EARLY HEARING DETECTION AND INTERVENTION VIRTUAL CONFERENCE
MARCH 2-5, 2021

(Virtually the same conference, without elevators, airplane tickets, or hotel room keys)

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5/23/2019  |   9:30 AM - 9:45 AM   |  THE POWER, POTENTIAL, AND PITFALLS OF OPPORTUNISTIC DATA FOR VULNERABILITY ASSESSMENTS: LESSONS FROM THE FISHES   |  150 G

THE POWER, POTENTIAL, AND PITFALLS OF OPPORTUNISTIC DATA FOR VULNERABILITY ASSESSMENTS: LESSONS FROM THE FISHES

The rate, pace, and magnitude of environmental change demands efficient vulnerability assessments of many taxa, including freshwater species that make up one of the most threatened taxa globally. Opportunistically collected, publicly available occurrence data - e.g., museum records, state and federal databases, and observation-based public initiatives - provide a promising but largely untested resource in systematically evaluating the vulnerability of traditionally data-poor freshwater species to a changing climate. We present findings from ongoing efforts using data from the Global Biodiversity Information Facility (GBIF) to evaluate vulnerability of >100 freshwater fishes native to the US. By focusing on area of occupancy and climate niche breadth, our results indicate that opportunistically collected point-occurrence data have the potential to complement vulnerability assessments derived from coarse-grain (e.g., range map) data, particularly for data-poor species. We explore how issues such as uneven sampling efforts manifest in opportunistic datasets, and we provide evaluation and screening strategies essential for use of these data in formal decision-support tools. Finally, we discuss incorporation of these data into web-based tools, such as the US Geological Survey National Biogeographic Map, enabling users to explore GBIF-derived vulnerability and risk assessments directly.

  • Fish
  • ClimateChange
  • Distribution

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Presenters/Authors

Meryl Mims (), Virginia Tech, mims@vt.edu;


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Meryl C. Mims (), Virginia Tech, mims@vt.edu;


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Samuel Silknetter (), Virginia Tech, silknets@vt.edu;


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Jennifer A. Smith (), University of Texas San Antonio, Jennifer.smith@utsa.edu;


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Abigail L. Benson (), USGS, albenson@usgs.gov ;


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