Despite the burgeoning interest in new and more complex accounts of the organism-environment dyad by biologists and philosophers, little attention has been paid in the resulting discussions to the history of these ideas and to their deployment in disciplines outside biology—especially in the social sciences. Even in biology and philosophy, there is a lack of detailed conceptual models of the organism-environment relationship. This volume is designed to fill these lacunae by providing the first multidisciplinary discussion of the topic of organism-environment (...) interaction. It brings together scholars from history, philosophy, psychology, anthropology, medicine, and biology to discuss the common focus of their work: entangled life, or the complex interaction of organisms and environments. (shrink)

The use of multiple means of determination to “triangulate” on the existence and character of a common phenomenon, object, or result has had a long tradition in science but has seldom been a matter of primary focus. As with many traditions, it is traceable to Aristotle, who valued having multiple explanations of a phenomenon, and it may also be involved in his distinction between special objects of sense and common sensibles. It is implicit though not emphasized in the distinction between (...) primary and secondary qualities from Galileo onward. It is arguably one of several conceptions involved in Whewell’s method of the “consilience of inductions” (Laudan 1971) and is to be found in several places in Peirce. (From M. Brewer and B. Collins, eds., (1981); Scientific Inquiry in the Social Sciences (a festschrift for Donald T. Campbell), San Francisco: Jossey-Bass, pp. 123–162.). (shrink)

Theorizing in ecology and evolution often proceeds via the construction of multiple idealized models. To determine whether a theoretical result actually depends on core features of the models and is not an artifact of simplifying assumptions, theorists have developed the technique of robustness analysis, the examination of multiple models looking for common predictions. A striking example of robustness analysis in ecology is the discovery of the Volterra Principle, which describes the effect of general biocides in predator-prey systems. This paper details (...) the discovery of the Volterra Principle and the demonstration of its robustness. It considers the classical ecology literature on robustness and introduces two individual-based models of predation, which are used to further analyze the Volterra Principle. The paper also introduces a distinction between parameter robustness, structural robustness, and representational robustness, and demonstrates that the Volterra Principle exhibits all three kinds of robustness. *Received September 2006; revised May 2007. ‡Earlier versions of this paper were presented at the Australasian Association of Philosophy, the London School of Economics, and the University of Bristol. The authors wish to thank those audiences as well as Patrick Forber, Ken Waters, Deena Skolnick Weisberg, Uri Wilensky, and Bill Wimsatt for many helpful comments. Special thanks to Giacomo Sillari for his assistance in translating Volterra's original paper and his insightful thoughts about Volterra's aims and methods. Some of the research in this paper was supported by NSF grant SES-0620887 to MW. †To contact the authors, please write to: Michael Weisberg, Department of Philosophy, University of Pennsylvania, 433 Logan Hall, Philadelphia, PA 19104; e-mail: [email protected]; Kenneth Reisman, Pluribo, Inc., 100 Park Avenue, Suite 1600, New York, NY 10017; e-mail: [email protected]. (shrink)

Recently, a number of philosophers of biology have endorsed views about random drift that, we will argue, rest on an implicit assumption that the meaning of concepts such as drift can be understood through an examination of the mathematical models in which drift appears. They also seem to implicitly assume that ontological questions about the causality of terms appearing in the models can be gleaned from the models alone. We will question these general assumptions by showing how the same equation (...) — the simple 2 = p2 + 2pq + q2 — can be given radically different interpretations, one of which is a physical, causal process and one of which is not. This shows that mathematical models on their own yield neither interpretations nor ontological conclusions. Instead, we argue that these issues can only be resolved by considering the phenomena that the models were originally designed to represent and the phenomena to which the models are currently applied. When one does take those factors into account, starting with the motivation for Sewall Wright’s and R.A. Fisher’s early drift models and ending with contemporary applications, a very different picture of the concept of drift emerges. On this view, drift is a term for a set of physical processes, namely, indiscriminate sampling processes. (shrink)

I claim that the balance of nature metaphoris shorthand for a paradigmatic view of natureas a beneficent force. I trace the historicalorigins of this concept and demonstrate that itoperates today in the discipline of populationecology. Although it might be suspected thatthis metaphor is a pre-theoretic description ofthe more precisely defined notion ofequilibrium, I demonstrate that balance ofnature has constricted the meaning ofmathematical equilibrium in population ecology.As well as influencing the meaning ofequilibrium, the metaphor has also loaded themathematical term with values.Environmentalists (...) and critics use thisconflation of meaning and value to theiradvantage. This interplay between the balanceof nature and equilibrium fits aninteractionist interpretation of the role ofmetaphor in science. However, it seems theinteraction is asymmetric, and the balance ofnature metaphor has had a larger influence onmathematical equilibrium than vice versa. Thisdisproportionate influence suggests that themetaphor was and continues to be a constitutivepart of ecological theories. (shrink)

This paper gives a detailed narrative of a controversial empirical research in postwar population genetics, the analysis of the cytological polymorphisms of an Australian grasshopper, Moraba scurra. This research intertwined key technical developments in three research areas during the 1950s and 1960s: it involved Dobzhansky’s empirical research program on cytological polymorphisms, the mathematical theory of natural selection in two-locus systems, and the building of reliable estimates of natural selection in the wild. In the mid-1950s the cytologist Michael White discovered an (...) interesting case of epistasis in populations of Moraba scurra. These observations received a wide diffusion when theoretical population geneticist Richard Lewontin represented White’s data on adaptive topographies. These topographies connected the information on the genetic structure of these grasshopper populations with the formal framework of theoretical population genetics. As such, they appeared at the time as the most successful application of two-locus models of natural selection to an empirical study system. However, this connection generated paradoxical results: in the landscapes, all grasshopper populations were located on a ridge while they were expected to reach a peak. This puzzling result fueled years of research and triggered a controversy attracting contributors from Australia, the United States and the United Kingdom. While the original problem seemed, at first, purely empirical, the subsequent controversy affected the main mathematical tools used in the study of two-gene systems under natural selection. Adaptive topographies and their underlying mathematical structure, Wright’s mean fitness equations, were submitted to close scrutiny. Suspicion eventually shifted to the statistical machinery used in data analysis, reflecting the crucial role of statistical inference in applied population genetics. In the 1950s and 1960s, population geneticists were not simply in search for new generalizations about the evolutionary process and for new evidence about genetic variation: struggling against statistical artifacts, they were searching for reliable tests and descriptors to analyze their data. (shrink)

Wright’s “adaptive landscape” has been influential in evolutionary thinking but controversial, especially because the landscape that organisms encounter is altered by the evolutionary process itsel...

This is the second of two articles in which I reflect on “generalized Darwinism” as currently discussed in evolutionary economics. In the companion article (Callebaut, Biol Theory 6. doi: 10.1007/s13752-013-0086-2, 2011, this issue) I approached evolutionary economics from the naturalistic perspectives of evolutionary epistemology and the philosophy of biology, contrasted evolutionary economists’ cautious generalizations of Darwinism with “imperialistic” proposals to unify the behavioral sciences, and discussed the continued resistance to biological ideas in the social sciences. Here I assess Generalized Darwinism (...) as propounded by Geoffrey Hodgson, Thorbjørn Knudsen, and others, concentrating on the roles of theory and model building in science (and the roles of analogy and metaphor therein), generative replication, and the relation between selection and self-organization. I then point to advances in current biology that promise to be more fruitful as sources of inspiration for evolutionary economics than the project to generalize Darwinism in its current, “hardened Modern Synthesis” form; and I draw some conclusions. (shrink)