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https://github.com/equitable-equations/fqar

The fqar package provides R tools for downloading and analyzing floristic quality assessment data from www.universalFQA.org
https://github.com/equitable-equations/fqar

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The fqar package provides R tools for downloading and analyzing floristic quality assessment data from www.universalFQA.org

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README 

        
# fqar 






  

  [![R-CMD-check](https://github.com/equitable-equations/fqar/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/equitable-equations/fqar/actions/workflows/R-CMD-check.yaml)

  [![CRAN status](https://www.r-pkg.org/badges/version/fqar)](https://CRAN.R-project.org/package=fqar)

  [![DOI](https://joss.theoj.org/papers/10.21105/joss.06366/status.svg)](https://doi.org/10.21105/joss.06366)



  

  

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](https://universalfqa.org/), an online database maintained by [Openlands](https://openlands.org/).



## Installation

 

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



```{r install}

install.packages("fqar")

```



Alternatively, the development version can be installed from [GitHub](https://github.com/equitable-equations/fqar).



```{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](https://universalfqa.org/). 



```{r indexing}

# download a list of all fqa databases:

databases <- index_fqa_databases()



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

chicago_fqas <- index_fqa_assessments(database_id = 149) 



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

chicago_transects <- index_fqa_transects(database_id = 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](https://universalfqa.org/). These identifiers 

# can be found using `index_fqa_assessments`.

woodland <- download_assessment(assessment_id = 25640)



# download multiple assessments:

mcdonald_fqas <- download_assessment_list(database_id = 149, 

                                          site == "McDonald Woods")

```



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



```{r downloading2}

# download a single transect assessment:

rock_garden <- download_transect(transect_id = 6875)



# download multiple transect assessments:

lord_fqas <- download_transect_list(database = 63,

                                    practitioner == "Sam Lord")

```



Unfortunately, the [universalfqa.org](https://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:

woodland_species <- assessment_inventory(woodland)



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

woodland_summary <- assessment_glance(woodland)



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

mcdonald_summary <- assessment_list_glance(mcdonald_fqas)

```



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:

survey_species <- transect_inventory(rock_garden)



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

survey_phys <- transect_phys(rock_garden)



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

rock_garden_summary  <- transect_glance(rock_garden)



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

lord_summary <- transect_list_glance(lord_fqas)

```



### 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 <- download_assessment_list(database = 2)



# Extract inventories as a list:

ontario_invs <- assessment_list_inventory(ontario)



# Enumerate all co-occurrences in this database:

ontario_cooccurrences <- assessment_cooccurrences(ontario_invs)



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

ontario_cooccurrences <- assessment_cooccurrences_summary(ontario_invs)

```



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](https://github.com/equitable-equations/fqar/blob/main/vignettes/fqar.Rmd) 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.