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Abstract PremiseUnderstanding relationships among grass traits, fire, and herbivores may help improve conservation strategies for savannas that are threatened by novel disturbance regimes. Emerging theory, developed in Africa, emphasizes that functional traits of savanna grasses reflect the distinct ways that fire and grazers consume biomass. Specifically, functional trade‐offs related to flammability and palatability predict that highly flammable grass species will be unpalatable, while highly palatable species will impede fire. MethodsWe quantified six culm and leaf traits of 337 native grasses of Texas—a historical savanna region that has been transformed by fire exclusion, megafaunal extinctions, and domestic livestock. ResultsMultivariate analyses of traits revealed three functional strategies. “Grazer grasses” (N = 50) had culms that were short, narrow, and horizontal, and leaves with high width to length (W:L) and low C to N ratios (C:N)—trait values that attract grazers and avoid fire. “Fire grasses” (N = 104) had culms that were tall, thick, and upright, and leaves that were thick, with low W:L, and high C:N—trait values that promote fire and discourage grazers. “Generalist tolerators” and “generalist avoiders” (N = 183) had trait values that were intermediate to the other groups. ConclusionsOur findings confirm that the flammability–palatability trade‐offs that operate in Africa also explain correlated suites of traits in Texas grasses and highlights that the grass flora of Texas bears the signature of Pleistocene megafauna and the influence of fires that predate human arrival. We suggest that grass functional classifications based on fire and grazer traits can improve prescribed fire and livestock management of savannas of Texas and globally. 

Abstract Background and AimsQuantifying niche similarity among closely related species offers myriad insights into evolutionary history and ecology. In this study, our aim was to explore the interplay of geographical and niche space for rare, endemic plant species and to determine whether endemic habitats were environmentally similar or unique. MethodsWe characterized the niche of all Leavenworthia species, a genus of rare plants endemic to rocky glades in the eastern USA, using WorldClim data, surface geology, elevation and slope. We calculated the area of range overlap and estimated niche similarity between pairs of species in their total occupied niche space and the subset of niche space shared by both species. We used linear discriminant analyses to determine which niche dimensions differed the most between species. We used niche dimensions with consistently high discriminatory power to perform a random forest classification analysis and principal component analysis. Using a linear model, we related geographical distance to distance in niche space. Key ResultsMost species comparisons concluded that species niches had diverged, with niche similarity increasing linearly with range overlap. Temperature variation, precipitation amount and seasonality, and surface geology were the most divergent niche dimensions among all species comparisons. Geographical distance explained 42 % of the variation in niche space distance. Sites that were closer in niche space than expected were oriented east–west owing to the strong correlation between latitude and scores on the first principal component. ConclusionsDespite being endemic seemingly to very similar habitat, niche similarity is low among Leavenworthia species. Low niche similarity, combined with low geographical overlap, suggests that this lineage of rare plants potentially diversified in isolation but across a very small geographical area. The correlation between geographical space and niche space has received considerable attention, but our results suggest that geographical distance is a weak predictor of distance in niche space. 

Abstract Generalization is difficult to quantify, and many classifications exist. A beta diversity framework can be used to establish a numeric measure of generalist tendencies that jointly describes many important features of species interactions, namely spatiotemporal heterogeneity. This framework is promising for studying generalized symbiotic relationships of any form.We formulated a novel index, turnover importance (T).Tdescribes spatiotemporal heterogeneity in interactor assemblages, an inherent feature of generalist relationships that is not captured by available metrics. We simulated the behaviour ofTrelative to other available metrics, calculatedTfor native North American orchid‐insect relationships, and tested correlations betweenTand eco‐geographic variables. We performed case studies to demonstrate applications ofTfor conservation and eco‐evolutionary studies.Tbehaves predictably across simulations, and dynamically interacts with site number, gamma diversity, and species range sizes.Tis moderately sensitive to sampling depth. Orchids with higherTscores occupy larger ranges and broader climatic niches.Alternative interactor‐specific measures of generalism are best employed for local‐level community networks over short timespans. While these interactor metrics can assess use versus availability in local communities,Tcan be used to measure spatiotemporal patterns of variation in interactor assemblages across a focal species' range. This study provides a roadmap for future work focused on better understanding the patterns and consequences of generalized relationships. 

Summary Poales are one of the most species‐rich, ecologically and economically important orders of plants and often characterise open habitats, enabled by unique suites of traits. We test six hypotheses regarding the evolution and assembly of Poales in open and closed habitats throughout the world, and examine whether diversification patterns demonstrate parallel evolution.We sampled 42% of Poales species and obtained taxonomic and biogeographic data from the World Checklist of Vascular Plants database, which was combined with open/closed habitat data scored by taxonomic experts. A dated supertree of Poales was constructed. We integrated spatial phylogenetics with regionalisation analyses, historical biogeography and ancestral state estimations.Diversification in Poales and assembly of open and closed habitats result from dynamic evolutionary processes that vary across lineages, time and space, most prominently in tropical and southern latitudes. Our results reveal parallel and recurrent patterns of habitat and trait transitions in the species‐rich families Poaceae and Cyperaceae. Smaller families display unique and often divergent evolutionary trajectories.The Poales have achieved global dominance via parallel evolution in open habitats, with notable, spatially and phylogenetically restricted divergences into strictly closed habitats. 

Abstract Species interactions drive ecosystem processes and are a major focus of global change research. Among the most consequential interactions expected to shift with climate change are those between insect herbivores and plants, both of which are highly sensitive to temperature. Insect herbivores and their host plants display varying levels of synchrony that could be disrupted or enhanced by climate change, yet empirical data on changes in synchrony are lacking. Using evidence of herbivory on herbarium specimens collected from the northeastern United States and France from 1900 to 2015, we provide evidence that plant species with temperature‐sensitive phenologies experience higher levels of insect damage in warmer years, while less temperature‐sensitive, co‐occurring species do not. While herbivory might be mediated by interactions between warming and phenology through multiple pathways, we suggest that warming might lengthen growing seasons for phenologically sensitive plant species, exposing their leaves to herbivores for longer periods of time in warm years. We propose that elevated herbivory in warm years may represent a previously underappreciated cost to phenological tracking of climate change over longer timescales. 

Summary Though substantial effort has gone into predicting how global climate change will impact biodiversity patterns, the scarcity of taxon‐specific information has hampered the efficacy of these endeavors. Further, most studies analyzing spatiotemporal patterns of biodiversity focus narrowly on species richness.We apply machine learning approaches to a comprehensive vascular plant database for the United States and generate predictive models of regional plant taxonomic and phylogenetic diversity in response to a wide range of environmental variables.We demonstrate differences in predicted patterns and potential drivers of native vs nonnative biodiversity. In particular, native phylogenetic diversity is likely to decrease over the next half century despite increases in species richness. We also identify that patterns of taxonomic diversity can be incongruent with those of phylogenetic diversity.The combination of macro‐environmental factors that determine diversity likely varies at continental scales; thus, as climate change alters the combinations of these factors across the landscape, the collective effect on regional diversity will also vary. Our study represents one of the most comprehensive examinations of plant diversity patterns to date and demonstrates that our ability to predict future diversity may benefit tremendously from the application of machine learning.