Recology has moved to Github, using Jekyll.
I just finished moving the Recology blog content, etc. to Github. This move is intended to make it easy to do exactly what I want with this blog without the constrictions of Blogger. Thanks for continuing to come back and read. I won't delete the Blogger version of this blog, but only new content will appear on the new site.
I haven't figured out how to get the RSS working yet, but I'm working on it.
Recology
Recology HAS MOVED TO http://recology.info/. To get to the same blog post on the new site replace the http://r-ecology.blogspot.ca/ with http://recology.info/, but with the same ending, e,g. /2011/12/weecology-can-has-new-mammal-dataset.html (except remove the .html at the end)
Friday, January 6, 2012
Thursday, December 29, 2011
Weecology can has new mammal dataset
Recology has moved - go to http://recology.info/2011/12/weecology-can-has-new-mammal-dataset
So the Weecology folks have published a large dataset on mammal communities in a data paper in Ecology. I know nothing about mammal communities, but that doesn't mean one can't play with the data...
Their dataset consists of five csv files: communities, references, sites, species, and trapping data.
Where are these sites, and by the way, do they vary much in altitude?
Let's zoom in on just 'the states'?
What phylogenies can we get for the species in this dataset?
We can use the rOpenSci package treebase to search the online phylogeny repository TreeBASE. Limiting to returning a max of 1 tree (to save time), we can see that X species are in at least 1 tree on the TreeBASE database. Nice.
So there are 321 species in the database with at least 1 tree in the TreeBASE database. Of course there could be many more, but we limited results from TreeBASE to just 1 tree per query.
Here's the code:
So the Weecology folks have published a large dataset on mammal communities in a data paper in Ecology. I know nothing about mammal communities, but that doesn't mean one can't play with the data...
Their dataset consists of five csv files: communities, references, sites, species, and trapping data.
Where are these sites, and by the way, do they vary much in altitude?
Let's zoom in on just 'the states'?
What phylogenies can we get for the species in this dataset?
We can use the rOpenSci package treebase to search the online phylogeny repository TreeBASE. Limiting to returning a max of 1 tree (to save time), we can see that X species are in at least 1 tree on the TreeBASE database. Nice.
So there are 321 species in the database with at least 1 tree in the TreeBASE database. Of course there could be many more, but we limited results from TreeBASE to just 1 tree per query.
Here's the code:
Friday, December 23, 2011
Recology is 1 yr old...
Recology has moved, go to http://recology.info/2011/12/recology-is-1-yr-old
This blog has lasted a whole year already. Thanks for reading and commenting.
There are a couple of announcements:
Anywho, here is the breakdown of visits to this blog, visualized using #ggplot2, of course. There were a total of about 23,000 pageviews in the first year of this blog. Here is the pie chart code I used:
Visits to top ten posts:
Visits by by pages:
Visits by top referring sites:
Visits by country:
Visits by browsers:
Visits by operating system:
This blog has lasted a whole year already. Thanks for reading and commenting.
There are a couple of announcements:
- Less blogging: I hope to put in many more years blogging here, but in full disclosure, I am blogging for Journal of Ecology now, so I am going to be (and already have been) blogging less here.
- More blogging: If anyone wants to write guest posts at Recology on the topics of using R for ecology and evolution, or open science, please contact me!
- Different blogging: I was going to roll out the new dynamic views for this blog, but Google doesn't allow javascript, which is how I include code using GitHub gists. Oh well...
Anywho, here is the breakdown of visits to this blog, visualized using #ggplot2, of course. There were a total of about 23,000 pageviews in the first year of this blog. Here is the pie chart code I used:
Visits to top ten posts:
Visits by by pages:
Visits by top referring sites:
Visits by country:
Visits by browsers:
Visits by operating system:
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