Developing a Centralized Digital Archive of Vouchered Animal Communication Signals

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Digitization TCN: Developing a Centralized Digital Archive of Vouchered Animal Communication Signals (VACS)

Animal Communication TCN
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Project Summary

An award is made to establish a thematic collection network that will digitize and make accessible media recordings associated with physical voucher specimens, broadly organized around the research theme of understanding the evolution and ecology of communication signals. Research on these questions has been challenged by the relative inaccessibility of the signal recordings and their associated physical specimens. This project will meet this challenge by partnering together multiple biological research collections and the Macaulay Library of Natural Sounds, the world's largest scientific archive of animal signal recordings. Collectively, these institutions will co-curate and make accessible digitized and vouchered recordings of the communication signals of birds, frogs, fish and insects, and will establish direct and transparent links across collections between physical voucher specimens and their digitized recordings. This project will make accessible digital audio recordings of animal signals that can be used to address a host of scientific questions, including the responses of animals to anthropogenic noise and other human activities. By providing a useful co-curation system and encouraging collection of recordings along with physical specimens, this project will have a transformative influence on the way that researchers collect and use biological specimens in the future, and will serve as a useful model for collections facing similar co-curation challenges.

This project will also provide materials for extensive educational outreach at all age levels, and will have significant conservation impacts because the digitized material will contribute directly to our ability to assess and monitor biodiversity. Finally, this project will expand biological collection methods and help train the "next generation" of museum curators, collectors, and researchers. This award is made as part of the National Resource for Digitization of Biological Collections through the Advancing Digitization of Biological Collections program and all data resulting from this award will be available through the national resource (iDigBio.org).

Current Research

Proposed research involves linking voucher collections with media records to understand the tempo and mode of animal signal evolution.

  • Understanding the response of organisms to anthropogenic noise and other perturbations.
  • Discovery of cryptic species.
  • Determining the extent to which vocal and other signals evolve in concert, mechanisms of sound production, role of morphology in signal evolution.
  • Influence of habitat and ecological selection pressures on animal signals.
  • Population variation both temporally and geographically.
  • Behavioral variation and sexual selection.
  • Seasonality and circadian dependencies.

Project Websites & Social Media

http://macaulaylibrary.org

Citizen Science & Outreach Projects

Project Leadership

Project Sponsor: Cornell University (NSF Award 1304425)

Principal Investigators (PIs): Michael Webster (PI), Gregory Budney (Co-PI), John Friel (Co-PI), Kimberly Bostwick (Co-PI), Edwin Scholes (Co-PI)

Collaboratoring Award PIs: Rafe Brown, University of Kansas; David Kavanaugh, California Academy of Sciences; Travis LaDuc, University of Texas at Austin; Daniel Lane, Louisiana State University & Agricultural and Mechanical College

Project Collaborators

Map of Collaborating Institutions

Macaulay Library, Cornell Lab of Ornithology
American Museum Natural History
California Academy of Sciences (NSF Award 1304901)
Louisiana State University & Agricultural and Mechanical College (NSF Award 1305052)
University of Kansas (NSF Award 1304585)
University of Texas - Austin (NSF Award 1304938)
Yale University, Peabody Museum

Protocols & Workflows

Publications

Professional Presentations

iDigBio Summit V, 2015

Other project documentation