Code Monkey home page Code Monkey logo

plotbiomes's Introduction

plotbiomes

DOI

AppVeyor Build status Travis Build Status Coverage Status

Overview

R package for plotting Whittaker' biomes with ggplot2.

The original graph is Figure 5.5 in Ricklefs, R. E. (2008), The economy of nature. W. H. Freeman and Company. (Chapter 5, Biological Communities, The biome concept). The figure was processed and brought into an R friendly format. Details are given in Whittaker_biomes_dataset.html document.

Plotting Whittaker' biomes was also addressed in BIOMEplot package by Georges Kunstler and in ggbiome package by Guillem Bagaria, Victor Granda and Georges Kunstler.

Installation

You can install plotbiomes from github with:

# install.packages("devtools")
devtools::install_github("valentinitnelav/plotbiomes")

Examples & Vignettes

Check examples at Whittaker_biomes_examples.html and Check_outliers.html vignettess.

Simple example of plotting Whittaker' biomes:

library(plotbiomes)

whittaker_base_plot()

How to cite the package?

I just uploaded this packge on Zenodo after almost 5 years :) I noticed that there are several forks by now and I presume people adapt it to their needs, plus I do not have the time to fully maintain this. Nevertheless, would be nice to cite this package if you make use of it.

You can cite the first release of the package as:

Valentin Ștefan, & Sam Levin. (2018). plotbiomes: R package for plotting Whittaker biomes with ggplot2 (v1.0.0). Zenodo. https://doi.org/10.5281/zenodo.7145245

Examples of scientific papers using and citing the package can be found here:

Wolf, S., Mahecha, M.D., Sabatini, F.M. et al. Citizen science plant observations encode global trait patterns. Nat Ecol Evol (2022). https://doi.org/10.1038/s41559-022-01904-x

Carmona, C.P., Bueno, C.G., Toussaint, A., Träger, S., Díaz, S., Moora, M., Munson, A.D., Pärtel, M., Zobel, M. and Tamme, R., 2021. Fine-root traits in the global spectrum of plant form and function. Nature, 597(7878), pp.683-687.

Laughlin, D.C., Mommer, L., Sabatini, F.M., Bruelheide, H., Kuyper, T.W., McCormack, M.L., Bergmann, J., Freschet, G.T., Guerrero-Ramírez, N.R., Iversen, C.M. and Kattge, J., 2021. Root traits explain plant species distributions along climatic gradients yet challenge the nature of ecological trade-offs. Nature Ecology & Evolution, 5(8), pp.1123-1134.

Hammond, W.M., Williams, A.P., Abatzoglou, J.T., Adams, H.D., Klein, T., López, R., Sáenz-Romero, C., Hartmann, H., Breshears, D.D. and Allen, C.D., 2022. Global field observations of tree die-off reveal hotter-drought fingerprint for Earth’s forests. Nature communications, 13(1), pp.1-11.

Lembrechts, J.J., Van den Hoogen, J., Aalto, J., Ashcroft, M.B., De Frenne, P., Kemppinen, J., Kopecký, M., Luoto, M., Maclean, I.M., Crowther, T.W. and Bailey, J.J., 2022. Global maps of soil temperature. Global Change Biology, 28(9), pp.3110-3144.

Falster, D., Gallagher, R., Wenk, E.H., Wright, I.J., Indiarto, D., Andrew, S.C., Baxter, C., Lawson, J., Allen, S., Fuchs, A. and Monro, A., 2021. AusTraits, a curated plant trait database for the Australian flora. Scientific Data, 8(1), pp.1-20.

Massante, J.C., Götzenberger, L., Takkis, K., Hallikma, T., Kaasik, A., Laanisto, L., Hutchings, M.J. and Gerhold, P., 2019. Contrasting latitudinal patterns in phylogenetic diversity between woody and herbaceous communities. Scientific reports, 9(1), pp.1-10.

plotbiomes's People

Contributors

levisc8 avatar valentinitnelav avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar

plotbiomes's Issues

Dataset vignette will not build on systems without Ghost Script installed

This particular vignette will not build on any system that doesn't already have Ghost Script installed. This is not a problem if we decide to keep the package on Github, but will be an issue if submitting to CRAN.

One alternative I've found is to use "static vignettes". In other words, create a pdf version of the vignette ahead of time and use that instead of having an RMarkdown file that is rebuilt each time it is installed/checked. They can still include code that is fully reproducible, but removes the Ghost Script dependency so that people who haven't installed yet can still download, build, and install the package.

One drawback of this is that I'm not sure if we'd be able to include a dynamic vignette along with the static one, so we might be forced to change how the Examples vignette is produced as well. I don't think it would add too much work, but may be slightly annoying at first.

R.rsp provides a mechanism for building static vignettes. See this vignette for details and let me know what you think.

Extract the names of the Whittaker biome regions from the plot

Request:

Is there an easy / swish way to extract the names of the Whittaker biome regions from the plot and align them with the data I’m plotting? I just want the names of each biome associated with each site so I can use them for plotting the discreet biome variables later.

Estimate the biome for outliers

I have some sample data points and I would like to extract corresponding Whittaker biome information based on the annual average temperature and annual average precipitation of these data points. Do you have any solutions for this? Can you identify outliers (i.e. those not in Whittaker communities), and also determine which biome each sample data point belongs to? If you are able to help with this, I would be grateful. Thank you!

Failed to install - unsupported proxy error message

When installing the plotbiomes package one can get something like below:

devtools::install_github("valentinitnelav/plotbiomes")
## Error: Failed to install 'unknown package' from GitHub:
## Unsupported proxy 'https://proxy.companydomain:8080', libcurl is built without the HTTPS-proxy support.

Same happens with remotes::install_github("valentinitnelav/plotbiomes").

Note that, https://proxy.companydomain:8080/ is just an example here (can be whatever the case).

Installation issues - HTTP error 401

> devtools::install_github("valentinitnelav/plotbiomes")
Using github PAT from envvar GITHUB_TOKEN
Error: Failed to install 'unknown package' from GitHub:
  HTTP error 401.
  Bad credentials

  Rate limit remaining: 56/60
  Rate limit reset at: 2021-10-06 23:56:59 UTC

Anything to be done other than cloning?

Originally posted by @technocrat in #7 (comment)

Installation issues

Rtools missing

> devtools::install_github("valentinitnelav/plotbiomes")
WARNING: Rtools is required to build R packages, but is not currently installed.

Please download and install Rtools 4.0 from https://cran.r-project.org/bin/windows/Rtools/.
Downloading GitHub repo valentinitnelav/plotbiomes@HEAD
Installing 51 packages: proxy, wk, e1071, units, s2, Rcpp, DBI, classInt, later, promises, httpuv, sp, plyr, raster, systemfonts, uuid, svglite, sf, htmlwidgets, htmltools, base64enc, colorspace, isoband, gtable, gridExtra, ggplot2, viridisLite, munsell, labeling, farver, lazyeval, leaflet.providers, viridis, scales, RColorBrewer, png, markdown, crosstalk, sfheaders, rapidjsonr, jsonify, geometries, leaflet, geojsonsf, webshot, servr, satellite, leafpop, leafem, mapview, data.table
Installing packages into ‘C:/Users/vs66tavy/Documents/R/win-library/4.0’
(as ‘lib’ is unspecified)

  There are binary versions available but the source versions are later:
          binary source needs_compilation
sf         1.0-2  1.0-3              TRUE
satellite  1.0.2  1.0.3              TRUE

  Binaries will be installed
...

Proxy issues

See #6 - Failed to install - unsupported proxy error message

HTTP error 401

See #8 - Installation issues - HTTP error 401

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.