Help for package Rveg

Title:

Digitization of Phytosociological Relevés

Version:

0.1.8

Description:

Simple and fast tool for transforming phytosociological vegetation data into digital form for the following analysis. Danihelka, Chrtek, and Kaplan (2012, ISSN:00327786). Hennekens, and Schaminée (2001) <doi:10.2307/3237010>. Tichý (2002) <doi:10.1111/j.1654-1103.2002.tb02069.x>. Wickham, François, Henry, Müller (2022) https://CRAN.R-project.org/package=dplyr.

URL:

https://plant-ecology-lab-czu.com/rveg/

License:

GPL (≥ 3)

Encoding:

UTF-8

RoxygenNote:

7.3.3

Imports:

utils, xml2

Suggests:

knitr, rmarkdown

VignetteBuilder:

knitr

NeedsCompilation:

Packaged:

2026-03-01 10:10:33 UTC; premek

Author:

Přemysl Král

[aut, cre], Jan Douda

[aut]

Maintainer:

Přemysl Král <kralp@fzp.czu.cz>

Repository:

CRAN

Date/Publication:

2026-03-01 10:30:10 UTC

Rveg: Digitization of Phytosociological Relevés

Description

Simple and fast tool for transforming phytosociological vegetation data into digital form for the following analysis. For detailed guide run vignette("Rveg","Rveg") or check the quick start guide on https://github.com/sesitcsl2/Rveg

Author(s)

Maintainer: Přemysl Král kralp@fzp.czu.cz (ORCID)

Authors:

Jan Douda douda@fzp.czu.cz (ORCID)

References

Danihelka, Chrtek, and Kaplan (2012, ISSN:00327786), "Checklist of vascular plants of the czech republic. Preslia".

Hennekens, and Schaminée (2001) doi:10.2307/3237010, "TURBOVEG, a comprehensive data base management system for vegetation data. Journal of Vegetation Science".

Tichý (2002) doi:10.1111/j.1654-1103.2002.tb02069.x, "JUICE, software for vegetation classification. Journal of Vegetation Science".

Wickham, François, Henry, Müller (2022) https://CRAN.R-project.org/package=dplyr, "dplyr: A Grammar of Data Manipulation".

Višňák (1986, ISSN:00327786) https://www.preslia.cz/archive/Preslia_58_1986_353-368.pdf, "Příspěvek k poznání antropogenní vegetace v severních Čechách, zvláště v městě Liberci. Preslia".

Kaplan, Danihelka, Chrtek, Kirschner, Kubát, Štech, and Štěpánek (eds) (2019, ISBN:9788020026606) https://botanospol.cz/cs/node/2681, "Key to the flora of the Czech Republic, Ed. 2., Academia, Praha".

CreateChecklist: Create a custom checklist for Rveg

Description

Generates a custom species checklist formatted for use within the Rveg package. This function takes a list of full botanical names and deterministically converts them into unique, 7-character ShortName codes.

Rveg includes the following built-in checklists:

cz_dh2012 (Default: Checklist of vascular plants of the Czech Republic)
Czechia_slovakia_2015 (Turboveg compatible checklist)
cz_kaplan2019 (Rveg generated - Kaplan et al. 2019)
wcvp_que (example WCVP subset for Quebec)
wcvp_por (example WCVP subset for Portugal)

Usage

CreateChecklist(specieslist, export = "export")

Arguments

specieslist

Character vector OR Character. Either a vector of full botanical names in your R environment, or a path to a .txt file containing a single column named "FullName".

export

Character. The output path and name for the exported checklist. Defaults to a temporary directory.

Details

ShortName Generation Rules: The function guarantees a unique 7-character code for every species. The first 4 characters always represent a unique Genus code. The remaining 3 characters depend on the taxonomic rank:

Standard Species: Genus (4) + first 3 letters of the specific epithet (e.g., GENUEPI).
Species (sp.): Genus (4) + -SP (e.g., GENU-SP).
Hybrids (x): Genus (4) + * + first 2 letters of hybrid epithet (e.g., GENU*HY).
Aggregates (agg.): Genus (4) + ⁠#⁠ + first 2 letters of main epithet (e.g., GENU#EP).
Subspecies (ssp.): Genus (4) + first letter of main epithet + - + first letter of infra epithet (e.g., GENUE-I).
Varieties/Forms (var./f.): Genus (4) + first letter of main epithet + ⁠;⁠ + first letter of infra epithet (e.g., ⁠GENUE;I⁠).
Sections (sect.): Genus (4) + SE + first letter of section epithet (e.g., GENUSEE).

Note: If a 7-character code clash occurs, the 7th character is automatically adjusted using trailing letters or alphanumeric fallbacks to ensure absolute uniqueness.

Value

Writes a .txt file containing two columns (ShortName and FullName) to the location specified by export. The output can be then used inside addReleve and other functions.

Examples

  # Example 1: Creating a checklist from a local txt file
  CreateChecklist(
    specieslist = paste0(path.package("Rveg"), "/extdata/SpeciesList"),
  )

RvegCheck: Inspect, Validate, Edit and Repair an Rveg Database

Description

A diagnostic and managing utility to verify the health and integrity of an Rveg database. RvegCheck() reads your database, checks for missing or corrupted data, and outputs a summary of the database's current state.

Usage

RvegCheck(database, export = "export", checklist = "default")

Arguments

database

Character. The path and name of the existing Rveg database to inspect (e.g., "path/to/my_db").

export

Character. The output path and name where the modified database will be saved. Defaults to a temporary directory.

checklist

Character. The species checklist to validate the database against. By default, it uses the checklist defined in the database's metadata.

Details

Note: This function is currently under active development. #' At present, the function serves primarily as a diagnostic and metadata-repair tool. When run, it checks the database for a project_name and project_description. If these are missing, it will interactively prompt the user to supply them. It also prints vital database statistics, including the internal ID, creation date, last modification date, and any custom species added to the checklist.

In future updates, this function will also allow users to modify core database parameters, such as swapping the underlying species checklist or altering the header schema.

Value

Currently prints diagnostic information directly to the R console. If modifications are made, it exports the updated database files (⁠*HEAD.csv⁠ and ⁠*REL.csv⁠) to the path specified by export.

Examples

if (interactive()) {
  # Inspect the built-in example database
  RvegCheck(
    database = file.path(path.package("Rveg"), "extdata/ExampleDB", "example_1")
  )
}

RvegCombine: Merge Species or Vegetation Layers in an Rveg Database

Description

An interactive utility that allows users to merge the abundance covers of specific species or entire vegetation layers within an existing Rveg database.

Usage

RvegCombine(database, export = "export", checklist = "default")

Arguments

database

Character. The path and name of the existing Rveg database to be modified (e.g., "path/to/my_db").

export

Character. The output path and name where the modified database files (⁠*HEAD.csv⁠ and ⁠*REL.csv⁠) will be saved. Defaults to a temporary directory.

checklist

Character. The species checklist to be used. By default, it uses the checklist defined in the database's metadata.

Details

RvegCombine() operates via a console menu with two primary modes:

Layer Merging (LAYER): Moves all species recorded in one specific layer (e.g., shrub layer 2) into another layer (e.g., tree layer 3).
Species Merging (SPEC): Merges the records of one specific taxon into another across the entire database, which is highly useful for resolving taxonomic aggregates or correcting identification errors after data entry.

Mathematical Consolidation: #' When merging entities that both have non-zero percentage covers in the same relevé, the function does not simply add them together (which could exceed 100%). Instead, it uses a probabilistic sum formula to estimate the combined cover:

Combined = C_1 + C_2 \times (1 - \frac{C_1}{100})

Value

Writes two linked CSV files to the location specified by export, representing the modified Rveg database.

Examples

if (interactive()) {
  RvegCombine(
    database = file.path(path.package("Rveg"), "extdata/ExampleDB", "example_1")
  )
}

RvegLoad: Load an Rveg Database into the R Environment

Description

Reads an existing Rveg database (containing relevé data, header data, and metadata) into R for analysis. By default, it automatically translates the internal 7-character ShortName codes back into full botanical names and extracts the layer information.

Usage

RvegLoad(
  database = "default",
  checklist = "default",
  customscale = FALSE,
  variation = 1
)

Arguments

database

Character. The path and name of the Rveg database to load (e.g., "path/to/my_db"). Defaults to "default", which loads the package's built-in example database.

checklist

Character. The species checklist to use for taxonomy translation. By default, the function uses the checklist specified in the database's metadata.

customscale

Logical. If TRUE, launches an interactive prompt to convert custom abundance scales into numeric percentages. Defaults to FALSE.

variation

Numeric. Determines the format of the returned object (1, 2, or 3). Defaults to 1.

Details

The structure of the imported data is controlled by the variation parameter:

variation = 1 (Default): Returns a single, large data frame. The header data (HEAD) is bound to the top of the species composition data (REL), with new columns added for FullName and layer.
variation = 2: Returns the raw database as a list of three elements: ⁠$HeaderDATA⁠, ⁠$RelDATA⁠, and ⁠$meta⁠ (metadata) without any taxonomic translation.
variation = 3: Returns the database as a list of three elements, but ⁠$RelDATA⁠ is processed to include the translated FullName and layer columns.

Custom Scales: If customscale = TRUE, the function operates interactively. It will pause and prompt the user to manually define percentage replacements for any custom abundance symbols found in the data.

Value

A data frame (if variation = 1) or a list containing data frames and metadata (if variation = 2 or 3).

Examples

# Example 1: Load the built-in Rveg database into a single data frame
my_data <- RvegLoad()

# Example 2: Load the database as a list with separated Header and Releve tables
my_list <- RvegLoad(variation = 3)

RvegMerge: Merge Two Rveg Databases

Description

Combines two separate Rveg databases into a single, unified database. This function cleanly merges both the species composition data (REL) and the environmental plot header data (HEAD), and seamlessly combines their metadata.

Usage

RvegMerge(database_1, database_2, export = "export")

Arguments

database_1

Character. The path and name of the first Rveg database (e.g., "path/to/db1").

database_2

Character. The path and name of the second Rveg database (e.g., "path/to/db2").

export

Character. The output path and name where the merged database files (⁠*HEAD.csv⁠ and ⁠*REL.csv⁠) will be saved. Defaults to a temporary directory.

Details

During the merge process:

Relevé Re-indexing: The relevé columns from both databases are sequentially re-indexed (e.g., X1, X2, ..., Xn) to prevent column name collisions.
Checklist Validation: The function checks the metadata of both databases to ensure they were built using the same species checklist. If the checklists differ, it will issue a warning, though the merge will still proceed.
Missing Species: If a species exists in one database but not the other, the function automatically fills the absences with 0.
Metadata: The total number of relevés is updated, and any custom species (extra_spec) from both databases are concatenated together.

Value

Writes two linked CSV files to the location specified by export, representing the combined Rveg database.

Examples

# Example: Merging the built-in database with itself
db_path <- file.path(path.package("Rveg"), "extdata/ExampleDB", "example_1")

RvegMerge(
  database_1 = db_path,
  database_2 = db_path
)

RvegToJuice: Export an Rveg Database to JUICE compatible format

Description

Exports an existing Rveg database into a format directly compatible with JUICE, a comprehensive software for vegetation classification. This function processes both the species composition data and the header data, formatting them to meet JUICE's import requirements.

Usage

RvegToJuice(database, export = "export", checklist = "default")

Arguments

database

Character. The path and name of an existing Rveg database to be exported (e.g., "path/to/my_db").

export

name of your exported csv file

checklist

Character. The species checklist to use. By default, the function attempts to read the checklist specified in the database's metadata. You can override this by providing a custom file path or a built-in dictionary string.

Details

To ensure seamless compatibility with JUICE, this function performs several background transformations:

Layer Mapping: Rveg layers are automatically converted to JUICE's numeric layer representations (e.g., Tree layer "3" becomes "2", Shrub "2" becomes "4", Herb "1" becomes "6", etc.).
Absence Encoding: Zero values (0) are converted to ..
Encoding: Files are written using ISO-8859-15 encoding, which is the standard expected by JUICE for proper character rendering.

For JUICE import first import relevé data as Spreadsheet file and follow with Header data as Tab delimineted file.

Value

Writes two text-based CSV files to the location specified by export: one containing the header data (⁠*H.csv⁠) and one containing the relevé species data formatted with JUICE headers (⁠*R.csv⁠).

Examples

# Example: Exporting the built-in example Rveg database to JUICE format
RvegToJuice(
  database = file.path(path.package("Rveg"), "extdata/ExampleDB", "example_1")
)

RvegToTv: Export an Rveg Database to Turboveg Compatible Format

Description

Exports an existing Rveg database into a CSV format compatible with the Turboveg vegetation database management system. The function automatically reconstructs full botanical names from the internal ShortName codes and maps vegetation layers to standard Turboveg abbreviations.

Usage

RvegToTv(database, export = "export", checklist = "default", ver = 3)

Arguments

database

Character. The path and name of the existing Rveg database to be exported (e.g., "path/to/my_db").

export

Character. The output path and name where the resulting Turboveg CSV file(s) will be saved. Defaults to a temporary directory.

checklist

Character. The species checklist used to match Rveg's 7-character ShortName codes back to their full botanical names. Defaults to "default".

ver

Numeric. The target Turboveg version format to export to (either 2 or 3). Defaults to 3.

Details

During export, Rveg's alphanumeric layers are translated into Turboveg's specific layer codes (e.g., 0 becomes ml, 1 becomes hl, 2 becomes s1, 3 becomes t1, and J becomes jl).

The output structure changes depending on the target Turboveg version specified by the ver parameter:

Turboveg v3 (ver = 3): Writes a single, combined .csv file containing both header and species data.
Turboveg v2 (ver = 2): Writes two separate files: ⁠*R.csv⁠ for relevé species data and ⁠*H.csv⁠ for header data.

Value

Writes one or two CSV files to the location specified by export, depending on the chosen Turboveg version.

Examples

# Example: Exporting the built-in Rveg database to Turboveg v3 format
RvegToTv(
  database = file.path(path.package("Rveg"), "extdata/ExampleDB", "example_1"),
  ver = 3
)

TvToRveg: Import Turboveg Data into an Rveg Database

Description

Converts a Turboveg export file into a fully functional Rveg database. The function parses plot headers, standardizes species nomenclature against a specified checklist, and maps vegetation layers.

Usage

TvToRveg(tv, export = "export", checklist = "default", Rveglayers = TRUE)

Arguments

tv

Character. The file path to the Turboveg export file (.csv or .xml).

export

Character. The output path and name of the new Rveg database Defaults to a temporary directory.

checklist

Character. The species checklist used to match Turboveg full names to Rveg's 7-character ShortName codes. Defaults to "default". Select one you want to use in your Rveg database or the one most similar to the one used in Turboveg.

Rveglayers

Logical. If TRUE (the default), Turboveg layer codes (e.g., 't', 's', 'h', 'm', 'j') are automatically translated into standard Rveg numeric/character layers (3, 2, 1, 0, J).

Details

This function natively supports both .csv and .xml Turboveg export formats. In Turboveg, either selecet ⁠Standard XML file⁠ or ⁠Spreadsheet table⁠. In the case of spreadsheet table, select format 'semicolon delimited and requested header data.

During the import process, the function operates interactively:

Species Resolution: If a species in the Turboveg file cannot be automatically matched to the provided checklist, the function will pause and prompt the user to manually resolve the unknown species using a search interface.
Scale Selection: The user will be prompted to specify whether the imported abundance data uses percentages ("P") or the Braun-Blanquet scale ("BB").

Value

Writes two linked CSV files (⁠*REL.csv⁠ and ⁠*HEAD.csv⁠ = ⁠Rveg database⁠) to the location specified by export.

Examples

if (interactive()) {
  # Example: Importing a Turboveg CSV export (or use tvexport.xml)
  TvToRveg(
    tv = file.path(path.package("Rveg"), "extdata/ExampleDB", "tvexport.csv"),
    Rveglayers = TRUE
  )
}

addReleve: Digitize and Edit Relevés in an Rveg Database

Description

The core interactive function of the Rveg package. addReleve() launches a console-based menu system that allows users to create new vegetation databases, digitize new relevés, and edit existing ones. It seamlessly manages both the species composition data (REL) and the environmental plot header data (HEAD). Parameter start was removed.

For list of commands in addReleve menu prompt help or ⁠?⁠

Usage

addReleve(
  database = "NEW",
  save = "default",
  checklist = "default",
  customhead = NULL,
  extrahead = NULL,
  metadata = NULL
)

Arguments

database

Character. The path and name of an existing Rveg database (e.g., "path/to/my_db"). Defaults to "NEW" which creates a fresh database.

save

Character. The output path and name where the resulting database files (⁠*HEAD.csv⁠ and ⁠*REL.csv⁠) will be exported. Defaults to a temporary directory.

checklist

Character. The species checklist to use. Can be a built-in checklist (atm: cz_dh2012, Czechia_slovakia_2015, cz_kaplan2019, wcvp_que, wcvp_por) or a file path to a custom txt checklist. Default use cz_dh2012. see function CreateChecklist.

customhead

Character vector. A vector of strings defining completely custom header fields. Overrides the default schema.

extrahead

Character vector. Additional header fields to append to the end of the default or existing header schema.

metadata

Character vector of length 2. Used to store the Project Title and Project Description (e.g., c("Alpine Flora", "Summer 2024 survey")).

Value

Writes two linked CSV files (Rveg database) to the location specified by save: one containing the relevé species data (⁠*REL.csv⁠) and one containing the header data (⁠*HEAD.csv⁠).

Examples

if (interactive()) {
  # Launch the interactive menu for a new database
  addReleve(
    database = "NEW",
    save = "my_new_project",
    metadata = c("Project Title", "Project Description")
  )
}

Rveg: Digitization of Phytosociological Relevés

Description

Author(s)

References

See Also

CreateChecklist: Create a custom checklist for Rveg

Description

Usage

Arguments

Details

Value

Examples

RvegCheck: Inspect, Validate, Edit and Repair an Rveg Database

Description

Usage

Arguments

Details

Value

See Also

Examples

RvegCombine: Merge Species or Vegetation Layers in an Rveg Database

Description

Usage

Arguments

Details

Value

See Also

Examples

RvegLoad: Load an Rveg Database into the R Environment

Description

Usage

Arguments

Details

Value

Examples

RvegMerge: Merge Two Rveg Databases

Description

Usage

Arguments

Details

Value

See Also

Examples

RvegToJuice: Export an Rveg Database to JUICE compatible format

Description

Usage

Arguments

Details

Value

Examples

RvegToTv: Export an Rveg Database to Turboveg Compatible Format

Description

Usage

Arguments

Details

Value

Examples

TvToRveg: Import Turboveg Data into an Rveg Database

Description

Usage

Arguments

Details

Value

Examples

addReleve: Digitize and Edit Relevés in an Rveg Database

Description

Usage

Arguments

Value

Examples