Back in 2014, evolutionary biologist Andreas Wagner blew my mind. His book Arrival of the Fittest: Solving Evolution’s Greatest Puzzle gave fascinating answers to the question of where evolutionary innovations come from. I will say more about it below, but in short, there are many ways to solve a problem. But, as Life Finds a Way shows, not all solutions are equally good. To evolve from a suboptimal solution to a superior one usually involves several steps through intermediary solutions that are even worse, something that natural selection acts against. So how does evolution overcome such obstacles? And what does the answer have to do with human creativity? Can we apply these ideas further afield in education or economics? And is this book going to be as good as his last one? So many questions…
Wagner begins by introducing the central concept of this book: the adaptive landscape, a powerful metaphor originally formulated by geneticist Sewall Wright in 1932. A technical discussion and retrospective is given in The Adaptive Landscape in Evolutionary Biology, but I will outline the basics below. Evolutionary biologists should feel free to skip the next paragraph.
One way to visualise evolution in action is as a topographic drawing of a mountainous landscape with peaks and valleys, as seen here. The horizontal axes show all possible values for two continuous traits (e.g. body size and wing colour of a butterfly), while the vertical axis shows biological fitness (the odds of contributing offspring to the next generation). Each individual in a population falls somewhere on this graph, depending on its trait values, but not all will contribute equally to the next generation. Those at or near a peak have the best chance of doing so. As this system evolves over multiple generations, you can imagine how this population is pushed towards the nearest peak, natural selection eliminating those individuals in the valleys or plains who are less fit. If this sounds abstract, it could be because their combination of trait values makes them more susceptible to predation.
“the adaptive landscape [is] a powerful metaphor […] to visualise evolution in action”
Those are the basics, but there are some caveats. One is that some peaks are higher than others – some trait combinations bestow more fitness on individuals. What if a population ends up on a suboptimal peak? From the image you can see that, unless you can do it in a single step, you cannot just descend one peak, move through a valley, and up the other peak. Natural selection will eliminate those indivduals who “try” (I use quotes here because it is worth remembering that this process is not goal-directed; evolution acts blindly through trial and error, and individuals have no knowledge of where they are on the landscape). How big of a problem that is depends on how many suboptimal peaks there are.
This is where caveat two comes in. See, this image oversimplifies things – an organism’s fitness depends on far more than two, often hundreds of traits. Our poor brains cannot visualise objects with that many dimensions. But you can describe them mathematically and Wagner explains how the number of peaks is astronomically large.
“an organism’s fitness depends on far more than two, often hundreds of traits. Our poor brains cannot visualise objects with that many dimensions.”
So, how does nature get off suboptimal peaks? Biological traits are ultimately coded for by DNA and as biologists know, life has other options to change DNA than single mutations such as genetic drift and recombination. The former is the chance disappearance of certain genes when all individuals carrying it die, something that is statistically much more likely in small populations. The latter is the wholesale exchange of chromosome regions during meiosis, the cell divisions that creates sperm and egg cells. Drift is dangerous and can push whole populations away from fitness peaks and into extinction (this is why conservation biologists are so concerned about habitat fragmentation). Wagner likens recombination to nothing less than teleportation; it allows offspring to take large leaps to a completely different part of an adaptive landscape.
If this all sounds a bit abstract, that is because I am summarising what Wagner lucidly explains in 100 pages and multiple diagrams. It is a daring feat of writing to describe such abstract processes for a general audience. Biologists might shrug: “genetic drift and recombination as sources of new genetic variation – that’s old hat”. Sure, but what is exciting is that Wagner and colleagues are investigating how these mechanisms work in the complex multidimensional sequence spaces he described in his last book. Say what? Last abstract concept, I promise.
“Wagner likens recombination to nothing less than teleportation; it allows offspring to take large leaps to a completely different part of an adaptive landscape.”
The Arrival of the Fittest introduced sequence spaces: the astronomically large number of all possible ways in which you can order a series of DNA bases to form a gene, or a series of amino acids to form a protein. Wagner poetically describes it as:
“a giant realm of possibility […] a library of texts that encodes not only all the countless innovative proteins that evolution has discovered in its history, but also all the proteins that it could discover in the future. It is the space where nature goes to find new parts for its biochemical machines” (p. 40).
Most combinations will be nonsensical, but many will not. Interestingly, Wagner’s computational work suggests that the number of viable genes or proteins encoded by these possibilities is vast. There are many possible solutions to a problem. So many, in fact, that they form networks. Wagner called it a hidden architecture that accelerates life’s ability to innovate. It was an idea that blew my mind back then, and I certainly did not tire reading of it here again, nor of reading how drift and recombination play out in these spaces.
“Wagner poetically describes sequence spaces as the “space where nature goes to find new parts for its biochemical machines””
Midway the book, Wagner completely changes gear. Having covered adaptive landscapes in biology, he asks if this metaphor can have wider use. It can in chemistry, where there are many possible solutions to the problem of arranging atoms or molecules into larger structures. And in computing, such as delivery companies finding the optimal route for their fleet of vehicles. But Wagner even sees parallels in how artists, writers, or composers work, comparing what they do to a form of creative problem-solving in a mental landscape. Here too, finding better solutions sometimes requires big leaps, which can be brought about by play, daydreaming, or other means. Finally, he asks how we can apply these lessons to education, business, and politics to foster more creativity. The second half of the book might not be to everyone’s liking, but I think it is important to take it in the right spirit. Not a grandiose theory, but excited lateral thinking.
As with his previous book, I found Life Finds a Way insanely fascinating. Wagner’s descriptions, in turn poetic or amusing, suggest an author at ease writing about his subject. He has a knack for making abstract, mind-bending concepts comprehensible, though that does not mean the book is not challenging (I reread certain passages multiple times while writing this review to make sure I was describing things right). But when you are reading it, Life Finds a Way feels like an intellectual ride that has sparks flying off it in all directions.
Disclosure: The publisher provided a review copy of this book. The opinion expressed here is my own, however.
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