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Abstract Grasslands cover approximately a third of the Earth’s land surface and account for about a third of terrestrial carbon storage. Yet, we lack strong predictive models of grassland plant biomass, the primary source of carbon in grasslands. This lack of predictive ability may arise from the assumption of linear relationships between plant biomass and the environment and an underestimation of interactions of environmental variables. Using data from 116 grasslands on six continents, we show unimodal relationships between plant biomass and ecosystem characteristics, such as mean annual precipitation and soil nitrogen. Further, we found that soil nitrogen and plant diversity interacted in their relationships with plant biomass, such that plant diversity and biomass were positively related at low levels of nitrogen and negatively at elevated levels of nitrogen. Our results show that it is critical to account for the interactive and unimodal relationships between plant biomass and several environmental variables to accurately include plant biomass in global vegetation and carbon models. 

Abstract In our changing world, understanding plant community responses to global change drivers is critical for predicting future ecosystem composition and function. Plant functional traits promise to be a key predictive tool for many ecosystems, including grasslands; however, their use requires both complete plant community and functional trait data. Yet, representation of these data in global databases is sparse, particularly beyond a handful of most used traits and common species. Here we present the CoRRE Trait Data, spanning 17 traits (9 categorical, 8 continuous) anticipated to predict species’ responses to global change for 4,079 vascular plant species across 173 plant families present in 390 grassland experiments from around the world. The dataset contains complete categorical trait records for all 4,079 plant species obtained from a comprehensive literature search, as well as nearly complete coverage (99.97%) of imputed continuous trait values for a subset of 2,927 plant species. These data will shed light on mechanisms underlying population, community, and ecosystem responses to global change in grasslands worldwide. 

Abstract All multicellular organisms host a diverse microbiome composed of microbial pathogens, mutualists, and commensals, and changes in microbiome diversity or composition can alter host fitness and function. Nonetheless, we lack a general understanding of the drivers of microbiome diversity, in part because it is regulated by concurrent processes spanning scales from global to local. Global-scale environmental gradients can determine variation in microbiome diversity among sites, however an individual host’s microbiome also may reflect its local micro-environment. We fill this knowledge gap by experimentally manipulating two potential mediators of plant microbiome diversity (soil nutrient supply and herbivore density) at 23 grassland sites spanning global-scale gradients in soil nutrients, climate, and plant biomass. Here we show that leaf-scale microbiome diversity in unmanipulated plots depended on the total microbiome diversity at each site, which was highest at sites with high soil nutrients and plant biomass. We also found that experimentally adding soil nutrients and excluding herbivores produced concordant results across sites, increasing microbiome diversity by increasing plant biomass, which created a shaded microclimate. This demonstration of consistent responses of microbiome diversity across a wide range of host species and environmental conditions suggests the possibility of a general, predictive understanding of microbiome diversity. 

Abstract Research internships provide students with invaluable experience conducting independent research, contributing to larger research programs, and embedding in a professional scientific setting. These experiences increase student persistence in ecology and other science, technology, engineering, and mathematics (STEM) fields and promote the inclusion of students who lack opportunities at their home institutions and/or are from groups that are underrepresented in STEM. While many ecology internship programs were canceled during the 2020 COVID‐19 pandemic, others successfully adapted to offer virtual internships for the first time. Though different from what many researchers and students envision when they think of internships, virtual ecology internship programs can create more accessible opportunities and be just as valuable as in‐person opportunities when research programs and advisors develop virtual internships with intention and planning. Here, we highlight six ways to structure a virtual intern project, spanning a spectrum from purely computer‐based opportunities (e.g., digital data gathering, data analysis, or synthesis) to fully hands‐on research (e.g., sample processing or home‐based experiments). We illustrate examples of these virtual projects through a case study of the Smithsonian Environmental Research Center's 2020 Virtual Internship Program. Next, we provide 10 recommendations for effectively developing a virtual internship program. Finally, we end with ways that virtual internships can avoid the limitations of in‐person internships, as well as possible solutions to perceived pitfalls of virtual internships. While virtual internships became a necessity in 2020 due to COVID‐19, the development and continuation of virtual internships in future can be a valuable tool to add to the suite of existing internship opportunities, possibly further promoting diversity, equity, and inclusion in ecology and STEM. 

Abstract Grassland and other herbaceous communities cover significant portions of Earth's terrestrial surface and provide many critical services, such as carbon sequestration, wildlife habitat, and food production. Forecasts of global change impacts on these services will require predictive tools, such as process‐based dynamic vegetation models. Yet, model representation of herbaceous communities and ecosystems lags substantially behind that of tree communities and forests. The limited representation of herbaceous communities within models arises from two important knowledge gaps: first, our empirical understanding of the principles governing herbaceous vegetation dynamics is either incomplete or does not provide mechanistic information necessary to drive herbaceous community processes with models; second, current model structure and parameterization of grass and other herbaceous plant functional types limits the ability of models to predict outcomes of competition and growth for herbaceous vegetation. In this review, we provide direction for addressing these gaps by: (1) presenting a brief history of how vegetation dynamics have been developed and incorporated into earth system models, (2) reporting on a model simulation activity to evaluate current model capability to represent herbaceous vegetation dynamics and ecosystem function, and (3) detailing several ecological properties and phenomena that should be a focus for both empiricists and modelers to improve representation of herbaceous vegetation in models. Together, empiricists and modelers can improve representation of herbaceous ecosystem processes within models. In so doing, we will greatly enhance our ability to forecast future states of the earth system, which is of high importance given the rapid rate of environmental change on our planet. 

Abstract Dominance often indicates one or a few species being best suited for resource capture and retention in a given environment. Press perturbations that change availability of limiting resources can restructure competitive hierarchies, allowing new species to capture or retain resources and leaving once dominant species fated to decline. However, dominant species may maintain high abundances even when their new environments no longer favour them due to stochastic processes associated with their high abundance, impeding deterministic processes that would otherwise diminish them.Here, we quantify the persistence of dominance by tracking the rate of decline in dominant species at 90 globally distributed grassland sites under experimentally elevated soil nutrient supply and reduced vertebrate consumer pressure.We found that chronic experimental nutrient addition and vertebrate exclusion caused certain subsets of species to lose dominance more quickly than in control plots. In control plots, perennial species and species with high initial cover maintained dominance for longer than annual species and those with low initial cover respectively. In fertilized plots, species with high initial cover maintained dominance at similar rates to control plots, while those with lower initial cover lost dominance even faster than similar species in controls. High initial cover increased the estimated time to dominance loss more strongly in plots with vertebrate exclosures than in controls. Vertebrate exclosures caused a slight decrease in the persistence of dominance for perennials, while fertilization brought perennials' rate of dominance loss in line with those of annuals. Annual species lost dominance at similar rates regardless of treatments.Synthesis.Collectively, these results point to a strong role of a species' historical abundance in maintaining dominance following environmental perturbations. Because dominant species play an outsized role in driving ecosystem processes, their ability to remain dominant—regardless of environmental conditions—is critical to anticipating expected rates of change in the structure and function of grasslands. Species that maintain dominance while no longer competitively favoured following press perturbations due to their historical abundances may result in community compositions that do not maximize resource capture, a key process of system responses to global change. 

Plants are subject to tradeoffs among growth strategies such that adaptations for optimal growth in one condition can preclude optimal growth in another. Thus, we predicted that a plant species that responds positively to one global change treatment would be less likely than average to respond positively to another treatment, particularly for pairs of treatments that favor distinct traits. We examined plant species abundances in 39 global change experiments manipulating two or more of the following: CO2, nitrogen, phosphorus, water, temperature, or disturbance. Overall, the directional response of a species to one treatment was 13% more likely than expected to oppose its response to a another single-factor treatment. This tendency was detectable across the global dataset but held little predictive power for individual treatment combinations or within individual experiments. While tradeoffs in the ability to respond to different global change treatments exert discernible global effects, other forces obscure their influence in local communities.