My research has concentrated on issues of kin selection and the evolution of altruism, with a particular focus on the application of these principles to the evolution of sociality in insects. I have pursued these issues both with theoretical studies using computer modeling and empirical studies using molecular techniques.
I began my career by working in collaboration with Dave Queller to develop a measure of genetic relatedness using single-locus codominant genetic markers (such as allozymes and, more recently, DNA microsatellites). I used this measure in a comparative study of relatedness values within colonies of several species of social wasps. This work was done in collaboration with Joan Strassmann and Dave Queller and was the first extensive examination of relatedness values in primitively eusocial species which offer a good model system for the origins of sociality in insects. I collected genetic data using allozyme markers and to analyze the data developed a computer program for calculating relatedness, which has been important in my subsequent research.
I next turned my attention to a theoretical study involving the dynamics of kin selection in viscous populations. Population viscosity, in which individuals never disperse far from their natal site, had been thought to promote the evolution of altruistic social behaviors by kin selection, by keeping genetic relatives in proximity to each other. However, several authors had suggested that competitive costs counteract inclusive fitness benefits in viscous populations, so that kin-selected altruism is therefore impossible in such conditions. Only effects on the actor's own direct fitness remained.
I used computer models to address the consequences of competitive as well as altruistic behaviors when population viscosity keeps relatedness among neighbors high. My results confirmed the finding that viscosity alone could not promote kin selection. However, I further found that any mechanism that allowed interactions to be confined to individuals of higher relatedness than the general neighborhood (such as a kin recognition system, or a specific timing of interactions to periods of higher than average relatedness) would break the equivalence and allow inclusive fitness effects to overcome the added costs of local competition. Although any degree of relatedness arising from viscosity must be discounted in inclusive fitness calculations, population viscosity is not universally fatal to the inclusive fitness approach, as had been suggested by some researchers.
In my postdoctoral research I developed software tools for analyzing data from genetic markers, and have applied these tools to empirical studies in social insects. The rise of molecular techniques for obtaining genetic markers such as DNA microsatellites has made possible detailed studies of reproductive allocation and relatedness structure within colonies. The new data permit the formation and testing of detailed hypotheses concerning the inclusive fitness interests of different colony members, how these lead to conflicts of interest and how such conflicts are resolved. Exploring these questions provides specific tests of inclusive fitness theory and its application to the evolution of social behavior in general, and has been the focus of my recent research.
The software I have designed to take advantage of these new opportunities includes an upgrade of my Relatedness software, with new capabilities for performing more sophisticated analyses and calculations exploiting the new genetic markers to the full. I have also written a new program, called Kinship, which performs maximum likelihood tests to determine the specific pedigree relationships between pairs of individuals in a population. Between them, these two software tools permit a thorough investigation of colony demographics and inclusive fitness issues within social insect colonies.
These programs have not been useful to my own research alone. Since they were written, they have been available to any interested researcher. Currently they are available from my software download page. At last count, Relatedness has received approximately 1000 downloads, with 150 users registered before the web site became active, for a total of roughly 1150 users. Kinship has been downloaded approximately 700 times. Registered users of the two programs include researchers from Australia, England, Germany, Japan and Israel as well as the US. E-mail messages I have received show that they have been used in studies of various birds and fish, as well as mice, lizards, gray wolves, baboons, dolphins and beluga whales. They have been used for inclusive-fitness studies comparable to my own, for conservation projects, and for tracing family trees within populations.
In my own research I have used these tools primarily in studies using DNA microsatellite data I gathered for species of neotropical, swarm-founding wasps, especially Parachartergus colobopterus. This research has been done in collaboration with Dave Queller, Joan Strassmann, and others in their lab group. I was able to determine that queens of this species are singly-mated, and to describe the structure and demography of their colonies. This information provided the answer to a puzzling feature of the colony cycle of Parachartergus colobopterus and other swarm-founding species. These wasps maintain high relatedness on their colonies despite having a large number of queens. Relatedness is maintained by producing new reproductive individuals only when mortality has reduced the number of queens to 1; thus the new queens are all full sisters. However, this mechanism results in a potential problem for the wasps: queen mortality cannot be relied upon to synchronize itself with the ecologically best time for swarming. My research on this issue showed that swarm production is uncoupled from the colony cycle, allowing it to be timed to the best swarming season.
Besides my general-use programs, I have written many short programs for special purposes in my research such as estimating the numbers of queens which produced the genotypes in a sample population, creating simulated data sets to test the power of different statistical methods, and testing theoretical ideas by simulation. These are skills which I intend to apply in collaborative projects as well as my own research. In developing new general-use software and in providing specific software tools needed by colleagues for a particular project, my interest in programming lends itself naturally to collaboration.
I plan to continue applying this combination of molecular
techniques and computer programming to pursue my interests in
social insect biology and the workings of kin selection and social
evolution. I also hope to have the opportunity to extend my research
to other areas of evolution and behavioral ecology in which I
have an interest. I am particularly interested in applications
of game theory, sexual selection, and the use of genetic algorithm
programming to investigate evolutionary processes.
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