easyFulcrum: An R package to process and analyze ecological sampling data generated using the Fulcrum mobile application
Autor: | Matteo Di Bernardo, Timothy A. Crombie, Erik C. Andersen, Daniel E. Cook |
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Rok vydání: | 2021 |
Předmět: |
Atmospheric Science
Nematoda Computer science computer.software_genre Field (computer science) Environmental data Database and Informatics Methods Data Management Multidisciplinary Ecology Data Collection Sampling (statistics) Software Engineering Eukaryota Animal Models Mobile Applications Disparate system Experimental Organism Systems Caenorhabditis Elegans Computers Handheld Medicine Engineering and Technology Mobile device Sequence Analysis Research Article Genotyping Computer and Information Sciences Geospatial analysis Process (engineering) Bioinformatics Science Environment Research and Analysis Methods Specimen Handling Set (abstract data type) Computer Software Data visualization Meteorology Model Organisms Animals Molecular Biology Techniques Molecular Biology Metadata business.industry Data Visualization Organisms Biology and Life Sciences Humidity Invertebrates Earth Sciences Animal Studies Caenorhabditis business computer Sequence Alignment Zoology Software |
Zdroj: | PLoS ONE PLoS ONE, Vol 16, Iss 10, p e0254293 (2021) |
ISSN: | 1932-6203 |
Popis: | Large-scale ecological sampling can be difficult and costly, especially for organisms that are too small to be easily identified in a natural environment by eye. Typically, these microscopic floral and fauna are sampled by collecting substrates from nature and then separating organisms from substrates in the laboratory. In many cases, diverse organisms can be identified to the species-level using molecular barcodes. To facilitate large-scale ecological sampling of microscopic organisms, we used a geographic data-collection platform for mobile devices called Fulcrum that streamlines the organization of geospatial sampling data, substrate photographs, and environmental data at natural sampling sites. These sampling data are then linked to organism isolation data from the laboratory. Here, we describe the easyFulcrum R package, which can be used to clean, process, and visualize ecological field sampling and isolation data exported from the Fulcrum mobile application. We developed this package for wild nematode sampling, but it is extensible to other organisms. The advantages of using Fulcrum combined with easyFulcrum are (1) the elimination of transcription errors by replacing manual data entry and/or spreadsheets with a mobile application, (2) the ability to clean, process, and visualize sampling data using a standardized set of functions in the R software environment, and (3) the ability to join disparate data to each other, including environmental data from the field and the molecularly defined identities of individual specimens isolated from samples. |
Databáze: | OpenAIRE |
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