Shortgrass Steppe Research Articles

Predictions of Aboveground Herbaceous Production from Satellite-Derived APAR Are More Sensitive to Ecosite than Grazing Management Strategy in Shortgrass Steppe

The accurate estimation of aboveground net herbaceous production (ANHP) is crucial in rangeland management and monitoring. Remote and rural rangelands typically lack direct observation infrastructure, making satellite-derived methods essential. When ground data are available, a simple and effective way to estimate ANHP from satellites is to derive the empirical relationship between ANHP and plant-absorbed photosynthetically active radiation (APAR), which can be estimated from the normalized difference vegetation index (NDVI). While there is some evidence that this relationship will differ across rangeland vegetation types, it is unclear whether this relationship will change across grazing management regimes. This study aimed to assess the impact of grazing management on the relationship between ground-observed ANHP and satellite-derived APAR, considering variations in plant communities across ecological sites in the shortgrass steppe of northeastern Colorado. Additionally, we compared satellite-predicted biomass production from the process-based Rangeland Analysis Platform (RAP) model to our empirical APAR-based model. We found that APAR could be used to predict ANHP in the shortgrass steppe, with the relationship being influenced by ecosite characteristics rather than grazing management practices. For each unit of added APAR (MJ m−2 day−1), ANHP increased by 9.39 kg ha−1, and ecosites with taller structured herbaceous vegetation produced, on average, 3.92–5.71 kg ha−1 more ANHP per unit APAR than an ecosite dominated by shorter vegetation. This was likely due to the increased allocation of plant resources aboveground for C3 mid-grasses in taller structured ecosites compared to the C4 short-grasses that dominate the shorter structured ecosites. Moreover, we found that our locally calibrated empirical model generally performed better than the continentally calibrated process-based RAP model, though RAP performed reasonably well for the dominant ecosite. For our empirical models, R2 values varied by ecosite ranging from 0.49 to 0.67, while RAP R2 values ranged from 0.07 to 0.4. Managers in the shortgrass steppe can use satellites to estimate herbaceous production even without detailed information on short-term grazing management practices. The results from our study underscore the importance of understanding plant community composition for enhancing the accuracy of remotely sensed predictions of ANHP.

Adaptive multi-paddock grazing management reduces diet quality of yearling cattle in shortgrass steppe

Adaptive multi-paddock (AMP) grazing is hypothesised to improve livestock diet quality by allowing managers to move livestock among paddocks in a manner that tracks phenological variation in forage growth related to variation in plant community composition. We compared yearling steer (Bos taurus) dietary crude protein (CP), digestible organic matter (DOM), and diet composition on a ranch-scale (2600 ha, 10 pairs of 130 ha paddocks) experiment in shortgrass steppe for 6 years (2014–2019) in contrasting grazing treatments: Collaborative Adaptive Rangeland Management (CARM, a type of AMP with a stakeholder group making science-informed management decisions within the grazing season) and season-long, continuous grazing (TRM, traditional rangeland management). These grazing treatments had the same system-level stocking rate annually but differed in stocking density, with CARM being 10-fold higher than TRM because of all steers in the CARM treatment being in a single herd. Mean grazing-season dietary CP was consistently 13–28% higher in TRM than CARM; in contrast, DOM in TRM was similar to CARM or only slightly higher (2.5%). Differences in diet quality between CARM and TRM grazing strategies were largest early in the grazing season, with CP being 14–36% higher for TRM compared to CARM steers during the first 4 weeks; these diet-quality differences between treatments disappeared towards the end of the grazing season. Implementing AMP on the basis of a diverse stakeholder group’s experiential knowledge about plant communities, soils, and ecological sites did alter within-grazing season plant functional group contributions to steer diets. Although we implemented adaptive decision-making within the grazing season, which allowed CARM steers to track the seasonal phenology of C3 versus C4 grasses as steers rotated among paddocks varying in plant community composition, these adaptive movements did not offset the detrimental effects on diet quality associated with grazing in a herd with 10-fold higher stocking density. Managers applying AMP in semiarid rangelands should be cognisant that high stocking density can be associated with lower diet quality early in the growing season, which can compromise livestock gain responses.

Timing and magnitude of drought impacts on carbon uptake across a grassland biome.

Although drought is known to negatively impact grassland functioning, the timing and magnitude of these impacts within a growing season remain unresolved. Previous small-scale assessments indicate grasslands may only respond to drought during narrow periods within a year; however, large-scale assessments are now needed to uncover the general patterns and determinants of this timing. We combined remote sensing datasets of gross primary productivity and weather to assess the timing and magnitude of grassland responses to drought at 5km2 temporal resolution across two expansive ecoregions of the western US Great Plains biome: the C4 -dominated shortgrass steppe and the C3 -dominated northern mixed prairies. Across over 700,000 pixel-year combinations covering more than 600,000 km2 , we studied how the driest years between 2003-2020 altered the daily and bi-weekly dynamics of grassland carbon (C) uptake. Reductions to C uptake intensified into the early summer during drought and peaked in mid- and late June in both ecoregions. Stimulation of spring C uptake during drought was small and insufficient to compensate for losses during summer. Thus, total grassland C uptake was consistently reduced by drought across both ecoregions; however, reductions were twice as large across the more southern and warmer shortgrass steppe. Across the biome, increased summer vapor pressure deficit (VPD) was strongly linked to peak reductions in vegetation greenness during drought. Rising VPD will likely exacerbate reductions in C uptake during drought across the western US Great Plains, with these reductions greatest during the warmest months and in the warmest locations. High spatiotemporal resolution analyses of grassland response to drought over large areas provide both generalizable insights and new opportunities for basic and applied ecosystem science in these water-limited ecoregions amid climate change.

Arboreal Spiders of Native Shrubs in Shortgrass Steppe Ecosystems of Eastern Colorado

Biological diversity is a key descriptor to evaluate ecological systems and is often used to identify specific components of local habitat that can be quantified. Heterogeneous habitats provide increased environmental variation in habitat type and might support increase in biological diversity. Spiders (Araneae) are a diverse taxonomic group that fills numerous niches in a grassland landscape. I hypothesized that plant type (shrub species) affects habitat availability of arboreal spiders and expected differences in spider diversity patterns (Shannon index, abundance) to be observed locally. This research was done at Comanche and Pawnee National Grasslands in Colorado and studied how spiders occupy native shrubs in the grassland steppe ecoregion. Araneae taxa are reported for both Comanche and Pawnee National Grassland locations. For Comanche National Grassland, significant differences in spider diversity existed between specific shrub species, especially the spider families Salticidae, Philodromidae, Oxyopidae, and Dictynidae. Fewer shrub species were at Pawnee National Grassland, but Salticidae, Dictynidae, and Oxyopidae were abundant. Twenty-seven genera and thirty-one species were at CNG, and seven genera and sixteen species were at PNG. Analyses provide support that spiders prioritize certain shrubs that provide more resources. Results suggested that changes in available shrub habitat might significantly impact spider diversity in the grassland ecosystems.

Balancing ecosystem service outcomes at the ranch-scale in shortgrass steppe: The role of grazing management

• Grazing management for providing multiple ecosystem services at the ranch scale requires balancing desired outcomes. • Abundant challenges involve matching the spatial heterogeneity in soils and associated plant community characteristics with the temporal variability in precipitation. • Prescriptive grazing (season-long continuous and time-controlled rotational grazing) removes the human experiential knowledge to adapt to changing conditions, whereas adaptive multipaddock (AMP) grazing often invokes high stock densities, which reduce livestock weight gain. • A “mix-and-match” or blending of both approaches for grazing management in the shortgrass steppe can result in reduced drought risk, enhanced breeding habitat availability for grassland bird species of concern, and sustained livestock production.

Movement Dynamics and Energy Expenditure of Yearling Steers Under Contrasting Grazing Management in Shortgrass Steppe

A potential mechanism for lower livestock weight gains with rotational grazing is the additional movement and associated energy expenditures incurred with rotation of animals among paddocks. We evaluated these metrics in 2016 and 2017 using pedometers affixed to free-ranging naïve yearling steers grazing semiarid, shortgrass steppe under contrasting grazing management treatments with the same stocking rate: traditional season-long (mid-May to October) grazing management and collaborative adaptive rangeland management (CARM) at a ranch scale (2-600 ha: ten 130-ha paddocks for each treatment). Mean daily number of steps by steers in paddocks during the grazing season, excluding those associated with moves between paddocks, were 3.0% lower (2016) and 7.8% greater (2017) for CARM, but energy expenditures did not differ significantly between treatments in either year. Daily step counts decreased in traditional rangeland management (TRM) as the grazing season progressed. Step counts decreased from day 1 to day 8 in CARM paddocks following rotation of steers. Steers in the TRM treatment took more steps daily than CARM steers in the first third of the grazing season, but this reversed in the last third of the grazing season. These findings suggest that observed 12%−16% reductions in livestock weight gains with CARM were not influenced by differences in total grazing season steps as energy expenditures of steers did not differ. Two additive influences of within-season steer movement dynamics suggest that forage quality was the primary driver for the decrease in weight gains in CARM. First, fewer steps in the early growing season, when forage quality is highest, indicate reduced selectivity for nutrient-rich patches. Second, more steps by yearlings in the late growing season suggest that these heavier animals expending more energy for maintenance were searching to satisfy gut fill as forage quantity and quality on offer per steer was limiting with the 10-fold higher stocking density.

Water availability dictates how plant traits predict demographic rates.

A major goal in ecology is to make generalizable predictions of organism responses to environmental variation based on their traits. However, straightforward relationships between traits and fitness are rare and likely to vary with environmental context. Characterizing how traits mediate demographic responses to the environment may enhance the predictions of organism responses to global change. We synthesized 15 years of demographic data and species-level traits in a shortgrass steppe to determine whether the effects of leaf and root traits on growth and survival depended on seasonal water availability. We predicted that (1) species with drought-tolerant traits, such as lower leaf turgor loss point (TLP) and higher leaf and root dry matter content (LDMC and RDMC), would be more likely to survive and grow in drier years due to higher wilting resistance, (2) these traits would not predict fitness in wetter years, and (3) traits that more directly measure physiological mechanisms of water use such as TLP would best predict demographic responses. We found that graminoids with more negative TLP and higher LDMC and RDMC had higher survival rates in drier years. Forbs demonstrated similar yet more variable responses. Graminoids grew larger in wetter years, regardless of traits. However, in both wet and dry years, graminoids with more negative TLP and higher LDMC and RDMC grew larger than less negative TLP and low LDMC and RDMC species. Traits significantly mediated the impact of drought on survival, but not growth, suggesting that survival could be a stronger driver of species' drought response in this system. TLP predicted survival in drier years, but easier to measure LDMC and RDMC were equal or better predictors. These results advance our understanding of the mechanisms by which drought drives population dynamics, and show that abiotic context determines how traits drive fitness.

The Clean Water Act and biosolids: A 45‐year chronological review of biosolids land application research in Colorado

The 1972 U.S. Clean Water Act set forth the generation of biosolids. In Colorado, biosolids land application research began in 1976 and continues today. Pastureland research suggested that sewage effluent could effectively be land applied to benefit aboveground plant growth and to polish water prior to reaching receiving waters. Forest wildfire-affected ecosystems can also benefit from biosolids applications; application rates of up to 80 Mg ha-1 can lead to greater plant establishment, soil microbial activity, and nutrient turnover and reduced nutrient and heavy metal concentrations in runoff below livestock and USEPA drinking water standards. Long-term (24-yr) observations in oil shale-mined lands showed that biosolids (up to 224 Mg ha-1 ) can have a positive effect on microbial-mediated nutrient cycling and, in turn, on aboveground plant community structure. Biosolids applications of up to 40 Mg ha-1 in high-elevation shrubland ecosystems, dominated by Mo-containing shale deposits, can aid in reducing imbalances between Mo and Cu in soils and plants; excessive plant Mo, when consumed by ruminants, can lead to molybdenosis. Biosolids and lime applications (both at 224 Mg ha-1 ) have been shown to improve long-term reclamation success on acid-generating, heavy metal-containing fluvial mine tailings. Thirty years of grazing land research, focused on soil and aboveground plant benefits, illustrate that soil health and plant productivity can be improved to the greatest extent at biosolids application rates close to 10 Mg ha-1 . Finally, 40 yr of dryland agroecosystem research (a) have helped identify biosolids N fertilizer equivalency (∼8kg N Mg-1 ) and thus dryland winter wheat application rates (e.g., 4.5-6.7 dry Mg ha-1 ); (b) have identified first-year mineralization rates of 25-32%; (c) dispute the "time bomb" theory by showing that plant metal uptake follows an exponential rise to a maximum; (d) showcase economic return to producers via increased wheat grain protein content; (e) suggest that biosolids-borne proteins and their degradation products are labile C and N sources; (f) have led to long-term tracking of micronutrients and heavy metals in soils and revealed that plants-soil concentrations will not lead to groundwater degradation and that plants are safe for human consumption; and (g) have shown that biosolids provide Zn, helping to overcome soil deficiencies and enhancing Zn biofortification in wheat grain. This latter point is important because ∼2 billion people globally suffer from Zn deficiencies. Forty-five years of research in Colorado have proven that biosolids can enhance environmental quality, improve soil health, and produce healthy food products.

Remotely Sensed Spatiotemporal Variation in Crude Protein of Shortgrass Steppe Forage

In the Great Plains of central North America, sustainable livestock production is dependent on matching the timing of forage availability and quality with animal intake demands. Advances in remote sensing technology provide accurate information for forage quantity. However, similar efforts for forage quality are lacking. Crude protein (CP) content is one of the most relevant forage quality determinants of individual animal intake, especially below an 8% threshold for growing animals. In a set of shortgrass steppe paddocks with contrasting botanical composition, we (1) modeled the spatiotemporal variation in field estimates of CP content against seven spectral MODIS bands, and (2) used the model to assess the risk of reaching the 8% CP content threshold during the grazing season for paddocks with light, moderate, or heavy grazing intensities for the last 22 years (2000–2021). Our calibrated model explained up to 69% of the spatiotemporal variation in CP content. Different from previous investigations, our model was partially independent of NDVI, as it included the green and red portions of the spectrum as direct predictors of CP content. From 2000 to 2021, the model predicted that CP content was a limiting factor for growth of yearling cattle in 80% of the years for about 60% of the mid-May to October grazing season. The risk of forage quality being below the CP content threshold increases as the grazing season progresses, suggesting that ranchers across this rangeland region could benefit from remotely sensed CP content to proactively remove yearling cattle earlier than the traditional October date or to strategically provide supplemental protein sources to grazing cattle.

Monitoring standing herbaceous biomass and thresholds in semiarid rangelands from harmonized Landsat 8 and Sentinel-2 imagery to support within-season adaptive management

Adaptive management requires rangeland managers to respond to changing forage conditions (e.g., standing herbaceous biomass) within the grazing season at the scale of individual pastures. While within-season biomass can be measured or estimated in the field, it is often impractical to make field measurements in extensive rangeland systems with adequate frequency and spatial representation for responsive decision-making by rangeland managers. We sought to develop a single model to accurately predict daily herbaceous biomass across seasonally and annually varying conditions from the Harmonized Landsat-Sentinel satellite time series. We also sought to assess how information about plant community composition derived from a high-spatial resolution map would improve model performance. We used herbaceous biomass data from 1764 ground observations collected over 8 years in North American shortgrass steppe for training in a cross-validated model selection approach to evaluate (1) predictive performance of candidate models both spatially and temporally, (2) relative variable importance of individual spectral bands, vegetation indices, and recently developed broadband spectral angle indices, and (3) the degree to which including plant community composition improved model performance. All 11 candidate models identified in the model selection procedure contained a band angle index and an individual spectral band, and 6 contained one of each input feature type, demonstrating the benefit of combining spectral features for predicting herbaceous biomass across varying conditions. The spatial and temporal cross-validation and selection procedures produced the same top model with similar performance (mean absolute error = 151–182 kg ha−1; R2 = 0.75–0.79), suggesting that a single model performs well over space and time. Including plant community composition in the model reduced mean absolute error by 11–13%. Bootstrapping revealed that –six to seven years of training data were required to achieve consistent model performance across years with varying environmental conditions (e.g., wet, average, dry). The top model could accurately detect (70–87% accuracy) the week that biomass dropped below management-related thresholds as low as 450 kg ha−1 in an independent dataset (n = 950) with modest commission error (10–26%). We discuss how maps showing the probability that herbaceous biomass is below a given threshold can support adaptive management in extensive semiarid rangelands across differing scenarios of risk perception and avoidance. In addition to producing maps to support precision rangeland management strategies, this study demonstrates the importance of combining complementary vegetation indices and acquiring long-term training datasets to achieve reliable predictions of herbaceous standing biomass in highly variable systems.

Predicting spatial-temporal patterns of diet quality and large herbivore performance using satellite time series.

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 (R2 =0.68) across a wide range of aboveground net herbaceous production. Season-long predictions of average daily gain and cattle off-mass had mean absolute errors of 8.9% and 2.9%, respectively. The model performed better temporally (across repeated observations in the same paddock) than spatially (across all paddocks within a given year), highlighting the need for accurate vegetation maps and robust field data collection across both space and time. This study demonstrates that free-ranging cattle performance in rangelands is strongly affected by diet quality, which is related to the timing of vegetation green-up and senescence. Senescing vegetation suppressed mass gains, even if adequate forage was available. The satellite-based pseudo-daily approach presented here offers new opportunities for adaptive management of large herbivores, such as identifying within-season triggers to move livestock among paddocks, predicting wildlife herd health, or timing the grazing season to better match earlier spring green-up caused by climate change and plant species invasion.

UAV−Enabled Quantification of Grazing-Induced Changes in Uniformity of Green Cover on Semiarid and Mesic Grasslands

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.

Vegetation characteristics and precipitation jointly influence grassland bird abundance beyond the effects of grazing management

AbstractGrassland 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.

Collaborative Adaptive Rangeland Management, Multipaddock Rotational Grazing, and the Story of the Regrazed Grass Plant

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.

Long‐Term Effects of Black‐Tailed Prairie Dogs on Livestock Grazing Distribution and Mass Gain

ABSTRACTThe conservation and management of black‐tailed prairie dogs (Cynomys ludovicianus) have been contentious issues in grasslands of central North America for much of the past century, primarily because of the perception that they compete with livestock for forage. Studies quantifying the magnitude of competition between prairie dogs and cattle are difficult to conduct because of the large spatial and long temporal scales needed to quantify how competition varies in response to interannual variation in precipitation and prairie dog abundance. We examined variation in mass gains of yearling steers in shortgrass steppe of northeastern Colorado, USA, with and without prairie dogs from 2008–2019, a period that encompassed a full cycle in prairie dog abundance from a nadir following plague‐induced population collapse, to peak abundance following population recovery, to plague‐induced population lows again. Analyses of cattle grazing distribution with global positioning system (GPS)‐collars revealed preferential grazing on colonies following a period of unusually high vegetation production, and preferential grazing off colonies following a period of rapid vegetation senescence, but these patterns were not clearly related to cattle mass gains. Across all 12 years of the study, average daily mass gain (ADG) during the growing season was 0.97 kg/steer/day in pastures where prairie dogs were controlled annually, and 0.95 kg/steer/day in pastures where they were not. Average daily mass gain was a quadradic function of precipitation and a linear function of prairie dog occupancy within a pasture, with a generalized linear mixed model predicting an 8.0% decrease in ADG as prairie dog occupancy increased from 0 to 60% of a pasture with average growing‐season precipitation. We did not detect a significant interaction between precipitation and prairie dog occupancy, but one limitation of our study is that the only drought year (2012) occurred when prairie dogs occupied low percentages (10–25%) of the study pastures. Prairie dogs had a small but detectable negative effect on cattle mass gains during the growing season in shortgrass steppe. The magnitude of this effect can be used by managers in combination with market conditions and the spatial extent of prairie dog colonies to estimate economic effects of prairie dogs on livestock operations. © 2021 The Wildlife Society. This article is a U.S. Government work and is in the public domain in the USA.

Long live the data! Embedded data management at a long‐term ecological research site

AbstractOpen‐access data associated with research efforts depend upon managing, packaging, and preserving data for sharing with collaborators and the public. The U.S. Long‐Term Ecological Research (LTER) Network, established in 1980, provides an early example of embedded data management supporting long‐term, place‐based research and contributes to our understanding of the enactment of open data access within scientific research arenas. Here, we examine collective data activities enabled by embedding data management within the Shortgrass Steppe (SGS) research site. Study of the SGS LTER, a member of the U.S. LTER Network for more than three decades, provided a unique opportunity to investigate data management practices and challenges during the life cycle of a long‐term project. It illustrates how a continuous, uninterrupted focus on data management positioned in dynamic interaction with researchers at a site as well as with an active network‐wide data management committee can stimulate the growth of both data expertise and data infrastructure. We report on an ethnographic study by a collaborative team of researchers, all having been involved with the LTER network and well‐positioned for investigating data management challenges faced during the periods of activation, maturation, and decommissioning of a project at a research site. Termination of the SGS site's membership in the U.S. LTER Network prompted rethinking about long‐term data management. During the decommissioning phase, we document how views on temporality and data management strategies shift from planning for a longitudinal, ongoing site to wrapping up a long‐term project. Striving to ensure “long live the data” at the end, novel data arrangements, such as development of a digital legacy project collection, contribute to data stewardship. Lastly, from this study of a long‐term research site, we offer five recommendations about data management and describe strategies pertinent to planning for data management and open access for other research projects.

Sensitivity of productivity to precipitation amount and pattern varies by topographic position in a semiarid grassland

AbstractAboveground 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.

Adaptation and forage productivity of cool‐season grasses in the central USA

AbstractCool‐season grass species (18) and cultivars (85) were evaluated for use in seeded grasslands in the tallgrass prairie and shortgrass steppe ecoregions of the central United States at the test locations of Ithaca and Sidney, NE, respectively. Both native and introduced grasses were evaluated in sward trails. Significant differences existed among species and cultivars for all traits evaluated except for in vitro dry matter digestibility (IVDMD) among cultivars within species at Sidney. The grasses that had the best establishment, persistence, and forage yields in the Ithaca trial were introduced wheatgrass (Thinopyrum) and bromegrass (Bromus) species. At the Sidney location, the best species using the same criteria were wheatgrasses (Thinopyrum, Agropryon, Pascopyrum, and Elymus spp.) and wildryes (Psathyrostachys). The only native grasses that were marginally competitive with the introduced grasses were western wheatgrass [Pascopyrum smithii (Rydb.) A. Löve] and thickspike wheatgrass [Elymus macrourus (Turcz.) Tzvelev] at the Sidney location and western wheatgrass at Ithaca. The study was the largest cool‐season forage grass multispecies and cultivar sward evaluation to date in these two major land areas. The superior species and cultivars that were identified represent the best cool‐season grasses available for restoring marginal croplands to grazed grasslands in these two major land areas.

How big is big enough? Surprising responses of a semiarid grassland to increasing deluge size.

Climate change has intensified the hydrologic cycle globally, increasing the magnitude and frequency of large precipitation events, or deluges. Dryland ecosystems are expected to be particularly responsive to increases in deluge size, as their ecological processes are largely dependent on distinct soil moisture pulses. To better understand how increasing deluge size will affect ecosystem function, we conducted a field experiment in a native semiarid shortgrass steppe (Colorado, USA). We quantified ecological responses to a range of deluge sizes, from moderate to extreme, with the goal of identifying response patterns and thresholds beyond which ecological processes would not increase further (saturate). Using a replicated regression approach, we imposed single deluges that ranged in size from 20 to 120mm (82.3rd to >99.9th percentile of historical event size) on undisturbed grassland plots. We quantified pre- and postdeluge responses in soil moisture, soil respiration, and canopy greenness, as well as leaf water potential, growth, and flowering of the dominant grass species (Bouteloua gracilis). We also measured end of season above- and belowground net primary production (ANPP, BNPP). As expected, this water-limited ecosystem responded strongly to the applied deluges, but surprisingly, most variables increased linearly with deluge size. We found little evidence for response thresholds within the range of deluge sizes imposed, at least during this dry year. Instead, response patterns reflected the linear increase in the duration of elevated soil moisture (2-22days) with increasing event size. Flowering of B. gracilis and soil respiration responded particularly strongly to deluge size (14- and 4-fold increases, respectively), as did ANPP and BNPP (~60% increase for both). Overall, our results suggest that this semiarid grassland will respond positively and linearly to predicted increases in deluge size, and that event sizes may need to exceed historical magnitudes, or occur during wet years, before responses saturate.

Can Collaborative Adaptive Management Improve Cattle Production in Multipaddock Grazing Systems?

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.