fqar

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Floristic Quality Assessment (FQA) is a standardized method for rating the ecological value of natural areas based on the plant species found within them. The ${\tt fqar}$ package provides tools to download and analyze floristic quality assessments from universalfqa.org, an online database maintained by Openlands.

Installation

The ${\tt fqar}$ package is available on CRAN.

{r install} install.packages("fqar")

Alternatively, the development version can be installed from GitHub.

{r github} devtools::install_github("equitable-equations/fqar")

Usage

The ${\tt fqar}$ package consists of four categories of functions: indexing, downloading, tidying, and analytic functions. ${\tt fqar}$ also includes two sample data sets.

Indexing functions

At the simplest level, fqar allows users to obtain specific information about the databases, assessments, and transect assessments available from universalfqa.org.

```{r indexing}

download a list of all fqa databases:

databases <- indexfqadatabases()

download a list of all assessments in a specific database:

chicagofqas <- indexfqaassessments(databaseid = 149)

download a list of all transect assessments in a specific database:

chicagotransects <- indexfqatransects(databaseid = 149) ```

Downloading functions

Floristic quality assessments can be downloaded individually by ID number or collectively using dplyr::filter syntax.

```{r downloading}

download a single assessment using the assessment_id assigned by

universalfqa.org. These identifiers

can be found using index_fqa_assessments.

woodland <- downloadassessment(assessmentid = 25640)

download multiple assessments:

mcdonaldfqas <- downloadassessmentlist(databaseid = 149, site == "McDonald Woods") ```

${\tt fqar}$ also provides functions for downloading transect assessments.

```{r downloading2}

download a single transect assessment:

rockgarden <- downloadtransect(transect_id = 6875)

download multiple transect assessments:

lordfqas <- downloadtransect_list(database = 63, practitioner == "Sam Lord") ```

Unfortunately, the universalfqa.org server is often slow, and downloads (especially for transect assessments) may take some time.

Tidying functions

Data sets obtained from universalfqa.org are quite messy. ${\tt fqar}$ provides tools for converting such sets into a more convenient tidy format.

```{r tidying}

obtain a data frame with species data for a downloaded assessment:

woodlandspecies <- assessmentinventory(woodland)

obtain a data frame with summary information for a downloaded assessment:

woodlandsummary <- assessmentglance(woodland)

obtain a data frame with summary information for multiple downloaded assessments:

mcdonaldsummary <- assessmentlistglance(mcdonaldfqas) ```

Similar functions are provided for handling transect assessments. For those sets, physiognometric information can also be extracted.

```{r tidying2}

obtain a data frame with species data for a downloaded transect assessment:

surveyspecies <- transectinventory(rock_garden)

obtain a data frame with physiognometric data for a downloaded transect assessment:

surveyphys <- transectphys(rock_garden)

obtain a data frame with summary information for a downloaded transect assessment:

rockgardensummary <- transectglance(rockgarden)

obtain a data frame with summary information for multiple downloaded transect assessments:

lordsummary <- transectlistglance(lordfqas) ```

Analytic functions

As of version 0.3.0, ${\tt fqar}$ includes tools for analyzing species co-occurrence across multiple floristic quality assessments. A typical workflow consists of downloading a list of assessments, extracting inventories from each, then enumerating and summarizing co-occurrences of the species of interest.

```{r analysis}

Obtain a tidy data frame of all co-occurrences in the 1995 Southern Ontario database:

ontario <- downloadassessmentlist(database = 2)

Extract inventories as a list:

ontarioinvs <- assessmentlist_inventory(ontario)

Enumerate all co-occurrences in this database:

ontariocooccurrences <- assessmentcooccurrences(ontario_invs)

Sumamrize co-occurrences in this database, one row per target species:

ontariocooccurrences <- assessmentcooccurrencessummary(ontarioinvs) ```

Of particular note is the species_profile() function, which returns the frequency distribution of C-values of co-occurring species for a given target species.

{r profile} aster_profile <- species_profile("Aster lateriflorus", ontario_invs)

Learn More

• Read the ${\tt fqar}$ vignette to learn how to download and analyze FQAs with fqar.
• View the help files of any function in the ${\tt fqar}$ package for more examples.

Contribute

To contribute to ${\tt fqar}$ you can fork this repository and create pull requests to add features you think will be useful for users. You can also open an issue if you find a bug or wish to make a suggestion.