Search for: All records

Abstract While some relationships in phylogenomic studies have remained stable since the Sanger sequencing era, many challenging nodes remain, even with genome-scale data. Incongruence or lack of resolution in the phylogenomic era is frequently attributed to inadequate data modeling and analytical issues that lead to systematic biases. However, few studies investigate the potential for random error or establish expectations for the level of resolution achievable with a given empirical data set and integrate uncertainties across methods when faced with conflicting results. Ants are the most species-rich lineage of social insects and one of the most ecologically important terrestrial animals. Consequently, ants have garnered significant research attention, including their systematics. Despite this, there has been no comprehensive genus-level phylogeny of the ants inferred using genomic data that thoroughly evaluates both signal strength and incongruence. In this study, we provide insight into and quantify uncertainty across the ant tree of life by utilizing the most taxonomically comprehensive ultraconserved elements data set of ants to date, including 277 (81%) of recognized ant genera from all 16 extant subfamilies, and representing over 98% of described species. We use simulations to establish expectations for resolution, identify branches with less-than-expected concordance, and dissect the effects of data and model selection on recalcitrant nodes. Simulations show that hundreds of loci are needed to resolve recalcitrant nodes on our genus-level ant phylogeny. This demonstrates the continued role of random error in phylogenomic studies. Our analyses provide a comprehensive picture of support and incongruence across the ant phylogeny, while offering a more nuanced depiction of uncertainty and significantly expanding generic sampling. We use a consensus approach to integrate uncertainty across different analyses and find that assumptions about root age exert substantial influence on divergence dating. Our results suggest that advancing the understanding of ant phylogeny will require not only more data but also more refined phylogenetic models. We also provide a workflow for identifying under-supported nodes in concatenation analyses, outline a pragmatic way to reconcile conflicting results in phylogenomics, and introduce a user-friendly locus selection tool for divergence dating. 

Abstract Insects are declining in abundance and species richness, globally. This has broad implications for the ecology of our planet, many of which we are only beginning to understand. Comprehensive, large-scale efforts are urgently needed to quantify and mitigate insect biodiversity loss. Because there is broad interest in this topic from a range of scientists, policymakers, and the general public, we posit that such endeavors will be most effective with precise and standardized terms. The Entomological Society of America is the world’s largest association of professional entomologists and is ideally positioned to lead the way on this front. We provide here a glossary of definitions for biodiversity loss terminology. This can be used to enhance and clarify communication among entomologists and others with an interest in addressing the multiple overlapping research, policy, and outreach challenges surrounding this urgent issue. 

There is a general lack of consensus on the best practices for filtering of single‐nucleotide polymorphisms (SNPs) and whether it is better to use SNPs or include flanking regions (full “locus”) in phylogenomic analyses and subsequent comparative methods. Using genotyping‐by‐sequencing data from 22Glycinespecies, we assessed the effects of SNP vs. locus usage and SNP retention stringency. We compared branch length, node support, and divergence time estimation across 16 datasets with varying amounts of missing data and total size. Our results revealed five aspects of phylogenomic data usage that may be generally applicable: (1) tree topology is largely congruent across analyses; (2) filtering strictly for SNP retention (e.g., 90–100%) reduces support and can alter some inferred relationships; (3) absolute branch lengths vary by two orders of magnitude between SNP and locus datasets; (4) data type and branch length variation have little effect on divergence time estimation; and (5) phylograms alter the estimation of ancestral states and rates of morphological evolution. Using SNP or locus datasets does not alter phylogenetic inference significantly, unless researchers want or need to use absolute branch lengths. We recommend against using excessive filtering thresholds for SNP retention to reduce the risk of producing inconsistent topologies and generating low support. 

Biodiversity is the word used to describe the rich variety of life on Earth. Right now, Earth’s biodiversity is threatened. Museums, zoos, and other kinds of natural history collections help to protect biodiversity. One way they do this is by helping researchers study life on Earth. Another way is by teaching people, through exhibits and events. Natural history collections face many challenges. One challenge is getting enough money to stay open. Another is finding new space as collections grow. Finally, some people who want to use and learn from collections cannot access them because they are not nearby. Museum collections are now putting information on the internet, so that many people can access and use it. We can all help natural history collections to continue protecting Earth’s biodiversity by visiting them, volunteering, and donating specimens or other resources. 

The last Xerces blue butterfly was seen in the early 1940s, and its extinction is credited to human urban development. This butterfly has become a North American icon for insect conservation, but some have questioned whether it was truly a distinct species, or simply an isolated population of another living species. To address this question, we leveraged next-generation sequencing using a 93-year-old museum specimen. We applied a genome skimming strategy that aimed for the organellar genome and high-copy fractions of the nuclear genome by a shallow sequencing approach. From these data, we were able to recover over 200 million nucleotides, which assembled into several phylogenetically informative markers and the near-complete mitochondrial genome. From our phylogenetic analyses and haplotype network analysis we conclude that the Xerces blue butterfly was a distinct species driven to extinction. 

Abstract Dated, geo‐referenced museum specimens are a rich data source for reconstructing species' distribution and abundance patterns. However, museum records are potentially biased towards over‐representation of rare species, and it is unclear whether museum records can be used to estimate relative abundance in the field.We assembled 17 coupled field and museum datasets to quantitatively compare relative abundance estimates with the Dirichlet distribution. Collectively, these datasets comprise 73,039 museum records and 1,405,316 field observations of 2,240 species.Although museum records of rare species overestimated relative abundance by 1‐fold to over 100‐fold (median study = 9.0), the relative abundance of species estimated from museum occurrence records was strongly correlated with relative abundance estimated from standardized field surveys (r²range of 0.10–0.91, median study = 0.43).These analyses provide a justification for estimating species relative abundance with carefully curated museum occurrence records, which may allow for the detection of temporal or spatial shifts in the rank ordering of common and rare species.