In this article, I consider the term “environment” in various claims and models by evolutionists and ecologists. I ask whether “environment” is amenable to a philosophical explication, in the same way some key terms of evolutionary theorizing such as “fitness,” “species,” or more recently “population” have been. I will claim that it cannot. In the first section, I propose a typology of theoretical terms, according to whether they are univocal or equivocal, and whether they have been the object of formal (...) or conceptual attempts of clarification. “Environment” will appear to be in a position similar to “population,” yet almost no extant attempt has been made to make sense of its meaning and reference. In the second section, I will present several theoretical claims or issues that refer to “environment” in apparently very diverse ways, but always supposing a contrastive term, which is not always the same. The third section directly considers models in evolution and in ecology, and asks “where” in them is the environment term. The fourth section proposes that “environment” refers to a distinction between a varying and an invariant term, but shows that this does not exhaust its meaning, which requires making more conceptual differences. Then, I take on the suggestion that there might be two “environment” terms, one in ecology and one in evolution, but show that is not the case. Finally I center on the specific notion of “complex environment,” which is the object of several research programs, and propose a typology of “complex environments” across theories. (shrink)

In this paper I critically evaluate Reisman and Forber’s :1113–1123, 2005) arguments that drift and natural selection are population-level causes of evolution based on what they call the manipulation condition. Although I agree that this condition is an important step for identifying causes for evolutionary change, it is insufficient. Following Woodward, I argue that the invariance of a relationship is another crucial parameter to take into consideration for causal explanations. Starting from Reisman and Forber’s example on drift and after having (...) briefly presented the criterion of invariance, I show that once both the manipulation condition and the criterion of invariance are taken into account, drift, in this example, should better be understood as an individual-level rather than a population-level cause. Later, I concede that it is legitimate to interpret natural selection and drift as population-level causes when they rely on genuinely indeterministic events and some cases of frequency-dependent selection. (shrink)

Single-case and long-run propensity theories are among the main objective interpretations of probability. There have been various objections to these theories, e.g. that it is difficult to explain why propensities should satisfy the probability axioms and, worse, that propensities are at odds with these axioms, that the explication of propensities is circular and accordingly not informative, and that single-case propensities are metaphysical and accordingly non-scientific. We consider various propensity theories of probability and their prospects in light of these objections. We (...) argue that while propensity theories face challenges, these challenges do not undermine their validity as prospective interpretations of probability in science. (shrink)

This volume focuses on various questions concerning the interpretation of probability and probabilistic reasoning in biology and physics. It is inspired by the idea that philosophers of biology and philosophers of physics who work on the foundations of their disciplines encounter similar questions and problems concerning the role and application of probability, and that interaction between the two communities will be both interesting and fruitful. In this introduction we present the background to the main questions that the volume focuses on (...) and summarize the highlights of the individual contributions. (shrink)

I define a concept of causal probability and apply it to questions about the role of probability in evolutionary processes. Causal probability is defined in terms of manipulation of patterns in empirical outcomes by manipulating properties that realize objective probabilities. The concept of causal probability allows us see how probabilities characterized by different interpretations of probability can share a similar causal character, and does so in such way as to allow new inferences about relationships between probabilities realized in different chance (...) setups. I clarify relations between probabilities and properties defined in terms of them, and argue that certain widespread uses of computer simulations in evolutionary biology show that many probabilities relevant to evolutionary outcomes are causal probabilities. This supports the claim that higher-level properties such as biological fitness and processes such as natural selection are causal properties and processes, contrary to what some authors have argued. (shrink)