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ABSTRACT Disruptions to functionally important symbionts with global change will negatively impact plant fitness, with broader consequences for species' abundances, distribution, and community composition. Fungal endophytes that live inside plant leaves and roots could potentially mitigate plant heat stress from global warming. Conversely, disruptions of these symbioses could exacerbate the negative impacts of warming. To better understand the consistency and strength of warming‐induced changes to fungal endophytes, we examined fungal leaf and root endophytes in three grassland warming experiments in the US ranging from 2 to 25 years and spanning 2000 km, 12°C of mean annual temperature, and 600 mm of precipitation. We found that experimental warming disrupted symbiosis between plants and fungal endophytes. Colonization of plant tissues by septate fungi decreased in response to warming by 90% in plant leaves and 35% in roots. Warming also reduced fungal diversity and changed community composition in plant leaves, but not roots. The strength, but not direction, of warming effects on fungal endophytes varied by up to 75% among warming experiments. Finally, warming decoupled fungal endophytes from host metabolism by decreasing the correlation between endophyte community and host metabolome dissimilarity. These effects were strongest in the shorter‐term experiment, suggesting endophyte‐host metabolome function may acclimate to warming over decades. Overall, warming‐driven disruption of fungal endophyte community structure and function suggests that this symbiosis may not be a reliable mechanism to promote plant resilience and ameliorate stress responses under global change. 

Abstract Global change is impacting plant community composition, but the mechanisms underlying these changes are unclear. Using a dataset of 58 global change experiments, we tested the five fundamental mechanisms of community change: changes in evenness and richness, reordering, species gains and losses. We found 71% of communities were impacted by global change treatments, and 88% of communities that were exposed to two or more global change drivers were impacted. Further, all mechanisms of change were equally likely to be affected by global change treatments—species losses and changes in richness were just as common as species gains and reordering. We also found no evidence of a progression of community changes, for example, reordering and changes in evenness did not precede species gains and losses. We demonstrate that all processes underlying plant community composition changes are equally affected by treatments and often occur simultaneously, necessitating a wholistic approach to quantifying community changes. 

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.