The Tanner Lectures are a collection of educational and scientific discussions relating to human values. Conducted by leaders in their fields, the lectures are presented at prestigious educational facilities around the world.

The problem of how to make optimal choices in the face of risk arises in both economics/decision theory and also evolutionary biology; in the former, ‘optimal’ means utility maximizing, while in the latter it means fitness maximizing. This article explores the links, thematic and formal, between the economic and evolutionary theories of optimal choice in risky situations, with particular reference to the relationship between utility and fitness. It is argued that the link is strongest between evolution and ‘nonexpected’ utility theory, (...) rather than traditional expected utility theory. (shrink)

Biologists studying ecology and evolution use the term “population” in many different ways. Yet little philosophical analysis of the concept has been done, either by biologists or philosophers, in contrast to the voluminous literature on the concept of “species.” This is in spite of the fact that “population” is arguably a far more central concept in ecological and evolutionary studies than “species” is. The fact that such a central concept has been employed in so many different ways is potentially problematic (...) for the reason that inconsistent usages (especially when the usage has not been made explicit) might lead to false controversies in which disputants are simply talking past one another. However, the inconsistent usages are not the only, or even the most important reason to examine the concept. If any set of organisms is legitimately called a “population,” selection and drift processes become purely arbitrary, too. Moreover, key ecological variables, such as abundance and distribution, depend on a nonarbitrary way of identifying populations. I sketch the beginnings of a population concept, drawing inspiration from the Ghiselin-Hull individuality thesis, and show why some alternative approaches are nonstarters. (shrink)

The dominant view among macroeconomists is that macroeconomics reduces to microeconomics, both in the sense that all macroeconomic phenomena arise out of microeconomic phenomena and in the sense that macroeconomic theory—to the extent that it is correct—can be derived from microeconomic theory. More than that, the dominant view believes that macroeconomics should in practice use the reduced microeconomic theory: this is the program of microfoundations for macroeconomics to which the vast majority of macroeconomists adhere. The "microfoundational" models that they actually (...) employ are, however, characterized by another feature: they are highly idealized, even when they are applied as direct characterizations of actual data, which itself consists of macroeconomic aggregates. This paper explores the interrelationship between reductionism and idealization in the microfoundational program and the role of idealization in empirical modeling. (shrink)

Ecologists have proposed several incompatible definitions of ecological stability. Emulating physicists, mathematical ecologists commonly define it as Lyapunov stability. This formalizes the problematic concept by integrating it into a well‐developed mathematical theory. The formalization also seems to capture the intuition that ecological stability depends on how ecological systems respond to perturbation. Despite these advantages, this definition is flawed. Although Lyapunov stability adequately characterizes perturbation responses of many systems studied in physics, it does not for ecological systems. This failure reveals a (...) limitation of its underlying mathematical theory, and an important difference between dynamic systems modeling in physics and ecology. *Received March 2006; revised June 2008. †To contact the author, please write to: Philosophy Department, 151 Dodd Hall, Florida State University, Tallahassee, FL 32306; e‐mail: [email protected]. (shrink)

Ecologists attempt to understand the diversity of life with mathematical models. Often, mathematical models contain simplifying idealizations designed to cope with the blooming, buzzing confusion of the natural world. This strategy frequently issues in models whose predictions are inaccurate. Critics of theoretical ecology argue that only predictively accurate models are successful and contribute to the applied work of conservation biologists. Hence, they think that much of the mathematical work of ecologists is poor science. Against this view, I argue that model (...) building is successful even when models are predictively inaccurate for at least three reasons: models allow scientists to explore the possible behaviors of ecological systems; models give scientists simplified means by which they can investigate more complex systems by determining how the more complex system deviates from the simpler model; and models give scientists conceptual frameworks through which they can conduct experiments and fieldwork. Critics often mistake the purposes of model building, and once we recognize this, we can see their complaints are unjustified. Even though models in ecology are not always accurate in their assumptions and predictions, they still contribute to successful science. (shrink)

Reductionism is often understood to include two theses: (1) every singular occurrence that the special sciences can explain also can be explained by physics; (2) every law in a higher-level science can be explained by physics. These claims are widely supposed to have been refuted by the multiple realizability argument, formulated by Putnam (1967, 1975) and Fodor (1968, 1975). The present paper criticizes the argument and identifies a reductionistic thesis that follows from one of the argument's premises.

Ecological communities, I argue, are objective units of nature if theyhave structure that regulates their membership. Evidence of suchstructure in contemporary ecology is scant, but the palaeoecologicalphenomenon of co-ordinated stasis is a prima facie example ofinternal regulation. I argue that no individualist attempts to explainaway the appearance of internal regulation succeeds. But no internalistmodel is fully satisfactory, either, in explaining the contrast betweenpre and post Pleistocene ecology.

This chapter contains section titled: Introduction Emergence of the Stability‐Diversity—Complexity Debate Mathematization of Ecological Stability The End of the Consensus Contextualization and Classification of Ecological Stability Measures of Ecological Diversity and Complexity Evaluating Stability‐Diversity—Complexity Relationships Acknowledgments References Further Reading.