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Estimates of recent biodiversity change remain inconsistent, debated, and infrequently assessed for their functional implications. Here, we report that spatial scale and type of biodiversity measurement influence evidence of temporal biodiversity change. We show a pervasive scale dependence of temporal trends in taxonomic (TD) and functional (FD) diversity for an ~50-year record of avian assemblages from North American Breeding Bird Survey and a record of global extinctions. Average TD and FD increased at all but the global scale. Change in TD exceeded change in FD toward large scales, signaling functional resilience. Assemblage temporal dissimilarity and turnover (replacement of species or functions) declined, while nestedness (tendency of assemblages to be subsets of one another) increased with scale. Patterns of FD change varied strongly among diet and foraging guilds. We suggest that monitoring, policy, and conservation require a scale-explicit framework to account for the pervasive effect that scale has on perceived biodiversity change.

Butterflies are a diverse and charismatic insect group that are thought to have evolved with plants and dispersed throughout the world in response to key geological events. However, these hypotheses have not been extensively tested because a comprehensive phylogenetic framework and datasets for butterfly larval hosts and global distributions are lacking. We sequenced 391 genes from nearly 2,300 butterfly species, sampled from 90 countries and 28 specimen collections, to reconstruct a new phylogenomic tree of butterflies representing 92% of all genera. Our phylogeny has strong support for nearly all nodes and demonstrates that at least 36 butterfly tribes require reclassification. Divergence time analyses imply an origin ~100 million years ago for butterflies and indicate that all but one family were present before the K/Pg extinction event. We aggregated larval host datasets and global distribution records and found that butterflies are likely to have first fed on Fabaceae and originated in what is now the Americas. Soon after the Cretaceous Thermal Maximum, butterflies crossed Beringia and diversified in the Palaeotropics. Our results also reveal that most butterfly species are specialists that feed on only one larval host plant family. However, generalist butterflies that consume two or more plant families usually feed on closely related plants.

The characterization of species’ environmental niches and spatial distribution predictions based on them are now central to much of ecology and conservation, but implicitly requires decisions about the appropriate spatial scale (i.e.,grain) of analysis. Ecological theory and empirical evidence suggest that range‐resident species respond to their environment at two characteristic, hierarchical spatial grains: (1)response grain, the (relatively fine) grain at which an individual uses environmental resources, and (2)occupancy grain, the (relatively coarse) grain equivalent to a typical home range. We use a multi‐grain (MG) occupancy model, aided by fine‐grain remotely sensed imagery, to simultaneously estimate species–environment associations at both grains, conduct grain optimization to measure response grain, and apply this analysis framework to an example species: a medium‐sized bird (Tockus deckeni) in a heterogeneous East African landscape. Based on home range analysis of movement data, we calculate an occupancy grain of 1 km forT. deckeni. Using a grain optimization procedure across 32 grains from 10 to 500 m, we identify 60 m as the most strongly supported response grain for a suite of environmental variables, slightly coarser than opportunistic behavioral observations would have suggested. Validation confirms that the accuracy of the optimized MG occupancy model substantially exceeds that of equivalent single‐grain (SG) occupancy models. We further use a simulation approach to assess the potential impacts of accounting for the multi‐scale structure of species’ environmental requirements on estimates of population size. We find that the more strongly supported MG approach consistently predicts a minimum population size in the study landscape that is much lower than that provided by the SG model. This suggests that SG approaches commonly used in conservation applications could lead to overly optimistic abundance and population estimates, and that the MG approach may be more appropriate for supporting species conservation goals. More generally, we conclude that multi‐grain approaches of the sort presented, and increasingly enabled by growing high‐resolution remotely sensed data, hold great promise for offering a more mechanistic framework for assessing the appropriate grain(s) for population monitoring and management and enable more reliable estimates of abundances and species’ distributions.

Assessments of spatial patterns of biodiversity change are essential to detect a signature of anthropogenic impacts, inform monitoring and conservation programs, and evaluate implications of biodiversity loss to humans. While taxonomic diversity (TD) is the most commonly assessed attribute of biodiversity, it misses the potential functional or phylogenetic implications of species losses or gains for ecosystems. Functional diversity (FD) and phylogenetic diversity (PD) are able to capture these important trait‐based and phylogenetic attributes of species, but their changes have to date only been evaluated over limited spatial and temporal extents. Employing a novel framework for addressing detectability, we here comprehensively assess a near half‐century of changes in localTD,FD, andPDof breeding birds across much of North America to examine levels of congruency in changes among these biodiversity facets and their variation across spatial and environmental gradients. Time‐series analysis showed significant and continuous increases in all three biodiversity attributes until ca. 2000, followed by a slow decline since. Comparison of avian diversity at the beginning and end of the temporal series revealed net increase inTD,FD, andPD, but changes inTDwere larger than those inFDandPD, suggesting increasing biotic homogenization of avian assemblages throughout the United States. Changes were greatest at high elevations and latitudes – consistent with purported effects of ongoing climate change on biodiversity. Our findings highlight the potential of combining new types of data with novel statistical models to enable a more integrative monitoring and assessment of the multiple facets of biodiversity.

Understanding patterns and drivers of species distribution and abundance, and thus biodiversity, is a core goal of ecology. Despite advances in recent decades, research into these patterns and processes is currently limited by a lack of standardized, high‐quality, empirical data that span large spatial scales and long time periods. The NEON fills this gap by providing freely available observational data that are generated during robust and consistent organismal sampling of several sentinel taxonomic groups within 81 sites distributed across the United States and will be collected for at least 30 years. The breadth and scope of these data provide a unique resource for advancing biodiversity research. To maximize the potential of this opportunity, however, it is critical that NEON data be maximally accessible and easily integrated into investigators' workflows and analyses. To facilitate its use for biodiversity research and synthesis, we created a workflow to process and format NEON organismal data into the ecocomDP (ecological community data design pattern) format that were available through the ecocomDP R package; we then provided the standardized data as an R data package (neonDivData). We briefly summarize sampling designs and data wrangling decisions for the major taxonomic groups included in this effort. Our workflows are open‐source so the biodiversity community may: add additional taxonomic groups; modify the workflow to produce datasets appropriate for their own analytical needs; and regularly update the data packages as more observations become available. Finally, we provide two simple examples of how the standardized data may be used for biodiversity research. By providing a standardized data package, we hope to enhance the utility of NEON organismal data in advancing biodiversity research and encourage the use of the harmonized ecocomDP data design pattern for community ecology data from other ecological observatory networks.