Do not flip-flop variables to make them work in your #@%*^& ANOVA

I was reading a paper this morning. It included a perversion of a common statistical analysis that is fundamentally wrong, utterly unneccesary, and has an easy solution. This perversion, unfortunately, is also distressingly common. Inspired by O’Hara and Kotze’s 2010 paper Do Not Log-Transform Count Data, I now offer you this blog post/rant, entitled “Do not flip-flop variables to make them work in your #@%*^& ANOVA.”

What set me off was a statement about the presence or absence of a particular fish in alpine lakes (details have been blurred to protect the guilty):

Lakes containing [fish] were lower in elevation…than lakes without [fish].

This statement was followed by the results of a non-parametric ANOVA confirming that lakes with fish were at significantly lower elevations than lakes without them. Can you spot the problem here? This model implies–wait for it–that you can flatten mountain ranges by adding fish to their lakes. Who knew?

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Hvalreki

Hvalreki really should have been the title of my last post. It is my favorite Icelandic word, which I learned visiting that country almost five years ago. It translates to “windfall” in English, and, like that word, originally referred to a concrete event. But where a windfall is some fruit blown from the high branches, a hvalreki is much grander. It literally means “beached whale.”

Back in the old days in Iceland, a hvalreki really was a huge stroke of good luck. (“Olav, come quick! It’s a hvalreki! We can eat this winter!”) For some marine mammal acousticians, it still is. (“Ted! Come quick! It’s a hvalreki! We can ship its head to Utah to CT scan it for a finite-element model!”) But most of the time, these days, a hvalreki is more trouble than it is worth.

That was the opinion of the town of Brookhaven, New York, this past October, when a nearly 60-foot long fin whale (Balaenoptera physalus) washed up at Smith Point County Park on the south shore of Long Island. Continue reading

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Bone Conduction is Better than Pressure, or, Put your Whale in my Rocket Scanner

ResearchBlogging.org What do a decapitated whale, an x-ray scanner for solid-fuel rockets, and noise pollution have in common? This is not the start of a really weird joke–they are all major elements in a new paper by Ted Cranford and Petr Krysil, published this week in PLOS One. In a word, the first went through the second to help understand the impact of the third.

This was, believe it or not, a very logical plan for a research project. The modern ocean is increasingly filled with man-made noise, and some of them may be affecting marine mammals. Blue whales, for instance, have lowered the pitch of their songs over the past few decades, possibly in reaction to the rising volume of ship noise in the ocean. However, we don’t actually know how well many of the largest whales hear, because there is no way to measure it.

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No, New York, the forecast didn’t fail

Cliff Mass of the University of Washington has a good breakdown of the “failure” of meteorologists to correctly predict snowfall during this week’s storm. “Failure” gets the scare-quote treatment because the forecast wasn’t actually far off: models showed most of the snow falling in a relatively narrow band on the west side of the storm system, which is exactly what happened. The placement of that snow band, however, was uncertain–depending on which of the several major weather models you looked at, it fell somewhere between New Jersey and Cape Cod. Small differences in the storm’s track would mean large differences in snow over NYC.

That uncertainty was understood and acknowledged by NOAA and the National Weather Service. This graph hoisted from Mass’s blog post shows snow accumulation from Monday through Thursday, as predicted by a group of models (one line per forecast). Each model was started with slightly different initial conditions, or subtly different representations for how the atmosphere works. This is what atmospheric scientists cal an ensemble, and it gives a sense of the uncertainty in NYC’s forecast: the forecast accumulation varied from about 6 inches at the low end to almost 40 inches at the top.

New York snow forecasts

Predicted snow accumulation (in inches) in New York City from different models

For a variety of reasons, the reported forecasts skewed high. The NWS doesn’t do the best job it could communicating the uncertainty. TV news, all else equal, would rather have you freaked out and glued to your screen watching their parka-clad weatherman, and they report the forecast accordingly. I suspect a lot of it is just due to the fact that we aren’t that good at dealing with uncertainty.

And, of course, a lot of that “failure” can be traced to a certain attitude that mistakes a certain eight-mile island for the majority of the civilized universe. Out here in Suffolk County, the forecast was more or less right on, and we got hammered. The highest snowfalls in the state were at Orient Point, the tip of Long Island’s North Fork. There were no humans there to measure, but I suspect they were probably even higher at Great Gull Island.

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The Best Norwegian Horror Comedy that is Actually About Wildlife Biology You Will See This Year

Troll Hunter

The movie is called Troll Hunter.

I’d seen this movie a few years ago, but re-watched it this weekend and remembered how much I like it. It’s a found-footage Scenario. Thomas, Johanna, and Kalle are three Norwegian college students attempting to film a documentary about a man they think is a bear poacher. When they follow him into the woods, however, they discover that he is after much bigger game. Trolls.

Hans, the troll hunter, is not any kind of mythic hero. He is a long-time employee of the Norwegian Wildlife Board, working in a secret office called the TSS (Troll Security Service). When trolls break out of their territories and come too close to livestock or people, he has to trap or kill them. The usual weapons are powerful ultraviolet flash bulbs (trolls, of course, turn to stone in daylight). Hans is sick of it. The hours are terrible, the work is dangerous, and he doesn’t even get overtime.

Troll Hunter is alternately beautiful, scary, and bone-dry hilarious. Many of the jokes will be especially appreciated by anyone familiar with wildlife or fisheries management. Hans, and a sympathetic veterinarian named Hilde, explain troll biology and ecology with impossibly straight faces. Like many other large predators, trolls have a long lifespan and very low fecundity. Like many people who study large predators, Hans and Hilde argue passionately that the creatures are misunderstood. Human activity, and possibly climate change, are causing unpredictable changes in troll behavior. Conflicting demands by the public and different government offices make rational troll management nearly impossible.

Troll Hunter is on Netflix. I highly recommend it.

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Grad School is a Job

Grad school is a job. A conversation on Twitter tonight got me worked up about this point, but I’ve heard it questioned a number of times in my five years in postgraduate education. And it seems that each time I’ve heard it questioned, it has irked me just a little more.

Grad school in the sciences is a complicated transaction. You are given free access to the highest levels of academic education. You have the freedom to think freely and develop your ideas into original, often thrilling, research. You develop deep intellectual and personal bonds with your peers and mentors. You also work long hours doing highly skilled technical work for near-poverty wages, put your mental health at risk, expose yourself to personal disasters, and graduate trained for a job that may not even be there.

Grad school is not like a “normal” job. In theory, it is only part-time; a temporary training post or apprenticeship for better things later. But if you are being payed money and given health insurance, if you are required to perform certain work, and this arrangement lasts for somewhere between four years and a decade…I have news for you. You have a job.

I don’t think this is just semantic. Continue reading

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James Cameron, Back from the Deep

Deepsea Challenger new species

New species found during the Deepsea Challenger expedition in 2012. From the caption in Gallo et al. 2015: “A and B: Unknown Teuthidodrilus polychaete species from 1 km in the NBT. C. Large hadal ulmarid cnidarian observed at 8.2 km in the NBT. D. Crustacean (decapod or mysid) observed during submersible and baited lander deployments at 8.2 km in the NBT. E and F. Caymenostellid asteroids observed on wood debris and bones at 8.2 km in the NBT. G and H. Epidiid holothurians observed at 10.9 km in the MT CD. NBT = New Britain Trench, MT CD = Mariana Trench Challenger Deep.”


“Hi, I’m James Cameron. You may remember me from such blockbusters as Alien and Titanic. But today, I’m here to talk to you about something different: trends in deep-sea epibenthic biodiversity.”

Well, that’s how Troy McClure might say it. On Twitter this morning, Andrew Thaler drew my attention to a new publication by Natasha Gallo et al. in Deep Sea Research I, on biodiversity in several of the worlds deepest ocean trenches. The paper is notable for its sampling locations, its observations of novel species, and for its second author. That would be James Cameron, filmmaker and now ocean explorer.

I wrote, somewhat skeptically, about Cameron’s Deepsea Challenger expedition back in 2012. I’m now prepared to eat a few of those words. It’s great to see some of the results from that expedition showing up in the scientific literature, and that Cameron has apparently remained involved in the analysis and writing-up of those results after he got back to land.

However, a larger point still stands. I think it is admirable that Cameron is spending his $900 million net worth on research submersibles rather than gold-plated jet skis or something. But in the long run, well-intentioned billionaires are not a substitute for an equitable society with strong support for science as a public institution.

As a side note, Deepsea Challenger failed to beat the depth record set by the Trieste in 1960. By three meters—10,908 to 10,911. Call it a gentle karmic rebuke.

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Adventure Time on Great Gull Island

Particularly diligent readers of this blog may have noticed a couple of changes last week to its About and Research pages, for the first time since I finished my master’s in Seattle and moved to Long Island. In that time, I haven’t just been adjusting my GI tract from its former steady diet of pho, teriyaki, and coffee to a new, equally steady one of bagels, pizza, and “coffee.” I’ve been developing some new scientific interests as well, such as easing into the field of “movement ecology,” and adding “amateur radar engineering” to the list of skills I never thought I would posses.

This is all involved in my current research project, a study of seabird foraging behavior. There are a boatload of interesting theoretical questions related to the foraging behavior of marine predators, including seabirds. How do you search for small patches of food in a large, constantly moving ocean? Are others of your species collaborators or competitors in the search? Are there perhaps simple mathematical descriptions for the best search strategies? Is Lévy flight the one ring to rule them all, or is it a load of phenomenological crap?

To answer these questions, I went to Great Gull Island.


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Must it be Santa? A case study in Bayesian updating

Ah, Christmas eve. A magical day when we reflect on the deep questions. Is there anything more valuable than family togetherness? What is the true meaning of the season? Who is that strange man breaking into my house at 2:00 in the morning?

In an effort to answer at least one of these, I have prepared a short white paper on the problem of identifying Santa, from a Bayesian perspective. In particular, I take as my inspiration the song Must be Santa, performed in its perhaps definitive form by Bob Dylan on his album Christmas in the Heart (2009).

For those interested, I have made the paper and the code used to perform the analysis available in a GitHub repository. The paper, in PDF form, may be downloaded here.

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Πолярник


I learned a new word this week: полярник, polyarnik, which is Russian and translates roughly as “polar explorer.” This word, along with another set of interesting thoughts on dedication to science and the polar regions, comes from a beautiful photo essay in the New Yorker. In it, photographer Evgenia Arbugaeva shows us a glimpse of the life of Vyacheslav Korotki, a Russian meteorologist and polyarnik, whose job is to live, alone, for long stretches, on the shores of the Barents Sea, recording weather observations and relaying them to Moscow via a set of Soviet-era radios. If this is not dedication to science, I’m not sure what qualifies.

But according to Arbugaeva, “He doesn’t get lonely at all. He kind of disappears into tundra, into the snowstorms. he doesn’t have a sense of self the way most people do. It’s as if he were the wind, or the weather itself.”

Go check out all the photos.

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