So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Human biochemical genetics

From the Publisher:
The old opposition of matter versus mind stubbornly persists in the way we study mind and brain. In treating cognition as problem solving, Andy Clark suggests, we may often abstract too far from the very body and world in which our brains evolved to guide us. Whereas the mental has been treated as a realm that is distinct from the body and the world, Clark forcefully attests that a key to understanding brains is to see them as controllers of embodied activity. From this paradigm shift he advances the construction of a cognitive science of the embodied mind.

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Being There: Putting Brain, Body, and World Together Again

Criticism and the Growth of Knowledge. Edited by I. Lakatos and A. Musgrave. Pp. viii, 282. £3·50, paperback £1. 1970. (Cambridge University Press.)

Beginning with Emlen (1966) and MacArthur and Pianka (1966) and extending through the last ten years, several authors have sought to predict the foraging behavior of animals by means of mathematical models. These models are very similar,in that they all assume that the fitness of a foraging animal is a function of the efficiency of foraging measured in terms of some "currency" (Schoener, 1971) -usually energy- and that natural selection has resulted in animals that forage so as to maximize this fitness. As a result of these similarities, the models have become known as "optimal foraging models"; and the theory that embodies them, "optimal foraging theory." The situations to which optimal foraging theory has been applied, with the exception of a few recent studies, can be divided into the following four categories: (1) choice by an animal of which food types to eat (i.e., optimal diet); (2) choice of which patch type to feed in (i.e., optimal patch choice); (3) optimal allocation of time to different patches; and (4) optimal patterns and speed of movements. In this review we discuss each of these categories separately, dealing with both the theoretical developments and the data that permit tests of the predictions. The review is selective in the sense that we emphasize studies that either develop testable predictions or that attempt to test predictions in a precise quantitative manner. We also discuss what we see to be some of the future developments in the area of optimal foraging theory and how this theory can be related to other areas of biology. Our general conclusion is that the simple models so far formulated are supported are supported reasonably well by available data and that we are optimistic about the value both now and in the future of optimal foraging theory. We argue, however, that these simple models will requre much modification, espicially to deal with situations that either cannot easily be put into one or another of the above four categories or entail currencies more complicated that just energy.

Citation classic - optimal foraging - a selective review of theory and tests

It comes as something ofa surprise to reflect that the New York Review ofBooks is now over twenty years old. Even people of my generation (that is, old enough to remember the revolutionary 196os but not young enough to have taken a very exciting part in them) think of the paper as eternally youthful. In fact, it has gone through years of relatively quiet life, yet, as always in a competitive journalistic market, it is the controversies that attract the interest of the reader and to which the history (especially an admittedly impressionistic survey that tries to include something of the intellectual context in which a journal has operated) must give some attention. Not all the attacks which the New York Review has attracted, both early in its career and more recently, are worth more than a brief summary. What do we now make, for example, of Richard Kostelanetz's forthright accusation that 'The New York Review was from its origins destined to publicize Random House's (and especially [Jason] Epstein's) books and writers'?1 Well, simply that, even if the statistics bear out the charge (and Kostelanetz provides some suggestive evidence to support it, at least with respect to some early issues), there is nothing surprising in a market economy about a publisher trying to push his books through the pages of a journal edited by his friends. True, the New York Review has not had room to review more than around fifteen books in each issue and there could be a bias in the selection of

http://www.jstor.org/stable/pdfplus/3507774.pdf

The New York Review of Books

In Discovering Complexity, William Bechtel and Robert Richardson examine two heuristics that guided the development of mechanistic models in the life sciences: decomposition and localization. Drawing on historical cases from disciplines including cell biology, cognitive neuroscience, and genetics, they identify a number of "choice points" that life scientists confront in developing mechanistic explanations and show how different choices result in divergent explanatory models. Describing decomposition as the attempt to differentiate functional and structural components of a system and localization as the assignment of responsibility for specific functions to specific structures, Bechtel and Richardson examine the usefulness of these heuristics as well as their fallibility -- the sometimes false assumption underlying them that nature is significantly decomposable and hierarchically organized. When Discovering Complexity was originally published in 1993, few philosophers of science perceived the centrality of seeking mechanisms to explain phenomena in biology, relying instead on the model of nomological explanation advanced by the logical positivists (a model Bechtel and Richardson found to be utterly inapplicable to the examples from the life sciences in their study). Since then, mechanism and mechanistic explanation have become widely discussed. In a substantive new introduction to this MIT Press edition of their book, Bechtel and Richardson examine both philosophical and scientific developments in research on mechanistic models since 1993.

Discovering Complexity: Decomposition and Localization as Strategies in Scientific Research

Human beings, like other organisms, are the products of evolution Like other organisms, we exhibit traits that are the product of natural selection Our psychological capacities are evolved traits as much as are our gait and posture This much few would dispute Evolutionary psychology goes further than this, claiming that our psychological traits -- including a wide variety of traits, from mate preference and jealousy to language and reason -- can be understood as specific adaptations to ancestral Pleistocene conditions In Evolutionary Psychology as Maladapted Psychology, Robert Richardson takes a critical look at evolutionary psychology by subjecting its ambitious and controversial claims to the same sorts of methodological and evidential constraints that are broadly accepted within evolutionary biology The claims of evolutionary psychology may pass muster as psychology; but what are their evolutionary credentials? Richardson considers three ways adaptive hypotheses can be evaluated, using examples from the biological literature to illustrate what sorts of evidence and methodology would be necessary to establish specific evolutionary and adaptive explanations of human psychological traits He shows that existing explanations within evolutionary psychology fall woefully short of accepted biological standards The theories offered by evolutionary psychologists may identify traits that are, or were, beneficial to humans But gauged by biological standards, there is inadequate evidence: evolutionary psychologists are largely silent on the evolutionary evidence relevant to assessing their claims, including such matters as variation in ancestral populations, heritability, and the advantage offered to our ancestors As evolutionary claims they are unsubstantiated Evolutionary psychology, Richardson concludes, may offer a program of research, but it lacks the kind of evidence that is generally expected within evolutionary biology It is speculation rather than sound science -- and we should treat its claims with skepticism

Evolutionary Psychology as Maladapted Psychology

Evolutionary Psychology (EP) views the human mind as organized into many modules, each underpinned by psychological adaptations designed to solve problems faced by our Pleistocene ancestors. We argue that the key tenets of the established EP paradigm require modification in the light of recent findings from a number of disciplines, including human genetics, evolutionary biology, cognitive neuroscience, developmental psychology, and paleoecology. For instance, many human genes have been subject to recent selective sweeps; humans play an active, constructive role in co-directing their own development and evolution; and experimental evidence often favours a general process, rather than a modular account, of cognition. A redefined EP could use the theoretical insights of modern evolutionary biology as a rich source of hypotheses concerning the human mind, and could exploit novel methods from a variety of adjacent research fields.

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Darwin in Mind: New Opportunities for Evolutionary Psychology

We will show that there is a strong form of emergence in cell biology. Beginning with C.D. Broad’s classic discussion of emergence, we distinguish two conditions sufficient for emergence. Emergence in biology must be compatible with the thought that all explanations of systemic properties are mechanistic explanations and with their sufficiency. Explanations of systemic properties are always in terms of the properties of the parts within the system. Nonetheless, systemic properties can still be emergent. If the properties of the components within the system cannot be predicted, even in principle, from the behavior of the system’s parts within simpler wholes then there also will be systemic properties which cannot be predicted, even in principle, on basis of the behavior of these parts. We show in an explicit case study drawn from molecular cell physiology that biochemical networks display this kind of emergence, even though they deploy only mechanistic explanations. This illustrates emergence and its place in nature.

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Emergence and Its Place in Nature: A Case Study of Biochemical Networks

It is here argued that functionalist constraints on psychology do not preclude the applicability of classic forms of reduction and, therefore, do not support claims to a principled, or de jure, autonomy of psychology. In Part I, after isolating one minimal restriction any functionalist theory must impose on its categories, it is shown that any functionalism imposing an additional constraint of de facto autonomy must also be committed to a pure functionalist--that is, a computationalist--model for psychology. Using an extended parallel to the reduction of Mendelian to molecular genetics, it is shown in Parts II and III that, contrary to the claims of Hilary Putnam and Jerry Fodor, there is no inconsistency between computational models and classical reductionism: neither plurality of physical realization nor plurality of function are inconsistent with reductionism as defended by Ernest Nagel. Employing the results of Part I, the conclusions of Parts II and III are generalized in Part IV to cover any version...

Robert C. Richardson

Papers

Discovering Complexity: Decomposition and Localization as Strategies in Scientific Research

Evolutionary Psychology as Maladapted Psychology

Darwin in Mind: New Opportunities for Evolutionary Psychology

Emergence and Its Place in Nature: A Case Study of Biochemical Networks

Functionalism and Reductionism