TY - JOUR
T1 - A long-term dataset on wild bee abundance in Mid-Atlantic United States
AU - Kammerer, Melanie
AU - Tooker, John F.
AU - Grozinger, Christina M.
N1 - Funding Information:
We are indebted to Sam Droege and the USGS BIML team for generously sharing data from their pioneering monitoring effort. We also thank Sarah Goslee, Maggie Douglas, DJ McNeil and Grozinger lab members for helpful discussions on project framing and an earlier version of this manuscript. We thank Shelby Kilpatrick, David Biddinger, and Sam Droege for assistance verifying species names and two anonymous reviewers for feedback that substantially improved the manuscript. Funding was provided by the United State Department of Agriculture National Institute for Food and Agriculture (USDA NIFA) pre-doctoral fellowship PENW-2017-07007 to MK, Foundation for Food and Agriculture Research grant #549032 to CMG, and the Pennsylvania State University Intercollege Graduate Degree Program in Ecology.
Publisher Copyright:
© 2020, The Author(s).
PY - 2020/12/1
Y1 - 2020/12/1
N2 - 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.
AB - 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.
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U2 - 10.1038/s41597-020-00577-0
DO - 10.1038/s41597-020-00577-0
M3 - Article
C2 - 32686678
AN - SCOPUS:85088257788
SN - 2052-4463
VL - 7
JO - Scientific data
JF - Scientific data
IS - 1
M1 - 240
ER -