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Abstract The plants of the circumpolar Arctic occupy a dynamic system that has been shaped by glacial cycles and climate change on evolutionary timescales. Yet rapid climatic change can compromise the floristic diversity of the tundra, and the ecological and evolutionary changes in the Arctic from anthropogenic forces remain understudied. In this review, we synthesize knowledge of Arctic floral biodiversity across the entirety of the region within the context of its climatic history. We present critical gaps and challenges in modeling and documenting the consequences of anthropogenic changes for Arctic flora, informed by data from the Late Quaternary (~20 ka). We found that previous forecasts of Arctic plant responses to climate change indicate widespread reductions in habitable area with increasing shrub growth and abundance as a function of annual temperature increase. Such shifts in the distribution and composition of extant Arctic flora will likely increase with global climate through changes to the carbon cycle, necessitating a unified global effort in conserving these plants. More data and research on the continuity of tundra communities are needed to firmly assess the risk climate change poses to the Arctic. 

The partitioning of global biodiversity into biogeographic regions is critical for understanding the impacts of global-scale ecological and evolutionary processes on species assemblages as well as prioritizing areas for conservation. However, the lack of globally comprehensive data on species distributions precludes fine-scale estimation of biogeographical regionalization for numerous taxa of ecological, economic and conservation interest. Using a recently published phylogeny and novel curated native range maps for over 10 000 species of butterflies around the world, we delineated biogeographic regions for the world’s butterflies using phylogenetic dissimilarity. We uncovered 19 distinct phylogenetically delimited regions (phyloregions) nested within 6 realms. Regional boundaries were predicted by spatial turnover in modern-day temperature and precipitation seasonality, but historical climate change also left a pronounced fingerprint on deeper- (realm-) level boundaries. We use a culturally and ecologically important group of insects to expand our understanding of how historical and contemporary factors drive the distribution of organismal lineages on the Earth. As insects and global biodiversity more generally face unprecedented challenges from anthropogenic factors, our research provides the groundwork for prioritizing regions and taxa for conservation, especially with the goal of preserving the legacies of our biosphere’s evolutionary history. This article is part of the discussion meeting issue ‘Bending the curve towards nature recovery: building on Georgina Mace's legacy for a biodiverse future’. 

While considerable evidence exists of biogeographic patterns in the intensity of species interactions, the influence of these patterns on variation in community structure is less clear. Studying how the distributions of traits in communities vary along global gradients can inform how variation in interactions and other factors contribute to the process of community assembly. Using a model selection approach on measures of trait dispersion in crustaceans associated with eelgrass ( Zostera marina ) spanning 30° of latitude in two oceans, we found that dispersion strongly increased with increasing predation and decreasing latitude. Ocean and epiphyte load appeared as secondary predictors; Pacific communities were more overdispersed while Atlantic communities were more clustered, and increasing epiphytes were associated with increased clustering. By examining how species interactions and environmental filters influence community structure across biogeographic regions, we demonstrate how both latitudinal variation in species interactions and historical contingency shape these responses. Community trait distributions have implications for ecosystem stability and functioning, and integrating large-scale observations of environmental filters, species interactions and traits can help us predict how communities may respond to environmental change.