TCN: iDigBees Network, Towards Complete Digitization of US Bee Collections to Promote Ecological and Evolutionary Research in a Keystone Clade: Difference between revisions
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Using protocols developed through SCAN, LepNet, and TPT TCNs, just making some workflows more efficient in general or more appropriate for bees. | Using protocols developed through SCAN, LepNet, and TPT TCNs, just making some workflows more efficient in general or more appropriate for bees. | ||
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Revision as of 13:18, 14 July 2023
iDigBees Network, Towards Complete Digitization of US Bee Collections to Promote Ecological and Evolutionary Research in a Keystone Clade
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Project Summary
Bees are the most important pollinators in both managed and natural landscapes, and concerns are quickly growing about declines in bee diversity and numbers. Only a fraction of the ca. 4,000 known bee species in the United States have adequate data for assessing their presence or absence in an ecosystem. The iDigBees Thematic Collections Network addresses this problem by transcribing specimen label information for thousands of bee specimens in US insect collections into a shared global database. As a result, bees will become the first major insect group to have specimen data sufficiently digitized to promote research projects and support conservation efforts. Specifically, the iDigBees project will (1) map distributions for thousands of bee species and quantify patterns of bee biodiversity; (2) identify data gaps to inform future inventory and monitoring efforts; (3) reveal changes in species distributions over time through historic records; (4) document the impacts of a changing climate on bees; (5) identify critical taxa and geographic areas for conservation; and (6) establish a network of researchers, conservationists, and land managers to rapidly utilize data for research, education, public policy, and land management. The education program will coordinate an array of existing programs and create a new technology-mediated learning tool, SMARTBees, to serve high school and college students. Obtaining specimen-level data on US bee species and communities, and integrating findings into education programs, are essential steps toward addressing the pollinator crisis.
iDigBees represents an in-depth insect biodiversity digitization initiative that will mobilize at least 350,000 bee specimen records, and 6,600 high-resolution image suites. Obtaining specimen-level data on US bee species and communities is an essential step toward addressing the pollinator crisis. Via the novel networks proposed here, species distribution patterns and “extended specimen” data will emerge, leading to testable hypotheses as to underlying mechanisms and predictions on how bees will respond to future global changes. Integrated data will also shed light on how particular life-history traits life-history traits respond to environmental change. iDigBees will help to highlight candidate pollinator restoration options for agricultural, urban, and other managed landscapes. This project, in partnership with researchers and government agencies, will provide open-source datasets for policy, research, and education. The iDigBees model will be promoted throughout North America and other continents to foster "deep global digitization”. The iDigBees network integrates educational and public engagement initiatives to work with the Biodiversity Literacy in Undergraduate Education (BLUE) RCN to build and implement novel biodiversity data-centric Open Education Resources that promote student-oriented learning. SMARTBees will serve as a digital platform featuring learning modules designed to serve culturally diverse high school students who are transitioning into community college as well as first year undergraduates. Building on the extended specimen model exemplary digital bee specimens will teach students host plant relationships, key evolutionary concepts and the important role pollinators have in sustaining the biodiversity of our planet.
Current Research
Project Websites & Social Media
Citizen Science & Outreach Projects
Project Leadership
Project sponsor: Biodiversity Outreach Network (NSF Award #2216927)
Principal Investigators (PIs): Neil Cobb (PI) , Melody Basham (Co-PI), Erika Tucker (Co-PI)
Project Collaborators
Digitizing Institutions:
Brigham Young University
- Shawn Clark (PI) (NSF Award #2216943)
- Michael Whiting (co-PI)
Colorado State University
- Crystal Cooke (PI) (NSF Award #2216945)
Mississippi State University
- JoVonn Hill (PI) (NSF Award #2216930)
New Mexico State University
- Scott Bundy (PI) (NSF Award #2216953)
North Carolina State Universityy
- Rebecca Irwin (PI) (NSF Award #2216946)
- Elsa Youngsteadt (co-PI)
Southeast Missouri State University
- Timothy Judd (PI) (NSF Award #2216949)
The American Museum of Natural History
- Christine Johnson (PI) (NSF Award #2216947)
University of Connecticut
- Katrina Menard (PI) (NSF Award #2217280)
University of Kentucky
- Julian Dupuis (PI) (NSF Award #2216955)
University of Nebraska
- Matthew Paulsen (PI) (NSF Award #2216936)
- Susan Weller (co-PI)
University of Wyoming
- Michael Dillon (PI) (NSF Award #2216932)
Washington State University
- Elizabeth Murray (PI) (NSF Award #2216934)
Protocols & Workflows
Using protocols developed through SCAN, LepNet, and TPT TCNs, just making some workflows more efficient in general or more appropriate for bees.
Publications
- (2023) James B. Dorey, Paige R. Chesshire, Angela N. Bolaños, Robert L. O’Reilly, Silas Bossert, Shannon M. Collins, Elinor M. Lichtenberg, Erika M. Tucker, Allan Smith-Pardo, Armando Falcon-Brindis, Diego A. Guevara, Bruno Ribeiro, Diego de Pedro, Erica E. Fischer, John Pickering, Keng-Lou James Hung, Katherine A. Parys, Lindsie M. McCabe, Matthew S. Rogan, Robert L. Minckley, Santiago J.E. Velazco, Terry Griswold, Tracy A. Zarrillo, Walter Jetz, Yanina V. Sica, Michael C. Orr, Laura Melissa Guzman, John A. Ascher, Alice C. Hughes, Neil S. Cobb. A globally synthesised and flagged bee occurrence dataset and cleaning workflow. Scientific Data: SUBMITTED. doi.
- (2023) Paige R. Chesshire, Erica E. Fischer, Nicolas J. Dowdy, Terry L. Griswold, Alice C. Hughes, Michael C. Orr, John S. Ascher, Laura M. Guzman, Keng-Lou James Hung, Neil S. Cobb, Lindsie M. McCabe. Completeness analysis for over 3000 United States bee species identifies persistent data gaps. Ecography. doi https://doi.org/10.1111/ecog.06584.
- (2023) Kelsey K. Graham, Paul Glaum, Joseph Hartert, Jason Gibbs, Erika Tucker, Rufus Isaacs, Fernanda S. Valdovinos. A century of sampling at an ecological preserve reveals declining diversity of wild bees. bioRxiv: PREPRINT. doi: 10.1101/2023.01.15.524123..