Top-down and bottom-up research in biodemography

Abstract The most efficient way to make scientific progress in biodemography is to encourage bi-directional exchange between 'top-down' and 'bottom-up' research. This will entail exchange along the continuum of research from microscopic intracellular processes to population-level consequences. In addition, our understanding of the biology of aging and its demographic consequences will be enriched by mutual influence between studies of mechanistic or 'proximate' causal processes and investigations of the evolutionary processes underlying the same phenomena. Researchers working at these different levels of explanation could be more productive if they were informed by research at other levels and interacted with scientists with complementary expertise. Such collaborations could be encouraged both through interdisciplinary workshops, research projects, program projects and training programs. 1. Overview The overarching theme of this essay is that given our current state of knowledge, the most efficient way to make scientific progress in biodemography is to encourage bi-directional exchange between 'top-down' and 'bottom-up' research. These terms are used in two senses here. First, they are used to refer to the continuum from microscopic intracellular processes to population-level consequences. In a second sense, 'bottom-up' is used to refer to mechanistic or 'proximate' explanations. 'Top-down' refers to 'ultimate,' or evolutionary explanations of phenomena, based on the action of natural selection working on genes and the phenotypic traits with which they are associated (Mayr 1961). Researchers working at these different levels of explanation could be more productive if they were informed by research at other levels and interacted with scientists with complementary expertise. Such collaborations could be encouraged both through interdisciplinary workshops, research projects, program projects and training programs. We now know that the processes linking genes to fertility and mortality outcomes, and the impacts of those processes on gene distributions in populations over generational time are both tremendously complex and highly structured. The genetic system is in many respects comparable to the generative grammars of human languages, which are capable of an almost infinite number of meaningful utterances. With a relatively small number of genes, based on only four base pairs, an immensely large number of phenotypes can be generated through additive and interactive effects of genes, gene-environment interactions and epigenetic processes. The action of natural selection brings order to those processes, but a very complex and difficult order to understand. Consider the immune system of higher organisms as an illuminating example. This type of immune system is generally thought to be composed of interacting components of innate and acquired cell-mediated responses (Rao 2005). The latter component is specifically designed to engage in life-long learning and to be capable of producing a very large distribution of lymphocyte cell types through processes of genetic recombination and differential cell reproduction due to the history of antigen exposure. This system is energetically expensive to build and produce, and competes directly with other processes affecting fitness, such as growth and reproduction. However, those large investments in the immune system evolved because they reduce mortality sufficiently over the life course in an ecological context of rapid reproductive rates of evolving populations of diverse pathogens. The overall effects on fitness of such expensive protection must be positive. The ultimate goal in the biodemography of aging should be to understand the processes linking genes to phenotypes, phenotypes to mortality and fertility outcomes, and those outcomes to gene distributions over generational time. This will require both mechanistic physical models and specific theories of how natural selection acts to order those processes, both within populations of a single species and among species in evolving ecosystems. …