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Context Technologies are now available to continuously monitor livestock foraging behaviours, but it remains unclear whether such measurements can meaningfully inform livestock grazing management decisions. Empirical studies in extensive rangelands are needed to quantify relationships between short-term foraging behaviours (e.g. minutes to days) and longer-term measures of animal performance. Aims The objective of this study was to examine whether four different ways of measuring daily foraging behaviour (grazing-bout duration, grazing time per day, velocity while grazing, and turn angle while grazing) were related to weight gain by free-ranging yearling steers grazing semiarid rangeland. Methods Yearling steers were fitted with neck collars supporting a solar-powered device that measured GPS locations at 5 min intervals and used an accelerometer to predict grazing activity at 4 s intervals. These devices were used to monitor steers in four different paddocks that varied in forage biomass, and across two grazing seasons encompassing a wide range of forage conditions. Steer weight gain (kg/steer.day) was measured in each paddock during each of three ∼60 day time intervals, and daily foraging behaviours were measured during 15–21 days in each interval. Results A model based on only two daily measurements of foraging behaviour, mean grazing bout duration (calculated at a 5 min resolution) and mean velocity while grazing explained 62% of the variation in animal weight gain. Conclusions Daily measurements of foraging behaviour vary substantially in response to varying foraging conditions in space and time, and can effectively serve as indicators of variation in cattle weight gain. Implications On-animal sensors that monitor foraging behaviour have the potential to transmit indicators to livestock managers in real time (e.g. daily) to help inform decisions such as when to move animals among paddocks, or when to sell or transition animals from rangeland to confined feeding operations.

Black-tailed prairie dogs (Cynomys ludovicianus) exhibit boom and bust cycles in landscapes where they are affected by outbreaks of plague caused by the introduced bacterium Yersinia pestis. We examined spatiotemporal dynamics of black-tailed prairie dog colonies in the Thunder Basin National Grassland, Wyoming over a period of 21 years. The colony complex experienced three plague epizootics during that time, and consequently three boom and bust cycles. The entire prairie dog colony complex collapsed over a 1-year period during the first and third epizootics, and over a 3-year period during the second epizootic. The boom and bust cycles were characterized by relatively rapid contractions in total area occupied by prairie dogs during a plague outbreak (e.g., >99% decline from 10,604 ha to 47 ha over 1 year [2017–2018]) followed by much slower recovery times (e.g., an increase from 410 ha to 10,604 ha over 11 years [2006–2017]). Prairie dogs occupied a total of 10,604 ha during at least one survey within the study period, but much of the area was not continuously occupied over time. We found that each of the three plague outbreaks occurred in years with highly connected prairie dog colonies and slightly above-average temperatures and summer precipitation, which were preceded by a dry year. Although plague outbreaks were associated with climatic conditions, we were unable to detect a role of climate in driving colony expansion. Our results illustrate the cyclic and extreme nature of fluctuations in black-tailed prairie dog colony size and distribution in a landscape where plague occurs and illuminate some of the drivers of these cycles. Further, our work shows how introduced diseases can dramatically influence populations of a keystone species, with important consequences for the broader ecological system.

On the Ground • Adaptive management should explicitly involve stakeholders, emphasize multiple iterations of identifying and prioritizing outcomes, and tightly link science-informed monitoring to decision-making benchmarks for effective feedback loops. • Short-term monitoring procedures should be simple, quick, and based on consistent methods that are focused on locations where meaningful change is expected or uncertainty is high. • Long-term monitoring procedures should emphasize consistent methodology across years that provides broader ecosystem context for multiple ecosystem services (e.g., watershed protection and grassland bird habitat). • Incorporating timely feedback from monitoring improves the capacity for rapid decision-making when benchmarks are attained and management should be modified.

Infectious diseases pose a significant threat to global health and biodiversity. Yet, predicting the spatiotemporal dynamics of wildlife epizootics remains challenging. Disease outbreaks result from complex nonlinear interactions among a large collection of variables that rarely adhere to the assumptions of parametric regression modeling. We adopted a nonparametric machine learning approach to model wildlife epizootics and population recovery, using the disease system of colonial black-tailed prairie dogs (BTPD, Cynomys ludovicianus) and sylvatic plague as an example. We synthesized colony data between 2001 and 2020 from eight USDA Forest Service National Grasslands across the range of BTPDs in central North America. We then modeled extinctions due to plague and colony recovery of BTPDs in relation to complex interactions among climate, topoedaphic variables, colony characteristics, and disease history. Extinctions due to plague occurred more frequently when BTPD colonies were spatially clustered, in closer proximity to colonies decimated by plague during the previous year, following cooler than average temperatures the previous summer, and when wetter winter/springs were preceded by drier summers/falls. Rigorous cross-validations and spatial predictions indicated that our final models predicted plague outbreaks and colony recovery in BTPD with high accuracy (e.g., AUC generally > 0.80). Thus, these spatially explicit models can reliably predict the spatial and temporal dynamics of wildlife epizootics and subsequent population recovery in a highly complex host-pathogen system. Our models can be used to support strategic management planning (e.g., plague mitigation) to optimize benefits of this keystone species to associated wildlife communities and ecosystem functioning. This optimization can reduce conflicts among different landowners and resource managers, as well as economic losses to the ranching industry. More broadly, our big data-model integration approach provides a general framework for spatially explicit forecasting of disease-induced population fluctuations for use in natural resource management decision-making. Thunder Basin Research Initiative; National Institute of Food and Agriculture [2020-67019-31153] Published version We are grateful to Paul Stapp, Eddie Childers, Buck Cully, Jeff Abeglen, Kristin Philbrook, Janice Naylor, Erin Considine, Andy Chappell, Jennifer Avising, Ruben Mares, Gwyn McKee, Peter McDonald, Travis Livieri, Lynne Deibel, Jessica Alexander, Daniel Kinka, Kristy Bly, Nicole Rosmarino, Tara Stephens, and numerous other biologists and field technicians for their data collection and sharing of prairie dog colony boundaries and other associated data across the Great Plains region. We thank David Eads, David Pellatz, and two anonymous reviewers for providing comments that helped to greatly improve the manuscript. This work is part of the Thunder Basin Research Initiative. Funding was provided by the National Institute of Food and Agriculture (Award no.: 2020-67019-31153). Public domain – authored by a U.S. government employee

Coverage of living (green) vegetation influences rangeland processes and biodiversity but remains a challenge to quantify at small spatial grain. We describe a technique for rapid airborne (unmanned aerial vehicle) measurements of continuous spatial coverage of living vegetation at a resolution (spatial grain) of 8 cm ground sampling distance. We then applied this technique at the pasture (paddock) scale (tens of hectares) in two contrasting grassland ecosystems (semiarid shortgrass steppe in northeastern Colorado, United States and mesic grassland in central Texas, United States) to determine effects of locally relevant grazing treatments on spatial variability and dependence (pattern) in fractional coverage of green vegetation (fractional vegetation cover; FVC). Site-specific regression models developed using reflectance in visible and near-infrared wavebands explained 90% and 89% of variance in FVC for semiarid and mesic grassland, respectively. Mean FVC was similar among shortgrass steppe pastures differing in grazing treatment (light or heavy grazing by cattle, moderate cattle grazing with prairie dogs present). In contrast, FVC was lower with rotational compared with continuous, year-long grazing in the mesic grassland. Heavy grazing in shortgrass steppe and rotational grazing in mesic grassland increased the spatial uniformity in FVC by reducing spatial variability and increasing spatial dependence in FVC, the latter by increasing the similarity in FVC values among spatially separated patches. Unmanned aerial vehicle−enabled remote sensing provides for FVC at sufficiently small spatial grain to characterize spatial variation in FVC at the pasture scale. Results can be used to evaluate the effectiveness of management actions intended to alter spatial variation in FVC to achieve conservation or diversity objectives. Enhanced capacity to monitor FVC at small spatial grain promotes adaptive management of grasslands.

State-and-transition models (STMs) are tools used in rangeland management to describe linear and nonlinear vegetation dynamics as conceptual models. STMs can be improved by including additional ecosystem services, such as wildlife habitat, so that managers can predict how local populations might respond to state changes and to illustrate the tradeoffs in managing for different ecosystem services. Our objective was to incorporate songbird density into an STM developed for sagebrush rangelands in northwest Colorado to guide local management of sagebrush birds. The STM included two shrub-dominated community phases, a native grassland state, and a shrubland and grassland phase within an exotic-dominated state. We surveyed plots for songbirds, collected a suite of vegetation indicators at each plot, and quantified songbird habitat relationships with count-based regression models. We then used the estimated models to predict songbird density based on average vegetation conditions per state or community phase. Moderate or increasing shrub cover were important predictors for shrubland-associated species, and responses to understory components varied by species. In the STM, we predicted higher densities of shrubland-associated bird species in the shrub-dominated phases and higher densities of grassland-associated bird species in the state and phase lacking shrub cover. No single state or phase captured the highest density for all songbirds, illustrating the value of alternative states. Our results also demonstrate the utility of displaying traditional wildlife count models against the range of vegetation conditions associated with each state or phase to understand how wildlife density can vary within states and phases. Our approach can assist land managers to gauge the potential impacts of land-use decisions and natural vegetation variability on wildlife, especially for species of conservation concern.

Frequent, severe defoliation reduces grass production and can alter plant species composition in grasslands. Multipaddock rotational grazing has been proposed as a grazing strategy that may reduce the frequency and intensity of defoliation on palatable grass plants without altering stocking rates. Previous studies evaluated this hypothesis using small, homogeneous paddocks and nonadaptive rotation schedules and found small and inconsistent differences between continuous and rotational grazing systems. Using a stakeholder-driven collaborative adaptive management (CAM) framework, we conducted the first ranch-scale experimental investigation into tiller defoliation patterns in the context of adaptive multipaddock rotational grazing. We monitored tiller defoliation frequency and intensity in 10 paired 130-ha pastures assigned to either a collaborative adaptive multipaddock rotational grazing treatment (CARM, one livestock herd) or a season-long continuous grazing treatment (traditional rangeland management [TRM]; 10 separate herds) in shortgrass steppe. Consistent with previous studies, we observed that frequencies of grazing and regrazing on a palatable, cool-season grass (western wheatgrass, Pascopyrum smithii) were much more sensitive to stocking rate than grazing system. Under moderate stocking rates used in both CARM and TRM treatments, roughly two-thirds of western wheatgrass tillers remained ungrazed annually, regardless of grazing system. Thus, season-long rest is present in season-long continuous and rotational grazing systems. Frequencies of tiller regrazing were low (5−15%) and similar between CARM and TRM treatments. Although defoliation patterns were similar between treatments at the whole-ranch scale, CARM enhanced spatial and temporal heterogeneity in defoliation frequencies among individual pastures. Pastures grazed earlier in the season or for longer experienced more defoliation. Managers implementing adaptive, multipaddock rotational grazing could use this heightened and predictable variability to strategically manage impacts of grazing on western wheatgrass at the individual pasture scale. The CAM model enabled our team to identify and directly address key stakeholder hypotheses and resulted in coproduction of management-relevant research.

Fauna of North America’s Great Plains evolved strategies to contend with the region’s extreme spatiotemporal variability in weather and low annual primary productivity. The capacity for large-scale movement (migration and/or nomadism) enables many species, from bison to lark buntings, to track pulses of productivity at broad spatial scales (> 1 000 km2). Furthermore, even sedentary species often rely on metapopulation dynamics over extensive landscapes for long-term population viability. The current complex pattern of land ownership and use of Great Plains grasslands challenges native species conservation. Approaches to managing both public and private grasslands, frequently focused at the scale of individual pastures or ranches, limit opportunities to conserve landscape-scale processes such as fire, animal movement, and metapopulation dynamics. Using the US National Land Cover Database and Cropland Data Layers for 2011−2017, we analyzed land cover patterns for 12 historical grassland and savanna communities (regions) within the US Great Plains. On the basis of the results of these analyses, we highlight the critical contribution of restored grasslands to the future conservation of Great Plains biodiversity, such as those enrolled in the Conservation Reserve Program. Managing disturbance regimes at larger spatial scales will require acknowledging that, where native large herbivores are absent, domestic livestock grazing can function as a central component of Great Plains disturbance regimes if they are able move at large spatial scales and coexist with a diverse array of native flora and fauna. Opportunities to increase the scale of grassland management include 1) spatial prioritization of grassland restoration and reintroduction of grazing and fire, 2) finding creative approaches to increase the spatial scale at which fire and grazing can be applied to address watershed to landscape-scale objectives, and 3) developing partnerships among government agencies, landowners, businesses, and conservation organizations that enhance cross-jurisdiction management and address biodiversity conservation in grassland landscapes, rather than pastures.

Collaborative adaptive management (CAM) is hypothesized to benefit management of rangeland ecosystems, but the presumed benefits have seldom been quantified, and never in a multipaddock rotational grazing system. Here, we evaluated average daily weight gain (ADG) of livestock (kg steer−1 d−1) in four grazing management treatments during the summers of 2016−2018 in a semiarid shortgrass steppe. These four treatments had the same stocking rate but differed in stocking densities. The three lowest stocking densities were implemented using nonadaptive grazing management, while the highest stocking density was implemented using CAM by an 11-member Stakeholder Group. Three of the four treatments used multipaddock rotational grazing. Growing season precipitation varied from drought in 2016 to near average in 2017 and dry in 2018. During nondrought years, ADG under nonadaptive grazing declined linearly as stocking density increased from low to high. This relationship was not significant during drought (2016). CAM increased absolute livestock production by 0.13 to 0.19 kg steer−1 d−1 in nondrought years, or a 23−25% relative increase in ADG. This benefit of CAM arose from the Stakeholder Group's ability to rotate cattle in response to spatiotemporal heterogeneity across the landscape—i.e., the ability to graze the “right pastures at the right time.” Multiplying the additional grazing season livestock gains achieved through CAM by the monetary value of gains ($ kg−1) resulted in an estimated additional gross revenue return from CAM of $48.16 to $55.54 per steer annually, as compared with revenues from nonadaptive multipaddock rotational grazing under nondrought conditions. These results indicate that CAM, supported with substantial and timely monitoring data, can minimize decreases in livestock production associated with high stocking densities used in multipaddock rotation systems. However, in this experimental context, the economic benefits of increased livestock production associated with CAM were likely insufficient to offset the substantial cost of this approach.

Livestock distribution in extensive rangelands of North America can present management challenges to land managers. Understanding the role of topography on livestock distribution, within and across diverse rangeland ecosystems, could provide land managers valuable information for adaptive management of livestock to address both conservation and production goals from these ecosystems. Here, we examine the influence of topography on grazing distribution unevenness and intensity of use of beef cattle in seven rangeland ecosystems spanning arid, semiarid, and subtropical environments. We focused on grazing distribution during the late growing season (summer and autumn) periods when topographic variation in rangelands is more coupled to low and nonuniform availability of high-quality forage. Pasture size and water sources strongly influence grazing distribution across ecosystems. High unevenness of grazing occurred in pastures with extensive distances to water, low stock density, and more rugged topography. Conversely, more uniform grazing distribution occurred in smaller, well-watered pastures that support higher stock density (animals per unit area) and gentler terrain. Comparison of two topographic indices, topographic wetness index and topographic position class index, in terms of their ability to predict cattle grazing distribution, revealed that categorical topographic position classes were more effective. For most arid and semiarid rangelands, livestock grazing distributions showed affinities for lowlands and flat plains compared with open slopes and uplands. In contrast to drier rangelands, livestock grazing distributions exhibited preference for upland and sloped areas of subtropical pastures, as low-lying areas with water-inundation likely curtailed selection. Across these diverse rangeland ecosystems of North America, results provide benchmark information on livestock grazing distribution to formulate improvements in adaptive management and decision making and incorporate technological advancements in precision livestock management to integrate abiotic environmental information with spatial movements of livestock and temporal vegetation dynamics.

Habitat loss and changing climate have direct impacts on native species but can also interact with disease pathogens to influence wildlife communities. In the North American Great Plains, black-tailed prairie dogs (Cynomys ludovicianus) are a keystone species that create important grassland habitat for numerous species and serve as prey for predators, but lethal control driven by agricultural conflict has severely reduced their abundance. Novel disease dynamics caused by epizootic plague (Yersinia pestis) within prairie dog colonies have further reduced prairie dog abundances, in turn destabilizing associated wildlife communities. We capitalized on a natural experiment, collecting data on prairie dog distributions, vegetation structure, avian abundance, and mesocarnivore and ungulate occupancy before (2015-2017) and after (2018-2019) a plague event in northeastern Wyoming, USA. Plague decimated black-tailed prairie dog populations in what was then the largest extant colony complex, reducing colony cover in the focal area from more than 10,000 ha to less than 50 ha. We documented dramatic declines in mesocarnivore occupancy and raptor abundance post-plague, with probability of occupancy or abundance approaching zero in species that rely on prairie dogs for a high proportion of their diet (e.g., ferruginous hawk [Buteo regalis], American badger [Taxidea taxus], and swift fox [Vulpes velox]). Following the plague outbreak, abnormally high precipitation in 2018 hastened vegetation recovery from prairie dog disturbance on colonies in which constant herbivory had formerly maintained shortgrass structure necessary for certain colony-associates. As a result, we observed large shifts in avian communities on former prairie dog colonies, including near-disappearance of mountain plovers (Charadrius montanus) and increases in mid-grass associated songbirds (e.g., lark bunting [Calamospiza melanocorys]). Our research highlights how precipitation can interact with disease-induced loss of a keystone species to induce drastic and rapid shifts in wildlife communities. Although grassland taxa have co-evolved with high spatiotemporal variation, fragmentation of the remaining North American rangelands paired with higher-than-historical variability in climate and disease dynamics are likely to destabilize these systems in the future.

A comprehensive understanding of multipaddock, rotational grazing management on rangelands has been slow to develop, and the contribution of adaptive management (Briske et al. 2011) and sufficient scale (Teague and Barnes 2017) have been identified as key omissions. We designed an experiment to compare responses of vegetation and cattle in an adaptively managed, multipaddock, rotational system with that of a season-long, continuous system at scales comparable with those of a working ranch. We hypothesized that 1) year-long rest periods in the adaptively managed, rotational pastures would increase the density and productivity of perennial C3 graminoids compared with continuously grazed pastures and 2) adaptive management, supported with detailed monitoring data, would result in similar cattle performance in the rotational as in the continuously grazed pastures. However, we found little supporting evidence for grazing management effects on C3 graminoid abundance or production under either above-average or below-average precipitation conditions during the 5-yr experiment. Furthermore, adaptive rotational grazing resulted in a 12–16% reduction in total cattle weight gain relative to continuous grazing each year. Our work shows that the implementation of adaptive management by a stakeholder group provided with detailed vegetation and animal monitoring data was unable to fully mitigate the adverse consequences of high stock density on animal weight gain. Under adaptive rotational grazing, C3 perennial grass productivity and stocking rate both increased following above-average precipitation. But when adaptive rotational management was directly compared with continuous grazing with the same increase in stocking rate, continuous grazing achieved similar vegetation outcomes with greater cattle weight gains. We suggest that managers in semiarid rangelands strive to maintain cattle at stock densities low enough to allow for maximal cattle growth rates, while still providing spatiotemporal variability in grazing distribution to enhance rangeland heterogeneity and long-term sustainability of forage production.

Adaptive management of large herbivores requires an understanding of how spatial-temporal fluctuations in forage biomass and quality influence animal performance. Advances in remote sensing have yielded information about the spatial-temporal dynamics of forage biomass, which in turn have informed rangeland management decisions such as stocking rate and paddock selection for free-ranging cattle. However, less is known about the spatial-temporal patterns of diet quality and their influence on large herbivore performance. This is due to infrequent concurrent ground observations of forage conditions with performance (e.g., mass gain), and previously limited satellite data at fine spatial and temporal scales. We combined multi-temporal field observations of diet quality (weekly) and mass gain (monthly) with satellite-derived phenological metrics (pseudo-daily, using data fusion and interpolation) to model daily mass gains of free-ranging yearling cattle in shortgrass steppe. We used this model to predict grazing season (mid-May to October) mass gains, a key management indicator, across 40 different paddocks grazed over a 10-year period (n = 138). We found strong relationships between diet quality and the satellite-derived phenological metrics, especially metrics related to the timing and rate of green-up and senescence. Satellite-derived diet quality estimates were strong predictors of monthly mass gains (R

Rangelands are composed of patchy, highly dynamic herbaceous plant communities that are difficult to quantify across broad spatial extents at resolutions relevant to their characteristic spatial scales. Furthermore, differentiation of these plant communities using remotely sensed observations is complicated by their similar spectral absorption profiles. To better quantify the impacts of land management and weather variability on rangeland vegetation change, we analyzed high resolution hyperspectral data produced by the National Ecological Observatory Network (NEON) at a 6500-ha experimental station (Central Plains Experimental Range) to map vegetation composition and change over a 5-year timescale. The spatial resolution (1 m) of the data was able to resolve the plant community type at a suitable scale and the information-rich spectral resolution (426 bands) was able to differentiate closely related plant community classes. The resulting plant community class map showed strong accuracy results from both formal quantitative measurements (F1 75% and Kappa 0.83) and informal qualitative assessments. Over a 5-year period, we found that plant community composition was impacted more strongly by weather than by the rangeland management regime. Our work displays the potential to map plant community classes across extensive areas of herbaceous vegetation and use resultant maps to inform rangeland ecology and management. Critical to the success of the research was the development of computational methods that allowed us to implement efficient and flexible analyses on the large and complex data.

Grassland birds have experienced some of the steepest population declines of any guild of birds in North America. The shortgrass steppe contains some of North America's most intact grasslands, which makes the region particularly important for these species. It is well known that grassland birds differentially respond to variation in vegetation structure generated by spatiotemporally varying disturbance like grazing management. However, understanding how species respond to characteristics beyond vegetation structure or grazing could better inform management for these species in the shortgrass steppe. We analyzed point count data for 5 grassland bird species breeding on the Central Plains Experimental Range in northeastern Colorado from 2013 to 2017 to examine the predictive capacity of models representing fine-scale (∼5 ha) vegetation attributes (vegetation structure and cover type) and topography, combined with interannual precipitation variability (i.e. vegetation-abiotic models). We then compared these models to models based on grazing management treatments (applied to whole pastures, ∼130 ha) and edaphic conditions (ecological sites), which represented information more generally available to rangeland managers. Precipitation, vegetation structure, and vegetation cover type influenced all species in a manner consistent with, but more nuanced than, vegetation structure alone. These models also explained more variation in abundance for species that responded to grazing management. Thus, while grazing management can be applied adaptively to improve habitat for these species, our more detailed vegetation-abiotic models identified species-specific habitat components that could be targeted for management. For example, not grazing pastures with extensive, homogenous stands of mid-height grasses (e.g., Hesperostipa comata) for an entire growing season during wet years could be one strategy to enhance Grasshopper Sparrow (Ammodramus savannarum) abundance and stockpile residual forage for future utilization by livestock. Our models provide a better understanding of and reveal nuances in the suite of environmental conditions to which grassland birds respond in shortgrass steppe rangelands. LAY SUMMARY We lack clear understanding of which environmental characteristics might support declining bird species breeding in the shortgrass steppe of the United States. These bird species often breed on lands managed for cattle grazing and are known to respond to vegetation structure generated by grazing and/or soil conditions. We sought to evaluate how precipitation and different types of vegetation cover (e.g., shrubs, shortgrasses) could explain additional variation in bird abundance in this system. We found vegetation cover, vegetation structure, and precipitation could explain more variation in abundance than cattle grazing management and/or ecological sites (i.e. unique soil types with associated plant communities) for most bird species. For bird species that did not respond to grazing management, ecological site and year effects explained more variation in abundance than vegetation characteristics and precipitation. Precipitation conditions, types of vegetation cover, and ecological sites often are not considered when developing grazing management plans to support grassland birds; incorporating these factors into management plans may help support populations of these declining species.

On the Ground • We assessed diet quality and livestock weight gains for shortgrass steppe pastures dominated by Loamy Plains or Sandy Plains ecological sites. • When growing season precipitation is “normal,” livestock gains are higher on Sandy Plains ecological sites, and diet quality is not limiting livestock production. • Conversely, when growing season precipitation declines by ≥ 20%, digestible organic matter, but not crude protein, influences livestock gains. These negative effects on livestock gains are more pronounced for the Loamy Plains ecological site. • Pastures with multiple ecological sites may provide range managers greater forage diversity for livestock and higher livestock gains during dry growing seasons.

This chapter focuses on the direct effects of the mesobrowsers on woody plants in savannas, focusing on the class of mammalian ungulates and macropodids that range in size from approximately 5kg to 1000kg, but which are mostly < 500 kg. It first reviews the distribution and abundance of mesobrowsers in savannas around the world. The chapter then reviews long-term studies of the effects of mesobrowsers on woody plant growth and community dynamics, most of which have been conducted in African savannas. It makes readers to understand ecosystem-level characteristics that allow or prevent mesobrowser regulation of woody plant recruitment and growth rates, as both native and domestic mesobrowser abundance are influenced by human activities and management. Furthermore, debates surrounding elephant management in African savannas often center on how elephants are affecting woody plants, but knowledge of mesobrowser effects is essential to determine whether elephant management will achieve desired outcomes for savanna vegetation.

Burrowing mammals play a role in rangeland disturbance worldwide, enhancing habitat for certain species while negatively affecting others. However, little is known concerning effects of disturbance spatial pattern on co-occuring fauna. In the North American Great Plains, colonial black-tailed prairie dogs (Cynomys ludovicianus) may enhance habitat for one suite of birds while degrading habitat for others. We examined the influence of prairie dogs on birds in a mosaic grassland–shrubland landscape. We evaluated how birds associated with shortgrass, midgrass, and sagebrush (Artemisia spp.) plant communities respond to spatial pattern of prairie dog disturbance and identified thresholds where abundance changes. We surveyed bird abundance on prairie dog colonies of varying sizes and shapes, across colony edges into undisturbed habitat, and within undisturbed sagebrush in northeastern Wyoming. We modeled species responses to colony presence, distance to colony edge, and total area and edge density of colonies at four spatial scales (100 m, 225 m, 500 m, 1000 m). Sagebrush specialists like Brewer’s sparrow (Spizella breweri) and sage thrasher (Oreoscoptes montanus) were 4.5 times more abundant in undisturbed shrublands. Conversely, the shortgrass-specialist mountain plover (Charadrius montanus) was abundant on colonies but showed a non-linear response to colony edge, increasing in abundance up to 600 m from edges then declining further towards colony cores. While some species may be broadly intolerant to disturbance, disturbance-dependent birds can display a “goldilocks syndrome” relative to disturbance size. As such, management for multiple species of conservation concern can be optimized relative to other goals by identifying thresholds associated with the effect of disturbance.

Recent work suggests that savanna woody plant species utilise two different strategies based on their defences against herbivory; a low nutrient/high chemical defence strategy and a nutrition paired with mostly architectural defences strategy. The concept that chemical and structural defences can augment each other and do not necessarily trade-off has emanated from this work. In this study, we examine woody plant defence strategies, how these respond to herbivore removal and how they affect plant growth in an East African savanna. At three paired long-term exclosure sites with high browser and mixed-feeder densities at Mpala Ranch, Kenya, we investigated: (a) whether defences employed by the dominant fine- and broad-leaved woody savanna species form defence strategies and if these align with previously proposed strategies, (b) how nine key plant defence traits respond to herbivore removal and (c) how effective the different defence strategies are at protecting against intense herbivory (by measuring plant growth with and without herbivores present). We identified three defence strategies. We found a group (a) with high N, short spines and high N-free secondary metabolites, a group (b) with high N, long spines and low N-free secondary metabolites and a group (c) with moderate N, no spines and low N-free secondary metabolites (most likely defended by unmeasured chemical defences). Structural defences (spine length, branching) were generally found to be induced by herbivory, leaf available N increased or did not respond, and N-free secondary metabolites decreased or did not respond to herbivory. Species with long spines combined with increased “caginess” (dense canopy architecture arising from complex arrangement of numerous woody and spiny axis categories) of branches, maintained the highest growth under intense browsing, compared to species with short spines and high N-free secondary metabolites and species with no spines and low N-free secondary metabolites. Synthesis. At our study site, structural traits (i.e. spines, increased caginess) were the most inducible and effective defences against intense mammalian herbivory. We propose that high levels of variability in the way that nutrient and defence traits combine may contribute to the coexistence of closely related species comprising savanna woody communities.

African savannas are the last stronghold of diverse large-mammal communities, and a major focus of savanna ecology is to understand how these animals affect the relative abundance of trees and grasses. However, savannas support diverse plant life-forms, and human-induced changes in large-herbivore assemblages-declining wildlife populations and their displacement by livestock-may cause unexpected shifts in plant community composition. We investigated how herbivory affects the prevalence of lianas (woody vines) and their impact on trees in an East African savanna. Although scarce (

Aboveground net primary productivity (ANPP) in grasslands is an important integrator of terrestrial ecosystem function, a key driver of global biogeochemical cycles, and a critical source of food for wild and domesticated herbivores. ANPP exhibits high spatial and temporal variability, driven by a suite of factors including precipitation amount and pattern, biotic and abiotic legacies, and topographic heterogeneity. Global climate models forecast an altered hydrological cycle due to climate change, including higher precipitation variability and more extreme events, which may further increase spatiotemporal variability in ANPP. Therefore, it is essential to understand the sensitivity of this central ecosystem function to various precipitation metrics, legacies, and topographic positions to better inform sustainable grassland management. In this study, we analyzed long‐term (36‐yr) ANPP data collected across a topographic sequence in the semiarid shortgrass steppe of North America to examine patterns and drivers of spatiotemporal variability in ANPP. We observed that (1) ANPP varied substantially by topographic position, with greater divergence during years with high production, (2) ANPP variability was higher temporally (16‐fold maximum difference across years) than spatially (4‐fold maximum difference across topographic positions), (3) warm‐season perennial grasses were the dominant plant functional type across all topographic positions and strongly influenced total ANPP dynamics, and (4) ANPP had strong sensitivities to current year precipitation amount and pattern that varied by plant functional type, as well as weaker sensitivities to precipitation and productivity legacies. Overall, the lowest topographic position had the highest sensitivity to precipitation, likely due to higher resource availability via the downhill movement of water and nutrients during years with high precipitation and large rainfall events. These results suggest that temporal and spatial ANPP variability in shortgrass steppe is primarily driven by the combined effects of precipitation amount and pattern during the current year, with the dominant warm‐season perennial grasses governing these responses.

Habitat loss and altered disturbance regimes have led to declines in many species of grassland and sagebrush birds, including the imperiled Mountain Plover (Charadrius montanus). In certain parts of their range Mountain Plovers rely almost exclusively on black-tailed prairie dog (Cynomys ludovicianus) colonies as nesting habitat. Previous studies have examined Mountain Plover nest and brood survival on prairie dog colonies, but little is known about how colony size and shape influence these vital rates or patterns of habitat selection. We examined how (1) adult habitat utilization, (2) nest-site selection, and (3) nest success responded to a suite of local- and site-level variables on large prairie dog colony complexes in northeastern Wyoming. Abundance of adult Mountain Plovers was highest on points within older, “medium”-sized (100–500 ha) colonies with high cover of annual forbs and bare ground (5.8 birds km−2), but lower on extremely large (>2,000 ha) colonies (2.1 birds km−2). Nest sites were characterized by high proportions of annual forbs and bare ground and low cactus cover and vegetation height. Nest survival was higher for older nests, and nests with lower cactus cover, and decreased with increasing temperatures. Uncertainty was high for models of daily nest survival, potentially because of 2 competing sources of nest failure: nest depredation and nest abandonment or inviability of eggs. Drivers of these 2 sources of nest failure differed, with inclement weather and higher temperatures associated with nest abandonment or egg inviability. We highlight how prairie dogs alter vegetation structure and bare ground heterogeneously across the landscape, and how this in turn influences bird abundance and nest distribution at different temporal and spatial scales. Furthermore, our work reveals how partitioning the causes of nest failure during nest survival analyses enhances understanding of survival rate covariates.