Integrative and Comparative Biology Advance Access originally published online on October 20, 2006
Integrative and Comparative Biology 2006 46(6):1000-1015; doi:10.1093/icb/icl049
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Linking immune defenses and life history at the levels of the individual and the species
Department of Ecology and Evolutionary Biology, Princeton University Princeton, NJ 08544, USA
Correspondence: 1E-mail: kallee{at}ucdavis.edu
Immune defenses have been suggested to play an important role in mediating life history trade-offs. Detecting and understanding such trade-offs, however, is complicated by the complexity of the immune system. The measurement of multiple immune indices in studies of "eco-immunology" has only recently become more common, but has great potential for furthering an understanding of the ecological and evolutionary forces driving immunological variation. Building on previous proposals, I create a framework integrating immunological and life history axes that can be used to formulate predictions and interpret variation in multiple types of immune defense at both the individual and species levels in vertebrates. In particular, this framework predicts that "fast-living" species (those with high reproductive and low survival rates) should rely more heavily on nonspecific and inflammatory immune defenses, while "slow-living" species should exhibit stronger specific and especially antibody-mediated immunity. At the level of individuals within species, nonspecific and inflammatory responses should be downregulated, and specific defenses upregulated (1) in individuals experiencing the greatest demands on their resources (for example, undertaking large reproductive efforts); (2) in the sex investing more in a particular activity (for example, females during reproduction); and (3) during the most demanding periods of the year (for example, the breeding season). A review of the literature reveals that incorporating multiple facets of the immune system into a model of the relationship between immune defense and life histories brings disparate questions and systems into a common context, and helps explain empirical results that are sometimes counterintuitive.
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