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Published on: April 10, 2017
Developing a standardized list of entomological collection methods for use in databases.
Michael L Ferro1, Morgan Summerlin2
1Clemson University Arthropod Collection, Department of Plant and Environmental Sciences, Clemson University, Clemson, SC 29634-0310, USA Clemson University Clemson United States of America.
Standardizing entomological specimen collection methods is crucial for biodiversity research. A proposed framework categorizes methods to improve data sharing and understanding in natural history databases.
Area of Science:
- Biodiversity informatics
- Entomology
- Museum science
Background:
- Natural history specimen databasing primarily standardizes occurrence data (where and when).
- Understanding how species are encountered and collected is vital for comprehensive species data.
- Current terminology for entomological collection methods lacks standardization, hindering inter-researcher communication.
Purpose of the Study:
- To propose a broad-scale framework for categorizing entomological collection methods.
- To enhance communication among researchers, particularly within public biodiversity databases.
- To facilitate more detailed information gathering on species collection techniques.
Main Methods:
- Development of a hierarchical framework for collection methods.
- Categorization into three main groups: active human collecting, active specimen orientation, and passive specimen collection/concentration.
- Inclusion of specific sub-categories within the general categories.
Main Results:
- A proposed framework with three primary categories for entomological collection methods.
- The framework allows for increasingly specific sub-categories.
- A bibliography of relevant entomological collection and curation resources is provided.
Conclusions:
- A standardized framework for collection methods can improve data utility in natural history collections.
- This framework aids researchers in understanding and communicating diverse entomological collection techniques.
- The proposed system supports more robust biodiversity data analysis and sharing.
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