In order to develop my interest in parasitism and pursue my ideas further, I decided to focus on theory, specifically on ways that parasites compare to free-living organisms with regard to life history strategies. In particular, I explored the life-history characteristics of parasites and examined those features that distinguish them from other organisms, with the objective of inferring evolutionary pathways to the parasitic mode of life.

The underlying hypothesis was that life histories could be defined according to both malthusian parameters and species to species interactions, for example, those included within Lotka-Volterra equations. A paradox of parasite life-history is that they combine high reproductive potential with large offspring and long life-expectancy (Calow, 1983). Richer nutrient conditions, compared with predators and grazers, may explain this paradox, however theoretical support is needed to explore its evolutionary origins and redefine the place of parasites within general life-history theory.

Upon examining this idea, my advisor, Dr. Philippe Rossignol, and I realized that it was possible to further extrapolate the Euler equation (&Mac183;e^-rt s_t n_t) in a way that would yield four extremes in life-history optimization, essentially by introducing an effect on host survival. The principal parameters involved were fecundity, adult survival and host survival. The equations that we suggested appear to define, in a rigorous fashion, the intuitively accepted categories of parasite, parasitoid, predator and grazer.

My first objective was to strictly formalize the mathematical basis of this idea. The mathematics of Euler's equation was fully elaborated, keeping in view the objective of defining overall life strategies.

The second objective was to state specific evolutionary consequences of these mathematical relationships. For example, a trophic relationship between a host and consumer could apparently evolve from one category to the other, however certain paths are more likely than others. Thus, a predatory relationship is likely to evolve into a parasitoid relationship, but unlikely to evolve into "typical" parasitism (sensu Kuris, 1997). Trophic relationships could also evolve into a category from two different directions. Additionally, given that both host and parasite parameters enter into a relationship, labels such as predator, grazer, parasite and parasitoid were only used to define a paired relationship, rather than an individual organism. The range of these different relationships is strictly limited and the labels we currently apply to species deserve critical scientific examination. As an example, we suggest that all members of the Phylum Nematomorpha are parasitoids, since they require the death of their insect host for completion of their life cycle. Also, morbidity and mortality are not dependent on the intensity of infection. Though they are normally classified as parasites, nematomorphs likely evolved into parasitoids from a parasite ancestor. Also, mostly due to taxonomic convenience, many protelean parasitic wasps are defined as parasitoids, but appear to have evolved from the direction of predation. The interesting convergence on parasitoidism from two different directions had not been explored or clearly stated before our work.

The third objective was to search the literature and identify paradigms and paradoxes of the theory. Quantitative measures of the above mentioned parameters were cataloged, and organisms were plotted according to the derived equations.

The theory is rigorous in that it is clearly refutable from quantitative results; closely related organisms tended to follow similar evolutionary paths. In addition, widely different species converging on a specific type of relationship could have done so from only two different directions, assessable from quantitative examination.

In the future we hope to test our model with experimental studies. This work has contributed important theoretical bases both to parasitism theory by developing a stricter definition, and to life strategy evolution by identifying convergencies.