Without having done extensive checking, I would guess that Wikipedia is the only encyclopedia in the world in which the section on primate taxonomy includes nude photos of male and female humans with all their body-hair removed.
I suppose one could argue that body hair would obscure some portion of our typically primate anatomy, or make the photos appear less clinical. That said, none of the other primates pictured are shaven, so why the humans? And honestly, human's body hair doesn't hide that much anyway. As humans are naturally the least hairy of any primate, the clean shaven models seem to me to unduly exaggerate our distinctness from other primates. I don't approve.
On further consideration of the nature of Wikipedia, the inclusion of these photos could be intended purely to annoy social conservatives who object on religious grounds to the placement of humans among the primates. In that case the hairlessness would presumably be intended to emphasize the nudity of the models.
Tuesday, April 21, 2009
Monday, April 20, 2009
Wherefore art thou, niche conseratism?
"Niche conservatism is the tendency of species to retain ancestral ecological characteristics." (PDF)
But why do species have this tendency, or more particularly, why do ecological traits not change more rapidly than they do as a lineage evolves? Wiens and Graham state that, "We refer to niche conservatism as a process, although it may be caused by more than one factor at the population level," but don't say what those factors may be, or provide a reference to someone who does.
So what causes niche conservatism:
Two basic mechanisms occur to me. The first is that new traits simply don't arise, and therefore can't be selected for or against. Why don't we have rats that can eat iron? There is lots of elemental iron around these days, and it is very high in energy. Surely a rat that could eat iron and extract all that energy would do very well, and make lots more iron-eating rats. But that trait has not occurred (and is not likely to do so) and as such there is no way for natural selection to favor the iron-eating rats. But for traits like sexual mass dimorphism, this type of constraint seems unlikely. We know that closely related species sometimes have very different mass dimorphisms (compare gorillas to humans). But closely related species usually don't have wildly different mass dimorphisms, so there is conservatism in the trait even though it is pliable.
The second possibility that occurs is that niche conservatism comes about simply because a trait works well with the way a population lives, and the other traits is has, and therefore some form of selection acts to keep the trait where it is. The trait is conserved because it is functional. Even if some other combination of traits would be more advantageous, that combination would require so many modifications that you can't get there from here. The population would have to go to far 'downhill' on the fitness landscape to get to that taller hill across the way. So selection, which tends to push the population 'uphill,' keeps it on the little local peak it is on. By keeping the population where it is, selection causes niche conservatism.
I'll call it a hypothesis. First I need to find out who has already said almost the same thing.
But why do species have this tendency, or more particularly, why do ecological traits not change more rapidly than they do as a lineage evolves? Wiens and Graham state that, "We refer to niche conservatism as a process, although it may be caused by more than one factor at the population level," but don't say what those factors may be, or provide a reference to someone who does.
So what causes niche conservatism:
Two basic mechanisms occur to me. The first is that new traits simply don't arise, and therefore can't be selected for or against. Why don't we have rats that can eat iron? There is lots of elemental iron around these days, and it is very high in energy. Surely a rat that could eat iron and extract all that energy would do very well, and make lots more iron-eating rats. But that trait has not occurred (and is not likely to do so) and as such there is no way for natural selection to favor the iron-eating rats. But for traits like sexual mass dimorphism, this type of constraint seems unlikely. We know that closely related species sometimes have very different mass dimorphisms (compare gorillas to humans). But closely related species usually don't have wildly different mass dimorphisms, so there is conservatism in the trait even though it is pliable.
The second possibility that occurs is that niche conservatism comes about simply because a trait works well with the way a population lives, and the other traits is has, and therefore some form of selection acts to keep the trait where it is. The trait is conserved because it is functional. Even if some other combination of traits would be more advantageous, that combination would require so many modifications that you can't get there from here. The population would have to go to far 'downhill' on the fitness landscape to get to that taller hill across the way. So selection, which tends to push the population 'uphill,' keeps it on the little local peak it is on. By keeping the population where it is, selection causes niche conservatism.
I'll call it a hypothesis. First I need to find out who has already said almost the same thing.
Sunday, April 19, 2009
A third way of seeing things
The paper I'm writing now is on sex-biased longevity in primates. I'm trying to understand why in some species the males live longer, and in others the females live longer. The story I'm trying to test goes like this:
The largest investment in primates' offspring is in the form of care, not eggs or sperm or pregnancy. In species where females provide all of the care, males need not stay with a single mate, so the operational sex ratio is male biased (i.e. lots of males are out looking for a mate, while most of the females are pregnant or nursing and therefore not looking to mate), reproductive skew is high for males (some males will father lots of offspring, others none), and the fitness rewards to successful male competitors are great. Larger males are more likely to win these competitions, resulting in an increase in optimal male size. These large belligerent males risk increased mortality through conflict, and through diversion of physiological and developmental resources away from longevity and into competitiveness. Simultaneously, selection for longevity in females may be increased by the need to stay alive until their young become independent (and in the case of humans, to care for grandkids). This leads to males who, relative to females, are non-caring, short-lived, large and conflict prone.
I have data (gleaned from the literature) for a bunch of primate species on how long males and females live, how much care the fathers provide in each species, how big males and females are and how frequently and intensely males fight with each other. Depending on how I analyze these data, I get two very different answers. If I treat each species as an independent sample, and look at the correlations between these variables, the data completely support the story. The species range along a continuum having short-lived belligerent large, uncaring males at one end and long-lived caring low-conflict small males at the other.
But most evolutionary biologists would say that is not the right way to analyze the data. I need to take into account the relationships among the species. Two traits might seem to be correlated not because the one makes the other selectively advantageous, but because a group related species all have the one and all have the second. Take the example of feathers and laying eggs. All birds have feathers and all birds lay eggs. Is this because something about feathers requires egg-laying (probably not) or because all birds are descendents of some ancestral birds that laid eggs and had feathers, and ever since no bird has arisen that didn't do both those things. That all birds have eggs and feathers is an example of what biologists call evolutionary inertia.
The question this poses for me in writing my paper on primates is whether the correspondence between sex-biased longevity and these other variables is because of the adaptive story I told you, or because of evolutionary inertia. So I look at the data a second way, and see that there is a great deal of evolutionary inertia in these traits. Most primate species are somewhere near the middle of that continuum I described. Ever species at one end is from one group of related monkeys. Every species at the other end of the continuum is either a great ape or from a different family of monkeys. Plugging my data into software designed to test for evolutionary inertia, I find that closely related species are very likely to have similar values for all the traits I am measuring, and that inertia is fully sufficient to explain the correlations between these traits. It is like eggs and feathers in bird.
As I am trying to write the paper to present all of this in a scientifically rigorous way, I am struggling with what to say about it. The easiest, and least interesting, conclusion would be to simply say that the correlations are purely illusions conjured by evolutionary inertia. What I'm attempting to find a way to argue it that it could just be inertia, but that the inertia might be because of selective effects. In other words, that both the inertia story and the selective story could simultaneously be true, and closely related species are similar not because they can't change, but because what was adaptive for their common ancestor is still adaptive for them. If a male from a very belligerent species was to grow in a way that made him not a good competitor, but able to live a long time and provide care to his young, this wouldn't fit with the way his species lives, so he wouldn't pass on his novel trait, and his species would stay like their ancestors had been. It is evolutionary inertia caused by adaptive mechanisms. I think my next step is to find out who has already written about adaptive evolutionary inertia, and what they said.
The largest investment in primates' offspring is in the form of care, not eggs or sperm or pregnancy. In species where females provide all of the care, males need not stay with a single mate, so the operational sex ratio is male biased (i.e. lots of males are out looking for a mate, while most of the females are pregnant or nursing and therefore not looking to mate), reproductive skew is high for males (some males will father lots of offspring, others none), and the fitness rewards to successful male competitors are great. Larger males are more likely to win these competitions, resulting in an increase in optimal male size. These large belligerent males risk increased mortality through conflict, and through diversion of physiological and developmental resources away from longevity and into competitiveness. Simultaneously, selection for longevity in females may be increased by the need to stay alive until their young become independent (and in the case of humans, to care for grandkids). This leads to males who, relative to females, are non-caring, short-lived, large and conflict prone.
I have data (gleaned from the literature) for a bunch of primate species on how long males and females live, how much care the fathers provide in each species, how big males and females are and how frequently and intensely males fight with each other. Depending on how I analyze these data, I get two very different answers. If I treat each species as an independent sample, and look at the correlations between these variables, the data completely support the story. The species range along a continuum having short-lived belligerent large, uncaring males at one end and long-lived caring low-conflict small males at the other.
But most evolutionary biologists would say that is not the right way to analyze the data. I need to take into account the relationships among the species. Two traits might seem to be correlated not because the one makes the other selectively advantageous, but because a group related species all have the one and all have the second. Take the example of feathers and laying eggs. All birds have feathers and all birds lay eggs. Is this because something about feathers requires egg-laying (probably not) or because all birds are descendents of some ancestral birds that laid eggs and had feathers, and ever since no bird has arisen that didn't do both those things. That all birds have eggs and feathers is an example of what biologists call evolutionary inertia.
The question this poses for me in writing my paper on primates is whether the correspondence between sex-biased longevity and these other variables is because of the adaptive story I told you, or because of evolutionary inertia. So I look at the data a second way, and see that there is a great deal of evolutionary inertia in these traits. Most primate species are somewhere near the middle of that continuum I described. Ever species at one end is from one group of related monkeys. Every species at the other end of the continuum is either a great ape or from a different family of monkeys. Plugging my data into software designed to test for evolutionary inertia, I find that closely related species are very likely to have similar values for all the traits I am measuring, and that inertia is fully sufficient to explain the correlations between these traits. It is like eggs and feathers in bird.
As I am trying to write the paper to present all of this in a scientifically rigorous way, I am struggling with what to say about it. The easiest, and least interesting, conclusion would be to simply say that the correlations are purely illusions conjured by evolutionary inertia. What I'm attempting to find a way to argue it that it could just be inertia, but that the inertia might be because of selective effects. In other words, that both the inertia story and the selective story could simultaneously be true, and closely related species are similar not because they can't change, but because what was adaptive for their common ancestor is still adaptive for them. If a male from a very belligerent species was to grow in a way that made him not a good competitor, but able to live a long time and provide care to his young, this wouldn't fit with the way his species lives, so he wouldn't pass on his novel trait, and his species would stay like their ancestors had been. It is evolutionary inertia caused by adaptive mechanisms. I think my next step is to find out who has already written about adaptive evolutionary inertia, and what they said.
Saturday, April 18, 2009
Science-based do-gooding.
Last month as we drove up to her mom's house, Iris and I were talking about what sorts of non-profits we think really use their money well, in terms of achieving a lot of good with relatively little money. I said that the ones that usually impressed me were those very focused on a single type of action that did that one thing extremely well, rather than trying to save the whales and reduce teen pregnancy and sue the manufacturers and put out a great picture book of homeless homosexual redwood trees. Iris asked what kind of action I had in mind, and I said that ultimately, the step that seems to do the most good for the least expense is educating girls in poor countries where girls don't traditionally get educations. The list of things one can accomplish by educating girls is truly amazing. The level of education of the females in a country is the single best predictor of longevity increases, decrease in infant and juvenile mortality, decrease in rate of population growth, decrease in rate of infectious disease, increase in future education of both boys and girls and so on and so on. It is more important than how rich a country it is, how many doctors it has, the religious practices of the population or how well educated the men are. There are decades of studies comparing between nations, between regions, between villages and between individual families, and at every level having better educated women around translates into a healthier, more stable and less quickly increasing population. And the greatest gains in all these outcomes come from the first steps in educating the women. Whether women have a masters or a PhD doesn't affect the chance of their babies dying much. Whether they finished third grade or had no school at all has an enormous impact. Every additional year of schooling is helpful, but less so than the previous year.
When I read these studies, I feel like we shouldn't be spending development money on anything but educating girls. I feel like we've known about the development wonder drug for decades (and unlike most wonder-drugs, this one actually works) but haven't bothered to use it. Iris pointed out that in many countries, such as Niger, where she was a Peace Corps volunteer, there are cultural sensitivities that would keep a westerner from marching in and educating girls. The education of boys is considered more important, and many boys don't get educated for lack of funding. Post-colonial resentments exist, and must be treated carefully. Iris argued that if an organization wanted to educated Niger's girls, its organizers would have to have the kinds of insights and sensitivities to Niger's culture that only Nigeriens have. She lamented the fact that there was no such organization in Niger.
Imagine then our surprise and delight when (less than a week later) Iris found out that some of her Nigerien contacts were founding an organization to promote and fund the education of Nigerien girls. If we were superstitious people, we could draw all sorts of conclusions from the coincidence. Instead, we have offered to do what we can to help them get up and running. They don't yet have anything more official than a possible name and a board of directors. They aren't even taking donations yet (they still have to apply for tax-exempt status). Iris has been contacting her Peace Corps friends who have particular useful expertise, and I've been unwisely taking time away from my thesis to gather up and summarize the published research on the benefits of educating women. Perhaps it is naive, but I can't help but think that it would be useful to have a well documented statement on the benefits of educating girls to show to potential donors and government types. We expect to be helpful to them however we can. If they are able to do what they want to do, Niger (currently one of the world's poorest and worst educated nations) should be an amazing success story in a decade or two.
When I read these studies, I feel like we shouldn't be spending development money on anything but educating girls. I feel like we've known about the development wonder drug for decades (and unlike most wonder-drugs, this one actually works) but haven't bothered to use it. Iris pointed out that in many countries, such as Niger, where she was a Peace Corps volunteer, there are cultural sensitivities that would keep a westerner from marching in and educating girls. The education of boys is considered more important, and many boys don't get educated for lack of funding. Post-colonial resentments exist, and must be treated carefully. Iris argued that if an organization wanted to educated Niger's girls, its organizers would have to have the kinds of insights and sensitivities to Niger's culture that only Nigeriens have. She lamented the fact that there was no such organization in Niger.
Imagine then our surprise and delight when (less than a week later) Iris found out that some of her Nigerien contacts were founding an organization to promote and fund the education of Nigerien girls. If we were superstitious people, we could draw all sorts of conclusions from the coincidence. Instead, we have offered to do what we can to help them get up and running. They don't yet have anything more official than a possible name and a board of directors. They aren't even taking donations yet (they still have to apply for tax-exempt status). Iris has been contacting her Peace Corps friends who have particular useful expertise, and I've been unwisely taking time away from my thesis to gather up and summarize the published research on the benefits of educating women. Perhaps it is naive, but I can't help but think that it would be useful to have a well documented statement on the benefits of educating girls to show to potential donors and government types. We expect to be helpful to them however we can. If they are able to do what they want to do, Niger (currently one of the world's poorest and worst educated nations) should be an amazing success story in a decade or two.
Thursday, April 16, 2009
Poster-time
In a couple of weeks I'll be attending the conference of the Population Association of America. It will be a bunch of demographers. Most of the conference is talks divided into topic-specific sessions. They don't have a session for biodemography, or really anything related to my research, but the poster-session is open to whatever topic, so I'm presenting a poster.
My title is, "Post-Reproductive Lifespan in Humans: Cultural Artifact, Widespread Primate Trait or Unique Adaptation?"
I've had fun making my poster, mostly because it is an excuse to play with Photoshop and Powerpoint instead of writing my thesis. For my poster I needed to find a compact easy way to display how the fertility and survival of a population changes with age, and simultaneously explain my methods. And I needed to be able to do that for several populations side by side in a small space. Now this is all tailored to make sense to the demographer, so it may not be that intuitive to anyone else, but I like what I've got. To clarify, in demographerese, lx means what portion of the individuals that survive to each age and mx means how fertile are individuals at that age.
By plotting mx and lx on the same graph I make it visually clear (to a demographer) that the population nears an endpoint to fertility (age M) long before it nears an endpoint of survival (age Z). I then go on to use some math and demographic methods to define good ways to measure post-fertile survival in ways that allow for straightforward comparisons between species. I call the two measurements G and S. But the fun part comes in when I use the graphical format established in Figure 1 to compare populations in Figure 2:
My hope is that having labeled and explained the parts of the graph in Fig. 1, the meaning of these graphs in Fig. 2 will be quickly obvious to the demography crowd. I'll leave you to interpret what these graphs say about post-fertile survival in humans and chimps in different environments. I can't give away everything.
My title is, "Post-Reproductive Lifespan in Humans: Cultural Artifact, Widespread Primate Trait or Unique Adaptation?"
I've had fun making my poster, mostly because it is an excuse to play with Photoshop and Powerpoint instead of writing my thesis. For my poster I needed to find a compact easy way to display how the fertility and survival of a population changes with age, and simultaneously explain my methods. And I needed to be able to do that for several populations side by side in a small space. Now this is all tailored to make sense to the demographer, so it may not be that intuitive to anyone else, but I like what I've got. To clarify, in demographerese, lx means what portion of the individuals that survive to each age and mx means how fertile are individuals at that age.
By plotting mx and lx on the same graph I make it visually clear (to a demographer) that the population nears an endpoint to fertility (age M) long before it nears an endpoint of survival (age Z). I then go on to use some math and demographic methods to define good ways to measure post-fertile survival in ways that allow for straightforward comparisons between species. I call the two measurements G and S. But the fun part comes in when I use the graphical format established in Figure 1 to compare populations in Figure 2:
My hope is that having labeled and explained the parts of the graph in Fig. 1, the meaning of these graphs in Fig. 2 will be quickly obvious to the demography crowd. I'll leave you to interpret what these graphs say about post-fertile survival in humans and chimps in different environments. I can't give away everything.
Monday, April 13, 2009
Diurnal Activity Cycles
My wife and I (both writing theses this spring) and two cats share a very small studio apartment. One way we make maximum use of the space is by having different sleep-wake schedules. I do my most effective writing between 9PM and 1AM. Iris gets the most done from 6AM to 10AM. I have the easiest time concentrating at that time, and only partly because everyone else is asleep. FeLion, our older cat, does some of her best suckling on inanimate objects in the middle of the day. Tigrinum, the kitten, expends most of his energy from 2AM to 6AM, charging around the house and leaping from the top of his cat-tree onto his sleeping humans. Come to think of it, it makes a pretty lousy system.
There is a well established pattern of individuals of different ages waking and sleeping at different times. Older adults and young children tend to go to sleep early and wake up early. Teenagers tend to stay up late and go to bed late. People in all the ages in between are pretty variable. These patterns are well known to most people, but I'm not sure we understand their evolutionary basis. Why did humans evolve to have sleep schedules that vary individually and with age as much as they do? My guess is that it had to do with avoiding competition within groups for space and forage. The old people and the little kids left the cave or the hut early in the morning and foraged before everyone else was up. In the evening, after everyone else was asleep the young people would stay up and try to impress potential mating partners. That was probably the easiest time to find some privacy without straying too far from the village. One thing I wonder about, do other primates have similar variation in their diurnal activity cycles? That right there is a good evolutionary biodemography question.
There is a well established pattern of individuals of different ages waking and sleeping at different times. Older adults and young children tend to go to sleep early and wake up early. Teenagers tend to stay up late and go to bed late. People in all the ages in between are pretty variable. These patterns are well known to most people, but I'm not sure we understand their evolutionary basis. Why did humans evolve to have sleep schedules that vary individually and with age as much as they do? My guess is that it had to do with avoiding competition within groups for space and forage. The old people and the little kids left the cave or the hut early in the morning and foraged before everyone else was up. In the evening, after everyone else was asleep the young people would stay up and try to impress potential mating partners. That was probably the easiest time to find some privacy without straying too far from the village. One thing I wonder about, do other primates have similar variation in their diurnal activity cycles? That right there is a good evolutionary biodemography question.
Sunday, April 12, 2009
Why I can love chocolate
The conversation usually goes something like this:
Me- I'm allergic to caffeine. It makes me get a terrible headache, then get really sleepy and sleep for 12 hours and then I still have a terrible headache.
You- Um, but I see you eat chocolate all the time. You're always talking about chocolate and writing about chocolate. You are a total chocolate adict.
Me- Yeah! I love chocolate. It's my main drug.
You- Um, but chocolate has caffeine.
Me- Well, it has a tiny bit, but mostly it has other closely related chemicals.
I've had this conversation with enough dozens of people that I figured I should look up what was in chocolate. And it turns out I actually did know what I was talking about (for once). According to this article in the journal European Food Research and Technology, cacao beans have three main kinds of very similar chemicals in the group called methylxanthines. These are theobromine (named for the Cacao tree, Theobroma cacao), caffeine, and theophylline. Raw fermented beans straight off the cacao tree have lots of theobromine, very little caffeine and almost no theophylline. In the various preparation steps between then and when I actually eat it, much of the caffeine is lost. The concentration of these various chemicals depends a lot on the strain of cacao, the growing conditions and the processing, but most chocolate has 20 to 100 times as much theobromine as caffeine. A cup of hot cocoa has about half as much caffeine as a cup of decaf coffee.
The fact that chocolate doesn't make me have a terrible headache and put me to sleep is likely (likely meaning I am speculating) either because there is too little caffeine in it to matter or because it has so much theobromine. Theobromine could be counteracting the caffeine, or it could be competitively excluding the caffeine from the neuroreceptors it normally binds to. Basically this means that theobromine and caffeine are so similar that they stick to the same spots on my neurons, and if the theobromine gets there first, the caffeine may not be able to stick, and therefore not affect me. But the moral of the story is I can eat chocolate without worrying about the caffeine making me sick.
Me- I'm allergic to caffeine. It makes me get a terrible headache, then get really sleepy and sleep for 12 hours and then I still have a terrible headache.
You- Um, but I see you eat chocolate all the time. You're always talking about chocolate and writing about chocolate. You are a total chocolate adict.
Me- Yeah! I love chocolate. It's my main drug.
You- Um, but chocolate has caffeine.
Me- Well, it has a tiny bit, but mostly it has other closely related chemicals.
I've had this conversation with enough dozens of people that I figured I should look up what was in chocolate. And it turns out I actually did know what I was talking about (for once). According to this article in the journal European Food Research and Technology, cacao beans have three main kinds of very similar chemicals in the group called methylxanthines. These are theobromine (named for the Cacao tree, Theobroma cacao), caffeine, and theophylline. Raw fermented beans straight off the cacao tree have lots of theobromine, very little caffeine and almost no theophylline. In the various preparation steps between then and when I actually eat it, much of the caffeine is lost. The concentration of these various chemicals depends a lot on the strain of cacao, the growing conditions and the processing, but most chocolate has 20 to 100 times as much theobromine as caffeine. A cup of hot cocoa has about half as much caffeine as a cup of decaf coffee.
The fact that chocolate doesn't make me have a terrible headache and put me to sleep is likely (likely meaning I am speculating) either because there is too little caffeine in it to matter or because it has so much theobromine. Theobromine could be counteracting the caffeine, or it could be competitively excluding the caffeine from the neuroreceptors it normally binds to. Basically this means that theobromine and caffeine are so similar that they stick to the same spots on my neurons, and if the theobromine gets there first, the caffeine may not be able to stick, and therefore not affect me. But the moral of the story is I can eat chocolate without worrying about the caffeine making me sick.
Elastic replacement
I've been thinking on an off for several years about the concept of 'elastic replacement.' That is term I made up to mean when the rate at which new things arise increases in response to the effort to remove old things. The example that got me started thinking about this was a political one. For the early years of the US occupation of Iraq, the Bush administration frequently cited statistics on how many terrorists had been killed or captured as a result of US action in Iraq. What they never seemed to consider was that US action in Iraq might also be increasing the replacement of terrorists by making it easier for terrorists to find and recruit young people who might have otherwise been non-violent. The size of any population is determined by not only the number leaving, but also the number entering, and by measuring only one portion of our effect, the US government necessarily got a biased picture of our effect. The CIA has confirmed that the number of active terrorist in Iraq rapidly increased rather than decreasing through the first years of the Iraq war.
This general idea carries over into all sorts of arenas. When a giant old tree falls, it makes space for hundreds of seedlings. When I comb my cat to remove loose hairs, I loosen lots more hairs and possibly even stimulate increased hair growth. WWII caused far fewer deaths of US soldiers than the ensuing baby-boom caused births of US babies. Eating all the chocolate so that my wife won't be tempted by it inspires her to go out and buy more chocolate. Responding to all the emails I should have responded to a long time ago brings in even more emails that need to be responded to.
Elastic replacement seems to be an extremely common class of unintended consequences. Humans don't seem to be good at considering it, but we should try.
This general idea carries over into all sorts of arenas. When a giant old tree falls, it makes space for hundreds of seedlings. When I comb my cat to remove loose hairs, I loosen lots more hairs and possibly even stimulate increased hair growth. WWII caused far fewer deaths of US soldiers than the ensuing baby-boom caused births of US babies. Eating all the chocolate so that my wife won't be tempted by it inspires her to go out and buy more chocolate. Responding to all the emails I should have responded to a long time ago brings in even more emails that need to be responded to.
Elastic replacement seems to be an extremely common class of unintended consequences. Humans don't seem to be good at considering it, but we should try.
Saturday, April 11, 2009
Making progress
Writing a paper is an iterative process. Figure out what my point is, start writing, change my point, adjust my writing, repeat. The process of rewriting the methods makes me realize it would be better to analyze the data a different way, so I do the analysis over which makes me realize that I need to modify not only my methods but also my conclusions. The new conclusion requires an additional analysis and therefore a further modified conclusion. Writing is very much like sculpture in that it is not so much a question of getting it perfect as getting it good enough that it isn't worth changing.
Friday, April 10, 2009
Fertility v. Fecundity
Fertility and fecundity are two closely related concepts.
One means the physiological state of being able to have offspring, the other means the state of actually producing offspring. In a population of 26 year old human females, 95% might be physiologically capable of giving live birth, while perhaps only 10% might actually have a baby that year. So fertility and fecundity are different. The problem is, which is which?
Demographers refer to the ability of have babies as fecundity, and the rate at which women actually have kids as fertility. Biologist do the opposite, saying that fertility is the capacity and fecundity is the realization.
This is just a quaint fact in academic linguistics until one tries to write papers and give presentations that will sit well with both demographers and biologists. Biologists think it is totally unreasonable to adopt the linguistic oddities of the social scientists, and demographers are not happy about people reversing the meaning of these terms. I usually go with the demographer's lingo. They are the ones who employ me.
One means the physiological state of being able to have offspring, the other means the state of actually producing offspring. In a population of 26 year old human females, 95% might be physiologically capable of giving live birth, while perhaps only 10% might actually have a baby that year. So fertility and fecundity are different. The problem is, which is which?
Demographers refer to the ability of have babies as fecundity, and the rate at which women actually have kids as fertility. Biologist do the opposite, saying that fertility is the capacity and fecundity is the realization.
This is just a quaint fact in academic linguistics until one tries to write papers and give presentations that will sit well with both demographers and biologists. Biologists think it is totally unreasonable to adopt the linguistic oddities of the social scientists, and demographers are not happy about people reversing the meaning of these terms. I usually go with the demographer's lingo. They are the ones who employ me.
Sex-biased longevity
Ive spent much of the last couple of weeks working on a paper on sex-biased longevity in primates.
Here is a draft of a portion of an introduction to said paper. Any similarities between this and the final published paper are purely coincidental:
The difference in longevity between the sexes of a population depends upon the selective forces each sex experiences, as well as the degree to which common genetic material limits independent demographic evolution. Sex-biased longevity has been proposed to arise from difference between the sexes in selective forces as diverse as reproductive physiology, care of offspring, parasite risk, mortality associated with reproduction, genomic stability and late-life support from kin. But measurements of sex-biased longevity have been made for relatively few species, and we have little sense of the degree to which sex-biased longevity is constrained by shared genetics or phylogenetic conservatism.
Most organisms, and likely all mammals, experience an evolved rapid increase in mortality and decrease in fertility at advanced ages, limiting longevity. The force of selection against mortality at a given age depends upon the likelihood of surviving to that age, and the mean remaining reproduction of individuals who do survive that long. Reproduction and survival are expected to drop to zero at similar ages, but reproduction can be direct (fertility) or indirect (care of offspring and kin effects).
Captive populations, the source of most demographic data on non-humans, will reflect sex-differences in evolved capacity for longevity more so than do wild populations, which tend to die younger (there are exceptions). For understanding the influence of experienced mortality patterns on evolved capacity for longevity, it is useful to make the distinction between extrinsic and intrinsic mortality. Extrinsic mortality is generally said to be that caused by the environment, while intrinsic death is driven by a failure of the organism's internal processes. In practice this distinction is difficult to make, as all environmental risk is influenced by the organism's characteristics and behaviors, and the timing and risk of intrinsic failure is inevitably influenced by an organism's history and environment. None-the less, much of our theory on the evolution of longevity is based on this intrinsic/extrinsic distinction. In general higher extrinsic mortality will lead to increased intrinsic mortality. However increased extrinsic risk at age x will influence evolved mortality at many ages, and not necessarily lead to a spike in intrinsic mortality centered at age x. This leaves overall sex-biased longevity as our best measure of sex-biased mortality when employing data from captive populations. Sex-biased longevity in captivity is highly correlated with sex-biased longevity in the wild even though the causes and timing of mortality may vary between species.
Much of the discussion of sex-biased longevity has focused on the idea that if one sex provides extended care to descendants, that sex should gain greater selective benefit from increased longevity. Allman et al. suggest that in primates, males who are the primary caregivers tend to live as long or longer than their females, while in species with little paternal care females tend to live longer. The Grandmother Hypothesis and its derivatives use indirect reproduction by post-menopausal women to explain their post-reproductive lifespan and therefore their tendency to live longer than men despite earlier decline in fertility. The Patriarch hypothesis instead argues that women's post-fertile survival is explicable based on late-life reproduction in males and the non-independence of male and female longevity.
Sex-biased longevity can also result from differences in mortality risk between the sexes. Trivers proposed that in species with frequent or intense male-male conflict, males incur significant mortality risk and therefore don't live as long as females. Alternatively, if females experience increased mortality in producing or rearing young, males should be expected to live longer. If either sex is the predominant disperser, and mortality risk during dispersal is high, this too could cause inter-sex differences in capacity for longevity. Finally, a variety of hypotheses have been put forward arguing that either the larger sex, or the smaller sex, should tend to live longer.
Using comparative primate life-history data, we examine the variability of sex-biased longevity in primates. We further examine the degree to which level of paternal care, grandmaternal care, male-male conflict, and mass dimorphism predict sex-biased longevity. Finally, we examine the patterns of correlated evolution among these variables in a phylogenetic context.
Here is a draft of a portion of an introduction to said paper. Any similarities between this and the final published paper are purely coincidental:
The difference in longevity between the sexes of a population depends upon the selective forces each sex experiences, as well as the degree to which common genetic material limits independent demographic evolution. Sex-biased longevity has been proposed to arise from difference between the sexes in selective forces as diverse as reproductive physiology, care of offspring, parasite risk, mortality associated with reproduction, genomic stability and late-life support from kin. But measurements of sex-biased longevity have been made for relatively few species, and we have little sense of the degree to which sex-biased longevity is constrained by shared genetics or phylogenetic conservatism.
Most organisms, and likely all mammals, experience an evolved rapid increase in mortality and decrease in fertility at advanced ages, limiting longevity. The force of selection against mortality at a given age depends upon the likelihood of surviving to that age, and the mean remaining reproduction of individuals who do survive that long. Reproduction and survival are expected to drop to zero at similar ages, but reproduction can be direct (fertility) or indirect (care of offspring and kin effects).
Captive populations, the source of most demographic data on non-humans, will reflect sex-differences in evolved capacity for longevity more so than do wild populations, which tend to die younger (there are exceptions). For understanding the influence of experienced mortality patterns on evolved capacity for longevity, it is useful to make the distinction between extrinsic and intrinsic mortality. Extrinsic mortality is generally said to be that caused by the environment, while intrinsic death is driven by a failure of the organism's internal processes. In practice this distinction is difficult to make, as all environmental risk is influenced by the organism's characteristics and behaviors, and the timing and risk of intrinsic failure is inevitably influenced by an organism's history and environment. None-the less, much of our theory on the evolution of longevity is based on this intrinsic/extrinsic distinction. In general higher extrinsic mortality will lead to increased intrinsic mortality. However increased extrinsic risk at age x will influence evolved mortality at many ages, and not necessarily lead to a spike in intrinsic mortality centered at age x. This leaves overall sex-biased longevity as our best measure of sex-biased mortality when employing data from captive populations. Sex-biased longevity in captivity is highly correlated with sex-biased longevity in the wild even though the causes and timing of mortality may vary between species.
Much of the discussion of sex-biased longevity has focused on the idea that if one sex provides extended care to descendants, that sex should gain greater selective benefit from increased longevity. Allman et al. suggest that in primates, males who are the primary caregivers tend to live as long or longer than their females, while in species with little paternal care females tend to live longer. The Grandmother Hypothesis and its derivatives use indirect reproduction by post-menopausal women to explain their post-reproductive lifespan and therefore their tendency to live longer than men despite earlier decline in fertility. The Patriarch hypothesis instead argues that women's post-fertile survival is explicable based on late-life reproduction in males and the non-independence of male and female longevity.
Sex-biased longevity can also result from differences in mortality risk between the sexes. Trivers proposed that in species with frequent or intense male-male conflict, males incur significant mortality risk and therefore don't live as long as females. Alternatively, if females experience increased mortality in producing or rearing young, males should be expected to live longer. If either sex is the predominant disperser, and mortality risk during dispersal is high, this too could cause inter-sex differences in capacity for longevity. Finally, a variety of hypotheses have been put forward arguing that either the larger sex, or the smaller sex, should tend to live longer.
Using comparative primate life-history data, we examine the variability of sex-biased longevity in primates. We further examine the degree to which level of paternal care, grandmaternal care, male-male conflict, and mass dimorphism predict sex-biased longevity. Finally, we examine the patterns of correlated evolution among these variables in a phylogenetic context.
Thursday, April 09, 2009
Tour of Science!
Walking back to the Valley Life Sciences Building this afternoon, I passed a large tour group of high-school students and their parents being led by an undergraduate. One mother, snickered into her cell phone, "they have an heeeeerb lab. They study herbs. This place is crazy. Crazy! No, no, no, the tour guide said they had a whole museum of herbs. I'm like what, parsley?!"
It took me an instant to figure out that she was talking about the University and Jepson Herbaria, a research museum dedicated to the study of plants generally, not culinary herbs in particular.
I emailed this story to the other grad students in my department. Many of them responded that they had heard the tour guides telling the tour groups all sorts of misleading and false information, including that a herbarium is a museum for studying cooking herbs.
Here are some other examples of overheard falsehoods made up by university tour guides to impress their tour groups and relayed to me by other grad students. Several of these things were independently reported by more than one observer:
- The Cretaceous display in front of the Herbaria contains extinct plants... Berkeley scientists rediscovered their ancient DNA, amplified it, germinated seedlings, and planted them there for museum visitors. (The display is of plants of types similar to those which existed during the Cretaceous, none of which have ever been extinct)
- The T. rex may be as many as 5 million years old. (It is at least 65 million years old)
- The T. rex came to the paleontology museum in a giant puzzle
box and when it got here, the paleontologists didn't know what to do with
it. One of the employees was about to get fired but he was able to figure
out how to put it back together so he was able to save his job. This man
is now the assistant director of the museum. (A complete fabrication, truth here)
- The T. rex is named "Osborn". (Sue)
- T. rex (the species) was discovered by Berkeley paleontologists. (False)
- Most of the UCMP fossils are actually in the Campanile. (False)
- UCMP geologists discovered asteroids. (False)
- The giant ammonite in the first floor south hallway is from a time on
Earth where everything was giant, even the snails. (Hilarious and false)
- The Herbaria is home to the world's largest pinecone, but they don't put
it on display because they are worried someone will steal it. (Goofy and false)
- The Herbaria has one example of every plant species known to man. (They wish)
- The plants outside the herbaria went extinct around the time T. rex went
extinct. (False)
- MVZ scientists save stem cells from each animal they capture in order to
help genetically engineer new animals to save endangered species from
going extinct. (And then we take over the world!)
- The Eucalyptus tree is native only to Berkeley, Australia, and New Zealand. (actually only Australia, New Guinea, eastern Indonesia and the Philippines)
- The Eucalyptus grove is protected by an Act of Congress and can never be
cut down for any reason. (Pure fabrication)
- Strawberry Creek used to flow all the way to the Ocean but then they
built roads over it and then there wasn't enough water so all the
strawberry plants that used to grow next to it died off. (A large portion of Strawberry creek between campus and the bay has been undergrounded. The rest is false.)
- The pterodon skeleton is hanging above the T-rex because they always flew over the T-rexes to keep them in view so the T-rex couldn't sneak up on them. (Awesomely hilarious)
It took me an instant to figure out that she was talking about the University and Jepson Herbaria, a research museum dedicated to the study of plants generally, not culinary herbs in particular.
I emailed this story to the other grad students in my department. Many of them responded that they had heard the tour guides telling the tour groups all sorts of misleading and false information, including that a herbarium is a museum for studying cooking herbs.
Here are some other examples of overheard falsehoods made up by university tour guides to impress their tour groups and relayed to me by other grad students. Several of these things were independently reported by more than one observer:
- The Cretaceous display in front of the Herbaria contains extinct plants... Berkeley scientists rediscovered their ancient DNA, amplified it, germinated seedlings, and planted them there for museum visitors. (The display is of plants of types similar to those which existed during the Cretaceous, none of which have ever been extinct)
- The T. rex may be as many as 5 million years old. (It is at least 65 million years old)
- The T. rex came to the paleontology museum in a giant puzzle
box and when it got here, the paleontologists didn't know what to do with
it. One of the employees was about to get fired but he was able to figure
out how to put it back together so he was able to save his job. This man
is now the assistant director of the museum. (A complete fabrication, truth here)
- The T. rex is named "Osborn". (Sue)
- T. rex (the species) was discovered by Berkeley paleontologists. (False)
- Most of the UCMP fossils are actually in the Campanile. (False)
- UCMP geologists discovered asteroids. (False)
- The giant ammonite in the first floor south hallway is from a time on
Earth where everything was giant, even the snails. (Hilarious and false)
- The Herbaria is home to the world's largest pinecone, but they don't put
it on display because they are worried someone will steal it. (Goofy and false)
- The Herbaria has one example of every plant species known to man. (They wish)
- The plants outside the herbaria went extinct around the time T. rex went
extinct. (False)
- MVZ scientists save stem cells from each animal they capture in order to
help genetically engineer new animals to save endangered species from
going extinct. (And then we take over the world!)
- The Eucalyptus tree is native only to Berkeley, Australia, and New Zealand. (actually only Australia, New Guinea, eastern Indonesia and the Philippines)
- The Eucalyptus grove is protected by an Act of Congress and can never be
cut down for any reason. (Pure fabrication)
- Strawberry Creek used to flow all the way to the Ocean but then they
built roads over it and then there wasn't enough water so all the
strawberry plants that used to grow next to it died off. (A large portion of Strawberry creek between campus and the bay has been undergrounded. The rest is false.)
- The pterodon skeleton is hanging above the T-rex because they always flew over the T-rexes to keep them in view so the T-rex couldn't sneak up on them. (Awesomely hilarious)
Tuesday, March 17, 2009
Decide what your point is before you write
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.
• 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.
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.
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