Mistaken Identities

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I'm away this week so here's some fun/interesting stuff to check out:

• I'm reading "The Invention of Nature" by Andrea Wulf about Alexander von Humboldt, right now he's up to some shenanigans in the Amazon. He and his companion, Bonpland went to "discover" the link between the Orinoco and the Amazon River, only to find that it was already well-known to the people in the region. (Sort of reminds of the the "discovery" of Victoria Falls shown above* or Columbus "discovering" the Americas...) 

• Who was the first woman in space? Not Sally Ride (ride, Sally Ride!... sorry) but Valentina Tereshkova, who is pretty cool.

• All the buzz about the author of The Bell Curve** got me thinking again about the Mismeasure of Man, a book by Stephen Jay Gould (not Screamin' Jay Hawkins). Then somehow I got lost in the Wikipedia page about the Flynn Effect and the weird stats of IQ testing, which was fun.

• Here is yet another plum quote*** for you about confirmation bias, this time from Karl Popper (not of penguins fame).

“The method of science is the method of bold conjectures and ingenious and severe attempts to refute them.”



• Finally, I recently got creamed at chess and then I learned the word zugswang in a different context, which brought both satisfaction and fresh humiliation.

* In the stamp image it sort of looks like Livingstone is getting airlifted out of Victoria Falls by some heartier explorers, but the travel hammock was actually a common form of transport in the colonial era.

** The recent incident at Middlebury and its terrible repurcussions.

*** Cherry-picked, of course. Am I guilty of confirmation bias in my sampling of quotes about confirmation bias?

Moose "Attack"

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So I posted earlier about encounters with urban wildlife when I lived in Anchorage, and in the summers I would travel all over Alaska for fieldwork, encountering wildlife in their natural habitat. I had plenty of training on bear safety, and in addition to the firearm I was required to carry I would often blow a dog whistle to let bears know we were around, since they normally don't want anything to do with humans. I would use the whistle when we were going through dense brush or coming over a rise, thinking it would alert bears to our presence and help to avoid encounters. It might have even worked on the bears, but one day as we came over the top of a big hill we found ourselves close by two baby moose.

One guy on our team wanted to get some pictures of the baby moose, and I was standing there watching him, holding a shovel and a backpack full of gear. Then suddenly the other guy on the team took off running. I looked around, and there was a mama moose, hackles up, barrelling towards me and the other guy. We zigzagged through the trees but she was still coming at us, and I realized at some point that (1) I do have a firearm, and (2) I can't draw my firearm while I'm holding a shovel. So I chucked the shovel aside and we found a steep ravine to go down, the mama moose stopped at the top of it. Moose being fairly top-heavy with spindly legs, I think running down a steep slope was too big a risk for her, and at that point we were far enough away from the babies.

But she wasn't done yet. She went after the guy who ran away before we knew what was happening, and chased him quite a long way. I think he was a bit miffed that I hadn't taken a shot at the moose, but our lives hadn't been in danger. Plus, if we had a moose carcass near our fieldsite, that would attract bears. In the end everything was fine, but we lost a day of sampling because we never did find that darned shovel.

Coding Sins

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I loved this recent twitter exchange on coding sins, where programmers confessed to looking up code on the internet all the time. This was to protest job interviews in which candidates are asked to come up with some code off the top of their head, which is a bad idea for a number of reasons. The first is that the interview style probably doesn't correlate well with job performance, especially since there are now training courses to get you ready for obscure "whiteboard coding" interview questions. The second problem is how it impacts diversity in programming fields, because who do you think has plenty of time for cramming for these type of interviews?

Whiteboard coding interview questions haven't really been a problem for me as a research scientist or academic, but I found some comfort in knowing that I'm not the only one who continually needs to look stuff up when I'm coding. I think it's important that we're open about the stuff that we don't know, or more importantly, don't need to know to do our jobs.

Some have focused on the downsides of always having information at your fingertips, saying it makes us less likely to commit to memory information that we know that we can re-access easily. But as a scientist I'm always looking for things I can safely ignore. The scientific process is an onerous one when you try to account for everything. Parsimony, or the ability to explain something using the least number of inputs, is highly prioritized because each new variable means additional resources required to answer the question. When I'm coding I try to focus on the structure of what I'm writing and how to produce outputs that are compatible with other products, rather than memorizing syntax structures or complex functions.

I'm pretty open with my students that when they start out, they may be re-working other people's published code, and there's nothing wrong with it. Most often, nobody has done something exactly in the way you want to, so you'll need to tweak and sometimes even correct their code**. And in the process, you'll be learning to code yourself!

*Common stuff I need to look up: how to delete all but one variable in R, how to make a Python program executable from a bash shell, plotting commands in R...

** This generally works well, but it might lead to doing things in a way that isn't well-suited to your datatype, or doesn't produce output in a format that is most useful to you. In the beginning, the only thing that matters if it works and if it makes sense to you.

Sandra Brown, 1944-2017

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Sandra Brown passed away two weeks ago and I wanted to register somewhere my great admiration for her and the influence she had on my own career. Sandra was a formidable scientist who dedicated her life to understanding carbon storage in tropical forests, forming the basis of methods we use today and programs to protect forest carbon such as REDD+. She was the external committee member for my dissertation at Clark University, and I can confirm (as others have noted) she never suffered fools (or foolishness) lightly. I remember Sandra being firm on the divide between policy and science, saying that the role of science was only to provide information for the policy, never to direct it. Policy, she emphasized, is best made by policy-makers, and it's not only the science that drives it.

Our paths crossed several more times after that, while I was teaching at Mount Holyoke College and again at Leicester, where she was an external examiner on a viva last year. We got together for dinner while she was here and we spent several hours chatting. We walked by the Attenborough Arboretum and she quizzed me on Sir David versus Sir Richard and which one was the actor and which one the naturalist. I passed her test and she locked arms with me as we walked around the streets near College Court where she was staying. She told me about her childhood growing up in London (not spending hours galavanting through the forest unattended, for what it's worth). Sandra was concerned about improving the capacity of those in developing countries to quantify and manage their own carbon resources, and emphasized the importance of PhD programs like ours in doing so. I admit I feel a bit cheated not to have had another chance to see her, but I know that she felt very lucky to have made it to 72, having experienced a serious illness as a young woman. I believe it was her gratitude for life that made her such a tireless promoter of science and a great proselytizer on the importance of tropical forests in the global carbon budget.

Of Aironauts and Astronauts

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I'm always happy when I find an earlier example of remote sensing than I knew about previously. This week I found Baldwin's Airopaidia, a book about observing the earth from hot air balloon, accompanied by wonderful maps of the earth's surface, obscured in places by billowing clouds that lend them a dream-like quality. (Here's an incredibly detailed image from the book.) In his descriptions, Baldwin says "The Imagination itself was more than gratified; it was overwhelmed." [emphasis Baldwin's]. He was fascinated that the River Dee in Wales looks like a "broad red Line" from the air, but silver or black to those on the ground.

Ballooning apparently had a great impact on the way we think about landscapes, possibly something like the "blue marble" image of earth from space has on the imagination today. In the 19th century Gaspard-Felix Tournachon, known as Nadar, took the first photographs of the earth from a balloon (but the word "nadir" comes from the Arabic, not Mr "Tourne-a-Dart"). In the early 20th century, truly "remote" images of the earth were acquired, by cameras were mounted on carrier pigeons, automatically recording images every few seconds. In 1947, we had the first images of earth from space, in which the curvature of the planet was visible.

What's most interesting to me about these developments is what people wanted to see in remotely sensed images of the earth. Baldwin's Airopaidia is so interesting because it really seems motivated by curiosity and wonder. Technological advancements often came from some need, particularly military advancements. With the development of orthophotos, or images in which the perspective view has been removed, it was possible to address more practical concerns like estimating agricultural area or timber stocks. Amusement was a common motivation, and aerial imagery was often used in marketing areas for tourism. Using images of the earth to study ecology and the environment necessarily came later, after these disciplines emerged.

The Young Life Scientific

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I've often heard (most recently by Franz de Waal on The Life Scientific), that the early life of scientists should be one spent mostly in nature. David Attenborough extols the virtues of rural Leicestershire. E. O. Wilson has talked about his passion for hunting snakes and ants in Alabama. I also spent a lot of time as a kid unobserved, exploring the State Forest adjacent to my backyard.

I'm concerned, though, about putting too fine a point on the rural aspect of a childhood filled with wonder for the natural world. Societies are becoming ever more increasingly urban, and it makes a lot of sense in terms of how we access material goods and services. Given how much more resources rural life requires, having all our budding little scientists in the woods may be a luxury we can't realistically afford. There's often (but not always) an aspect of privilege to rural life as well, and we don't want science to be constrained to kids lucky enough to live in "the country".

So I worry about this particular story line, the endless hours spent unattended in nature, about the formation of a young scientist's mind. Even as I recognize how important it was to me, I think there are probably broader opportunities of living in more densely populated areas that benefit young scientists as much if not more (like accessible museums* and educational programs). And we shouldn't discount the green spaces in urban environments that can spark kids' interests in the natural world. After all, E. O. Wilson grew up around Mobile and D.C., and Attenborough in Leicester proper, right next to the sprawling Victoria Park. Stephen Jay Gould grew up in New York City and was awed by the T. Rex skeleton at the American Museum of Natural History**. I think there's hope for little urban dwellers yet.

*"musea"

**I was partial to the habitat dioramas*** myself

***"dioramae"

Zen Mind, First Year PhD Student's Mind

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I use lots of different products for working with geospatial data, and sometimes I even build my own. I try to teach my students not to be limited by the tools they have available to them, and I have them use a few different platforms so they have options for processing data. After all, once you know the basics of a few, you're not restricted by the limitations of just one. Some of my students would rather learn how to do everything in a single package, but to me that's just training them to use software rather than teaching them about remote sensing or quantitative analysis.

The truth is, learning software these days is pretty easy (and if it's not then the software's probably no good). User interfaces are ever-more intuitive, and there's so much documentation and so many forums ("fora" for the prescriptivists, but do you say "musea"? Nobody does that) for asking questions. What's hard is figuring out how to implement an appropriate method for answering a research question. Once you know that, everything else falls into place. Well, mostly.

In the beginning, it might take a long time to work out a basic operation. (I remember when ArcMap 10 first came out the buffer operation didn't work). And just because you've generated some output doesn't mean that it worked. There are lots of pitfalls along the way, and it takes time to learn what these are (datums are important, pay attention to units, file formats, is the origin in the upper left or the center of the pixel, capitalization for crying out loud). Simple problems can be difficult to solve if error messages don't tell you how to fix them. I remember I learned a lot as a PhD student just watching other students troubleshoot problems. After a while you'll establish a relationship with the data and software you tend to use, and you'll even learn to anticipate issues before they arise.

There's a big psychological component to learning something new, and I think it's mostly about trusting that there is a solution to the problem and that you can find it. A professor of mine once told me that if you start thinking the computer might be broken, you should walk away for a bit. I guess one of the benefits of spending so many years on this stuff is that I need fewer walks when I'm working on something difficult. Neuroplasiticity for the win!