In temperate landscapes, habitat selection is constrained by resource availability during winter. Most studies of habitat selection by greater sage-grouse (Centrocercus urophasianus “sage-grouse”) have focused on breeding and summer rather than winter habitat. We focused on winter microhabitat when available habitat was influenced by snow conditions. Our objectives were to 1) identify what microhabitat characteristics sage-grouse select during winter and 2) evaluate whether sage-grouse selected microhabitat at the home range (third order) or the population range (second order) scale. In summer 2020, we measured shrub characteristics and herbivore dung counts at 90 sage-grouse locations from the previous 2019/2020 winter in northwest Colorado and southcentral Wyoming and compared them with 90 paired, available locations within sage-grouse home ranges and 90 unpaired, available locations within the population range. We found strong support for sage-grouse selecting for winter microhabitat at the home-range scale because we observed similar differences in shrub characteristics between sage-grouse use locations and available locations at both scales and no differences between randomly available habitat. Compared with available locations within home ranges, wintering sage-grouse selected areas of 57.1% greater big sagebrush (Artemisia tridentata spp. Nutt.) canopy cover, 23.7% taller big sagebrush, and 110.6% more visual obstruction at use locations. Sage-grouse dung piles were 7.1 × higher at used locations than available locations within home ranges, further indicating that habitat use was less random within home ranges. In winter, microhabitat selection focused on higher cover and height of big sagebrush like previous observations from nearby studies of microhabitat selected by sage-grouse during nesting and brood-rearing.

Ecological site descriptions have become a prominent way of describing plant communities across rangelands. Disturbance response groups (DRGs) stratify landscapes by grouping ecological sites on the basis of their responses to natural or anthropogenic disturbances. DRGs allow managers to organize, scale, and evaluate information collected on the ground, thus creating expectations of how sites with similar characteristics will respond to disturbance and management. While the importance and utility of these concepts are well understood, the location and spatial extent of DRGs are not. Uncertainty of DRG location and extent make it challenging to evaluate trends or degradation risks of a given area and difficult to define and organize adaptive management concerns and opportunities on a landscape scale. DRGs are organized by major land resource areas (MLRAs), which can make real-life applications across MLRA boundaries for natural phenomena (e.g., wildfire boundaries) repetitive for specific management objectives. Vegetative great groups have been used to overcome this challenge while retaining the state-and-transition model importance of ecological sites. Presented here is a gridded process for vegetative great group mapping across MLRA boundaries, as well as an assessment of the ecological implications of the information gained about the plant communities through the mapping efforts. The scale and output are designed to fit the Landsat library grid and its derived information. Computer machine learning was used to generate spatial maps of vegetative great groups that were compared with Natural Resources Conservation Services soil survey maps, which are currently used by public land management agencies. Machine learning enhanced accuracy by 14% versus conventional soil mapping, providing a more accurate way to conceptualize and manage plant communities at the landscape scale. Further, predictor variables used in machine learning can supplement our knowledge of ecological process information on sites and aid land managers in understanding the various plant community responses to disturbance.

Yak herding, a market-based tradition, is vanishing gradually. The changing environment such as climate change, policy context, and socioeconomic change is not in favor of yak herding. Using a choice experiment survey approach, this study determines the yak herders' preferences to improve yak herding in Kanchenjunga Landscape, Nepal. The results of the choice response analysis indicate that yak herders prefer to improve yak herding by improving rangeland management, infrastructure, and health and safety services. Herders have a high preference for yak insurance (US dollar [USD] 6.82/yak), followed by cultivating an improved variety of grass in rangeland (USD 6.71/yak), improved health services (USD 5.68/yak), allowing controlled burning (USD 4.72/yak), and permanent structure of shed (USD 4.39/yak). Additionally, this analysis suggests that a policy is required to allow controlled burning to improve the condition of rangeland, which can contribute to reducing the encroachment of shrubs. Similarly, there is also a need to further explore the appropriate insurance mechanism for yaks to involve all yak herders and reduce their risk.

Landscape distribution and grazing management of small ruminants are becoming more important issues as the sheep and goat industry continues to grow. The objective of this study was to evaluate spatial movement patterns of sheep and goats in Queensland, Australia using Global Positioning System (GPS) tracking to determine daily distance traveled, distance traveled from water, activity levels, and the influence of ambient temperature on these metrics. Optimized hotspot analysis was also performed to determine areas of increased small ruminant presence across the landscape. GPS positions were recorded at 10-min intervals over the course of several months. Sheep and goats traveled an average distance from water of 0.6–1.1 km, with a maximum of 2.4 km. Daily distance traveled of sheep and goats averaged 6–9 km·d–¹, with a maximum of 11 km·d–¹. Average daily activity ranged between 42% and 47%. The overall trend of the datum showed that increased temperature led to decreased daily distance traveled, distance traveled from water, and activity of sheep and goats. The hotspot analyses showed a higher concentration of sheep and goats near water sources. Understanding small ruminant distribution in extensive rangeland pastures helps producers implement management regimes to improve efficacy and sustainability of land use and production.

Cattle (Bos taurus) grazing is often excluded from restored grasslands due to potential risks to grassland recovery. This restriction has often been applied to the 5.6 million acres of Conservation Reserve Program (CRP) plantings designed to restore native grassland plant communities on former cropland. Because large herbivores historically played a key role in maintaining these grassland systems, excluding such grazers may hamper recovery of plant compositional and structural heterogeneity important to wildlife. We conducted a grazing experiment on 108 CRP sites in Kansas, quantifying the effects of periodic cattle grazing on plant communities restored via two CRP conservation practices (CP2, Establishment of Permanent Native Grasses and CP25, Rare and Declining Habitat) across a broad precipitation gradient. Cattle grazing was implemented during the growing season on 53 of the 108 sites in 2017–2018 with rest from grazing in 2019. Grazing reduced vegetation biomass and increased vegetation structural heterogeneity in 2017 and 2018. Grazing effects on plant community composition, specifically shifts in dominant grass abundances, were observed in 2018 but not 2017 or 2019. These effects were subtle and did not result in consistent changes to plant species richness, non-native abundance, or floristic quality. The effects of conservation practice were independent of grazing but strongly dependent on mean annual precipitation. Plant community composition differed significantly between CP2 and CP25 in the western (drier) and eastern (wetter) regions, but no differences were detected in the central region. Forb cover increased with precipitation at a greater rate on CP25 than CP2, indicating greater forb establishment in the eastern region. These results indicate that moderate, short-term grazing can enhance habitat structural heterogeneity that may be beneficial for wildlife while causing minimal plant community changes.

Livestock grazing is the most economically important use of rangeland ecosystems in many parts of the world. An extensive body of literature has investigated livestock grazing plans that are economically optimal or ecologically sustainable. This paper's contribution to the literature is development and application of an empirical mathematical programming model for optimizing the economic performance of livestock grazing on rangeland ecosystems for a wide array of vegetation biomes, forage productivity levels, and economic conditions. The model is calibrated to replicate historically observed data for select counties, in which predictions of the income optimization model match available data on county-wide forage, animal performance, grazing pressure, stocking level, and net income. Results show how climate stress and economic conditions affect the economically optimized choice of stocking rates and net income for 18 observed conditions and 126 potential conditions for six counties in the Intermountain West and Mediterranean western US. While findings show optimized outcomes for a large set of conditions in that region, the methods developed here have potential application to rangeland ecosystems internationally wherever data required by the model can be secured. The modeling results provide insight and utility for ranchers, scientists, and policymakers who seek economically optimal rangeland ecosystem outcomes.

Black greasewood (Sarcobatus vermiculatus Hook., Torr) is a native halophytic, resprouting shrub found on saline rangeland soils in the western United States, including the western Great Plains grasslands. Stands can become dense, with limited native herbaceous biomass, and are prone to invasion by exotic species. We tested fall and spring prescribed fire compared with nonburned controls in a degraded rangeland site near Miles City, Montana, and a healthy rangeland site near Laramie, Wyoming to determine effects on greasewood shrub survival, density, and canopy structure. We additionally tested fuel load, time since fire, fire seasonality and prefire measurement effects on postfire greasewood canopy structure. In a second experiment at the Montana site only, nontreated controls, fall fire, 2,4-D, and 2,4-D preceded by fire were tested for effects on herbaceous biomass and greasewood survival, density, and canopy structure. Fire did not affect greasewood survival, but fire in either season reduced canopy volume by 52% across two growing seasons and models projected four or five growing seasons for structural recovery. Fine fuel load was negatively related to greasewood density and canopy structure. Herbicide reduced greasewood survival by 55%, and fire plus herbicide reduced survival by 30%. No treatment effects were detected for herbaceous biomass at the degraded site. Prescribed fire can reduce greasewood canopy structure for multiple years without killing the shrubs. Herbicide is more effective than fire if the objective is to reduce greasewood density, but multiple applications may be required. While 2,4-D herbicide was less effective when applied to resprouts after fire, results may improve with later postfire application. Although 2,4-D provided the greatest reduction of greasewood, skeletons of dead shrubs remained. Following herbicide treatment with fire could be a treatment combination to strategically reduce greasewood influence because fire would remove skeletons and further reduce canopy structure.

This technical note asks what role Canadian Bison ranchers play in conserving North American Bison. Bison are keystone species in grassland ecosystems and pose numerous ecological benefits as wild animals. Unfortunately, most wild Bison have been eradicated through the process of colonization. Today, over 90% of Bison exist in commercial production rather than for conservation; however, the Canadian Bison Association—an organization committed to protecting the industry—wishes to blur the line between the two. Conversations with a few members of the CBA suggest that ranching may support the numerical recovery of Bison but may not support ecological recovery. Although there have been calls for cross-jurisdictional collaboration in the Bison conservation literature, more research is needed to reconcile what appear to be incompatible values between ranchers and ecological conservationists.

In light of climate change, ranchers need management tools to restore dry grasslands. To boost productivity and resilience, compost applications have shown promise, but little is known about the effect of composts that differ in initial feedstock and resulting biological and chemical characteristics. Our objective was to compare commonly available composts to evaluate how they affected soil microbial community composition and soil health–related responses in drylands. We added biosolid versus manure composts to 64-m² plots in a rangeland in Socorro County, New Mexico and measured microbial, soil, and plant characteristics after 6 mo and 1 yr. We found that while composts hosted diverse microbial taxa, relative abundance of native soil microbial communities did not shift dramatically from controls at either 6 mo or 1 yr after compost addition. Aggregate stability was 22% lower in manure than biosolid compost and controls (P = 0.048), but aboveground biomass tended to strongly increase depending on exclosure treatment (P = 0.048), and composition shifted to relatively abundant annual forbs with biosolid compost compared with controls. Together, these results suggest that while increased organic matter enhanced vegetation biomass, an important implication for range managers, the dominant microbial community members were not primarily responsible for observed shifts in responses.

Globally, land use and land cover change (LULCC) is recognized as posing a substantial environmental challenge with lasting and severe consequences. This study quantified LULCC within the Vea catchment area spanning 24 years, from 1998 to 2022. Landsat TM imagery from 1998, ETM+ imagery from 2006, and Landsat 8 OLI imagery from 2014 to 2022 were used. A supervised classification algorithm was employed to classify the LULC classes. The findings reveal a notable transformation in the Vea catchment area from 1998 to 2022, primarily by converting grassland to cropland. Agricultural activities emerged as a significant contributor to the observed LULCC trend. Notably, cropland expanded from 10.9% to 51.98% between 1998 and 2022, while grassland and mixed vegetation/forest areas decreased from 54.8% to 18.14% and 31.7% to 22.73%, respectively. These results, it is argued, underscore the potential implications for achieving the targets set by the UN's Sustainable Development Goals.

The Montezuma quail (Cyrtonyx montezumae) is a game bird that inhabits oak-juniper-pine savannas of Arizona, New Mexico, and Texas, extending its range south into montane grasslands of Mexico. The species occurs within a complex matrix of public and private rangeland in which land management regimes and habitat quality are disparate. Given that food limitation can be a driver of wildlife populations, studies of the Montezuma quail diet can inform the management of its habitat. Our objective was to determine the composition and variation of the Montezuma quail's diet in Arizona, New Mexico, and Texas by macrohistological analysis of crops (n = 175) collected in 2016–2020 during winter in all three states and during spring in Texas. We used Dirichlet regression to determine the effects of ecological factors on diet composition. Winter diet in Arizona was mainly represented by woodsorrel bulbs (Oxalis spp.; 35.22% of dry weight), sedge rhizomes and bulbs (Cyperus spp.; 30.92%), and acorns (Quercus spp.; 7.17%). Winter diet in New Mexico consisted mainly of sedge bulbs (64.13%), bushbean seeds (Macroptilium sp.; 15.82%), and Hall's panicum seeds (Panicum hallii; 10.11%). Winter diet in Texas was composed of sedge rhizomes and bulbs (28.17%), Texas snoutbeans (Rhynchosia senna; 22.49), Hall's panicum seeds (19.54%), and wild onions (Allium spp.; 8.58%). Spring diet in Texas included sedge rhizomes and bulbs (67.90%), woodsorrel bulbs (19.49%), and Texas snoutbeans (5.55%). Geographic variation in diet composition was related to climatic, ecological, and intrinsic factors. For instance, in addition to being consumed by males at a higher rate, woodsorrel bulbs were also consumed at a greater rate in hotter and wetter locations. Along with novel information about the Montezuma quail diet in Texas, our investigation will stimulate questions relevant to rangeland and wildlife management, including determinants of habitat quality and the effects of climate change on wildlife populations.

Rangelands globally face escalating threats from overgrazing, land conversion, and climate change. This study investigates spatio-temporal rangeland degradation patterns in Pakistan's Bhakkar District, a semiarid region dependent on fragile pastoral ecosystems, over the past four decades at 10-yr intervals (1990, 2000, 2010, 2020). Remote sensing offers a valuable tool for monitoring these vast yet understudied dryland environments. We employed Landsat satellite data and machine learning algorithms to map land cover change and analyze vegetation health indicators. The random forest classifier achieved high accuracy (94%) in delineating six land cover categories–water, built-up, forest, cropland, rangeland, and barren land. Classified rangeland area declined by over 25%, largely due to agricultural expansion. Vegetation indices showed mixed trends, with decreases in enhanced vegetation index but marginal improvement in normalized difference vegetation index. Meanwhile, rising land surface temperatures pointed to increased aridity. These concerning changes underscore the urgent need for conservation policies tailored to community needs through participatory engagement. Rangeland degradation threatens the livelihoods and welfare of pastoral communities reliant on these ecosystems. Integrated solutions centered on adaptation and resilience can promote sustainability in Bhakkar's marginal dryland environments. This study demonstrates the power of satellite monitoring coupled with social research for implementing holistic strategies to address the globally prevalent threat of rangeland disruption.

Deferred grazing regimes are viewed as a grazing management strategy that can aid in the enhancement of rangeland productivity and health. However, there is limited empirical evidence from drylands of East Africa. This study investigated the effects of deferred grazing regime on rangeland productivity and health in northern Tanzania. Aboveground vegetation biomass, plant species composition and diversity, as well as soil organic carbon (SOC) were assessed in 45 rectangular sample plots (20 × 50 m) which were randomly distributed in a rangeland subjected to deferred grazing for 8 years. For control adjacent rangelands subjected to continuous grazing management were evaluated. Statistical analyses were performed using an independent t-test to discern differences in vegetation biomass, SOC, species abundance and diversity between the two grazing regimes. Additionally, Multivariate General Linear Model (MvGLM) were performed to test if grazing system affected vegetation composition. Results revealed that the herbaceous biomass, SOC, and the richness of shrubs (with a diameter at breast height, or DBH ≥5 cm and <10 cm) and trees (DBH ≥10 cm) were higher in rangeland subjected to deferred grazing, in comparison to the rangeland under continuous grazing regime. Moreover, rangeland under continuous grazing was found to be more heavily invaded by non-native plant species, notably the invasive weeds Prosopis juliflora and Calotropis procera. The findings of this study suggest that rangelands in the study area can be both more productive and healthier when managed under a deferred grazing regime, as compared to continuously grazing rangeland.

Eastern redcedar (ERC) (Juniperus virginiana L.) encroachment into grassland ecosystems, facilitated by shelterbelt planting and fire suppression threatens the long-term health of the Great Plains grasslands. Goats browse (defoliate and debark) juniper tree trunks and branches. Since ERC do not resprout, trunk girdling may kill the tree, making targeted browsing with goats a potential ERC control tool. However, little field experimentation exists. The objective was to investigate how goats browse ERC of different heights and the impact on tree mortality. A randomized complete block design was used with five sites comprised of four replicate paddocks browsed two consecutive summers. Up to ten ERC in five height classes (< 50, 51–100, 101–150, 151–200, and 201–250 cm) were tagged permanently in each paddock and browsing measurements and forage disappearance were recorded. Juniper height was positively related with debarking (y = 0.12x; R² = 0.29; where x = plant height in cm) and negatively related with defoliation (y = –0.28x + 72.1; R² = 0.39; where x = plant height in cm). Two sites consistently showed that taller trees had more foliage browning (P < 0.001). Thus, since taller trees are more likely debarked, debarking may be related to tree death. On these sites, ERC trees 151–200 cm had more (P < 0.05) browned foliage and higher (P = 0.01) mortality. Sites with more deciduous browse had less debarking and mortality. Therefore, ERC debarking and mortality success with targeted browsing with goats will most likely depend on site plant community composition characteristics where juniper trees should be the only woody component. Targeted browsing with goats could be an effective ERC site pretreatment when integrated with prescribed fire or other control methods.

Adaptive multipaddock (AMP) grazing is a form livestock management that uses high stock density, frequent herd rotation, and long adaptive plant recovery periods to produce punctuated disturbances within pastures. This form of livestock management may benefit pasture biodiversity and ecosystem function. Arthropods are key to ecosystem functionality through the fulfillment of many ecological niches in pasture ecosystems like dung burial, pest control, and pollination. However, the effect of AMP grazing on arthropod communities has not been well studied. We assessed the effect of AMP grazing on arthropod community composition. Foliar, soil, and dung arthropod communities were collected from AMP and conventionally grazed (CG) pastures located in the southeastern US. Arthropod abundance, species richness, diversity, and guild composition were compared between grazing treatments. The herbaceous standing plant diversity was recorded in the immediate vicinity of arthropod sampling. AMP grazed pastures exhibited higher foliar arthropod species richness, along with higher foliar and dung guild diversity. The effects of AMP grazing on the arthropod community were likely correlated to changes to the vegetative community resulting from AMP grazing. No differences in pest abundance or species diversity were found between the AMP and CG pastures. This study shows AMP pasture management has a positive effect of arthropod community composition, which is likely to be an important mechanism to facilitating ecosystem services in AMP pastures.

Fritillaria imperialis L., an indicator plant species in Iran, is facing threats and its population has declined in recent years. To provide insights into the drivers affecting its loss, this research aims to identify the effects of three groups of factors, including climate, soil, and physiographic variables, on the current and future spatial distributions of F. imperialis. For this purpose, we used five machine learning algorithms as well as an ensemble forecasting of species distribution approach to explain the geographical distributions of the species as a function of these factors. In addition, we used two shared socio-economic pathways scenarios – SSP 1-2.6 and SSP 5-8.5 – to project the future distributions of F. imperialis in 2030, 2050, 2070, and 2090. Based on evaluation indices, area under the ROC curve (AUC) and true skill statistic (TSS), the Random Forest (RF) model generated the strongest prediction of the distribution of F. imperialis (TSS>0.9 and AUC>0.9). No significant difference observed among the three datasets (climate-only variables, climate + physiography variables, and climate + physiography + soil variables) in terms of AUC values. In models using climate + physiography + soil datasets, soil electrical conductivity, clay, and pH emerged as the most important variables affecting the growth and development of F. imperialis while climate factors played a lesser role in its distribution. Future projections revealed different patterns when using the optimistic (SSP 1-2.6) and pessimistic (SSP 5-8.5) socio-economic pathway scenarios and either the climate only or climate + physiography models. The climate + physiography + soil model produced similar prediction patterns for the scenarios. The climate-only models predicted larger areas suitable for crown imperial in the future than did the climate + physiography + soil model. These results emphasize the consideration of factors beyond climate scenarios when modeling biological responses to global warming and regional climate change.

Improved techniques are needed to estimate the dietary species composition of grazing animals. The fecal DNA metabarcoding technique has been proposed as a noninvasive method to determine dietary species composition. However, studies suggest that it is more effective to qualitatively estimate species composition of wild and domestic animals than for accurately quantifying diet composition. The technique, using the trnL barcode, was evaluated with 10 individually penned goats, which were fed hand-harvested plant materials that were collected fresh each morning before known amounts of each type of plant materials were fed and completely consumed by the goats. Goats were fed at 3% of their body weight on a DM basis. Broadleaf plant materials fed were Russian olive (Elaeagnus angustifolia), silver buffaloberry (Shepherdia argentea), western snowberry (Symphoricarpos occidentalis), and wormwood sage (Artemisia absinthium) plus a mixture of predominantly smooth bromegrass (Bromus inermis), which also included small amounts of other grasses such as Kentucky bluegrass (Poa pratensis) and forbs such as leafy spurge (Euphorbia esula). Estimates of the dietary composition of the goats were different (P ≤ 0.04) from those of their known dietary composition, except for wormwood sage when expressed on a crude protein basis (P = 0.98), regardless of whether known composition was expressed on a dry matter or crude protein basis. Therefore, we conclude that the fecal DNA metabarcoding technique for estimating the dietary composition of goat diets is useful qualitatively but needs further development to be a better quantitative technique.

Mineral nutrition deficiencies commonly occur in extensive sheep production systems, yet often coincide with critical production periods of breeding and gestation when quality and quantity of winter range are most limited. Ewe productivity may be limited by clinical and subclinical mineral deficiencies when grazing extensive rangelands during the winter months. The objectives of this study were to utilize fecal meta-barcoding DNA (f.DNA) to estimate dietary composition of ewes by plant morphological group (monocots and dicots), and quantified plant nutritional composition from clipped biomass to estimate adequacy of macro- and micro-minerals of the basal diet across extensively grazed sheep operations. Ewe fecal samples for f.DNA were collected from 19 extensive sheep operations across Wyoming and Colorado, USA, and analyzed at the plant morphological group level to estimate dietary composition as 1) Monocot (≥ 70%), 2) Dicot (≥ 70%), or 3) Mixed (monocot and dicot co-dominated, both proportions < 70%). Pooled forage species nutritional composition within morphological group (monocot vs. dicot) was then multiplied by the proportion of monocotyledonous species or dicotyledonous species and intake estimates of 2% of BW on an 80 kg ewe to estimate macro- and micro-mineral intake. Results from f.DNA indicated 36% of operations were categorized as Monocot (≥ 70% dietary component), 42% Dicot (≥ 70% dietary component), or 21% Mixed. A significant effect of plant morphological group category was observed for CP, Ca, K, Mg, and S (P < 0.05) where dicot dominated rangelands contained higher concentrations of these minerals compared to monocot or mixed monocot-dicot rangelands. Overall, dicot dominated rangelands provided greater macro- and micro-mineral content ultimately meeting more requirements for breeding and gestation than monocot or mixed monocot-dicot rangelands. Therefore, targeted supplementation must be considered for ewes on monocot or mixed monocot-dicot rangelands during winter months that coincide with critical production stages.

Mule deer (Odocoileus hemionus) populations have declined steadily across their geographic range due to a multitude of factors including habitat degradation associated with the encroachment of invasive annual grasses including cheatgrass (Bromus tectorum), medusahead (Taeniatherum caput-medusae), and North Africa grass (Ventenata dubia). These grasses can drive changes in vegetation composition that significantly reduce the quantity and quality of summer mule deer forage. Application of annual grass selective herbicides is a management tool being used in efforts to restore invaded grasslands. We assessed the effect of an imazapic application on mule deer use, home range size, and proportional overlap with treatment areas. We evaluated differences in summer (June–August) use between fifteen 8-ha paired control and treatment plots, comparing responses among pretreatment, 1 yr post treatment, and 2 yr post treatment. Results from tests were statistically insignificant but suggest a weak positive response by mule deer to imazapic-treated areas. Proportional use of treatment plots in the first summer post treatment was 4.4% higher than use of control plots and was greater than pretreatment use of the same plots. In the second summer post application, use of treatment plots decreased and returned to pretreatment levels. Mule deer increased use of treatment plots in alignment with improvements in crude protein and digestible energy content of forage. As annual grasses began reinvading and nutritional quality of forage was no longer higher than the control, use of treatment plots declined and returned to pretreatment levels.

Plant communities in a stable, long-term state with high sagebrush cover and low desirable perennial herbaceous cover and/or relatively high invasive annual cover are widespread across the Great Basin and distinct from areas affected by wildfire. Restoring these areas, collectively called “degraded sagebrush understories,” and preventing future degradation are management challenges that require maintaining desirable levels of sagebrush cover while simultaneously increasing understory perennial abundance and diversity. Defining degradation based on a firm grasp of current and potential vegetation composition is a fundamental aspect of setting restoration goals and selecting methods. Assigning degraded status to any given site is also a considerable challenge in many sagebrush landscapes due to widespread (and long-standing) lack of intact herbaceous plant communities in some landscapes, as well as high interannual variation in herbaceous community composition (particularly cover). In this manuscript, we provide a workflow for defining degraded understories and present a framework for identifying restoration approaches emphasizing the pathways (causes) of degradation in this system, such as historical cultivation, inappropriate grazing, invasive species, and drought, as well as the size and extent of degraded areas. We also describe the relative paucity of well-documented successful restoration approaches for degraded understories, particularly for one-time restoration treatments. This lack of success may be due to lack of propagules, potential competition from sagebrush, invasive species, and/or altered soil conditions. Multiple restoration treatments in specific sequences and/or years may increase success; however, the effectiveness of these techniques is uncertain due to infrequent implementation and rigorous evaluation across a range of environmental conditions. Due to the extent of degraded understories in Great Basin sagebrush ecosystems, meeting biome-level conservation goals will likely require additional research to characterize the types and development pathways of the degraded understories, spatiotemporal recovery or ongoing degradation patterns, and targeted restoration techniques.

Demographic studies suggest that mortality of emerging bunchgrass seedlings limits restoration success across North American cold desert rangelands, but how variation in seedling resilience to ecophysiological stress contributes to this is unclear. We measured light-saturated photosynthetic rate (A_sat), apparent CO₂ assimilation quantum yield (ΦCO₂), and light-adapted PSII yield (Φ_PSII) of seedlings from two native perennial bunchgrasses (Elymus elymoides, Pseudoroegneria spicata) during and in recovery from acute water stress (6% soil moisture). All seedlings of both species survived the 14-d dry-down and recovery, and both had ∼95% reduction in A_sat and ΦCO₂ by day 3 of the dry-down but had divergent recoveries from the acute water stress. E. elymoides took a single day to recover A_sat and ΦCO₂ to prestress levels, while it took P. spicata 6 d to have 50% recovery from acute water stress. Especially notable is that after reduction in Φ_PSII on d 7 of the dry-down, E. elymoides recovered within 1 d at a lower Φ_PSII compared with pretreatment, while P. spicata had an additional 1-d lag in Φ_PSII recovery. These results suggest that E. elymoides (Turkey Lake germplasm) seedlings are more physiologically resilient to acute water stress than P. spicata (Anatone germplasm), which has implications for restoration planning and native plant breeding.

Virtual fence (VF) is the use of a global positioning system (GPS) to dictate where on the landscape livestock can graze without relying on traditional physical fence such as barbed wire. The recent acceleration in the development and adoption of VF technology for grazing management has been characterized by the evolution of divergent terminology. Different research and commercial entities have adopted terms and definitions independently. Some terms and definitions are inherently problematic, while others are more aligned, and the simple fact that differences exist contributes to confusion in communication among scientists, producers, land managers, manufacturers, government agencies, and the public. In this paper, we propose a standard terminology determined during a 2-d in-service workshop at the annual meeting of the Society of Rangeland Management in February 2023. Standard terminology will aid in efficient and effective communication among all entities and interested parties.

Precipitation and temperature inputs are the primary factors affecting net primary plant production across rangeland ecoregions. Skillful seasonal climate forecasts have the potential to directly aid in informing management for multiple agricultural and natural resource applications across the western United States. A key limitation in using these forecasts has been the availability of high-resolution climate forecasts across rangeland ecoregions given the high spatiotemporal heterogeneity in precipitation and temperature across these regions. This study examines the skill, or the correlation between of a climate forecast to actual data. Seasonal climate forecasts at lead times of up to 7 months lead times are statistically downscaled from models participating in the North American Multi-Model Ensemble (NMME). The skill of seasonal climate forecasts has typically been assessed at regional scales which may obscure forecast utility for site-specific management applications. Skill assessments are also typically only conducted on individual models, or the ensemble mean of all models which may overlook value-added skill by subsampling models. Here, we evaluated the skill of statistically downscaled monthly precipitation and temperature forecasts derived from seven NMME models for multiple rangeland ecoregions across the western United States. We found that multimodel aggregate forecasts often had synergistic skill when compared to both individual model forecasts as well as the ensemble mean. We also found that forecast skill was dependent on location, the month in which the forecast was made, and the forecast length. We suggest that a site and time-specific optimization of multimodel ensemble skill would increase the potential utility of these forecasts to inform rangeland management decision-making.

Tallgrass prairie is one of the major ecosystems in the Southern Great Plains of the United States of America (USA). We investigated the impact of diverse weather conditions on the vegetation dynamics obtained through satellite remote sensing and the dynamics of carbon dioxide (CO₂) fluxes, evapotranspiration (ET), and ecosystem water use efficiency (EWUE) obtained through eddy covariance (EC) in a native tallgrass prairie pasture in central Oklahoma, USA. The study was conducted from 2019 to 2022, considering varying growing conditions. Daily peak net ecosystem CO₂ exchange (NEE), gross primary production (GPP), and ET were –8.7 g C m^–2, 15.1 g C m^–2, and 5.9 mm, respectively. Dynamics of eddy fluxes aligned with the dynamics of vegetation, indicating the accuracy and reliability of satellite-based vegetation indices in tallgrass prairie. Both CO₂ fluxes and ET rates showed little variation over the years during the non-growing season (November to March). However, eddy fluxes exhibited diverse patterns during growing seasons. During the regrowth phase after the hay harvest, the differences in eddy fluxes were particularly substantial due to large variations in late-season rainfall. Consequently, the strength and duration of carbon gain during growing seasons varied substantially by year (i.e., carbon sink for 6 mo in 2019 vs. 2 mo in 2022). The highly variable magnitude of EWUE over the years illustrates that EWUE is not a constant property of this prairie ecosystem. A greater reduction in GPP than ET during dry years led to reduced EWUE. Strong relationships between eddy fluxes and vegetation indices suggest that CO₂ fluxes and ET can be estimated from satellite imagery alone for tallgrass prairie across large spatial scales. Overall, this study provides valuable insights into the carbon and water cycles of tallgrass prairie and the impacts of environmental drivers and disturbances on their function.