These raw survey data and associated explanatory covariates were used to model western bumble bee occupancy across the western conterminous United States from 1998 to 2020. These data underlie the analyses found in the publication of “Recent and future declines of a historically widespread pollinator linked to climate, land cover, and pesticides” by Janousek et al. 2023 in the Proceedings of the National Academy of Sciences vol. 120, issue 5. The covariate data are provided in a scaled format for use in the occupancy model, and the scaling parameters used to transform the data to the original (real) scale are provided in the scaling information file.

Bee-Gap describes the ecology, life-history, and distribution of 3,925 bee species in the United States that have geographical data and verified taxonomy. The database was constructed by compiling information from a broad range of internet sources and peer-reviewed journal articles. The 10 traits included in the database are: native status (native versus exotic/introduced), state and territory presence/absence, adult habitat, nesting strategy, voltinism, sociality, host bee species (for parasitic bees only), foraging strategy (generalist vs specialist), known host plants, and tongue length.

This study generated genetic 'metabarcode' data using high-throughput sequencing to characterize pollen foraging behavior of pollinating bee species on managed field habitat within units of the National Park Service. Specimens were collected within parks of the National Capital Region from 2021-2023 and subsequently identified to species or genus. DNA was then extracted from specimens using leg samples if pollen was adherent to the corbiculae ("pollen baskets") of corbiculate bees, otherwise using whole-body samples. This data release consists of three tab-delimited files and a file of DNA sequences: 1) sample.metadata.txt includes sample identifiers and the accessions they have been assigned by the National Center for Biotechnology Information (NCBI), the authoritative repository for publicly funded genetic data in the United States. These accessions can be used individually to obtain raw sequencing data or sample information at www.ncbi.nlm.nih.gov. Alternatively, the BioProject accession PRJNA1236404 can be searched to retrieve the full set of data and sample accessions listed in the file. Entity and attribute metadata are provided for this file herein. 2) ITS2.raw.pollen.counts.txt includes the inferred taxon counts at the ITS2 locus, i.e. number of ITS2 sequences in a sample attributable to each identified taxon in each sample. 3. potential.contaminants.txt lists plant taxa that were over-represented in negative controls samples within a particular sequence run. Values for these plant taxa in these runs should either be zeroed-out or adjusted based on a statistical model to account for potential sample contamination. Censoring data based on results in negative controls is a standard practice in metabarcoding. Many samples in this study were very small and/or had no visible pollen, which increases the potential for contamination as the endogenous DNA concentration is expected to be very low in these cases. 3) reference.db.fas contains the plant reference DNA sequences used for taxonomic assignment of the pollen sample sequences.

,Supplemental information from a project describing the transcriptome of a beetle parasite of honey bees,The small hive beetle (SHB), Aethina tumida, is a major pest of managed honey bee (Apis mellifera) colonies in the United States and Australia, and an emergent threat in Europe. While strong honey bee colonies generally keep SHB populations in check, weak or stressed colonies can succumb to infestations. This parasite has spread from a sub-Saharan Africa to three continents, leading to immense management and regulatory costs. We performed a transcriptomic analysis involving deep sequencing of multiple life stages and both sexes of this species. The assembled transcriptome appears to be nearly complete, as judged by conserved insect orthologs and the ability to find plausible homologs for 11,952 proteins described from the genome of the red flour beetle. Expressed genes include each of the major metabolic, developmental and sensory groups, along with genes for proteins involved with immune defenses and insecticide resistance. We also present a total of 23,085 high-quality SNP's for the assembled contigs. We highlight potential differences between this beetle and its honey bee hosts, and suggest mechanisms of future research into the biology and control of this species. SNP resources will allow functional genetic analyses and analyses of dispersal for this invasive pest.,,