Abstract
With documented global declines in insects, including wild bees, there has been increasing interest in developing and expanding insect monitoring programs. Our objective here was to organize, validate, and share an analysis-ready version of one of the few existing long-term monitoring datasets for wild bees in the United States. Since 1999, the Native Bee Inventory and Monitoring Lab (BIML) of the United States Geological Survey has sampled wild-bee communities in the Mid-Atlantic U.S., but samples were collected in multiple studies and the datasets are not fully integrated. Furthermore, critical information about sampling methodology was often lacking, though these factors can significantly influence collection outcomes and must be considered in analyses. We cleaned and verified BIML data from Maryland, Delaware, and Washington DC, USA, and generated sampling methodology for over 84% of the 99,053 pan-trapped occurrences in this region. We enthusiastically invite creative analyses of this rich dataset to advance understanding of the biology and ecology of wild bees, inform conservation efforts, and perhaps help design a nationwide bee monitoring program.
Highlights
Background & SummaryWild bees are crucial pollinators of many crop and wild-plant species
To fully utilize the Bee Inventory and Monitoring Lab (BIML) dataset collected with multiple methods, trap color should be included as a variable in statistical analyses
We focused on occurrences collected in pan traps because they represent more than 82% of the larger BIML dataset
Summary
Background & SummaryWild bees are crucial pollinators of many crop and wild-plant species. To fully utilize the BIML dataset collected with multiple methods, trap color should be included as a variable in statistical analyses. We cleaned and verified BIML data and extracted trap color, volume, and sampling effort for more than 84% of the pan-trapped occurrences.
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