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Global climate change has been identified as a potential driver of observed insect declines, yet in many regions, there are critical data gaps that make it difficult to assess how communities are responding to climate change. Poleward regions are of particular interest because warming is most rapid while biodiversity data are most sparse. Building on recent advances in occupancy modeling of presence-only data, we reconstructed 50 years (1970-2019) of butterfly occupancy trends in response to rising minimum temperatures in one of the most under-sampled regions of North America. Among 90 modeled species, we found that cold-adapted species are far more often in decline compared with their warm-adapted, more southernly distributed counterparts. Furthermore, in a post hoc analysis using species' traits, we find that species' range-wide average annual temperature is the only consistent predictor of occupancy changes. Species with warmer ranges were most likely to be increasing in occupancy. This trend results in the majority of butterflies increasing in occupancy probability over the last 50 years. Our results provide the first look at macroscale butterfly biodiversity shifts in high-latitude North America. These results highlight the potential of leveraging the wealth of presence-only data, the most abundant source of biodiversity data, for inferring changes in species distributions., (© 2024 John Wiley & Sons Ltd.)

The monarch butterfly is arguably the best-known butterfly species throughout its global range. Declines in the size of the overwintering colonies in Mexico have sparked controversy regarding the conservation of the species and this controversy has been heightened since the United States Fish and Wildlife Service and International Union for the Conservation of Nature concluded that the eastern monarch populations were threatened (or in the case of United States Fish and Wildlife Service, warranted listing). Drivers of decline vary through space and time. Here, we present a synthesis of longitudinal monarch abundance studies that aim to disentangle the putative drivers of decline from one another. We find remarkable consistency that suggests monarch populations are indeed declining and that potential drivers of such decline shift over time. We strongly encourage future work on the species paired with mechanistic, experimental designs to address some long-standing knowledge gaps., Competing Interests: Declaration of Competing Interest We the authors declare no conflict of interest in this work., (Copyright © 2023 Elsevier Inc. All rights reserved.)

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., (© 2023. The Author(s).)

Here, we present the largest, global dataset of Lepidopteran traits, focusing initially on butterflies (ca. 12,500 species records). These traits are derived from field guides, taxonomic treatments, and other literature resources. We present traits on wing size, phenology,voltinism, diapause/overwintering stage, hostplant associations, and habitat affinities (canopy, edge, moisture, and disturbance). This dataset will facilitate comparative research on butterfly ecology and evolution and our goal is to inspire future research collaboration and the continued development of this dataset., (© 2022. The Author(s).)

Large occurrence datasets provide a sizable resource for ecological analyses, but have substantial limitations. Phenological analyses in Fric et al. (2020) were misleading due to inadequate curation and improper statistics. Reanalysing 22 univoltine species with sufficient data for independent analysis, we found substantively different macroscale phenological patterns, including later onset at higher latitude for most species., (© 2021 John Wiley & Sons Ltd.)

The volume of and interest in unstructured participatory science data has increased dramatically in recent years. However, unstructured participatory science data contain taxonomic biases—encounters with some species are more likely to be reported than encounters with others. Taxonomic biases are driven by human preferences for different species and by logistical factors that make observing certain species challenging. We investigated taxonomic bias in reports of butterflies by characterizing differences between a dedicated participatory semi‐structured dataset, eButterfly, and a popular unstructured dataset, iNaturalist, in spatiotemporally explicit models. Across 194 butterfly species, we found that 53 species were overreported and 34 species were underreported in opportunistic data. Ease of identification and feature diversity were significantly associated with overreporting in opportunistic sampling, and strong patterns in overreporting by family were also detected. Quantifying taxonomic biases not only helps us understand how humans engage with nature but also is necessary to generate robust inference from unstructured participatory data. [ABSTRACT FROM AUTHOR]

Natural history collections (NHCs) have been indispensable to understanding longer‐term trends of the timing of seasonal events. Massive‐scale digitization of specimens promises to further enable phenological research, especially the ability to move towards a deeper understanding of drivers of change and how trait–environment interactions shape phenological sensitivity.Despite the promise of NHCs to answer fundamental phenology questions, the use of these data resources presents unique and often overlooked challenges requiring specialized workflow steps, such as assembling multisource data, accounting for date imprecision and making decisions about trade‐offs between data density and spatial resolution.We provide a set of key best practice recommendations and showcase these via a case study that utilizes NHC data to test hypotheses about spatiotemporal trends in adult Lepidoptera (i.e. butterflies and moths) flight timing across North America. Our case study is a worked example of these best practices, helping practitioners recognize and overcome potential pitfalls at each step, from data acquisition and cleaning, to delineating spatial units and proper estimation of phenological metrics and associated uncertainty, to building appropriate models.We confirm and extend the critical importance of voltinism and diapause strategy, but less‐so daily activity patterns, for predicting Lepidoptera phenology spatiotemporal trends. Our case study also showcases the unique power of NHC data to test existing hypotheses and generate new insights about temporal phenological trends. Specifically, migratory species and species that enter diapause as adults are advancing the start of flight periods in more recent years, even after accounting for climate context. These results highlight the physiological and adaptive differences between species with different overwintering strategies.We close by noting the value of partnerships between data scientists, museum experts and ecological modellers to fully harness the power of digital data resources to address pressing global change challenges. These partnerships can extend approaches for integrating multiple data types to fully unlock our understanding of the tempo, mode, drivers and outcomes of phenological changes at greater spatial, temporal and taxonomic scales. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Aggregate biodiversity data from museum specimens and community observations have promise for macroscale ecological analyses. Despite this, many groups are under‐sampled, and sampling is not homogeneous across space. Here we used butterflies, the best documented group of insects, to examine inventory completeness across North America. We separated digitally accessible butterfly records into those from natural history collections and burgeoning community science observations to determine if these data sources have differential spatio‐taxonomic biases. When we combined all data, we found startling under‐sampling in regions with the most dramatic trajectories of climate change and across biomes. We also used multiple methods with each supporting the hypothesis that community science observations are filling more gaps in sampling but are more biased towards areas with the highest human footprint. Finally, we found that both types of occurrences have familial‐level taxonomic completeness biases, in contrast to the hypothesis of less taxonomic bias in natural history collections data. These results suggest that higher inventory completeness, driven by rapid growth of community science observations, is partially offset by higher spatio‐taxonomic biases. We use the findings here to provide recommendations on how to alleviate some of these gaps in the context of prioritizing global change research. [ABSTRACT FROM AUTHOR]

Climate change in concert with fire suppression is increasing the size, severity and frequency of fires globally. At the same time, insects, an exceptionally biodiverse group that provide essential ecosystem services such as pollination and decomposition, are declining precipitously. We know little, however, about the fire mechanisms that contribute to insect decline. To understand if there is a larger global signature of fire on insect communities, we conducted a global systematic search and meta-analyses on the pyroentomology literature for butterflies (Lepidoptera: Rhopalocera), bees (Hymenoptera: Apoidea), and ground beetles (Coleoptera: Carabidae) and report how each taxa's richness and abundance response to overall fire, 16 different fire and site characteristics, as well as fire combined with forest/grassland management treatments. Across 100 studies and 445 effects, we found that bee biodiversity increased after fire and fire in combination with forest/grassland management treatments. In contrast, fire had no significant positive or negative effect on ground beetle and butterfly biodiversity. Furthermore, we did not find any fire and site characteristics that decreased richness across our taxa. Surprisingly, we found that only 7% of the studies quantified fire severity, which likely explains the inconsistent results within the pyroentomology literature. We conclude that further consideration of fire mechanisms will advance our understanding of how insects respond to fires. Our findings on how each taxa's richness and abundance respond to each fire and site characteristic will create a stronger foundation to help scientists and conservation managers make better decisions and predictions to achieve their research and management goals. • We conducted a meta-analysis on 100 pyroentomology studies for three insect taxa. • Only 7% of pyroentomology studies quantified fire severity in their study. • Bee richness and abundance significantly increased from most fire characteristics. • Butterfly and ground beetle richness does not decrease from any fire characteristics. • Limited forest/meadow treatments with prescribed fire show no decrease on our taxa. [ABSTRACT FROM AUTHOR]