Evolution

So I want to mine some #altmetrics data for some research I’m thinking about doing. The steps would be: Get journal titles for ecology and evolution journals. Get DOI’s for all papers in all the above journal titles. Get altmetrics data on each DOI. Do some fancy analyses. Make som pretty figs. Write up results. It’s early days, so jus working on the first step. However, getting a list of journals in ecology and evolution is frustratingly hard. This turns out to not be that easy if you are (1) trying to avoid Thomson Reuters, and (2) want a machine interface way to do it (read: API). ...

Many R packages/tools have come out recently for doing ecology and evolution. All of the below were described in Methods in Ecology and Evolution, except for spider, which came out in Molecular Ecology Resources. Here are some highlights. mvabund paper - get R pkg Model-based analysis of multivariate abundance data. Visualising data, fitting predictive models, checking assumptions, hypothesis testing. popdemo paper - get R pkg Population demography using projection matrix analysis. motmot paper - get R pkg Models of trait macroevolution on trees spider paper - get R pkg Analysis of species identity and evolution, with particular reference to DNA barcoding BaSTA paper - get R pkg Bayesian estimation of age-specific survival from incomplete mark–recapture/recovery data with covariates abc paper - get R pkg Approximate Bayesian Computation (ABC) RNetLogo paper - get R pkg Running and exploring individual-based models implemented in NetLogo phytools paper - get R pkg Tools for phylogenetic comparative biology smatr paper - get R pkg Estimation and inference about allometric lines RBrownie paper - get R pkg ? Testing hypotheses about rates of evolutionary change polytomy resolver paper - get R pkg Resolve polytomies on dated phylogenies with their R scripts [here][]. And a cool tool came out for the Python programming language. ...

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. ...

I gave a talk today on doing very basic phylogenetics in R, including getting sequence data, aligning sequence data, plotting trees, doing trait evolution stuff, etc. Please comment if you have code for doing bayesian phylogenetic inference in R. I know phyloch has function mrbayes, but can’t get it to work… Phylogenetics in R View more presentations from schamber

So, I’ve blogged about this topic before, way back on 5 Jan this year. Matt Helmus, a postdoc in the Wootton lab at the University of Chicago, published a paper with Anthony Ives in Ecological Monographs this year (abstract here). The paper addressed a new statistical approach to phylogenetic community structure. As I said in the original post, part of the power of the PGLMM (phylogenetic generalized linear mixed models) approach is that you don’t have to conduct quite so many separate statistical tests as with the previous null model/randomization approach. ...

Carl Boettiger gave a talk on the topic of open science to incoming UC Davis graduate students. Here is the audio click here Here are the slides clickhere

Stalking the Fourth Domain with Jonathan Eisen, Ph D from mendelspod on Vimeo.

There is an awesome position opening up for an assistant professor in systematics at the University of Vermont. Below is the announcement, and see the original post at the Distributed Ecology blog. Why is this related to R? One can do a lot of systematics work in R, including retrieving scientific collections data through an upcoming package handshaking with VertNet (part of the rOpenSci project), managing large data sets, retrieval of GenBank data through the ape package (see fxn read.genbank), phylogenetic reconstruction and analysis, and more. So I am sure a systematist with R ninja skills will surely have a head up on the rest of the field. ...

Interesting talks/posters: Richard Lankau presented research on trade-offs and competitive ability. He suggests that during range expansion selection for increased intraspecific competitive ability in older populations leads to loss of traits for interspecific competitive traits due to trade-offs between these traits. Ellner emphatically states that rapid evolution DOES matter for ecological responses, and longer-term evolutionary patterns as well. [His paper on the talk he was giving came out prior to his talk, which he pointed out, good form sir] ...

Interesting talks/posters: Ethan White’s poster describing EcologicalData.org was of course awesome given my interest in getting data into the hands of ecologists over at rOpenSci.org. Ethan also has software you can download on your machine to get the datasets you want easily - EcoData Retriever. [rOpenSci will try to take advantage of their work and allow you to call the retriever from R] Carl Boettiger’s talk was awesome. He explained how we need better tools to be able to predict collapses using early warning signals. He developed a way to estimate the statistical distribution of probabilities of system collapse. Jennifer Dunne: Explained how she put together an ancient network from Germany. Bravo. Carlos Melian explained his model of network buildup that starts from individuals, allows speciation, and other evolutionary processes. Rachel Winfree told us that in two sets of mutualistic plant-pollinator networks in New Jersey and California, that the least connected pollinator species were the most likely to be lost from the network with increasing agricultural intensity. Dan Cariveau suggests that pollination crop services can be stabilized even with increasing agriculture intensity if in fact pollinator species respond in different ways. That is, some pollinators may decrease in abundance with increasing ag intensity, while other species may increase - retaining overall pollination services to crops.