The dynamics of antagonism

The fourth and final characteristic is the dynamics of antagonism. Many cases of co-evolution involve escalating degrees of antagonism. Included here are escape-and-radiation co-evolution, arms races, and co-evolutionary alternation. Arms races are interesting because they can occur, as in pollination interactions, within a mutualism,which serves to underline how fragile such mutualisms are to exploitation. Other modes highlight decreasing degrees of antagonism: mutual dependence and co-evolutionary successional cycles. Co-evolutionary turnover, while antagonistic, does not imply any change in the degree of antagonism during the interaction. Diversifying co-evolution does not specify any particular degree of antagonism.

Hence, co-evolution may or may not result in changes in the specificity of the interaction, in the degree of antagonism, in species richness through speciation or extinction, and variable dynamics of the traits involved. These are the things we wish to understand or predict. To do so we must make some starting assumptions and formulate models with them. The models that have attempted to predict co-evolutionary outcomes mainly address three types of interaction: competition (Chapter 9), predator-prey, and host-symbiont (Chapter 10). Some have been successful in identifying conditions under which the observed modes of co-evolution occur. As we saw in the last chapter, there is some theory that can now predict the conditions for mutual dependence in a symbiosis. With regard to competition, Roughgarden (1995, p. 110) and co-workers have extensively modelled scenarios of invasion and competition with regard to the Anolis lizard patterns. They find that a taxon-loop involving invasion of larger bodied species, followed by displacement and extinction of the smaller resident can be predicted if competition is asymmetric and the width of the carrying capacity small. This may then explain the patterns of body size and species richness seen on certain islands. In this model the trait, body size, is assumed to be controlled by numerous genes of small effect (quantitative genetics), which is a reasonable assumption.

Other types of interaction demand alternative genetic assumptions. Models investigating plants and their pathogens, such as rust fungi, frequently assume a single major gene locus controlling the interaction in each species, so-called 'gene-for-gene' co-evolution. For example, a pathogen may be virulent or avirulent and a host resistant or not resistant. This appears to be the case in many plant/plant-pathogen interactions. Gene-for-gene co-evolution has elsewhere been described as an alternative type of co-evolution,but it refers really to an assumption rather than an outcome. However, the assumption can generate rather characteristic outcomes: stable or fluctuating genotypic polymorphisms, or fixation of one allele in both populations. Similarly, variable dynamics are implied from field studies of plant resistance across populations (Thompson and Burdon 1992). One interesting outcome occurs when the fitness of host or parasite is frequency-dependent; that is, that it is highest when rare. Under such conditions there can be cycling of host and parasite allele frequency, so-called 'Red Queen' evolution, the type of conditions that can favour variability among offspring, and hence sexual reproduction (Chapter 2) as well as polyandry (females mating with several males). There is now increasing evidence for the frequency-dependent fitness of hosts under attack from parasites, as well as for links between polyandry or recombination, and susceptibility to parasites (Lively 2001).

The theory of predator-prey co-evolution has, in contrast, evolved largely in the absence of any background empirical data (Abrams 2001). The long timescales involved in detecting both ecological and evolutionary dynamics have been the most prohibitive hurdle. Recently, however, some studies on planktonic algae and their predators have been successful in generating short-term evolution in the algae that affect the ecological dynamics of both species (Johnson and Agrawal 2003). While this is not co-evolution, the use of microcosm systems like this holds the potential for generating useful data that can test and further develop predator-prey co-evolutionary theory.

Thus there has been some useful but limited interplay between theory and data in studies of co-evolution, though one could argue that greater potential still exists. In some cases, empirical studies have provided knowledge of outcomes or assumptions that have led to the development of theory capable of explaining them. In other cases theoretical developments have predicted outcomes that demand further empirical study.

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