easyFulcrum: An R package to process and analyze ecological sampling data generated using the Fulcrum mobile application.
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 substrat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2021-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0254293 |
| _version_ | 1818993006120796160 |
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| author | Matteo Di Bernardo Timothy A Crombie Daniel E Cook Erik C Andersen |
| author_facet | Matteo Di Bernardo Timothy A Crombie Daniel E Cook Erik C Andersen |
| author_sort | Matteo Di Bernardo |
| collection | DOAJ |
| description | 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 can be used with 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. |
| first_indexed | 2024-12-20T20:35:11Z |
| format | Article |
| id | doaj.art-faaef8759def4ca9849125d6ae552012 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-20T20:35:11Z |
| publishDate | 2021-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-faaef8759def4ca9849125d6ae5520122022-12-21T19:27:15ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-011610e025429310.1371/journal.pone.0254293easyFulcrum: An R package to process and analyze ecological sampling data generated using the Fulcrum mobile application.Matteo Di BernardoTimothy A CrombieDaniel E CookErik C AndersenLarge-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 can be used with 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.https://doi.org/10.1371/journal.pone.0254293 |
| spellingShingle | Matteo Di Bernardo Timothy A Crombie Daniel E Cook Erik C Andersen easyFulcrum: An R package to process and analyze ecological sampling data generated using the Fulcrum mobile application. PLoS ONE |
| title | easyFulcrum: An R package to process and analyze ecological sampling data generated using the Fulcrum mobile application. |
| title_full | easyFulcrum: An R package to process and analyze ecological sampling data generated using the Fulcrum mobile application. |
| title_fullStr | easyFulcrum: An R package to process and analyze ecological sampling data generated using the Fulcrum mobile application. |
| title_full_unstemmed | easyFulcrum: An R package to process and analyze ecological sampling data generated using the Fulcrum mobile application. |
| title_short | easyFulcrum: An R package to process and analyze ecological sampling data generated using the Fulcrum mobile application. |
| title_sort | easyfulcrum an r package to process and analyze ecological sampling data generated using the fulcrum mobile application |
| url | https://doi.org/10.1371/journal.pone.0254293 |
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