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. 2020 Jul 20;7:240. doi: 10.1038/s41597-020-00577-0

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

Melanie Kammerer 1,2,✉, John F Tooker 1,2, Christina M Grozinger 1,2
PMCID: PMC7371858  PMID: 32686678

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.

Subject terms: Conservation biology, Biodiversity, Entomology

Measurement(s) Abundance
Technology Type(s) digital curation
Factor Type(s) site • year
Sample Characteristic - Organism Apoidea
Sample Characteristic - Location United States of America
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Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12473270

Background & Summary

Wild bees are crucial pollinators of many crop and wild-plant species. Globally, 87 out of 115 major food crops require insect pollination and 78% of temperate plant species and 94% of tropical plant species require insect pollination for reproductive success and persistence1,2. Wild-bee conservation is crucial for global biodiversity as pollinators represent several extremely diverse taxa and have a vital co-evolved role in supporting and selecting for diverse plant communities3.

In Europe and the United States, there has been a surge of interest in developing programs to monitor wild-bee populations4–7. There have been documented declines in several North American bumble bees populations and species8, but we largely lack baseline data to assess declines in many other taxa. In response to heavy colony losses since 2006, monitoring of honey bee (Apis mellifera L.) populations has greatly increased9. These data have greatly contributed to our understanding of honey bee population dynamics, ecological interactions, colony stressors, and effective management.

We expect coordinated, wild-bee monitoring will enable similar advances in understanding wild-bee diversity, natural history, and conservation strategies, but there are still several challenges in collecting and analysing monitoring data. Ideally, a wild-bee monitoring program, or any monitoring program for that matter, would utilize consistent methods over time to detect long-term population trends. In practice, monitoring protocols often shift over time, and many existing datasets were compiled from studies using multiple sampling methods10.

Our goal here was to organize, validate, and share an analysis-ready version of one of the few existing long-term, wild-bee monitoring datasets in the United States. Since 1999, the Native Bee Inventory and Monitoring Lab (BIML) of the United States Geological Survey has collected, curated, and identified over 99,000 specimens of more than 314 wild bee species from over 1400 sites in Maryland, Delaware, and Washington DC. The BIML collection is among the most geographically dense, recent sampling of wild bees in the country. Also, all specimens were lethally collected and expert-identified to species, which provides a crucial comparison for observation-based datasets with coarser taxonomic information, including rapidly growing citizen science data11,12.

BIML data contain considerable diversity in wild-bee-sampling methods and critical sampling information is often missing or not easily accessible to end-users. One goal of BIML research was to test a variety of passive sampling methods to establish a standard protocol for wild-bee monitoring. They studied sampling efficiency of passive pan traps (bee bowls) with varying trap color, volume, and liquid. Pan traps are a reliable method for monitoring wild bees13,14, particularly in combination with net collections or transect walks, but the specific pan-trapping method, especially trap color and visibility, influences the abundance and composition of wild bees collected15–17. To fully utilize the BIML dataset collected with multiple methods, trap color should be included as a variable in statistical analyses. Currently, this is not possible with the publicly available BIML data18 as 90% of the pan-trapped occurrences in Maryland, Delaware, and DC have no trap color data. Similarly, 36% of occurrences are missing trap volume and 21% lack sampling effort (the number of traps used during each sampling period). Fortunately, much of the missing information was recorded in BIML field notes, but not in a consistent, accessible format.

To fill these gaps, we cleaned and verified BIML data and extracted trap color, volume, and sampling effort for more than 84% of the pan-trapped occurrences. We focused on occurrences collected in pan traps because they represent more than 82% of the larger BIML dataset. We also created, for all pan-trapped occurrences, identifier variables and verified species binomials, date, and locality. We enthusiastically invite analyses of this rich dataset to advance understanding of bee biology and ecology, inform current wild bee conservation efforts, and perhaps even help design a national wild bee monitoring program.

Methods

Identifier variables

To facilitate aggregation and analysis of the BIML data, we added ‘site’, ‘site-year’, ‘sampling event’, and ‘transect’ identifier variables. We defined ‘sites’ as unique combinations of latitude and longitude, and ‘site-years’ as unique combinations of site and year of sampling. Within site-years, we defined ‘sampling events’ according to the date of sampling and ‘transects’ as unique combinations of sampling event and text field notes. For some specimens, field notes included a transect ID, indicating that the BIML used multiple sets of pan traps at the same site. In other cases, field notes recorded differing sampling methods, or different information on the number of missing traps (traps that were cracked, tipped over, or otherwise compromised). If field notes recorded different methods or number of lost traps, we assumed that the BIML deployed multiple sets of traps (transects). We reviewed the field notes for all sampling events with multiple transects and reassigned these occurrences to a single transect if there was no evidence of multiple transects in the field notes.

Locality and taxonomic identification

Next, we reviewed and excluded occurrences lacking critical date and locality information. We removed all occurrences lacking sampling date or latitude and longitude of sampling location and occurrences with duplicated specimen identifiers. We filtered occurrences to a limited geographic area (Maryland, Delaware, and Washington DC, Fig. 1) that represents the densest region of BIML sampling (39.6% of dataset). This filtering removed wild-bee communities collected in desert or tropical biomes, which are likely governed by very different floral resource and climate dynamics19,20, and within the Mid-Atlantic USA, limited sampling locations to a region with a consistent dominant forest type21. Bee occurrences in 1999 and 2001 represented fewer than three sites per year, so we removed these years, retaining sites sampled from 2002–2016.

Fig. 1.

Fig. 1

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Abundance per day per trap of wild bees at locations surveyed between 2002 and 2016 by the United States Geological Survey Native Bee Inventory and Monitoring Lab (USGS BIML).

We also filtered data to our taxa of interest. We removed non-bee occurrences (species outside superfamily Apoidea, clade Anthophila) and records lacking species-level identity, discarding occurrences identified to family or genus (Online-only Table 1). Almost all non-bee occurrences we removed were wasps in the Vespidae, Crabronidae, and Sphecidae families, which are primarily predators, rather than pollen-collectors like most wild bees. For the transect-level dataset22 (see ‘Data Records’ below), we calculated the abundance of Apis mellifera L., then removed A. mellifera from the dataset before calculating total bee abundance per transect, since often A. mellifera specimens likely originated from managed colonies and are not considered to be wild bees.

Online-only Table 1.

List of all specimen names that were modified or removed during data cleaning with justification for each change.

Original species name Cleaned name Grouped name Genus species Family Reason for modification/removal
Modified species names
  Andrena arabis/algida Andrena algida/arabis Andrena algida/arabis Andrena algida/arabis Andrenidae Reordered multiple species names
  Lasioglossum carlini Andrena carlini Andrena carlini Andrena carlini Andrenidae Incorrect genus
  Andrena tridens/erythronii Andrena erythronii/tridens Andrena erythronii/tridens Andrena erythronii/tridens Andrenidae Reordered multiple species names
  Amdrema imitatrix/morrisonella Andrena imitatrix/morrisonella Andrena imitatrix/morrisonella Andrena imitatrix/morrisonella Andrenidae Corrected spelling
  Andrena morisonella Andrena morrisonella Andrena imitatrix/morrisonella Andrena morrisonella Andrenidae Corrected spelling
  Melissodes nivalis Andrena nivalis Andrena nivalis Andrena nivalis Andrenidae Incorrect genus
  Lasioglossum perplexa Andrena perplexa Andrena perplexa Andrena perplexa Andrenidae Incorrect genus
  Nomada personata Andrena personata Andrena personata Andrena personata Andrenidae Incorrect genus
  Andrena puni Andrena pruni Andrena pruni Andrena pruni Andrenidae Corrected spelling
  Pseudopanurgus rudbeckiae Pseudopanurgus near rudbeckiae Pseudopanurgus near rudbeckiae Pseudopanurgus rudbeckiae Andrenidae Recommended by data source (S. Droege)
  apis mellifera Apis mellifera Apis mellifera Apis mellifera Apidae Standardized format
  bombus bimaculatus Bombus bimaculatus Bombus bimaculatus Bombus bimaculatus Apidae Standardized format
  ceratina calcarata Ceratina calcarata Ceratina calcarata/dupla/mikmaqi Ceratina calcarata Apidae Standardized format
  Ceratina mikmaqi/calcarata Ceratina calcarata/mikmaqi Ceratina calcarata/dupla/mikmaqi Ceratina calcarata/mikmaqi Apidae Reordered multiple species names
  ceratina dupla Ceratina dupla Ceratina calcarata/dupla/mikmaqi Ceratina dupla Apidae Standardized format
  Ceratina miqmaki Ceratina mikmaqi Ceratina calcarata/dupla/mikmaqi Ceratina mikmaqi Apidae Corrected spelling
  Ceratina Strenua Ceratina strenua Ceratina strenua Ceratina strenua Apidae Standardized format
  ceratina strenua Ceratina strenua Ceratina strenua Ceratina strenua Apidae Standardized format
  Melissodes tineta Melissodes tinctus Melissodes tinctus Melissodes tinctus Apidae Corrected spelling
  Nomada sayi/illinoensis Nomada illinoensis/sayi Nomada illinoensis/sayi Nomada illinoensis/sayi Apidae Reordered multiple species names
  Nomada sayi/illinoense Nomada illinoensis/sayi Nomada illinoensis/sayi Nomada illinoensis/sayi Apidae Corrected spelling
  Nomada sulphurata/luteola Nomada luteola/sulphurata Nomada luteola/sulphurata Nomada luteola/sulphurata Apidae Reordered multiple species names
  Nomada luteolodies Nomada luteoloides Nomada luteoloides Nomada luteoloides Apidae Corrected spelling
  hylaeus affinis/modestus Hylaeus affinis/modestus Hylaeus affinis/modestus Hylaeus affinis/modestus Colletidae Standardized format
  hylaeus ornatus Hylaeus ornatus Hylaeus ornatus Hylaeus ornatus Colletidae Standardized format
  Agapostemon angelicus/texanus Agapostemon texanus Agapostemon texanus Agapostemon angelicus/texanus Halictidae One species of set not found in Mid-Atlantic USA
  augochlorella aurata Augochlorella aurata Augochlorella aurata Augochlorella aurata Halictidae Standardized format
  Augochlora aurata Augochlorella aurata Augochlorella aurata Augochlorella aurata Halictidae Incorrect genus
  Lasioglossum aurata Augochlorella aurata Augochlorella aurata Augochlorella aurata Halictidae Incorrect genus
  Augochlorellagratiosa Augochlorella gratiosa Augochlorella gratiosa Augochlorella gratiosa Halictidae Standardized format
  Augochloropsis Metallica Augochloropsis metallica Augochloropsis metallica Augochloropsis metallica Halictidae Standardized format
  Halictus poeyi/ligatus Halictus ligatus/poeyi Halictus ligatus/poeyi Halictus ligatus/poeyi Halictidae Reordered multiple species names
  Halitcus poeyi/ligatus Halictus ligatus/poeyi Halictus ligatus/poeyi Halictus ligatus/poeyi Halictidae Corrected spelling
  Haclictus tectus Halictus tectus Halictus tectus Halictus tectus Halictidae Corrected spelling
  Andrena bruneri Lasioglossum bruneri Lasioglossum bruneri Lasioglossum bruneri Halictidae Incorrect genus
  Ceratina callidum Lasioglossum callidum Lasioglossum callidum Lasioglossum callidum Halictidae Incorrect genus
  lasioglossum coreopsis Lasioglossum coreopsis Lasioglossum coreopsis Lasioglossum coreopsis Halictidae Standardized format
  Lasioglossum coeropsis Lasioglossum coreopsis Lasioglossum coreopsis Lasioglossum coreopsis Halictidae Corrected spelling
  Lasioglossum geminum Lasioglossum geminatum Lasioglossum geminatum Lasioglossum geminatum Halictidae Corrected spelling
  Lasioglossum Gotham Lasioglossum gotham Lasioglossum gotham Lasioglossum gotham Halictidae Standardized format
  Andrena hitchensi Lasioglossum hitchensi Lasioglossum hitchensi/weemsi Lasioglossum hitchensi Halictidae Incorrect genus
  Nomada lustrans Lasioglossum lustrans Lasioglossum lustrans Lasioglossum lustrans Halictidae Incorrect genus
  lasioglossum pilosum Lasioglossum pilosum Lasioglossum pilosum Lasioglossum pilosum Halictidae Standardized format
  Sphecodes cressonii/atlantis Sphecodes atlantis/cressonii Sphecodes atlantis/banksii/cressonii Sphecodes atlantis/cressonii Halictidae Reordered multiple species names
  Hoplitis producta/pilosifrons Hoplitis pilosifrons/producta Hoplitis pilosifrons/producta Hoplitis pilosifrons/producta Megachilidae Reordered multiple species names
  hoplitis spoliata Hoplitis spoliata Hoplitis spoliata Hoplitis spoliata Megachilidae Standardized format
  Megachile apicata Megachile apicalis Megachile apicalis Megachile apicalis Megachilidae Corrected spelling
  megachile brevis Megachile brevis Megachile brevis/mendica Megachile brevis Megachilidae Standardized format
  Megachile mendica/brevis Megachile brevis/mendica Megachile brevis/mendica Megachile brevis/mendica Megachilidae Reordered multiple species names
  Osmia atriventis Osmia atriventris Osmia atriventris/pumila Osmia atriventris Megachilidae Corrected spelling
  Osmia pumila/atriventris Osmia atriventris/pumila Osmia atriventris/pumila Osmia atriventris/pumila Megachilidae Reordered multiple species names
  Osmia callinsia Osmia collinsiae Osmia collinsiae Osmia collinsiae Megachilidae Corrected spelling
  Lasioglossum conjuncta Osmia conjuncta Osmia conjuncta Osmia conjuncta Megachilidae Incorrect genus
  Osmia conjucta Osmia conjuncta Osmia conjuncta Osmia conjuncta Megachilidae Corrected spelling
  osmia sandhouseae Osmia sandhouseae Osmia sandhouseae Osmia sandhouseae Megachilidae Standardized format
Removed species names
  Lasioglossum melanopus Not found in Mid-Atlantic USA
  Lasioglossum incompletum Not found in Mid-Atlantic USA
  Hylaeus cressonii Species epithet could not be verified
  Lasioglossum kevensi Species epithet could not be verified
  Osmia composita Species epithet could not be verified
Removed, Genus-only identifications
  Aculeata Specimen identified to genus or subgenus
  Agapostemon Specimen identified to genus or subgenus
  Ancistrocerus Specimen identified to genus or subgenus
  Andrena Specimen identified to genus or subgenus
  Andrena (Melandrena) Specimen identified to genus or subgenus
  Andrena (Scrapteropsis) Specimen identified to genus or subgenus
  Andrena (Trachandrena) Specimen identified to genus or subgenus
  Andrena melandrena Specimen identified to genus or subgenus
  Anthophila Specimen identified to genus or subgenus
  Apidae Specimen identified to genus or subgenus
  Apoidea Specimen identified to genus or subgenus
  Arachnida Specimen identified to genus or subgenus
  Augochlorella Specimen identified to genus or subgenus
  Bombus Specimen identified to genus or subgenus
  Carabidae Specimen identified to genus or subgenus
  Ceratina Specimen identified to genus or subgenus
  Chalcid Specimen identified to genus or subgenus
  Chrysidid Specimen identified to genus or subgenus
  Chrysididae Specimen identified to genus or subgenus
  Coelioxys Specimen identified to genus or subgenus
  Colletes Specimen identified to genus or subgenus
  Figitidae/Eucoilinae Specimen identified to genus or subgenus
  Formicidae Specimen identified to genus or subgenus
  Halictus Specimen identified to genus or subgenus
  Hedychridium Specimen identified to genus or subgenus
  Heriades Specimen identified to genus or subgenus
  Hoplitis Specimen identified to genus or subgenus
  Hylaeus Specimen identified to genus or subgenus
  Ichneumonidae Specimen identified to genus or subgenus
  Ichneumonidae/Ichneunominae Specimen identified to genus or subgenus
  Ichneumonidae/Phygadeuontinae Specimen identified to genus or subgenus
  Ichneumonidae/Tryphoninae Specimen identified to genus or subgenus
  Larrinae Specimen identified to genus or subgenus
  lasioglossum Specimen identified to genus or subgenus
  Lasioglossum Specimen identified to genus or subgenus
  Lasioglossum male Specimen identified to genus or subgenus
  Megachile Specimen identified to genus or subgenus
  Melissodes Specimen identified to genus or subgenus
  Nomada Specimen identified to genus or subgenus
  Osmia Specimen identified to genus or subgenus
  Panurginus Specimen identified to genus or subgenus
  Parancistrocerus Specimen identified to genus or subgenus
  Perdita Specimen identified to genus or subgenus
Pompilidae Specimen identified to genus or subgenus
  Pseudopanurgus Specimen identified to genus or subgenus
  Pteromalidae Specimen identified to genus or subgenus
  Scoliidae Specimen identified to genus or subgenus
  Sphecidae Specimen identified to genus or subgenus
  sphecodes Specimen identified to genus or subgenus
  Sphecodes Specimen identified to genus or subgenus
  Sphecodogastra Specimen identified to genus or subgenus
  Svastra Specimen identified to genus or subgenus
  Tenthredinidae Specimen identified to genus or subgenus
  Tenthredo Specimen identified to genus or subgenus
  Tiphia Specimen identified to genus or subgenus
  Tiphiidae Specimen identified to genus or subgenus
  Tiphiidae/Tiphiinae Specimen identified to genus or subgenus
  Tiphiinae Specimen identified to genus or subgenus
  Triepeolus Specimen identified to genus or subgenus
  Vespidae Specimen identified to genus or subgenus
  Zanysson Specimen identified to genus or subgenus
Removed, species that are not bees
  Acmaeodera ornata Species outside superfamily Apoidea, clade Anthophila
  Acmaeodera pulchella Species outside superfamily Apoidea, clade Anthophila
  Acmaeodera tubulus Species outside superfamily Apoidea, clade Anthophila
  Ammophila fernaldi Species outside superfamily Apoidea, clade Anthophila
  Ammophila nigricans Species outside superfamily Apoidea, clade Anthophila
Ammophila pictipennis Species outside superfamily Apoidea, clade Anthophila
Ammophila procera Species outside superfamily Apoidea, clade Anthophila
  Ammophila urnaria Species outside superfamily Apoidea, clade Anthophila
  Anacrabro ocellatus Species outside superfamily Apoidea, clade Anthophila
  Ancistrocerus adiabatus Species outside superfamily Apoidea, clade Anthophila
  Ancistrocerus albophaleratus Species outside superfamily Apoidea, clade Anthophila
  Ancistrocerus antilope Species outside superfamily Apoidea, clade Anthophila
  Ancistrocerus campestris Species outside superfamily Apoidea, clade Anthophila
  Ancistrocerus cressonii Species outside superfamily Apoidea, clade Anthophila
  Argogorytes nigrifrons Species outside superfamily Apoidea, clade Anthophila
  Astata unicolor Species outside superfamily Apoidea, clade Anthophila
  Bicyrtes ventralis Species outside superfamily Apoidea, clade Anthophila
  Caenochrysis doriae Species outside superfamily Apoidea, clade Anthophila
  Caenochrysis doriae/Cleptes alienus Species outside superfamily Apoidea, clade Anthophila
  Ceratochrysis declinis Species outside superfamily Apoidea, clade Anthophila
  Ceratochrysis enhuycki Species outside superfamily Apoidea, clade Anthophila
  Ceratochrysis kansensis Species outside superfamily Apoidea, clade Anthophila
  Chalybion californicum Species outside superfamily Apoidea, clade Anthophila
  Chrysis angolensis Species outside superfamily Apoidea, clade Anthophila
  Chrysis antennalis Species outside superfamily Apoidea, clade Anthophila
  Chrysis cembricola Species outside superfamily Apoidea, clade Anthophila
  Chrysis conica Species outside superfamily Apoidea, clade Anthophila
  Chrysis derivata Species outside superfamily Apoidea, clade Anthophila
  Chrysis inaequidens Species outside superfamily Apoidea, clade Anthophila
  Chrysis montana Species outside superfamily Apoidea, clade Anthophila
  Chrysis nisseri Species outside superfamily Apoidea, clade Anthophila
  Chrysis nitidula/coerulans Species outside superfamily Apoidea, clade Anthophila
  Chrysis pattoni Species outside superfamily Apoidea, clade Anthophila
  Chrysis pellucidula Species outside superfamily Apoidea, clade Anthophila
  Chrysis propria Species outside superfamily Apoidea, clade Anthophila
  Chrysis remissa Species outside superfamily Apoidea, clade Anthophila
  Chrysis scitula Species outside superfamily Apoidea, clade Anthophila
  Chrysis smaragdala Species outside superfamily Apoidea, clade Anthophila
  Chrysis tripartita Species outside superfamily Apoidea, clade Anthophila
  Chrysura cobaltina Species outside superfamily Apoidea, clade Anthophila
  Chrysura cobaltina/pacifica Species outside superfamily Apoidea, clade Anthophila
  Chrysura kyrae/pacifica Species outside superfamily Apoidea, clade Anthophila
  Chrysura pacifica Species outside superfamily Apoidea, clade Anthophila
  Cicindella sexguttata Species outside superfamily Apoidea, clade Anthophila
  Cinthophora abrupta Species outside superfamily Apoidea, clade Anthophila
  Compsomeris plumipes Species outside superfamily Apoidea, clade Anthophila
  Dolichovespula arenaria Species outside superfamily Apoidea, clade Anthophila
  Dolichovespula maculata Species outside superfamily Apoidea, clade Anthophila
  Ectemnius lapidarius Species outside superfamily Apoidea, clade Anthophila
  Ectemnius rufipes Species outside superfamily Apoidea, clade Anthophila
  Ectemnius scaber Species outside superfamily Apoidea, clade Anthophila
  Epinysson mellipes Species outside superfamily Apoidea, clade Anthophila
  Eremnophila aureonotata Species outside superfamily Apoidea, clade Anthophila
  Eumenes fraternus Species outside superfamily Apoidea, clade Anthophila
  Eumenes reticalis Species outside superfamily Apoidea, clade Anthophila
  Euodynerus annulatus Species outside superfamily Apoidea, clade Anthophila
  Euodynerus boscii Species outside superfamily Apoidea, clade Anthophila
  Euodynerus castigatus Species outside superfamily Apoidea, clade Anthophila
  Euodynerus crypticus Species outside superfamily Apoidea, clade Anthophila
  Euodynerus foraminatus Species outside superfamily Apoidea, clade Anthophila
  Euodynerus hidalgo Species outside superfamily Apoidea, clade Anthophila
  Euodynerus hidalgo boreoorientalis Species outside superfamily Apoidea, clade Anthophila
  Euodynerus leucomelas Species outside superfamily Apoidea, clade Anthophila
  Euodynerus megaera Species outside superfamily Apoidea, clade Anthophila
  Euodynerus schwarzi Species outside superfamily Apoidea, clade Anthophila
  Euodyrnus megaera Species outside superfamily Apoidea, clade Anthophila
  Hedychridium dimidiatum Species outside superfamily Apoidea, clade Anthophila
  Hedychrum confusum/violaceum Species outside superfamily Apoidea, clade Anthophila
  Hedychrum parvum Species outside superfamily Apoidea, clade Anthophila
  Hedychrum violaceum Species outside superfamily Apoidea, clade Anthophila
  Isodontia apicalis Species outside superfamily Apoidea, clade Anthophila
  Isodontia auripes Species outside superfamily Apoidea, clade Anthophila
  Isodontia mexicana Species outside superfamily Apoidea, clade Anthophila
  Isodontia philadelphica Species outside superfamily Apoidea, clade Anthophila
  Leptochilus acolhuus Species outside superfamily Apoidea, clade Anthophila
  Leptochilus republicans Species outside superfamily Apoidea, clade Anthophila
  Leptochilus republicanus Species outside superfamily Apoidea, clade Anthophila
  Lestica confluenta Species outside superfamily Apoidea, clade Anthophila
  Lestica producticollis Species outside superfamily Apoidea, clade Anthophila
  Liris argentatus Species outside superfamily Apoidea, clade Anthophila
  Lyroda subita Species outside superfamily Apoidea, clade Anthophila
  Monobia quadridens Species outside superfamily Apoidea, clade Anthophila
  Oxybelus emarginatum Species outside superfamily Apoidea, clade Anthophila
  Oxybelus emarginatus Species outside superfamily Apoidea, clade Anthophila
  Oxybelus subulatus Species outside superfamily Apoidea, clade Anthophila
  Palmodes collinsiae Species outside superfamily Apoidea, clade Anthophila
  Palmodes dimidiatus Species outside superfamily Apoidea, clade Anthophila
  Palmodes pumila Species outside superfamily Apoidea, clade Anthophila
  Parancistrocerus fulvipes Species outside superfamily Apoidea, clade Anthophila
  Parancistrocerus histrio Species outside superfamily Apoidea, clade Anthophila
  Parancistrocerus leionotus Species outside superfamily Apoidea, clade Anthophila
  Parancistrocerus pedestris Species outside superfamily Apoidea, clade Anthophila
  Parancistrocerus pedestris or pensylvanicus Species outside superfamily Apoidea, clade Anthophila
  Parancistrocerus pedestris pedestris Species outside superfamily Apoidea, clade Anthophila
  Parancistrocerus pensylvanicus Species outside superfamily Apoidea, clade Anthophila
  Parancistrocerus perennis Species outside superfamily Apoidea, clade Anthophila
  Parancistrocerus salcularis Species outside superfamily Apoidea, clade Anthophila
  Parancistrocerus vagus Species outside superfamily Apoidea, clade Anthophila
  Parazumia perennis Species outside superfamily Apoidea, clade Anthophila
  Parazumia symmorpha Species outside superfamily Apoidea, clade Anthophila
  Philanthus gibbosus Species outside superfamily Apoidea, clade Anthophila
  Polistes bellicosus Species outside superfamily Apoidea, clade Anthophila
  Polistes dominula Species outside superfamily Apoidea, clade Anthophila
  Polistes dorsalis Species outside superfamily Apoidea, clade Anthophila
  Polistes exclamans Species outside superfamily Apoidea, clade Anthophila
  Polistes fuscatus Species outside superfamily Apoidea, clade Anthophila
  Polistes hirsuticornis Species outside superfamily Apoidea, clade Anthophila
  Polistes metricus Species outside superfamily Apoidea, clade Anthophila
  Polistes parametricus Species outside superfamily Apoidea, clade Anthophila
  Pompilidae Ctenocerinae Species outside superfamily Apoidea, clade Anthophila
  Prionyx parkeri Species outside superfamily Apoidea, clade Anthophila
  Pseduoanthidium nanum Species outside superfamily Apoidea, clade Anthophila
  Pseudodynerus quadrisectus Species outside superfamily Apoidea, clade Anthophila
  Scolia dubia Species outside superfamily Apoidea, clade Anthophila
  Sphex nudus Species outside superfamily Apoidea, clade Anthophila
  Sphex pensylvanicus Species outside superfamily Apoidea, clade Anthophila
  Stenodynerus ammonia Species outside superfamily Apoidea, clade Anthophila
  Stenodynerus ammonia paraensis Species outside superfamily Apoidea, clade Anthophila
  Stenodynerus anormis Species outside superfamily Apoidea, clade Anthophila
  Stenodynerus blepharus Species outside superfamily Apoidea, clade Anthophila
  Stenodynerus fundatiformis Species outside superfamily Apoidea, clade Anthophila
  Stenodynerus fundatiformis gonosceles Species outside superfamily Apoidea, clade Anthophila
  Stenodynerus histrionalis Species outside superfamily Apoidea, clade Anthophila
  Stenodynerus krombeini Species outside superfamily Apoidea, clade Anthophila
  Stenodynerus oculeus Species outside superfamily Apoidea, clade Anthophila
  Symmorphus canadensis Species outside superfamily Apoidea, clade Anthophila
  Synnevrus plagiatus Species outside superfamily Apoidea, clade Anthophila
  Tachysphex acutus Species outside superfamily Apoidea, clade Anthophila
  Tachysphex antennatus Species outside superfamily Apoidea, clade Anthophila
  Tachysphex belfragei Species outside superfamily Apoidea, clade Anthophila
  Tachysphex mundus Species outside superfamily Apoidea, clade Anthophila
  Tachysphex similis Species outside superfamily Apoidea, clade Anthophila
  Tachysphex tarsatus Species outside superfamily Apoidea, clade Anthophila
  Tachysphex terminatus Species outside superfamily Apoidea, clade Anthophila
  Tachytes abdominalis Species outside superfamily Apoidea, clade Anthophila
  Tachytes chrysopyga obscurus Species outside superfamily Apoidea, clade Anthophila
  Tachytes distinctus Species outside superfamily Apoidea, clade Anthophila
  Tachytes guatemalensis Species outside superfamily Apoidea, clade Anthophila
  Tachytes validus Species outside superfamily Apoidea, clade Anthophila
  Trypoxylon clavicerum Species outside superfamily Apoidea, clade Anthophila
  Trypoxylon frigidum Species outside superfamily Apoidea, clade Anthophila
  Trypoxylon pennsylvanicum Species outside superfamily Apoidea, clade Anthophila
  Typocerus velutinus Species outside superfamily Apoidea, clade Anthophila
  Vespa crabro Species outside superfamily Apoidea, clade Anthophila
  Vespula consobrina Species outside superfamily Apoidea, clade Anthophila
  Vespula flavopilosa Species outside superfamily Apoidea, clade Anthophila
  Vespula germanica Species outside superfamily Apoidea, clade Anthophila
  Vespula maculifrons Species outside superfamily Apoidea, clade Anthophila
  Vespula squamosa Species outside superfamily Apoidea, clade Anthophila
  Vespula vidua Species outside superfamily Apoidea, clade Anthophila
  Zethus spinipes Species outside superfamily Apoidea, clade Anthophila
  Zethus spinipes variegatus Species outside superfamily Apoidea, clade Anthophila
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Species names included in the final datasets22 were verified against a current species list23 and reviewed by S. Droege, the original data producer.

We verified species names by cross-referencing all species binomials with the Discover Life database23. We corrected genus and species names that were clear spelling errors (Online-only Table 1) and consulted the original data source (S. Droege) for remaining species binomials that did not exist on Discover Life. We also referenced Discover Life occurrence maps to confirm that all species in the BIML dataset occur in the Mid-Atlantic US. After these data cleaning steps, we removed six occurrences of the remaining five unknown or out-of-region species (Online-only Table 1). Some species in the BIML data were identified singularly and as part of a species set. To avoid double counting these species, we created a new variable with cleaned, mutually exclusive species names (termed ‘grouped name’). In ‘grouped name’, we combined singular species names with their associated species sets (Online-only Table 1). For example, we reclassified occurrences identified as Halictus ligatus/poeyi, Halictus ligatus, or Halictus poeyi to Halictus ligatus/poeyi to avoid inflating future species richness estimates when occurrences might be the same species. In the final occurrence datasets, we included the cleaned, singular names (‘name’) and cleaned, grouped names (‘grouped_name’), so future analysts can select the appropriate taxonomic aggregation for their research objectives. Voucher specimens for most species in the BIML dataset are housed in the Smithsonian collection, but some are not yet permanently archived. We suggest interested parties contact Sam Droege (current email: sdroege@usgs.gov) to access voucher specimens. We also included, to the best of our knowledge, current affiliations for individuals who identified BIML specimens (Supplementary Information, Table S1), and standardized names of identifiers (‘identifiedBy’) in the final datasets.

Sampling method and effort

To describe sampling method and effort, we used regular expressions to extract these data from field notes. We sought to compare bee communities sampled with a standard methodology, so we discarded bee occurrences collected with vane traps or nets, only retaining occurrences sampled with pan traps (i.e., bee bowls). Using the stringr package in R24,25, we searched the text of field notes to document trap volume, trap color, total number of traps, and the number of traps missing or disturbed. The most common BIML pan-trapping method involved setting out traps of multiple colors and combining the bees in all traps into one sample. Consequently, BIML recorded trap color in field notes as the number of traps of each color used for a specific sampling event. We designed regular expressions to extract the number of traps for the eight most common colors (white, blue, yellow, pale blue, fluorescent yellow, fluorescent blue, and florescent pale blue). For some occurrences, our regular expressions yielded no sampling information, so we manually reviewed these field notes and recorded any data missed by the automated search.

Next, we simplified the trap color and volume classification to facilitate future statistical analyses. To reduce the number of trap volume categories, we rounded trap volume to the nearest 0.5 ounces, and removed trap volumes greater than 40 ounces, assuming these were errors in data entry or extraction. When the trap color or volume used at a specific site changed within a year, we manually reviewed the field notes and corrected color or volume classifications when necessary. After correcting these discrepancies, we found the BIML very rarely changed sampling methods within a year, so we filled in most missing trap color or volume information by assuming a constant sampling method for all transects within a site-year. Finally, we combined rarely used color/volumes (fewer than 1% of transects) into an ‘Other’ category. In the archived datasets with sampling information, we included original and simplified variables for trap color and volume.

Lastly, we summarized sampling effort and calculated effort-adjusted abundance of wild bees. We calculated the total number of traps for each sampling event, and, when available, we also described the number of traps missing or disturbed. If there was no documentation of missing or disturbed traps, we assumed all traps were recovered successfully. When the total number of traps differed between the field notes and ‘number of traps’ column, we selected the lower value. We defined the final number of traps in each transect as the original number minus the number missing or disturbed. We calculated the duration of sampling as the difference between the date traps were collected and date traps were set. If traps were set and collected on the same day, we set the duration of sampling to one day. For each occurrence in the BIML dataset, we converted bee abundance to abundance day−1 trap−1. We conducted all data manipulation and aggregation with the R statistical and computing language 3.6.025,26

Data Records

We produced two primary datasets and a third analytical dataset22 (details below), which are all archived at figshare.com. The first dataset (‘Mid-Atlantic USA wild bee occurrences, all records’) contains all 99,053 wild bee occurrences collected in pan traps by BIML from 2002 to 2016 in Maryland, Delaware, and Washington DC, USA. We describe all variables included in dataset one in Table 1. The second dataset (‘Mid-Atlantic USA wild bee occurrences, records with sampling info’) is all pan-trapped occurrences with sampling effort information. We retained 83,583 wild bee occurrences in dataset two representing 300 species from 1225 sites sampled over 1322 site-years. Dataset two documents the trap color and volume when these data were available. See Online-only Table 2 for full meta-data for dataset two.

Table 1.

Description of all fields in dataset 1, all wild bee specimens in Maryland, Delaware, and Washington DC. Variables marked as ‘Original’ are unmodified from Droege and Sellers18.

Field Name Unit Description
Identifiers
  identifier Original, specimen ID
  id Original, specimen URL
  TransectID transect ID
  SamplEvent sampling event ID
  SiteID site ID
  SiteID_Year site ID and year of bee sampling
  year year of bee sampling
Taxonomy
  name taxonomic classification
  Genus taxonomic classification
  species taxonomic classification
  grouped_name grouped taxonomic classification
  orig_name Original, taxonomic classification
sex Original, specimen sex
  identifiedBy Individual who determined specimen identity
Locality and Date
  latitude decimal degrees Original
  longitude decimal degrees Original
  coordinateUncertaintyInMeters meters Original
  time1 Original, start date and time
  time2 Original, end date and time
  startdate month/day/year sampling start date
  enddate month/day/year sampling end date
  country Original
  countryCode Original
  state Original
  county Original
  municipality Original
Field notes
  habitat Original, habitat in location of sampling
  field_note Original
  note Original
  modif_fieldnote modified field note used for automated string search
  modif_note modified note used for automated string search
Sampling method and effort
  SampleType type of sampling method
  TrapLiquid Original, liquid used in traps
  TrapColor Original, color of trap
  TrapVolume Original, volume of trap
  Ntraps Original, number of traps
Wild bee abundance
  Abundance wild bee abundance
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Online-only Table 2.

Description of all fields in archived dataset 2, wild bee specimens in Maryland, Delaware, and Washington DC with recorded sampling effort.

Field Name Unit Description
Identifiers
  identifier Original, specimen ID
  id Original, specimen URL
  TransectID transect ID
  SamplEvent sampling event ID
  SiteID site ID
  SiteID_Year site ID and year of bee sampling
  year year of bee sampling
Taxonomy
  name taxonomic classification
  Genus taxonomic classification
  species taxonomic classification
  grouped_name grouped taxonomic classification
  orig_name Original, taxonomic classification
  sex Original
  identifiedBy Individual who determined specimen identity
Locality and Date
  latitude decimal degrees Original
  longitude decimal degrees Original
  coordinateUncertaintyInMeters meters Original
  time1 Original, start date and time
  time2 Original, end date and time
  startdate month/day/year sampling start date
  enddate month/day/year sampling end date
  trapdays days length of sampling period
  country Original
  countryCode Original
  state Original
  county Original
  municipality Original
Field notes
  habitat Original, habitat in location of sampling
  field_note Original
  note Original
  modif_fieldnote modified field note used for automated string search
  modif_note modified note used for automated string search
Sampling method and effort
  SampleType type of sampling method
  TrapLiquid Original, liquid used in traps
   TrapColor Original, color of trap
  TrapVolume Original, volume of trap
  Ntraps Original, number of traps
  nwhite number of white pan traps
  nblue number of blue pan traps
  nyellow number of yellow pan traps
  nFLblue number of fluorescent blue pan traps
  nFLyellow number of fluorescent yellow pan traps
  nFLwhite number of fluorescent white pan traps
  isblue T/F sampling method = blue pan traps?
  isyellow T/F sampling method = yellow pan traps?
  iswhite T/F sampling method = white pan traps?
  isFLblue T/F sampling method = fluorescent blue pan traps?
  isFLyellow T/F sampling method = fluorescent yellow pan traps?
  isFLwhite T/F sampling method = fluorescent white pan traps?
  ispaleblue T/F sampling method = pale blue pan traps?
  isFLpaleblue T/F sampling method = fluorescent pale blue pan traps?
  TrapVolumeParsed trap volume (from regex string search)
  TrapVolumeFinal trap volume (combined original and regex)*
  Nparse number of traps set (from regex string search)
  Nmissing number of traps missing (from regex string search)
  NTrapsFinal number of successful traps (set-missing)*
Wild bee abundance
  Abundance specimens wild bee abundance
  AbundDay specimens day−1 wild bee abundance day-1
  AbundTrap specimens trap−1 wild bee abundance trap-1
  AbundDayTrap specimens day−1 trap−1 wild bee abundance day-1 trap-1*
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Variables marked as ‘Original’ are unmodified from Droege and Sellers18. *Variable recommended for analysis (within set of similar variables).

We also generated an analytical dataset22 (‘Mid-Atlantic USA wild bee abundance per transect, records with sampling info’) derived from dataset two. Dataset three documents wild-bee abundance, trapping method, and sampling effort per transect (see ‘Identifier Variables’ methods above). At the transect level, we defined trap color and volume as the combination of all trap colors and volumes associated with specimens captured in a transect. Table 2 describes all meta-data for dataset three.

Table 2.

Description of all fields in archived dataset 3, wild bee abundance per transect.

Field Name Unit Description
Identifiers
  TransectID transect ID
  SamplEvent sampling event ID
  SiteID_Year site ID and year of bee sampling
Apis mellifera abundance
  apis_abund Apis mellifera abundance
  prop_apis Apis mellifera proportional abundance
Sampling method and effort
  TstVolume trap volumes used in this transect
  TstColor trap colors used in this transect
  ColorVolume color and volume of traps in transect
  VolumeSimple simplified classification of ‘TstVolume'
  ColorSimple simplified classification of ‘TstColor'
  trapdays days length of sampling period
  NTrapsFinal number of successful traps (set-missing)
Wild bee abundance
  Abundance specimens wild bee abundance
  AbundDayTrap specimens day−1 trap−1 wild bee abundance day−1 trap−1
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Technical Validation

We verified our sampling method and effort data in two ways. First, as described above (see ‘Sampling method and effort’), we manually reviewed field notes for all occurrences lacking sampling effort information. This allowed us to correct instances where sampling data were missed by our automated processing. Second, for occurrences that had sampling effort information, we quantified the accuracy of our processing procedure. We selected a random sample of 1000 occurrences and compared field-note text and sampling-method variables from the original dataset with our sampling effort and method data. We noted whether trap color, trap volume, and the total number of traps were assigned correctly and quantified how much information we created compared with the original BIML dataset.

Overall, we were able to generate or verify pan-trap sampling effort and methodology for 84% of BIML specimens in the Mid-Atlantic U.S. We improved data coverage for trap color, trap volume, and sampling effort by 71%, 4.7%, and 6.1%, respectively. The percentage of occurrences with present, accurate sampling data was good to excellent for all three variables (trap color: 82.2%, trap volume: 88.6%, sampling effort: 95.9%,). Specifically, 888 observations in our validation set were missing trap color data. Using our automated text search, we accurately described trap color for 714 occurrences. Of the remaining 174 occurrences, we generated partial or incorrect data for 27 and 2 occurrences, respectively, and 145 had no color data in the text field notes. For trap volume and sampling effort (the total number of traps used in each sampling event), the original BIML dataset was much more complete. Out of 1000 specimens in our validation dataset, sampling effort and trap volume were missing for 50 and 161 occurrences, respectively. We generated accurate sampling effort for 41 occurrences and corrected BIML data for an additional 20. Of the 161 occurrences lacking trap volume, we filled in 47.

Usage Notes

The BIML data is a rich source of information on wild-bee biodiversity but it has some notable limitations. First, the BIML sampled few locations more than three years. The main goal of BIML collections was to establish baseline estimates of wild-bee species richness in the Mid-Atlantic region. They selected sites representing a wide variety of habitats, focusing on sampling many sites rather than repeated sampling at the same sites over time. Consequently, the BIML dataset has excellent geographic coverage in Maryland, Delaware, and Washington DC (Fig. 1), but lacks long time-series of bee abundance or community composition in consistent locations. Similarly, the BIML did not sample an equal number of sites for all habitat types represented in the dataset. For example, there are relatively few sites in highly agricultural landscapes compared with forested areas, so an analysis of the whole dataset may fail to reveal processes specific to agricultural land. For analyses focused on specific habitat types, we recommend sub-sampling or otherwise adjusting for uneven representation among habitat types.

Second, the dominant sampling method changed over the study period. We found that the BIML utilized different colors and volumes of pan traps over time (Figs. 2 and 3). Before 2003, the BIML used a variety of pan-trap colors and volumes. From 2003–2013, the most common sampling method was 3.25 ounce white, blue, and yellow pans, and in 2014, the BIML transitioned almost all their sampling to 12-ounce white, fluorescent blue, and fluorescent yellow bowls.

Fig. 2.

Fig. 2

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Color of wild bee traps used by USGS BIML from 2002–2016.

Fig. 3.

Fig. 3

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Volume of wild bee traps used by USGS BIML from 2002–2016.

These features limit, or at best complicate, interpretation of temporal patterns of bee abundance or community composition in the BIML data. For example, a pattern of declining bee abundance over time could be explained by a less effective sampling method or sampling poorer sites or less attractive habitats in later years. In our view, the BIML data are not well suited for assessing temporal trends, as researchers must account for sampling and location changes over time or use a small subset of the data sampled with consistent methodology.

The BIML data we archive here were sampled with pan traps, which impose some inherent biases and limitations. Pan traps significantly under sample large-bodied bees15,27, probably because larger-bodied individuals are able to break surface tension in a container of liquid and fly away. Consequently, Bombus sp., Xylocopa virginica, and other large-bodied bees are less common in pan-trapped data than net-collected or observational datasets. Additionally, some evidence suggests pan traps perform poorly in areas with highly abundant flowering plants28–30, such as field edges adjacent to mass-flowering crops. In proximity to flowering plants, pan traps are less attractive to wild bees than real flowers, leading to an artificially depauperate wild-bee community captured by the pan traps.

Consequently, the BIML datasets we produced are not well suited for studies on large-bodied taxa or in areas with highly abundant flower resources, however these limitations could likely be addressed by combining this dataset with net collections or direct observations. Net collecting has its own limitations of more active time spent per specimen and observer biases, but there are few limitations in common between the two methods. In addition to pan-trapped specimens, the BIML net-collected approximately 16,000 specimens from 2002–2016 in Maryland, Delaware, and Washington DC18, but these collections did not necessarily occur at pan-trapping sites. Also, we did not include net-collected occurrences in our data processing pipeline, so species names should be verified before analysis, and sampling effort information may not exist.

We also advise future analysts that some BIML sampling locations are very close to each other. We created ‘site’ designations as all unique combinations of latitude and longitude, no matter the distance from other sites. In the format we provide, the BIML data violates the assumption of independent observations imposed by a frequentist statistical framework. Not all analytical frameworks assume independent observations, so we did not combine or thin sites, but refer interested parties to statistical methods or software designed for this task (k-means clustering or similar, spThin31 for spatial thinning).

Supplementary information

Supplementary Information (80.6KB, pdf)

Acknowledgements

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.

Online-only Tables

Author contributions

M.K., J.F.T. and C.M.G. originated concepts. M.K. accessed, cleaned, and processed data and prepared archival version of data and accompanying code. M.K., J.F.T. and C.M.G. wrote the manuscript.

Code availability

All R code used to generate the archived data is available at Zenodo26.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

is available for this paper at 10.1038/s41597-020-00577-0.

References

  • 1.Klein A-M, et al. Importance of pollinators in changing landscapes for world crops. Proc. R. Soc. B Biol. Sci. 2007;274:303–313. doi: 10.1098/rspb.2006.3721. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Ollerton J, Erenler H, Edwards M, Crockett R. Extinctions of aculeate pollinators in Britain and the role of large-scale agricultural changes. Science. 2014;346:1360–1362. doi: 10.1126/science.1257259. [DOI] [PubMed] [Google Scholar]
  • 3.Fontaine C, Dajoz I, Meriguet J, Loreau M. Functional diversity of plant–pollinator interaction webs enhances the persistence of plant communities. PLoS Biol. 2005;4:e1. doi: 10.1371/journal.pbio.0040001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Carvell, C. et al. Design and Testing of a National Pollinator and Pollination Monitoring Framework. Final summary report to the Department for Environment, Food and Rural Affairs (Defra), Scottish Government and Welsh Government: Project WC1101, https://www.ceh.ac.uk/our-science/projects/pollinator-monitoring (2016).
  • 5.Droege, S., Engler, J. D., Sellers, E. A. & O’Brien, L. National protocol framework for the inventory and monitoring of bees, https://pubs.er.usgs.gov/publication/70176107 (2016).
  • 6.Scherber C, Beduschi T, Tscharntke T. Novel approaches to sampling pollinators in whole landscapes: a lesson for landscape-wide biodiversity monitoring. Landsc. Ecol. 2019;34:1057–1067. doi: 10.1007/s10980-018-0757-2. [DOI] [Google Scholar]
  • 7.Lebuhn, G. et al. A standardized method for monitoring Bee Populations – The Bee Inventory (BI) Plot, http://online.sfsu.edu/beeplot/pdfs/Bee%20Plot%202003.pdf (2003).
  • 8.Cameron SA, et al. Patterns of widespread decline in North American bumble bees. Proc. Natl. Acad. Sci. 2011;108:662–667. doi: 10.1073/pnas.1014743108. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Odoux J-F, et al. ECOBEE: a tool for long-term honey bee colony monitoring at the landscape scale in West European intensive agroecosystems. J. Apic. Res. 2014;53:57–66. doi: 10.3896/IBRA.1.53.1.05. [DOI] [Google Scholar]
  • 10.Magurran AE, et al. Long-term datasets in biodiversity research and monitoring: assessing change in ecological communities through time. Trends Ecol. Evol. 2010;25:574–582. doi: 10.1016/j.tree.2010.06.016. [DOI] [PubMed] [Google Scholar]
  • 11.Theobald EJ, et al. Global change and local solutions: Tapping the unrealized potential of citizen science for biodiversity research. Biol. Conserv. 2015;181:236–244. doi: 10.1016/j.biocon.2014.10.021. [DOI] [Google Scholar]
  • 12.Chandler M, et al. Contribution of citizen science towards international biodiversity monitoring. Biol. Conserv. 2017;213:280–294. doi: 10.1016/j.biocon.2016.09.004. [DOI] [Google Scholar]
  • 13.Westphal C, et al. Measuring bee diversity in different European habitats and biogeographical regions. Ecol. Monogr. 2008;78:653–671. doi: 10.1890/07-1292.1. [DOI] [Google Scholar]
  • 14.Nielsen A, et al. Assessing bee species richness in two Mediterranean communities: importance of habitat type and sampling techniques. Ecol. Res. 2011;26:969–983. doi: 10.1007/s11284-011-0852-1. [DOI] [Google Scholar]
  • 15.Joshi NK, et al. Comparative Trapping Efficiency to Characterize Bee Abundance, Diversity, and Community Composition in Apple Orchards. Ann. Entomol. Soc. Am. 2015;108:785–799. doi: 10.1093/aesa/sav057. [DOI] [Google Scholar]
  • 16.Leong JM, Thorp R. The pan trap colour preferences of oligolectic and nonoligolectic bees associated with a vernal pool plant. Ecol. Entomol. 1999;24:329–335. doi: 10.1046/j.1365-2311.1999.00196.x. [DOI] [Google Scholar]
  • 17.Tuell JK, Isaacs R. Elevated pan traps to monitor bees in flowering crop canopies. Entomol. Exp. Appl. 2009;131:93–98. doi: 10.1111/j.1570-7458.2009.00826.x. [DOI] [Google Scholar]
  • 18.Droege, S. & Sellers, E. USGS PWRC - Native Bee Inventory and Monitoring Lab (BIML). Version 1.5. United States Geological Survey. Occurrence Dataset, 10.15468/6autvb (2017).
  • 19.Minckley, R. L., Roulston, T. H. & Williams, N. M. Resource assurance predicts specialist and generalist bee activity in drought. Proc. R. Soc. B Biol. Sci. 280 (2013). [DOI] [PMC free article] [PubMed]
  • 20.Stone GN, et al. Windows of opportunity and the temporal structuring of foraging activity in a desert solitary bee. Ecol. Entomol. 1999;24:208–221. doi: 10.1046/j.1365-2311.1999.00181.x. [DOI] [Google Scholar]
  • 21.Dyer JM. Revisiting the Deciduous Forests of Eastern North America. BioScience. 2006;56:341. doi: 10.1641/0006-3568(2006)56[341:RTDFOE]2.0.CO;2. [DOI] [Google Scholar]
  • 22.Kammerer M, Tooker JF, Grozinger CM. 2020. A long-term dataset on wild bee abundance in Mid-Atlantic United States. figshare. [DOI] [PMC free article] [PubMed]
  • 23.Ascher, J. S. & Pickering, J. Discover Life bee species guide and world checklist (Hymenoptera:Apoidea:Anthophila), http://www.discoverlife.org/mp/20q?guide=Apoidea_species (2013).
  • 24.Wickham, H. stringr: Consistent, Wrappers for Common String Operations. (2018).
  • 25.R Core Team. R: A Language and Environment for Statistical Computing. (2019).
  • 26.Kammerer, M. melaniekamm/CleanParseDroegeBees: Source code for: A long-term dataset on wild bee abundance in Mid-Atlantic United States. Zenodo, 10.5281/zenodo.3528323 (2020). [DOI] [PMC free article] [PubMed]
  • 27.Roulston TH, Smith SA, Brewster AL. A Comparison of Pan Trap and Intensive Net Sampling Techniques for Documenting a Bee (Hymenoptera: Apiformes) Fauna. J. Kans. Entomol. Soc. 2007;80:179–181. doi: 10.2317/0022-8567(2007)80[179:ACOPTA]2.0.CO;2. [DOI] [Google Scholar]
  • 28.Baum KA, Wallen KE. Potential Bias in Pan Trapping as a Function of Floral Abundance. J. Kans. Entomol. Soc. 2011;84:155–159. doi: 10.2317/JKES100629.1. [DOI] [Google Scholar]
  • 29.Rhoades P, et al. Sampling technique affects detection of habitat factors influencing wild bee communities. J. Insect Conserv. 2017;21:703–714. doi: 10.1007/s10841-017-0013-0. [DOI] [Google Scholar]
  • 30.Popic TJ, Davila YC, Wardle GM. Evaluation of Common Methods for Sampling Invertebrate Pollinator Assemblages: Net Sampling Out-Perform Pan Traps. PLoS ONE. 2013;8:e66665. doi: 10.1371/journal.pone.0066665. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Aiello-Lammens, M. E., Boria, R. A., Radosavljevic, A., Vilela, B. & Anderson, R. P. spThin: Functions for Spatial Thinning of Species Occurrence Records for Use in Ecological Models. (2019).

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Citations

  1. Kammerer M, Tooker JF, Grozinger CM. 2020. A long-term dataset on wild bee abundance in Mid-Atlantic United States. figshare. [DOI] [PMC free article] [PubMed]

Supplementary Materials

Supplementary Information (80.6KB, pdf)

Data Availability Statement

All R code used to generate the archived data is available at Zenodo26.

Articles from Scientific Data are provided here courtesy of Nature Publishing Group

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