H Allen Orr’s research while affiliated with University of Rochester and other places

Significance An important puzzle in economics concerns the equity premium. Why does anyone hold bonds given the option of holding stocks? Stocks are riskier, but they do much better on average in the long run than bonds, thus generating the equity premium puzzle. Standard economic models of preferences have difficulty accounting for this anomaly on the basis of a level of risk aversion that is consistent with risk-taking behavior elsewhere. We show that considering the biological basis of preferences is fruitful here. Biological evolution predicts that individuals should be more averse to aggregate—shared—risks than they are to risks that are idiosyncratic—personal. Since the stock market involves aggregate risk, this helps to resolve the puzzle.

Biological change and social change are similar. Both involve attempts to alter complex arrangements that have been pieced together through long periods of time. And both run the risk of unintended consequences. In biology, an apparently helpful mutation that confers, say, insecticide resistance in an insect might inadvertently also cause, say, sterility. And in societies, an apparently helpful change to correct a conspicuous problem might inadvertently also cause other, perhaps more serious, problems. Biological and social change also differ in some ways. Biological evolution depends on a random process of mutation whereas social change involves agents who sometimes rationally conceive of ideas directed at fixing a problem. Evolutionary biologists have modeled biological change using Fisher’s so-called geometric model of adaptation. Here we slightly modify Fisher’s model to study social change. We find that, even when agents (e.g., central planners) are skilled enough to perfectly correct the problem that they set out to fix, unintended consequences are so common and severe that half the time society is left worse off than before. Put differently, the median society is no better or worse off after a “perfect” intervention than before.

Most population genetic theory assumes that populations adapt to an environmental change without a change in population size. However, environmental changes might be so severe that populations decline in size and, without adaptation, become extinct. This "evolutionary rescue" scenario differs from traditional models of adaptation in that rescue involves a race between adaptation and extinction. While most previous work has usually focused on models of evolutionary rescue in haploids, here we consider diploids. In many species, diploidy introduces a novel feature into adaptation: adaptive evolution might occur either on sex chromosomes or on autosomes. Previous studies of nonrescue adaptation revealed that the relative rates of adaptation on the X chromosome versus autosomes depend on the dominance of beneficial mutations, reflecting differences in effective population size and the efficacy of selection. Here, we extend these results to evolutionary rescue and find that, given equal-sized chromosomes, there is greater parameter space in which the X is more likely to contribute to adaptation than the autosomes relative to standard nonrescue models. We also discuss how subtle effects of dominance can increase the chance of evolutionary rescue in diploids when absolute heterozygote fitness is close to 1. These effects do not arise in standard nonrescue models.

Natural selection is not perfectly efficient: it does not cause the instantaneous substitution of a beneficial mutation. Instead, substitution takes time, reflecting the statistical consequences of fitness differences over some number of generations. In this note, I suggest two measures of the efficiency of natural selection during gene substitution. I compare these measures against both ideal (instantaneous) and failed evolution. I also compare these measures to Haldane's cost of natural selection.

We propose an evolutionary framework for optimal portfolio growth theory in which investors subject to environmental pressures allocate their wealth between two assets. By considering both absolute wealth and relative wealth between investors, we show that different investor behaviors survive in different environments. When investors maximize their relative wealth, the Kelly criterion is optimal only under certain conditions, which are identified. The initial relative wealth plays a critical role in determining the deviation of optimal behavior from the Kelly criterion regardless of whether the investor is myopic across a single time period or maximizing wealth over an infinite horizon. We relate these results to population genetics, and discuss testable consequences of these findings using experimental evolution.

Attempts to use evolutionary ideas in finance have often neglected mathematical population genetics. Population genetics provides a natural approach to certain problems in finance that involve the relative wealth that accrues to competing investment strategies. In our model, competing investment strategies differ only in their allocation to a risky asset versus a riskless asset. Here we use results from the population genetics of natural selection to find the investment strategy that maximizes the expected increase in relative wealth. Though we focus on single-period analysis, some of our key findings are reminiscent of those from the growth optimal portfolio literature, e.g., the Kelly criterion.

Evolutionary rescue occurs when a population that is threatened with extinction by an environmental change adapts to the change sufficiently rapidly to survive. Here we extend the mathematical theory of evolutionary rescue. In particular, we model evolutionary rescue to a sudden environmental change when adaptation involves evolution at a single locus. We consider adaptation using either new mutations or alleles from the standing genetic variation that begin rare. We obtain several results: i) the total probability of evolutionary rescue from either new mutation or standing variation; ii) the conditions under which rescue is more likely to involve a new mutation versus an allele from the standing genetic variation; iii) a mathematical description of the U-shaped curve of total population size through time, conditional on rescue; and iv) the time until the average population size begins to rebound as well as the minimal expected population size experienced by a rescued population. Our analysis requires taking into account a subtle population-genetic effect (familiar from the theory of genetic hitchhiking) that involves "oversampling" of those lucky alleles that ultimately sweep to high frequency. Our results are relevant to conservation biology, experimental microbial evolution, and medicine (e.g., the dynamics of antibiotic resistance).

Infrastructure needs and opportunities in evolutionary biology. (DOCX)

An example of the enormous phylogenetic trees that soon will represent the norm in phylogenetic analyses. This is the consensus tree of the maximum likelihood phylogenies for 55,473 species of seed plants with the location of significant shifts in species diversification rates marked in red across the tree. Adapted from [4]. (TIF)