable from the ecosystem's climate signal. This study separates seasonal weather influences from influences caused by disturbances and management decisions, making interannual time-series analysis more consistent and interpretable. We compared the actual ecosystem performance (AEP) of five rangeland vegetation types in the Owyhee Uplands for 9 yr to their expected ecosystem performance (EEP). Integrated growing season Normalized Difference Vegetation Index data for each of the nine growing seasons served as a proxy for annual AEP. Regression-tree models used long-term site potential, seasonal weather, and land cover data sets to generate annual EEP, an estimate of ecosystem performance incorporating annual weather variations. The difference between AEP and EEP provided a performance measure for each pixel in the study area. Ecosystem performance anomalies occurred when the ecosystem performed significantly better or worse than the model predicted. About 14% of the Owyhee Uplands showed a trend of significant underperformance or overperformance ( P <0.10). Land managers can use results from weather-based rangeland ecosystem performance models to help support adaptive management strategies.

Oregon;Idaho↗

USGS2015

Mapping and monitoring cheatgrass dieoff in rangelands of the Northern Great Basin, USA

Understanding cheatgrass (Bromus tectorum) dynamics in the Northern Great Basin rangelands, USA, is necessary to effectively manage the region’s lands. This study’s goal was to map and monitor cheatgrass performance to identify where and when cheatgrass dieoff occurred in the Northern Great Basin and to discover how this phenomenon was affected by climatic, topographic, and edaphic variables. We also examined how fire affected cheatgrass performance. Land managers and scientists are concerned by cheatgrass dieoff because it can increase land degradation, and its causes and effects are not fully known. To better understand the scope of cheatgrass dieoff, we developed multiple ecological models that integrated remote sensing data with geophysical and biophysical data. The models’ R 2 ranged from 0.71 to 0.88, and their root mean squared errors (RMSEs) ranged from 3.07 to 6.95. Validation of dieoff data showed that 41% of pixels within independently developed dieoff polygons were accurately classified as dieoff, whereas 2% of pixels outside of dieoff polygons were classified as dieoff. Site potential, a long-term spatial average of cheatgrass cover, dominated the development of the cheatgrass performance model. Fire negatively affected cheatgrass performance 1 year postfire, but by the second year postfire performance exceeded prefire levels. The landscape-scale monitoring study presented in this paper helps increase knowledge about recent rangeland dynamics, including where cheatgrass dieoffs occurred and how cheatgrass responded to fire. This knowledge can help direct further investigation and/or guide land management activities that can capitalize on, or mitigate the effects of, cheatgrass dieoff.

Northern Great Basin↗

USGS2011

Resistance to invasion and resilience to fire in desert shrublands of North America

Settlement by Anglo-Americans in the desert shrublands of North America resulted in the introduction and subsequent invasion of multiple nonnative grass species. These invasions have altered presettlement fire regimes, resulted in conversion of native perennial shrublands to nonnative annual grasslands, and placed many native desert species at risk. Effective management of these ecosystems requires an understanding of their ecological resistance to invasion and resilience to fire. Resistance and resilience differ among the cold and hot desert shrublands of the Great Basin, Mojave, Sonoran, and Chihuahuan deserts in North America. These differences are largely determined by spatial and temporal patterns of productivity but also are affected by ecological memory, severity and frequency of disturbance, and feedbacks among invasive species and disturbance regimes. Strategies for preventing or managing invasive plant/fire regimes cycles in desert shrublands include: 1) conducting periodic resource assessments to evaluate the probability of establishment of an altered fire regime; 2) developing an understanding of ecological thresholds associate within invasion resistance and fire resilience that characterize transitions from desirable to undesirable fire regimes; and 3) prioritizing management activities based on resistance of areas to invasion and resilience to fire.

Rangeland Ecology and Management↗

USGS2006

Spatial modeling of biological soil crusts to support rangeland assessment and monitoring

Biological soil crusts are a diverse soil surface community, prevalent in semiarid regions, which function as ecosystem engineers and perform numerous important ecosystem services. Loss of crusts has been implicated as a factor leading to accelerated soil erosion and other forms of land degradation. To support assessment and monitoring efforts aimed at ensuring the sustainability of rangeland ecosystems, managers require spatially explicit information concerning potential cover and composition of biological soil crusts. We sampled low disturbance sites in Grand Staircase-Escalante National Monument (Utah, USA) to determine the feasibility of modeling the potential cover and composition of biological soil crusts in a large area. We used classification and regression trees to model cover of four crust types (light cyanobacterial, dark cyanobacterial, moss, lichen) and 1 cyanobacterial biomass proxy (chlorophyll a), based upon a parsimonious set of GIS (Geographic Information Systems) data layers (soil types, precipitation, and elevation). Soil type was consistently the best predictor, although elevation and precipitation were both invoked in the various models. Predicted and observed values for the dark cyanobacterial, moss, and lichen models corresponded moderately well (R 2 = 0.49, 0.64, 0.55, respectively). Cover of late successional crust elements (moss + lichen + dark cyanobacterial) was also successfully modeled (R2 = 0.64). We were less successful with models of light cyanobacterial cover (R2 = 0.22) and chlorophyll a (R2 = 0.09). We believe that our difficulty modeling chlorophyll a concentration is related to a severe drought and subsequent cyanobacterial mortality during the course of the study. These models provide the necessary reference conditions to facilitate the comparison between the actual cover and composition of biological soil crusts at a given site and their potential cover and composition condition so that sites in poor condition can be identified and management actions can be taken.

Rangeland Ecology and Management↗

USGS2007

Habitat effects on condition of doe mule deer in arid mixed woodland-grassland

Productivity of mule deer (Odocoileus hemionus Raf.) populations is closely linked to individual nutritional condition. We modeled body fat of individual does as a function of vegetation cover, composition, and water characteristics of their annual, summer, and winter home ranges in north-central New Mexico. We also modeled home range size as a function of the same characteristics. Levels of body fat were most closely and negatively related to the amount of pinyon-juniper in an individual deer's annual home range (F1,21 = 7.6; P = 0.012; r2 = 0.26). Pinyon-juniper types provided little (combined ground cover of preferred forbs and shrubs = 5.7%) mule deer forage but were included in home ranges in excess of their availability on the landscape, likely because of security cover attributes. Proportion of grasslands in home ranges was most strongly related to both annual (F1,23 = 4.9; P = 0.037; r2 = 0.18) and summer (F2,25 = 5.7; P = 0.009; r2 = 0.31) home range sizes, and home ranges increased as the grassland component increased, indicating that this habitat type was providing little value to mule deer. Grassland (0.2% combined cover of preferred forb and shrub) and montane conifer (3.2% ground cover of preferred forb and shrub) habitat types similarly lacked preferred mule deer food, and grasslands also lacked cover. Most immediate gains in mule deer habitat in north-central New Mexico may be attained by management of pinyon-juniper communities to increase forage quantity and quality while maintaining cover attributes. Gains can also be realized in grasslands, but here management must establish both cover and forage.

Rangeland Ecology and Management↗

USGS2016

Spatially explicit rangeland erosion monitoring using high-resolution digital aerial imagery

Nearly all of the ecosystem services supported by rangelands, including production of livestock forage, carbon sequestration, and provisioning of clean water, are negatively impacted by soil erosion. Accordingly, monitoring the severity, spatial extent, and rate of soil erosion is essential for long-term sustainable management. Traditional field-based methods of monitoring erosion (sediment traps, erosion pins, and bridges) can be labor intensive and therefore are generally limited in spatial intensity and/or extent. There is a growing effort to monitor natural resources at broad scales, which is driving the need for new soil erosion monitoring tools. One remote-sensing technique that can be used to monitor soil movement is a time series of digital elevation models (DEMs) created using aerial photogrammetry methods. By geographically coregistering the DEMs and subtracting one surface from the other, an estimate of soil elevation change can be created. Such analysis enables spatially explicit quantification and visualization of net soil movement including erosion, deposition, and redistribution. We constructed DEMs (12-cm ground sampling distance) on the basis of aerial photography immediately before and 1 year after a vegetation removal treatment on a 31-ha Piñon-Juniper woodland in southeastern Utah to evaluate the use of aerial photography in detecting soil surface change. On average, we were able to detect surface elevation change of ± 8−9cm and greater, which was sufficient for the large amount of soil movement exhibited on the study area. Detecting more subtle soil erosion could be achieved using the same technique with higher-resolution imagery from lower-flying aircraft such as unmanned aerial vehicles. DEM differencing and process-focused field methods provided complementary information and a more complete assessment of soil loss and movement than any single technique alone. Photogrammetric DEM differencing could be used as a technique to quantitatively monitor surface change over time relative to management activities.

Utah↗

USGS2016

Cheatgrass percent cover change: Comparing recent estimates to climate change − Driven predictions in the Northern Great Basin

Cheatgrass ( Bromus tectorum L.) is a highly invasive species in the Northern Great Basin that helps decrease fire return intervals. Fire fragments the shrub steppe and reduces its capacity to provide forage for livestock and wildlife and habitat critical to sagebrush obligates. Of particular interest is the greater sage grouse ( Centrocercus urophasianus ), an obligate whose populations have declined so severely due, in part, to increases in cheatgrass and fires that it was considered for inclusion as an endangered species. Remote sensing technologies and satellite archives help scientists monitor terrestrial vegetation globally, including cheatgrass in the Northern Great Basin. Along with geospatial analysis and advanced spatial modeling, these data and technologies can identify areas susceptible to increased cheatgrass cover and compare these with greater sage grouse priority areas for conservation (PAC). Future climate models forecast a warmer and wetter climate for the Northern Great Basin, which likely will force changing cheatgrass dynamics. Therefore, we examine potential climate-caused changes to cheatgrass. Our results indicate that future cheatgrass percent cover will remain stable over more than 80% of the study area when compared with recent estimates, and higher overall cheatgrass cover will occur with slightly more spatial variability. The land area projected to increase or decrease in cheatgrass cover equals 18% and 1%, respectively, making an increase in fire disturbances in greater sage grouse habitat likely. Relative susceptibility measures, created by integrating cheatgrass percent cover and temporal standard deviation datasets, show that potential increases in future cheatgrass cover match future projections. This discovery indicates that some greater sage grouse PACs for conservation could be at heightened risk of fire disturbance. Multiple factors will affect future cheatgrass cover including changes in precipitation timing and totals and increases in freeze-thaw cycles. Understanding these effects can help direct land management, guide scientific research, and influence policy.

Idaho, Montana, Nevada, Oregon, Utah, Washington, ↗

USGS2006

Remote sensing for grassland management in the arid Southwest

We surveyed a group of rangeland managers in the Southwest about vegetation monitoring needs on grassland. Based on their responses, the objective of the RANGES (Rangeland Analysis Utilizing Geospatial Information Science) project was defined to be the accurate conversion of remotely sensed data (satellite imagery) to quantitative estimates of total (green and senescent) standing cover and biomass on grasslands and semidesert grasslands. Although remote sensing has been used to estimate green vegetation cover, in arid grasslands herbaceous vegetation is senescent much of the year and is not detected by current remote sensing techniques. We developed a ground truth protocol compatible with both range management requirements and Landsat's 30 m resolution imagery. The resulting ground-truth data were then used to develop image processing algorithms that quantified total herbaceous vegetation cover, height, and biomass. Cover was calculated based on a newly developed Soil Adjusted Total Vegetation Index (SATVI), and height and biomass were estimated based on reflectance in the near infrared (NIR) band. Comparison of the remotely sensed estimates with independent ground measurements produced r2 values of 0.80, 0.85, and 0.77 and Nash Sutcliffe values of 0.78, 0.70, and 0.77 for the cover, plant height, and biomass, respectively. The approach for estimating plant height and biomass did not work for sites where forbs comprised more than 30% of total vegetative cover. The ground reconnaissance protocol and image processing techniques together offer land managers accurate and timely methods for monitoring extensive grasslands. The time-consuming requirement to collect concurrent data in the field for each image implies a need to share the high fixed costs of processing an image across multiple users to reduce the costs for individual rangeland managers.

Rangeland Ecology and Management↗