Biology subjects

Barve, V.

Publications and source records attributed to Barve, V..

4 recordsLinked to original sources

bioRxiv2022

Evolution and diversification dynamics of butterflies

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.

evolutionary biology↗

bioRxiv2020

Spatial phylogenetics of butterflies in relation to environmental drivers and angiosperm diversity across North America

Broad-scale quantitative assessments of biodiversity and the factors shaping it remain particularly poorly explored in insects. Here, we undertook a spatial phylogenetic analysis of North American butterflies via assembly of a time-calibrated phylogeny of the region coupled with a unique, complete range assessment for ~75% of the known species. We utilized a suite of phylodiversity metrics and associated environmental data to test whether climate stability and temperature gradients have shaped North American butterfly phylogenetic diversity and endemism. We also undertook the first direct, quantitative comparisons of spatial phylogenetic patterns between butterflies and flowering plants in North America. We expected concordance between butterflies and angiosperms based on both shared historical environmental drivers and presumed strong butterfly-host plant specializations. We instead found that biodiversity patterns in butterflies are strikingly different from flowering plants in some regions of the continent. In particular, the warm desert regions of the southwestern United States and Mexico showed surprisingly high butterfly phylogenetic diversity and endemism, in contrast to much lower values for angiosperms. Butterflies did not show patterns of phylogenetic clustering as found in flowering plants, suggesting differences in habitat conservation between the two groups. Finally, we found weak relationships and spatially structured biases in relative branching timing between angiosperms and butterflies. These results suggest that shared biogeographic histories and trophic associations do not necessarily assure similar diversity outcomes. The work has applied value in conservation planning, documenting warm deserts as an important North American butterfly biodiversity hotspot.

ecology↗

bioRxiv2020

Closing Gaps But Increasing Bias In North American Butterfly Inventory Completeness

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 found support for 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.

ecology↗

bioRxiv2019

Methods for broad-scale plant phenology assessments using citizen scientists’ photographs

Broad-scale plant flowering phenology data has predominantly come from geographically and taxonomically restricted monitoring networks. However, platforms such as iNaturalist, where citizen scientists upload photographs and curate identifications, provide a promising new source of data. Here we develop a general set of best practices for scoring iNaturalist digital records supporting downstream re-use in phenology studies. We focus on a case study group, Yucca, because it has showy flowers and is well documented on iNaturalist. Additionally, drivers of Yucca phenology are not well-understood despite need for Yucca to synchronize flowering with obligate moth pollinators. Finally, evidence of anomalous flowering events have been recently reported, but the extent of those events is unknown. We use best-practices approach to annotate nearly 9,000 Yucca iNaturalist records, and compare the spatiotemporal coverage of this dataset with other broad-scale monitoring resources. Our findings demonstrate that iNaturalist provides unique phenology information, including delineation of extents of unusual flowering events. We also determine if unusual early flowering events impact later, typical flowering periods. Finally, we adapt a plant phenology global knowledge-store to integrate iNaturalist annotation results, supporting broadest reuse. Our approach has application to other plant groups, leveraging rapidly increasing data resources from iNaturalist to study phenology.

ecology↗