View source for FOSS Ecology

= Free and Open Source ecological software =

== R ==

'''Intro to R'''

Here are some pages that go through the basics of R programming.

Materials from an [[R workshop for ecologists]] developed by members of the New Zealand Ecological Society.

'''[https://github.com/swcarpentry/bc/tree/master/novice/r Intro material from Software carpentry on git-hub]'''
Read more about [http://software-carpentry.org/ Software carpentry] and their mission to teach lab skills for scientific computing.

[http://ecology.msu.montana.edu/labdsv/R/labs/ '''R labs for (vegetation) ecologists'''] by the [http://ecology.msu.montana.edu/labdsv/ Laboratory for Dynamic Synthetic Vegephenomenology] at Montana State University. The site includes an [http://ecology.msu.montana.edu/labdsv/R/labs/R_ecology.html#packages introduction on the basics of R programming]

Resources from Ben Bolker's book "'''Ecological Models and Data in R'''" are available from [http://ms.mcmaster.ca/~bolker/emdbook/ this website] and  [http://emdbolker.wikidot.com/ the book's very own wiki]. 

The '''[http://www.statmethods.net/ quick R wiki]''' is a website created for both current R users, and experienced users of other statistical packages (e.g., SAS, SPSS, Stata) who would like to transition to R. The goal of the website is to help you quickly access this language in your work.


'''Task views'''

[http://cran.r-project.org/web/views/ The R task views] are a good starting point for finding a relevant package and function to carry out tasks spanning from "[http://cran.r-project.org/web/views/Bayesian.html Bayesian inference]" to "[http://cran.r-project.org/web/views/TimeSeries.html Time series analysis]". There are currently 33 [http://cran.r-project.org/web/views/ R task views].

'''For-purchase books'''

Even though the R software is all about being open source most of the books about R are not free. From [http://www.r-project.org/doc/bib/R-books.html this website] you can find a list of '''147 for-purchase books relating to R'''.

=== Community ecology ===

'''vegan''' - Ordination methods, diversity analysis and other functions for community and vegetation ecologists.
* [https://github.com/naupaka/esa_vegan Slides and examples from a workshop on vegan held at ESA 2014]

=== Data Visualization ===

'''ggplot2''' - Powerful graphics package for both exploratory data analysis and publication quality figures.
* [https://github.com/naupaka/esa_data_viz_2014 Slides and examples from a workshop on ggplot2 held at ESA 2014]

=== Functional ecology ===
'''LeafArea''' - An interface for the image processing program ImageJ, which allows a rapid digital image analysis for particle sizes.
* [https://github.com/mattocci27/LeafArea Readme]

=== Networks ===

'''igraph''' is a package for complex graph analysis, which implements useful metrics of centrality, and has great visualization capacities. [http://bit.ly/pcz3wj ]

'''bipartite''' is designed specifically for two-mode (predator–preys, parasites–hosts, pollinators–plants) networks. It implements most of the metrics used in the food web literature, and has really powerful null models simulators built in. [http://bit.ly/q30ROr ]

'''network''' is a package to create and modify network objects. [http://bit.ly/n5msWr ]

=== Phylogenetics ===

=== Simulations ===

=== Spatial ecology ===

[https://github.com/gfoss-jrc/mainrepo/wiki/Documentation-resources GFOSS-JRC] and [http://www.spatial-ecology.net/dokuwiki/doku.php?id=start Spatial-ecology.net] are wikis to help people learning open source tools for spatial analysis, modelling and data processing. You will find scripts and links for performing basic and advanced GIS operations in GRASS GIS, AWK, BASH, PKtools, R, GDAL, etc.

[https://www.docker.com/ Docker] is an open platform for developers to build, ship, and run applications under linux environments. Docker images that are ready for performing Geospatial Analysis, such as [https://registry.hub.docker.com/u/javimarlop/ubuntugis-docker/ this ubuntu image] can be useful tools for ecologists for easily running or embedding code or applications requiring specific linux environment under any OS.