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| Main Authors: | , |
|---|---|
| Format: | Dataset Open Access |
| Language: | en |
| Published: |
PANGAEA
2019
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| Subjects: | |
| Online Access: | https://doi.org/10.1594/PANGAEA.896941 |
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| _version_ | 1867171860242759680 |
|---|---|
| author | Taillie, Paul Poulter, Benjamin |
| author_facet | Taillie, Paul Poulter, Benjamin |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | This project was originally designed and implemented by Ben Poulter in 2003/2004 to investigate vegetation composition across a gradient of saltwater exposure. The study was then replicated by Paul Taillie in 2016/2017 to investigate vegetation change. The files are grouped in an R project and thus are relatively linked. This means that you do not have to change your working directory to get scripts to run on your machine. Simply unzip the folder, open R, select file>open project>browse to the unzipped folder>click the Rproject file called "APPveg_data." Each script starts with a preamble that will clear your workspace and load the required packages. You may have to install packages first if they are not yet installed on your machine. Otherwise, the script should run from start to finish. Non-R users can still access the raw data easily, which is in .csv format. |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_896941 |
| institution | PANGAEA |
| language | en |
| publishDate | 2019 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | Eastern North Carolina coastal vegetation inventory Taillie, Paul Poulter, Benjamin Eastern_North_Carolina; MULT; Multiple investigations; North Carolina This project was originally designed and implemented by Ben Poulter in 2003/2004 to investigate vegetation composition across a gradient of saltwater exposure. The study was then replicated by Paul Taillie in 2016/2017 to investigate vegetation change. The files are grouped in an R project and thus are relatively linked. This means that you do not have to change your working directory to get scripts to run on your machine. Simply unzip the folder, open R, select file>open project>browse to the unzipped folder>click the Rproject file called "APPveg_data." Each script starts with a preamble that will clear your workspace and load the required packages. You may have to install packages first if they are not yet installed on your machine. Otherwise, the script should run from start to finish. Non-R users can still access the raw data easily, which is in .csv format. |
| title | Eastern North Carolina coastal vegetation inventory |
| topic | Eastern_North_Carolina; MULT; Multiple investigations; North Carolina |
| url | https://doi.org/10.1594/PANGAEA.896941 |