Happy Half Tau Day to everyone! What’s that, you say? It’s Pi Day? Whatever. π is wrong. Need convincing? See the brilliant video by Vi Hart below and visit The Tau Manifesto.
So go out there, and celebrate the fact that you’re halfway to the day where you can make 2 Pi!
(And don’t worry, you should still make some π today! It’s delicious!)
I’m having one of those days. One of those “I have a meeting that will finalize the analyses for a paper, let’s just check that ONE thing that didn’t matter in early versions of this model, so, it shouldn’t matter now, and OMGWTFBBQ everything changed!” kinds of days. Well, OK, not everything – just the new piece of the story that intrigued me the most because it was so delightfully intuitive. It’s made me feel a little blue. Well, a lot blue. So, fingers flying across the keyboard to fit new models, I flipped on some Muddy Waters. At the same time Miriam G suggested the Low Down Poor Abused Data Blues. While I’m no Robert Johnson, Muddy Waters, or BB King, clearly, this must be done. I’ve got a first verse. I’m welcome to contributions:
This is me. Right now. Except replace the guitar with a laptop furiously churning through R code.
Low Down Poor Abused Data Blues
Oh my data’s got autocorrelation,
eats up my treatment effect.
Oh my data’s got autocorrelation,
eats up my treatment effect.
But the decrease in sample size, it makes my analysis such a wreck.
Science is a giant family. Each Professor gives “birth” to a litter of PhD students over time, many of whom go on to have their own students, who have their own students, and so on and so forth ad infinitum.
While all of us know our academic parent (right?), at least some of our sciblings (depending on the age of the lab), and usually our academic grandparent, what about our great-grandparent? Or great-great-grandparent. Can my aacadmic lineage be traced back to Darwin? Or Linneaus? Indeed, something like 40% of mathematicians can indeed trace themselves back to Leibniz.
Not it’s time for Marine Ecologists to do the same.
Mary O’Connor has graciously setup a Marine Ecology Family Tree over at the wonderful academictree.org. The site endeavours to see how all academic geneologies end up connecting. Is your discipline not there? Contact the admins. But if you’re a marine ecologist, go there now, login, and fill in your info! Let’s see how many degrees we’re separated by!
(also, as more info is filled in, I’ll update my tree on the right)
I love modeling! I love modeling! Modeling will solve everything!
Let’s model the spatial distribution of Bigfoot!
WAIT, WHAT?!
Figure 1 from the paper. Foots denote sighting of Sasquatch footprints. Circles for just visual/auditory sightings. I ask, how does one know what Bigfoot sounds like?
Yes, it sounds silly, but in the current issue of the Journal of Biogegraphy, Lozier et al give us their stunning contribution Predicting the distribution of Sasquatch in western North America: anything goes with ecological niche modelling. Finally, all will be revealed. And for those wondering:
Sasquatch belongs to a large primate lineage descended from the extinct Asian species Gigantopithicus blacki, but see Milinkovich et al. (2004) and Coltman & Davis (2005) for phylogenetic analyses indicating possible membership in the ungulate clade.
They do this to prove a point – that Ecological Niche Models for determining species ranges are amazing – invaluable conservation tools, really. But if the taxonomy on the data that goes into them are shoddy (like, say, calling a Black Bear a Sasquatch), the results will be, well, interesting.
They use data on sightings (see Fig. 1 above) from… the Bigfoot Field Research Organization
and then used the latest and greatest in Ecological Niche Modeling to determine, given environmental parameters, just where does Bigfoot live? And, under current climate change scenarios, where might we find Sasquatch in the future?
So cryptozoologists take note! Here is a veritable treasure trove of information as to where to place your next tripwire camera!
In fairness, the authors use this dubious analysis to point out that, when we have a record of species occurrences that seem tidy and orderly, we often don’t question their taxonomic validity. The output of these models, vital to some conservation efforts, will only be as good as their input. Indeed, in this case, the authors find striking overlap with the (far less frequently observed) Black Bear (yes, people report sightings of Sasquatch more than that of Black Bears). It’s a real problem, and the assessment of data uncertainty is a real pressing issue for any method that attempts to draw inference from sparse data.
But, really, in the end, this is an Ig-Nobel award winner in the making. Bravo.
Lozier, J., Aniello, P., & Hickerson, M. (2009). Predicting the distribution of Sasquatch in western North America: anything goes with ecological niche modelling Journal of Biogeography DOI: 10.1111/j.1365-2699.2009.02152.x