International Society for History, Philosophy, and Social Studies of Biology


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Program

MONDAY, JULY 6  /  09:00 - 10:30  /  DS-1520
Individual papers
Measuring Evolutionary Forces

Challenges for determining which traits are selected for and to what degree

Wes Anderson (Arizona State University, United States)

Biologists often use selection gradients or selection differentials, not merely to determine that selection is occurring on traits, but also to determine which traits are selected for and to what degree. I hold that to make such determinations one must be able to make claims like: this trait is selected for in this context but selected against in that context. Modeling interactive causation is a necessary and sufficient condition for making claims of this kind. Selection gradients represent the expected effect of interactive variable or type causation. Selection differentials represent the covariance of a trait variable and a fitness variable, relative to a token context. Then either (1) selection is individuated at a type level and conceptualized as merely influencing the expectation over fitness or (2) selection is individuated at a token level and conceptualized as having to do with how two variables covary in a token context. I argue that neither consequence for determining which traits are selected for and to what degree is particularly appealing.


In search of invariance in evolutionary biology

Jun Otsuka (Kobe University, Japan)

The ontological and epistemological status of evolutionary principles has long been a topic of various discussions in the philosophy of biology. Are they empirical laws or mathematical tautologies? Do they represent dynamical processes or statistical patterns? Equally controversial is the nature of the concepts used in these principles or of the objects to which they are supposed to apply. What is fitness, phenotype, or gene? Do evolutionary equations apply to groups as well as individuals? If so, do they represent the same or different process(es)? In physics, the nature of laws has been studied by using the concept of invariance. The principal idea is that the form of physical laws must be invariant through a specified group of transformations. In classical non-relativistic mechanics, for example, the Newtonian laws and the distance between two objects do not depend on frames of reference related to each other by the so-called Galilean transformations. It is such invariance through a transformation group that makes physical laws and properties objective. The centrality and success of invariance principle in contemporary physics suggests that a similar approach may be useful in understanding the nature of evolutionary laws or equations. In this presentation I try to portray the philosophical puzzles about evolutionary principles as different facets of the same problem: the lack of a definite invariance principle in evolutionary theory. If this is correct, an effective approach would be to find an appropriate group of transformations through which evolutionary principles remain invariant. With this prospect, I explore what these transformations might look like in some simple cases of evolutionary genetics.


Quantifying form versus function in current evolutionary transitions

Roger Sansom (Texas A & M University, United States)

I take the form/function debate to be an empirical issue about the relative contribution to evolution from (a) the bias in the production of variation (due to probabilistic developmental constraints) and (b) the bias in elimination of variation (due to probabilistic natural selection). I develop a model that combines these two influences to predict a population’s current path through morphospace to a local optimum and calculate the relative contribution of each bias to that path. Any such analysis is relative to the traits concerned, but there is no upper limit to how many traits can be included in an analysis and increasing that number should improve objectivity. The most important predictor in this model is a fact about the relationship between extant trait values in a population that is relatively easy to discover. The reason for its importance shall be discussed.