EARLY HEARING DETECTION AND INTERVENTION VIRTUAL CONFERENCE
MARCH 2-5, 2021
(Virtually the same conference, without elevators, airplane tickets, or hotel room keys)
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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