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)

Evolutionary processes such as natural selection and random drift are commonly regarded as causes of population-level change. We respond to a recent challenge that drift and selection are best understood as statistical trends, not causes. Our reply appeals to manipulation as a strategy for uncovering causal relationships: if you can systematically manipulate variable A to bring about a change in variable B, then A is a cause of B. We argue that selection and drift can be systematically manipulated to produce (...) different kinds of population-level change. They should therefore be regarded as causes. (shrink)

Do evolutionary processes such as selection and random drift cause evolutionary change, or are they merely convenient ways of describing or summarizing it? Philosophers have lined up on both sides of this question. One recent defense (Reisman and Forber 2005) of the causal status of selection and drift appeals to a manipulability theory of causation. Yet, even if one accepts manipulability, there are still reasons to doubt that genetic drift, in particular, is genuinely causal. We will address two challenges to (...) treating drift as causal within a manipulation framework. We will argue that both challenges ultimately fail, but that they raise interesting and subtle issues about the nature of causation and the differences between selection and drift. ‡Thanks to audiences at the ‘PBDB1' Conference and the 2006 PSA Meeting for valuable feedback. †To contact the authors, please write to: Patrick Forber, Tufts University, Philosophy Department, Miner Hall, Medford, MA 02155; e-mail: [email protected]. (shrink)

Biological phenomena can be investigated at multiple levels, from the molecular to the cellular to the organismic to the ecological. In typical biology instruction, these levels have been segregated. Yet, it is by examining the connections between such levels that many phenomena in biology, and complex systems in general, are best explained. We describe a computation-based approach that enables students to investigate the connections between different biological levels. Using agent-based, embodied modeling tools, students model the microrules underlying a biological phenomenon (...) and observe the resultant aggregate dynamics. We describe 2 cases in which this approach was used. In both cases, students framed hypotheses, constructed multiagent models that incorporate these hypotheses, and tested these by running their models and observing the outcomes. Contrasting these cases against traditionally used, classical equation-based approaches, we argue that the embodied modeling approach connects more directly to students’ experience, enables extended investigations as well as deeper understanding, and enables “advanced” topics to be productively introduced into the high school curriculum. (shrink)

In this article I challenge the widely held assumption that human culture is inherited by means of social learning. First, I address the distinction between “social” learning and “individual” learning. I argue that most cultural ideas are not acquired by one form of learning or the other, but from a hybrid of both. Second, I discuss how individual learning can interact with niche construction. I argue that these processes collectively provide a non-social route for learned ideas to be inherited and (...) cumulatively modified. I conclude that human culture is not inherited by social learning alone; the capacities to learn from and modify our environments also play a significant role. (shrink)