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Abstract Forbs (“wildflowers”) are important contributors to grassland biodiversity but are vulnerable to environmental changes. In a factorial experiment at 94 sites on 6 continents, we test the global generality of several broad predictions: (1) Forb cover and richness decline under nutrient enrichment, particularly nitrogen enrichment. (2) Forb cover and richness increase under herbivory by large mammals. (3) Forb richness and cover are less affected by nutrient enrichment and herbivory in more arid climates, because water limitation reduces the impacts of competition with grasses. (4) Forb families will respond differently to nutrient enrichment and mammalian herbivory due to differences in nutrient requirements. We find strong evidence for the first, partial support for the second, no support for the third, and support for the fourth prediction. Our results underscore that anthropogenic nitrogen addition is a major threat to grassland forbs, but grazing under high herbivore intensity can offset these nutrient effects. 

ABSTRACT Accurately representing the relationships between nitrogen supply and photosynthesis is crucial for reliably predicting carbon–nitrogen cycle coupling in Earth System Models (ESMs). Most ESMs assume positive correlations amongst soil nitrogen supply, leaf nitrogen content, and photosynthetic capacity. However, leaf photosynthetic nitrogen demand may influence the leaf nitrogen response to soil nitrogen supply; thus, responses to nitrogen supply are expected to be the largest in environments where demand is the greatest. Using a nutrient addition experiment replicated across 26 sites spanning four continents, we demonstrated that climate variables were stronger predictors of leaf nitrogen content than soil nutrient supply. Leaf nitrogen increased more strongly with soil nitrogen supply in regions with the highest theoretical leaf nitrogen demand, increasing more in colder and drier environments than warmer and wetter environments. Thus, leaf nitrogen responses to nitrogen supply are primarily influenced by climatic gradients in photosynthetic nitrogen demand, an insight that could improve ESM predictions. 

Abstract Nutrient enrichment impacts grassland plant diversity such as species richness, functional trait composition and diversity, but whether and how these changes affect ecosystem stability in the face of increasing climate extremes remains largely unknown.We quantified the direct and diversity‐mediated effects of nutrient addition (by nitrogen, phosphorus, and potassium) on the stability of above‐ground biomass production in 10 long‐term grassland experimental sites. We measured five facets of stability as the temporal invariability, resistance during and recovery after extreme dry and wet growing seasons.Leaf traits (leaf carbon, nitrogen, phosphorus, potassium, and specific leaf area) were measured under ambient and nutrient addition conditions in the field and were used to construct the leaf economic spectrum (LES). We calculated functional trait composition and diversity of LES and of single leaf traits. We quantified the contribution of intraspecific trait shifts and species replacement to change in functional trait composition as responses to nutrient addition and its implications for ecosystem stability.Nutrient addition decreased functional trait diversity and drove grassland communities to the faster end of the LES primarily through intraspecific trait shifts, suggesting that intraspecific trait shifts should be included for accurately predicting ecosystem stability. Moreover, the change in functional trait diversity of the LES in turn influenced different facets of stability. That said, these diversity‐mediated effects were overall weak and/or overwhelmed by the direct effects of nutrient addition on stability. As a result, nutrient addition did not strongly impact any of the stability facets. These results were generally consistent using individual leaf traits but the dominant pathways differed. Importantly, major influencing pathways differed using average trait values extracted from global trait databases (e.g. TRY).Synthesis. Investigating changes in multiple facets of plant diversity and their impacts on multidimensional stability under global changes such as nutrient enrichment can improve our understanding of the processes and mechanisms maintaining ecosystem stability. 

Abstract Biotic and abiotic factors interact with dominant plants—the locally most frequent or with the largest coverage—and nondominant plants differently, partially because dominant plants modify the environment where nondominant plants grow. For instance, if dominant plants compete strongly, they will deplete most resources, forcing nondominant plants into a narrower niche space. Conversely, if dominant plants are constrained by the environment, they might not exhaust available resources but instead may ameliorate environmental stressors that usually limit nondominants. Hence, the nature of interactions among nondominant species could be modified by dominant species. Furthermore, these differences could translate into a disparity in the phylogenetic relatedness among dominants compared to the relatedness among nondominants. By estimating phylogenetic dispersion in 78 grasslands across five continents, we found that dominant species were clustered (e.g., co‐dominant grasses), suggesting dominant species are likely organized by environmental filtering, and that nondominant species were either randomly assembled or overdispersed. Traits showed similar trends for those sites (<50%) with sufficient trait data. Furthermore, several lineages scattered in the phylogeny had more nondominant species than expected at random, suggesting that traits common in nondominants are phylogenetically conserved and have evolved multiple times. We also explored environmental drivers of the dominant/nondominant disparity. We found different assembly patterns for dominants and nondominants, consistent with asymmetries in assembly mechanisms. Among the different postulated mechanisms, our results suggest two complementary hypotheses seldom explored: (1) Nondominant species include lineages adapted to thrive in the environment generated by dominant species. (2) Even when dominant species reduce resources to nondominant ones, dominant species could have a stronger positive effect on some nondominants by ameliorating environmental stressors affecting them, than by depleting resources and increasing the environmental stress to those nondominants. These results show that the dominant/nondominant asymmetry has ecological and evolutionary consequences fundamental to understand plant communities. 

Abstract Spatial rarity is often used to predict extinction risk, but rarity can also occur temporally. Perhaps more relevant in the context of global change is whether a species is core to a community (persistent) or transient (intermittently present), with transient species often susceptible to human activities that reduce niche space. Using 5–12 yr of data on 1,447 plant species from 49 grasslands on five continents, we show that local abundance and species persistence under ambient conditions are both effective predictors of local extinction risk following experimental exclusion of grazers or addition of nutrients; persistence was a more powerful predictor than local abundance. While perturbations increased the risk of exclusion for low persistence and abundance species, transient but abundant species were also highly likely to be excluded from a perturbed plot relative to ambient conditions. Moreover, low persistence and low abundance species that were not excluded from perturbed plots tended to have a modest increase in abundance following perturbance. Last, even core species with high abundances had large decreases in persistence and increased losses in perturbed plots, threatening the long‐term stability of these grasslands. Our results demonstrate that expanding the concept of rarity to include temporal dynamics, in addition to local abundance, more effectively predicts extinction risk in response to environmental change than either rarity axis predicts alone.