Completeness analysis for over 3000 United States bee species identifies persistent data gap

Abstract

Native bee species in the United States provide invaluable pollination services. Concerns about native bee declines are growing, and there are calls for a national monitoring program. Documenting species ranges at ecologically meaningful scales through coverage completeness analysis is a fundamental step to track bees from species to communities. It may take decades before all existing bee specimens are digitized, so projections are needed now to focus future research and management efforts. From 1.923 million records, we created range maps for nearly 88% (3158 species) of bee species in the contiguous United States, provided the first analysis of inventory completeness for digitized specimens of a major insect clade, and perhaps most important, estimated spatial completeness accounting for all known bee specimens in USA collections, including undigitized bee specimens. Completeness analyses were very low (3–37%) across four examined spatial resolutions when using the currently available bee specimen records. Adding a subset of observations from community science data sources did not significantly increase completeness, and adding a projected 4.7 million undigitized specimens increased completeness by only an additional 12–13%. Assessments of data, including projected specimen records, indicate persistent taxonomic and geographic deficiencies. In conjunction with expedited digitization, new inventories that integrate community science data with specimen‐based documentation will be required to close these gaps. A combined effort involving both strategic inventories and accelerated digitization campaigns is needed for a more complete understanding of USA bee distributions.

Biodiversity conservation at the digital age, will Africa meet the challenge?

“…Collecting data in the de cient classes should therefore be among the priorities for new collections. New data collections that integrate community science data with specimen-based documentation and development of societal initiatives like citizen science can help achieve that purpose [32,33,34]. Many medicinal plants, microalgae, and phytoplankton belong to the underrepresented plant classes.…”

“…Opening of new roads, with more representativeness of ecological conditions of the landscapes across African countries, can signi cantly contribute to less biased data collections. Addressing less charismatic species and developing societal initiatives like citizen science can also contribute to less biased data collection [32]. More incentives in data publication and more intense connections between researchers can also contribute to lling gaps of information [10].…”

A globally synthesised and flagged bee occurrence dataset and cleaning workflow

“…Where public and private data were duplicated, we gave preference to private data providers over the public data aggregators under the assumption that data providers have the most recent information. We also preferred manually cleaned occurrence records from Chesshire, et al 93 over those sourced directly from data aggregators. All pairwise duplicates were clustered where they overlapped and a single best occurrence was kept using the above arrangement.…”

“…InputData. Contains the major repository downloads, additional input datasets, and custom Chesshire, et al 93 data files. 4.…”

“…Contains the “cleaned” (05_cleaned_database.csv) and “flagged-but-uncleaned” (05_unCleaned_database.csv) datasets, reports, and the R console outputs from the script (RunNotes_BeeBDC_1Sep23.txt). InputData. Contains the major repository downloads, additional input datasets, and custom Chesshire, et al 93 data files. ExtraTables. Contains metadata for the major repository downloads (MajorRepoAttributes_2023-09-01.xlsx) and the added taxonomy variants (AddedTaxonomyVariants.xlsx). The beesTaxonomy.Rda and beesChecklist.Rda datasets that are downloaded using BeeBDC (see 10.…”