Behavio(u)r defined.

Published in this month's Animal Behaviour. British spelling.

Behavioural biologists do not agree on what constitutes behaviour

Daniel A. Levitis, William Z. Lidicker Jr. and Glenn Freund

"Behavioural biology is a major discipline within biology, centred on the key concept of ‘behaviour’. But how is ‘behaviour’ defined, and how should it be defined? We outline what characteristics we believe a scientific definition should have, and why we think it is important that a definition have these traits. We then examine the range of available published definitions for behaviour. Finding no consensus, we present survey responses from 174 members of three behaviour-focused scientific societies as to their understanding of the term. Here again, we find surprisingly widespread disagreement as to what qualifies as behaviour. Respondents contradict themselves, each other and published definitions, indicating that they are using individually variable intuitive, rather than codified, meanings of ‘behaviour’. We offer a new definition, based largely on survey responses:

Behaviour is the internally coordinated responses (actions or inactions) of whole living organisms (individuals or groups) to internal and/or external stimuli, excluding responses more easily understood as developmental changes.

Finally, we discuss the usage, meanings and limitations of this definition."

Demography of Islamic Extremism

The size of any population is determined by births, deaths, immigrations and emigrations.

Change in population= Births-Deaths+Immigrations-Emigrations.

This is one of the first facts mentioned in any class or text on demography, and is so obvious that we often simply take it for granted. But like many concepts which are obvious in context, this can be easily forgotten.

I am thinking here particularly of the population President Obama refers to as "Islamic Extremists." What determines the global population of these extremists? We can assume that no one is born as a violent extremist, so it isn't births. The Bush administration tended to assume the population of extremists was a declining stock, whose numbers would be determined primarily through deaths. We saw how well that worked out. What the Obama folks seem to understand, and what I believe to be the goal of much of the US's redirected foreign policy and rhetoric, is that the number of violent extremists in the world is determined primarily through immigration (recruitment) and emigration (defections, retirements, going homes, laying down of arms).

Let's assume, again that no one is born a violent extremist. Let's further assume that 1% of the world's 1.5 Billion Muslims have the backgrounds and personality traits such that the proper circumstances could push them to violent extremism. We estimate 15 Million potential extremists. What proportion of those will turn to violent extremism at any one time? The answer is clearly a very small. Depending on how we define our terms, maybe there are 150,000 violent Islamic extremists in the world today. That is if we add together the Taliban forces, al Qaeda, al Shabab, Hamas fighters, Hezbolah fighters and so forth. It is a rough estimate, but will do for now. We estimate that 1% of 1% of the worlds' Muslims are violent extremists.

What if, instead of 1% of potential extremists becoming actual extremists, 2% were? Then we double the number of extremists, to 300,000. If only 0.5% of those with the potential for extremism experienced circumstances causing them to act on that potential? Then we have 75,000 extremists, and our problem of eliminating extremists is half solved.

Nothing the US does is going to kill 75 thousand extremists, or 150 thousand extremists. Not that the US military isn't still trying to kill as many violent extremists as possible, but we seem to kill maybe five thousand a year, if we are lucky. Let's look again at our equation and start plugging numbers into it.

Change in population= Births-Deaths+Immigrations-Emigrations.
Change in population= 0-5000+Immigrations-Emigrations.

Let's plug in numbers for the two scenarios we outlined above.

Change in population= 0-5000+150,000=145,000
Change in population= 0-5000-75,000= -80,000

The number of extremists killed is largely irrelevant in these two scenarios. If we kill 15,000 instead of 5,000, we end up with
Change in population= 135,000 or -90,000

The potential fluxes through immigration and emigration are just so much bigger than the number we kill. Nor are these numbers necessarily independent. One can easily imagine that if brother A has the capacity to be a violent extremist, brother B is more likely than average to have the same capacity. Killing A may increase deaths by one, but it may also increase immigrations by one. If there is a brother C, it may increase immigrations by two.

The point of all this is to say that the most effective way to manage the population of violent extremists is decrease their recruiting and increase the number of their colleagues who go home. Killing them is useful in limiting the damage they can do, reducing their moral and providing alternative opportunities to those who could join them. But the number killed is far less important than the effect that that killing has on recruiting and defections.

I could get into a long discussion of what I think will ultimately influence that (Immigration-Emigration) term, but I won't, as that would stray too far from anything I have any scientific basis for considering. Rather I will simply say that I think the US government has finally caught on that the conditions determining (Immigration-Emigration) are far more important than the number killed, and I think this is a key insight.

Scientific publishing after paper

Yesterday I submitted a paper to the Proceedings of the National Academy of Sciences. Like most high profile journals they have strict page limits, and my paper was carefully planned to be just under the limit. I got an email from them today saying that they had recently changed the format in which references are given in the journal, and I would have to use the new, longer, format, and resubmit. I had 65 references, so the longer format made my paper half a page too long, which means I have spent the morning making the paper shorter again.

All this has got me thinking about the future of publishing, as fewer and fewer people read their journals on actual paper. The traditional justification for page limits, and a lot of the other rules journals have, was that it cost the journal money to print the extra pages, or the color, or figures above a certain size. Several journals, including PNAS, have even offered authors the option of going over the page limit or adding colors, but paying the extra printing costs. What happens to these limitation as fewer and fewer subscribers bother with the paper edition, and almost everyone goes straight to the digital version?

We are not near abandoning the paper journal yet. Even journals that start out as internet only, as PLoS did a few years back, often end up printing a paper edition because libraries and some readers (especially the older and more established) really like have a paper journal to thumb through. But this is changing. I, and most researchers my age, read almost everything from a digital copy. Some people print out the individual articles they want to read, others read from a screen. It is rare to see anyone my age or younger reading from a bound print journal, unless of course it is one of those rare journals that isn't available online. It is becoming increasingly common for libraries, to save shelf space and money, to provide access to only the digital copies of the less frequently read journals. There are journals which can only be found online, and I suspect their number will increase rapidly over the next decades. These journals (e.g. JoVE) can be far more multimedia than the old ink on rectangle.

So far, this seems to be having relatively little effect on the page limit. Journal editors want authors to get to the point, even if they don't have to worry about the cost of paper and ink. Journals are increasingly offering the option of accompanying the paper with supplemental online material. Those experimental protocols, that video sequence, the large table and the mathematical appendix can all be posted online, with the permalink listed in the main paper and hyperlinked directly from the digital versions. PNAS allows up to ten such files, and the length of all these add-ons often surpass the article itself, but without busting the page limit.

Annoying as it is to have to go through and find three more lines of text to cut to get down to that page limit, I suppose I should be happy that the page limit will be around long after the page itself has gone the way of the mimeograph. I don't want to have to read as much as all those people would write.

I do think the journals themselves will last, even if only online. Someone has to organize the peer review, and everyone needs to have a limit on the number of places they need to look to find relevant papers. I doubt I will see the day when one can be a successful scientist just by uploading my own work onto my own website and inviting people to read it.

A lack of enemies

I am working on submitting a paper to the Proceedings of the National Academy of Sciences. They ask that I suggest editors and reviewers who are qualified to evaluate my paper. They also give me the option of listing a few people who I want to not be given the chance to peer review my paper. I assume this is so that if two authors have written on the same topic, and clashed on that topic, one can't keep the other from publishing by writing very negative reviews. It is a way to ask that your paper not be sent to your rival and then treated unfairly.

There are people whose previous conclusions I disagree with, but nobody I can think of who I have any reason to believe would treat my paper unfairly. I haven't been in the field long enough or published enough papers to make enemies yet. Something to look forward to, I guess.

The University that Was

The University of California at Berkeley has long claimed, with reasonable justification, to be the world's top public University. The University of Massachusetts has some very good campuses, but they have never been any challenge to Harvard. The University of Connecticut is no Yale. But Berkeley and Stanford have often been considered on equal footing (or rather people at Berkeley thought Berkeley was clearly better and people at Stanford held the opposite opinion). In terms of prestige of faculty, Nobel Prizes won, National Academy members, number of important scientific publications, number of top-ranked programs and so on, Berkeley has long been among the US's top universities and far and away the best among the public institutions. California, historically a big wealthy state with a high standard of living and strong emphasis on education, made Berkeley the jewel of its enormous system of public education.

Berkeley now has this wonderful global reputation, amazing arsenal of high-powered faculty, several former faculty in high positions in the Obama administration and world-class facilities. It also has a crushing budget shortfall coming on top of several years of budget cuts, pay for grad students and many staff that is well below what the university considers a living wage, the expectation of massive staff layoffs in the near future, vanishing budgets for maintenance, supplies and support and deep sense that things are going to get a lot worse before they get any better.

The voters of California, in their wisdom, have used the state's mechanisms for direct democracy to require spending increases, but forbid tax increases. They have amended the state constitution to dictate budget items and make it enormously difficult to pass a budget. They have elected politicians based on looks and swagger and reacted with petulance when those politicians had more looks than brains. The state government has deteriorated to the point that most state spending not mandated by ballot initiatives will need to be completely cut. The budget for higher education is expected to be cut by about $1 Billion for the next school year. Similar shortfalls are expected until the global economy has rebounded, or the state constitution has been scraped and more workable one written.

Berkeley, I think it is safe to say, will not retain its reputation for excellence if this goes on for long. For some years now, as the budget has worsened, Berkeley has had a tougher time attracting the most competitive faculty. Many faculty searches have been canceled, and those which weren't often ended up offering positions to researchers who went for much better deals at private institutions. Berkeley has also been having trouble recruiting grad students. My department this year had six first year grad students enter and 17 PhDs graduate. Administrative departments are being eliminated or combined. Journal subscribtions are being scalled back. Phone lines are being turned off. Scholarships are being eliminated. It's ugly, and likely to get uglier fast.

I suspect that given a few years the economy will improve, and the budgetting process in California will be reformed, and Berkeley's budget will start to improve. I fear that by the time that happens Berkeley will have lost its global reputation, many of its most famous faculty, and its culture of intellectual greatness. UC Berkeley may from now on be just a very good public university.

Forthcoming paper

The paper I wrote with two colleagues on how biologists define the word behavior should be coming out in Animal Behaviour in June or July. I am guessing it is the first article to appear in that journal to reference both a supreme court decision and a Sherlock Holmes mystery. I am certain it is the first one to tell behavioral biologists that they don't agree on what they mean by 'behavior.' I am very curious to see how it will be received.

Adaptive male lactation?

It has long been known that male mammals, including male humans, are physiologically capable of lactating. Screw with a man's physiology by giving him the right hormones, or the wrong series of starvation and then plenty, and he may start to produce milk. No one, as far as I know, has ever suggested that this is adaptive, that this capacity exists because men gain some reproductive advantage through lactation. Rather, it is usually seen as a result of the fact that we share almost all of our genetic material with females, who do make good use of their lactational prowess. Male lactation across the mammalian world is largely thought to be a side effect of intersexual correlation, the tendency for the two sexes of a species to have similar traits.

I am therefore skeptically excited to read that males of two species of fruit bats, one in Malaysia, and one in Papua New Guinea, are said to have "well-developed lacteriforus ducts and underlying mammary tissue similar to that found in lactating females" and that milk has been "expressed" from a large number of male bats.

It is not actually known whether these males are feeding young, and if so how commonly and to what effect, but this is the closest suggestion I have yet seen of the possibility of adaptive male lactation.

Hobbits had big odd looking feet.

Well, duh...

Next they'll discover that Homo floresiensis were fond of tea cakes and lived in holes with circular green doors.

The Free Encyclopedia and 'Hairless' Apes

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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)

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.

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.

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.

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.)

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.

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.

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.

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.

Happy Birthday!

By the time Darwin was my age, I wasn't born for another 169 years!

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Why most scientists are not poets

As I try to write my thesis, I am coming to a realization. Writing complex scientific chains of thought in a way that is both clear and interesting is hard. Much harder than the natural history writing I have much more experience with. One of the many reasons this is so is because scientific writing must rely almost entirely on sentence meaning rather than speaker meaning. My wife, a linguist, has helped me to appreciate the difference. Sentence meaning is the information actually contained in the words of the sentence, accessible without knowledge of the thought processes or social context of the speaker. If a young man says, "Oh, I hate spiders!" the sentence meaning is simply, "I hate spiders." However, if the young man has just been asked to help clean out a garage, walks into the garage, looks around, then turns to the person who asked for his help and says, "Oh, I hate spiders!" much more is conveyed. The young man is not just signaling his dislike of spiders, but also that he has detected spiders in the garage, and is therefore reluctant to help with the cleaning. He may even be conveying that while he doesn't want to help he is a friendly person and therefore is reluctant to refuse outright, but please take this hint. This additional information, the speaker meaning, is nowhere in the text of his words, but is obvious to most humans who have healthy social comprehension skills. Much of the artistry of writing is in the careful crafting of speaker meaning. Beautiful writing, poetry in particular, generally conveys far more through speaker meaning than sentence meaning. But scientific writing by tradition and necessity relies almost entirely on sentence meaning. If any piece of information or logic is a necessary part of a scientific argument, the author has little choice but to state it outright. Likewise, if something has not been stated, scientific authors generally cannot assume the reader knows or agrees with it. This of course goes only so far. Scientists, as humans using human languages, are incapable of avoiding speaker meaning entirely. But the injunction is clear: thou shalt not ask thine audience to read between the lines.

Writing a complex chain of mathematics laced evolutionary thought in a way that is readable and elegant is a real challenge. I begin to understand why so many scientists over the centuries have largely let elegance and readability fall by the wayside. I very much hope to avoid following that clearly but unattractively marked trail.

Students

One of the great things about having lots of students involved in my research over the last few semesters is that the ones who aren't that interested tend to drift away and the ones who are really interested and energetic keep coming back for more. It is like a distillation process where now, my last semester in grad school, I have this awesome group of highly motivated students and very few who are just along for the ride. It makes me happy.

Very rough section of a very rough draft.

Today between 11 and midnight I wrote a very rough section of a section of a rough draft of one of the several papers that will go into my thesis. Feels like progress. I don't expect to have much time for blogging over the next few months, but I will try to post bits like this that are potentially interesting, and that show what efforts keep me from having time for blogging.

The Measurement of Post-Reproductive Lifespan
Advancement in the study of PRLS has been hampered by differences over terminology, the use of a wide range of non-comparable measures and the failure to put measures of the scale of PRLS in the context of the time scales on which the organisms live.

Some authors have used the term "post-fertile" rather than "post-reproductive" arguing that anything that an organism does that increases her genetic representation in future generations is a form of reproduction, and that "post-reproductive" is therefore an inaccurate term to apply to post-fertile individuals who are still caring for their young (REFS). Indeed Hamilton (1966) argues that, "if the organism practises parental care 'birth' should be considered to occur... at the age at which the offspring becomes independent." While not disputing the biology behind this argument, we feel that the term "post-reproductive" is deeply enough ensconced in the literature on this topic that the use of alternative terminology to convey the same concept may tend to muddy communication. For this reason we use the term "post-reproductive" to refer to life after direct reproduction (fertility), excluding indirect reproduction (care of young and indirect fitness benefits).
Beyond semantic disagreements, so many methods have been used to calculate the scale of PRLS that efforts at comparisons across species and studies have been few and confusing. For example, XXXX and ZZZZ (REF) present a table of PRSL for 12 primate species, all given in units of years, but calculated in six different ways. Disagreements exist as to how to define the end of reproduction, how to determine the end of survival, and which individuals to include. The measures vary because the type of data used vary, and the interests of the authors vary, figuratively leading to comparisons of the shelf-life of apples to the refrigerator hardiness of oranges. The effect of sample size on these estimates is generally not addressed.
Even when these drawbacks are not found, authors generally fail to correct for the overall longevity of the species in question. One should expect a species that lives 100 years to, on the average, experience more years of PRLS than a species that lives 20 years. Without a denominator related to the time scale of the organism's life history, the numerator of PRLS is fairly uninformative.

In this study, we use a type of data that allow for broad comparability: age specific mortality and fertility figures as calculated in standard demographic methodology. Because the form of the data is highly standardized, the same measures can be calculated across taxa, for males and females, and in a wide range of environments. The use of data sources as information rich as are age specific mortality and fertility tables allows for the use of multiple measures which illuminate different aspects of PRLS, but which need not be falsely compared to each other, because we can calculate every measure for each population for which these data are fully available. Furthermore, the use of age-specific demographic tables allow us to put our measures of PRLS in the context of the reproductive and actuarial longevity of the organisms, allowing for meaningful comparisons between populations with very different lifespans.

New York's Geese are exploding in another way

The Christmas Bird Count is one of the great success stories of Citizen Science. Every year in late December, tens of thousands of volunteers across North America brave snow and sleet and Christmas Shopping traffic to go out and see how many birds they can see. Everyone writes down how many individual birds they see of each species, and where they were looking, and all these data are collected into a central database. The Audubon Society's scientists know how many people were looking, and where, and they have large numbers of observers, so they can calculate pretty reliable winter range maps, and calculate rates of population change in each area.

Looking at their data for Canada Geese, a pretty remarkable number emerges. The number of Canada Geese in New York State in December has, for quite a while, been increasing by 22% per year! At that rate of increase, population would double about every three and a half years (1.22^3.5=2), and the population doubled at this rate starting about 1955 and leveled off about 1990, so it had time to double about 10 times. 2^10=1024. So for every goose in New York in late December before the 1950s, there is now a kilogoose in the same area at the same season. To put it another way, most CBC observers in NY in the first half of the 20th century saw not one geese. The average NY state observer these days sees 50 or 60 geese.

Here is a graph from the CBC historical query page.


There is a lot of noise in the data, but the trend is very clear.

So why are there so many more geese in NY in the winter? Partly, there are just more geese everywhere. Humans have been good to Canada Geese. Lawns, golf courses and grain stubble are all feasts for geese. We've killed off a lot of the natural predators, and we don't hunt them ourselves as much as we used to. And New York winters aren't nearly as cold and snow-buried as they used to be, especially around the city, which means fewer of the geese bother migrating any further south than New York.

In considering the causes of the bird-plane collision that caused yesterday's much publicized crash, we should keep in mind that a few decades ago, there would have been no geese to hit in January above the Bronx.

Plane-Strike, not "Bird-Strike"

Yesterday a plane that had taken off from New York City was forced to make an emergency water landing shortly after take off. The reason given? "Bird-strike" on both engines minutes after takeoff. It seems quite likely that the cause was truly a collision between a flock of birds and the plane. But does it really make sense to call it "bird-strike?" Canada Geese, the type of bird mostly likely to have been involved, fly about 40 mph. The takeoff speed of an Airbus 320 is 170mph, its cruising speed above 500mph, and the plane was presumably somewhere between these two speeds when the collision happened. So the plane was probably going five to ten times as fast as the birds.

So saying that the birds "slammed into the plane" as some news sources have done is akin to saying, "the pedestrians slammed into the speeding tanker truck." The birds were relatively stationary and the plane plowed through them. All the humans survived. The birds got the worst of it. Not to imply that the people on the plane were at fault. Perhaps the pilot's instruments don't even register anything as small and dispersed as a flock of geese. But really, does it make sense to blame the geese?

Can't live with'em can't live without 'em.

Biologists and Ecologists have (mostly) learned to give at least some forethought to the consequences of introducing non-native species. The problems invasive species cause are often most sever on islands, where the native species often have limited evolutionary experience dealing with the relative of the invaders. For example, many island endemic bird species were flightless, as there were no land based predators to need to fly away from, so why bother building all that expensive escape equipment when there is nobody to escape from. Other island nesting birds, like those on Macquarie Island can fly (except the penguins) but don't seem to have the right tricks in their behavioral repertoires to escape from introduced predators.

A recent attempt to help these birds is making ecologists aware that one has to be very careful not only about introducing invasive species, but also about removing them. A commentary in Nature describes the story:

Cats were introduced to the Macquarie Island in 1818; sealers introduced rabbits 60 years later.

The rabbits tore through the island's vegetation. In 1968, the rabbit flea was introduced. Once that had established the lethal myxomatosis virus — which the flea spreads — was introduced in 1978.

Rabbit numbers crashed, but then the cats, which had previously eaten rabbits, switched their attentions to the island's birds.

But once the cats were gone, the few hardy rabbits that had survived both the cats and the myxomatosis emerged and began doing what rabbits do best — breeding and eating.

So the island has cats, rabbits, rabbit fleas, rabbit viruses as well as rats and mice, all introduced. The cats were bad for the birds because they ate them. The rabbits were introduced and were bad for the birds because they destroyed the vegetation, but good in that they distracted the cats. And the cats were at least partly good for the birds, because they ate the rabbits. Some kind of unstable plateau was reached. And then disease was introduced to reduce the rabbit population, leaving a whole bunch of hungry cats, which were bad for the birds. But then the cats were killed off, which was bad for the birds and everything else (except the rabbits, rats and mice) because for the first time there were rabbits without cats on the island. The rabbits, unchecked, ate through most of the island's plants. And this, of course, is a vast over simplification.

The Australian authorities who run Macquarie Island are now trying to figure out how to exterminate the rabbits, rats and mice without harming other native populations, such as the seals and sea lions that breed on the island. They estimate it will take tens of millions of dollars, and that may be optimistic. Few efforts to irradicate rodents from any land mass of decent size have succeeded. Macquarie Island, at 128 km², offers a lot of hiding places big enough for a rat. Miss one pregnant rat and in just few years you are back to square one. And who knows what effect the rats would have without rabbits around harboring disease and eating potential cover? Rats eat bird eggs, and have been known to finish off large bird colonies in just a few years.

The lesson learned is that just because introducing species is generally bad, removing those introduced species from an ecosystem that has started to adjust to their input isn't always good. At least it has to be done very carefuly.

If this science thing doesn't work out.....

As I've mentioned before, my cousin David is the National Sales Director at Ozone Socks. Ozone has a yearly sock design competition. I submitted three designs themed around (what else?) science.
I just got the call from David. He had to recuse himself from much of the judging, in order to avoid bias. He didn't even tell them I was his cousin, he claims. But my oceanic drawing, "30000 Feet" won second place. Iris will be so excited. We get 12 free pairs of socks.


Oh, and by the way. It is not at all certain they will actually make this sock. They have in effect purchased rights to my design for the price of 12 pairs of any socks they already make. If you want to see this sock made, and would purchase a pair, please contact@ozonesocks.com and tell them.

Just like old times, only with more world-savingness

My freshman year in college, my neighbor down the hall, the fellow in the picture above, was building a contraption that looked very much like this one, only much more home-made looking with various colors of extension cords, duct tape and PVC pipe. One end face the door of his room. The other pointed out his window, like a cannon out the gun port of a ship. I asked him if he was a pirate. We became friends anyway. He eventually explained that it was a sort of cannon, a "linear inductance accelerator." It used electrical current to induce electrical fields that accelerated little aluminum rings down the length of the gun and shot them out the window. They didn't shoot very fast or very far, but Stephen built the thing while he was in high school, mostly from stuff he scavenged from his parents' basement. When the campus security guards would do their once a semester safety checks of the dorm rooms, Stephen would put Christmas lights and stuffed animals all over it and tell them it was a sculpture project.

Stephen is one of those people who is instantly recognizable as brilliant. Walk into a room where Stephen is and try not to get knocked over by the slightest meanderings of his enormous brain. But in addition to intellectual brilliance, Stephen is incredibly tireless, multi-talented and helpful. He was known as the "campus super hero."

It was therefore with very little surprise then that I watched as Stephen got degrees in mathematics, physics, electrical engineering, plasma physics, then went to work for a company whose goal is to save the world by producing cheap clean electricity from hydrogen fusion. And the company Stephen went to work for is of course going to do it much sooner, cleaner and at 1/100th the cost of anything any government or university could think to try. The picture above is of Stephen working on a piston he designed for that fusion reactor, and is from an article in this month's Popular Science. The similarity to the linear inductance accelerator is mostly in my mind. I can tell the photo is posed, though, because Stephen is not grinning, which he normally would be when fine-tuning one of his machines.

Stephen, by the way is Stephen Howard, who has occasionally posted to this blog. These days he is too busy saving the world.

A tiger does not declare his tigritude, nor live in Africa.

Last night Iris, reading a book on French linguistics, came upon the word "tigritude." She asked me what it meant, and I Googled it. I came upon several references to a "Nigerian Proverb" stating that, "Un tigre ne proclame pas sa tigritude." (A tiger does not declare/proclaim/shout his tigritude.)

This stuck me as a useful saying, but something about it wasn't quite right. It took me until just now to remember. There are no tigers in Africa. Haven't been for at least a million years. Either that saying was handed down from before the time Homo sapiens existed, or it isn't a traditional saying from Nigeria.

I looked it up again, in more detail, and it is actually a quote, from the Nigerian author Wole Soyinka, whom Iris of course has read but I had never heard of.

It is funny how many people, including "proverb dictionaries" have labeled various versions of it as traditional Nigerian wisdom. Is "Happy families are all alike; every unhappy family is unhappy in its own way," an ancient Russian proverb?