AppId is over the quota
Both Nature and Science are currently celebrating the 100th anniversary of the birth of an icon of logic, computer science, and mathematical biology: Alan Turing. In reading Andrew Hodges’s spectacular biography of Turing (1983) many years ago I came to appreciate that the subject of the book was both a deeply creative and extraordinarily rigorous thinker. Although Turing is known for seminal achievements in mathematical logic and computer science, his most directly practical and immediately consequential contribution was his facilitation of the Allied cause in World War II through his guidance of the effort to break the Nazi military code. This effort called primarily on his prodigious talents for far-reaching inference and it was in reading about this effort that I was prompted to consider a concept that might be called “maximum deduction.” Turing and his able colleagues needed to make every possible deductive inference (or at least very close to every possible inference) supported by the available data on German military communications in order to solve a problem of immense and immediate impact (the saving of Allied ships from devastating German submarine attacks).
In reading Samir Okasha’s thorough and insightful guide to the theoretical debates about multi-level selection, Evolution and the Levels of Selection (2006), I am reminded of Turing’s logical rigor. Like Turing, Okasha possesses the ability to fully explore the implications of an intellectual position. Of similar value, he makes key distinctions that elude or at least receive inadequate attention from others and fairly assesses alternative conceptual schemes or theoretical approaches. For example, his examination of the relative merits of the Price equation versus what he refers to as the “contextual analysis” for assessing and partitioning selection in differing evolutionary scenarios reveals that each has important advantages as well as significant weaknesses. Much to his credit, he does not seek a neat but oversimplified and misleading conclusion. The figures are simple but effective and substantially aid the exposition.
I cannot attempt to summarize all of the arguments in the book of about 240 pages because Okasha’s arguments are of sufficient intricacy and subtlety that it would be nearly impossible to substantially compress them without causing serious distortions in the reasoning. Therefore, I will just note the topics addressed and remark on a limited number of particularly interesting points.
Okasha begins the book by introducing and characterizing the levels-of-selection problem and explicating the essence of natural selection in abstract formal terms. He then addresses the distinction between the synchronic and diachronic perspectives, where the former deals with the hierarchical organization of the living world (e.g. cells, multicellular organisms, communities of multicellular organisms) such as it is and the latter is concerned with how the hierarchy arose. Next, the author introduces and explains the interpretation of the equation formulated by George Price forty years ago to describe in mathematical terms the evolution of a population from one generation to the next. He also delves into the sometimes-consequential differences between statistical and causal decompositions of changes in organismal characters across generation. This chapter ends with an interesting discussion of the connections between the Price equation and the formal conditions for evolution promulgated more than forty years ago by the eminent population geneticist, Richard Lewontin, which were initially described at the beginning of the chapter.
The second chapter explains the fundamentals of multi-level selection, including explorations of life cycles, relevant definitions of fitness, and the distinction between multi-level selection 1 (MLS1) and multi-level selection 2 (MLS2). For MLS1, what Okasha calls the ‘focal’ level is concerned with the number of offspring, in the next generation, of the particles that constitute a collective or group and for MLS2 the ‘focal’ level is concerned with the number of offspring groups in the succeeding generation. Another key distinction that Okasha addresses is that between aggregate and emergent properties of collectives. Okasha then tackles heritability and how the concept differs for MLS1 and MLS2 and includes a discussion of how the Price equation can be applied for the two types of multi-level selection.
Chapter three focuses on notions of causality and deals with the fairly subtle notion of cross-level by-products in which apparent selection on one level can in fact result from selection at another level. In this portion of the book, the author introduces contextual analysis, which relies on linear regression models, and compares it to the approach associated with the Price equation.
What the author describes as philosophical issues take up the fourth chapter. The section sub-headings will give a sense of the subject matter being addressed: emergence and additivity, screening off and the levels of selection, realism versus pluralism about the levels of selection, and reductionism.
Chapter five is entitled “The Gene’s-Eye View and its Discontents.” After tracing the gene-centered perspective back to R. A. Fisher and reviewing the contributions of individuals such as W. D. Hamilton, G. C. Williams, and Richard Dawkins, Okasha makes the critical distinction between a gene’s-eye view of evolution and genic selection. In this context, Okasha notes what he believes to be a shift in position by Dawkins. Next the author discusses outlaw genes or selfish genetic elements (SGEs). These DNA sequences manage to be transmitted at increased frequencies into the gametes (the phenomenon of meiotic drive or segregation distortion) and, therefore, into the next generation thereby exhibiting increased fitnesses relative to non-SGEs. Thus, I would suggest that selfishness is a quantitative not a qualitative trait. The Price equation and contextual analysis are then compared as to how these two approaches account for the behavior of SGEs. Okasha then demonstrates why the gene-centered perspective is not, as sometimes claimed, a completely general way to account for any evolutionary scenario, e.g., when dealing with non-genetic inheritance, plants that produce vegetative entities that are often genetically chimeric (i.e., ramets), and insect colonies founded by multiple queens or multiply-mated queens. The genic perspective also is less obviously successful when non-additive interactions between genes are present, which is reasonably common. An interesting point that Okasha makes is that whenever SGEs arise, there is likely to be selection on the unlinked ‘law abiding’ genetic elements to suppress the ‘cheaters’ since SGEs typically enhance their own fitnesses at the cost of diminishing the fitness of the organism with respect to which they may reasonably regarded as parasites of a sort.
The sixth chapter addresses the still active and evolving controversy or group selection as of 2006. Okasha provides historical background, discusses the distinction between MLS1 and MLS2 in the context of the controversy, explores how ideas about kin selection, reciprocal altruism, and evolutionary game theory feature in the debates, and describes the roles of a number of other concepts in the key disagreements in the literature.
The final two chapters address macroevolutionary issues that may be less obviously relevant to those focused on the relevance of evolution to medicine. Therefore, I will refrain from a detailed description of the content of these sections and just note an insight offered therein. Whenever there is a major evolutionary transition, as from individual genes to whole genomes or single-celled to multi-celled organisms, there must be selection against within-group conflict and selfishness of the ‘lower-level’ units and this selection must be effective for the more-complex level of the biological hierarchy to be successfully established. Thus, one consequence of relentless competition is cooperation and all genes are not, as Dawkins suggested early in The Selfish Gene (1976, 1989), ruthlessly selfish unless ruthless selfishness embodies some measure of cooperativeness.
References
Hodges, A. Alan Turing: The Enigma. A Touchstone Book, Simon & Schuster, Inc., New York, 1983.
Okasha, Samir. Evolution and the Levels of Selection. Oxford University press, 2006.
Dawkins, R. The Selfish Gene. Oxford University Press, Oxford, 1976, 1989 p. 2.
Tags: additive characters, Alan Turing, causal decomposition, cells, computer science, contextual analysis, cooperation, cross-level by-products, diachronic, emergent characters, evolution, evolutionary game theory, focal level, G. C. Williams, gametes, genes, gene’s-eye perspective, genic selection, George Price, hierarchical organization, kin selection, levels-of-selection controversy, logic, macroevolution, mathematics, maximum deduction, meiotic drive, military code, multi-cellular organisms, multi-level selection 1, multi-level selection 2, pluralism, Price equation, R. A. Fisher, realism, reciprocal altruism, reductionism, Richard Dawkins, Richard Lewontin, selfish genetic element, statistical decomposition, synchronic, W. D. Hamilton
0 comments:
Post a Comment