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ccviR

ccviR: an R package and Shiny app to implement the NatureServe Climate Change Vulnerability Index - Published in JOSS (2024)

https://github.com/landscitech/ccvir

Science Score: 98.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 9 DOI reference(s) in README and JOSS metadata
  • ✓
    Academic publication links
    Links to: joss.theoj.org
  • ○
    Committers with academic emails
  • ○
    Institutional organization owner
  • ✓
    JOSS paper metadata
    Published in Journal of Open Source Software

Scientific Fields

Engineering Computer Science - 40% confidence
Last synced: 6 months ago · JSON representation ·

Repository

Implement NatureServe climate change vulnerability index in R

Basic Info
Statistics
  • Stars: 3
  • Watchers: 1
  • Forks: 2
  • Open Issues: 31
  • Releases: 7
Created about 5 years ago · Last pushed 6 months ago
Metadata Files
Readme Changelog License Citation

README.Rmd 

---
output: github_document
---



```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# ccviR 



[![R-CMD-check](https://github.com/LandSciTech/ccviR/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/LandSciTech/ccviR/actions/workflows/R-CMD-check.yaml)
[![Lifecycle: stable](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://lifecycle.r-lib.org/articles/stages.html#stable)
[![DOI](https://joss.theoj.org/papers/10.21105/joss.07150/status.svg)](https://doi.org/10.21105/joss.07150)
[![R-CMD-check](https://github.com/steffilazerte/ccviR/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/steffilazerte/ccviR/actions/workflows/R-CMD-check.yaml)
[![Codecov test coverage](https://codecov.io/gh/steffilazerte/ccviR/graph/badge.svg)](https://app.codecov.io/gh/steffilazerte/ccviR)


The ccviR package implements the [NatureServe Climate Change Vulnerability Index (CCVI) version 3.02](https://www.natureserve.org/conservation-tools/climate-change-vulnerability-index) in an R package and Shiny App. The package allows all of the geospatial aspects of calculating the CCVI to be done in R, removing the need for separate GIS calculations. The app provides an interactive application designed to offer a user-friendly and simple interface for calculating the NatureServe CCVI. 

The NatureServe CCVI is a rapid assessment tool designed to allow a relative grouping of unrelated taxa by vulnerability to climate change and to highlight which factors contribute to the climate change vulnerability of individual species or groups of taxa. This information can be used to inform conservation decision making and to help identify actions to increase species resilience to climate change. See [Young et. al (2012)](https://www.degruyter.com/document/doi/10.7208/9780226074641-007/html), [Young et. al. (2015)](https://doi.org/10.1002/wsb.478) and the [NatureServe CCVI Guidelines](https://www.natureserve.org/sites/default/files/guidelines_natureserveclimatechangevulnerabilityindex_r3.02_1_jun_2016.pdf) for more detailed descriptions of the index and how it was created.

## Installation

You can install the development version of ccviR from [GitHub](https://github.com/) with:

``` r
# install.packages("devtools")
devtools::install_github("LandSciTech/ccviR")
```

## Launching the app

The code below will open the app in your default browser with an example data set available. 

```r 
library(ccviR)
run_ccvi_app("demo")
```
While the following will open the app with the current working directory as the default data location.

```r 
run_ccvi_app()
```

## Comparison to the NatureServe CCVI tool
 
ccviR uses the same vulnerability factors and scoring algorithm as the original NatureServe Excel spreadsheet. The index values, scores and Monte Carlo uncertainty analysis produced are the same.

### New Features
- Spatial analyses are included in the package so only minimal GIS skills are needed 
- Uses climate data from the whole species range rather than the range in the assessment area to score thermal and hydrological niche factors
- Simultaneously calculates the index for multiple scenarios such as, emissions scenarios, time horizons or GCMs
- A function and Shiny app to classify new climate data sets into exposure categories 
- Plots that explain the drivers of the index value
- Allows the full assessment to be carried out in a reproducible environment
- Simplifies synthetic analyses across many species, groups or regions
- The Shiny app provides a Graphical User Interface to calculate the NatureServe CCVI
- The Shiny app allows users to calculate the index without knowing R
- Makes the NatureServe CCVI accessible to a wider audience


## Vignettes/tutorials available

See `vignette("app_vignette", package = "ccviR")` for an introduction to how to use the app with a demo data set, `vignette("app_details_vignette", package = "ccviR")` for a more detailed look at how to use the app in practice, `vignette("data_prep_vignette", package = "ccviR")` for how to use an app to prepare custom climate data sets, and `vignette("package_vignette", package = "ccviR")` for a tutorial on how to use the package to calculate the index directly in R.


## Citation 

  Endicott, S., Naujokaitis-Lewis, I., 2024. ccviR: an R package and Shiny app
  to implement the NatureServe Climate Change Vulnerability Index. Journal of
  Open Source Software 9, 7150. https://doi.org/10.21105/joss.07150

Owner

  • Name: Landscape Science & Technology Division, Environment & Climate Change Canada
  • Login: LandSciTech
  • Kind: organization
  • Location: National Wildlife Research Centre, Carleton University, Ottawa, ON

JOSS Publication

ccviR: an R package and Shiny app to implement the NatureServe Climate Change Vulnerability Index
Published
November 15, 2024
DOI
Volume 9, Issue 103, Page 7150
Authors
Sarah Endicott ORCID
Landscape Science and Technology Division, National Wildlife Research Centre, Environment and Climate Change Canada, Ottawa, ON, Canada
Ilona Naujokaitis-Lewis ORCID
Landscape Science and Technology Division, National Wildlife Research Centre, Environment and Climate Change Canada, Ottawa, ON, Canada
Editor
Mengqi Zhao ORCID
Tags
climate change vulnerability shiny
View PDF Review Thread Software Archive

Citation (CITATION.cff) 

cff-version: "1.2.0"
authors:
- family-names: Endicott
  given-names: Sarah
  orcid: "https://orcid.org/0000-0001-9644-5343"
- family-names: Naujokaitis-Lewis
  given-names: Ilona
  orcid: "https://orcid.org/0000-0001-9504-4484"
doi: 10.5281/zenodo.14170051
message: If you use this software, please cite our article in the
  Journal of Open Source Software.
preferred-citation:
  authors:
  - family-names: Endicott
    given-names: Sarah
    orcid: "https://orcid.org/0000-0001-9644-5343"
  - family-names: Naujokaitis-Lewis
    given-names: Ilona
    orcid: "https://orcid.org/0000-0001-9504-4484"
  date-published: 2024-11-15
  doi: 10.21105/joss.07150
  issn: 2475-9066
  issue: 103
  journal: Journal of Open Source Software
  publisher:
    name: Open Journals
  start: 7150
  title: "ccviR: an R package and Shiny app to implement the NatureServe
    Climate Change Vulnerability Index"
  type: article
  url: "https://joss.theoj.org/papers/10.21105/joss.07150"
  volume: 9
title: "ccviR: an R package and Shiny app to implement the NatureServe
  Climate Change Vulnerability Index"

GitHub Events

Total
  • Create event: 1
  • Release event: 2
  • Issues event: 75
  • Watch event: 2
  • Member event: 1
  • Issue comment event: 164
  • Push event: 38
  • Pull request event: 8
Last Year
  • Create event: 1
  • Release event: 2
  • Issues event: 75
  • Watch event: 2
  • Member event: 1
  • Issue comment event: 164
  • Push event: 38
  • Pull request event: 8

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 547
  • Total Committers: 6
  • Avg Commits per committer: 91.167
  • Development Distribution Score (DDS): 0.154
Past Year
  • Commits: 36
  • Committers: 2
  • Avg Commits per committer: 18.0
  • Development Distribution Score (DDS): 0.028
Top Committers
Name Email Commits
see24 s****4@g****m 463
Sarah Endicott s****t@e****a 62
Adriana Caswell a****l@e****a 16
ilonaECCC 6****C 4
sarahouimette s****6@u****a 1
sarahgeargeoura 1****a 1
Committer Domains (Top 20 + Academic)
ec.gc.ca: 2 uottawa.ca: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 188
  • Total pull requests: 48
  • Average time to close issues: 6 months
  • Average time to close pull requests: 9 days
  • Total issue authors: 8
  • Total pull request authors: 5
  • Average comments per issue: 1.68
  • Average comments per pull request: 0.21
  • Merged pull requests: 45
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 54
  • Pull requests: 6
  • Average time to close issues: about 2 months
  • Average time to close pull requests: about 2 months
  • Issue authors: 3
  • Pull request authors: 2
  • Average comments per issue: 1.3
  • Average comments per pull request: 0.0
  • Merged pull requests: 6
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • see24 (112)
  • adricaswell (29)
  • steffilazerte (26)
  • sarahgeargeoura (9)
  • sebdalgarno (3)
  • plestiodon (2)
  • out2lunch22 (2)
  • mengqi-z (1)
Pull Request Authors
  • see24 (52)
  • adricaswell (12)
  • ilonaECCC (8)
  • steffilazerte (2)
  • sarahgeargeoura (1)
Top Labels
Issue Labels
enhancement (55) bug (33) Priority: High (25) documentation (16) Priority: Low (14) question (4) Priority: Med (4) test needed (2) wontfix (1) good first issue (1) help wanted (1)
Pull Request Labels

Packages

  • Total packages: 2
  • Total downloads: unknown
  • Total dependent packages: 0
    (may contain duplicates)
  • Total dependent repositories: 0
    (may contain duplicates)
  • Total versions: 4
proxy.golang.org: github.com/LandSciTech/ccviR
  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.4%
Average: 5.6%
Dependent repos count: 5.8%
Last synced: 6 months ago
proxy.golang.org: github.com/landscitech/ccvir
  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.4%
Average: 5.6%
Dependent repos count: 5.8%
Last synced: 6 months ago

Dependencies

DESCRIPTION cran
  • R >= 2.10 depends
  • R.utils * imports
  • dplyr * imports
  • exactextractr * imports
  • fs * imports
  • ggplot2 * imports
  • pkgload * imports
  • plotly * imports
  • purrr * imports
  • raster * imports
  • rgdal * imports
  • scales * imports
  • sf * imports
  • shiny * imports
  • shinyFiles * imports
  • shinycssloaders * imports
  • shinyjs * imports
  • shinyvalidate * imports
  • stats * imports
  • stringr * imports
  • tidyr * imports
  • tmap * imports
  • units * imports
  • utils * imports
  • furrr * suggests
  • future * suggests
  • knitr * suggests
  • readxl * suggests
  • rmarkdown * suggests
  • shinytest * suggests
  • testthat >= 2.1.0 suggests
.github/workflows/R-CMD-check.yaml actions
  • actions/checkout v2 composite
  • r-lib/actions/check-r-package v1 composite
  • r-lib/actions/setup-r v1 composite
  • r-lib/actions/setup-r-dependencies v1 composite
.github/workflows/pkgdown.yaml actions
  • actions/checkout v2 composite
  • r-lib/actions/setup-pandoc v1 composite
  • r-lib/actions/setup-r v1 composite
  • r-lib/actions/setup-r-dependencies v1 composite