Meiosis kills! (Now in print, and video)

Scientists are rarely dispassionate about their research. Why spend years trying to figure out the fine details of something you have no interest in? Before my wife and I lost two pregnancies, I had thought abstractly about the question of why developmental failure is so common across plants and animals, but it wasn't personal. I was interested in the fact that dying before reproductive age means an individual does not get to pass on whatever traits caused it to die. In other words, natural selection should quickly remove any heritable trait that commonly causes developmental failure. At the same time, pretty much any organism loses some of its offspring, implying some broad based mechanism WAS commonly causing developmental failure. I even went so far as to publish a review article focusing on what this mechanism might be.

But once developmental failure became personal, I wasn't just interested, I needed to know.  

The result of that impulse was just published by Proceedings B, one of my favorite scientific journals. 

In addition, I worked with Sarah Friedrich, the extremely talented Graphics Specialist in my department, to make this video explaining the science in public-friendly ways:

Who has an adaptive post-reproductive life-stage?

To establish a case for an adaptive post-reproductive life-stage, one needs to show (at least) the following things:

(1) Prevalence: Across environments, but especially in a wild or non-protected environment, the population experiences more post-reproductive lifespan than is expected due solely to demographic stochasticity.

(2) Utility: Post-reproductive individuals do something selectively advantageous, such as helping younger kin to survive or reproduce.

In many cases, one would like to also address

(3) Advantage: Those individuals who become post-reproductive have a selective advantage over same-age individuals who simply continuing reproducing indefinitely.

However, this third is more complicated, because in many cases there are no individuals who fail to stop reproducing to compare to. For example, 55 year old women giving birth are rare and not easily compared to those who stopped at a more usual time. So testing (3) requires extrapolation and counter-factuals. This assumes that if continuing to reproduce past the current age of cessation were selectively advantageous, that the species' reproductive physiology would allow for it. In many cases, theoretically advantageous traits simply don't exist in the population, and therefore cannot be selected for. If the choice is not between ceasing reproducing or continuing, but rather between ceasing and being useful or ceasing and not being useful, useful wins.

So we are left with basically two fairly simple tests to make decent case an adaptive post-reproductive life-stage. And after some decades of interest in the evolution of post-reproductive lifespan, for how many species has this case been convincingly made? By my count, three. Humans, orcas and a gall-forming social aphid, Quadrartus yoshinomiyai. There are several other likely candidates. Short-finned pilot whales, and possibly other social cetaceans. African and Asian elephants. But I've become very interested in a much more accessible and experimentally tractable species. It lives in multi-generational groups of (very) closely related individuals.  Individuals play subtly different roles in the group throughout their lives. Older individuals stop reproducing and can (assuming no one comes along and kills them) live for extended periods post-reproductively (on the time scale these things live). You may have it in your garden.

Any guesses? Later this week I'll give you the answer.

Breaking a truly ancient tradition

"Modal age at death" means the age at which the largest number of individual deaths occur. The modal age at death is determined by the interaction of two factors, the increasing risk to each individual with advancing age, and the decreasing number of individuals still alive with advancing age. As a population of adults gets older, each person is at ever increasing risk of death, so at first the number of deaths at each age goes up. But eventually, even though individual risk is still increasing, the number of people experiencing that risk is going down so fast that the number of deaths at each age (what demographers call dx) goes down. So modal age at death is neither at the age with the most individuals or the age at the highest risk, but somewhere in between. And studying the modal age at death, how it varies between populations and over time can tell demographers many useful things that I'm not going to go into because I am more interested in subverting the paradigm.

The paradigm in this case is that modal age at death is some time in early old-age, when death rate is going up but not too many people have died yet. Except that often it hasn't been. If one looks at life-tables for historical populations of humans, the highest dx (by far) is often d0, the number of individuals who die before their first birthday. Put another way, far more people died between birth and their 1st birthday than during any other year of age. The Human Mortality Database (the world's premier source for data on this sort of thing) estimates that of the baby girls born in Sweden between 1751 and 1759, slightly over 20% died in their first year. To put in perspective how the resulting distribution of deaths over age looks, please glance at this graph:

If I asked you to guess at what exact age a random female had died, by far your best guess would be age 0. And surely the people living in such a population must have been affected in all sorts of ways by the frequency that babies die. To ask how this population would have adjusted to such a thing is to ask a misleading question, because adjustment would imply that this is something new. In fact, the modal age at death is almost always 0, and modern humans are highly unusual in having it be much later in life. In fact, even in the cohort of Swedes born in the 1920s, modal age at death was still 0. In some countries it may still be 0, although such places are generally harder to get good demographic data from.

How far back does this go? Well it is 0 for hunter gather populations. It is zero for wild primates. It is zero for other mammals. It is zero for.... As far as I can tell, modal age at death has been zero for almost every population of almost every kind of organism for the entire history of life on earth. Contemporary wealthy humans still suffer much higher mortality in our first year than at any other pre-adult age, but infant mortality has been gradually brought down over the last centuries, so far that somewhere in the 1930s and '40s, many of the world's nations unknowingly broke with hundreds of millions of years of tradition by having a modal age of death that wasn't zero. So the right question to ask may well be not, "how did they adjust to zero being the mode?" but rather, "how are we adjusting to zero not being the mode?" And my impression is that one important way that we have adjusted is by very gladly forgetting that things were ever different than they are now.

Seen another way though, we haven't changed the modal age at death at all. If one is willing to classify the loss of an embryo or fetus as a death, modal age at death has never been zero. It has always been, and remains, -1. Minus one because far more individuals are lost in the year prior to birth (even if only nine months) than the year after it, or any other age. Where before many cultures avoided naming newborns until a week or month or even a year had passed, we still often avoid it for those not yet born, for the same set of emotional (some say superstitious) reasons.

Will science progress to the point that we feel safe naming that recently implanted embryo, knowing that she will almost surely make it? Perhaps. If so, modal age at death will finally, at long last, be in the age range that my demographer friends like to consider.

Knee deep in the fetid pools of evolution

I am, as I may have told you before, an evolutionary biologist at heart. And one of the things I love about evolution is how messy, random and complicated it is. Evolutionary outcomes aren't just survival of the fittest, but also reproduction of the luckiest and replication of the not overly deleterious. Natural selection often doesn't get its way and the optimal trait often doesn't exist or can't quite win out. Evolution is a box of dirty tooth-marked mismatched Legos with no instructions all in clumps from previous projects, and that is how I like my Legos

So I always enjoy talking with colleagues who really think about evolution in depth, not as a nice neat optimization process (which it isn't) or a collection of family tree (which it can be, but this misses the forest) but rather as the beautiful mucky anarchic tangled mess of genes, lineages, mutations and highly fallible biology that it is. Sure, there is a lot of phylogeny in there, and a bunch of natural selection, which to an extent can optimize things, but it is like optimizing the design of a boat when all you have to work with is coconut husks, maple syrup and a swarm of fire ants. It isn't so much optimization with constraints as a bowl of constraints with optimized sprinkles on top. To really capture the beauty of it you have to do away with the basically creationist notion that organisms are perfect for their niches and the anarchic view that biology follows the rules we write in text books. Organisms only breed with members of their own species, except when they don't, and clones are genetically identical to each other, unless you look closely.  Only changes to DNA are heritable, except those non-DNA heritable traits. Rules, broadly defined, do not apply to fungi. The dissertation that was defended from me this week showed that in real wild populations, genetic drift is sufficient to speed aging and shorten lifespan. These populations aren't short lived because there is something optimal about it, but rather because drift isn't letting selection have its own way. I'm oversimplifying, and you'll have to wait for the details to come out, but it is a wonderful example of evolution in its slip-shod Rube Goldberg glory.

I'd like spend more time with colleagues who think deeply about the gorgeous multi-layered sub-optimality of evolution. That's where the fun is.

Article in The Scientist

http://www.the-scientist.com/?articles.view/articleNo/37154/title/Why-Women-Lose-Fertility/

Egg-maculate conception

I've long said that if I was a benevolent deity the first thing I would do was give penguins the ability to produce live offspring at sea, the way whales and otters do.  My opinion has been that all birds lay eggs that need to be kept warm and be exposed to air, and no bird can give live birth, and therefore it would require the intercession of a god to produce a bird that could develop its eggs either internally or under (cold) water.

Well, that may still be true, but consider the following  from the BBC today:

'Eggless' chick laid by hen in Sri Lanka 

Instead of passing out of the hen's body and being incubated outside, the egg was incubated in the hen for 21 days and then hatched inside the hen.
The chick is fully formed and healthy, although the mother has died.

Let's assume for a moment that this is true, and neither a prank nor a misunderstanding. What seems to have happened is that the egg was retained inside the mother's reproductive tract. This (technically called dystocia) happens occasionally, especially to older hens. The egg just gets stuck, and usually eventually breaks and comes out in pieces, which can often kill the mother, and which also smells terrible, as the egg is usually quite rotten. But in this case it appears that the retained egg developed successfully, and the mother wasn't killed until the chick was viable. So assuming this is true, it is the first example of live birth in a bird I can find.

Now before all you penguins trade in your carefully maintained rock scrapes and hole-nests for shrines to the fertility god, keep in mind the following:
1. The mother died, probably quite painfully, and therefore is not around to feed the chick.
2. It would be hard for a trait like that to spread through a population, as each mother could produce only one offspring, and sexually reproducing mothers need to produce at least two adult offspring to reach replacement.
3. It probably isn't true anyway.

Still, it is an interesting story. If a group of birds could for some other reason first evolve to have un-calcified eggs, then it seems more likely that live birth would have a chance of evolving.

Evolutionary biology vs. evolved biology

Once, during a medical exam, the doctor asked me what I did. I said I was an evolutionary biologist, to which he replied, "oh, so not a creation biologist?" His tone of voice made it clear he thought it was funny that I had to specify evolutionary, as though a biologist in Berkeley could possibly not believe in evolution. Considering where his hands were at the time, I didn't stop to explain to him what the term "evolutionary biologist" means. Every biologist knows, or should, that Theodosius Dobzhansky wrote, "Nothing in biology makes sense except in the light of evolution." The vast majority of biologists, of all disciplines not only know about evolution, but accept it as a necessary part of any complete explanation for the things they study. But a large portion of biologists don't regularly think about evolution; it is not the part of the explanation they are interested in. A large (and I think increasing) proportion of biologists study the interactions of atoms, molecules, organelles, genes, cells, etc. And while they may connect their work to evolution in some way, they are not basically asking questions about evolution, but about the details of the proximate mechanisms which make organisms work. That these mechanisms are the result of evolution is often not particularly relevant to the present question.

An example: A couple of years ago I attended a workshop on bioinformatics in aging research. There was a dinner the night before the talks started, and the bioinformaticist organizing the workshop asked me about my training and research. I said, "well I study the evolution of demographic patterns, particularly how constraints on natural selection lead observed demographic patterns to differ from the predictions of evolutionary theory." He replied, "Oh, but you are also trained in biology?" What he meant by this, I discovered, was that I also had some training in the molecular nuts and bolts that to him are biology. Evolution is a process that shapes biology, but in his view, and I think the view of many of the people there, does not in itself count as biology. Asking him if he ever incorporated evolution into his work, he explained that he had, comparing how networks of gene interactions differed between fruit fly and nematode. Fair enough, comparative biology is surely the study of evolution, but his approach to it required no technique or concept from evolutionary theory. He produces good and useful science, and gives no more daily thought to evolution than I give to promoter regions. I am certain that he would not be offended to be described as a good biologist who believes in evolution, but is not an evolutionary biologist.

A definition from wikipedia: "Evolutionary biology is a sub-field of biology concerned with the study of the evolutionary processes that have given rise to the diversity of life." This is somewhat too narrow in my view, but it is close enough given that it is past my bedtime.

This has all come to mind because of the post I wrote yesterday, about weeds evolving resistance to Monsanto's best-selling herbicide, and the failure of Monsanto's biologists to predict this. A good friend of mine, who is deeply knowledgeable about matters environmental and agricultural, responded by asking how Monsanto's biologists could have failed to predict the apparently obvious facts I was pointing out unless they were A, Tools; B, Fools; or C, having their results manipulated by suits. This is a reasonable and interesting question, and I'll venture an answer. My guess is that they were neither A nor B, and that C went on but was not a major factor. Monsanto did have an enormous financial stake in convincing regulators that weeds would not evolve resistance to Roundup, but they also had an enormous stake in having weeds actually not evolve resistance to Roundup.  So my guess is they honestly thought it was a highly unlikely outcome.

Why did they think so, despite being smart, honest biologists? Because they weren't trained in, or primarily thinking about, evolution as it occurs in nature. They were plant geneticist and bioengineers, spending many years and countless millions of dollars to unravel the finest details of how Roundup kills plants and how to build a crop that will have resistance to it (without passing that resistance on to its offspring). That was an enormous challenge, and their success was unprecedented. They had achieved what many, even within their own company, must have thought was an impossible SciFi dream.

Surely someone was assigned to think deeply about the problem of whether weeds would evolve resistance, but surely that someone had been involved in the project for years, and was so wrapped up in the grotesque details of the genetic magic they had just achieved that no perspective was possible. In other words, they couldn't see the field for the soybeans. A person highly trained in artificial selection, and used to that way of thinking, will think of the evolution of weed resistance in those terms, despite the fact that natural selection has inherent advantages.

In hindsight, their logical errors are obvious, probably even to them. In foresight, reasonable and well intentioned people frequently fail to think of highly relevant and potentially obvious things. This is particularly likely if those things require a perspective they don't possess, doubly particularly if they are thinking deeply about the problem from a very different perspective. Monsanto had many biologists who knew about evolution, used a particular type of evolution as a tool, and thought about evolution. But my guess is they didn't have any evolutionary biologists.

Evolution infringes upon Monsanto's patent

NPR has a useful story today by a guy who interviewed people who were involved in Monsanto's application for release, in 1993, of "Roundup Ready" crops, that is crops that are genetically engineered to be resistant to Monsanto's best selling herbicide, glyphosate, sold as Roundup. The idea, which has made Monsanto many billions of dollars, is that if the crops are immune to the herbicide, and weeds are not, fields can be sprayed liberally. Farmers don't have to do mechanical weeding, and Monsanto gets to sell them both the patented herbicide and the patented resistant seed. This set of facts, along with Monsanto acting like the faceless corporate giant that it is in defending its patents, has made it probably the most despised company among the organic farming crowd, vilified far more than competitors like ADM or DuPont.

The point of the article is that Monsanto falsely rejected the possibility that carpeting the world in Roundup would lead to the evolution of Roundup resistant weeds.

Then the story, written by Daniel Charles, continues like so:

Oops. Since then, resistance to glyphosate has emerged in 20 different weed species.
  I called up several people who were at Monsanto at that time. Why didn't people there think resistance would happen? They all told a similar story.
First, the company had been selling Roundup for years without any problems. Second, and perhaps most important, the company's scientists had just spent more than a decade, and many millions of dollars, trying to create the Roundup-resistant plants that they desperately wanted — soybeans and cotton and corn. It had been incredibly difficult. When I interviewed former Monsanto scientists for my book on biotech crops, one of them called it the company's "Manhattan Project."
Considering how hard it had been to create those crops, "the thinking was, it would be really difficult for weeds to become tolerant" to Roundup, says Rick Cole, who is now responsible for Monsanto's efforts to deal with the problem of resistant weeds.

In case the holes in their logic haven't struck you, allow me to provide a quick lesson in how natural selection (or in this case semi-natural selection), as opposed to genetic engineering, works.

Engineers at Monsanto were surely aware of natural selection and its proclivity to producing resistant pests, but they considered the idea that there would be even a hint of heritable resistance in the weed populations to be highly unlikely. This is because they failed to consider the following facts:

A. They were testing thousands of highly targeted potential genetic alterations in the lab, on a few crop species, and found that almost none of them conferred significant resistance. They didn't consider that after global distribution of their crops, trillions of genetically distinct (although totally untargetted) genetic modifications (that is, natural mutations) in thousands of weed species would be tested for their resistance. When something potentially useful did pop up, Monsanto was again able to test hundreds or maybe thousands of slight modifications on that, while natural selection could within a few years test millions of potential modifications iteratively over several generations. So they didn't consider that nature's search for solutions would be far more exhaustive than theirs.

B. I'm sure engineers have a term for closely examining one type of failure risk while completely ignoring others. That's what Monsanto did. They were look hard at making plant tissue resistant.  From the same story:

Some weeds, Cole says, appear to keep glyphosate from entering the plant at all; others sequester the herbicide in a spot where it can't do much damage. Monsanto's genetically engineered crops use a different technique entirely.

So they didn't consider the possibility that some plants would simply shield their vital tissues from the toxin, the way many metal resistant plants do.

C. They assumed that because Roundup had been used broadly for several years already, and there were no known resistant weeds, weed populations simply had no resistance traits available for natural selection to favor. They failed to consider that with the introduction of their crops, and the resulting increase in usage, both the population size of the exposed weeds and the force of selection for resistance would increase dramatically.

The force of selection is a measure biologists use to ask the question, how much difference does a heritable change of a certain size in a trait (for example a 0.1% increase the probability of surviving a spraying with Roundup) make to the fitness of the individuals with that altered trait. So long as most individuals in a weed population were never exposed to Roundup, the force of selection for resistance to it was small. Resistance doesn't help much if you are never exposed. The seeds blowing into farmers fields were coming from unexposed sub-populations, and so were not resistant. When we started blanketing the world in Roundup, the force of selection increased, because most every weed subpopulation over huge areas was exposed. So their experience up to that point led them to underestimated the force of selection for resistance. And if there is one thing that evil empires should know, it is to never underestimate the force.

Undermining the Wall of Death

Different fields of science often don't talk to each other, even when coming at the same problem from different angles. A stark example of this can be found in the literature on aging. I'm in the field of evolutionary demography, and aging is one of our central focuses. We ask why and how it happens by studying the demographic patterns of different species under different circumstances. The evolutionary demographic theory of aging is built around the idea that there are alleles that have effects at different ages and natural selection acts on these genes to sculpt the age-specific mortality at different ages. Because dying young (before you've had a chance to reproduce) is more disadvantageous than dying old (after you've already passed on some genes) natural selection acts more strongly to minimize mortality in early adulthood than later adulthood, resulting in a chance of dying that increases in age. There are decades of theory built up around this idea, and the idea is not without merit, but it does assume these age-specific gene effects, generally without bothering to say what the actual genes are or how they influence mortality.

Another field within biology that focuses heavily on understanding aging is biogerontology. Biogerontology focuses on understanding the mechanistic basis of aging at the cellular and molecular level. They describe aging as a process of narrowing of the homeodynamic space, often due to accumulation of damage. Homeodynamic space is a concept related to homeostasis (the tendency of organisms to push their physiological state back to some optimum), but with the recognition that the goal that the individual is pushing towards, and its options for pushing, change over time. For example, as the cells in an organism accumulate mutations, it becomes more dangerous to allow them to continue replicating, because this could spawn a cancer. So the cells are forced to turn down expression of genes that allow for cell replication. But if your cells are replicating less, then you should be more reluctant to allow apoptosis, programmed cell death, because cells that die can't as easily be replaced. But if you've down-regulated the genes involved in apoptosis, this means infected cells will be less likely to kill themselves, so you need to have a stronger inflammation response, so that white blood cells will be brought to areas of infection and kill the infected cells from the outside. But increased inflammation has all sorts of nasty side effects, which themselves need to be compensated for. Note that I am just making this chain up as an example. The point being that the organism, in order to deal with the accumulation of damage, has to adjust various aspects of its physiology, which can cause damage or challenges to the system, which requires further adjustments. The organism gradually loses wiggle room, paints itself into a corner as it were. When this homeodynamic space gets too small, the organism can't respond to whatever insults (internal or external) come along and gets killed.

Reading papers in biogerontology, I am struck by two things. The first is how naive and outdated their evolutionary assumptions tend to be. For example, they still will state that aging is not observed in the wild because no individual lives long enough to grow old in the wild, an opinion that evolutionary biologists began to reject in the 1960s and have now disproved with data from numerous species from plankton to humans and birds to aphids. But I am also struck by how naive they would think our assumptions about age-specific genes are. They state as one of the basic principles of biogerontology that are no genes whose roll it is to cause aging, or which act at a particular age to regulate the chance of death. You will remember I said that such age-specific gene effects, from unspecified genes, are at the center of much of the theory behind evolutionary demography. Yet biogerontologists know such genes not to exist. So our assumptions about the mechanisms are as naive and simplistic as their assumptions regarding the demography.

This lack of communication, with each field basing its thinking on ideas the other has long since rejected, is common in science. There are simply too many journals, papers, conferences, etc., too many fields that may produce important information, for anyone to keep a useful fraction of an eye on most of them. So the lack of communication between fields is to some extent inevitable, but it does have significant consequences.

This is obvious when we introduce the gerontological observation that gene expression is not highly age specific (at least not late in life) to the evolutionary literature on post-reproductive lifespan (PRLS). Much of the study of PRLS has been motivated by the idea that PRLS shouldn't exist unless post-reproductive individuals do something useful for their younger kin. This idea arises from the evolutionary demographic theory of aging I described above. If an individual has reached the age where it can no longer reproduce, the genes it is expressing at that age should be genes that selection doesn't care about at all, because whether she dies at that age has no effect on how many offspring she has. So mutations that kill post-reproductive individuals should accumulate rapidly, unopposed by natural selection. W.D. Hamilton, a preeminent evolutionary theorist of the mid-20th century, wrote in 1966 that “In the absence of complications due to parental care or other altruistic contributions due to post-reproductives, the [mortality] curve should be roughly asymptotic to the age of the ending of reproduction.” By this he means that as the individual approaches the end of her reproductive period, her chance of dying at each instant should approach 100%. This has been dubbed "Hamilton's Wall of Death." Hamilton's work is influential enough, and his basic logic sound enough, that many of my colleagues still believe we should find the Wall of Death. But in fact we can find PRLS in a huge range of organisms where there is no parental care or anything comparable, and the Wall of Death is nowhere to be found. Hamilton's prediction fails because his model is built around high age-specificity of gene expression, which we now know not to exist. Genes which are being expressed at and after the age of reproductive cessation are the same genes being expressed prior to that age, doing the same things they did prior to that age (except of course reproduction) and so they can't just suddenly cause all sorts of lethal effects. This represents a major constraint on the ways selection can shape the pattern of mortality over age, and we evolutionary demographers are just starting to come to terms with the ramifications of this. When I have time to write another longish post, I'll explain how this leads to a major question in evolutionary demography that I have been thinking about but don't yet have any plausible answer to.

Constraints

The field of life-history evolution, into which the stuff I do roughly fits, spends a lot of time thinking about optimality. What is the optimal age to start reproducing? What is the optimal amount of time to spend foraging each day? What is the optimal body size for a creature in a particular niche? The factor being optimized here is fitness, usually measured by the rate at which a sub-population with a particular trait would increase in size. The trait value that leads to the fastest increase is the optimum. Quite often when we calculate an optimum value and then measure the actual values in the population, most individuals are fairly close to the optimum. But fairly often this does not happen, and then we start talking about "optimality with constraints." By this we mean that there are certain conditions that must be met, and the optimum we are looking for is the best value that is consistent with those conditions. The most commonly considered constraint in my field is the constraint of limited resources. If you have only 100 calories a day of energy to expend, you can't expend it all on growth and maintenance and all on reproduction, your reproduction is constrained by the need for maintenance, and vice versa. So we can calculate, given a set of biologically informed assumptions, what the optimal investment in reproduction is at each age. This kind of constraint makes sense to people, and yields many useful insights. That said, it is often the only type of constraint considered in situations where many other constraints potentially come into play.

One type of constraint that is particularly hard to build theory around is that natural selection can only favor those traits that exist. That is, a trait may be drastically suboptimal, but if all individuals in the population have that trait, and the genes which determine it cannot easily be altered by mutation such that they allow a higher fitness solution, the population will continue being far from optimal.

A classic example of this type of suboptimality is known as the 'obstetric dilemma.' This is the problem that humans have narrow pelvises and big heads, and the head has to pass through the pelvis during birth. In a (now somewhat out of date but still sound for our purposes) summary of one hypothesis of how humans diverged from our chimply relatives, Kristen Hawkes (the anthropologist behind the Grandmother Hypothesis) described (in 2003) the central role this obstetric dilemma played in human evolution thusly:

* Drying environments in the late Tertiary constricted African forests, making capacities to use alternative foods more advantageous among ancestral apes.
* Bipedalism was then favored because it freed hands for tool use, which
increased success at hunting big animals, and this put a premium
on larger brains.
* But the mechanics of bipedal locomotion limited pelvic width, so brain expansion created an ‘‘obstetrical dilemma’’ requiring most brain growth to be postnatal.
Consequently, children with developing brains were immature longer and were more dependent, for a longer time, on maternal care.
* The care requirements interfered with maternal hunting, so mothers relied on
provisioning from hunting mates. This help from fathers allowed mothers to produce more surviving offspring.
* Thus, parents formed lasting bonds and nuclear families became the fundamental
units of cooperation in which a sexual division of labor served familial goals of production and reproduction.

Now according to this story, variations of which are still supported by the scientific evidence,much of the distinctness of human life-history comes through:
1. The need for large brains and small pelvises
2. Which explains why our babies are so undeveloped
3. Which explains we take so long to mature
4. Which is an important part in explaining why we end up with our social system.
5. Which explains why we live so long.

So the optimality of a narrow pelvis, the optimality of a large brain and the need for
that brain to pass through that pelvis ends up being a central fact of human evolution. And why, we may ask, is it optimal for the baby's skull to pass through the mother's pelvis? The apparent answer is that if there is only one possible trait, that trait is the best of all possible traits.

The pattern of vertebrates expelling their young through their pelvis dates back to
before vertebrates actually had pelvises.

Note that this fish has its gonads above and in front of its pelvic fin. That is a common trait among fish, including the lobe-finned fish from which all terrestiral vertebrates are descended. The lobe-finned fishes had bony feet with which they could support themselves on the sea floor, and the bones in their pelvic fins would eventually be modified by evolution into the legs and pelvis.



Now the first terrestrial vertebrates were amphibians, and like most frogs and salamanders, laid small soft eggs, so it was probably no problem for them to continue having the gonads in front and running a tube through the pelvis to the cloaca. This system only became problematic when the eggs got large and hard, as they are in reptiles like turtles. Turtle people like to talk about "pelvic consraint" when they discuss why turtles don't make bigger eggs.

The only non-fish vertebrates to escape the need to run the babies through the pelvis are those that no longer have ana full pelvis, like whales and most snakes. To my knowledge nobody has managed to invent an alternative outlet, so everybody, including us, has to find one way or another to get through the pelvis. In fact, the only alternative is a human invention, the cesarian section.

This obstetric dillema is a very obvious contraint of the 'no alternative' type. Whenever I get a chance to write another longish post, I'll give an example of a constraint where the lack of alternatives is less obvious because it is genetic rather than anatomical.

Why there are no whale-like birds.

For my birthday, my parents sent DVDs of the Life series with David Attenborough, nature films from the BBC. These are wonderfully made, with amazing photography, and you will likely never hear me say that about any other films. One aspect of the photography that is amazing are the underwater shots. This has got me thinking about marine mammals and seabirds, and the differences between them.

There are five independent lineages of extant (extant is the opposite of extinct) marine mammals:
1. The Cetaceans (whales, porpoises and dolphins), relatives of pigs and hippos.
2. The Sirenians (manatees and dugongs), mildly related to elephants and hyraxes.
3/4. The Pinnepeds (walrus, seals and sea lions), descended from a dog-like carnivore.
3/4. The sea otter, an otter, which is an aquatic weasel.
5. The polar bear, bear.

I have ordered these in the degree to which they have become fully aquatic. The Cetaceans neither need to, nor safely can, leave the water. This is true of Sirenians also, but they tend to feed and birth in shallow water near shorelines, where whales wander the open oceans and dive to amazing depths. The Pinnepeds aren't so good on land, but they do haul up to breed and pup. The sea otter is in some ways more fully marine than the Pinnepeds, mating and usually giving birth at sea. But again, otters are more tied to the land than are Pinnepeds the rest of the year, living and feeding in coastal kelp forests and being capable of fast and efficient movement on land. The polar bear is marine in that it swims long distances, hunts at sea, and has structures that specifically help it do these things. But it still prefers to walk rather than swim, brings its food onto solid ground to feed, breeds and pups out of the water and so forth.

There are more independent groups of sea birds, even if you don't consider each transition from freshwater to saltwater. Penguins are perhaps the most fully marine, flying only in water, feeding entirely on seafood, having special mechanisms for dealing with high levels of salt. The Procellariiformes (albatrosses and petrels) are not far behind, spending about as much time at sea (although over rather than in) as penguins do. The Phaethontiformes (tropicbirds) spend most of their lives at sea, as do many of the Pelicaniformes (pelicans, frigatebirds, boobies, gannets, cormorants and shags). While many gulls live far from the sea, many Charadriiformes (gulls, terns, skuas, plovers, puffins, auks etc.) are extremely marine. Many Anseriformes (ducks, swans and geese), particularly the Merginae (sea ducks) are, well, sea ducks. It was recently discovered that gyrfalcons spend long periods hunting on and around sea-ice, although they probably don't actually swim. I'm sure I've forgotten other examples.

Why so many birds moving out to sea, but so few mammals?

The obvious first hypothesis is that the ability to fly is very useful at sea, while the ability to walk/run/hop etc. is not. The falcons are a pretty terrestrial group, but with few changes beyond the behavioral, gyrfalcons can spend extended periods at sea. Ospreys and eagles, relatives of falcons, use talons that evolved grabbing terrestrial prey to scoop fish. Even hummingbirds and warblers that can't forage or land at sea regularly spend long periods migrating over open ocean. Birds may have an easier entree than do mammals.

Given this, it may be surprising that the most fully marine descendent of terrestrial vertebrates are not birds. All birds lay eggs, and none have figured out how to make that work at sea, so all need to maintain the ability to be land animals. Almost all mammals give live birth, and three groups (Cetaceans, Sirineans and sea otters) can do that without ever leaving the water. The birds may have an easier time getting started down evolutionary paths that lead to a marine life, but they seem to have an inescapable constraint that keeps them from finishing that path: shelled eggs.

The marine reptiles show an interesting parallel to this. Marine iguanas, saltwater crocs and sea turtles all lay eggs, and all do so on land. Sea snakes, excepting one genus, birth live young, and do so at sea. That one genus lays eggs on land.

If some snakes have evolved the ability to have their eggs hatch internally and their hatchlings ready to swim the moment they emerge from the mother, why can't some bird do the same? Imagine how much better off an emperor penguin would be if instead of spending the Antarctic winter fasting in the cold, it could spend that time feasting in the ocean with it's chick developing internally.

Any answer I could offer would be pure speculation. One class of question that evolutionary biology is very bad at answering is "why didn't X evolve." Why hasn't any bird evolved live birth? Maybe it is something about their egg shells. Maybe they are in a habitat where that just doesn't work. Probably it just never happened.

Jon Asks: 1

I've read that fungi are the only organisms that can degrade the longer-chain fibers in wood, such as lignin, and that without saprobic fungi the world would be blanketed in dead, undecayed trees. I see on Wikipedia that it is not literally true that no bacteria can degrade lignins, however, by Wiki's account, it does seem that no known bacteria are very good at it. (http://en.wikipedia.org/wiki/Ligninase) So why would that be the evolutionary case? Bacteria have evolved to break down pretty much everything else on the planet (roughly speaking), and wood has been around for something like 350+ million years. Why would they be such second-rate degraders when it comes to lignin?

This is an interesting question, but not one I can give a very satisfying answer to. Explanations of why something didn't evolve are always fairly speculative. Why no six legged tigers? Why no live-birthing birds? Why no Ents?

So why no lignin devouring bacteria? If they can do it poorly, why not well? Maybe it isn't worth their while to invest in that capacity, as they are always outcompeted by the fungi who can already do it? Maybe they can rely on the fungi to make the enzymes, and then they can just mooch. Perhaps the process of making the necessary enzymes requires separate cellular compartments, which bacteria lack. Maybe the necessary mutations just never occurred, and so couldn't be selected for. Certainly I don't know.

Evolutionary models of evolution

I've been asked to attend an upcoming workshop on modeling the evolution of aging. Modeling in this sense means building a computer model that provides insight into a process. Most of the people who will be there have some experience in modeling, which I don't. So I decided my roll, as the participant most focused on evolutionary theory, should be to make sure that they are doing evolution right. We were asked to each produce a seed, or opening idea, to get the conversation going. Following is a draft of mine. Note that while you can figure out what most of this means, it was written for other scientists and so includes a smattering of jargon and techniquese.



As an evolutionary biologist, I would like to encourage those modeling the evolution of aging to include in their models actual evolution. Optimization models and even Markov Chain models, while very useful, are not evolutionary. By this I mean that they do not include populations changing through descent with modification. To meet a biologist's definition of evolution, a process must include individuals who are reproducing and the offspring must be modified copies of the parents. This requires a population of individuals with heritable traits and mutation rates which modify the parents' traits in the offspring. In order for adaptive evolution to occur, these heritable traits must also influence how many copies of its genome each individual passes on to the next generation.
Markov-chain models, while somewhat closer to evolutionary, still lack the aspect of a population, which is essential for evolution. In many cases the outcome of evolution will depend on having competing or interacting sets of genes within the same population. This cannot be meaningfully understood if the whole population is assumed to have only one set of genes at any one time.
A truly evolutionary model of aging must therefore be fairly complex. It must simulate individuals, who have age-specific mortality and fertility probabilities. These age-specific schedules must be determined by a set of genes. These genes in turn must be determined by a process of inheritance and a process of mutation.
Using such a method, we can address questions that are difficult to get at through optimization. For example, suppose we would like to know why closely related populations have similar patterns of aging, even when they live in different habitats, or occupy different niches. This pattern has been observed in comparative data and comes under the heading of phylogenetic inertia. With an evolutionary simulation, we can impose environments which mediate the relationship between the genes and the demography. We can then ask what characteristics of the environment or what characteristics of the relationship between environment and demography would allow the starting point (that is the initial genes and demography of the population), to influence the ending point (that is the genes and demography the population ends up with).
To take another example, optimization models generally lack any information on the structure of the genome or the process by which that genome changes. However, genomic structure and mutation process are not irrelevant to what demography the population evolves. An evolutionary simulation will allow for modification of the genomic structure or the mutations process. Compare for example, two populations, each of which has a genetically controlled pattern of investment in various tasks such as reproduction, repair, growth or immune function. In population A, as many genes control this at the beginning of life as at the end. In population B, many genes control the pattern of investment early in life, while relatively few are still influencing late life investment. In both populations the genes affecting these investments are subject to mutational pressure and to selection. In each a mutation-selection balance will emerge, but these mutation selection balances will differ between the two populations. The two populations living in the same environment will arrive at different demographies, each nonoptimal.
These are but two of the many complicating factors which can be explored using an evolutionary simulation and are difficult to get at in a model that does not include explicit evolution. Of course models should be simple enough that one can figure out what factor is influencing what outcome. A model cannot include every complicating factor biologists might like to throw in. As such, I propose a modular evolutionary simulation. By this I mean we start with as simple a model as we can which still has real evolution going on and we write it in such a way that one can add more complicated processes. For example, the basic model could have an extremely simple process of mutation, but could be written such that that this process is easy to remove and replace with a more complicated mutational process. Reproduction could be clonal, but again that process of inheritance could be coded such that it could be pulled out and replaced with sexual reproduction by someone who is interested in what effect the mode of reproduction would have on the evolved demography. The environment could be extremely simple and replaceable with a more complicated environment. I am a slow and inexpert programmer but I imagine that it would not be impossible to write such a simulation in a way that genome, inheritance, mutation, environments, and demography are interacting pieces which can be replaced as one replaces the batteries, bulb, wire, switch and casing of a flashlight. One need not modify the casing to replace acid batteries with rechargeables, or replace rechargeables batteries with lithium rechargeables. One can swap a white bulb for a yellow one without modifying the wires or switch. A properly designed base simulation would allow each of us to experiment and still be able to compare our results without any one model becoming unnecessarily complex.

To survive and reproduce in good times and bad

jte asks:

Is there reason to believe, or evidence to support, that the forms of evolution occurring among species during a period of abundant resources is different from the forms of evolution occurring among species during a period of deficient resources?

It seems that a lot of the argument in evolutionary theory is that it takes a lot of energy to grow extra and useless appendages or what have you, so if they really are useless, you'd expect them to evolve away. But if resources are abundant--energy is not a particularly limiting factor--do you then get a scenario in which all kinds of wacky and useless appendages appear and are not attritioned away? Which gives those appendages time to hang around enough to be available when the environment changes and all of a sudden they are useful and confer an advantage?

Or something like that?

I wouldn't go so far as to say the "forms of evolution" are different. In good times and bad evolution acts through natural selection, genetic drift, mutation and all the same basic mechanisms. Rather I would say that selection acts of different traits, or favors different forms of those traits, depending on if times are good or bad. One excellent example of this has been documented by Peter and Rosemary Grant in long term studies of Darwin's Finches on the Galapagos Islands. The climate in the Galapagos is impacted hugely by the El Nino/La Nina climate cycles. In some parts of the cycle, the islands are cool and damp, vegetation grows lush, and there are lots of big seeds to be had. In other parts of the cycle, it is very hot and very dry and only the desert plants with their tiny little seeds are producing. In the good years, the finches with the big bills can eat lots of big seeds, and reproduce like mad. In only a few years the population of one finch species is dominated by big-billed finches. Then when the rains stop, the population starts to crash, and the finches with the little bills good for extracting and opening small seeds are much more likely to survive. After a few years of that, the population of that same species is again dominated by small billed finches. This isn't individuals developing differently depending on the food supply, this is just massive, cyclical natural selection driving the population's genetic make-up around in circles.

On a much larger time scale, generalists are much more likely to survive large extinction events, while specialists often dominate in habitats that have been very stable for millions of years. Consider which of each of these pairs of species is in greater danger of extinction?

German Cockroaches or Lord Howe Island Woodeating Cockroaches
The Black Rat or the Salt-Marsh Harvest Mouse
The Common Pigeon or the Mariana Fruit Dove
The Common Raccoon or the Cozumel Raccoon
Goats or Alpine Ibex
Humans or Sumatran Orangutans

In each case the generalist are doing fine, while their specialized relatives can't cope with change. The fossil record shows multiple examples of large groups going extinct when the coprolites hit the fan, but one or two very generalized species in those groups making it through and giving rise to many new species. The amazing thing is that over and over most of those new species are specialists, evolving to be increasingly good at dominating increasingly narrow sets of resources. Give Rattus rattus a few tens of millions of years and no other mammals on the planet, and they would evolve into many thousands of separate species, filling a vast array of niches, and most of those species would be specialists. If another great collapse came, the ones most likely to make it through would again be the super generalized rat.

As far as the "useless appendages" argument goes, remember that even when resources are abundant, there is still the race to see who can convert those resources into the most offspring the fastest. Plus, the ideal situation rarely lasts very long. Usually within a few generations the population of predators has increased, the food supply has diminished, or population density has gotten so high that pathogens are spread easily. Exponential growth is not to be underestimated. So with the possible exception of humans over the last couple of hundred years, it is almost never the case that a population goes on growing for many generations without selection knocking back those who spend their energy recklessly.

That said, there are traits that are advantageous in bad time and costly in good times, or the opposite. Sometimes species evolve plasticity, such as the ability to grow a thicker coat when the winter is colder, but not waste the protein in mild winters. And sometimes, like Darwin's finches, they just evolve back and forth. The camel's hump is probably something of a hindrance when water and food are plentiful, but it bears that cost because more often than not things will get dry again, and that hump will save its life. If camels lived in an environment where it didn't get dry for some thousands of years, they might end up sans hump, looking more like big llamas. Or they might just die out, vanquished by cows and goats. Camels, after all, are specialists.

Individuality

The central question of interest here in the Laboratory for Evolutionary Biodemography is: how does evolution determine demographic patterns (usually individual lifespan) and, secondarily, how do demographic patterns (again usually individual lifespan) influence the evolution of other traits? This questions leads to all manner of difficult sub-questions. One of these, that comes up surprisingly often is, "what is an individual in this case?"

One colleague has been pondering this question in the context of eusocial insects. Eusocial means that some individuals do all the reproducing, and others don't reproduce at all, they just work to increase the survival and reproductive success of the breeders. Queen ants and their workers are a good example. It seems pretty easy to count ants, they have separate little bodies and they are genetically distinct "individuals" but because they don't breed (usually) from the viewpoint of propagating genetic material, their only role is to perform their appointed task within the colony, in order to aid the queen. This has led some ant experts to refer to the ant nest as a super organism, with the queen functioning as the reproductive organ, and the workers, like the cells in our intestines, as merely the body that supports this reproduction. In many organisms reproductive cells can last the whole lifetime, which intestinal cells are disposable, and frequently replaced. Likewise, queens live as long as the colony does, greater than 30 years in some species, while workers usually last only a few weeks or months. So is the colony a single organism, and therefore the workers its sub-parts, or is each worker an individual, and therefore the colony a multiplicity?

Another colleague is studying the demography of hydra, small mostly sessile cnidarians. Hydra are among the most demographically bizarre organisms. For starters, no one has been able to prove that hydra age at all, despite multiple long term attempts. Second, their primary means of reproduction is through budding, where a bump on the side of the organism gradually elongates, grows tentacles, forms a digestive cavity and takes on the form of a fully formed and functional (but somewhat small) hydra before detaching and becoming a separate individual. Add to this that if you mash them up to separate their cells from each other, each cell has the capacity to grow into a new hydra. Yesterday, I spent a few minutes watching through a microscope as a hydra with a large bud sticking off the side, about half the size of the main body, wiggled in a perti dish. Both sets of tentacles, both digestive systems worked, like conjoined twins. As I watched, I wondered if I was looking at one individual, or two, or hundreds. Each cell had the capacity to found a new colony, build a new hydra, and therefore each cell was in a sense an individual. Each stem could be called an individual, by the loose analogy to humans. Or the whole genetically identical, physically attached, coordinated being could be an organism. Depending on what unit we call the individual, we get very different answers as to the lifespan.

A final example I've been wondering about is the giant redwood tree. A single trunk of a redwood seems to the casual observer to be one huge individual. But redwoods bud prolifically from the base, and multiple trunks can grow out of the same stump, the same root system. Large groups of huge trees can be genetically identical, save for the mutations accumulated in their growing tissues over thousands of years of growth. If we consider one stem to be the individual, redwoods can live for thousands of years. But if we consider everything derived from one seed to be the individual, I don't know of any reason not to consider redwoods, like hydra, effectively immortal. Sequoia sempervirens indeed.

So I'm posing the question to you dear reader, what is an individual? What operational rule should be applied? How do we find the individual in a hydra, or in a redwood forest?

And it's off to Germany with us

I spent last week in Berkeley. My finishing talk was the first joint demography and biology seminar at Berkeley in at least 30 years, possibly ever. I closed with an appeal for the demographers and the biologists to talk to each other more. Evolution is the source of many ultimate explanations in demography, and demography has extremely important methods and insights for understanding evolution in age-structured populations. There was a good discussion, with the demographers and biologists both asking questions, and even talking to each other. Then I spent a couple of days fighting my way through the bureaucracy surrounding the filing of dissertations. I filed, cleaned out my office, packed up my stuff and missed my plane east. I went standby, got to my parents' house at 5AM the next day, spent a day with the family. Then we rushed to the airport only to find that our flight to Germany was canceled because the flight attendants are on strike. Air Berlin assures us we will get to fly today, but in the mean time we are in the JFK Holiday Inn. Being stuck here has given me my first chance to stop and reflect on the fact that:

1. I am now Dr. Daniel Levitis, Ph.D.
2. I am moving to Germany.
3. After nursery school, kindergarten, elementary school, junior high, high school, college and grad school, 22.5 years of schooling in all, I am no longer a student. Being a student was getting pretty old anyway.
4. I am starting a new job very soon, and don't know exactly what I will be doing.
5. I am on vacation for the next few weeks.

Time to go see if our flight will happen today. Posting may be sporadic until I am ensconced somewhere.

Intro to Chapter 1

University rules say I have to have transitions between my chapters. They don't say what they have to be, and my professors don't care, so I'm writing little essays.

Here is the intro to Chapter 1:

Demographers and evolutionary biologists have a great deal to learn from each other. That there is no Demographic Evolution Society or Journal of Evolutionary Biodemography attests to the fact that most biologists, even those strongly interested in population processes and the interactions of individuals of different ages don't fully incorporate the insights and methods of demography. Similarly, most demographers give little thought to why such basic variables as mortality risk and fertility vary with age as they do. Any demographer can tell you that the qx curve is shaped like a U or a J or a bathtub, but precious few seem interested in ultimate explanations of how that came to be. Only evolutionary biology can provide such ultimate explanations. Demography is a social science; questions are expected to have some relevance to humans, and the vast majority are solely about humans. In evolutionary biology the assumption that humans must be interesting is quickly labeled as anthropocentrism.

Human demography offers the evolutionary biologist fascinating questions, tremendous stores of readily available data, and the quantitative tools to analyze them to. Evolutionary biology offers demographers the concepts to understand why humans are as we are, how we came to be this way, and how we differ from other organism. A uniquely human, cultural explanation is not needed to explain a trait humans share with all primates. Where humans are unique, this could be because of evolution, or culture, or more likely feedback between the two. Judging whether a trait of human demography is unique requires the methods and concepts of both demography and evolutionary biology.

Chapter 1 asks how unusual women's post-fertile survival is among primates, and what role culture plays. It combines the tools of demography (in developing appropriate measures of post-fertile survival) with those of evolutionary biology (in the comparative method). The result, it is my hope, clarifies a debate in which people have been talking past each other for some time.

Draft of thesis Abstract

While my committee is happy for my thesis to be a pile of loosely connected papers, the university still expects it to be a single unified document with a single topic, a single Abstract, and transitions. This is a bit of a stretch, considering how far afield some of my chapters are (chapters 2 and 4 for example have almost nothing in common). Here is my first attempt at an Abstract that ties it all together:


Abstract:
Humans are a demographically unusual species in many ways, but perhaps the most unusual thing about our demography is the huge portion of our adult females who are post-fertile. This thesis, in four chapters, explores the evolution of post-fertile survival, attempting to understand, from four different angles, how unusual women are in this respect and how they come to be that way.

Chapter 1 is a methodological and comparative study of post-fertile survival in primates. Post-fertile survival is most frequently measured as post-reproductive lifespan, the length of time between reproductive cessation and death. I show that post-reproductive lifespan is not a useful measure for comparative studies and use demographic life-table methods to create more useful measures of post-fertile survival. I then calculate these measures for several human populations and a large group of primate species. These results indicate that women in all populations experience post-fertile survival which greatly exceeds that in other primates under all circumstances. Non-human primates under natural conditions do not experience significant post-fertile survival, while human hunter-gatherers do.

Chapter 2 arises from the question of whether selective pressures associated with being a care-giver tend to increase longevity, potentially partly explaining women's longevity and therefore their post-fertile survival. The chapter focuses on the tradeoff between providing care to existing offspring and competing for matings so as to produce additional offspring. Data on male primates, in which variation in care provided is much greater than in females, are used in a comparative study. I ask whether these data support the assumption of a tradeoff between male care and male mating competition, and if so if one strategy or the other is associated with greater longevity. I find strong support that such a trade-off exists (males in most primate families invest significantly in one or the other, but not both, and care and competition coevolve in a phylogenetically robust pattern). However these data do not support the prediction that level of male care and degree of sex-bias in longevity coevlove meaningfully.

Chapter 3 is an allometric study of brain size, body size, age at reproductive cessation and longevity in primates, in which I ask if human post-fertile survival is predictable based on primate patterns. Again using life-table methods to create parameters more appropriate for comparative study than those used in the literature, I show that while women's age at reproductive cessation can be fairly accurately predicted based on primate scaling patterns, their longevity cannot. This result indicates that the selective forces which regulate these scaling patterns in primates have been altered or amended in humans.

Finally, Chapter 4 is an experimental evolution study. Using rotifers, a short lived microscopic metazoan, I experimentally make the survival of young depend on the continued survival of their mothers and grandmothers in a species which has no natural care of juveniles. I show that under this regime those familial lines which are longer lived, and which bear a larger portion of their young before mother and grandmother die, increase while others die out. However because of low heritability of demographic traits in this population, the experiment does not demonstrate adaptive change, but rather differential success based on stochastic variation.

Taken together these four papers serve primarily to underscore the uniqueness of post-fertile survival in women. Some have argued that human post-fertile survival is either an artifact of social rather than biological evolution, or a widespread trait in female primates simply exaggerated in human females. These studies make clear that human post-fertile survival must be considered as a novel trait, and its evolution explained as such.

Science and religion

There is a piece in the NYTimes by Robert Wright, trying to reconcile evolutionary biology. He proposes, in effect that if creationists would just accept that evolution happens as it does, and evolutionary biologists would just accept that the universe could have been set up the way it is by a creator who chose natural laws that would lead to organic evolution, we could all just get along. He makes the theistic evolution argument as well as I've seen it made, and I still think it is lousy both in its internal illogic and in its total lack of realpolitik.
The religious aren't about to accept a greatly diminished (or at least distanced) role of God in the universe, and secular scientists aren't going to accept that the fact that there could possibly be some space for God to slip into the cracks that science can't explain yet means that God is a scientifically viable option. Wright's proposed "bargain" wouldn't satisfy anyone, and wouldn't even be more satisfying than the status quo to many people. Wright questions why most people on both sides of this divide seem more inclined to leave it alone than to either argue over it or try to bridge the two views. The answer seems obvious to me: it is not particularly likely that one will either convince someone on the other side, or come to a common understanding, and people have other things to do with their time.

Why don't males care?

The defining difference between males and females biologically is that males produce smaller gametes than females do. Sperm are much smaller than eggs. This difference is the starting point for most arguments describing how the sexes have evolved divergent traits. In mammal further apparently inescapable differences arise because only females harbor internal development of young, and only females lactate (while male lactation is not unknown, there are no document cases of male lactation providing meaningful nutrition to the young of a species). These three apparently fixed differences underlie most arguments describing the evolution of sexual dimorphisms found in mammals, including the tendency among mammals for females to be the sole caretakers of dependent young.
Paternal care is rarer in mammals than in most other taxa where parental care is the norm. Post-birth maternal care is found in all mammals (most fundamentally in the form of lactation), and females care alone in ~90% of mammal species. This contrasts sharply with birds, where female-only care is found in fewer than ~10% of species. Primates are unusual among mammals in that approximately 40% of genera display at least some male care, according to an older and therefore probably low estimate (Kleiman et al. 1981). Primates provide the opportunity to examine what factors lead to evolution of paternal care, even when sex specific structural factors (internal development and lactation) require maternal care.
Why do so few mammalian males engage in care? Mated individuals face the choice to continue investing in caring of current offspring (bearing fitness costs in the form of time, individual quality and mortality risk), produce new offspring with the same mate, or abandoning mate and young to seek new mating opportunities. In all mammals lack of post-zygotic and post-pregnancy investment from mothers is fatal to the offspring. Males therefore have earlier opportunities to abandon, leaving females to bear these costs for both of them, than females do. Depending upon timing and the particulars of a species' natural history, mothers may also be more likely to successfully raise the young of the abandoning male than a male could be in raising the young of his absent mate.
Males not only have greater opportunity to desert, but also greater potential payoffs. A male's reproductive success increases more rapidly with multiple matings than a female's would (although females may gain social and genetic benefits from multiple matings), and males therefore experience higher variance in reproductive success than females. This variance is often non-random, relying on traits which influence female choice or the outcome of male-male competition. These traits are necessarily expensive in order to serve as honest signals, and potentially reduce males' ability as care-givers (and longevity, reducing their reliability as care givers) as they increase their ability as competitors. Therefore males who have already mated, and therefore have the opportunity to care for their own young, are likely to also be those who could most successfully remate, and have invested heavily in the capacity to do so. A female who has mated may not be of unusually high fitness, and may not gain fitness from remating, particularly given the cost in future grandchildren associated with abandoning current dependent young. Males, lacking internal incubation, are also less certain of parentage of social young (both probabilistically and in terms of lack of individual information) than are females, further reducing the value of social offspring (measured in number of genetic grandchildren). Mated males in this standard case, have more opportunity to desert, lower risk of losing future grandchildren by deserting and higher potential for remating than do mated females. Given these conditions, it is reasonable to turn the question around, and ask not why so few mammalian males care, but why do those mammalian males who care do so?
The clear answer to this question is that these conditions, or at least the fitness inequalities they imply, are not universal. Under certain conditions, males may gain more by continuing to invest in existing offspring than by attempting to produce additional offspring. Where biparental care is necessary for production of successful young, the opportunity cost associated with abandonment and competitive risk taking increases. Under the same condition, male reproductive success is likely to increase less sharply with multiple matings, at least in cases where certainty of paternity is fairly high. If this results in a decrease in non-random variance in male reproductive success, it is likely to also decrease the potential benefit to competing for new matings, and in investing in the weaponry necessary for that competition.

This by the way, was another start to an intro that didn't quite work out. The problem isn't that the analysis is internally flawed, but that it raises issues I don't have the data to address, and doesn't really lead to the question I can answer.