easyFulcrum: An R package to process and analyze ecological sampling data generated using the Fulcrum mobile application
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| izdano v: | PLoS One vol. 16, no. 10 (Oct 2021), p. e0254293 |
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| Glavni avtor: | |
| Drugi avtorji: | , , |
| Izdano: |
Public Library of Science
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| Teme: | |
| Online dostop: | Citation/Abstract Full Text Full Text - PDF |
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| 022 | |a 1932-6203 | ||
| 024 | 7 | |a 10.1371/journal.pone.0254293 |2 doi | |
| 035 | |a 2579572130 | ||
| 045 | 2 | |b d20211001 |b d20211031 | |
| 084 | |a 174835 |2 nlm | ||
| 100 | 1 | |a Matteo Di Bernardo | |
| 245 | 1 | |a easyFulcrum: An R package to process and analyze ecological sampling data generated using the Fulcrum mobile application | |
| 260 | |b Public Library of Science |c Oct 2021 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a 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. | |
| 610 | 4 | |a Northwestern University | |
| 651 | 4 | |a United States--US | |
| 653 | |a Data transfer (computers) | ||
| 653 | |a Nematodes | ||
| 653 | |a Applications programs | ||
| 653 | |a Electronic devices | ||
| 653 | |a Transcription | ||
| 653 | |a Mobile computing | ||
| 653 | |a Sampling | ||
| 653 | |a Organisms | ||
| 653 | |a Data collection platforms | ||
| 653 | |a Streamlines | ||
| 653 | |a Substrates | ||
| 653 | |a Exports | ||
| 653 | |a Photographs | ||
| 653 | |a Data collection | ||
| 653 | |a Spreadsheets | ||
| 653 | |a Laboratories | ||
| 653 | |a Natural environment | ||
| 653 | |a Data visualization | ||
| 653 | |a Environmental | ||
| 700 | 1 | |a Crombie, Timothy A | |
| 700 | 1 | |a Cook, Daniel E | |
| 700 | 1 | |a Andersen, Erik C | |
| 773 | 0 | |t PLoS One |g vol. 16, no. 10 (Oct 2021), p. e0254293 | |
| 786 | 0 | |d ProQuest |t Health & Medical Collection | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/2579572130/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/2579572130/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/2579572130/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |