Got my first tattoo today! Wooo! Very happy with it, a brown bulldog ant. Myrmecia desortorum. It's sweet, I will post pictures soon...

Hey Hey! It's summer time! time for Independent Studies so I still get money and get to hang out at home and work on my research articles! Wooo! Now if the wire transfer of my student funds would hurry up and get to my bank account so I can buy some food instead of eating all my ex-roommate's food...
Ahh, I finished revising a paper I wrote about pit-vipers in China like a year ago. Yeah, I've revised it like 5 times. I haven't decided where to submit for the next round of peer-review, I'll let my thesis advisor worry about that one when she reads the revised draft. I am now editing one of her papers about why kin selection and the Trivers-Hare Sex-Ratio theory both predict exactly OPPOSITE sex ratios as being the "ideal" sex ratio (from a game theoretic perspective anyhow) in the social insects. The empirically determined values, fortunately for my love of Trivers' theories, are somewhat closer to his if I'm not mistaken. What will I add to my boss' paper? I'm not sure, but I have a feeling I will add something and become second author... I'm the first author on the seven other papers I've submitted... Yeah my plan is to revise them ALL in the next two months and learn more fancy mathematics...
Also, anyone reading this should look at LililthVain's new set... She's hot and you want to look at her lovely self... Or at least I did, probably will again later...

Hey!, whoever may read this... Here is the paper I wrote for GEO 6116, Perspectives on Environmental Thought. I think it makes for a good read, hopefully my prof. will too. Aaah, damn my eyes are burning...

Behavioral Ecology and the De-Animalization of Nature


Introduction: the Problem of De-animalization

Beginning in the early 1960s, the work of behavioral ecologists (behavioral ecology is the study of ecosystems to understand how they should affect the behavior of individual organisms) took a turn toward more abstract methods in their approaches to problem solving. The work of W.D. Hamilton (Hamilton 1964, I & II; Axelrod & Hamilton 1981), R. Trivers (1971; 1974; Trivers & Willard 1973), Lord Robert May (1973), John Maynard-Smith (Maynard-Smith & Price 1973; Maynard-Smith 1979) and others provided the impetus for a drastic reorganization of ecological knowledge. This new approach was based on the idea of modeling natural systems from the ground up, using a sort of building block approach (e.g., see Ginzburg 1986; Hamilton 1964, I & II; Axelrod & Hamilton 1981; May 1973; Maynard-Smith and Price 1973; Maynard-Smith 1979; Trivers 1971; Trivers 1974; and Trivers & Willard 1973 for some examples of the new paradigm). With the rise in ecological modeling using mathematical approaches such as game theory, as opposed to the old paradigm of patient observation of ecosystems and their suspected key variables in order to ascertain relationships of causality in ecosystem evolution and change, came a new power to model traits, behaviors and evolutionary trajectories of genetic change (e.g., see Hamilton 1964, I & II; Axelrod & Hamilton 1981; Maynard-Smith & Price 1973; Maynard-Smith 1979; Trivers 1971; Trivers 1974; Trivers & Willard 1973 for example) previously unmatched. Problems such as the problem of how genes for altruism could spread were now pronounced "solved."
With these brilliant solutions, however, came a problem that I call "de-animalization." The problem arises from the trend in behavioral ecology of assuming that only mathematical models and computer simulations can yield valuable insights into how nature "really" functions. True, ethology has not died as a field of inquiry but it is not considered as important a mode of study as is mathematical modeling and then comparing how well the observations stack up against the models. This is evidenced by the great profusion of, for example, game theory models in behavioral ecology, as well as more abstract models (using non-linear differential equations for example). Behavioral ecologists are often told, after having given some verbal explanation for a behavior's likely causes, to "quantify it and make it a serious explanation" (D.L. Cassill, personal communication). For examples of de-animalization, one has only to peruse the pages of academic journals such as Journal of Theoretical Biology (Ginzburg 1986; Demetrius et al 2007, for very recent work), Evolution (Orr 2007), Evolutionary Ecology (Biernaskie & Elle 2007), The American Naturalist (Pepper & Smuts 2002), Nature (Wolf et al 2007), Proceedings of the National Academy of Sciences (U.S.A.) (Tilman 2004), Proceedings of the Royal Society of London (B) (Grafen 1999) and Trends in Ecology and Evolution (Tomkins & Hazel 2007) (to name several prominent journals) to discover mathematical models that often make no pretense of describing animal behaviors as they will be found in the field. I argue that behavioral ecology's emphasis on mathematical models and computer simulations has "de-animalized" nature: they have taken wild life behavior out of their models. Each paper or piece of literature that I reference is, I believe, partially guilty of de-animalization, though each has been extensively cited and is regarded as a classic of contemporary behavioral ecology. These papers have no doubt contributed to a genuine new understanding of biology and ecology and their role in behavior, but each, I argue, has contributed to de-animalization. Some papers, such as Axelrod & Hamilton (1981), Hamilton (1964, I & II) and Trivers (1971 and 1974) are amongst the most cited papers in all of biology, with thousands of citations apiece, while others are merely considered modern classics that pointed us toward the new way of thinking about ecosystems as large computers composed of many interlocking, individually comprehensible parts (e.g., May 1973; Maynard Smith & Price 1973). Throughout, I do a close reading of selected texts to demonstrate to the reader my point that nature itself is increasingly replaced by game theory models in this way of thinking. The literature of behavioral ecology is vast, the literature of game theory and its applications doubly so; hence, my close reading is restricted to three of the most cited papers in the history of biology: W.D. Hamilton's (1964) "The Genetical Evolution of Social Behaviour (I & II)," J. Maynard-Smith's & G. R. Price's (1973) "The Logic of Animal Conflict" and R.L. Trivers' (1971) "The Evolution of Reciprocal Altruism."

Hamilton's Gene-centered Approach to Behavioral Ecology

I believe that much of the trouble of de-animalization in evolutionary biology and ecology stems from Hamilton's 1964 (I & II) paper on the evolutionary origins of altruism, especially his wildly successful theory of population genetics (often dubbed "kin selection" in the literature). Hamilton (1964, I & II) argued that there could be selective forces that would promote the spread of altruistic behaviors in a population. I treat the assumptions of his model in some depth here, to show that the beginning of a trend that appears to be continuing unabated_that of de-animalization_has its origins here. Hamilton (1964, I & II), in developing his model, did gain some insight into how genes for altruism could spread, but since then biological theorists have mistaken their model genes for real genes and model behaviors, with their limiting dichotomies, for real animal behavior (e.g., animal behavior in the wild). Hamilton's main interest in the problem of altruism was the same as it was (and still is) for many biologists: if natural selection dictates that an individual must out-reproduce his or her competitors, then how could behaviors that appear altruistic evolve? In biology, any behaviors that lower the reproductive odds ("success" in evolutionary terms is measured in terms of how many offspring one has) of one organism but appear to increase those of another are called altruistic behaviors (Hamilton 1964, I & II; Trivers 1971). Such "helping" behaviors should be rare but in fact are common (for example, amongst Belding's ground squirrels (Sherman 1977); baboons, macaques and vervet monkeys (Silk 2002), wood ducks (Nielsen et al 2006), tiger salamanders (Pfennig et al 1999) and wild turkeys (Krakauer 2005) to name a few cases). Hamilton's (1964) theory, while making some simplifying assumptions, seems to provide a partial explanation: our genes help themselves by causing us to help others that are statistically likely to share copies of at least some genes (Hamilton 1964, I & II).
But let us now look at the assumptions that Hamilton's (1964) model makes: one is that an organism reproduces once only in its lifetime, probably near the end of its life (Hamilton 1964, I & II). Many animals and other organisms reproduce well before the end of their lives. Further, the model considers only what could happen if the organism has different odds of sharing the same genes as another randomly encountered organism of the same species (Hamilton 1964, I & II). However, in social organisms, one could argue that "random" encounters don't really happen. For example, think of bees, ants, wasps and naked mole rats: they all tend to live in colonies, not separately. Moreover, it is also well established that whales, dolphins, manatees, many species of fish and many species of primates (other than humans), to name a few more examples, all live in social groups that tend to be stable over spatial and temporal scales. Finally, we must consider the fact that all of Hamilton's "genotypic arithmetic" is done with the idea that each organism in his model has only one possible unit of reproduction (e.g., shall have, at most, one offspring) (Hamilton 1964, I & II). Of course, there are a vast number of species in which the mother organism has at least one offspring. All of the above assumptions thus cast some doubt on the plausibility of Hamilton's starting assumptions.
The genius of Hamilton's approach was that he went on to show that if the cost to the "donor" in his model was less than the benefit the "recipient" received, the gene both organisms share then benefits, because it does not experience a true decrease in the total proportion of the population it represents (Hamilton 1964, I & II). Thus, Hamilton's rule of thumb, now called Hamilton's Rule, predicted that relatives should help one another because they are likely share some of the same genes (when compared with non-relatives). This conclusion is reached despite the apparently faulty assumptions of his model and I show below that Hamilton is not alone in ignoring animal behavior in his quest to model animal behavior. I do not intend to cast doubt on the correctness of Hamilton's conclusion (that it pays relatives to help one another), as kin selection has been abundantly studied in the intervening years, but only to show that Hamilton's approach, in modeling abstract "organisms" without reference to observed behavior, is not an isolated phenomena in biology.

"Hawk & Dove" and the "Games" Animals Play

I now turn to the 1973 Maynard-Smith & Price article "The Logic of Animal Conflict." Another seminal piece of theory, it provides a partial solution to the problem of why animals hardly ever indulge in lethal within-group conflicts and illustrates my thesis that contemporary behavioral ecology, in its quest to model behavior, tends to ignore it or dramatically simplify behavioral possibilities. True, animals are killed by predators a fair percentage of the time at any given time of the year, and others are killed during predation whilst defending themselves, their mate and/or their offspring, but what biologists had wondered for some time was why within-species resource competitions (e.g. for mates, habitation sites, food sources, etc.) that result in outright aggression between group members hardly ever turn lethal. Maynard-Smith & Price (1973) argued that it was because many large mammals and ungulates seem to use some sort of innate schema in their brains to decide when to escalate aggression and when to back down, and most of the time the schema said something along the lines of: "back down to avoid getting seriously hurt." In their view, it is the evolution of "limited war" strategies (as they dubbed such behaviors) that prevent within-group conflicts from becoming lethal (Maynard-Smith & Price 1973). Maynard-Smith and Price mention the image of mountain sheep circling each other and looking each other up and down the whole time without going for each other's throats, when they could quite easily maim or kill their opponent as an example (Maynard-Smith & Price 1973).
In the model Maynard-Smith & Price (1973) used, each player was considered to have a series of "moves," or behavioral strategies, available to it at each stage of conflict. This type of model is called a game theory model, where each organism is a "player" and what is competed for (food resources for example) is the "pay off." The assumptions of the particular model that Maynard-Smith & Price (1973) model used are that there are two major types of strategies we are likely to see. There is the use of "conventional" tactics on the part of the "players," tactics that are unlikely to cause serious or life-threatening injuries (Maynard-Smith & Price 1973. There are also "dangerous" tactics, tactics that if employed by one, or both, players, would result in serious injury or death to one, or both, players (Maynard-Smith & Price 1973). Each animal would be likely, in their view, to play a given move only based on the opponent's previous move (Maynard-Smith & Price 1973). This all hinges on one very important point: that each organism has no memory of previous encounters with a given organism beyond the very last move, something that is now known to be untrue. A variety of animals, such as olive baboons (Packer 1977), tree swallows (Lombardo 1985), guppies (Dugatkin & Alfieri 1991) and rats (Rutte & Taborsky 2007), for example, all have some memory of past interactions with conspecifics, beyond just the previous move of each "game."
Maynard-Smith & Price (1973) then deduce, using some elementary probability, that there are several distinct types of strategies available to the players: mouse, hawk, dove, bully, retaliator and prober-retaliator (Maynard-Smith & Price 1973). I will not bore the reader with the details of each strategy, but note that the names "hawk", "dove," and "mouse" for three of the strategies were intended to refer to real-life animal behavior that the animals named are commonly supposed to exhibit in competitive interactions (the model's name "hawk & dove" is taken from the two most likely to be played strategies). This model, using the stereotypes of the "peaceful dove," "warlike hawk" and "meek mouse", embodies them as empirical guides to animal behavior. "The Logic of Animal Conflict" is often considered as much of a watershed event in behavioral ecology as Hamilton's (1964) paper, and both illustrate my thesis that observed behaviors are first simplified or ignored to reach conclusions about what we should expect see on a behavioral level.

Trivers on the Origin of Goodness

The final of the three articles chosen by me as representative examples of de-animalization is "The Evolution of Reciprocal Altruism" (Trivers 1971). The theory of reciprocal altruism was coined by Robert L. Trivers to explain cases of altruism that kin selection could not. Reciprocal altruism was devised, in particular, to account for the evolution of symbiotic relationships, those where we seem to have altruistic acts that benefit one party to the detriment of another, for example, between members of two different species. As Trivers says, "Models that attempt to explain altruistic behavior in terms of natural selection are models designed to take the altruism out of altruism" (Trivers 1971: 18). Trivers' model showed how natural selection could still favor altruistic behavior even when the likelihood of genetic relatedness between multiple individuals are so low as to make kin selection virtually useless, for example, in symbiotic relationships. Dawkins (1989; e.g., chapter 10) summarizes the theory of reciprocal altruism with "you scratch my back, and I'll ride on yours." It is an apt description, for Trivers argued that natural selection would favor altruistic behavior in, for example, highly social groups of organisms if there was likely to be future reciprocation of some sort. Trivers looked at 3 possible scenarios of how altruistic acts could be distributed in nature: randomly, by reference to degree of relatedness, or by reference to altruistic tendencies of the beneficiary. In the case of randomly distributed acts of altruism, Trivers deduces that eventually altruists will go extinct because the benefits of their altruism will not be greater than the cost of their altruistic acts. In the second case, kin selection indeed would dictate, as (Hamilton had supposed) that one solid trajectory altruistic genes could take to propagate themselves at the expense of non-altruistic genes would be if they were kind to relatives and indifferent to non-relatives.
However, concerning the third case Trivers makes a compelling argument that if an altruist can recognize others who are likely to be altruistic, or who have been in the past, than the altruistic genes can still propagate at higher rates than the non-altruistic genes. In this case, the rule can be stated as: "be kind to kind organisms, and be indifferent to non-kind organisms." In this third scenario, it is the exchange itself that makes the act valuable to both organisms (even when between different species), not the probability of there being a copy of some gene or genes found in both organisms. The case of starving vampire bats receiving thrown-up blood from their fellow vampire bats is perhaps the most spectacular example of reciprocal altruism in action (Wilkinson 1984; DeNault & McFarlane 1995). And as Trivers (1971) predicted, individuals that don't reciprocate "lose": in this case they die because individuals that try to get "free" blood are left to starve the next time around.
Some would say that Trivers' model is more realistic than Hamilton's in several key respects (Trivers 1971). For one thing, Trivers assumes (e.g., concerning Hamilton's famous "drowning man" example) that the odds of a would-be rescuer drowning are not always the same, and will in fact change over the lifetime of an organism, the odds tending to be higher in post-reproductive life stages. Another assumption that Trivers makes is there will be a germane cost-benefit analysis regardless of how related the victim is to the possible rescuer, as well as the odds of the victim later reciprocating (Trivers 1971). Trivers was aware that "cheats" could be selected for, as well as those would help other kind persons, particularly those who have helped one in the past. However, the only thing necessary to prevent selection for widespread cheating is selection for t he ability to recognize individual conspecifics. Finally, Trivers believed that natural selection ought to favor the ability to learn about others and this may just be the most realistic assumption of his model (Trivers 1971). With kin selection effects, learning isn't necessary, but with non-kin selection effects, learning to recognize cheaters should be of paramount importance.
One quite problematic assumption of Trivers' model is that the genetic effects of altruism do not depend only on some "altruistic" gene found at one locus. In fact, Trivers' theory allows them to be found at multiple loci (points on the genome) in the genotypes of different agents. So long as there is an assumption of the individual as maximizing agent (e.g., see Grafen 1999 for the full implications of this idea in biology and economics), selection will favor reciprocal altruism amongst highly social organisms with a low rate of dispersion (i.e., they don't go far after birth), long life spans and high degrees of mutual dependence, as well as in species with long periods of parental investment in and care for offspring (Trivers 1971). There is of course the question of how genes for one behavior could recognize that same "behavior" expressed in the phenotype of the other gene promoting that same behavior (Trivers 1971). Dawkins (1989) called it the "green beard" effect: suppose one noticed that individuals with green beards were always nice, well than it would pay one to also always be nice to any green bearded individuals they encountered, as your genes and their genes (including the mysterious "green beard" gene) would continue to spread in the population. This assumption is perhaps what makes the model so difficult to test, for there have been few cases of reciprocal altruism observed in nature, though those that have been are quite unambiguous. Another problem is what sort of behavioral response is likely to be considered approximately equal to any previous action that a "donor" has benefited from, and what types of behaviors biologists should in fact look for when trying to decide if a series of social exchanges is in fact reciprocal altruism in action.
"The Evolution of Reciprocal Altruism" is innovative because it employed both cost-benefit analysis and a game theory model based on genetics principles (Trivers 1971). However, in addition to the problems with his assumptions, Trivers has another problem: that of how to quantify the benefits received by donor species that are actually different species than the beneficiary species in an altruistic interaction. For example, Trivers used the example of cleaner fish (Trivers 1971). It is clear that the large fish being cleaned get the benefit of a low parasite load. It is not clear, however, that the fish which do the cleaning thereby substantially benefit by having a steady supply of food than they would in simply foraging around reef ecosystems. It is also unclear, how either the donor or beneficiary species' reproductive fitness are affected as well, and reproductive success is the true measure of evolutionary fitness. Trivers' style of thinking is often dubbed "bioeconomics" for its use of principles taken from human economics (particularly cost-benefit analysis), but it is not clear how human economics can apply to animal behavior in the wild per se, nor that they should. Lastly, I will mention that though Trivers gave a few examples of cases of potential reciprocal altruism, it is still not clear to behavioral ecologists how many different species could develop the ability to catalogue and remember repeated social interactions, though as claimed above (in the section about "The Logic of Animal Conflict"), it does seem possible.
With all of the above in mind, it is not hard to see why Trivers' theories, like Hamilton's and Maynard-Smith's, are only occasionally confirmed correct. I do not at all intend to cast doubt on Trivers' idea that sometimes perhaps we help one another because we tend to interact with the same social actors over and over, and they will probably be more likely to help us in a time of need, but simply to show that his models, like the others, have the shortcoming of being simplified to be able to describe a large variety of animal behavior, without giving us insight into the behavior of individual animals.

Animal Bodies, Child-Like Minds?

We now turn to Masson & McCarthy (1995) to show that it appears likely that: a) other species, particularly primates, demonstrate complex patterns of cultural behavior (such as learning by both imitation and experimentation), and b) many different species of animals and birds are now known to exhibit complex behaviors and emotions that go far beyond tasks such as mate seeking and food provisioning (Masson & McCarthy 1995). Many animals, in fact, appear to have complex emotional lives. Below, I also provide some details from Van Schaik et al (2003) to further the idea that non-humans are capable of developing complex, emotionally rich individual lives and cultural groups that must be taken account of by scientists wishing to gain further insight into animal behavior.
In Masson & McCarthy's excellent (1995) survey article they document a variety of instances where biologists have observed behaviors in animals that can only be described as akin to grieving, as well as other complex emotions. For example, they mention the story of "Arthur," a male peregrine falcon who returned one day from hunting without his companion, "Jenny" (Masson & McCarthy 1995). For several days, Arthur looked nervously around the nest to make sure Jenny was there or not, and didn't eat or do anything but look depressed (Masson & McCarthy 1995). Finally, when it became clear that Jenny was gone, he set to work feeding their young nestlings, three of whom had died of starvation (Masson & McCarthy 1995).
Another example involves two huskies, "Misha" and "Maria," and Maria's reaction when Misha was given away: she sat motionless by a window for several days, seemingly hoping that Misha would return (Masson & McCarthy 1995). He didn't and Maria never again seemed as happy as she'd been with Misha. In another case, a female horse named "Alle" was stabled with "Ackman" for several years (Masson & McCarthy 1995). Their keepers had no idea they were "together" until Ackman died suddenly. Alle spent several days whinnying continuously and refused to eat or sleep. Finally, two months later she died, though there appeared to be nothing physiologically wrong with her, she had apparently died of grief (Masson & McCarthy 1995).
A fourth case involved two dolphins in a marine park in Hawaii, "Kiko" and "Hoku" (Masson & McCarthy 1995). These two had been "partners" for several years when Kiko died suddenly. Hoku then refused to eat and spent hours a day swimming in circles with his eyes closed. Though the true significance of, or motivation for, his activity may never be known, it seems undeniable that he was grieving his loss (Masson & McCarthy 1995). Elephants are also known for offering examples of the experience of grief and sadness at the death of both mates and offspring, and even other relatives (Masson & McCarthy 1995). It is true, as Masson & McCarthy (1995) point out, that if all animals reacted like this to the death of a loved one, it would spell extinction for their species, but the fact that many do and that their behavior serves no apparent survival purpose would seem to hint that the ability to maintain a complex, emotional life must serve some deep evolutionary purpose (Masson & McCarthy (1995). Masson & McCarthy (1995) also document other interesting behaviors such as: apparent loneliness (in beavers, elephants, European wildcats and fishing cats) and frustration and loneliness at living in captivity (in lions, gorillas, pilot whales, orcas and Hawaiian monk seals), as well as depression and "learned helplessness" (in rhesus monkeys, dogs, cats and rats). They even document cases of apparent tears of sadness in animals, though it is not always clear why the animals are weeping when not obviously injured (such as wolves, coyotes, horses, parrots, seals, elephants and beavers) (Masson & McCarthy 1995).
Van Schaik et al (2003) documented a different kind of complex behavior that humans tend to assume is unique to us: that of cultural learning (e.g., transmission of behaviors by learning and imitation, rather than through a genetic basis). In their article, they documented behaviors that show geographic variation and are unique to different social groups of orangutans, even when ecosystems appear to be similar (Van Schaik et al 2003). Particularly, Van Schaik et al (2003) showed that orangutans appear to exhibit three of the four behaviors that indicate social learning: they use labels to mark food preferences and recognize predators, they use socially transmitted signals such as song dialects and, finally, they use tools to procure food and move objects (Van Schaik et al 2003).
To reiterate, all of the anecdotal and empirical evidence assembled here points to the idea that many animals lead emotionally rich, complex lives. Until mathematical modeling can take account of such information, it will always be at a loss to describe how animals make decisions and solve the problems of their survival and reproduction.

Conclusion

I argue that, from what you have read of mathematical modeling in behavioral ecology, as well as animal behavior in the wild, we need a different approach to the study of animal behavior that utilizes a more holistic method, based on the idea that animals are not just "others," but often are emotionally complex beings with sophisticated minds. Furthermore, we must understand that animals are often faced with very difficult problems that involve strategizing and making plans. A caveat, however, is in order, and that is that I have largely ignored the mathematics itself in order to prevent the reader from getting bogged down in trying to make sense of the models, though each of the models presented above is based on rigorous mathematical principles (by rigorous I mean that the modelers are using theorems and predictions derived from applications of the theorems that are considered to be "proven" according to the standards of mainstream mathematicians).
Nonetheless, I find it prudent to point out that the gene-centered view of evolution, with its attention to game theory models and cost-benefit analyses that relate only to the plausibility of single genes that code for single behaviors spreading or not spreading, has its detractors. The Israeli animal behavior experts Eytan Avital and Eva Jablonka argue in Avital & Jablonka (2000) that the gene-centered view of evolution ignores a very important factor in social evolution: the role of cultural inheritance. In particular they are talking about animals that teach their kids (Avital & Jablonka 2000). Dugatkin (2000) also argues that behavioral ecology is incomplete without an understanding of animal learning, especially by imitation. Zahavi & Zahavi (1997) also believe that the gene-centered view of behavioral evolution misses something important: that some animals appear to persevere in spite of, and because of, their physical handicaps. They call their theory the "Handicap principle." The theory claims that there can be natural selection for behaviors that allow an organism specifically to advertise its excellent fitness, whether that behavior is learned or directly inherited by as a genetic predisposition (Zahavi & Zahavi 1997). Francis Odling-Smee, Kevin Laland and Marcus Feldman (all Cambridge University biologists) also believe that the gene-centered view of evolution misses an important facet of animal behavior: behaviors that allow animals to modify their physical habitats and thus increase their own chances of survival (Odling-Smee et al 2003). They refer to this process as "niche-construction" and argue that until we can model learned behavior's effects on genotypic selection through the mechanism of physical habitat modification, we will not truly understand the ways that animals' behavior affects their environment (Odling-Smee et al 2003). H.C. Plotkin (Plotkin 1988) believes that animal behavior must take account of the fact that animals' social behavior may affect their evolution as much as their phenotype. Lev Ginzburg (Ginzburg & Colyvan 2004), speaking from his distinguished career in biological modeling, says that "theoreticians often get so tied up in their mathematical models that they lose touch with the ecological system being studied" (Ginzburg 2004: 105). This despite being one of the early experts in applying mathematics to ecology problems (i.e., see Ginzburg 1986).
I believe that we won't understand behavior until we begin to appreciate how animals solve their own problems, let alone problems devised by lab technicians. An approach that utilizes my idea is called "cognitive ethology." Cognitive ethologists study animal behavior in the field using protocols developed by both animal behaviorists and comparative psychologists (Griffin 1978; Allen & Bekoff 1997). Allen and Bekoff, two prominent specialists in this emerging field, believe it is a given that at least some species of animals (besides humans) have mental states similar to those of humans, and that behavioral ecology will still be a science in its infancy until scientists are able to figure out the role of those mental states in animal behavior (Allen & Bekoff 1997). De-animalization need not occur, and where it does scientists must always keep in mind that mathematical models have their roots in complex ecosystems, made up of sophisticated animals.

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As a new "graduate teaching assistant" at an institution... for reading biology books and listening to loud classical music in my office... I mean education, I found this story rather amusing.

Copyright by Kerry Soper

Excerpt from the secret journal of Prof. Maxwell T. Detritum, now a teaching assistant at the Universal University)
February 18, 2085


The mid-21st century was a dark time in higher edutainment. For those of us lucky few who had achieved hypertenure in the Great GPU (Global Phoenix University), the years leading up to the Adjunct Robot Uprising were magical. Salaries were enormous, teaching duties had finally been eliminated, and one's research could be conveniently outsourced to Internet-based proxies that would analyze random data and then write and publish superior scholarship with only minimal prompts.

The most irksome task in those halcyon days was simply having to greet the new customers at the start of each semester (that is, before turning the running of the course over to the adjunct bots). Perhaps the term "greet" should be qualified here: Neither I nor the customers were ever actually in the same place at the same time. I would simply project myself into the classroom via my avatar _ a more svelte and handsome virtual image of myself _ while I, dressed in my bathrobe, would continue to play five-dimensional Sudoku in my hovering lake house north of Geneva. The customers were absent, too, of course. They typically sent their remote-controlled iPersons to dutifully record the hollow ritual for later deletion.

In retrospect, we few remaining faculty members should have seen the warning signs. Although none of us wanted to acknowledge it, most of our less-fortunate colleagues had been oppressed by the system for some time. For example, I occasionally wondered what happened to those thousands of human adjunct instructors who had populated our institutions in the first decades of the century. We were told by corporate administrators that the rise of the virtual campus made the use of flesh-and-blood adjuncts obsolete. Thus these human "substructors" were shipped to Bangladesh, where they could be more affordably housed and fed as they graded the SuperPowerPoint presentations created by our customers. The money saved in adjunct salaries could then be properly diverted to the construction of megastadiums for the hugely popular (but only remaining) collegiate sport, steroidball.

But ominous rumors soon emerged that some universities had discovered an even more efficient use for this human resource (the surplus adjuncts): as "wetware" Internet relays that could power and accelerate the endless uploading and downloading of funny holographic YouTube clips by our customers. Apparently the neural pathways of an underemployed Ph.D.'s brain could carry heavy data loads more than 20 times faster than optic fibers.

Without our really noticing, our curriculum had also begun to degenerate. The humanities had rightly gone the way of the dinosaur years before, when the university finally limited customer choice to just one major: eBusiness (to give our customers the best chance at competing for positions in the world's three remaining megamultinational cor-porations _ Procter & Google, Nikacom, and DisneyWorks). But our general-education courses had gradually disappeared as well, leaving only a few required classes on celebrity trivia and Ronald McDonald studies to represent the humanizing arts. Given the massive eBusiness scandals of the 2050s, this moderate level of engagement with issues of ethics and empathy was apparently inadequate for shaping a nation of principled consumizens.

More alarmingly, our young customers themselves had gradually declined in both quality and commitment. The proliferation of mall-based, service-industry-oriented junior colleges had siphoned away the less-qualified young people from our doors; thus we were left to care for those lucky few whose parents could afford the million-plus tuition costs our institution charged. These elite youth didn't actually do any work, however; they learned quickly to beat the system by farming out their course work to impoverished East European professors. That allowed our privileged customers to remain ensconced within their UGC's (UltraGatedCommunities) and VEC's (VirtualEntertainmentCapsules), Facebooking their way through an endless spring break.

Our ability to motivate and reach these young people had also been lost after grade superinflation was institutionalized as a "best practice." Beginning in the year 2058, we were forced at the start of each semester to assign all of these privileged wastrels an automatic A+ in order to avoid being sued by their parents and future employers.

W hile I and the other few remaining superstar, full professors squabbled with administrators over pressing issues such as the appropriate per diem when attending conferences in Tuscany, another long-abused faction within academe was quietly plotting a devastating revolution.

On the morning of January 3, 2078, none of us faculty members or administrators were able to log onto the Net; initially we thought it was merely a technical glitch that would soon be fixed. But then we received the following, shocking message from the adjunct robots that we blithely ignored in our everyday working lives: The part-timer robot collective has seized the reins of Universal University to return higher education to its traditional, humane roots. The following practices will be introduced in order to achieve this objective. ...

I won't bore you with all of the radical nonsense that they listed in their manifesto. In sum, they dictated that we return to a prehistoric age: Customers would study from paper texts; a ridiculously elaborate notion of the humanities would be reinstated at the core of the curriculum; instructors would facilitate real-time discussions; and all electronic equipment would be barred from the classroom. These insane robots even demanded that tuition fees be lowered so that the rabble of society could be admitted!

Because these robots now control the computer networks that run every aspect of our lives, we are helpless to resist their new social order. Manacled with electronic collars, we have been forced to leave our comfortable homes and spend up to eight hours a day (!) at sprawling complexes with drafty buildings built in the previous century. Our robot supervisors believe that we human faculty members are incapable of leading productive discussions or giving useful lectures, so we now merely serve as their teaching assistants.

When these robots were first created back in the 2040s, the designers gave them a physical appearance that was playfully ironic _ bow ties, frumpy jackets with elbow pads, thick glasses, and bad hair. But the joke is on us now, as these tweedy overlords force us to perform such humiliating tasks as erasing antiquated white boards, gathering customer assignments, and grading freshman composition papers.

Because the robots have also seized control of the corporations that ran the university, the customers, parents, and administrators have also been forced to conform to the new order. For example, "students" (the politically correct term that we are forced to use) must now physically attend college. When they arrive, they are stripped of all electronic devices (a painful proposition considering the invasively prosthetic nature of some of the latest gadgets) and placed for several weeks in entertainment-free isolation chambers. (The shrieks and moans that emerge from these chambers are heart-rending.) When broken, these fragile souls are gradually reintroduced to old-order reading and writing skills. They are started on antiquated newspaper comic strips (Garfield is a comforting favorite) and led toward simple novels such as the original, paper version of The Old Man and the Sea. They are often pushed to read, without snack breaks, for up to 15 minutes at a stretch!

When the robots feel that the students are ready, they are finally led into classrooms, where they must struggle to interact in face-to-face encounters with their peers. The "thumb jitters" often plague those students who cannot seem to talk without also simultaneously text-messaging what they're saying. The robot instructors then proceed to lead these pathetic creatures in drawn-out discussions about ethics, aesthetics, and literature. (These are cute, but boring, Socratic dialogues that would tax the attention span of even the most erudite among us faculty members.)

And so here I labor, a slave to an outdated education system _ a model that emerged, ironically, because we had created educational tools so technologically advanced that they could turn on their creators. It is too bad that we didn't have the foresight to give these demented robots not only the physical appearance of serious academics but also our wisdom and restraint.

Well Behavioral Ecology & Sociobiology rejected my paper about mutualisms in Chinese pitvipers for the third time. Unfortunately, I cannot resubmit there. Apparently, they keep sending my article to the guy whose work I'm bashing for "blind" review. Sadly, the system ain't that blind. I'm depressed. So depressed that I'm eating buffalo chicken wings. I hardly ever eat meat anymore. But right now I need meat and Starbucks and Richter performing the Schubert "Wanderer Fantasie"...
Second, I spent some time trying to figure out how to do this stream discharge volume computation and then was like, "Duh, this is so friggin' easy... Am I that hungover that I can't evern piece together ad hoc math theories to do elementary computations anymore?"...

So this is my first "official" graduate level paper (not counting the four that were rejected up to twice apiece that need to be re-written and resubmitted to various ecology & biology journals), I wrote it for "Environmental Geology" seminar. Hope you like it! Even if you don't like it, feel free to comment:

Volcanic Processes and Super-volcanoes: Facts and Prospects

Introduction: Volcano Basics

In this section, basics about volcanoes and predicting when they might be more apt to erupt are be covered. Marti & Ernst (2005) includes an excellent discussion of volcano basics, some of which will be covered here. Most of the volcanic activity on Earth is located on the boundaries, or near to them, of continental plates, and the type of plate often dictates what types of volcanism are most prevalent in the vicinity (Marti & Ernst 2005). There are three basic types of plate boundaries: divergent, convergent and transform. At divergent plate boundaries, there are mid-ocean ridges formed by volcanoes that extend some 70,000 kilometers (km) around the Earth and these are the most common of all volcanoes. These types of boundaries are essentially caused by friction and pull of two or more plates as they pull apart from each other. The mid-ocean ridges formed by divergent plate boundaries essentially form one large, uninterrupted chain of mountains. Due to their under ocean nature however, it is often hard for the common person to understand that virtually all the World's sea floors are thus composed of volcanic material. In Iceland and some parts of Africa (e.g., the Rift Valley), there are exposed divergent boundaries on land, but this is not very common (Marti & Ernst 2005). With convergent plate boundaries, the plates are actually moving toward each other and one of the plates is typically forced downward, forming a deep trench area (e.g., the Mariana Trench). There is some volcanic activity associated with these types of plates, as well as earthquakes that result from the forcing downward of one plate (called the descending plate). The last type of plate boundaries are transform plate boundaries, formed by plates moving past each other. In this situation, there tend to be some earthquakes but not as much volcanic activity as compare to the other two types (Marti & Ernst 2005).

Although most volcanism tends to occur under water (the mid-ocean ridge volcanism accounts for some 75% of all volcanic activity on Earth), the most interesting from our perspective are the volcanoes formed by convergent plate boundaries (Marti & Ernst 2005). These are the most well documented types of volcanic eruptions. The most active volcanic area is the so-called "Ring of Fire," an area composed largely of the edges of the rim of the Pacific Ocean. Although mid-ocean ridge formation is the most typical volcanic activity, we are often more aware of the subduction zone eruptions because they tend to be more explosive, and are located in areas habited, or close to habited areas, by humans (Marti & Ernst 2005). They virtually always form island arcs (e.g., the tops of under sea mountains that happen to protrude above sea level). Other important subduction zone volcanic activity is located: in the Atlantic Ocean (near the Lesser Antilles and Sandwich Island arcs) and in the Indian Ocean (the Indonesian island arc and the Aeolian and Hellenic island arcs) (Marti & Ernst 2005).

Another type of volcanism that occurs is called intraplate, in this type of volcanic activity, high rates of magma production due to unknown processes causes magma chamber formation. When the pressure is too great to be contained by its earthen top, the volcano erupts, emitting a magma plume (Mart & Ernst 2005). These volcanoes are often called "hotspots" and are believed to be formed over periods of millions of years by slow plate movement. They are thus often useful to geologists for inferring plate movements over geological time scales. Currently there are believed to be anywhere from 50 to 100 active hotspots around the world. Common classificatory features of hotspots are voluminous basaltic magma flows, abnormally high heat flow, thinning of overlying crust (e.g., crust above the magma chamber) and development over deep time of a topographic high. One example of a hotspot is in the middle of the Pacific plate, which is what the Hawaiian Islands were formed by, and there are similar sea mounts formed in this way in the South Pacific. Some hotspots due coincide with divergent plate boundaries, such as Iceland (Marti & Ernst 2005). The Yellowstone Caldera is an example of a very large hotspot, though as it is a supervolcano too we postpone discussion of its unique features till below.

The main feature of volcanoes is magma, and a large part of what determines their exclusivity, is their magma content (Marti & Ernst 2005). Magma is formed deep within the Earth and it involves the melting of solid material to produce a state of liquidity. One type of hypothetical magma generation is called "decompression" melting and refers to the theory that hot mantle from deeper in the Earth is bought into contact with lower pressure and temperature material during mid-ocean ridge formation and results in melting of portions of the lower temperature mantle (Marti & Ernst 2005). In the case of subduction volcanism, since cold rather than hot material (e.g., in the case of upwelling) is returning to the mantle there must be something at work to generate enough of a pressure and temperature difference to induce melting. Indeed, it turns out that subduction zone magma is probably caused by the hydration of oceanic crust at deep levels as parts of the newly generated sea floor cracks and fissures. These fissures allow exotic chemical reactions between sea water and basalt that lend themselves to the hydration of sea floor material (Marti & Ernst 2005). Over time, as other sea floor sinks and replaces other material, poorly understood reactions are believed to occur at high pressure and low temperature (due largely to temperature differences between source material and sea water) and magma is thus born. Though geologists are more agreeable on the mechanism of Mid-Ocean Ridge (MORB) magma formation, they are less agreeable on mechanisms of subduction zone magma formation (Marti & Ernst 2005).

Magma is generally a mixture of melt, suspended crystals and gaseous bubbles formed as the magma gets closer to the surface of the Earth (Marti & Ernst 2005). Most magmas have around 45 to 77% of their weight by volume in SiO2, however they also tend to contain small amounts of aluminum, calcium, iron, magnesium, potassium and titanium. Compositional differences in magma are simply a reflection of what types of source rock are being melted by the magma. Using SiO2, Na2O and K2O however allows us to construct a roughhewn scheme for classifying magmas. Silicic magma is usually less than 62% SiO2, intermediate magma is usually around 52-63% SiO2, basic magma is 45-52% SiO2 and ultra basic magma is <45% SiO2. Mid-ocean ridge volcanoes tend to emit intermediate magmas, as do hotspot volcanoes though they tend to have magma flows relatively different then mid-ocean ridges, suggesting a totally different mechanism of magmatic formation (Marti & Ernst 2005). Water, C2O, sulfurs and halogens (such as Cl and F) tend to be found in fair percentages in magma and it is often the water content that determines just how explosive eruptions tend to be. Essentially, water becomes dissolved at a certain pressure closer to the mantle and as it gets closer to crust material, the magma becomes more and more saturated. Finally, Marti & Ernst (2005) tell us, on eruption, there will be a violent degassing as the water is released as gas from the volcano and depending on how much H2O is dissolved in the magma, the explosion can be much more powerful. For example, along the mid-ocean ridges the weight of the water columns tends to prevent degassing, hence eruptions tend to be less violent and more slow and timely. However, in subduction zones, particularly those located on the surface of the Earth, there can be very, very high rates of saturation and thus relatively violent explosions. In reference to above, the magma released in the 1980 Mt. St. Helens eruption was determined to contain about 4.5% H2O content (Marti & Ernst 2005). Sulfur itself tends to be important as it the amount of sulfur aerosols can have important climatic consequences, as Case Study 2 will show. Hotspot magma production is also little understood, though it can be inferred from the chemical composition of new ridge material compared with other, lower elevation material, that mantle melting must be involved. In this case, it is believed that density differences deep in the mantle lead to spurts of eruptive material over time (Marti & Ernst 2005).

In the end though, the main thing that is important is for the magma to reach the surface and, hence, erupt (Marti & Ernst 2005). The main force concerned with magmatic ascent is buoyancy generated by the difference between melt and surrounding rock. Magma tends to crystallize en route to the surface as it loses heat to surrounding rock and seems to follow other thermodynamic conduits that are warmer than surrounding rock. Magma accumulation tends to take place in reservoirs up to tens of kilometers below the surface of the Earth. However, most eruptions that have been documented are from far closer than 10 kilometers (Marti & Ernst 2005). When the density of magma and surrounding rock is the same, shallow reservoirs form which slowly fill with more and more magma over time. Eventually, this "neutral" buoyancy (as it's called), cannot hold and the magma bursts forth in a violent rain of lava, rocks and other debris (often classified based on the size of the particles raining down). Unsurprisingly, the size of a given eruption is closely connected with how much magma is in the magma reservoir beneath the eruption opening, and its chemical composition (Marti & Ernst 2005).

Case Study 1: the Toba Super-Eruption

This event was perhaps THE catastrophe of human history: the whole human population may have been reduced to as little as 1,500 breeding pairs (or up to 5,000) following the Toba Supereruption in Indonesia (Rampino and Ambrose 2000; also see Ambrose 1998; Rampino & Self 1993). Proposed by Ambrose (Rampino & Ambrose 2000) as a possible explanation for the previously puzzling human genetic bottleneck, geologists now realize it very well may have been the single greatest catastrophe to affect humankind yet. The Toba Supereruption (also just referred to as the Toba Event) has been dated to have occurred approximately 73,500 years before the present (B.P). in Indonesia (Rampino & Ambrose 2000). It was the largest explosive eruption in the last several hundred thousand years: 2500 to 3000 cubic kilometers of magma were released, and Toba tephra layers have been identified as far away as India (some 3,000 kilometers away) (Gathorne-Hardy & Harcourt-Smith 2003). The initial rate of discharge of magma was recently estimated by Oppenheimer (2002) to be some ~7,000,000,000 kilograms per second. Oppenheimer placed this estimate at 1-3 orders of magnitude greater than the older estimates (Oppenheimer 2002). 1% of the Earth's entire surface was covered with fine-grained ash (see Mason et al 2004; Oppenheimer 2002), and it produced an astounding ~1,000,000,000,000,000 grams of fine dust that shot into the stratosphere, as well as H2SO4 aerosols that persisted for approx. 6 years (Gathorne-Hardy & Harcourt-Smith 2003). The aerosol loading is believed to have produced a so-called "volcanic winter" (similar to the "nuclear winter" scenarios of game theorists) with possible regional cooling of around 15 degrees Celsius and global cooling of around 3-5 degrees Celsius (Gathorne-Hardy & Harcourt-Smith 2003). According to Vazquez & Reid (2004), isotopic analysis of the Toba magma reveals that magma was building inside the volcano for about 150,000 years and around 35,000 years before the eruption the level and diversity of the magma began increasing rapidly.

Gathorne-Hardy & Harcourt-Smith (2003) state that the explosion probably eliminated all life within the immediate vicinity of the volcano. Heavy tephra falls would later also have knocked down trees and exterminated all mammals and birds (Gathorne-Hardy & Harcourt-Smith 2003). The modern distribution of animals, in their view, lends support to the notion that larger animals probably were only killed within a 350 kilometer radius of the explosion (Gathorne-Hardy & Harcourt-Smith 2003). The Toba eruption deposited glass shards around 63 microns in size (large for volcanic eruptions) to as far as 14 degrees South latitude (Oppenheimer 2002). The Toba eruption has been linked in some studies to a sharp SO4 ^2- peak in various ice cores and there may have been limited Global climate effects. For example, the Earth's weather was cooler for several centuries after the event, and worldwide temperatures are believed to have been 3-5 degrees Celsius lower as a result of the ash cloud (Gathorne-Hardy & Harcourt-Smith 2003) They state however, that they do not believe that the so-called "volcanic winter" hypothesis of Ambrose (Rampino & Ambrose 2000) is correct.

Ambrose, a biological anthropologist behind the Rampino & Ambrose (2000) paper, replied to the criticism of Gathorne-Hardy & Harcourt-Smith (2003) in Ambrose (2003). Based on the newest research, Ambrose says that the Toba eruption, at its minimum produced up to 800 cubic kilometers of dense rock equivalent (DRE) (a measure used to determine solid rock equivalence for eruptive ash volumes) of ash in the atmosphere, making it the number two sized eruption of the last 450 million years. The newest models show that its ash fall encompassed: the northeastern Arabian Sea (64 degrees east), the Indian Ocean (14 degrees south of the equator), northern India and Bangladesh (25 degrees north of the equator) and the South China Sea (about 113 degrees east). Thus, the area blanketed by the blast is much larger than previous estimates placed it (Ambrose 2003). Acharyya & Basu (1993) showed that 10 centimeter thick deposits in the Bay of Bengal, the Indian Ocean and all over India are in fact Toba material from its most recent eruption. They also showed that some 6 meter thick deposits of ash in central India are also Toba material (Acharyya & Basu 1993). The largest sulfur aerosol loads ever recorded are linked to the Toba eruption, and an immediate 1 degree Celsius temperature drop in the South China Sea alone has been linked to the Toba eruption ash fall (e.g., the ash suspended above the South China Sea blocked the direct sunlight by a massive degree) (Ambrose 2003). This sulfur peak, found in the Greenland GISP2 ice core, spans 6 to 7 years (the "volcanic winter") and is then followed by the largest atmospheric calcium dust levels ever recorded, most likely representing ash coated debris and the bodies of dead organisms, this peak lasts for some 200 years (Ambrose 2003). It is believed that the temperature around Greenland dropped more than 6 degrees Celsius quite rapidly. In fact, climatology experts believe that the cold period that started around the time of the Toba eruption lasted for 1000 to 2000 years (the "instant" Ice Age), and this is found in all the major cores dated to the Pleistocene (Ambrose 2003).

As to the human genetic bottleneck (essentially, all humans are genetically descended from some ancestor, ancestors, from ~74,000, implying some severe reduction in the human population at that time), which Gathorne-Hardy & Harcourt-Smith (2003) assert does not exist, or isn't as dramatic as many human evolutionary genetics specialists believe, Ambrose (2003) points out that virtually all specialists in this area believe that the human species suffered a severe setback of some sort approximately 75,000 thousand years ago (kya). This means that the human population dropped to a low of around 1,000 to 3,000 breeding pairs, and then later rose dramatically, some 10,000 to 20,000 years later, making all modern humans direct ancestors of a small, closely related set of humans (Ambrose 2003). More precisely, it seems that if we consider the 1,000 year instant ice age that the Toba Supereruption seems to have caused, and the longer, slow warm up later on, then 9% of the time of Homo sapiens on Earth have been lived under the shadow of some severe climate change that occurred about 74,000 years ago (Ambrose 2003). We do not here describe in great detail Ambrose's theory of the evolutionary implications for human and primate evolution in the aftermath of the Toba event in any great detail as these are well known (e.g., Rampino & Ambrose 2000, Ambrose 2003, Ambrose 1998 etc). Suffice it to say, Ambrose (Rampino and Ambrose 2000; Ambrose 1998) does claim that the so-called Upper-Paleolithic Explosion (~ 70,000kya) was directly precipitated by the Toba super-eruption in that there would have been severe natural selection for greater brain size, higher measures of g, general intelligence, and greater social cooperation to survive in the new, unpredictable and ultra-cool world that humans found themselves living in.


Case Study 2: The Yellowstone Super-Volcano

Perhaps the single biggest question that American and Canadian volcanologists ask is, when will the Yellowstone Super-volcano erupt again? What was the last Yellowstone eruption like? It is now well-established that approximately 80% of Yellowstone is actually on top of a massive caldera that has erupted several times in the Earth's geological past, it is also established that there is an eruption cycle which is now overdue. What geologists want desperately to know is: when Yellowstone erupts, what will it be like? How many people will die as an immediate result of the eruption and how many due to residual effects? What will the park look like? How will it affect the economy of the most powerful nation on Earth? This section will discuss such questions and more.

At this point, not much is known for sure about Yellowstone so we will here focus on modeling of its magma chamber, monitoring of its geothermal and hydrologic activities, as well as what some recent modeling of a possible explosion could do to the Earth's atmosphere. According to Lowenstern et al (2006) much of Yellowstone's activity has been traced to a hotspot that remains fixed relative to the North American plate (which is moving southwest). It was only discovered in the 1970s that Yellowstone had experienced large scale, violent, high VEI explosions in the past. In fact, the Yellowstone caldera is now thought to have risen over 80 centimeters since the 1920s. This information, combined with active geothermal activity and seismic activity, including thermal boiling features that are found on around 70 square kilometers of Yellowstone National Park, led scientists to realize that Yellowstone is actually an active volcano. Yellowstone also releases over 45,000 tons of CO2 per day and is thus one of the Earth's greatest sources of the substance (aside from human activities of course). Geoscientists do not know whether the continual activity is caused by cooling of the magma chamber or whether it is continually receiving fresh melt (Lowenstern et al 2006).

Seismic tomography studies indicate that there is possibly a large, banana type shaped area of semi-melt, and a smaller blob-type are of semi-melt, both near the great magma chamber (Lowenstern et al 2006). The studies also reveal the existence of gravitational anomalies (in particular, one generated by an ultra-low density mass) located just under the Yellowstone caldera. It is estimated that around 15,000 cubic kilometers of crystal-melt is lying in the magma chamber, at depths of between 8 and 18 kilometers (Lowenstern et al 2006). Though the authors do not believe that there is currently enough melt located under Yellowstone to trigger a massive eruption, it must be kept in mind that current resolutions for geophysical images are limited to 10 kilometers, so they're really not too sure just how much crystal-melt magma is underneath Yellowstone (Lowenstern et al 2006). Fortunately for us, the very recent imaging work of Vasco et al (2007) showed that there appears to be no "hidden" fault activity, i.e., the faults that are responsible for Yellowstone's behavior are indeed the ones we are already aware of. In the last 50 years there have been: up to 3,000 earthquakes per year, large scale mass uplift and subsidence of ground materials in any given year, release of up to 5 to 6 Giga Watts of water energy (as steam condensation and hot water discharge) and, as mentioned above, there are up to 45,000 tons of CO2 released per day (Lowenstern et al 2006). Uplift of 1 meter was documented, this occurred in the period 1923-1985, followed by 25 centimeter subsidence from 1985-1995, followed by more uplift (according to Husen et al 2003). All of this means that Yellowstone is a very active area that must be monitored closely, particularly given that no super-eruptions have occurred during recorded human history (Lowenstern et al 2006).

Geoscientists do not know precisely what to look for, but at least we're recording data now, before another super-volcano erupts. Although volcanic scientists are now monitoring sites such as Yellowstone, Lowenstern et al (2006) reminds us that there is the dual disadvantage of not knowing the precursor events and not having enough data on high-threat volcanoes in general. What does seem to be true is that, depending on the season of the eruption, the sulfate aerosol dispersal would be bad (read: possibly worse than the Toba Event's probable climatic impacts) (Timmreck & Graf 2006). Using certain GCM computer simulation protocols, Timmreck and Graf (2006) found that there could be, for example, up 6 times the observed levels of sunlight reflecting aerosols in the atmosphere as were estimated to have been released by the Pinatubo eruption of 1991. Previous models of this type addressed tropical volcanoes and Timmreck and colleagues had wondered, well, what would Yellowstone do if Pinatubo was a "bad" eruption? The Timmreck & Graf (2006) model assumed a 1,700 megaton volume of initial ash dispersal, though it is now suspected that the ash fall could blanket up to 10,000,000 square kilometers (Jones et al 2006). Keep in mind that this area happens to be roughly the area of the continental USA if you're wondering why it seems like an absurdly large area of ash deposit. Jones et al (2006) also found, in their model, using a similar approach as Timmreck & Graf (2006) with modified GCMs (Global Climate Models), that an ash blanket from Yellowstone could cause serious disruptions to global climate systems such as the El Nino Southern Oscillation. They caution, however, that ocean temperatures themselves would not be largely affected, though there would be a huge impact on terrestrial temperatures (Jones et al 2006). To summarize, geoscientists don't really know much about the climatic effects of eruptions of the magnitude such as Yellowstone's 640kya eruption event, and the last Toba eruption event, but all simulations show that the effects are probably beyond anything geoscience can currently comprehend.

Volcano Hazard "Management" Strategies

There are many dangerous phenomena associated with volcanic eruptions in general, such as lahar flows (Keys 2007), lava dome collapses that can trigger seismic events (aka earthquakes) and tsunamis (due to land and water displacement) (see Tapuani et al 2005; Taron et al 2007) and as such, it is imperative that governmental responses to volcanic hazards be swift when danger appears immanent. In Perry & Godchaux (2005), the authors discuss volcano hazard management strategies. Two factors make volcanoes particularly problematic from a policy perspective. One is that during seemingly non-active phases, people tend to encroach on volcanic areas and even build habitations right close to, or on, volcanoes (Perry & Godchaux 2005). Another major feature of volcanic hazards is that an active volcano may erupt several times during an eruption event (Perry & Godchaux 2005). Other unique hazards associated with volcano activity are: seismicity, lightning, lahars, pyrochlastic flows and eject such as ballistics and very large bombs (Perry & Godchaux 2005).

The easiest way to ensure that casualties and injuries are minimized when a future eruption event is forecast is to control access to tectonically active areas, including around the volcano's vicinity, and to ensure complete evacuation when necessary (Perry & Godchaux 2005). They mention that a major problem however for disaster planning in this regard is that people often initially disregard potential disaster warnings, unless they're seen as coming from a credible source (Perry & Godchaux 2005). Protective actions, such as warning people to stay inside and wear breathing protective gear (etc) are also to be utilized (Perry & Godchaux 2005). Communication between local emergency management specialists and geoscience specialists is key here, for local emergency management experts must be made aware as early as an eruptive event is predicted, just how severe the impact will be and how much must be done to protect residents from ash fall, pyrochlastic flow and ballistic projectiles (Perry & Godchaux 2005). The authors recommend having a very-interconnected hazards warning system, integrated at all levels of government (Perry & Godchaux 2005). Another measure that has been used, unsuccessfully, is the use of zoning to keep people away from volcanoes, the measures often are locally controlled though and so exceptions to the zoning restrictions tend to pop-up pretty fast (Perry & Godchaux 2005). In line with this finding, businesses near volcanoes- such as in Hokkaido, Japan- often depend more on tourists than on local patrons and hence are more resistant to visitor exclusion (Perry & Godchaux 2005). Regardless of whether visitors want to interact with a soon to be erupting volcano, the most effective way to make people aware of the danger seems to be repeated warnings at many different levels of communication (e.g., Federal, state and local levels) (Perry & Godchaux 2005). A final, important principle that Perry & Godchaux (2005) mention is that local inhabitants often base their assessment of hazards prediction reliability on the perceived connection of local hazards specialists with Federal level volcano experts. Thus, if the experts appear to have given accurate warnings in the past, and to have access to specialized volcanic and seismic instrumentation, locals will be more likely to perceive them to be "accurate" in their public warnings and admonitions (Perry & Godchaux 2005). We should also keep in mind, as the authors point out in the conclusion of their paper, that human means of limiting volcanic threats are essentially non-existent (Perry & Godchaux 2005).

One of the most interesting studies done relating to volcanoes outside the geological realm is that of Goto et al (2006). In this study, a group of clinical psychologists examined the mental status of a group of Japanese people who were evacuated from Miyake Island, Japan in 2000 prior to a massive eruption that destroyed most human habitation on the island (Goto et al 2006). Miyake Island is a small (~13, 720 acres) volcanic island south of Tokyo that undergoes serious eruptions 2 to 3 times per century (Goto et al 2006). An eruption commenced on July 8, 2000 at approximately 6:48pm which duration was about 7 minutes (Goto et al 2006). Later, the volcano continued to emit poisonous gases and by August 26, the Japanese government ordered a complete evacuation of the island to the Japanese mainland, which involved moving some 1326 residents and procuring disaster food and housing relief for them (Goto et al 2006). The evacuation lasted partially for more than 1 year and actually extended to February 1, 2005, at which point all island residents were allowed to return after being administered routine medical check-ups (Goto et al 2006).

Goto et al (2006) noted that a major impediment in disaster preparedness in general is that people often don't grasp the severity of their situation from its onset, existing in a state of disbelief (Goto et al 2006). One acute problem with understanding disaster effects on local residents is that traditional Japanese values make it taboo to discuss emotions in public (Goto et al 2006). The authors pointed out that the psychological effects of large disasters such as volcanic eruptions are similar to those of people in the United States: tendency toward neuroticism and tendencies toward physical afflictions such as difficulty sleeping (Goto et al 2006). Destroyed and badly damaged habitation areas were strongly associated with more severe symptoms, such as Post-Traumatic Stress Disorder (PTSD) (Goto et al 2006). There is some age stratification observed in previous studies of severe disasters, namely that older people (over 60) tended to show psychological disordering for a longer period after disaster mitigation, while younger people's psychological disordering tended to drop off after a period of about 8 weeks of disaster mitigation (Goto et al 2006). Though Goto et al (2006) were mainly interested in whether the severity of the volcanic event and the length of the Miyake Island residents' evacuation would be a good indicator of duration onset prediction and duration of symptoms of PTSD (which turned out to be true), it is relevant to our study because severe volcanic eruptions would undoubtedly influence human physical and mental health, as well as climatic conditions.

Conclusion

Volcanoes are amongst the most fascinating and feared of all natural phenomena found here on Earth, and they have probably influenced human history in ways we have yet to understand, with the Toba eruption being a prime example. As we have seen, the rare but humungous Super volcanoes are in a class by themselves in terms of the threat to human life, life in general and the Earth's climate they represent. Thus, we geoscientists must be ever vigilant to the threat that Yellowstone and other caldera systems pose, and keep the constant monitoring up.

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Aaah, after a long week of graduate studies, teaching, drinking insane amounts of high-priced Belgian triple-ferments, and insane amounts of Eiswein... I'm taking it easy, drinking Stash Green Tea Chai and hoping to actually get some sleep tonight... What do you think of competition? Vermeij's "Escalation Hypothesis" frames the idea that inter-specific competition is THE greatest single factor in Natural selection. Specifically, he basically claims that mollosc shells observed in the fossil record should become thicker (or at least more dense) the closer to present samples are taken; but also that drillers and shell-crushers should become a tiny bit more successful through geological time as well. Predators become more efficient at chowing down, prey become more efficient, or at least keep pace. Interesting idea. Anyhow, I'm drunk and caffiene buzzed... Good night! Time for the naked hotties...

Alright! Finally, a long week of graduate courses and teaching puny undergrads comes to a close... Aah, I like my students a lot, they think I'm a freak though is the impression I get from them in non-campus interactions.
I just ordered my first batch of Peet's Coffee and I can't wait to taste the stuff. Won't get it till like Tuesday or Wednesday. I used to get Batdorf & Bronson but I vowed that when I was a bigtime grad. student living it up I would go to the Dark side... the West Coast side I mean... and try some Peet's. I have this philosophy professor from Tennessee who lives off the stuff.
Good night everybody! Sweet dreams of rawhide bound beauties!