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Why some species are consistently more abundant than others, and predicting how species will respond to global change, are fundamental questions in ecology. Long-term observations indicate that plant species with high stoichiometric homeostasis for nitrogen ( H N ), i.e., the ability to decouple foliar N levels from variation in soil N availability, were more common and stable through time than low- H N species in a central U.S. grassland. However, with nine years of nitrogen addition, species with high H N decreased in abundance, while those with low H N increased in abundance. In contrast, in climate change experiments simulating a range of forecast hydrologic changes, e.g., extreme drought (two years), increased rainfall variability (14 years), and chronic increases in rainfall (21 years), plant species with the highest H N were least responsive to changes in soil water availability. These results suggest that H N may be predictive of plant species success and stability, and how plant species and ecosystems will respond to global-change-driven alterations in resource availability.

Grazing, fire, and climate shape mesic grassland communities. With global change altering all three factors, understanding how grasslands respond to changes in these combined drivers may aid in projecting future changes in grassland ecosystems. We manipulated rainfall and simulated grazing (clipping) in two long-term fire experiments in mesic grasslands in North America (NA) and South Africa (SA). Despite their common drivers, grasslands in NA and SA differ in evolutionary history. Therefore, we expected community structure and production in NA and SA to respond differently to fire, grazing, and drought. Specifically, we hypothesized that NA plant community composition and production would be more responsive than the SA plant communities to changes in the drivers and their interactions, and that despite this expected stability of SA grasslands, drought would be the dominant factor controlling production, but grazing would play the primary role in determining community composition at both sites. Contrary to our hypothesis, NA and SA grasslands generally responded similarly to grazing, drought, and fire. Grazing increased diversity, decreased grass cover and production, and decreased belowground biomass at both sites. Drought alone minimally impacted plant community structure, and we saw similar treatment interactions at the two sites. Drought was not the primary driver of grassland productivity, but instead drought effects were similar to or less than grazing and fire. Even though these grasslands differed in evolutionary history, they responded similarly to our fire, grazing, and climate manipulations. Overall, we found community and ecosystem convergence in NA and SA grasslands. Grazing and fire are as important as climate in controlling mesic grassland ecosystems on both continents.

Understanding determinants of local species diversity remains central to developing plans to preserve biodiversity. In the continental United States, climate, grazing by large mammals, fire, and topography are important ecosystem drivers that structure North American tallgrass prairie, with major impacts on plant community composition and vegetation structure. Frequency of fire and grazing by bison (Bos bison), through effects on plant community composition and altered spatial and structural heterogeneity of vegetation in tallgrass prairie, may act as bottom-up processes that modulate insect community species richness. As previously seen for plant species richness, I hypothesized that grazing had more impact than fire frequency in determining species richness of insect herbivore communities. I examined this prediction with grasshoppers at Konza Prairie, a representative tallgrass prairie site in which fire frequency and bison grazing are manipulated over long terms with landscape-level treatments. Topographic position (upland vs. lowland) and fire frequency (1-, 2-, 4-year intervals, and unburned) did not significantly influence grasshopper species richness or indices of diversity, while grazing had significant effects. On average, I found ~45% more grasshopper species and significantly increased values of Shannon H' diversity at sites with bison grazing. Species abundances were more equally distributed (Shannon's Evenness Index) in grazed sites as well. No significant interactions among burning and grazing treatments explained variation in grasshopper species diversity. Grasshopper species richness responded positively to increased heterogeneity in vegetation structure and plant species richness, and negatively to average canopy height and total grass biomass. Variation in forb biomass did not influence grasshopper species richness. A significant positive relationship between grasshopper species richness and overall grasshopper density was observed. Species richness increased marginally as watershed area of treatments in grazed areas increased, but not in ungrazed areas. Disturbance from ecosystem drivers operating at watershed spatial scales exhibits strong effects on local arthropod species diversity, acting indirectly by mediating changes in the spatial heterogeneity of local vegetation structure and plant species diversity.

Growth of tallgrass prairie plants, many of which maintain substantial bud banks, can be limited by nitrogen (N), water, and/or light. We hypothesized that tallgrass prairie plants respond to increases in N through demographic effects on the bud bank. We tested the effects of a pulse of N on (1) bud bank demography, (2) plant reproductive allocation, and (3) ramet size. We parameterized matrix models, considering each genet as a population of plant parts. Nitrogen addition significantly impacted bud bank demography in two subdominant species of bunchgrass: Sporobolus heterolepis (a C₄ grass) and Koeleria macrantha (a C₃ grass), but had no effect on the size of individual ramets. Emergence from the bud bank and ramet population growth rates (λ) were significantly higher in S. heterolepis genets that received supplemental N. Nitrogen addition also affected the bud demography of K. macrantha, but N addition decreased rather than increased λ. Prospective and retrospective demographic analyses indicated that bud bank dynamics were the most important demographic processes driving plant responses to nutrient availability. Thus, the variation in productivity in these tallgrass prairie species is driven principally by the demography of the bud bank rather than by the physiology and growth of aboveground tillers. Improved understanding of bud bank dynamics may lead to improved predictive models of grassland responses to environmental changes such as altered N deposition and precipitation.

North American grasslands have experienced increased relative abundance of shrubs and trees over the last 150 yr. Alterations in herbivore composition, abundance, and grazing pressure along with changes in fire frequency are drivers that can regulate the transition from grassland to shrubland or woodland (a process known as woody encroachment). Historically, North American grasslands had a suite of large herbivores that grazed and/or browsed (i.e., bison, elk, pronghorn, deer), as well as frequent and intense fires. In the tallgrass prairie, many large native ungulates were extirpated by the 1860s, corresponding with increased homesteading (which led to decreased fire frequencies and intensities). Changes in the frequency and intensity of these two drivers (browsing and fire) have coincided with woody encroachment in tallgrass prairie. Within tallgrass prairie, woody encroachment can be categorized in to two groups: non-resprouting species that can be killed with fire and resprouting species that cannot be killed with fire. Resprouting species require additional active management strategies to decrease abundance and eventually be removed from the ecosystem. In this study, we investigated plant cover, ramet density, and physiological effects of continuous simulated browsing and prescribed fire on Cornus drummondii C.A. Mey, a resprouting clonal native shrub species. Browsing reduced C. drummondii canopy cover and increased grass cover. We also observed decreased ramet density, which allowed for more infilling of grasses. Photosynthetic rates between browsed and unbrowsed control shrubs did not increase in 2015 or 2016. In 2017, photosynthetic rates for browsed shrubs were higher in the unburned site than the unbrowsed control shrubs at the end of the growing season. Additionally, after the prescribed fire, browsed shrubs had ~90% decreased cover, ~50% reduced ramet density, and grass cover increased by ~80%. In the roots of browsed shrubs after the prescribed fire, nonstructural carbohydrates (NSC) experienced a twofold reduction in glucose and a threefold reduction in both sucrose and starch. The combined effects of browsing and fire show strong potential as a successful management tool to decrease the abundance of clonal-resprouting woody plants in mesic grasslands and illustrate the potential significance of browsers as a key driver in this ecosystem.

Central to understanding global C cycle dynamics is the functional relationship between precipitation and net primary production (NPP). At large spatial (regional) scales, the responsiveness of aboveground NPP (ANPP) to inter-annual variation in annual precipitation (AP; ANPP sensitivity ) is inversely related to site-level ANPP, coinciding with turnover of plant communities along precipitation gradients. Within ecosystems experiencing chronic alterations in water availability, plant community change will also occur with unknown consequences for ANPP sensitivity . To examine the role plant community shifts may play in determining alterations in site-level ANPP sensitivity , we experimentally increased precipitation by ~35% for two decades in a native Central US grassland. Consistent with regional models, ANPP sensitivity decreased initially as water availability and ANPP increased. However, ANPP sensitivity shifted back to ambient levels when mesic species increased in abundance in the plant community. Similarly, in grassland sites with distinct mesic and xeric plant communities and corresponding 50% differences in ANPP, ANPP sensitivity did not differ over almost three decades. We conclude that responses in ANPP sensitivity to chronic alterations in water availability within an ecosystem may not conform to regional AP-ANPP patterns, despite expected changes in ANPP and plant communities. The result is unanticipated functional resistance to climate change at the site scale.

Understanding spatial and temporal variation in plant traits is needed to accurately predict how communities and ecosystems will respond to global change. The National Ecological Observatory Network’s (NEON’s) Airborne Observation Platform (AOP) provides hyperspectral images and associated data products at numerous field sites at 1 m spatial resolution, potentially allowing high-resolution trait mapping. We tested the accuracy of readily available data products of NEON’s AOP, such as Leaf Area Index (LAI), Total Biomass, Ecosystem Structure (Canopy height model [CHM]), and Canopy Nitrogen, by comparing them to spatially extensive field measurements from a mesic tallgrass prairie. Correlations with AOP data products exhibited generally weak or no relationships with corresponding field measurements. The strongest relationships were between AOP LAI and ground-measured LAI (r = 0.32) and AOP Total Biomass and ground-measured biomass (r = 0.23). We also examined how well the full reflectance spectra (380–2,500 nm), as opposed to derived products, could predict vegetation traits using partial least-squares regression (PLSR) models. Among all the eight traits examined, only Nitrogen had a validation R² of more than 0.25. For all vegetation traits, validation R² ranged from 0.08 to 0.29 and the range of the root mean square error of prediction (RMSEP) was 14–64%. Our results suggest that currently available AOP-derived data products should not be used without extensive ground-based validation. Relationships using the full reflectance spectra may be more promising, although careful consideration of field and AOP data mismatches in space and/or time, biases in field-based measurements or AOP algorithms, and model uncertainty are needed. Finally, grassland sites may be especially challenging for airborne spectroscopy because of their high species diversity within a small area, mixed functional types of plant communities, and heterogeneous mosaics of disturbance and resource availability. Remote sensing observations are one of the most promising approaches to understanding ecological patterns across space and time. But the opportunity to engage a diverse community of NEON data users will depend on establishing rigorous links with in-situ field measurements across a diversity of sites.

Intermittent streams that regularly dry up constitute over half of the world's river network. They exhibit biogeochemical processes distinct from those of continuously flowing perennial rivers. In perennial rivers, discharge is often perceived as predominantly driving water chemistry, as demonstrated by the widespread use of concentration–discharge (CQ) relationships. Does discharge similarly drive water chemistry in intermittent streams? Given its extended periods of no flow, we hypothesized that stream chemistry depends less on discharge alone but more on the granularity of dry‐wet transitions, including their direction (drying or rewetting), history (antecedent conditions), and intermittency. We tested this hypothesis by analyzing three decades of streamflow and solute chemistry data from an intermittent stream (N04D) in the Konza Prairie Biological Station, a Long‐Term Ecological Research site in Kansas, USA. Results showed that concentrations are generally higher at no flow compared to flow conditions and depend on dry‐wet transitions. Geogenic solutes were predominantly chemostatic (relatively constant C without Q dependence), contrasting primarily dilution patterns (decreasing C with Q) in perennial rivers. Biogenic solutes did not exhibit pronounced discharge‐dependent patterns commonly observed in perennial rivers at decadal scale; at monthly scale, however, they exhibited a transition from highly variable CQ patterns at low flows to consistent flushing patterns (increasing C with Q) at flows higher than 2.5–5 mm/day. These observations support our hypothesis of weaker chemistry dependence on discharge in intermittent streams. We further hypothesize that the emerging discharge thresholds signal a tipping point at which intermittent streams switch from a dry state governed by intermittency‐driven biogeochemistry to a wet, discharge‐driven state resembling perennial rivers. The hypothesis calls for intensive data collection at dry‐wet transitions to develop theories and models for intermittent streams that have become increasingly prevalent globally.

Context The > 25,000 km 2 Flint Hills ecoregion in eastern Kansas and northeastern Oklahoma, USA, is an economically and ecologically important area encompassing the largest remaining tallgrass prairie ecosystem in North America. Prescribed fires are used routinely to control invasive woody species and improve forage production for the beef-cattle industry. However, burning releases harmful pollutants that, at times, contribute to air quality problems for communities across a multi-state area. Objectives Establish a modeling framework for synthesizing long-term ecological data in support of Flint Hills tallgrass prairie management goals for identifying how much, where, and when rangeland burning can be conducted to maximize ecological and economic benefits while minimizing regional air quality impacts. Methods We used EPA’s VELMA ecohydrology model to synthesize long-term experimental data at the 35 km 2 Konza Prairie Biological Station (KPBS) describing the effects of climate, fire, grazing, topography, and soil moisture and nutrient dynamics on tallgrass prairie productivity and fuel loads; and to spatially extrapolate that synthesis to estimate grassland productivity and fuel loads across the nearly 1000 times larger Flint Hills ecoregion to support prescribed burning smoke trajectory modeling using the State of Kansas implementation of the U.S. Forest Service BlueSky framework. Results VELMA provided a performance-tested synthesis of KPBS data from field observations and experiments, thereby establishing a tool for regionally simulating the combined effects of climate, fire, grazing, topography, soil moisture, and nutrients on tallgrass prairie productivity and fuel loads. VELMA’s extrapolation of that synthesis allowed difficult-to-quantify fuel loads to be mapped across the Flint Hills to support environmental decision making, such as forecasting when, where, and how prescribed burning will have the least impact on downwind population centers. Conclusions Our regional spatial and temporal extrapolation of VELMA’s KPBS data synthesis posits that the effects of integrated ecohydrological processes operate similarly across tallgrass prairie spatial scales. Based on multi-scale performance tests of the VELMA-BlueSky toolset, our multi-institution team is confident that it can assist stakeholders and decision makers in realistically exploring tallgrass prairie management options for balancing air quality, tallgrass prairie sustainability, and associated economic benefits for the Flint Hills ecoregion and downwind communities.

Human induced climate and land-use change are severely impacting global biodiversity, but how community composition and richness of multiple taxonomic groups change in response to local drivers and whether these responses are synchronous remains unclear. We used long-term community-level data from an experimentally manipulated grassland to assess the relative influence of climate and land use as drivers of community structure of four taxonomic groups: birds, mammals, grasshoppers, and plants. We also quantified the synchrony of responses among taxonomic groups across land-use gradients and compared climatic drivers of community structure across groups. All four taxonomic groups responded strongly to land use (fire frequency and grazing), while responses to climate variability were more pronounced in grasshoppers and small mammals. Animal groups exhibited asynchronous responses across all land-use treatments, but plant and animal groups, especially birds, exhibited synchronous responses in composition. Asynchrony was attributed to taxonomic groups responding to different components of climate variability, including both current climate conditions and lagged effects from the previous year. Data-driven land management strategies are crucial for sustaining native biodiversity in grassland systems, but asynchronous responses of taxonomic groups to climate variability across land-use gradients highlight a need to incorporate response heterogeneity into management planning.