We are very excited to announce the newest release of our EcoData Retriever software and the first release of a supporting R package, ecoretriever. If you’re not familiar with the EcoData Retriever you can read more here.

The biggest improvement to the Retriever in this set of releases is the ability to run it directly from R. Dan McGlinn did a great job leading the development of this package and we got ton of fantastic help from the folks at rOpenSci (most notably Scott Chamberlain, Gavin Simpson, and Karthik Ram). Now, once you install the main EcoData Retriever, you can run it from inside R by doing things like:

install.packages('ecoretriever')
library(ecoretriever)

# List the datasets available via the Retriever
ecoretriever::datasets()

# Install the Gentry dataset into csv files in your working directory
ecoretriever::install('Gentry', 'csv')

# Download the raw Gentry dataset files, without any processing,
# to the subdirectory named data
ecoretriever::download('Gentry', './data/')

# Install and load a dataset as a list
Gentry = ecoretriever::fetch('Gentry')
names(Gentry)
head(Gentry$counts)

The other big advance in this release is the ability to have the Retriever directly download files instead of processing them. This allows us to support data that doesn’t come in standard tabular forms. So, we can now include things like environmental data in GIS formats and phylogenetic data such as supertrees. We’ve used this new capability to allow the automatic downloading of the Bioclim data, one of the most widely used climate datasets in ecology, and the supertree for mammals from Fritz et al. 2009.

Finally, we’ve also add the very cool mammalian diet dataset from Dryad