I have spent most of my time recently writing papers for publication, and I have come to a realization. It is one of those realizations where I knew it all along, but had forgotten, or had never considered how important it was. What I realized is this: every paper should have a point, expressible in a sentence or two, and everything in the paper should be relevant to understanding and evaluating that point. Analyze the data, read the literature, analyze the data some more, but before one actually starts writing, one should have a pretty good sense of what one's point is. I've taken to making the point of the paper also be the title of the paper. Here are three titles I've written recently:
• Post-fertile survival in comparative perspective: humans are qualitatively different
• Behavioral biologists don't agree on what constitutes behavior
• The grandmother hypothesis is supported, but only in humans
I don't know that these will be the titles these papers actually have when they get published, but they serve to remind me that there is a point I am trying to make, and I'm not just spilling out everything that I've done or found out or thought. In many cases the point changes somewhat once I start writing the paper, and then I change the title. But in those cases where I start writing not really having a point in mind, I end up in a morass, casting about, writing several pages and then deleting them because they don't really say anything, the bits don't go together into a single logical argument.
The null assumption of many paper writers is that one starts writing at the beginning of the paper, writes until one gets to the end, then stops. In some forms of writing, (e.g. writing a short essay for one's blog) this is probably the most reasonable approach. I have heard it suggested that in writing a scientific paper, one should write the sections in revers order. Compile the list of references one needs to mention, write the conclusion, then the discussion, the results, the methods, the intro and only very last the abstract. I am think that what works well for me in creating a first draft is more like this: Reference, title, abstract, decide what journal I hope to submit to, methods, results, discussion, conclusion, add more references and then re-write the abstract and then write the introduction last, putting in only that information necessary for readers to understand the rest of the paper. These are arranged into the document in the order the journal demands, but I write them in the order that I feel leads to an efficient writing process. Of course I then end up going back and reading it in the final order to make sure the document does not read as disjointed.
Now that I've come to this realization, and begun to implement it in my writing, I need to also impress it upon my students. I have more than one very talented student struggling somewhat in writing a paper for publication, and in some cases I think what the papers lack most is a clear and central point. We need to rectify that. New rule for the lab: decide what your point is first, then continue writing after that.
Tuesday, March 17, 2009
Saturday, March 14, 2009
A little praise goes a long way
I gave a draft to one of my mentors, and it came back covered in red. Comments, suggested edits, deletions, additions, objections, pointing out "wordiness," "bogging down" and opportunities to make it "more fun to read." However the comments start with the statement, "this is a very valuable paper, and I expect it will be widely cited."
A teaspoon of sugar does in fact make the medicine go down in the most delightful way.
A teaspoon of sugar does in fact make the medicine go down in the most delightful way.
Tuesday, March 10, 2009
Academic constipation
The NYTimes has a recent article about the current academic job market. In two words, it sucks. Professors who thought they could afford to retire are staying on, so positions aren't opening. Even when they do retire, hiring freezes are leaving their positions vacant until the economy improves, so post-doctoral researchers aren't likely to find a tenure-track position, and remain in underpaid temporary jobs. This means there are extremely few positions (as faculty or post-docs) for recent grad-students, and the usual routes out of academia, industry jobs, also aren't available. But while the routes out for grad-students are limited, recent college graduates who can't find real jobs are apply to graduate programs in record numbers.
While the situation is bleaker for the humanities, which have long been in decline economically, the scientific community in the US is keenly aware that however this turns out will have effects that will be felt for generations. The closest comparison I can make is the tremendous expansion of enrollment in colleges in the 1960s and '70s. As the students flooded in, colleges hired large numbers of professors right out of grad school. By the 1980s there were extremely few positions opening up, almost every professor had been hired in the previous two decades, and there were almost no retirements. A whole generation of academics had almost no chance of finding a professorship. I know several people of that era whose careers were permanently put onto alternate tracks because they simply couldn't find a professorship. Then, just in the last decade, that flood of professors hired to teach the baby-boomers have been retiring in droves, and many people were expecting a new wave of hires. More than one person has told me, "When I finished grad school, there were no jobs. When you finish, there will be openings everywhere." Now, given the economy into which I am graduating, I feel lucky to be in a sub-field that has some post-doctoral positions for a few years. Perhaps in three or four years universities will start filling all those vacant positions, and a new wave of young faculty, hopefully including me, will be an impediment to the career aspirations of our younger colleagues.
While the situation is bleaker for the humanities, which have long been in decline economically, the scientific community in the US is keenly aware that however this turns out will have effects that will be felt for generations. The closest comparison I can make is the tremendous expansion of enrollment in colleges in the 1960s and '70s. As the students flooded in, colleges hired large numbers of professors right out of grad school. By the 1980s there were extremely few positions opening up, almost every professor had been hired in the previous two decades, and there were almost no retirements. A whole generation of academics had almost no chance of finding a professorship. I know several people of that era whose careers were permanently put onto alternate tracks because they simply couldn't find a professorship. Then, just in the last decade, that flood of professors hired to teach the baby-boomers have been retiring in droves, and many people were expecting a new wave of hires. More than one person has told me, "When I finished grad school, there were no jobs. When you finish, there will be openings everywhere." Now, given the economy into which I am graduating, I feel lucky to be in a sub-field that has some post-doctoral positions for a few years. Perhaps in three or four years universities will start filling all those vacant positions, and a new wave of young faculty, hopefully including me, will be an impediment to the career aspirations of our younger colleagues.
Sunday, March 01, 2009
Evolutionary challenges to gene engeneering a better human
My friend Terry is a bioengineer, as well as a part time futurist. Much of what people in his field work on (as judged by what Terry talks about when he puts on his futurist hat and has a couple of glasses of wine) is thinking about how to modify the human genome to increase our lifespan and healthspan (I just made up the word healthspan, but I bet someone out there is already using it). Much of my work is to understand how and why we evolved to have the lifespan and healthspan we currently do. My understanding of my work is not promising to my understanding of this part of Terry's colleagues' work. In my view, bioengineering a much longer lived human will be extraordinarily difficult for several reasons.
First, we have a great many systems that seem to fail at about the same age, and there are good evolutionary reasons why this should be. Why bother building a femur that last longer than your heart, or your brain, or your pancreas? So to engineer a much longer-lived human, one has to be prepared to make a large number of changes to see a small effect. Terry counters that there will inevitably be some low-hanging fruit, and I concede this point. Simply by editing out some of the purely harmful mutations in the human gene-pool, we can probably extend average life span by a few months or maybe a couple of years. But because so many things fail at similar ages, no one or two or 100 changes could give us healthy 150 year olds.
Second, many individual genes have an enormous number of different effects in a wide range of systems, tissues and traits. When a gene has more than one effect, this is called pleiotropy, and we are chock full of pleiotropies, most of which we don't yet know about or understand. DNA is not like a blueprint, where you can just erase one wall, re-route a few wires, and draw in a new door. It is more like a vastly sprawling and disorganized system of interacting computer applications, add-ons, duplicates, and operating systems (only without any comprehensible order, annotation or easily understood compartmentalization). Something which functions as part of an unnecessary application may also be used in several disparate parts of the operating system. Modify a line of code and all sorts of unintended things can happen. Evolution has fine-tuned this system of interactions through millions of generations of trial and error, with emphasis on the error. Our best computer simulations are barely able to comprehend the folding of a single amino acid string into a protein, let alone a whole cell or organ or human, and animal models only go so far. So the process to modify evolution's optimization would not be fun, fast or clean. Our various bits are tuned to work together, and most potential single modifications can only move us away from that local optimum.
Terry counters that in many cases what evolution was tuning was utility in the form of health/strength/life vs. cost in the form of calories. A large part of the theory of life-history evolution is based on models where developing organisms have limited nutritional resources to invest in important tasks like growing, healing and reproducing. If one assumes unlimited calories are available, one can theoretically grow, reproduce and heal maximally all at the same time. And in Terry's view (which I can't help but see the wisdom in) anyone who can afford to play with the human genome can also afford plenty of potato chips. For the relevant population, calories are no longer limiting. In fact, we go out of our way to burn extra calories now. Spending calories lavishly to buy a few extra years of life or more garish secondary sexual traits is a win-win. The bioengineers of the future will have the advantage over evolution, because they won't have to worry about one of the main constraints evolution was dealing with, calorie restriction. So we may have to change a few things at once to make it all work well together, but we can do that. We can, in my imagining of Terry's thinking, reengineer the organism to its new environment.
It occurred to me last night that there is third, bigger and more insurmountable barrier to re-tuning. One that is not just a technological limitation: Breeding. Humans have been known to breed with each other, and in doing so they mix their genomes. You have half the genome of your biological father and half the genome of your biological mother. Imagine if your uber-mench father had a carefully altered suite of genes, and your mother was a good old-fashioned non-GMO woman. What do you get? You get half a carefully altered genome mixed with genes they were never designed to interact with. Chances are, you have all sorts of wacky health problems, and greatly reduced longevity. It would be like taking half the code of Mac OS 9 and half the code of OS X and expecting a stable operating system.
This means that every change and group of changes would have to be carefully designed to be back-compatible. The alternatives are gene altering the entire human population (which would never ever ever ever work (and I very rarely use that many "ever"s in a row)) or engineering the longevous new humans to be incapable of interbreeding with the old model. They'd have to start by separating off one population as a seperate species, Homo terrii, and only thereafter get serious about reengineering.
So suppose the engineers decide they want to make everything back compatible?
I'm not convinced this would work either. Most mutations are bad for you not only because they break a piece of the system, but because they make a new piece that doesn't work with what is already there. Requiring back compatibility means we have to have every piece work with not only the old set of genes and the new set of genes, but every possible combination of old and new. Evolution, largely free from constraints of time, funding and ethics, accomplishes this by letting those individuals who have bad combinations die out until there are very few harmful combinations possible. To extend the computer code analogy, this would be like trying to write OS XI in such a way that if one blended the code with OS X, it would still work. It is possible to do, but XI would end up looking an awful lot like X, too similar to be more than a service update.
This leaves only the option of creating a population incapable of breeding with normal humans and altering their genes extensively to try to overcome a large number of age-limiting factors at once. Again my understanding of evolution suggests a major difficulty. To do this successfully, one would need a large population all gene-altered simultaneously, to avoid inbreeding effects. One can't start a new population with just a few individuals and expect that species to have a decent chance of surviving well. Even if the species does make it through, there is likely to be an extended period of decreased lifespan and healthspan while the inbreeding kinks work themselves out and the population increases in size and genetic diversity.
Without doubting that bioengineers will continue to make things that seem impossible become projects of undergraduates, I consider it highly unlikely they will achieve any very significant advances in human longevity in the next few decades.
(NOTE: I sent this to Terry for comment or objection some time ago but he has been busy with 'job' and 'editing the book.' I take his failure to offer a substantive reply as evidence that in some basement deep under campus, his department is already failing to build an immortal human.)
First, we have a great many systems that seem to fail at about the same age, and there are good evolutionary reasons why this should be. Why bother building a femur that last longer than your heart, or your brain, or your pancreas? So to engineer a much longer-lived human, one has to be prepared to make a large number of changes to see a small effect. Terry counters that there will inevitably be some low-hanging fruit, and I concede this point. Simply by editing out some of the purely harmful mutations in the human gene-pool, we can probably extend average life span by a few months or maybe a couple of years. But because so many things fail at similar ages, no one or two or 100 changes could give us healthy 150 year olds.
Second, many individual genes have an enormous number of different effects in a wide range of systems, tissues and traits. When a gene has more than one effect, this is called pleiotropy, and we are chock full of pleiotropies, most of which we don't yet know about or understand. DNA is not like a blueprint, where you can just erase one wall, re-route a few wires, and draw in a new door. It is more like a vastly sprawling and disorganized system of interacting computer applications, add-ons, duplicates, and operating systems (only without any comprehensible order, annotation or easily understood compartmentalization). Something which functions as part of an unnecessary application may also be used in several disparate parts of the operating system. Modify a line of code and all sorts of unintended things can happen. Evolution has fine-tuned this system of interactions through millions of generations of trial and error, with emphasis on the error. Our best computer simulations are barely able to comprehend the folding of a single amino acid string into a protein, let alone a whole cell or organ or human, and animal models only go so far. So the process to modify evolution's optimization would not be fun, fast or clean. Our various bits are tuned to work together, and most potential single modifications can only move us away from that local optimum.
Terry counters that in many cases what evolution was tuning was utility in the form of health/strength/life vs. cost in the form of calories. A large part of the theory of life-history evolution is based on models where developing organisms have limited nutritional resources to invest in important tasks like growing, healing and reproducing. If one assumes unlimited calories are available, one can theoretically grow, reproduce and heal maximally all at the same time. And in Terry's view (which I can't help but see the wisdom in) anyone who can afford to play with the human genome can also afford plenty of potato chips. For the relevant population, calories are no longer limiting. In fact, we go out of our way to burn extra calories now. Spending calories lavishly to buy a few extra years of life or more garish secondary sexual traits is a win-win. The bioengineers of the future will have the advantage over evolution, because they won't have to worry about one of the main constraints evolution was dealing with, calorie restriction. So we may have to change a few things at once to make it all work well together, but we can do that. We can, in my imagining of Terry's thinking, reengineer the organism to its new environment.
It occurred to me last night that there is third, bigger and more insurmountable barrier to re-tuning. One that is not just a technological limitation: Breeding. Humans have been known to breed with each other, and in doing so they mix their genomes. You have half the genome of your biological father and half the genome of your biological mother. Imagine if your uber-mench father had a carefully altered suite of genes, and your mother was a good old-fashioned non-GMO woman. What do you get? You get half a carefully altered genome mixed with genes they were never designed to interact with. Chances are, you have all sorts of wacky health problems, and greatly reduced longevity. It would be like taking half the code of Mac OS 9 and half the code of OS X and expecting a stable operating system.
This means that every change and group of changes would have to be carefully designed to be back-compatible. The alternatives are gene altering the entire human population (which would never ever ever ever work (and I very rarely use that many "ever"s in a row)) or engineering the longevous new humans to be incapable of interbreeding with the old model. They'd have to start by separating off one population as a seperate species, Homo terrii, and only thereafter get serious about reengineering.
So suppose the engineers decide they want to make everything back compatible?
I'm not convinced this would work either. Most mutations are bad for you not only because they break a piece of the system, but because they make a new piece that doesn't work with what is already there. Requiring back compatibility means we have to have every piece work with not only the old set of genes and the new set of genes, but every possible combination of old and new. Evolution, largely free from constraints of time, funding and ethics, accomplishes this by letting those individuals who have bad combinations die out until there are very few harmful combinations possible. To extend the computer code analogy, this would be like trying to write OS XI in such a way that if one blended the code with OS X, it would still work. It is possible to do, but XI would end up looking an awful lot like X, too similar to be more than a service update.
This leaves only the option of creating a population incapable of breeding with normal humans and altering their genes extensively to try to overcome a large number of age-limiting factors at once. Again my understanding of evolution suggests a major difficulty. To do this successfully, one would need a large population all gene-altered simultaneously, to avoid inbreeding effects. One can't start a new population with just a few individuals and expect that species to have a decent chance of surviving well. Even if the species does make it through, there is likely to be an extended period of decreased lifespan and healthspan while the inbreeding kinks work themselves out and the population increases in size and genetic diversity.
Without doubting that bioengineers will continue to make things that seem impossible become projects of undergraduates, I consider it highly unlikely they will achieve any very significant advances in human longevity in the next few decades.
(NOTE: I sent this to Terry for comment or objection some time ago but he has been busy with 'job' and 'editing the book.' I take his failure to offer a substantive reply as evidence that in some basement deep under campus, his department is already failing to build an immortal human.)
Moving the last rotifer
For much of the last year my life and schedule have revolved around daily rotifer census. How often I go to campus, at what times, when I have time for anything else and the energy and time I have for anything else have all depended on lab work. When I could rely on my students to take care of it, I could do other things. Frequently, very frequently, my supply of dependable students was not up to the demands of taking data on and caring for several hundred animals each day. Even when my students are scheduled to do everything, it is rare for a day to go by without questions, problems or scheduling issues. If I am not in lab for a day or two both the quality of the data and the survival of the animals begins to decline.
So it feels like a big deal that my lab work will be done this week. Thursday. I've told my students that after that they are free to continue working on their side projects, but I'm not going to be in the lab. I'm not going to spend hours moving rotifers. I'm not going to be harassing them about keeping the lab organized and the rotifers' containers clean. I'm not going to be on campus six or seven days a week. I'm going to be at home, writing a thesis, and will come to campus on Wednesdays and Thursdays. And I'm taking my desktop (the lab's erstwhile main computer) home.
I like my students, and the rotifers are fascinating, and microscopes are fun. But I really like the idea of not needing to be in the lab every morning at 8. And the prospect of being able to have whole days to work on writing my thesis is positively thrilling.
So it feels like a big deal that my lab work will be done this week. Thursday. I've told my students that after that they are free to continue working on their side projects, but I'm not going to be in the lab. I'm not going to spend hours moving rotifers. I'm not going to be harassing them about keeping the lab organized and the rotifers' containers clean. I'm not going to be on campus six or seven days a week. I'm going to be at home, writing a thesis, and will come to campus on Wednesdays and Thursdays. And I'm taking my desktop (the lab's erstwhile main computer) home.
I like my students, and the rotifers are fascinating, and microscopes are fun. But I really like the idea of not needing to be in the lab every morning at 8. And the prospect of being able to have whole days to work on writing my thesis is positively thrilling.
Wednesday, February 18, 2009
Re-write
It finally occurred to me that the paper I have been writing on the evolution of post-fertile survival (a.k.a. post-reproductive lifespan) really needed to be two papers. I had too many interwoven points I was trying to make simultaneously, and the paper was getting too long and ungainly. So I needed to write two shorter papers, and as a bonus, I needed to have a draft of one to present at a lab meeting tomorrow. I sat myself down this morning at 8AM and wrote for 15 hours with only a few short brakes. Some of this was cutting and pasting, although the pasted bits often required significant revising. I now have a full rough draft of the text of one paper, except that it does not yet include the figures, the tables, the statistics, the references, the appendixes or the complimentary online material. Oh well, I should be able to fill in a few of the holes tomorrow afternoon. Now it is time to see if I can stand up and walk as far as the bed.
Monday, February 16, 2009
Persickity-Split
I've often vented about how terrible science journalism in this country is. The journalists never seem to understand the science they are writing about, and the more I know about the topic, the less they seem to know. I am finding now that as I gain greater expertise in particular topics, large portions of the scientific papers on those topics, written by scientists and published in peer-reviewed journals, strike me as incorporating significant misunderstandings. I many cases, I feel these misunderstandings are significant enough to call the value of the papers into question. By the time I retire, I will undoubtedly think even my own work is crap. I begin to understand why the practitioners in some fields seem to be primarily interested in trashing each other's work.
Friday, February 13, 2009
Progress!
The first draft of the abstract of a first chapter of my thesis! None of this will survive the editing process.
Human females have the unusual life-history trait of frequently surviving well past their reproductively fertile period. While a variety of adaptive hypotheses have been proposed to explain this trait, some authors argue that post-reproductive lifespan (PRL) is a phylogenetically widespread trait, requiring no special adaptive explanation for humans. Still others have argued that PRL is the result of cultural and physiological traits, not adaptive evolution. We suggest that the continued confusion on this front arises from two primary sources, the treatment of non-alternative hypotheses as mutually exclusive, and the use of PRL, an inconsistently calculated and theoretically ill-suited parameter. Given the drawbacks of PRL as a comparative measure, a variety of more useful and comparable measures of post-reproductive survival (PRS) can be calculated using data in the form of standard demographic life tables. Using life tables from 20 human populations, 78 non-human primate populations and two non-primate species, we present a set of measures of PRS which allow for direct comparability between populations and to evolutionary null hypotheses. We find strong support for the uniqueness of the scale of human PRS, for the widespread presence of PRS in primates and for the influence of culture in extending PRS.
Human females have the unusual life-history trait of frequently surviving well past their reproductively fertile period. While a variety of adaptive hypotheses have been proposed to explain this trait, some authors argue that post-reproductive lifespan (PRL) is a phylogenetically widespread trait, requiring no special adaptive explanation for humans. Still others have argued that PRL is the result of cultural and physiological traits, not adaptive evolution. We suggest that the continued confusion on this front arises from two primary sources, the treatment of non-alternative hypotheses as mutually exclusive, and the use of PRL, an inconsistently calculated and theoretically ill-suited parameter. Given the drawbacks of PRL as a comparative measure, a variety of more useful and comparable measures of post-reproductive survival (PRS) can be calculated using data in the form of standard demographic life tables. Using life tables from 20 human populations, 78 non-human primate populations and two non-primate species, we present a set of measures of PRS which allow for direct comparability between populations and to evolutionary null hypotheses. We find strong support for the uniqueness of the scale of human PRS, for the widespread presence of PRS in primates and for the influence of culture in extending PRS.
Thursday, February 12, 2009
Tuesday, February 10, 2009
Finallly!
We have submitted our paper on the meaning of the word behavior (or, since the journal is British, behaviour). It took much longer to get it to the point where we could all agree on it than I expected, and there are still a few stylistic points I am not fully satisfied with, but overall I think it is a good paper, and has a good chance of being accepted. I am sure none of the reviewers will entirely agree with out conclusions, but the point of the paper is that we don't agree, so I think that is okay.
Friday, February 06, 2009
My people are nerdier than your people
As I walked by two of my labmates today, one of them was introducing a visitor to the other.
LM1: "I initially falsely synonomized you with Robert!"
LM2: "He does phenotypically converge with Robert."
Translation into English:
LM1: "I mistook you for Robert at first!"
LM2: "He does look a lot like Robert."
Note that while the English version is shorter and easier to read, the original is easier for people in my line of work to say.
LM1: "I initially falsely synonomized you with Robert!"
LM2: "He does phenotypically converge with Robert."
Translation into English:
LM1: "I mistook you for Robert at first!"
LM2: "He does look a lot like Robert."
Note that while the English version is shorter and easier to read, the original is easier for people in my line of work to say.
Carnival of Science!
The lead story on the BBC New's Science and Environment page is on the research of one of the post-doctoral researchers in my professor's lab. The idea is rather simple, the process was complex.
We know that climate changes over time, and that where one can find a particular type of habitat changes with the climate. Recently, using a wide range of data sources, scientists have been constructing both a detailed history of how climate has changed over time and what climate parameters limit the extent of particular habitats, such as South America's Atlantic Rainforest. My lab-mate, Ana Carnival (along with several collaborators) combined the climate history data with the climate requirement data to make maps of how the extent of the Atlantic forest has changed over the last 20,000 years. She found that there were a few relatively small areas that had been rainforest the whole time, even when climate shifts caused the rest of it to change to other habitat types, such as grassland. She identified these as 'rainforest refugia,' areas where rainforest species could survive through the millenia when the climate was inhospitable elsewhere. She then predicted that these refugia should be the centers from which genetic diversity spread to the rest of the forest once its borders once again grew. To test these predictions, she gathered genetic samples from three species of frogs which can survive only in the rainforest. Sure enough, the frog's DNA told the story she had predicted, confirming the refugia she had identified based on climate models. This is not only cool science, it has significant conservation implications. These refugia should house a large portion of the diversity found in the rainforest, because at some points in the last 20K years, all the rainforest species lived there. This suggests that if we are forced to make choices about which land to preserve (which we are) we might do well to preserve these refugia. And both the methods and the conclusions are potentially generalizable to other thretened habitats around the world.
One final thought: This is very cool work, and very much in line with what most people in my adviser's lab study, but it is so far from my own work that I barely understand the details. This may be why I don't notice any glaring errors in the BBC article, or maybe the UK press are not as bad at writing about science as the American press.
We know that climate changes over time, and that where one can find a particular type of habitat changes with the climate. Recently, using a wide range of data sources, scientists have been constructing both a detailed history of how climate has changed over time and what climate parameters limit the extent of particular habitats, such as South America's Atlantic Rainforest. My lab-mate, Ana Carnival (along with several collaborators) combined the climate history data with the climate requirement data to make maps of how the extent of the Atlantic forest has changed over the last 20,000 years. She found that there were a few relatively small areas that had been rainforest the whole time, even when climate shifts caused the rest of it to change to other habitat types, such as grassland. She identified these as 'rainforest refugia,' areas where rainforest species could survive through the millenia when the climate was inhospitable elsewhere. She then predicted that these refugia should be the centers from which genetic diversity spread to the rest of the forest once its borders once again grew. To test these predictions, she gathered genetic samples from three species of frogs which can survive only in the rainforest. Sure enough, the frog's DNA told the story she had predicted, confirming the refugia she had identified based on climate models. This is not only cool science, it has significant conservation implications. These refugia should house a large portion of the diversity found in the rainforest, because at some points in the last 20K years, all the rainforest species lived there. This suggests that if we are forced to make choices about which land to preserve (which we are) we might do well to preserve these refugia. And both the methods and the conclusions are potentially generalizable to other thretened habitats around the world.
One final thought: This is very cool work, and very much in line with what most people in my adviser's lab study, but it is so far from my own work that I barely understand the details. This may be why I don't notice any glaring errors in the BBC article, or maybe the UK press are not as bad at writing about science as the American press.
Wednesday, February 04, 2009
Public Science
The government, in its many forms, funds a large portion of academic science. This has given many people the idea that taxpayers should have access to the output of that science. But in many cases the output is a publication in a subscription journal, which non-subscribers don't have digital access to. Somebody up and said, "Hey, we paid for that research, we want access to it." So NIH has reached understandings with many of the corporations that publish scientific journals saying that if an author was funded by the NIH while working on any part of a paper, the journal has to make that article free to the public, even if the rest of the journal is subscription only.
This works out great for me. My fellowship is through National Institute on Aging, part of NIH. So any journal article I publish while I am on fellowship, or based on data I gathered while on fellowship, can't be hidden from the eyes of non-subscribers.
This works out great for me. My fellowship is through National Institute on Aging, part of NIH. So any journal article I publish while I am on fellowship, or based on data I gathered while on fellowship, can't be hidden from the eyes of non-subscribers.
Monday, February 02, 2009
Referees
I'm submitting a paper to Animal Behaviour. Their instructions to authors require that I suggest four referees, people who they could send the paper to who are qualified to review it and decide if it goes in Animal Behaviour. They don't necessarily take my suggestions, but they require that I suggest.
I found myself rather stumped. I decided to write the paper because as far as I could tell, nobody had written anything similar. So who should I suggest they send it to?
I wrote to one of my professors for advice. One of his suggestions was that it was their job to figure out who was the best person to review it, and I should just make up four fictitious names and send them in. He even suggested a made up name to use: G. Hector Meckel.
This is the adviser who is notorious for scoffing at the etiquette and protocol of bureaucracies in general and the scientific societies in specific. Despite the humor value, I think I will submit real names of potentially interested people.
I found myself rather stumped. I decided to write the paper because as far as I could tell, nobody had written anything similar. So who should I suggest they send it to?
I wrote to one of my professors for advice. One of his suggestions was that it was their job to figure out who was the best person to review it, and I should just make up four fictitious names and send them in. He even suggested a made up name to use: G. Hector Meckel.
This is the adviser who is notorious for scoffing at the etiquette and protocol of bureaucracies in general and the scientific societies in specific. Despite the humor value, I think I will submit real names of potentially interested people.
Saturday, January 31, 2009
Oldest old
Among my demography colleagues there is considerable academic interest in the 'oldest old,' the people who make 90 year olds seem positively youthful. I once heard a series of talks on "Sardinian Super-Centenarians" (a truly lovely phrase to hear repeated in an Italian accent). So first you're old, then you are really old, then you are a centenarian, then you are a super-centenarian, then, once having turned 100 is ancient history, you get to be oldest old. And once you are oldest old, having outlived many millions of your cohort, lots of people start taking an interest in you. Locals take it as a mark of pride to have someone so incredibly longevous living among them. People wonder what kind of yogurt you eat, and how often. Geneticists want blood samples to find all the things that didn't kill you. Demographers need data on you to know how the rightmost extremes of their graphs of anything over age should look. Is mortality rate higher among 115 year olds than 116 year olds, and what does that tell us about the possibility of increasing human lifespan generally? Is maximum longevity still increasing with improved technology?
It is hard to find very many data points for these questions, and significant resources have been invested in scouring the world for very old people whose ages can be positively verified.
Tuti Yusupova of Uzbekistan is a good example. According to her recently "noticed" birth certificate, she is 128 years old, by far the oldest living person ever recorded. But was the birth certificate really made in 1880, or was it slipped into a folder in 1920 or 2008? Could it be a clerical error? Some priest or bureaucrat may have written the wrong year for some reason. These things are surely being investigated.
And is she the original Tuti? A colleague told me of a case in which a potential oldest woman turned out to have adopted her mother's name, persona and possessions when her mother died. In the process she added 30 years to her age. She was old, but not oldest old. Publicity surrounding her apparent record brought the truth to light. So my colleagues are understandably dubious about the new record holder. If she is that old (which I hope is the case just because a real record is nicer than a fake one) some of my colleagues will have to (slightly) modify their thinking about how long a human being can stay alive.
It is hard to find very many data points for these questions, and significant resources have been invested in scouring the world for very old people whose ages can be positively verified.
Tuti Yusupova of Uzbekistan is a good example. According to her recently "noticed" birth certificate, she is 128 years old, by far the oldest living person ever recorded. But was the birth certificate really made in 1880, or was it slipped into a folder in 1920 or 2008? Could it be a clerical error? Some priest or bureaucrat may have written the wrong year for some reason. These things are surely being investigated.
And is she the original Tuti? A colleague told me of a case in which a potential oldest woman turned out to have adopted her mother's name, persona and possessions when her mother died. In the process she added 30 years to her age. She was old, but not oldest old. Publicity surrounding her apparent record brought the truth to light. So my colleagues are understandably dubious about the new record holder. If she is that old (which I hope is the case just because a real record is nicer than a fake one) some of my colleagues will have to (slightly) modify their thinking about how long a human being can stay alive.
Editing I know not what.
My wife often asks me to edit her writings in linguistics. This is an interesting exercise, as my knowledge of linguistics is probably sufficient to get me a D+ on a Linguistics 1A final. And most of that limited knowledge is derived from the works I have helped to edit. This makes me very good at finding sentences that are not crystal clear, but very bad at knowing whether the lack of clarity arises from my lack of knowledge. The result is that Iris's writing ends up being much clearer to the non-linguist (or at least to me) than most technical writing is to non-experts.
Perhaps all academics should be encouraged to have their work edited by a practitioner of an unrelated field prior to publication.
Perhaps all academics should be encouraged to have their work edited by a practitioner of an unrelated field prior to publication.
Saturday, January 24, 2009
Cephalic rotiferitis
I've been in the lab every day all day for the last week looking at rotifers. When I close my eyes, I not only see rotifers, I can count their eggs, see their teeth chewing and estimate their age.
Thursday, January 22, 2009
Rep. Boehner, Ludite
This morning on NPR, I heard an interview with Rep. John Boehner, the House Minority Leader. When asked about his reservations with President Obama's stimulus plan, he responded by saying that some of the spending did not seem wise to him.
"Remember, the goal of the stimulus package is to preserve jobs and help create new jobs in America," Boehner said. "And I don't know how giving NASA $400 million to study global warming is going to meet the goals."
It occurs to me to wonder if perhaps Rep. Boehner has so little conception of how science works that he truely doesn't know that when money is spent to study a problem, that money goes into the economy. NASA does not simply trassubstantiate the money into knowledge about global warming. NASA employs thousands of Americans on problems such as these; NASA contractors employ many thousands more. NASA advances technologies that help create new jobs.
My guess is that Rep. Boehner knows all this. It seems likely that Rep. Boehner knows that engineers and scientists are being laid off along with workers in almost every other field. Rather, I suspect the congressman is simly trying to rally his political base by warning them that the government is spending money on a problem they have been trained to think is a liberal hoax, global warming.
Which shows a certain level of consistency. Rep. Boehner is as derisive of the conclusions of science as he is ignorant of the process by which we reach those conclusions.
"Remember, the goal of the stimulus package is to preserve jobs and help create new jobs in America," Boehner said. "And I don't know how giving NASA $400 million to study global warming is going to meet the goals."
It occurs to me to wonder if perhaps Rep. Boehner has so little conception of how science works that he truely doesn't know that when money is spent to study a problem, that money goes into the economy. NASA does not simply trassubstantiate the money into knowledge about global warming. NASA employs thousands of Americans on problems such as these; NASA contractors employ many thousands more. NASA advances technologies that help create new jobs.
My guess is that Rep. Boehner knows all this. It seems likely that Rep. Boehner knows that engineers and scientists are being laid off along with workers in almost every other field. Rather, I suspect the congressman is simly trying to rally his political base by warning them that the government is spending money on a problem they have been trained to think is a liberal hoax, global warming.
Which shows a certain level of consistency. Rep. Boehner is as derisive of the conclusions of science as he is ignorant of the process by which we reach those conclusions.
Wednesday, January 21, 2009
Text is a battlefield
I have spent a week of evenings trying to impose order upon this section on the measurement of post-reproductive survival. The document is littered with dead and broken bits of cast away paragraphs, sentence fragments, disembodied equations, references to tables that don't yet exist and citations of papers I remember reading a long time ago but need to check what they actually say. Multiple passages providing identical information vie to eliminate each other. Clean up is going to be long and ugly. Some concepts that don't make it will be scavenged for other papers. Others, too badly broken, will simply be left for dead.
After all this textual carnage, I finally have a good idea of how to ram all my multi-dimensional conceptual links into a single linear string of text. I even have most of it there. If I pretend I have a year more to finish than I actually do, I feel like I am making great progress, and greatly enjoying it.
After all this textual carnage, I finally have a good idea of how to ram all my multi-dimensional conceptual links into a single linear string of text. I even have most of it there. If I pretend I have a year more to finish than I actually do, I feel like I am making great progress, and greatly enjoying it.
Scientist Poitical Humor
me: Obama has appointed two Berkeley professors.
Karen: Who are the Berkeley professors?
me: Christina Romer and Steve Chu
Karen: Do you know them?
me: No, but I know people who know them, which is the square root of as good.
Karen: Who are the Berkeley professors?
me: Christina Romer and Steve Chu
Karen: Do you know them?
me: No, but I know people who know them, which is the square root of as good.
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