In search of great ideas

Not surprisingly, I'm still on the hunt for a great thesis topic. My advisor and I have been meeting weekly, and while he says that I've got a couple of established projects that could become solid PhD theses, it's early enough yet in my graduate experience that I can still spend time challenging myself in search of a super-shiny topic. So we've been putting a good bit of thought into what makes particular topics time appropriate, influential, etc, such that they result in classic, highly cited papers. Good things to think about, but not always entirely obvious.

The last week or so was dubbed ' 70's week ', and we've been hitting up a bunch of classic papers from the 70's. Some of them are terrible, some of them are pretty neat. Mostly what I've been struck by however, is the realization that a lot of the topics that turn up in weekly lab meetings and paper discussions and over lunch at the cafeteria - they're not really 'new' hot topics to the extent that I usually consider them. I've been surprised by just how much these 'old' papers are really discussing the same ideas that we still wrestle with today in ecology and evolution. Sure their discussions tend to be a little more qualitative and verbal than quantitative, and they aren't using all of the powerful new methods and resources that have been developed more recently. But a lot of the ideas are there.

Maybe I shouldn't be so surprised - lots of smart people have been (and are) ecologists. Wading into the literature though has been a good experience. I am both comforted and somewhat stymied by these realizations though - on the one hand, it's good to realize that even though a lot of the really foundational ideas in our discipline have been thought out and written about for decades, people are still making a living and doing good work to flesh out these ideas without having to come up with paradigm shaking new concepts. On the other hand, while I'm challenging myself to try to come up with a super shiny new idea, it's intimidating to realize how much has already been though out/discovered, and the extent to which most of what is done these days is 'just' filling in the blanks.

Ok, back to the late 70's....

Where do classics come from?

Quotes from R. McIntosh, "Citation Classics of Ecology"

"A less professional recognition was given to a Scottish landlady who fed J. H. Connell very economically, and stretched out his G. I. Bill funds. [...] Collateral stimuli were attributed by some authors to liquid refreshments ranging from soup to bitters and to the cup that cheers without inebriating, tea."

"Several [Ecological Classics] were explicitly considerations or tests of theory, and some urged the utility of theory as a guide in their research. Paul Dayton, however, among others, had reservations. He commented, 'Ecology often seems dominated by theoretical bandwagons driven by charismatic mathematicians; lost to many is the realization that good ecology rests on a foundation of solid natural history...'"

Grad students are people...

"Initial premise: Graduate Students are People.

Graduate students can be described by models identifying their many functional and structural roles in research labs, field projects, classrooms, and budgets. However, the most encompassing model of the nature of a graduate student is the humanistic model, encompassing submodels of both physical and psychological well-being. Given this premise, a long list of corollaries can be developed. [...] "

- D. Binkley, 1988. Some advice for graduate advisors. Bulletin of the Ecological Society of America, 69 (1): 10-13.

Unknowable

"A wonderful fact to reflect upon, that every human creature is constituted to be that profound secret and mystery to every other. A solemn consideration, when I enter a great city by night, that every one of those darkly clustered houses encloses its own secret; that every room in every one of them encloses its own secret; that every breathing heart in the hundreds of thousands of breasts there, is, in some of its imaginings, a secret to the heart nearest it! Something of the awfulness, even of Death itself, is referable to this. No more can I turn the leaves of this dear book that I loved, and vainly hope in time to read it all. No more can I look into the depths of this unfathomable water, wherein, as momentary lights glance into it, I have had glimpses of buried treasure and other things submerged. It was appointed that the book should shut with a spring, for ever and for ever, when I had read but a page. It was appointed that the water should be locked in an eternal frost when the light was playing on its surface, and I stood in ignorance on the shore. My friend is dead, my neighbour is dead, my love, the darling of my soul, is dead; it is the inexorable consolidation and perpetuation of the secret that was always that individuality, and which I shall carry in mind to my life's end. In any of the burial-places of this city through which I pass, is there a sleeper more inscrutable than its busy inhabitants are, in their innermost personality, to me, or than I am to them?"

- Charles Dickens, "A Tale of Two Cities"

Changing structure of scientific inquiry

At ESA the other week (this post got slowed down by my now traditional post ESA cold), I attended an intriguing symposium on Ecoinformatics that led my thoughts in an interesting direction. Ecoinformatics (short for Ecological informatics) is, broadly, concerned with solving the technological challenges of making the increasing wealth of ecological data broadly available, accessible, and analyzable (?). In the symposium, several presentations were given on different efforts to unite existing ecological databases (DataONE) and to create a system for authors to submit datasets related to their publications (Dryad - which currently focuses on evolutionary biology, not ecology specifically).

This second project I find particularly exciting. There are many challenges that need to be worked out to make it a reality, but I really just want to comment on a few of the things that I found especially cool:

1) Authors will be expected to submit properly formatted and annotated data related to their papers for archival at the time they submit papers for publication. If done well, with an appropriate system, this means lots of cool data available to the scientific community allowing many interesting synthesis and modeling projects, and potentially fostering many cool collaborations. (Obviously lots of interesting challenges involving appropriate citations, etc, embargoing sensitive data or allowing authors more time to publish follow up papers, infrastructure issues, funding, etc.)

2) I was amused thinking about how this would mark a further step in the Ford-ification of Science; already within big lab groups, PI's have Big Ideas and write grants and get funding that supports various post docs and grad students and technicians who experiment, collect data, and analyze it. Open access data sets could compartmentalize science even more, making it totally possible to do great science and synthesis without ever collecting data. Fascinating to think about. Specialization can bring rewards in terms of skill levels at particular tasks, and increased efficiency, along with new challenges, such as making sure that appropriate data are gathered, and that communication between roles is good.

Anyways; fun to think about.

Back from ESA

Just returned from an intense week of ecology thanks to the ESA's annual conference in Pittsburgh. It was a stimulating and eventful meeting for me, and has me motivated to start blogging again occasionally. As soon as I unpack, do laundry, water my plants, attempt to rescue my garden besieged with weeds, make dinner.........

Day 3 update: the magical land of spring-break campus

Ok, so today went a little differently than expected...

I read in the morning as usual for this week, but did so at a coffee shop in near campus instead of at home, to mix things up and to get some caffeine into the system. Spring break is a marvelous thing - I didn't have to wait in line at the shop, I didn't have to fight for a table, and I didn't have to wear headphones to drown out the usual crowd of students and others. I got a seat near the fire place AND the window. Magical. Walking around campus is a lot more fun too - fewer cars, fewer maniacal bikers trying to run me over, and fewer slow walkers to dodge (yeah, I'm one of those fast-walking types). The only downside is that the library closes early. Ooops. Guess I'll have to wait another day before delving into the catacombs of hierarchy theory.

Mid-day I showed up at one of my reading groups (having not been prepared enough last week to imply upcoming absence). But it was cool - one of the better little interactions I've had with such groups - everyone was tasked with bringing a single slide containing graphs/analysis of data they've been working on. I think I was the only one that rigidly followed the directions, managing to get 5 graphs intelligibly on a powerpoint slide. It was cool though to hear really succinct tidbits about a real diversity of different projects in progress - I feel like I learned something interesting from each one, which is more than I usually expect.

However, the downside to all of this is that, in addition to taking me away from my reclusive reading for a while, it also got me thinking about my current data analysis project again... and I had new ideas that I couldn't wait to try out. It's possible that I spent pretty much all afternoon tinkering with R code. But my new stuff works decently well (still a bit kloodgy) and I think it will save me a lot of time in the coming weeks, as I've been able to generalize a function so that I can give it in short notation the statistical model that I want to fit, and it will go off and do it for me, without my having to write out explicitly what I want each time with minor variations and new names. Pretty exciting. Now if only I could do it more elegantly.... hmmmm

BEWARE: Caution my dear readers; for those of you not already hooked... programming can get really really addictive. It has a way of inspiring the feeling that the breakthrough you've been waiting for is just around the corner, and then holding out success on you for hours or days on end. In this case, I've got a general formula now that lets me combine multiple linear regression and multiple logistic regression on two different distributions combined in a mixture distribution and fit in one fell swoop by maximum likelihood analysis. Fear me.

Oh, and it makes pretty graphs too.

Tomorrow I will strengthen my resolve and return to another day of reading. It's supposed to be rainy too, so I'll be less inclined to frolic around campus pretending that I don't have to share it with anyone. I'm off to delete a few dozen emails before bed.

Theo out.