On a regular basis I am using open source software that substantially facilitates my work. I think open science producing transparent and clear results is very closely related to the use of open source software. Thus I am following many others already strongly promoting open science. Here I can really recommend a recent Letter to Trends in Ecology and Evolution by Rocchini and Neteler (2012).
# Recommended software
Of course, all my work strongly depends on already existing and powerful software products with very strong and helpful user communities. Most of my work is just combining them in a useful way to answer or create questions in my research field of freshwater ecology. Some of them especially those I use very regurily and those I can really recommend can be found under “Recommended Software”.
# Contributed packages and add-ons
For my research work I often use and apply manifold coupling and interfacing methods of open source software (e.g. GRASS GIS, R) to develop my own applications and scripts for daily work. As some of them might be very useful also to other users I want to share them. In the following, I listed R-packages and GRASS add ons I contributed and which are officially already available online.
# R packages
Functions to predict fish movement parameters based on multiple regression and plotting leptokurtic fish dispersal kernels (see Radinger and Wolter, 2013: Patterns and predictors of fish dispersal in rivers. Fish and Fisheries.)
As for every R-package a manual with working examples can be found here.The most recent version of the package can be download from CRAN repository respectively directly installed via R’s install.packages(“fishmove”).
# GRASS GIS add-ons
Modelling heterogeneous (leptokurtic) fish dispersal in river networks. A detailed description can be found here.
r.rdfilter is a raster-python add-on for GRASS which computes a new raster map by applying a focal filter on the input raster map. Thus each cell value depends on the values of adjacent cells. Instead of the “moving window”-algorithm (e.g. r.neighbors), r.rdfilter is a “real distance”-filter based on GRASS’ r.cost tool.
The most recent version of the add-on for GRASS 6.5 (GRASS 7 is untested yet) can be found and downloaded from the GRASS add-on SVN repository and also be installed via g.extension.[svn co https://svn.osgeo.org/grass/grass-addons/grass6/raster/r.rdfilter]
Python scripts that I used for different analysis, for generating example datasets and/or showing how my GRASS add-ons (especially FIDIMO) can be applied will br accessible on an open code platform soon.