I just read the excellently forward thinking year end editorial of the new journal Ideas in Ecology and Evolution. The editorial was written by Lonnie Aarssen and Christopher Lortie and is filled with Aarssen’s trademark,creative, outside the proverbial box, thinking.

I’m going to be participating in a Royal Society Discussion Meeting and they’ve asked us to advertise this to interested parties so I figured I’d just post about it here. The meeting is on Biological Diversity in a Changing World and (other than your humble narrator) has a pretty impressive list of speakers. Here are the key bits of information (straight from the meeting’s web page).

If you’re looking for a quantitatively oriented postdoc in ecology this position with Kiona Ogle is a great opportunity. I can’t vouch for her collaborator, but I’ve worked with Kiona and she is smart, has a good scientific philosophy, and is a patient & hard working collaborator – all goods signs for a postdoctoral mentor.

I had an interesting conversation with someone the other day that made me think I needed one last frequency distribution post in order to avoid causing some people to not move forward with addressing interesting questions. As a quantitative ecologist I spent a fair amount of time trying to figure out the best way to do things. In other words, I often want to know what the best method is available for answering a particular question.

This is a table of contents of sorts for five posts on the visualization, fitting, and comparison of frequency distributions. The goal of these posts is to expose ecologists to the ideas and language related to good statistical practices for addressing frequency distribution data. The focus is on simple distributions and likelihood methods.

Summary Likelihood, likelihood, likelihood (and maybe some other complicated approaches), but definitely not r^2 values from fitting regressions to binned data. A bit more nitty gritty detail In addition to causing issues with parameter estimation, binning based methods are also inappropriate when trying to determine which distribution provides the best fit to empirical data.

Summary Don’t bin you’re data and fit a regression. Don’t use the CDF and fit a regression. Use maximum likelihood or other statistically grounded approaches that can typically be looked up on Wikipedia. A bit more detail OK, so you’ve visualized your data and after playing around a bit you have an idea of what the basic functional form of the model is. Now you want to estimate the parameters.

If you don’t have an easily accessible RSS feed available (and by easily accessible I mean in the browser’s address bar on your journal’s main page) for your journal’s Table of Contents (TOCs), there is a certain class of readers who will not keep track of you TOCs.

I read a handful of experimental ecology papers the other day. I liked some of them and didn’t like some of them. It wasn’t that there was anything inherently wrong with the ones I didn’t like, they just didn’t fit in with my world view.

Within the small community of ecologist bloggers much has been of the lack of blogging (and other odd pursuits like twittering) among ecologists (this is, afterall, EEB & Flow’s raison d’etre), and I recently read over at academHacK that “in the future [academics] can be online or be irrelevant”. So, this semester I did what I could to get some future ecologists blogging.