Analysis of Evolutionary Analysis

Biology is a hot subject. There's already a fourth edition out of Freeman and Herron's Evolutionary Analysis, but such is life that I tend to get books faster than I read them, so I only recently got around to reading the book I bought a couple of years ago.

We know that currently existing organisms, plants, bacteria, fungi, animals, etc, are descendants of earlier, different, organisms. This book gives an introduction to how we know this to be the case. This ranges from what features are naturally selected in plants of the same species growing in different environments, to the “deep homologies” that tie together bacteria and kangaroos in the same tangled tree of life.

So how do we know? Sometimes you observe, which may imply that you sit in a hideout from sunrise to sundown for weeks and watch a flock of birds nesting to check if any of them nip out of the nest for a bit of nookie with the neighbour and then work the statistics on the results of those liaisons, to see if reality matches your theory of mate selection.

Or you do experiments, formulate a hypothesis of how a certain feature benefits the organism and then try to manipulate that feature for a group of individuals to see what happens. Superglue turns out to be useful in many of these experiments. (My unhappy experiences with superglue make me even more impressed with scientists who can use it properly.)

Other work involves searching through gene databases and using various mathematical means to determine at some level of probability how genes have been duplicated, modified, deleted (and how we can tell that that is what has happened) over time to result in organisms greatly different from their ancestors.

The book lays this out in an easily accessible manner, not without humour—merely reading the first chapter using the case of HIV to explain evolutionary thinking and put it in context managed to clarify a number of things to me. The exercises and suggestions for further reading in each chapter show ways in which to go beyond the material that has been presented in the chapter proper. One reason it took me so long to read the book was that I tried to work through at least some of the exercises. Often I felt handicapped by my high school biology crash course not having gone into detail on exactly how DNA is copied during mitosis, why crossover takes place and how transcription proceeds in detail. Surely I'm not so old it wouldn't have been known at the time?

An important thing which struck me was the way in which the scientific method was presented, many of the exercises were concerned with the proper way of phrasing a research hypothesis, how to design an experiment to test that hypothesis, and how to analyse the results of the experiment. This is an undergraduate text book. When I was an engineering undergrad the idea of hypothesis generation and testing was quite alien, rather the sentiment tended to be: “if it works, you're home”. When I went into graduate studies and teaching I tried to amend this as best I could, given my own barely adequate studies in the subject. I remember one time giving an exam question: “Explain how to design a formal experiment to test X.” and a (fourth-year!) student looking confused and asking “How can an experiment be formal, experimenting means just trying random stuff, right?”.

I do not know to what extent things have improved since then.

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