Rangeland degradation in arid and semi-arid regions poses significant environmental and socioeconomic challenges globally. This study aims to assess the Spatio-temporal dynamics of rangeland changes in Khushab district, Pakistan, between 2000 and 2020 by developing an integrated approach combining remote sensing, vegetation indices, and machine learning techniques. The specific objectives were to: (1) quantify rangeland extent changes using multi-temporal Landsat imagery, (2) evaluate rangeland health through multiple vegetation indices, and (3) analyze the primary drivers of rangeland transformation. The methodology integrated Landsat-derived land use land cover (LULC) classification using Random Forest and SMILE CART algorithms, analysis of six vegetation indices (NDVI, GNDVI, SAVI, EVI, ARVI), and land surface temperature (LST) assessment. The classification accuracy exceeded 90% for Random Forest and 87% for SMILE CART across all time periods. Results revealed significant rangeland degradation, with area declining from 9% to 6% of total land between 2000 and 2020. Cropland expansion was the primary driver, increasing from 16% to 29% and converting 218 sq km of rangeland. Vegetation indices showed stable NDVI but declining GNDVI maximums from 0.37 to 0.36, indicating deteriorating plant health. Rising minimum LST from 27.82°C to 31.81°C suggested increasing heat stress on vegetation. This research demonstrates the effectiveness of integrating multiple remote sensing approaches with machine learning for comprehensive rangeland monitoring. The findings provide crucial baseline data for evidence-based policy making and sustainable rangeland management in Pakistan's semi-arid regions. Future work should incorporate ground validation and socioeconomic surveys to better understand degradation drivers and develop targeted conservation strategies.

In remote and sparsely populated pastoral areas where formal institution is often insufficiently supplied and slackly enforced, informal peer collaboration provides a critical support for local smallholder farmers to maintain livelihood resilience against uncertain environments. A set of key drivers to the formation of such self-organized collaboration have been identified by the existing literature, but studies that quantitatively investigate the roles of existing institution therein have been rarely seen, presumably because of measurement difficulty. Using household survey data collected from a case village on the Qinghai-Tibetan plateau, we applied network modeling methods to quantitatively examine the effects of preexisting strong and weak social ties on the formation of collaborative network among herders. The results show that the odds of establishing collaborative relationship between a pair of herders with a strong or weak tie was 21.06 or 10.86 times higher than those without, implying that trust and social norms embedded in the strong-tie network effectively reduced collaborative cost and mitigated collaborative risk, whereas novel nonredundant knowledge and resources carried by the weak-tie network facilitated collaboration across boundaries of social groups. Popularity and transitivity were two key endogenous structural relationship development mechanisms, signaling the emergence of Matthew effect and relational clusters. Social status and group affiliation were the key attributes that herders considered in choosing collaborative partners. To enhance livelihood resilience, local policymakers can regularly organize collective activities to reinforce emotional bonds between herders, and proactively engage with broader stakeholders to develop more diverse weak ties. Meanwhile, the leadership of central network actors should be fully mobilized and effectively supervised to facilitate successful collective actions.

Droughts are projected to become more extreme and more frequent throughout the remainder of the 21st century. Our ability to sustain rangeland functioning relies on understanding the interactive effects of extreme drought and herbivory on vegetation. Here, we report on an experiment in northeast Wyoming, USA that simulated five levels of drought intercepting 0 %, 25%, 50%, 75%, or 99% of ambient rainfall for two years. These treatments were crossed with two grazing intensity (50%, 70% utilization) and two browsing intensity (background, +50% leader removal) treatments. We measured canopy volume changes, leader growth, and leaf water potential on a dominant shrub, Artemisia tridentata ssp. wyomingensis (Beetle & Young), to test three major predictions: (1) canopy volume and leader growth decline with greater drought magnitude, (2) heavy grazing reduces the effects of drought magnitude, and (3) heavy browsing amplifies effects of drought magnitude. Under ambient browsing intensity, extreme drought caused Wyoming big sagebrush (Beetle & Young) canopies to shrink. Interestingly, this effect went away in our heavy browsing treatment, despite overall negative effects of heavy browsing on shrub canopies and leader survival. We show that this drought-buffering effect may be driven by reduced leaf-level water stress in droughted, heavily browsed shrubs compared with droughted, ambiently browsed shrubs; this may have resulted from lower early-season leaf area leading to lower transpiration-related water loss. This potential mechanism for drought resistance in sagebrush steppe highlights the importance of maintaining intact food webs, despite perceived deleterious effects of herbivores for plant abundance and growth. To promote sustainability of sagebrush and other shrub-dominated ecosystems in face of extreme precipitation change, it may be necessary for land managers and policy makers to prioritize conservation of native herbivores within ecosystems.

We compared six Snake River wheatgrass (Elymus wawawaiensis J. Carlson & Barkw.) populations, including Destination Germplasm (released 2023), ‘Discovery’ (2007), and ‘Secar’ (1980), for seed-yield components, a reproductive-health score, ecological fitness, and persistence of fitness. In two consecutive years, we measured fecundity in a transplanted trial at North Park Farm (Hyde Park, UT) and survivorship (stand percentage) in a seeded trial at Nephi, UT. Across the six populations, seed yield per spike exceeded spike number in importance as a seed-yield component, seeds per plant exceeded seed mass, seeds per spike exceeded both spike number and seed mass, and seed area exceeded seed-specific mass. Compared to Discovery, from which it was derived, in 2022 (2023) at North Park, Destination displayed 61.1% (113.0%) greater seed yield per plant, 45.3% (81.6%) greater seed number per plant, and 14.4% (18.1%) greater seed mass (P < 0.05). Destination’s greater seed yield than Discovery in 2022 was accounted for by increases in seed mass, spike number, and seeds per spike in roughly a 1:2:1 ratio, though the latter was not significant (P > 0.05). At Nephi in 2023 (2024), Destination displayed a 65.8% (32.1%) stand, while Discovery’s stand was much lower at 34.0% (14.1%). Destination’s reproductive-health score (15 of 16 possible points) exceeded Secar’s (4) and Discovery’s (1). Relative ecological fitness (and its persistence) was 1.000 (1.000) for Destination, 0.302 (0.662) for Discovery, and 0.147 (0.711) for Secar. By all measured parameters, Destination shows greater promise for rangeland revegetation and restoration efforts than Secar or Discovery.

To understand and estimate the effects of environmental drivers on temperate wet heathland vegetation, pin-point cover data from 42 Danish sites sampled during a 15-year period was regressed onto selected environmental variables. The effects of nitrogen deposition, soil pH, soil C–N ratio, soil type, precipitation, and grazing on the heathland vegetation was modeled in a spatiotemporal structural equation model using a Bayesian hierarchical model structure. The results suggest that the modeled environmental variables have various regulating effects on the large-scale spatial variation as well as plant community dynamics in wet heathlands. Most noticeably, nitrogen deposition and yearly precipitation had relatively large and opposite temporal effects on the characteristic species Erica tetralix and Molinia caerulea, where nitrogen deposition had negative effects on E. tetralix and positive effects on M. caerulea. The results of this study differed in important qualitative aspects from the findings of an earlier study where comparable data from a shorter time series (7 years instead of 15 years) were analyzed with a similar model, which suggests that relatively long time series are needed for studying ecosystem dynamics. Furthermore, it was concluded that the effect of nitrogen deposition on plant community dynamics mainly was through direct effects, whereas the effect of soil type on plant community dynamics was both direct and indirect mediated by the effect of soil type on soil pH. It was concluded that the modeled environmental variables are sufficient for predicting the average plant community dynamics of wet heathlands. However, caution is required if the fitted model is used for generating local ecological predictions as input to a process of generating adaptive management plans for specific wet heathland sites. Moreover, the results suggest that the ratio between the two species E. tetralix and M. caerulea may be used as an indicator for the conservation status of wet heathlands.

The working landscapes approach is valuable for extending conservation beyond the boundaries of strict protected areas. Conservation on working landscapes relies heavily on social acceptance and the alignment of conservation programs with local livelihoods. This paper examines farmers and ranchers' preferences for different policy instruments and incentives that form programs for endangered species conservation in Canada's temperate grassland ecosystem—one of the most imperiled ecosystems on earth. Generally, farmers and ranchers are more concerned about the restrictions that programs impose than they are about the amount of funding the programs provide. Although, trust in the program delivery agent is also a key consideration. Overall, farmers and ranchers prefer instruments that maintain their property rights and provide continuous financial incentives. Additionally, they prefer shorter-term contracts to longer-term contracts or agreements in perpetuity. Many of their preferences extend beyond status quo conservation in Canada, which relies heavily on restrictions, non-continuous financial incentives (i.e., one-time payments), and long-term agreements. We need to augment the existing suite of programs to include flexible and adaptive options to maintain, improve and protect grasslands and the species that depend on them.

In recent decades, woody plant cover has increased across many North American grasslands, with important implications for wildlife habitat availability. Scaled quail (Callipepla squamata), a declining ground-dwelling bird species, is known to use woody vegetation in arid and semiarid rangelands. However, it is unclear how vegetation changes due to woody encroachment affect scaled quail space use or if scaled quail perceive various species of woody cover differently. We examined breeding season habitat use and survival of scaled quail in 2018 and 2019 in southeastern New Mexico, USA, in a landscape with various species of shrubs, including mesquite (Prosopis L. spp.), which is thought to have increased over time. We used generalized linear mixed models (GLMMs) to compare vegetation characteristics between used quail locations and random (available) locations. We used resource selection functions (RSF) to examine selection for dominant vegetation cover types and anthropogenic features at the third order (within home ranges). We also investigated the influence of third-order selection and weather on quail survival (adult and brood). We found that both brooding and nonbrooding quail preferentially used locations with greater visual obstruction and high densities of tall (≥1.5 m) shrubs relative to availability. Within home ranges, scaled quail selected for proximity to mixed shrub cover, mesquite cover, and bare ground but demonstrated weak avoidance of herbaceous-dominated patches. However, third-order space use did not affect daily survival probability for either adult quail or broods. The only variable related to quail survival was daily average wind speed, which was positively associated with brood survival. Our findings highlight the importance of shrubs as a source of visual, thermal, and olfactory cover for scaled quail. In increasingly shrub-dominated communities, we recommend that scaled quail management plans prioritize practices that create spatially and compositionally diverse vegetation, including patches of tall, dense shrubs.

Indaziflam is a relatively new herbicide that kills newly germinated plants. There is interest in using indaziflam to improve rangeland restoration but applying it around the time of seeding risks damaging seeded plants. A better strategy may be using indaziflam long before seeding to deplete weed seedbanks and then seeding after it dissipates. Dissipation rates vary and are difficult to predict, so testing is needed to determine whether indaziflam remains present. The manufacturer-recommended test involves seeding small indaziflam-treated areas and then monitoring for herbicide damage. A disadvantage here is that rangeland seeding is failure-prone, so seeded species can fail to emerge whether indaziflam is present or not. Another disadvantage is that test areas cannot be reliably evaluated until many months to a year after seeding, by which time evaluations are obsolete. We sought a more reliable, rapid bioassay. We gathered soil samples from nontreated and indaziflam-treated plots in two experiments treated 565 d and 204 d earlier. In these samples in a greenhouse, we planted seeds of native grasses (Elymus lanceolatus [Scribn. & J.G. Sm.] Gould and Pascopyrum smithii [Rydb.] Á. Löve) and an exotic invasive grass (Bromus japonicus Thunb.) and then measured plant responses. Plant densities and heights were similar across experiments. Indaziflam reduced native grass density 50% ± 8%, native grass height 74% ± 6% (mean ±SE), and exotic grass density and height nearly 100% (p < 0.05). The grasses that emerged from treated soil were discolored. Plant data were gathered 18 d after seeding, which illustrates that restoration managers can rapidly test for indaziflam in advance of seeding. To prevent being misled by natural variability among samples, we recommend testing ≥ five nontreated and treated soil samples. In addition to greenhouses, other well-illuminated areas held at 16–24°C are sufficient for testing.

Ponds have been constructed by ranchers in Oklahoma and Texas to offer drinking water to livestock while helping to mitigate the consequences of extreme weather. In this study, the water composition of 72 ponds from ranches in Oklahoma and Texas was surveyed in October and November of 2023, with the objectives to: 1) assess pond water suitability for ruminant livestock consumption, and 2) examine bivariate and multivariate relationships among water quality parameters. Most of the parameters were well below the maximum acceptable upper levels. Even with average values within safe limits, pH, potassium, and manganese concentrations exceeded maximum upper levels in 6.9%, 18.1%, and 15.3% of ponds, respectively. A single pond had an unexpectedly high concentration of cadmium, which placed the average value above the maximum upper limit. Total coliform bacteria (TCB) and Escherichia coli were detected in 95.8% and 55.6% of the samples, respectively, and 39% of the samples exceeded the maximum upper level for TCB. Two major groups of intercorrelated variables identified by the Spearman correlation matrix were confirmed by principal component analysis. Most of the macroconstituents formed one positively intercorrelated group associated with electrical conductivity and total dissolved solids. The second group included several microconstituents that were positively correlated among themselves but negatively correlated with pH. Ensuring animals can access alternative safe water sources within pastures as well as rotating them among pastures throughout the ranch could potentially mitigate health issues when ponds present low-quality water.

Restoring fire in fire-adapted ecosystems is necessary to curtail woody plant expansion, enhance biodiversity, and reduce wildfire risks, yet prescribed fire is promoted less by federal agencies than other grassland conservation practices. The U.S. Department of Agriculture Natural Resources Conservation Service (NRCS) is the primary federal agency responsible for the delivery of rangeland conservation incentives to private landowners in the Great Plains. The degree to which NRCS employees choose to offer technical guidance on prescribed fire and whether they encourage landowners to consider financial support is not well-understood and varies among states. Our study explored the extent to which prescribed fire awareness and social interaction factors influence NRCS employees' knowledge and comfort level regarding prescribed fire and the frequency with which they recommend this conservation practice. The results show that while prescribed fire awareness influences knowledge, it was not significantly associated with frequency of prescribed fire recommendations. Rather, social interaction factors were significantly related to recommendation frequency; these included priority of prescribed fire education in their jobs, positive interactions with landowners regarding prescribed fire, and how often they were asked to deal with brush management. An important implication is that while better knowledge about prescribed fire is necessary, it is not sufficient for more frequent prescribed fire recommendation by natural resource professionals. Instead of focusing primarily on technical proficiency, federal agencies tasked with expanding the application of prescribed fire as an ecosystem restoration and wildfire mitigation tool should focus more on building stronger social networks through, for example, providing greater support of existing and new prescribed burning associations. Our findings also have implications for a national unified policy that supports the application of prescribed fire on privately-owned rangelands because negative fire culture at the federal level has an erosive effect on agencies' willingness to assist landowners with prescribed fire applications.

Public land managers often conduct rehabilitation and restoration actions to achieve desired conditions or specific natural resource objectives. These “land treatments” include a variety of techniques, such as biomass removal or manipulation, seeding, and herbicide application. Limited information exists on the costs of conducting many common types of land treatments, but such information can be paired with treatment effectiveness data to prioritize application of limited resources where they may have the greatest benefit and improve efficiency. Here, we investigated cost information recorded in the Land Treatment Digital Library, a catalog of legacy land treatment information on public lands managed by the U.S. Department of the Interior's Bureau of Land Management. Based on 1,701 treatment records across eleven western U.S. states, we developed empirical per-acre cost estimates for representative land treatments in eight categories: three seeding categories (aerial seeding, drill seeding, and seedling planting), prescribed burning, soil disturbance, soil stabilization, vegetation disturbance, and weed control. We evaluated spatio-temporal factors that may be associated with variation in treatment costs and found strong evidence for nonlinear decreases in per-acre costs as treatment areas increased and that per-acre treatment costs have increased in real terms in recent decades. We also found evidence that per-acre costs for drill seeding, prescribed burns, and soil stabilization increased with the average slope of the terrain of a treated area and that per-acre costs for prescribed burns, seedling planting, and soil stabilization were influenced by distance to urban areas or major roads. These results can inform planning, prioritization, and assessment of common land treatments on public lands in the western United States, in particular supporting greater consideration of costs and cost effectiveness.

The use of drones has increased in recent years for monitoring and managing rangelands. High-resolution cameras and improved sensors provide an opportunity to investigate pasture-scale sampling methodology as an operational approach to estimate forage mass on rangelands using canopy height models derived from drone data. Our objectives were (1) to compare double sampling and vegetation clipping methods with very fine 3D data derived from drone-based imagery, (2) to compare forage mass estimation between methods using different numbers of drone-derived samples, and (3) estimate time efficiency of each one of these methods. To accomplish this, we acquired drone imagery in a 1 060-ha pasture in the South Texas Plains ecoregion in June 2020. We used two different pixel sizes for the drone image acquisition: 1.5 cm (50 m above ground level [AGL]) and 3.0 cm (100 m AGL). We compared six forage mass sampling approaches: double sampling (DS-ground), vegetation clipping (VC-ground), drone-double sampling at 50 m (drone-DS50) and 100 m (drone-DS100) AGL, and drone-vegetation clipping at 50 m (drone-VC50) and 100 m (drone-VC100) AGL. We generated 100 and 500 digital samples per site (total 700 and 3500 digital samples) to compare our estimates. Simple linear regression analyses were used to evaluate relationships between drone derived vegetation volume and the forage mass derived from DS and VC. We compared three sampling sizes: 70 field-based quadrats, 700, and 3,500 digital samples. Drone-VC50 with 700 5818 ± 78 kg · ha^-1) and 3,500 (5653 ± 34 kg · ha^-1) samples provided the smallest forage mass estimations at a large-pasture scale. Number of samples.h^-1 increased from 22 to 52 with the DS methods and 1.2 to 38 with the VC methods. Our results suggest that a combination of DS and VC with drone data collection could be a reliable approach for future drone-based forage estimation.

Many beef producers in commercial rangelands rely on cow-calf operations. Unlike stocker operations, which typically seek to increase the weight of each animal over a grazing season, cow-calf producers often consider maternal productivity—the performance of both dam and calf—which affects a cow's lifetime reproductive output and longevity. Generally speaking, longer productive lives for cows reduce herd turnover and decrease costs for the producer. As rangeland grazing management strategies are evaluated, it is important also to consider their effects on maternal productivity, not just season-long weight gains. We compared 3 yr of cow and calf weight gains by dam age class to inform how patch-burn grazing, continuous grazing without fire, and rotational grazing might affect maternal productivity in an experimental Angus cow-calf herd in central North Dakota, United States. Overall, grazing management strategy explained variation in weight gain among cows, and dam age class explained variation in calf weight gains, leading us to conclude that mature cows (those with 4+ calves) on patch-burning and continuously grazed pastures had higher maternal productivity than cow-calf units on rotational grazing. When considered alongside previously published evidence that burned areas provided approximately twice as much net energy for maintenance, our data suggest that maternal productivity might be greatest among mature cows on patch-burned pastures, but this remains speculative until the actual intake of metabolizable energy for each cow-calf unit can be determined. These findings contribute further evidence of the potential for marginal gains to be found in grazing burned rangeland, with potentially direct positive effects on the financial viability of cow-calf operations.

Wild boar (Sus scrofa) is a widespread megaherbivore that can intensively disturb large areas of its habitat both in its native and non-native ranges, when populations reach high densities. The main problem is its rooting habit, which entails intensive disturbance of the topsoil and herbaceous layer. The extent of concomitant habitat degradation varies across ecoregions; some ecosystems are rather resilient, although the damages are long-lasting in others. In mown meadows, a secondary problem is the inability to resume mowing due to the uneven soil surface of rooted patches. This can lead to both economic loss and a loss of management-dependent biodiversity. We assessed the short-term effects of rooting on vegetation cover and composition in central European permanent hay meadows and tested the utility of manual soil surface resmoothing to enable the continuation of mowing. We found that rooting increased bare soil surface but vegetation recovery occurred within a year. Similarly, high resilience was found for species composition. We could not detect any difference between rooted and intact grassland patches after 1 yr. This short-term perturbation of the composition could be associated with a temporary decrease in grassland specialist species and an increase in ruderal and pioneer species. Soil surface resmoothing was an additional disturbance, but vegetation cover returned to the level of intact grasslands within a year. Vegetation composition needed a slightly longer time (2 yr) to recover than that without resmoothing. We thus recommend the application of manual resmoothing in hay meadows with high short-term resilience to rooting, but a risk of long-term degradation (e.g., shrub encroachment) if mowing is not resumed. In hay meadows with lower resilience (because of, e.g., steep slopes), resmoothing should be applied with caution and may be supplemented with seeding to support the recovery of the vegetation and prevent soil erosion.

The invasive annual grass medusahead (Taeniatherum caput-medusae [L.] Nevski) degrades the ecosystem function throughout the sagebrush biome of the western United States. Currently, there are knowledge gaps regarding the fecundity of medusahead and the ability of defoliation treatments (grazing and mowing) to reduce annual seed production. Our research aimed to 1) determine if the timing of defoliation impacts the quantity of seeds produced, and 2) evaluate the impacts of defoliation on the viability of medusahead seeds produced. We used a randomized complete block design (n = 20) in a near-monoculture of medusahead located in southeast Oregon to assess the effectiveness of defoliation three times (November, March, and May) against a nondefoliated control from 2019 to 2022. Outcomes included gross seed production, germination statistics, and a linear regression to rapidly estimate seed production dependent on inflorescence length. We found no evidence that defoliation in November or March reduced seed production relative to the control in all years (P > 0.05). However, the May defoliation produced fewer seeds than the control in all 3 yr (P < 0.05). Defoliation of medusahead had no impact on the viability of seeds produced, with mean germination rates >80% in all treatment-year combinations. Findings did indicate that the number of seeds produced per tiller is strongly correlated with the length of inflorescence (R² = 0.856), indicating that a generalized equation could be used to rapidly assess seed production in future works. The results of this study demonstrate that the effectiveness of defoliation is temporally limited and that the most effective treatments may still fail to reduce seed production by a meaningful degree. These findings indicate that defoliation treatments may be most effective included as a part of multifaceted, ecologically based treatments to effectively manage medusahead in the sagebrush biome.

Invasive annual grasses (IAGs) represent an unprecedented threat to native plant communities in rangeland ecosystems, displacing native vegetation, altering fire regimes, affecting wildlife species that depend on native perennials for food and shelter, and causing immense economic costs. Remote sensing allows the monitoring of IAGs through multispectral imagery, using phenological differences to separate invasive species from native vegetation. Our research goal was to evaluate the use of high-frequency, moderate-resolution multispectral Planet imagery and machine learning in detecting IAG species – specifically ventenata (Ventenata dubia [Leers] Coss.), medusahead (Taeniatherum caput-medusae [L.] Nevski), cheatgrass (Bromus tectorum L.), and Japanese brome (Bromus japonicus Thunb.). Our research questions were: 1) do IAG species groupings influence remote detection rates? and 2) can high spatio-temporal resolution imagery accurately identify IAG response to large-scale herbicide applications? Ventenata was best represented in our invasive grass training data and by classification models and accuracy indices. Models detected differences in IAG presence likelihood in pastures treated aerially with indaziflam at 73 g · ai · ha–¹ and untreated pastures, even in treated locations where no ground mapping took place. This suggests the possibility of extending these invasive grass prediction models beyond ground-mapped training areas in similar mixed-grass prairie environments to increase the efficiency of IAG monitoring.