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Elicited qualitative value of information scores for eastern black rail uncertainties on the Atlantic Coast from a 2020 adaptive management workshop

Metadata Updated: July 6, 2024

The eastern black rail (Laterallus jamaicensis jamaicensis; hereafter rail) is a small, cryptic marshbird that was recently listed as threatened under the U.S. Endangered Species Act. We organized a rapid prototyping workshop to initiate development of an adaptive management for rails on the Atlantic Coast. The in-person workshop spanned 2.5 days and was held in Titusville, Florida in January 2020. Workshop participants, comprised of species experts and land managers of rail habitats, chose to focus the framework on testing habitat management techniques to maximize rail occupancy, in which uncertainties could be reduced through a combination of field management experiments and coordinated monitoring. We used the qualitative value of information to prioritize uncertainties (stated as alternative hypotheses developed by participants in habitat-based breakout groups) that could serve as the basis for experiments within the adaptive management framework. Qualitative value of information (QVoI) is a newly-developed decision analysis tool that scores uncertainties in three areas: (1) Magnitude of uncertainty which reflects the strength of theoretical foundation and empirical support of the hypothesized relationship; (2) Relevance to management decisions which indicates how likely the preferred management alternative is to change if the uncertainty were resolved; and (3) Reducibility which is the degree to which the uncertainty could be resolved through research and monitoring. Magnitude is scored on a scale of 0–4, whereas Relevance and Reducibility can vary from 0–3. These data are the anonymized workshop participant (n=26) scores for nine hypotheses focused on testing habitat management techniques, to determine which hypotheses should serve as the basis for management experiments in an adaptive management framework. The data are contained in a .csv file that can be opened using a spreadsheet program such as Microsoft Excel, or read into a statistical analysis program such as Program R.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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Dates

Metadata Created Date June 1, 2023
Metadata Updated Date July 6, 2024

Metadata Source

Harvested from DOI EDI

Additional Metadata

Resource Type Dataset
Metadata Created Date June 1, 2023
Metadata Updated Date July 6, 2024
Publisher U.S. Geological Survey
Maintainer
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Identifier USGS:6266dfa7d34e76103cce5905
Data Last Modified 20220517
Category geospatial
Public Access Level public
Bureau Code 010:12
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://datainventory.doi.gov/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id 39d800c9-54d5-4d83-8308-eb53baac94fc
Harvest Source Id 52bfcc16-6e15-478f-809a-b1bc76f1aeda
Harvest Source Title DOI EDI
Metadata Type geospatial
Old Spatial -82.3535,24.7668,-69.6973,43.1972
Publisher Hierarchy White House > U.S. Department of the Interior > U.S. Geological Survey
Source Datajson Identifier True
Source Hash 27e003ebae3fadfa7f9ae889f8b0f241d8cba7ee126ba33234fac0725139e94e
Source Schema Version 1.1
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