Ecology is the study of the interactions of organisms and their environments. The methods of ecology fall roughly into three categories: descriptive surveys of patterns of species and resource distribution and abundance, theoretical modeling, and experimental manipulations. Ecological systems are “open” systems, and patterns and processes are products of a huge number of interacting forces. Ecology and the environmental sciences have made enormous advances since the mid-twentieth century in the understanding of ecological systems, as well as in the human impact (...) on the environment. Theory in ecology usually centers on the development of models. Environmental outcomes are uncertain and when making decisions under uncertainty, there are a variety of options available. One option is to carry out a cost benefit analysis based upon expected utilities and other is to adopt the precautionary principle. Uncertainty and under determination of theory by evidence is a fact of life in science. (shrink)

The recent literature in philosophy of biology has drawn attention to the different sorts of explanations proffered in the biological sciences—we have molecular, biomedical, and evolutionary explanations. Do these explanations all have a common structure or relation that they seek to capture? This paper will answer in the negative. I defend a pluralistic and pragmatic approach to explanation. Using examples from classical population genetics, I argue that formal demonstrations, and even strictly “mathematical truths,” may serve as explanatory in different historical (...) contexts. (shrink)

The object of this paper is to reply to Morrison's ([2000]) claim that while ‘structural unity’ was achieved at the level of the mathematical models of population genetics in the early synthesis, there was explanatory disunity. I argue to the contrary, that the early synthesis effected by the founders of theoretical population genetics was unifying and explanatory both. Defending this requires a reconsideration of Morrison's notion of explanation. In Morrison's view, all and only answers to ‘why’ questions which include the (...) ‘cause or mechanism’ for some phenomenon count as explanatory. In my view, mathematical demonstrations that answer ‘how possibly’ and ‘why necessarily’ questions may also count as explanatory. The authors of the synthesis explained how evolution was possible on a Mendelian system of inheritance, answered skepticism about the sufficiency of selection, and thus explained why and how a Darwinian research program was warranted. While today we take many of these claims as obvious, they required argument, and part of the explanatory work of the formal sciences is providing such arguments. Surely, Fisher and Wright had competing views as to the optimal means of generating adaptation. Nevertheless, they had common opponents and a common unifying and explanatory goal that their mathematical demonstrations served. Introduction: Morrison's challenge Fisher v. Wright revisited The early synthesis Conclusion: unification and explanation reconciled. (shrink)

Cancer is not one, but many diseases, and each is a product of a variety of causes acting (and interacting) at distinct temporal and spatial scales, or “levels” in the biological hierarchy. In part because of this diversity of cancer types and causes, there has been a diversity of models, hypotheses, and explanations of carcinogenesis. However, there is one model of carcinogenesis that seems to have survived the diversification of cancer types: the multi-stage model of carcinogenesis. This paper examines the (...) history of the multistage theory, and uses the theory as a case study in the limits and goals of unification as a theoretical virtue, comparing and contrasting it with “integrative” research. (shrink)

Cancer is not one, but many diseases, and each is a product of a variety of causes acting at distinct temporal and spatial scales, or ‘‘levels’’ in the biological hierarchy. In part because of this diversity of cancer types and causes, there has been a diversity of models, hypotheses, and explanations of carcinogenesis. However, there is one model of carcinogenesis that seems to have survived the diversification of cancer types: the multi-stage model of carcinogenesis. This paper examines the history of (...) the multistage theory, and uses the theory as a case study in the limits and goals of unification as a theoretical virtue, comparing and contrasting it with ‘‘integrative’’ research. (shrink)

I argued that the frameworks and mechanisms that produce unification do not enable us to explain why the unified phenomena behave as they do. That is, we need to look beyond the unifying process for an explanation of these phenomena. Anya Plutynski ([2005]) has called into question my claim about the relationship between unification and explanation as well as my characterization of it in the context of the early synthesis of Mendelism with Darwinian natural selection. In this paper I argue (...) that her methodological criticisms rest on a misinterpretation of my views on explanation and defend my historical interpretation of the work of Fisher and Wright. A statement of the problem Methodological differences: how to characterize explanation Historical matters: disagreements about details Explanation revisited: the possible versus the ‘merely actual’. (shrink)

A strong case has been made for the role and value of mechanistic reasoning in process-oriented sciences, such as molecular biology and neuroscience. This paper shifts focus to assess the role of mechanistic reasoning in an area where it is neither obvious nor expected: population genetics. Population geneticists abstract away from the causal-mechanical details of individual organisms and, instead, use mathematics to describe population-level, statistical phenomena. This paper, first, develops a framework for the identification of mechanistic reasoning where it is (...) not obvious: mathematical and mechanistic styles of scientific reasoning. Second, it applies this framework to demonstrate that both styles are integrated in modern investigations of evolutionary biology. Characteristic of the former, applied population genetic techniques provide statistical evidence for associations between genotype, phenotype, and fitness. Characteristic of the latter, experimental interventions provide causal-mechanical evidence for associations between the very same relationships, often in the same model organisms. The upshot is a richer perspective of how evolutionary biologists build evidence for hypotheses regarding adaptive evolution and a general framework for assessing the scope of mechanistic reasoning across the sciences. (shrink)

Godfrey-Smith ( 2001 ) has distinguished three types of adaptationism. This article builds on his analysis, and revises it in places, by distinguishing seven varieties of adaptationism. This taxonomy allows us to clarify what is at stake in debates over adaptationism, and it also helps to cement the importance of Gould and Lewontin’s ‘Spandrels’ essay. Some adaptationists have suggested that their essay does not offer any coherent alternative to the adaptationist programme: it consists only in an exhortation to test adaptationist (...) hypotheses more thoroughly than was usual in the 1970s. Here it is argued that the ‘Spandrels’ paper points towards a genuinely non-adaptationist methodology implicit in much evolutionary developmental biology. This conclusion helps to expose the links between older debates over adaptationism and more recent questions about the property of evolvability. (shrink)

The cis-regulatory hypothesis is one of the most important claims of evolutionary developmental biology. In this paper I examine the theoretical argument for cis-regulatory evolution and its role within evolutionary theorizing. I show that, although the argument has some weaknesses, it acts as a useful example for the importance of current scientific debates for science education.

Confirmation in evolutionary biology depends on what biologists take to be the genuine rivals. Investigating what constrains the scope of biological possibility provides part of the story: explaining how possible helps determine what counts as a genuine rival and thus informs confirmation. To clarify the criteria for genuine rivalry I distinguish between global and local constraints on biological possibility, and offer an account of how-possibly explanation. To sharpen the connection between confirmation and explaining how possible I discuss the view that (...) formal inquiry can provide a kind of confirmation-theoretic support for evolutionary models, and offer an example of how-possibly explanation interacting with testing practice. (shrink)

Proceedings of the Pittsburgh Workshop in History and Philosophy of Biology, Center for Philosophy of Science, University of Pittsburgh, March 23-24 2001 Session 4: Evolutionary Indeterminism.

Population genetics attempts to measure the influence of the causes of evolution, viz., mutation, migration, natural selection, and random genetic drift, by understanding the way those causes change the genetics of populations. But how does it accomplish this goal? After a short introduction, we begin in section (2) with a brief historical outline of the origins of population genetics. In section (3), we sketch the model theoretic structure of population genetics, providing the flavor of the ways in which population genetics (...) theory might be understood as incorporating causes. In sections (4) and (5) we discuss two specific problems concerning the relationship between population genetics and evolutionary causes, viz., the problem of conceptually distinguishing natural selection from random genetic drift, and the problem of interpreting fitness. In section (6), we briefly discuss the methodology and key epistemological problems faced by population geneticists in uncovering the causes of evolution. Section (7) of the essay contains concluding remarks. (shrink)