Elise A. Larsen

Understanding the impacts of climate on migratory dynamics is a priority for global change research, especially as phenological mismatches have been identified as a primary concern for long-distance migration. The eastern monarch ( Danaus plexippus ) is a flagship species for insect migration, but there has been surprisingly little research on their spring and summer migratory timing and mismatches with their key breeding resources. We show that spring, but not summer, phenological mismatch with their milkweed host plants has the potential to be a limiting factor in the eastern monarch’s yearly population growth. To better understand arrival at their breeding grounds, we developed models specifically to tease apart the factors that push (from departure grounds), pull (towards arrival grounds), or facilitate flow (in the flight corridor) during migration. We found wind (flow) dynamics to be the most important factor associated with arrival timing, especially in spring. Further, we show how spring and summer migratory flyways coincide with the large-scale Hadley and Ferrel atmospheric cells respectively, and how their dynamics appear to be essential for understanding monarch migratory timing.

Numerous declines have been documented across insect groups, and the potential consequences of insect losses are dire. Butterflies are the most surveyed insect taxa, yet analyses have been limited in geographic scale or rely on data from a single monitoring program. Using records of 12.6 million individual butterflies from >76,000 surveys across 35 monitoring programs, we characterized overall and species-specific butterfly abundance trends across the contiguous United States. Between 2000 and 2020, total butterfly abundance fell by 22% across the 554 recorded species. Species-level declines were widespread, with 13 times as many species declining as increasing. The prevalence of declines throughout all regions in the United States highlights an urgent need to protect butterflies from further losses.

Recent reports of insect declines have raised concerns about the potential for concomitant losses to ecosystem processes. However, understanding the causes and consequences of insect declines is challenging, especially given the data deficiencies for most species. Needed are approaches that can help quantify the magnitude and potential causes of declines at levels above species. Here we present an analytical framework for assessing broad‐scale plant–insect phenologies and their relationship to community‐level insect abundance patterns. We intentionally apply a species‐neutral approach to analyse trends in phenology and abundance at the macroecological scale. Because both phenology and abundance are critical to ecosystem processes, we estimate aggregate metrics using the overwintering (diapause) stage, a key species trait regulating phenology and environmental sensitivities. This approach can be used across broad spatiotemporal scales and multiple taxa, including less well‐studied groups. Using community (‘citizen’) science butterfly observations from multiple platforms across the Eastern USA, we show that the relationships between environmental drivers, phenology and abundance depend on the diapause stage. In particular, egg‐diapausing butterflies show marked changes in adult‐onset phenology in relation to plant phenology and are rapidly declining in abundance over a 20‐year span across the study region. Our results also demonstrate the negative consequences of warmer winters for the abundance of egg‐diapausing butterflies, irrespective of plant phenology. In sum, the diapause stage strongly shapes both phenological sensitivities and developmental requirements across seasons, providing a basis for predicting the impacts of environmental change across trophic levels. Utilizing a framework that ties thermal performance across life stages in relation to climate and lower‐trophic‐level phenology provides a critical step towards predicting changes in ecosystem processes provided by butterflies and other herbivorous insects into the future. Read the free Plain Language Summary for this article on the Journal blog.

Previous phenological analyses of GBIF records ignored data biases and produced misleading results. Here we demonstrate how data sufficiency and methodology affect inferred latitudinal patterns in lepidopteran phenology, highlighting the importance of spatiotemporal data aggregation decisions. Results indicate later and/or shorter flight period phenology at higher latitudes is common.

Caterpillars (larval Lepidoptera) are an essential link in trophic networks of forest ecosystems, as they serve as herbivores of vegetation and a food source for many organisms. Phenological mismatches between caterpillars, host plants, or predators may have negative effects across multiple trophic levels. Seasonal timing of caterpillar emergence and peak occurrence may be impacted by climate change, however, studying caterpillar phenology at broad spatial scales is challenging due to lack of data availability. Here, we examine two sources of caterpillar observations, opportunistic records from iNaturalist and structured surveys of forest caterpillars, and compare whether phenology patterns in these datasets are consistent across larval datasets and with more numerous records of adult butterflies. Despite substantial taxonomic differences between these three datasets, we found concurrence in patterns of early and late years in spring onset between datasets. However, the datasets do differ in how well they capture phenological responses to warmer spring temperatures. More data-rich iNaturalist caterpillar and adult butterfly records may provide a reasonable proxy of interannual deviations in forest caterpillars, however, expansions in structured survey efforts are needed to capture changing patterns in other ecologically important measures such as abundance and biomass.

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.

Data availability limits phenological research at broad temporal and spatial extents. Butterflies are among the few taxa with broad-scale occurrence data, from both incidental reports and formal surveys. Incidental reports have biases that are challenging to address, but structured surveys are often limited seasonally and may not span full flight phenologies. Thus, how these data source compare in phenological analyses is unclear. We modeled butterfly phenology in relation to traits and climate using parallel analyses of incidental and survey data, to explore their shared utility and potential for analytical integration. One workflow aggregated “Pollard” surveys, where sites are visited multiple times per year; the other aggregated incidental data from online portals: iNaturalist and eButterfly. For 40 species, we estimated early (10%) and mid (50%) flight period metrics, and compared the spatiotemporal patterns and drivers of phenology across species and between datasets. For both datasets, inter-annual variability was best explained by temperature, and seasonal emergence was earlier for resident species overwintering at more advanced stages. Other traits related to habitat, feeding, dispersal, and voltinism had mixed or no impacts. Our results suggest that data integration can improve phenological research, and leveraging traits may predict phenology in poorly studied species.

Butterflies are a diverse and charismatic insect group that are thought to have diversified via coevolution with plants and in response to dispersals following key geological events. These hypotheses have been poorly tested at the macroevolutionary scale because a comprehensive phylogenetic framework and datasets on global distributions and larval hosts of butterflies are lacking. We sequenced 391 genes from nearly 2,000 butterfly species to construct a new, phylogenomic tree of butterflies representing 92% of all genera and aggregated global distribution records and larval host datasets. We found that butterflies likely originated in what is now the Americas, ∼100 Ma, shortly before the Cretaceous Thermal Maximum, then crossed Beringia and diversified in the Paleotropics. The ancestor of modern butterflies likely fed on Fabaceae, and most extant families were present before the K/Pg extinction. The majority of butterfly dispersals occurred from the tropics (especially the Neotropics) to temperate zones, largely supporting a “cradle” pattern of diversification. Surprisingly, host breadth changes and shifts to novel host plants had only modest impacts.

Data availability limits phenological research at broad temporal and spatial extents. Butterflies are among the few taxa with broad-scale occurrence data, from both incidental reports and formal surveys. Incidental reports have observation biases that are challenging to address, but structured surveys are often limited seasonally and may not span full flight phenologies. Thus, which data source is more useful for phenological analyses is unclear. We use parallel analyses of incidental and survey data to determine how traits and climate drive phenological patterns for common butterflies. One workflow aggregated “Pollard” surveys, where sites are visited multiple times per year; the other aggregated incidental data from online portals: iNaturalist and eButterfly. For 40 routinely observed resident species, we estimated early (10%) and mid (50%) flight period metrics, and compared the spatiotemporal patterns and drivers of phenology across species and between datasets. Results were similar between datasets. Inter-annual variability was best explained by temperature, and seasonal emergence was earlier for resident species that overwinter at more advanced stages. Other traits had mixed or no impacts. The consistency in results suggests that data integration can improve phenological research, and leveraging traits may predict phenology in poorly studied species.

Insect phenological lability is key for determining which species will adapt under environmental change. However, little is known about when adult insect activity terminates and overall activity duration. We used community‐science and museum specimen data to investigate the effects of climate and urbanisation on timing of adult insect activity for 101 species varying in life history traits. We found detritivores and species with aquatic larval stages extend activity periods most rapidly in response to increasing regional temperature. Conversely, species with subterranean larval stages have relatively constant durations regardless of regional temperature. Species extended their period of adult activity similarly in warmer conditions regardless of voltinism classification. Longer adult durations may represent a general response to warming, but voltinism data in subtropical environments are likely underreported. This effort provides a framework to address the drivers of adult insect phenology at continental scales and a basis for predicting species response to environmental change.