Despite decades of study, current research on grazing management’s impacts on ecosystem health and its socioeconomic drivers remains too limited in scope and scale to enable adaptive, evidence-based decision making by producers. There is a pressing need for interdisciplinary research that collects ecosystem data at broader spatial and temporal scales while incorporating working farms and ranches. Such efforts are critical for informing grazing decisions and understanding grazinglands’ potential to deliver ecosystem services, including climate mitigation, water cycling, resilience, and rural livelihoods. The Metrics, Management, and Monitoring (3M) project addresses this need through a novel social-ecological framework that integrates biophysical, socioeconomic, and management data across U.S. grazinglands. The project combines controlled experiments at four intensively monitored “hubs” with data from 59 producer-managed farms and ranches. Its core objectives are to: (1) assess the social-ecological health of grazinglands across diverse ecoregions, (2) refine monitoring approaches to improve scalability and accuracy, and (3) integrate producer-led data to balance experimental rigor with real-world relevance. Over 50 scientists collaborate on 3M to evaluate how grazing strategies affect soil carbon, water dynamics, CO₂ fluxes, plant communities, productivity, social wellbeing, and producer economics. These insights support the development of ecosystem models and decision-support tools to help producers make evidence-based choices. Beyond data generation, 3M offers a scalable research model that bridges ecological and social sciences to support adaptive, informed grazing management. This integrated framework provides a transferable template for studying any working landscape where human and ecological systems are deeply interconnected.

Advances in on-animal sensors and remote sensing have generated vast data streams, but their impact on rancher decision-making remains limited due to fragmented and uncoordinated efforts. Integration of on-animal monitoring with remote sensing of the grazing resource base offers synergistic potential to assess, in near-real time, grazing behaviour metrics and animal health, thereby enhancing animal performance and improving vegetation conditions through adaptive grazing management. For example, ranchers could use this integration to match the spatio-temporal distribution of grazing animals more effectively across landscapes with available forage quantity and quality. Precision technologies support targeted grazing to achieve ecological goals such as invasive species control, fire break creation, and improved vegetation structure for wildlife-livestock coexistence. Integrating precision technologies show promise, but adoption is hindered by barriers including data accuracy, sensor durability, connectivity, high costs, and the need for effective data integration into decision-support tools. Co-production research efforts with ranchers are essential to bridge the gap between data and decision-making, thereby enabling adaptive grazing strategies that reduce labor inputs and improve both economic and ecological outcomes for ranchers.

Grazing lands cover approximately one-third of the contiguous United States, support much of the nation's beef production, and are an important component of the U.S. terrestrial carbon budget. In this study, we quantified net ecosystem carbon balance (NECB), the net status of grazing lands as a carbon sink (C-sink) or source (C-source) and a key determinant of soil health and productivity. Our primary objective was to synthesize multiple years of annual NECB across heterogeneous grazing lands across the continental U.S and evaluate annual NECB against physical drivers (mean annual precipitation (MAP), mean annual temperature (MAT), vegetation, and moisture condition) and management practices (grazing pressure index (GPI) and fertilization history). We hypothesized that (1) NECB is higher in mesic and fertilized grasslands; (2) NECB increases with MAP and MAT but decreases with GPI; and (3) interactive effects exist among MAP, MAT, and GPI. Using carbon fluxes measured by eddy covariance towers and methane emissions including both enteric methane and manure derived from stocking rates across seven USDA Long-term Agroecosystem Research Network sites, we found: (1) grazing lands were a C-sink or carbon neutral at most sites; (2) vegetation type, moisture conditions, or fertilization had no significant effect on NECB; (3) NECB increased with MAP and MAT, but decreased with a higher GPI; and (4) MAT had a significant positive effect on NECB when MAP exceeded 750 mm (greater water availability). The effect of GPI on NECB was significantly negative when MAP was below 1000 mm, significantly negative when MAT < 12 °C and significantly positive when MAT > 16 °C. Thus, most grazing lands in our study acted as C-sinks unless water deficit, low temperature, or heavy grazing were interactively present. Understanding how climate and management influence NECB of grazing lands is key to maintaining resilient agroecosystems that secure beef production and sustain rural prosperity.

Rangelands are a critical forage base for the livestock industry and provide ecosystem services such as open space preservation, wildlife habitat, and biodiversity. However, few long-term grazing studies have quantified the economic trade-offs associated with implementing conservation-oriented grazing systems at operational ranch scales. This study evaluated the profitability of traditional range management (TRM; continuous season-long grazing) compared to collaborative adaptive rangeland management (CARM; a stakeholder-driven adaptive rotational system) using yearling steers over a 10-year period (2014–2023) at the Central Plains Experimental Range (CPER) in a semiarid, shortgrass steppe of northeastern Colorado. We used steer weight gain data, historical Colorado cattle prices, and system-specific labor and infrastructure costs to determine economic outcomes for TRM and CARM. A Monte Carlo simulation (100 000 iterations) based on historical livestock price distributions was used to calculate annual and 10-year total net revenue and returns to labor and management for both grazing strategies. TRM was more profitable with an 8.8% higher mean net ($884 749) compared to CARM ($812 655). Further, total forecasted returns to labor and management was 78.4% higher ($243 889) for TRM compared to CARM ($136 715) due to decreased animal performance and higher infrastructure costs with CARM. While CARM improved some ecosystem service outcomes, such as increased vegetation heterogeneity, shrub cover, and maintenance of viable habitats for several native grassland bird species of conservation concern, the grazing strategy reduced livestock production and relative profitability. These findings confirm that intensive rotational systems may carry financial trade-offs under typical market and climate conditions in the semiarid shortgrass steppe. This research is relevant to ranchers because it quantifies the cost of achieving ecologically beneficial outcomes through adaptive rotational grazing. Further, it provides insight for ranchers considering system changes and policymakers aiming to design incentives that reflect both the benefits and costs of conservation oriented grazing management on working rangelands.

Drought and invasive species are threats to primary productivity in grassland ecosystems worldwide. A central challenge in ecological restoration is establishing plant communities that can withstand these abiotic and biotic stressors. We tested the efficacy of a trait-based framework for enhancing drought tolerance and invasion resistance in experimental restorations of contrasting grassland systems, a perennial mixed-grass prairie in Wyoming and annual interior grassland in California. Each experiment included four trait-based seeding treatments: drought tolerant, invasion resistant, functionally diverse, and a random control. All seeded communities were subjected to extreme precipitation reduction (-50% annual) and invasion by non-native annual grasses. We asked two questions: (1) Can we establish communities from seed that meet and maintain these desired trait-based targets? (2) Did the trait-based seeding treatments tolerate extreme precipitation reduction or resist invasion by non-native annual grasses? Based on analyses of compositional dissimilarities, we found trait-based restoration targets were more difficult to maintain in an annual-dominant grassland rather than in a perennial-dominant one, and targets composed of multiple community-weighted mean traits were more difficult to meet than targets that maximized functional diversity. In both grasslands, plant communities with drought-tolerant traits maintained growth rates under reduced precipitation, but these effects diminished after multiple years of drought and during drought release. This highlights the importance of including a diversity of strategies when restoring plant communities. Our proposed invasion-resistant traits did not consistently reduce non-native annual grass establishment, but communities with traits that conferred drought tolerance were the most effective at resisting invasion, suggesting that similar traits enhance drought tolerance and resist invasion in these grasslands. Our findings indicate that restored plant communities with high functional diversity may be able to respond to variable conditions better than communities with traits designed to meet specific restoration objectives. The results from this restoration experiment suggest that our understanding of the traits underlying drought tolerance is better than our understanding of the traits underlying invasion resistance. However, if drought tolerance enhances competitive ability in arid and semiarid grassland ecosystems, then physiological theories of resource use can be applied to enhance invasion resistance.

Adaptive, multi-paddock (AMP) grazing often involves a form of rotational grazing at high stocking densities with short grazing periods (days to weeks) during the growing season followed by a longer (months) nongrazed time for vegetation regrowth. Despite positive ecological benefits resulting from AMP, livestock production and resultant economic returns are reduced in semiarid rangelands, prompting this investigation into the conditions associated with differences in livestock weight gains under different grazing strategies in these rangelands. We used data from the decadal (2014-2023) Collaborative Adaptive Rangeland Management (CARM) experiment in the semiarid shortgrass steppe of the western Great Plains. For all 6 years (2014-2019) when CARM experienced the highest stock density (10-fold greater than traditional season-long grazing; hereafter TRM), CARM steers had lower grazing season weight gains and beef production than TRM steers (mean reduction of 13.2%). When CARM stock density was reduced 50% (still 5-fold greater than TRM) in 2020-2023, mean weight gains and beef production across the 4 years were just 1% lower in CARM than TRM. In the year with near normal forage production (2021), weight gains and beef production were 10% lower in CARM than TRM, but we did not observe differences between CARM and TRM when forage was limiting in 2 drought years (2020 and 2022), nor when forage production was extraordinarily high (2023). Our findings indicate grazing management practices have the strongest influence on weight gains when forage quantity is moderate, and the effects of management are reduced when forage quantity is very low or very high. This ten-year experiment provides additional evidence that in semiarid rangeland ecosystems, adaptive rotational grazing practices can be associated with a tradeoff between livestock production and the provisioning of other ecosystem services such as grassland bird habitat. Alternative management strategies may be needed for ranchers to minimize this tradeoff. Published by Elsevier Inc. on behalf of The Society for Range Management. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)

Near-real-time mapping of vegetation using satellite imagery is becoming increasingly common and valuable across a wide range of ecosystems. The availability of large datasets has led many researchers to complex machine learning algorithms (MLAs) to train satellite models. However, complex MLAs may underperform for the inherently extrapolative applications required for real-world vegetation monitoring. We used a dataset of nearly 10,000 training samples of standing herbaceous grazingland biomass collected over ten years to train progressively more complex MLAs, test them across progressively more extrapolative cross-validation (CV) groupings, and evaluate their transferability and consistency. The performance of all MLA's decreased substantially when tested against more extrapolative CV groupings. The commonly used approach of random k-fold CV produced overly optimistic performance (R2: 0.71-0.78) compared to a more realistic task of predicting for an unseen year (R2: 0.49-0.54). Simpler MLAs, such as partial least squares regression, were more consistent and outperformed complex MLAs for the most extrapolative tasks, and performance was less sensitive to the distinctness of unseen test data. We conclude that random k-fold CV likely produces unrealistically optimistic expectations for real-world applications of satellite vegetation models, and could be associated with major prediction misses when models are used in novel environmental conditions.

Rangelands in semiarid climates experience dramatic spatial and temporal variability in precipitation, which drives variation in forage production and plant species composition. With such variability, effects of grazing management on vegetation may only be detectable over long time periods. We examined the degree to which collaborative, adaptive, multipaddock rotational grazing management (CARM) influenced vegetation relative to traditional season-long continuous grazing management (TRM) over a decade in the semiarid shortgrass steppe. CARM herd(s) grazed paddocks dominated by C3 graminoids (Sandy Plains) early and late in the growing season and primarily grazed paddocks dominated by C4 grasses (Loamy Plains) during the middle of the season. Current growing season conditions determined the exact timing of rotations. Additionally, CARM incorporated periodic season-long rest (without grazing) for select paddocks. On the Loamy Plains, CARM increased cover and production of C3 relative to C4 graminoids, beginning in year 5 and persisting through year 10. Multivariate analyses identified Pascopyrum smithii, Hesperostipa comata, Elymus elymoides, and Carex duriuscula as the C3 species and Bouteloua gracilis and Bouteloua dactyloides as the C4 species responsible for the shift on Loamy Plains. In contrast, on the Sandy Plains, CARM had no detectable effects on herbaceous plants, whereas cover of the shrub Atriplex canescens increased in CARM relative to TRM. Sustained shifts in grazing timing (associated with the rotation sequences) across years altered the relative abundance of perennial grasses on Loamy Plains; however, these shifts were offsetting such that total forage production was unaffected. Our findings can be explained by the greater sensitivity of C3 versus C4 perennial graminoids to early-season grazing and highlight challenges associated with enhancing forage production via multipaddock rotations in semiarid rangelands. The degree to which vegetation compositional changes are desirable depends on paddock-scale and ranch-scale management objectives, as well as the composition of the landscape in which the livestock are managed.

Monitoring free-ranging livestock foraging behaviour and health with on-animal sensors has emerged as a potential means to enhance adaptive management for ranching operations. We evaluated the use of GPS collars collecting animal locations at 5-min intervals and estimating activity (grazing, walking, or stationary) via a 3-axis accelerometer to quantify foraging behaviour of lactating Bos taurus beef cows with calves on a similar to 7600 ha working ranch in a sagebrush grassland ecotone in northeast Wyoming. We used this sensor data to quantify five metrics of foraging behaviour at a daily time step including (1) mean velocity while grazing (VG), (2) mean grazing bout duration (GBD), (3) mean turn angle while grazing (TAG), (4) total daily grazing time (TTG) and (5) total daily travel distance (TD), and related these metrics to measurements of cattle diet quality, weight gain, and stock density. While foraging behaviour metrics varied among individual cows, we found that daily estimates of VG, GBD, TAG and TD were all significantly related to stock density and variation in remotely-sensed estimates of dietary crude protein content. Over longer time periods of weeks to months, cattle diet quality and weight gain were significantly related to VG (positive correlation; R-2 = 0.42 - 0.87), and GBD (negative correlation; R-2 = 0.58 - 0.78). These findings indicate that ranchers have the ability to influence diet quality and animal performance via (1) the rotation of herds among pastures of varying composition and quality, and (2) changes in herd size relative to pasture size (i.e., animal density). Furthermore, our results indicate there is substantial potential utility for near-real-time monitoring of foraging behaviour as an indicator of animal performance via the combination of GPS tracking, accelerometer data, and a method to wirelessly transmit data to the internet. However, operationalizing such a system will likely depend on continuing improvements in sensor durability and data management efficiency, and reductions in sensor and data transmission costs.

Semiarid rangelands constitute nearly 30 % of the world's grassland ecosystems and livestock grazing is the most widespread land use in these ecosystems. These semiarid rangelands provide a variety of ecosystem goods and services, many of which may depend on soil health. While advances have been made with indicators of soil health for croplands, similar efforts for rangelands are lacking. The North American Project to Evaluate Soil Health Measurements (NAPESHM) sampled soils to 15 cm from long-term (>= 40 years) grazing treatments spanning a range of grazing intensity (ungrazed to heavy grazing) in two semiarid rangelands, shortgrass steppe (SGS) and northern mixed-grass prairie (NMP), in fall 2019. Soils were analyzed for chemical (permanganate oxidizable carbon [POXC] and soil organic carbon [SOC]), biological (mineralizable soil carbon [MinC], phospholipid fatty acids [PLFA], ACE protein, and beta-glucosidase enzyme activity [BG]), and physical (saturated hydraulic conductivity [SHC], available water capacity [AWC], and aggregate stability) indicators of soil health. Light particulate organic carbon and mineral associated organic carbon fractions were also analyzed at the SGS. Additionally, annual net primary productivity and the relative production of warm-vs cool-season grasses were evaluated from 2010 to 2019. Soil health responses to grazing intensity treatments in these two semiarid rangeland ecosystems were generally inconsistent across and within chemical, biological, and physical indicators. For instance, POXC and SOC differed between the two rangeland ecosystems, but neither soil health response within a site was significantly affected by grazing intensity. MinC and saturated hydraulic conductivity consistently decreased as grazing intensity increased in both rangeland ecosystems, while all other biological and chemical indicators were either 1) solely influenced by rangeland ecosystem type, 2) the interaction between rangeland ecosystem and grazing intensity, or 3) unaffected by rangeland ecosystem or grazing intensity. At SGS, delta 13 C values of both organic carbon fractions became less negative as grazing intensity increased, consistent with a greater proportion of warm-season perennial grasses and lower proportion of cool-season grasses. Our results suggest that generalizations about the effects of multi-decadal grazing intensity gradients in western Great Plains semiarid rangelands in North America on chemical, biological, and physical indicators of soil health remain elusive.

Here, we present a first assessment of the US Department of Agriculture’s (USDA) “Grass-Cast Southwest,” which is a forecasting tool for rangeland aboveground net primary productivity (ANPP) for the southwest region of the United States. Our results show that ANPP forecasts in early April were relatively close to the observation-based ANPP estimates in late May for all years evaluated ( R = 0.6–0.9). The relatively high predictability of spring rangeland productivity in this region is likely because it is strongly driven by antecedent winter/early spring precipitation. Conversely, the first summer forecasts produced in June did not consistently predict the final observation-based ANPP estimates in late August ( R = −0.5–0.7), likely because summer rangeland productivity in this region is highly dependent on variable, less predictable precipitation from the North American Monsoon (NAM). Antecedent El Niño Southern Oscillation (ENSO) indices could be used to improve Grass-Cast Southwest performance in both the spring and summer. The ENSO JFM (January–March) index was significantly positively correlated with rangeland productivity during the spring season, whereas ENSO MAM (March–May) was significantly negatively correlated with rangeland productivity during the summer season.

Ranchers in the western Great Plains grazing yearlings (i.e., stockers) during the growing season need to understand how variation in starting animal weights influences subsequent end weights for marketing opportunities and prices received. Whether variation in stocker steer body size (i.e., entry weight) at the start of the growing season influences weight gains during the summer grazing (midMay through September), period on semiarid shortgrass prairie rangeland remains unclear. We used 10 yr (2014-2023) of weight gains from 2 162 stocker steers ( Bos taurus ) that had entry weights ranging from 222.7 to 370.0 kg to assess if grazing season weight gains under traditional, season-long grazing management with moderate stocking rate were influenced by entry weights under varying levels of spring (April through June) precipitation and pasture forage productivity (low vs. high productivity soils). Entry weight had no effect on grazing season weight gains regardless of precipitation level and soil type (as measured by ecological site). Stocker operations in this rangeland can anticipate steer weight gains of 135 kg steer-1 under average precipitation and forage productivity. Summer grazing season weight gains did exhibit a quadratic relationship between spring precipitation and pasture productivity. A 25% reduction in spring precipitation decreased weight gains by 16% and 23% in the high and low productivity pastures, respectively; 50% reduction in spring precipitation lowered weight gains by 40% and 55%, respectively. Conversely, increasing spring precipitation by 50% increased weight gains by only 15% and 20% in the high and low productivity pastures, respectively. These findings highlight that abundant precipitation can result in substantial forage production, but forage quality reductions will limit additional weight gain. The plateau in steer weight gain when April to June precipitation exceeds 170 mm suggests that forage quality limitations could potentially be ameliorated by strategic protein supplementation. Published by Elsevier Inc. on behalf of The Society for Range Management. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ )

We examined the spatial movement behavior, growth rates, and enteric CH4 emissions of yearling beef cattle in response to spatial distribution management with virtual fencing (VF) in extensive shortgrass steppe pastures. Over the 110-d grazing season (mid-May to early September), 120 British-breed stocker steers (~12 months of age; mean body weight [BW] 382 kg ± 35) were grazed with VF management (active VF collars) or free-range (non-active VF collars) in two pairs of ~130 ha physically fenced rangeland pastures (i.e., VF-managed vs. control). One pair was associated with a diverse mosaic of soil types supporting alkalai sacaton (Sporobolus airoides [Torr.] Torr.), blue grama (Bouteloua gracilis [Willd. Ex Kunth] Lag. Ex Griffiths), and needle-and-thread (Hesperostipa comata [Trin. &Rupr.] Barkworth), while the other pasture-pair was associated with the Sandy Plains ecological site, primarily hosting western wheatgrass (Pascopyrum smithii [Rydb.] Á. Löve), needle-and-thread, and blue grama. Within each pair of pastures, one herd was rotated among sub-pastures using the VF system, which focused grazing on varying native plant communities over the growing season. In control pastures, steers had access to the entire pasture for the grazing season. Spatial distribution management with VF maintained steers within desired grazing areas occurred 94–99% of the time, even though five of the 60 VF-managed steers consistently made short daily excursions outside the VF boundary. In all four pastures, an automated head-chamber system (AHCS, i.e., GreenFeed) measured the enteric CH4 emissions of individual steers. Steers that met the criteria of a minimum of 15 AHCS visits in each of at least two VF rotation intervals were analyzed for spatial behavior, growth performance, and enteric CH4 emissions. Screening based on AHCS visitation requirements resulted in 15 steers (nine VF, six control) in the diverse mosaic pasture pair, and 39 (17 VF, 22 control) in the Sandy Plains pasture pair. VF management significantly reduced growth rates for all steers across both pasture pairs by an average of 9%, resulting in steers that were 7.3 kg lighter than unmanaged steers at the end of the grazing season. VF management effects on enteric CH4 emissions varied among rotation intervals and pasture type. In the diverse mosaic pair, VF management significantly reduced CH4 emissions during the first rotation interval, when VF steers were concentrated on the C3 grass-dominated plant community, but increased emissions in the second and third intervals when VF steers were concentrated on C4 grass-dominated areas. In the Sandy Plains pasture pair, where cattle were rotated between sub-pastures with and without palatable four-wing saltbush (Atriplex canescens [Pursh] Nutt.) shrubs, VF management reduced CH4 emissions in three of four rotations as well as over the full grazing season. CH4 emissions intensity increased with VF management in the diverse mosaic, but not in the Sandy Plains pastures. Overall, our findings show VF management (1) controlled animals spatially within sub-pastures, (2) did not improve growth performance but rather decreased it, (3) did not consistently reduce enteric CH4 emissions, and (4) tended to increase emissions per kg of product via lowering steer growth performance. While some have posited that VF is a potential tool to reduce enteric emissions, our findings suggest VF management is not a straightforward solution for mediating the relationships between forage resources, growth performance, and enteric CH4 emissions of stocker steers on extensive rangeland. Furthermore, our fusion of animal GPS tracking, growth rates and AHCS data indicated that differences in spatial behavior and weight gain were consistent between VF-managed and control steers irrespective of their AHCS-acclimation status, supporting the perspective that AHCS-based gas flux measurements are a valid means of estimating enteric emissions in extensive rangelands.

Phenological differences between native and invasive plants can facilitate invasion, but can also be targeted by management. In the western Great Plains of North America, the invasive annual grasses Bromus tectorum L. (cheatgrass) and B. arvensis (field brome) begin and end growth earlier than native competitors, providing an opportunity for targeted grazing. However, managers need to know when grazers preferentially consume or avoid annual bromes. We implemented spring targeted grazing for 4 years and quantified temporal cattle consumption patterns at two mixedgrass prairie sites in Wyoming and Nebraska, USA. We used fecal DNA metabarcoding to measure consumption of annual bromes and coexisting native species twice per week. Concurrently, we measured plant phenology, forage quality, and biomass. Within years, brome consumption was predicted effectively using two phenological metrics- plant height and days after seed maturation. Targeted grazing windows, defined as periods with >= 75% of maximum cattle consumption within a year, started when bromes were 9.3 cm (+/- 3.6 SD) tall, ended one day (+/- 4 SD) after seed maturation, and lasted 38 d (+/- 11 SD). Cattle diet quality remained high throughout these grazing windows. Across years, brome consumption ranged from 19% to 55% of total graminoid consumption, and was consistently higher in years when annual bromes grew taller before flowering. Although cattle typically selected for native perennials over annual bromes, spring targeted grazing reduced brome seed production by 30-77% relative to adjacent pastures where grazing began later. These results indicate that simple phenological metrics can predict cattle consumption of bromes during spring, both within and among years. Carefully timing grazing to align with consumption should help managers to control annual bromes and restore native mixedgrass prairie plant communities. More broadly, combining temporal analyses of livestock diets and plant phenology can be useful for precisely targeting grazing of invasive species. Published by Elsevier Inc. on behalf of The Society for Range Management.

Matching animal demand to forage availability is a core principle in sustainable rangeland management. We evaluated the use of interannual flexibility in stocking rates compared with fixed stocking at light, moderate, and heavy stocking rates on livestock weight gains and economic responses for 7 yr (2016−2022) in North American northern mixed-grass prairie. The grazing season began in early June each year, so stocking rates in the flexible treatment were calculated on the basis of the amount of forage production predicted from actual precipitation received in April and May combined with long-term mean annual precipitation received at the study site in June, as well as an adjustment in stocking rate based on the amount of residual forage remaining at the end of the previous grazing season. Across years, mean stocking rate for the flexible stocking treatment (32.5 animal unit days [AUD] ha−1) was between heavy (38.6 AUD ha−1) and moderate (29.7 AUD ha−1) and was twice as high as the light (15.8 AUD ha−1). Cumulative total beef production for the 7 yr was highest with heavy stocking (282.6 kg ha−1), 17% less in the flexible (234.2 kg ha−1), and 19% less in the moderate (229.4 kg ha−1) stocking rates. It was 55% lower with light stocking (128.4 kg ha−1). Crude protein and digestible organic matter, as well as composition of plant functional groups in diets of yearlings, did not differ between the moderate versus the flexible stocking treatments. Compared with moderate stocking, flexible stocking resulted in 6.9% lower cumulative gross ($2 299) and 10.8% lower net ($1 407) economic returns per yearling. We suggest that future evaluations of flexible stocking strategies consider incorporating seasonal forecasts combined with intraseasonal adjustments in stocking rates as the growing season unfolds. Advancements in predictive forage forecasting tools and remote sensing capabilities are needed to support such a strategy.

Geyer larkspur is a native perennial forb that is toxic to cattle. Herbicide control of Geyer larkspur is variable and depends on the growth stage of the plant when the herbicide is applied. The objectives of this study were to 1) evaluate aminopyralid, aminopyralid + florpyrauxifen-benzyl, aminopyralid + 2,4-D, aminopyralid + metsulfuron-methyl, metsulfuron-methyl, triclopyr, and triclopyr + 2,4-D for efficacy in controlling Geyer larkspur; 2) determine whether plant growth stage (vegetative or flowering) at the time of herbicide application influences herbicide effectiveness; and 3) determine whether herbicide treatment alters the norditerpenoid alkaloid content of Geyer larkspur. Plots were established in eastern Wyoming in 2021 and northern Colorado in 2022. Herbicide application at the different phenological stages did not affect Geyer larkspur density at the Wyoming site (P = 0.1065; data not shown). Geyer larkspur density at the Wyoming site was reduced by all herbicide treatments 1 yr after treatment (YAT) at the vegetative stage and by all herbicides except triclopyr 2 YAT (P = 0.0249). Geyer larkspur density at the flowering stage was reduced by all herbicides except metsulfuron-methyl, triclopyr, and triclopyr + 2,4-D at 1 YAT and by triclopyr and triclopyr + 2,4-D at 2 YAT. In contrast, there were no differences in Geyer larkspur density across treatments at the Colorado site (P = 0.9621). Precipitation was below average several months prior to herbicide application, which may have affected herbicide effectiveness. The metsulfuron-methyl treatment resulted in the highest total alkaloid concentrations of Geyer larkspur at the vegetative stage and the lowest concentrations at the flowering stage at the Wyoming site. Efforts to control Geyer larkspur in semiarid rangelands can be effectively accomplished by applying aminopyralid herbicides at either the vegetative or flowering growth stage provided environmental conditions prior to herbicide application are sufficient for plant growth and uptake of the herbicide.

New satellite-based Remote Sensing (RS) data products provide near-real time vegetation monitoring capacities and potentially offer valuable insights to land managers. Since RS data products are rapidly evolving, it is important to understand what each product measures or estimates. Misinterpretations of the data products can lead to ineffective management decisions. In ecosystems with dynamic vegetation cover such as rangelands, grasslands, and savannas, it is particularly important to understand the key differences between estimates of standing biomass and Aboveground Net Primary Production (ANPP). We have three main objectives for this perspective paper: (1) clarify how ANPP and standing biomass differ, (2) examine how management can affect differences between ANPP and standing biomass in a systematic way; and (3) discuss why these differences matter in the context of using newly available RS data products for making decisions and monitoring outcomes. In this paper we clearly define important terminology used in ANPP and standing biomass RS data products and provide illustrative examples, equations, and simulated data to clarify the relationship between ANPP and standing biomass. The most important difference is that ANPP is a rate (biomass produced per unit of time) while standing biomass is a stock (the mass of vegetation present at a specific time). While RS data products provide accessible information about both metrics, it is critical to understand their distinct implications for land management. Equipped with a clear understanding of these key ecological concepts, users will be better informed to choose appropriate RS data products for specific management applications.