Litcius/Paper detail

A long-term dataset on wild bee abundance in Mid-Atlantic United States

Melanie Kammerer, John F. Tooker, Christina M. Grozinger

2020Scientific Data20 citationsDOIOpen Access PDF

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.

Topics & Concepts

Abundance (ecology)Sampling (signal processing)EcologyTerm (time)Honey beeGeographySampling designEnvironmental resource managementBiologyEnvironmental scienceComputer scienceDemographyPhysicsFilter (signal processing)Computer visionSociologyQuantum mechanicsPopulationPlant and animal studiesInsect and Pesticide ResearchInsect and Arachnid Ecology and Behavior