Thursday, October 30, 2008


In science, as in most anything, it pays to know your strengths and weaknesses.

I am about as good as anyone I have known at understanding, remembering, integrating and evaluating biological concepts. I am terrible at calculus. I am very good at recruiting, evaluating and training assistants. I am hopelessly slow at learning programming. I have very steady hands for lab work and a hip that is bad enough to keep me from doing much field work. I am a gifted improviser and a mediocre follower of protocols. I am the king of scrounging and am pretty good at applying for funding, but I struggle with remembering to do the accounting or keeping track of receipts. I am a great teacher but a disinterested disciplinarian. I am unrivaled in my ability to start research projects, but need serious improvement in my ability to finish them. I have great fun with ideas but no fun with spelling. I collaborate well but self-motivate poorly. I am good at being blunt and bad at being not-blunt. I am a good scientist, but need improvement as an academic.

Saturday, October 18, 2008

What I've been working on

Here is the last bit of my post-doc fellowship application:

Summary and Conclusion:
Evolutionary Biodemography has focused on explaining late-life mortality patterns and overall longevity. The evolutionary basis of early-life mortality has been studied more rarely and less systematically. My proposal boils down to four basic steps intended to firmly establish the field of early-life evolutionary biodemography:
1. Mathematically define and parameterize the age specific mortality patterns that characterize Human-like Early-life Mortality (HEM).
2. Compile, review and organize those evolutionary hypotheses potentially explaining HEM.
3. Use these hypotheses to predict life-history traits that may be necessary causative factors of HEM, and thereby predict which taxonomic groups are not subject to HEM.
4. Gather data to determine in what species or populations, if any, HEM does not occur, thereby testing my collection of evolutionary hypotheses.
Early life mortality has a tremendous effect on a wide range of populations, and our failure to date to understand its evolutionary basis is a major gap in our understanding of both evolution and demography. Working at MPIDR, I will begin to fill that gap.

Saturday, October 11, 2008

Writing to the audience

One of the most basic pragmatic points of writing is tailoring the language one uses to one's intended audience. I would use different words in a text book for first graders than in a paper sent to a scientific journal, even if the exact same concept was being communicated. I have to estimate the assumptions, interests, background knowledge, tolerance for jargon and a host of other parameters about my readers in order to write in the most useful voice and tone.

This becomes a problem when I don't know who my audience is. I am applying for a DAAD research grant, and while I know I need to submit four copies of my proposal, I have no information on the four people who will be reviewing it. They may be four evolutionary biologists, in which case I would like to write a fairly detailed and technical proposal, using all the appropriate terminology, so as to show that I know my topic and have detailed plans. They may be four non-biologists, but still natural scientists. They may be social-scientists, or a mix of academics from all fields. They may be (although I doubt it) four German first-graders, in which case I would write a very different proposal. But as I don't know who they are, I have been trying to write a proposal which is appropriate to all of these groups, and finding it nearly impossible. How does one write an audience-neutral grant application?

Friday, October 10, 2008

All global warming is local

I got home from the lab late last night and turned on NPR. There was a voice I instantly recognized, my major professor, and the director of the MVZ, Craig Moritz. What, I wondered, was Craig doing in my radio at this late hour? Being interviewed by All Things Considered for this piece on the effects of climate change on the wildlife of Yosemite National Park.
Mean monthly minimum temperatures in Yosemite have risen by 6 degrees Fahrenheit in the hundred years since the MVZ's first director, Joseph Grinnell, surveyed the wildlife there. Apparently in response, many of the wildlife species in the park have moved their upper and lower limits thousands of feet higher than they were.

The project is described in great detail here, and a subset of the Yosemite data were just published in Science. I wasn't involved in this work, in case you were wondering.

Thursday, October 09, 2008

Compresed Timeline

The Max Planck Society is a network of research institutes, mostly but not entirely in Germany. Many people consider it, to be the world's leading non-university research organization. The member institutes are more or less autonomous in terms of planning and executing research, as far as I understand, but all of them have the reputation for world-leading excellence.

A couple of years ago, at a conference on aging I had the pleasure of meeting the Executive Director of the Max Planck Institute for Demographic Research, Jim Vaupel. At the time, he and my professors, Ron Lee, discussed the possibility of me coming to MPIDR at some point. I was excited by the prospect. Here at Berkeley there is effectively no one outside of Ron's lab group who thinks much about the kinds of questions I do, while MPIDR has a whole Evolutionary Biodemography Lab, at which they think about and work on pretty much everything I do, plus a lot more.
But then I went off to PNG, and then I was injured, and pretty soon I figured the opportunity had passed. But then I got an email announcing that there was a fellowship available through the German Academic Exchange Service (better known by its German acronym, DAAD, for North American researchers to come work in Germany if they had the invitation of a German institution. The email conversation that followed was suprisingly short, spanning little more than 24 hours, and completely reorganized my timeline for finishing grad school. If I may paraphrase, it went something like this:

Me to Ron: Should I apply for a DAAD fellowship to work at MPIDR.
Ron to me: Do you want me to ask them?
Me: Yes, thank you.
Ron to Jim Vaupel: Dan is an excellent young biologist, should he apply for a DAAD fellowship to come work there?
Jim to Ron (to me): Yes, he should apply, but even if he doesn't get the fellowship he should come here as soon as is convenient, and we can support him.

Just like that, no application, no interview, I had a desirable post-doctoral position lined up at a time when the economy is tanking and most of my peers are wondering if there will be any positions for them at all. My deliberations consisted of describing the situation to my wife to make sure she didn't mind spending some time on the Baltic, and emailing Dr. Vaupel to make sure I understood him properly.

What this means for my grad-school timeline is that instead of 16 to 21 months, I have eight to ten months to finish. I was thinking I would finish December of 2009 or May of 2010. After the offer from MPIDR, I thought I would have to finish by August of 2009. Afer talking to my major proffessor today, it is clear I need to be pretty much done by May of 2009.

My department's commencment is May 23rd 2009, and I plan to walk then, if at all possible. I won't actually be finished at that point, but I will be finished enough to convince my faculty persons that I can file my disertation before the end of summer. My wife's graduation from UC Davis is mid-June 2009. That summer I will finish my dissertation, then we will pack up our lives, take the cat's to my sister's house, and fly to Germany.

That seems like a lot to accomplish in one year.


Student Researchers

I've added a Student Researcher section to my website, so all my students can have research sites. There will be more in the coming days.

Sunday, October 05, 2008

I wiggle my eyebrows ~1000 times a day.

I spend about eight hours a day in front of a microscope. I generally have a student on either side of me. I look at the first rotifer in our population and report how many eggs and juveniles it has, whether it is alive, and anything else notable about it. "Two forty six dash bee five is alive has three eggs, two juveniles and extended foot syndrome. The largest juvenile has one egg."
The student on my left, at the computer, enters all of this into the spreadsheet and tells me what to do with the juveniles, based on our established culling rules. "Put the biggest juvi in two forty eight dash a one, cull the other two."
I pick up the mom rotifer in a specially bent glass pipette and wiggle my eyebrows such that my glasses slide off my forehead and onto my nose so that I can see the student to my right. She uses her pipette to point at the hole where the rotifer is going. I squeeze the bulb at the end of my pipette to eject the rotifer into that hole. She looks through a second microscope to make sure the rotifer is actually there. I push my glasses back up, look through my microscope, pick up the juvenile, wiggle my eyebrows again, move it to the well where it needs to go, then move on. All of this takes 15 seconds to one minute, depending on the complexity and which students are working with me. We repeat this process 450 more times each day. By the end of each day we have gathered more demographic data than many field studies of long-lived vertebrates do in several decades. By the end of a month we can see significant evolutionary changes based on the selective pressures we apply through our decisions about who to cull and how much to feed them. It is not glamorous, but it is effective.